Citation
U.S. Army Medical Department journal

Material Information

Title:
U.S. Army Medical Department journal
Alternate title:
United States Army Medical Department journal
Alternate Title:
AMEDD journal
Running title:
Army Medical Department journal
Abbreviated Title:
U.S. Army Med. Dep. j.
Creator:
United States -- Army Medical Department (1968- )
Place of Publication:
Fort Sam Houston, TX
Publisher:
U.S. Army Medical Department
Publication Date:
Frequency:
Quarterly[<Oct.-Dec. 2001->]
Bimonthly[ FORMER Sept.-Oct. 1994-]
quarterly
regular
Language:
English
Physical Description:
volumes : illustrations ; 28 cm

Subjects

Subjects / Keywords:
Medicine, Military -- Periodicals -- United States ( lcsh )
Military Medicine ( mesh )
Medicine ( mesh )
Medicine, Military ( fast )
United States ( mesh )
United States ( fast )
United States
Genre:
Electronic journals.
Periodicals.
Periodicals. ( fast )
Fulltext.
Government Publications, Federal.
Internet Resources.
serial ( sobekcm )
federal government publication ( marcgt )
periodical ( marcgt )
Electronic journals ( lcsh )
Periodicals ( mesh )
Periodicals ( fast )
Fulltext
Government Publications, Federal
Periodicals
Internet Resources

Notes

Dates or Sequential Designation:
Sept.-Oct. 1994-
General Note:
Title from cover.

Record Information

Source Institution:
University of Florida
Holding Location:
University of Florida
Rights Management:
This item is a work of the U.S. federal government and not subject to copyright pursuant to 17 U.S.C. §105.
Resource Identifier:
32785416 ( OCLC )
98642403 ( LCCN )
1524-0436 ( ISSN )
ocm32785416
Classification:
RC970 .U53 ( lcc )
616.9/8023/05 ( ddc )
W1 JO96 ( nlm )

Related Items

Preceded by:
Journal of the US Army Medical Department.

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Digital Military Collection

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October – December 2013 Perspectives 1 MG Steve Jones; COL Mustapha Debboun; Richard Burton A System for Health: Essential Element of National Security 4 LTG Patricia D. Horoho Strategies for Optimizing Military Physical Readiness and 5 Preventing Musculoskeletal Injuries in the 21st Century Bradley C. Nindl, PhD; Thomas J Williams, PhD; Patricia A. Deuster, PhD; et al Physical Fitness: A Pathway to Health and Resilience 24 Patricia A. Deuster, PhD; Marni N. Silverman, PhD Extreme Conditioning Prog rams and Injury Risk 36 in a US Army Brigade Combat Team Tyson Grier, MS; Michelle Ca nham-Chervak, PhD; et al Measuring Physical Activity During US Army Basic Combat Training: 48 A Comparison of 3 Methods Jan E. Redmond, PhD; Bruce S. Cohen, PhD; Kathleen Simpson, MS; et al Quantification of Physical Activity Performed During 55 US Army Basic Combat Training Kathleen Simpson, MS; Jan E. Redmond, PhD; Bruce S. Cohen, PhD; et al Nutrition as a Component of the Perf ormance Triad: How Healthy Eating 66 Behaviors Contribute to Soldier Performance and Military Readiness Dianna L. Purvis, PhD; Cynthia V. Lentin o, MS; Theresa K. Jackson, PhD; et al The Importance of Leadership in Soldiers' Nutritional Behaviors: 79 Results from the Soldier Fueling Initiative Program Evaluation Theresa K. Jackson, PhD; COL Sonya J. Cable; Wana K. Jin, MPH; et al Assessment of Dietary Intake Using the Healthy Eating Index 91 During Military Training Laura J. Lutz, MS; Erin Gaffney-Stomberg PhD; Jenna L. Scisco, PhD; et al Sleep as a Component of the Performance Triad: 98 The Importance of Sleep in a Military Population Cynthia V. Lentino, MS; Dianna L. Purvis, PhD; et al The Challenge of Sleep Management In Military Operations 109 Nancy J. Wesensten, PhD; Thomas J. Balkin, PhD The foundation of a system for health: army medicine’s Performance Triad

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October December 2013 The Army Medical Department Center & School PB 8-13-10/11/12 By Order of the Secretary of the Army: Official: 1325501 RAYMOND T. ODIERNO General, United States Army Chief of Staff DISTRIBUTION: Special Administrative Assistant to the Secretary of the Army JOYCE E. MORROW Online issues of the AMEDD Journal are available at http://www.cs.amedd.army.mil/amedd_journal.aspx A Professional Publication of the AMEDD Community The Army Medical Department Journal [ISSN 1524-0436] is published quarterly for The Surgeon General by the US Army Medical Dept Center & School, Journal Office, AHS CDD Bldg 4011, 2377 Greeley RD STE T, Fort Sam Houston, TX 78234-7584. Articles published in The Army Medical Department Journal are listed and indexed in MEDLINE, the National Library of Medicines premier bibliographic database of life sciences and biomedical information. As such, the Journal s articles are readily accessible to researchers and scholars throughout the global scientific and academic communities. CORRESPONDENCE: Manuscripts, photographs, official unit requests to receive copies, and unit address changes or deletions should be sent to the Journal at the above address., or amedd.journal@amedd.army.mil. Telephone: (210) 221-6301, DSN 471-6301 DISCLAIMER: The AMEDD Journal presents clinical and nonclinical professional information to expand kn owledge of domestic & international military medical issues and technolo gical advances; promote collaborative partnerships among Services, components, Corps, and specialties; convey clinical and health service support information; and provide a peer-reviewed, high quality, print medium to encourage dialog ue concerning healthcare initiatives. Appearance or use of a commercial product name in an article published in the AMEDD Journal does not imply endorsement by the US Government. Views expressed are those of the author(s) and do not necessarily reflect official policies or positions of the De partment of the Army, Department of the Navy, Department of the Air Force, Department of Defense, nor any other agency of the US Government. The content does not change or supersede information in other US Army Publications. The AMEDD Journal reserves the right to edit all material submitted for publication (see inside back cover). CONTENT: Content of this publication is not copyright protected. Reprinted material must contain acknowledgement to the original author(s) and the AMEDD Journal OFFICIAL DISTRIBUTION: This publication is targeted to US Army Medical Department units and organiza tions, other US military medical organizations, and members of the worldwide professional medical community. LTG Patricia D. Horoho The Surgeon General Commander, US Army Medical Command MG Steve Jones Commanding General US Army Medical Department Center & School

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October – December 2013 1EDITOR’S PERSPECTIVE In her introduction to the contents of this issue, The Surgeon General outlines the genesis and concept of the Performance Triad foundation to the System of Health initiative for Army Medicine. Dr Bradley Nindl of the US Army Public Health Command organized and led the effort to collect articles for this issue which present a sample of the professional skill and knowledge resources of Army medicine which are dedicated to realizing this transition. Each pillar of the Performance Triad is represented by articles describing completed studies and ongoing research to allow implementation of policies and doctrine from a perspective of solid, science-based knowledge. Military service demands a strong, t body. Obviously, strength and tness cannot be achieved nor maintained without exercise. However, as Dr Nindl and his coauthors discuss in their article, both physical training and PerspectivesCOMMANDER’S INTRODUCTIONMG Steve JonesInstilling tness and resilience in our Soldiers, Families, and Army Civilians is as important today as it was during the long winter at Valley Forge. These qualities are critical as the Army continues to ght our nation’s longest war with an all-volunteer force. The Ready and Resilient Campaign seeks to institute a cultural change in the Army by directly linking personal resilience to readiness, and emphasizing the responsibility of each individual to build and maintain resilience. Taking a deliberate approach to strengthening physical, psychological, and emotional resilience will increase unit readiness and the ability of Soldiers, Families and Civilians to deal with the signi cant challenges of the Army Profession. The Army Medical Department’s Performance Triad supports the Ready and Resilient Campaign and is a key component of our transition from a healthcare system to a System for Health. Patients spend an average of 100 minutes each year in our healthcare system. Their decisions during the other 525,500 minutes of the year, the Lifespace, have a great impact on their health and their lives. Sound decisions concerning the basics of Activity, Nutrition, and Sleep are key to optimizing health, performance and resilience. The Performance Triad will lead to sound decisions, more healthy behaviors, and more optimal performance. We know that individual resilience can be built, maintained, and strengthened with an appropriate training regimen. By taking a systematic approach we can better include activities into our schedule, follow a healthy diet that supports our training, and ensure we get the rest we need. A thoughtful plan will make our training more effective, help prevent injuries and overtraining. Start by setting challenging but realistic goals. Include both short and long term goals that are speci c and measurable. Pick a physical activity that you enjoy and make it a regular part of your daily schedule. There’s no single best way to train, the best activity for you is one you will consistently stick with. Remember that it is just as important to train your mind and include mind-body activities as well. Meditation not only reduces stress but can also increase your ability to concentrate. Yoga increases exibility while reducing stress. Other mental training activities can improve your cognitive function. Diet has a major in uence on overall physical and psychological tness. Quality nutrition means eating the right foods in the right quantities to improve performance and maintain a healthy weight. Plan your meals in advance and follow your plan. Sleep, the nal element of the Performance Triad, is as important as the other two. Training overloads the body and a recovery period allows the adaptation which increases physical and psychological tness. Proper recovery includes cooling down, refueling, rehydrating, and sleep. And once again, make a point to include adequate time in your schedule. Soldier athletes following a more advanced training program can achieve even greater goals. Their training plan should incorporate a strategy to improve endurance, speed, strength, power, exibility, and the technical/ mental skills required in their job. They should speci cally tailor their training to accomplish their goals, and incorporate advanced techniques including training cycles and periodization. Rest may include active recovery activities such as walking, light biking, or swimming. With more intense and higher volume training, it’s even more important to follow a careful plan to avoid overtraining and overuse injuries. Finally, keep a training log—it helps you stay motivated, track your progress, and accomplish your goals.

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2 http://www.cs.amedd.army.mil/amedd_journal.aspxsports are essential, but are also the main cause of musculoskeletal injuries among military service members. Such injuries often render the service member medically not ready to deploy, or cause evacuation from theaters of operation. Their article presents a scholarly, wellresearched, carefully developed plan for achieving the necessary levels of tness and strength among Soldiers while signi cantly reducing the number of musculoskeletal injuries incurred during training and individual tness activities. This article should be the starting point for anyone charged with the development and implementation of physical training plans, programs, and doctrine for military service members. In their article, Dr Patricia Deuster and Dr Marni Silverman look at another bene t of physical tness beyond its necessity in the strength and endurance required to perform physically-demanding tasks. They explore resilience as an indispensable characteristic for military service, sometimes being the difference between life and death. Using their extensive research, they carefully develop the position that physical tness is essential for a person to grow and maintain the resilience necessary to deal with the stresses and uncertainties of constantly changing demands. Further, their article presents the demonstrated relationship of resilience and good health in general, adding yet another contribution of physical tness to the goals of the Performance Triad. The combat experiences of the past decade have emphasized the utmost importance of physical conditioning for the mission-speci c tasks faced in the environment of nonlinear warfare. Combat units throughout the Army are looking at ways to tailor physical training to speci cally address the demands presented by those tasks in order to improve immediate and long-term combat effectiveness. Tyson Grier and his team of coauthors looked at such new programs to determine if more intense and focused physical training had an effect on injury rates or physical tness beyond that experienced by units with standard Army tness training programs. They conducted detailed research in the literature, and collected and analyzed extensive amounts of data from battalions in training to discover any de nitive trends and/or relationships among focused training, regular training, tness levels, and injuries incurred by those involved in physical training. Their comprehensive analysis demonstrates various relationships depending on various physiological parameters of individuals involved, and provides a wealth of data on which planners can base their programs and policies for physical tness training and standards. Those involved in the transformation of raw recruits into combat Soldiers have many challenges, whether researching, designing, implementing, or conducting the training. This is particularly true for the physical tness requirements and programs in that they are charged with the training and physical development of people presenting a cross-section of physical, tness, capabilities, motivations, and dedication. They must do this while minimizing injury, but meeting the time limitations of the training schedule. Therefore, those who design the training regimen must have an understanding of the demands of the physical activity mandated by the training. To do that, those demands must be measured and quanti ed. In their study, Dr Jan Redmond and her team evaluated 3 measurement instruments used with Soldiers in the basic combat training environment to determine the agreement among them. Each instrument had its respective use limitations, overhead requirements, and other considerations which must be factored into any decisions concerning use in the training environment. Their article clearly describes the carefully designed and conducted study, the data analysis, and the results, conclusions, and recommendations which should be of great assistance for future training planners and evaluators. Accurate measurement of physical activity during training is valuable for many purposes, including to verify the level of standardization at different training sites. Kathleen Simpson and her team used the information concerning measurement instruments discussed in the above paragraph to design and conduct a study measuring the amount of physical activity involved in basic combat training at 2 different training locations. Their excellent article clearly describes the careful, extensive data collection and the detailed statistical analyses of the various data groups. The conclusions based on their solid research demonstrate that the physical activity in the training conducted at the 2 study sites closely match each other, indicating a good level of standardization in implementation of the prescribed training regimen. The prosperity of this nation, and to a lesser degree a large part of the world, since World War II has changed the perspective of nutrition from one of insuf ciency to that of abundance. However, that seemingly positive trend is not without its negative aspects. The prosperity has also given us the ability to exhaustively and seemingly endlessly evaluate the nutritive properties of the many substances classi ed as food, and publicize those ndings to the population. Even with the availability of that information, most food choices are not made from a nutritive aspect, but rather from convenience, advertising hype, habit, and other lifestyle factors. This trend has long been re ected in an inexorable increase in obesity and other unhealthy, nutrition-related manifestations such as cardio and digestive conditions. Since the PERSPECTIVES

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October – December 2013 3THE ARMY MEDICAL DEPARTMENT JOURNAL military is a snapshot, albeit a generally healthier one, of the population as a whole, the nutrition choices and habits of military members are of concern to health professionals. Since nutrition and good health—and therefore military readiness—are absolutely interdependent, nutrition is another of the designated foundation pillars of good health in The Surgeon General’s Performance Triad. This issue of the AMEDD Journal contains 3 articles presenting studies by Army health professionals addressing different aspects of nutrition within the Army, and which undoubtedly re ect the situation throughout all the US military services. Dr Dianna Purvis and her coauthors lead off with their article describing Soldier dietary behaviors and the relationship of healthy eating behaviors and demographic, lifestyle, and psychosocial factors. They collected a considerable amount of data from a relatively large study population, and methodically reduced, parsed, and analyzed that data, and correlated the results with extensive literature research re ected in the references cited throughout the article. The results of their efforts should be of great interest for everyone involved in organizational nutrition planning and management, whether civilian or military. Since many, perhaps most, military recruits are not well versed in good dietary behaviors when they enter the service, one of the efforts made by the Army to improve nutritional behaviors is called the Soldier Fueling Initiative. It provides nutrition education and improved dining facility menus to Soldiers at basic combat training and advanced individual training locations in an effort to instill good dietary habits in trainees as an inherent part of their military lifestyle. However, no program or policy will be successfully implemented without positive, effective leadership, especially in the early phases of the military experience. Dr Theresa Jackson and her research team conducted a study to examine the in uence and effectiveness of troop leaders at 2 training locations with regard to eating behavior of their Soldiers. Their study examined the activities and attitudes of Soldiers within the framework of the Soldier Fueling Initiative, and how it was or was not supported by their leadership during training. Their ndings clearly indicate the relationship of Soldier nutrition practices and the leadership they experienced in this area. This article is important to those designing and planning training for troop leaders working in these environments, as well as for Soldiers training under the Soldier Fueling Initiative. Laura Lutz and her coauthors examined the actual (selfreported) eating behaviors of Soldiers in basic combat training to quantify any changes in dietary quality between their start and completion of that training cycle. Their investigation focused on the types and quantities of food consumed during training, and demographic data and tobacco use were factored into the data analysis as well. The study was carefully designed with a solid background of research, and the data collection was detailed. The results of their analysis, clearly presented in the article, indicate that the efforts of initiatives to improve the dietary habits of Soldiers from the beginning of their Army experience are showing measureable success. The fact that adequate sleep, the third pillar of the Performance Triad, is essential to good health has been widely recognized for many years, not only by scientists and medical professionals, but by most people, usually based on personal experience. Unfortunately, similar to both healthy activity and good nutrition, adequate sleep loses against the time demands of our multitasked lifestyle of unlimited entertainment, universal contact, and 24 hour availability. Lack of sleep begins early as teenagers cannot prioritize their activities, and continues into the working life with too many commitments (and/or jobs) and the demands of parenthood. Cynthia Lentino and her coauthors looked at sleep habits in the military population to examine the relationship of sleep quality to physical performance, nutritional habits, measures of obesity, and lifestyle behaviors, among other things. Their excellent, thoroughly referenced article clearly presents the details of their data collection, its analysis, and the conclusions developed from that analysis. The results of their study reinforce the ndings of other research in this area, and unquestionably demonstrate that the 3 elements of the Performance Triad are highly interdependent in both positive and negative relationships. Dr Nancy Wesensten and Dr Thomas Balkin conducted an extensive, thorough literature review for research which could be used to address the adverse effect of insuf cient sleep on military readiness. Their primary goal was to identify data and research ndings for use in developing an optimally effective sleep health education program which could be taught to military personnel and their families, since good sleep habits are just as important in garrison as in a deployed environment. Just as importantly, such a program must be understood and supported by military leadership at all levels, so that the sleep of combat troops would be a major consideration in maintaining the combat effectiveness of the ghting force. Their article is a logically organized, easily understood presentation of their research ndings, which further undergird The Surgeon General’s concept of the Performance Triad as the foundation in the development and maintenance of a ghting force at the highest level of readiness and combat capability.

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4 http://www.cs.amedd.army.mil/amedd_journal.aspxArmy Medicine is transitioning from a healthcare system to a System for Health. This means shifting the focus to prevention of disease, injury, and disability. More importantly, it means advocating a culture shift to Soldiers and bene ciaries by encouraging them to develop a mindset that drives them to optimize their own health. The Performance Triad is the enabler of our transition to a System for Health, as well as the framework for helping to change the mindsets of those for whom we are professionally and personally responsible. If we can improve the health literacy of the Army community, our Army family will make better decisions about Activity, Nutrition, and Sleep, which form the 3 pillars of the Triad. The depth of science and professional knowledge represented by the articles in this issue is essential to the evidence-based foundation we are using to encourage and assist Army bene ciaries to choose good health. The successful transition to a System for Health is vitally important. Not only is it important to the survival of Army medicine as an affordable, viable entity, but also—I am convinced—to the security of our nation. We spend more than any other nation on healthcare, yet we are becoming less and less healthy. Obesity is increasing and tobacco use and substance abuse are on the rise among both children and adults, chronic diseases lead our nation in causes of death, and the cost of our healthcare system is simply not sustainable. The declining health status of our Soldiers, their Families and our nation as a whole are common concerns shared across and beyond Army Medicine. Additionally, we face the challenges of the drawdown, sequestration, budget cuts, and furloughs. These challenges ll our inboxes, consume our days, and negatively affect morale and our sense of value to the organization. Together, health issues and nancial pressures present a signi cant threat to our security and to our Army’s most basic mission: to ght and win our nation’s wars. However, we cannot—I repeat, cannot—allow the challenges we face to drive us to despair. We are part of an organization that has faced equal and greater challenges over the past 238 years. We have seized the opportunities that those challenges presented, and we emerged stronger and more resilient. Today is no different. Everyone in Army Medicine has an active role in changing not only the way Army Medicine is organized and operates, but how we interact with our bene ciaries, and how we in uence health. Whether in leadership positions at the headquarters, the regional medical commands, the major subordinate commands, or closer to the point of health care delivery in our medical treatment facilities or line units, each of us has a critical part in shaping the future of Army Medicine. What we do and how we do it will be our legacy. I believe that legacy will be the transformation of health care, not only across the Army, but across the nation.ARMY STRONG!A System for Health: Essential Element of National SecurityLTG Patricia D. Horoho The Surgeon General of the United States Army

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October – December 2013 5The United States military is being transformed as deployments in Iraq and Afghanistan come to an end and the Department of Defense (DoD) cuts budgets and personnel. The Chairman of the Joint Chiefs of Staff, General Martin Dempsey, has stated that strategies and capabilities are key factors in cutting $450 billion from DoD’s budget over the next 10 years.1 Further, on January 26, 2012, the strategic guidance from the Pentagon, presented from then Secretary of Defense, Leon Panetta and GEN Martin Dempsey, included the recommendation for Army personnel strength reductions from 570,000 to 490,000 over the next 5 years.2 Secondorder effects from this decline in troop strength superimposed upon the persistent and signi cant percentage of Soldiers considered medically not ready (MNR) to deploy could potentially have signi cant consequences if the manned force structure is not able to meet military operational requirements for protecting our nation’s vital and important interests. As a consequence of these austere changes/decrements in resources, protection of force health and performance optimization of Soldiers and other service members will be more important than ever. Musculoskeletal injuries (MSIs) are the cause of a large percentage of service members deemed to be MNR and placed on limited duty.3 These MSIs are a major threat to the health and tness of our Soldiers and other service members placing our nation’s war ghting capability at risk.3,4 The costs imposed by this threat are both nancial (such as the economic burden from medical, healthcare and disability costs) and human. The injuries exacerbate human manpower losses as Soldiers are medically unable to perform their duties for deployment.3,5-8 The majority of the injuries encountered in military populations are training-related, overuse injuries.8,9 Strategies for Optimizing Military Physical Readiness and Preventing Musculoskeletal Injuries in the 21st CenturyBradley C. Nindl, PhD Thomas J. Williams, PhD Patricia A. Deuster, PhD COL Nikki L. Butler, SP, USA Bruce H. Jones, MD, MPHABSTRACTWith downsizing of the military services and signi cant budget cuts, it will be more important than ever to optimize the health and performance of individual service members. Musculoskeletal injuries (MSIs) represent a major threat to the health and tness of Soldiers and other service members that degrade our nation’s ability to project military power. This affects both nancial (such as the economic burden from medical, healthcare, and disability costs) and human manpower resources (Soldiers medically unable to optimally perform their duties and to deploy). For example, in 2012, MSIs represented the leading cause of medical care visits across the military services resulting in almost 2,200,000 medical encounters. They also result in more disability discharges than any other health condition. Nonbattle injuries (NBIs) have caused more medical evacuations (34%) from recent theaters of operation than any other cause including combat injuries. Physical training and sports are the main cause of these NBIs. The majority (56%) of these injuries are the direct result of physical training. Higher levels of physical tness protect against such injuries; however, more physical training to improve tness also causes higher injury rates. Thus, military physical training programs must balance the need for tness with the risks of injuries. The Army has launched several initiatives that may potentially improve military physical readiness and reduce injuries. These include the US Army Training and Doctrine Command’s Baseline Soldier Physical Readiness Requirements and Gender Neutral Physical Performance Standards studies, as well as the reimplementation of the Master Fitness Trainer program and the Army Medical Command’s Soldier Medical Readiness and Performance Triad Campaigns. It is imperative for military leaders to understand that military physical readiness can be enhanced at the same time that MSIs are prevented. A strategic paradigm shift in the military’s approach to physical readiness policies is needed to avoid further degradation of war ghting capability in an era of austerity. We believe this can be best accomplished through leveraging scienti c, evidence-based best practices by Army senior leadership which supports, prioritizes, and implements innovative, synchronized, and integrated human performance optimization/injury prevention policy changes.

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6 http://www.cs.amedd.army.mil/amedd_journal.aspxControlling MSIs among military personnel and continuing to reduce injury rates depend on institutionalizing existing best practices for injury prevention and physical training, plus prioritizing relevant research in the future. Accomplishing this requires establishing stronger linkages across commands, operational personnel, researchers, medical providers, public health, and safety of cials.10 With the emphasis of the 2010 Quadrennial Defense Review Report11 on the health and tness of the total force, and the 2007 Joint Force Health Protection Concept of Operations12 encompassing a healthy, enhanced, and protected force, now is the time to critically review military physical readiness practices—both human performance optimization (HPO) and injury prevention (IP)—with the Army and other services. The promotion and sustainment of military physical readiness requires an energized sense of urgency from senior military leadership responsible for the implementation of policies and strategies that promote and sustain military physical readiness. Such actions will contribute to force readiness and align the DoD and the Military Healthcare System with a fundamental premise that the Soldier is the center of our War ghter capability. The human service member is the prime resource and key enabler of all War ghting systems.12(ES-2)This article proposes that the military approach to military physical readiness requires a new strategic paradigm that recognizes that physical training, physical tness, and injury prevention are interrelated and can be optimized simultaneously. For the purposes of this article, the term military physical readiness is an umbrella term referring to both HPO and IP efforts. This article describes (1) the scope and impact of the MSI problem on readiness; (2) the implications for the associations among physical training, tness, and injuries for readiness; (3) an assessment of current Army Physical Readiness Training Doctrine; (4) an overview of injury risk mitigation strategies and efforts; (5) current HPO/IP efforts in the Army targeting military physical readiness; (6) recommendations as to the implementation of organizational, communication, scienti c, and operational changes through strategic planning; and (7) alternative scenarios for HPO/IP. SCOPE AND IMPACT OF THE MUSCULOSKELETAL INJURY PROBLEM ON MILITARY READINESS Former Army Surgeon General LTG Eric Schoomaker identi ed that the Army’s deployment readiness was at just 85% for active duty and only 70% for Guard and Reserve forces.13 BG Brian Lein, former command surgeon at US Forces Command, warned that it would be dif cult for the Army to maintain unit manning levels in the future if nondeployable status remained at the current level: If we don’t get our arms around the nondeployable population, and the biggest population is the MNR population, we’re going to have a signi cant problem manning our units to get them to go downrange…. The Soldier is the center of our formations, so if the Soldier is not ready to go, then the unit is not ready to go.13Across the military services, injuries represent the biggest medical threat to readiness.8,14,15 In 2012, MSIs resulted in over 2.2 million medical encounters annually across the military.16 These injuries affect more than 600,000 individual service members each year.17 In comparison, the second leading cause of medical encounters, mental disorders, results in approximately 2.1 million encounters annually, affecting approximately 250,000 service members.17 The biggest share of the injury problem (over 40%) belongs to the Army.8 Across the services, overuse injuries can be estimated to cause more than 55% of all injury encounters by active duty service members.8Published research demonstrates that the physical training-related injury risk is the highest for basic combat training in the Army and Marine Corps.9 The incidence during US Army basic combat training ranges from 19% to 40% for men and 40% to 67% for women.18,19(pp6-7) For advanced individual training with training cycles from 9 to 16 weeks duration, the literature reports trainingrelated injury incidences ranging from 24% to 40% for men and 30% to 60% for women.19(pp6-7) For operational units including infantry, armor, and military police, injury incidence has been reported to range from 5% to 13% per month (equivalent to annualized rates of 60 to 150 injuries per 100 soldiers per month) depending on the type of unit.19(pp6-7) Soldiers report that physical training and sports activities caused the largest proportion of these injuries. Army research shows that physical training and sports cause 53% to 63% for ordnance Soldiers in advanced individual training, 40% for armor Soldiers, 38% for garrison Soldiers, 42% for senior of cers at the US Army War College, 58% for light infantry Soldiers, 53% for military police, and 34% for wheeled vehicle mechanics.19(pp6-7)Downstream effects from the MSI epidemic in the military profoundly impact hospitalizations and outpatient visits, lost/limited duty time, and disabilities. Acute MSIs and chronic musculoskeletal conditions arising from injuries are consistently the leading cause of hospitalizations and outpatient visits in the military. Of the over 20 million ambulatory visits to military medical treatment facilities reported in 2012, over 4 million (20%) were acute injuries and other injury-related musculoskeletal/connective conditions.16 STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

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October – December 2013 7THE ARMY MEDICAL DEPARTMENT JOURNAL It has been estimated that across all the services more than 25 million limited duty days annually result from injuries, an equivalent of 68,000 service members a year on limited duty.3,18(p11) If limited duty is prescribed in proportion to the percent of injuries reported by the services, the Army owns the largest share (slightly over 40%) of those limited duty days or about 10 million limited duty days (about 27,000 man-years on limited duty each year). The healthcare costs alone ascribed to those 68,000 DoD service members are over $700 million a year. The cost of salaries of Soldiers who cannot deploy is just over $3 billion annually. The costs to the Army for medical care and salaries of Soldiers on limited duty can be conservatively estimated to be about $1.5 billion per year. The time lost to commanders and organizations is incalculable. The long-term effects in terms of disability discharges are just as sobering. Disabilities from MSIs have increased over time disproportionately to medical treatment rates.6,20 From 1982 to 2002, the disability discharge rates speci cally for MSIs increased from less than 15 for both men and women to 140 per 10,000 for females (a 9-fold increase) and to 81 per 10,000 for males (a 5-fold increase).18(pp6-7) These disproportionate disability discharge rates between men and women imply that MSI risk mitigation strategies are essential for optimal performance among military women. Such injury risk mitigation strategies will be particularly critical as more women enter combat-centric occupations resulting from the elimination of the 1994 direct combat de nition and assignment rule on January 9, 2013. In addition to the manpower losses incurred by the Army and other services due to disabilities, the Department of Veterans Affairs (VA) costs for compensation have historically been high.6 The VA reported in 2001 that the annual compensation paid to disabled service members totaled over $21 billion, with over $5.5 billion to service members with musculoskeletal disabilities.18(p10) Although it is understood that soldiering is a physically demanding occupation,21-26 the Army as an enterprise organization should not accept these high injury incidence rates and medical costs associated with them, especially since the risk factors for these injuries are largely understood and many methods for reducing injuries are available. IMPLICATIONS FOR THE ASSOCIATION OF PHYSICAL TRAINING, FITNESS, AND INJURIES FOR READINESS The rigor of physical training, particularly preparing for physically demanding military occupations, places great demands on the musculoskeletal system. The many bene cial outcomes of effective physical training are well documented.18,27-30(pp6-7) Conversely, adverse outcomes also occur from physical training, the most common of which are MSIs. For example, many of the injury-related musculoskeletal conditions are due to the cumulative effects of repetitive microtrauma forces: overreaching/ training, overuse, overexertion, and repetitive movements experienced during both occupational duties and physical training.7 Overuse injuries are an indicator that a unit is overtraining. As a consequence, one can expect that units with increasing overuse injury rates can also expect decreases in physical tness. Thus, injury rates can be reduced and physical tness enhanced by judicious modi cations of training that can be calculated to optimize tness and minimize injury risks. Of the almost 750,000 MSIs reported in 2006 in military medical surveillance data on active duty, nondeployed service members, 82% were classi ed as overuse.18(p16) As stated previously, typically 30% to 50% of these injuries are speci cally attributable to physical training and sports activities.18(pp6-7)The physical training MSI epidemic in the military training/garrison environment, arguably under-recognized by military leaders and policy makers, has been well documented in the scienti c literature. Senior leaders should understand that the major cause of the more than 30,000 medical evacuations between 2001–2006 from Operations Iraqi Freedom and Enduring Freedom were not battle injuries but rather nonbattle injuries (NBIs) from participation in sports and physical training activities. Hauret et al reported that medical evacuations for NBIs (36%) were twofold greater than for battle related injuries (18%).4 The major causes for these nonbattle related medical evacuations were from physical training and sports (about 20% of the total). Further, Cohen et al reported that medical evacuations from Iraqi Freedom and Enduring Freedom were greater for musculoskeletal related injures (24%) than combat injuries (14%).31 Hence, effective physical training injury mitigation strategies are needed to keep more people “in the ght” and to decrease the number needed to be sent “to the ght” to replace those injured. Numerous extrinsic and intrinsic risk factors for MSIs have been identi ed. Extrinsic risk factors include high running mileage, age of running shoes, and seasonal variations, such as higher overall rates in summer.18(p23) Intrinsic risk factors include female gender, low aerobic tness, low levels of physical activity prior to military entrance, cigarette smoking prior to military entrance, past ankle sprains, low muscular endurance, and older age.18(p18)The most important modi able risk factor for trainingrelated injuries is the physical training program itself.

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8 http://www.cs.amedd.army.mil/amedd_journal.aspxWithout physical training, these type of injuries do not occur. The scienti c literature documents that greater volumes of training, especially weight-bearing physical training such as running or marching, are associated with higher risks of injuries.19,32-34 Among the intrinsic risk factors for training-related injuries, low levels of physical tness, in particular low levels of aerobic tness or slow run times, have been consistently shown to be associated with higher risks of such injuries.18,19,35-37 Ironically, this means that the Army and other services must expose service members to the risk of injury resulting from physical training in order to develop mission essential physical tness and accrue the bene ts of higher levels of tness. Interestingly, it has been shown that there are thresholds of physical training above which injury risks increase but physical tness plateaus or decreases.19,34,38 Increased injury risks and decreased physical performance are 2 of the cardinal signs of overtraining. If the thresholds of training indicative of overtraining can be identi ed, scientists and commanders should be able to design programs that simultaneously minimize injury rates for units and enhance physical tness of Soldiers and other service members. With the exception of considering aerobic tness levels in assigning basic trainees into groups for ability group runs,39 no systemic Army-wide policy exists for using known intrinsic risk factors to stratify Soldiers based upon injury risk potential and tailor their physical readiness training accordingly. More research is needed to identify modi able risk factors for injury and the effectiveness of prevention strategies employing that knowledge. ASSESSMENT OF CURRENT ARMY PHYSICAL READINESS TRAINING DOCTRINE The Army continually tries to improve its physical training curriculum by inserting new evidence-based physical training information into policy and doctrine in an effort to balance HPO/IP. In October 2012, the Army Training and Doctrine Command’s (TRADOC) Army Physical Fitness School published an authoritative doctrine in the form of Field Manual 7-22, Army Physical Readiness Training .39 Beginning in the early 2000s, the US Army Physical Fitness School initiated efforts to redesign Army physical training. In consultation with subject matter experts from the Army Institute of Public Health at the US Army Public Health Command (USAPHC) and the US Army Research Institute of Environmental Medicine, a program was designed to improve War ghter’s physical capability for military operations and reduce musculoskeletal injuries. This was achieved by examining the standard list of warrior tasks and determining: (1) physical requirements of military tasks; (2) tness components involved; and (3) training activities most likely to improve performance of military tasks. Injury prevention features included reduced running mileage, exercise variety (cross-training), and gradual, progressive training.40 This program was subsequently validated in eld and laboratory studies41-43 which demonstrated that the overall adjusted injury risk was 1.5 to 1.8 times higher in groups of Soldiers performing traditional military physical training compared to groups participating in the new physical readiness training (PRT). Scores on the Army Physical Fitness Test (APFT) and physical performance metrics were similar or higher in groups using the PRT programs.40,44 The Army adopted the new PRT as of cial doctrine as a result of these studies. Despite the advantages and bene ts of the current evidence-based Army PRT, several areas of concern and limitations with the current doctrine must be acknowledged. First, the PRT program was only assessed over a relatively short time period (approximately 8 weeks). Kraemer et al have shown that the incorporation of resistance training provides superior gains in strength, power, muscle hypertrophy, and military task performance over a 6-month training period when compared to conventional military eld training.45 Recently, Grier et al have shown that more weekly resistance training imparts a protective effect for injuries in infantry Soldiers.46 Fortunately, TRADOC is examining ways to encourage and monitor other test components of physical tness rather than relying solely on aerobic tness and muscle endurance. Although there are a number of short-term studies available in the literature, a paucity of research has considered physical performance adaptations over the “life-cycle spectrum” of the War ghter, particularly among operational units. Important considerations for physical training optimization among our Soldiers, in terms of incorporating resistance training, must be acknowledged. For relatively untrained Soldiers, improvements in strength at the onset of training are primarily due to neural factors (eg, increased agonist activation, improved motor unit coordination, and synchronization). Therefore, previously untrained Soldiers/recruits should participate rst in relatively low-load, low-volume resistance exercise protocols to induce substantial improvements in strength and minimize the likelihood of injury due to relatively modest loads and volume. Following 2 to 3 months of training, the initial period of rapid neural adaptations has elapsed and most additional strength gains are due to muscular factors (ie, hypertrophy). After the STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

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October – December 2013 9THE ARMY MEDICAL DEPARTMENT JOURNAL initial few months of resistance training, heavier loads and greater volumes of lifting appear to be required for further performance enhancement.19 It would be dif cult to identify the optimal physical training programs without additional validation studies. Second, the majority of eld validations utilized the APFT as the performance outcome measure. Debate is ongoing among military physical training subject matter experts with regard to the appropriateness of the APFT to assess the capability of a War ghter to perform occupational and/or combat duties.47 However, no other established and accepted metrics of “combat or functional performance” is yet available. In 2012, the Army evaluated 2 different tests for consideration as doctrine: (1) an APRT consisting of a 60-yard shuttle run, 1-minute rower, standing long jump, 1-minute push-up, and 2-mile run to replace the APFT; and (2) an Army Combat Readiness Test. Currently, a Baseline Soldier Physical Readiness Requirements study is being conducted by the TRADOC Initial Military Training Center with support from leading subject matter experts from the USAPHC, the US Army Research Institute of Environmental Medicine, the US Military Academy, the C onsortium for Health and Military Performance (CHAMP) at the Uniformed Services University of the Health Sciences (USUHS), and the TRADOC Physical Readiness Division. The intent of this study is to systematically quantify, evaluate, and summarize the physical demands of warrior tasks and battle drills to determine, validate, and implement appropriate physical testing that would be used to assess a Soldier’s ability to successfully execute warrior tasks and battle drills. This study is projected to result in implementation of a new physical readiness testing paradigm in May 2015. It is clear that continued efforts are required to identify and establish the most valid metrics for military physical performance assessment. These TRADOC efforts indicate a paradigm change for physical training and testing. INJURY RISK MITIGATION STRATEGIES AND EFFORTS In a 2003 policy memorandum, Secretary of Defense Donald Rumsfeld challenged the DoD to reduce the incidence of preventable accidents. The memo stated:World-class organizations do not tolerate preventable accidents. Our accident rates have increased recently, and we need to turn this situation around. I challenge all of you to reduce the number of mishaps and accident rates by at least 50% in the next two years. These goals are achievable and will directly increase our operational readiness. We owe no less to the men and women who defend our nation.48In response to that memorandum, the Defense Safety Oversight Council (DSOC), chaired by the Under Secretary of Defense for Personnel and Readiness, was formed to provide governance on DoD-wide efforts to reduce preventable injuries. The Military Training Task Force (MTTF), comprised of civilian and military injury experts from Johns Hopkins Center for Injury Research and Policy and the Army Center for Health Promotion and Preventive Medicine (now the USAPHC), was chartered to support this accident and injury prevention directive with a focus on interventions that relate to all aspects of military training.49 The Joint services Physical Training Injury Prevention Working Group (JSPTIPWG) was created under the MTTF in September 2004 to evaluate military physical training injury prevention programs, policies, and research for recommendations to reduce physical training-related injuries.49 An expedited systematic review process was used by the working group to: (1) establish the evidence base for making recommendations to prevent physical training-related injuries; (2) prioritize the recommendations for prevention programs and policies; and (3) prioritize further research and evaluation efforts that could likely reduce physical training-related injuries.49Of the 40 promising injury prevention strategies systematically reviewed, only 6 intervention strategies to reduce physical training-related injuries had the requisite evidence-based scienti c support to recommend for implementation across the military. These interventions in order of priority were: (1) prevent overtraining (ie, excessive running mileage); (2) perform multiaxial, neuromuscular, proprioceptive, and agility training; (3) wear mouthguards during high-risk activities; (4) wear semirigid ankle braces for high risk activities; (5) consume nutrients to restore energy balance within one hour following high-intensity activity; and (6) wear syntheticblend socks to prevent blisters.49 It is important to note that not all of these evidence-based interventions have been implemented as doctrine. Of equal interest, 23 intervention strategies with some theoretical basis for ef cacy were identi ed as lacking suf cient evidence to recommend at that time.49 The JSPTIPWG recommended that upon determination by systematic reviews that scienti c information is scant and gaps exist in knowledge about prevention, more research is needed before the implementation of policies and programs.50 The efforts of the DSOC and the MTTF work group indicated that the DoD and the services are no longer willing to accept injuries as a given cost of conducting training and operations.

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10 http://www.cs.amedd.army.mil/amedd_journal.aspxCURRENT HPO/IP EFFORTS IN THE ARMY TARGETING MILITARY PHYSICAL READINESS The Army published Technical Bulletin MED 592, Prevention and Control of Musculoskeletal Injuries Associated with Physical Training19 in May 2010. It is an important comprehensive document that translates stateof-the-art guidance into principles that military and civilian healthcare providers and allied medical personnel can understand and implement. Such evidence-based preventive principles can protect Army personnel from musculoskeletal injuries associated with physical training. The document serves as an authoritative source on HPO/IP and helps military care providers and leaders: understand physiologic and pathophysiologic responses to exercise, know risk factors associated with training-related musculoskeletal injuries, understand interventions with varying levels of evidence for effectiveness in preventing trainingrelated injuries, recognize the presentation and acute treatment of Soldiers with training-related MSIs, evaluate and appropriately treat Soldiers with acute training-related MSIs, and advise commanders on planning, implementing, and evaluating any proposed comprehensive program designed to reduce physical training-related MSIs. A common trend among War ghters is extreme conditioning programs (ECPs) (for example, CrossFit (CrossFit Inc, Washington, DC), Insanity (Beachbody LLC, Santa Monica, CA), Gym Jones (Gym Jones LLC, Salt Lake City, UT), and others) characterized by high-volume, intense training workouts. These well-marketed and popularized conditioning programs continue to generate interest and support among military and civilian tness communities. Acceptance of ECPs is reinforced by anecdotal reports of marked gains in physical performance. However, physicians and other primary care and rehabilitation providers have identi ed a potential emerging problem of disproportionate MSI risk, particularly for novice participants. Muscle strains, torn ligaments, stress fractures, and mild to severe cases of potentially life-threatening exertional rhabdomyolysis have been anecdotally reported in increasing numbers as the popularity of ECPs has grown.51 Unfortunately, the shortand long-term physiological, functional, and readiness outcomes or safety of ECPs have not been carefully studied. Only one study to date has reported tness outcomes in the peer-reviewed literature using a CrossFit-based program. Smith et al reported increases in maximal aerobic tness and body composition after 10 weeks of training. However, limitations for this study were that a control group was not included in the study and injury data were not reported.52On September 13 and 14, 2010, a workshop on ECPs, composed of the CHAMP, other members of the DoD, and representatives of the American College of Sports Medicine, was convened at the USUHS in Bethesda, Maryland, to begin a critical dialog on this important issue.53 From this workshop, the consensus was that further research was needed to con rm or negate the purported increase in injury risk from participating in ECPs and clarify other modi able contributing factors.53Former US Army Surgeon General LTG Eric Schoomaker initiated an ongoing effort germane to HPO/ IP in the military. LTG Schoomaker identi ed Soldier Medical Readiness as his number one priority.54 The US Army Medical Command (MEDCOM) has partnered with the Headquarters, Department of the Army (HQDA); US Army Forces Command (FORSCOM); TRADOC; Installation Management Command; US Army Reserve Command; US Army Special Operations Command; Director, Army National Guard; US Army Human Resource Command; HQDA G-1; and HQDA G3/5/7 to execute a coordinated campaign to increase medical readiness in the Army. Through execution of this campaign, MEDCOM expects support to: (1) deploy healthy, resilient, and t War ghters; (2) increase the medical readiness of the Army; and (3) effectively manage the medically not ready (MNR) population to return the maximum number of War ghters possible to deployable status. These goals will be accomplished through 3 primary lines of effort: 1.0 MNR Soldier Identi cation 2.0 MNR Management Programs 3.0 Evidence-Based Health Promotion, HPO/IP Programs Line of Effort (LOE) 3.0 of the Soldier Medical Readiness Campaign Plan54 (SMR-CP) embodies the key task to coordinate, synchronize, and integrate health promotion, injury prevention, and human performance optimization programs across the Army with key objectives to improve physical tness and reduce injury rates. Figure 1 lists the SMR-CP LOE 3.0 strategic objectives, objective statements, quanti able measures, target goals, and initiatives. The main objectives of this LOE are to: (1) provide evidence-based health promotion services to enable healthy lifestyle choices and eliminate preventable health issues that contribute to MNR Soldiers; (2) implement, support, and evaluate promising injury prevention and performance optimization best practices/programs; STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

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October – December 2013 11THE ARMY MEDICAL DEPARTMENT JOURNAL (3) assess existing best practices and their evidence base and evaluate the feasibility of incorporating them into standardized best practices to improve management of injuries and optimize Soldier Medical Readiness; and (4) identify research programs within Army Medicine that contribute to HPO/IP, and communicate evidencebased lessons learned from these studies. The Army MEDCOM is championing the initiatives of the Performance Triad Campaign conceived by The Surgeon General, LTG Patricia Horoho, which focuses on sustaining and enhancing Soldier stamina by implementing educational programs, motivational strategies, and revised policies to optimize aspects of Soldier health—activity, nutrition, and sleep—among the force. Operational implementation of this strategic initiative with an institutional, proactive system for health (as opposed to a reactive healthcare system) should maintain, restore, and improve health by improving tness and mitigating MSIs.55 A speci c area of emphasis related to physical readiness involves providing greater educational awareness for Army Physical Readiness Training Strategic Objective: Synchronize Medical Readiness Related Research Objective Statement: communicate commanders’ and public health research needs; collaborate with Army partners on HPO/IP projects; and enhance communication of evidence-based lessons learned to commanders, policy makers, and the health promotion community; ultimately contributing to the reduction in MNR Soldiers. Measures: (1) number of scienti c publications on MSI; (2) number of scienti c presentations on MSI; (3) number of current agreements that leverage Army partners. Target: (1) >50% manuscripts on MSI in peer-reviewed journals per scal year; (2) 5 talks/presentations per scal year speci cally on MSI research; (3) one agreement with and Army partner to disseminate MSI research lessons learned not later than September 30, 2011. Initiatives: (1) complete research inventory; (2) complete list of suggested future HPO/IP research; (3) develop communication/coordination strategy Strategic Objective: Improve Integration of Musculoskeletal Injuries Rehabilitation Programs Objective Statement: synchronize, coordinate, and improve unit-based and MTF-based musculoskeletal injury rehabilitation programs to enable Soldier medical readiness. Measures: number of Soldier pro le days due to musculoskeletal injury in FORSCOM units evaluated. Target: 15% decrease in pro le days due to MSI in FORSCOM units evaluated. Initiatives: (1) unit-based medical management; (2) unit-based rehabilitation program; (3) musculoskeletal action plan; (4) aquatic rehabilitation pilot program; (5) aquatic warrior exercise program standardization. Strategic Objective: Improve Soldier Injury Prevention/Human Performance Objective Statement: coordinate and synchronize evidence-based HPO/IP policies and programs that support Army Force Generation in each of its phases in order to improve the medical readiness of the Army. Measures: (1) percentage that pass APFT in FORSCOM units evaluated; (2) percentage of Soldier injury rate in FORSCOM units evaluated; (3) recommendations for injury prevention provided to FORSCOM units evaluated. Target: (1) >85% pass rate on current APFT in FORSCOM units evaluated; (2) 15% decrease in injury rate in FORSCOM units evaluated; (3) recommendations for injury prevention targets provided to FORSCOM units evaluated (25th ID, 4th ID). Initiatives: (1) conduct inventory of ongoing Army HPO/IP programs and initiatives; (2) conduct review of evidence-based support for HPO/IP initiatives and infantry division best practices and gaps; (3) implement, support, review and evaluate promising Army HPO/IP initiatives; (4) Initial Entry Training Soldier Athlete initiative; (5) 101st Eagle Tactical Athlete Program Research study; (6) 4th ID Iron Horse Performance Optimization US Army Medical Command/FORSCOM; (7) US Army Special Operations Command (USASOC) Tactical Human Optimization Rapid Rehabilitation Reconditioning initiative; (8) USASOC Ranger Athlete Warrior Program; (9) 25th ID Advanced Tactical Athlete Conditioning initiative; (10) implement policy, guidance, education, and training and incorporate them into HPO/IP initiatives. Note: Detailed descriptions of HOP/IP initiatives are presented in Figure 3. Figure 1. Soldier Medical Readiness Campaign Plan (SMR-CP) LOE 3.0: Evidence-Based Health Promotion, Injury Prevention, and Human Performance Optimization Programs Balanced Scorecard.54

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12 http://www.cs.amedd.army.mil/amedd_journal.aspx STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY Figure 2. Performance Triad Activity Concept of Operations. The presentation of this Concept of Operations was part of a Perfor mance Triad decision brief to The US Army Surgeon General on October 16, 2012. LOE 1: Education – Inculcating a paradigm shift with the manner in which the Army views health should must start with the train ing base with appropriate programs of instruction. Evidence-based activity-centric research conducted by the US Army Research Insti tute of Environmental Medicine and others and published in peer-reviewed journals will serve as the cornerstone for establishin g valid and effective best practices. Growing subject matter expertise within the Army can also be facilitated by partnering with relevant nonpro t health organizations such as the American College of Sports Medicine and the National Strength and Conditioning Association. These organizations offer industry-accepted certi cations for health and tness practitioners. Information dissemination of evidence-based scienti c information from credible sources, such as the USAPHC and the Human Performance Resource Center, will be critical in providing the military with accurate and timely information. LOE 2: Programs – There are many existing and emerging programs both within and outside of the Army that can be leveraged to fo ster greater awareness for activity among Soldiers and their families, such as Army Wellness Centers and Comprehensive Soldier a nd Family Fitness. Training and embedding master tness trainers and master resiliency trainers across the Army will provide subject matter experts to educate Soldiers in physical and mental activities, such as mindfulness. Programs outside the military, such as the American College of Sports Medicine’s Exercise Is Medicine, that promote activity as a vital sign could be useful for integrati ng physicians, as well as allied health and tness professionals prescribing exercise programs. The Army Morale, Welfare, and Recreation program serves as a platform to reach military families with activity-centric programs and initiatives. LOE 3: Policy – Enforcing physical readiness training and requiring Army Wellness Center orientations will ensure tness and exercise principles are practiced and disseminated. Active engagement by Army senior leaders in modeling and support via policy directiv es, as well as physical and mental activity efforts will resonate among Soldiers. Policies for families, civilians, and other speci al populations (pregnant Soldiers, etc) will ensure the Army family is engaged with improving their activity. Physical readiness assessm ent changes underway in the military have the potential to change the way Soldiers train. Environmental/infrastructure policy chang es can also change the manner in which activity is fostered. Integrating and synchronizing the Activity lines of effort for educat ion, programs, and policies should all summate to change the mindset of the Army family so that stamina is maintained, restored and improved.

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October – December 2013 13THE ARMY MEDICAL DEPARTMENT JOURNAL doctrine, functional tness, ECPs, minimalist running shoes, dangers of prolonged sitting, preventing injuries, safe running, preparing to perform physical activity, and resistance training. The Activity LOE within the Performance Triad (Figure 2) could be particularly successful if implementation of the TRADOC MFT program is adopted. Embedding MFTs within operational units down to the lowest level feasible could serve the dual role of providing and sustaining legacy subject matter experts on HPO/IP practices, as well as role modeling “what right looks like” to promote the desired behavior modi cation. Figure 2 illustrates a concept of operations for activity using education, program, and policy lines of effort. Figure 3 provides more detailed descriptions for the current HPO/IP initiatives listed under the SMR-CP strategic objective: improve soldier injury prevention/human performance. Although a number of innovative HPO/ IP initiatives are currently ongoing, most of these initiatives are largely unknown beyond where they are being locally conducted; they are not part of a larger synchronized, integrated, and coordinated HPO/IP effort. An opportunity exists to use these examples and adopt lessons learned so we can move forward with a more global, uni ed, and focused approach. This could lead to published research ndings providing militarily feasible, acceptable, and suitable HPO/IP interventions and performance outcome measures. Until such efforts have been fully validated as scienti cally credible and shown to be effective, caution should be exercised before widespread implementation. The 2 MEDCOM initiatives, the Soldier Medical Readiness and the Performance Triad campaigns, demonstrate that the Army medical community intends to transform their paradigm from one of reactive health care to one of proactive promotion of health. An analysis of the strengths, weaknesses, opportunities, and threats of current HPO/IP initiatives in the Army is provided in Figure 4. Clear strengths of the current state of military HPO/IP programs which could be exploited to facilitate further progress are indicated. However, to capitalize on current momentum, action by senior Army leaders is required to review HPO/IP policies and direct the development of strategic initiatives to improve upon weaknesses and neutralize growing threats. RECOMMENDATIONS FOR THE WAY AHEAD: IMPLEMENTING ORGANIZATIONAL, COMMUNICATION, SCIENTIFIC, AND OPERATIONAL CHANGE THROUGH STRATEGIC PLANNING A paradigm shift is beginning in the Army and DoD approaches to physical readiness policies, training, and doctrine. The Army initiatives described above testify to this need. In January 2004, the Deputy Secretary of Defense directed the Joint Staff to “develop the next generation of…programs designed to optimize human performance and maximize ghting strength.”58 Subsequently, a new joint human performance enhancement capabilities document addressed human-performance standards, metrics, capabilities, and gaps.58 The joint human performance enhancement capabilities outlined in the Joint Force Health Protection Concept of Operations12 include: (1) manage War ghter fatigue; (2) optimize human-systems integration; (3) enhance Warfighter sensory, cognitive, and motor capabilities; (4) enhance War ghter learning, communications, and decision making; (5) enhance physiological capability; (6) provide/maintain ability to operate across the full range of environments; and (7) provide a healthy and t force. In 2005, the DoD Of ce of Net Assessment published Human Performance Optimization and Military Missions .59 This report spawned a request from the Assistant Secretary of Defense, Health Affairs (ASD/HA) to the military services to convene a conference that was held June 7-9, 2006. The goal of the conference was to initiate development of a strategic plan for HPO within the military. The conference was titled “Human Performance Optimization in DoD: Charting a Course for the Future.”60The conference included subject matter experts from over 56 different DoD stakeholder groups: senior leaders (ADM Michael Mullen, Chairman of the Joint Chiefs of Staff was the keynote speaker),61 War ghters/ operators, unit commanders, allied health professionals, scientists and researchers, and safety of cers. Recommendations from the workshop were published in a report forwarded to ASD/HA and a special supplement issue of Military Medicine .62 In response to this report, the ASD/HA convened a HPO Integrated Product Team to review the USUHS report, collect relevant data from the services, and make recommendations for a novel comprehensive HPO program. Among these was a directive to The Army Surgeon General to incorporate key HPO requirements into a Joint Medical Research Command (under the US Uni ed Medical Command) as a key focus area. The plan for a US Uni ed Medical Command was later rejected in December 2006 primarily due to resistance from Air Force senior leadership.63 With current federal budgetary constraints and the potential to reduce redundancies, conserve resources, and implement interoperability and collaboration among the services, the concept of a uni ed medical command is again worth consideration.64,65 Currently, it appears the establishment off a Defense Health Agency in October 2013 is an effort toward developing a set of strategies

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14 http://www.cs.amedd.army.mil/amedd_journal.aspx STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY Initiative Title : Ranger, Athlete, Warrior (RAW) Program Proponent : 75th Ranger Regiment Description/Comments : Uses Army physical therapist-led train-the-trainer course and is a conglomeration of several physical performance techniques focusing on body mechanics, strength, speed, agility, and military task performance. Includes a RAW physical performance assessment as a metric. Initiative Title : Eagle Tactical Athlete Program Proponent : 101st Airborne/Air Assault Division and the University of Pittsburgh Description/Comments : Extramural funded (via the Army Medical Research and Material Command Telemedicine and Advanced Technology Research Center) research effort comprehensively evaluating aspects of HPO/IP: injury surveillance, task and demand analysis, predictors of injury and optimal performance, design and validation of interventions, program integration and implementation, and monitoring to determine effectiveness of program.56Initiative Title : Mountain Athlete Program Proponent : 4th ID/FORSCOM Description/Comments : HPO program team consists of an Army physical therapist, CrossFit certi ed trainers, and power lifting coaches who focus on muscular strength, muscular and cardiovascular endurance, speed, agility, and exibility. The goal is to reduce nondeployable injury rates and increase unit readiness. Initiative Title : Iron Horse Performance Optimization Program Proponent : 4th ID/FORSCOM Description/Comments : Uses an embedded musculoskeletal action team (MAT) in a Brigade Combat Team through a full Army Force Generation cycle focusing on optimizing performance, minimizing injuries, identifying/treating injuries early, reconditioning rehabilitated Soldiers. Initiative Title : Soldier Athlete Initiative Proponent : TRADOC/MEDCOM Description/Comments: Uses an MAT concept at TRADOC initial entry sites to address injury incidence rates. Initiative Title : Tactical Human Optimization Rapid Rehabilitation & Reconditioning Program Proponent : US Army Special Operations Command (USASOC) Description/Comments : Program incorporates a team consisting of physical therapists, strength and conditioning coaches, and a dietician to reduce injury, improve functional performance, and optimize proper fueling. Each team sets program priorities and performance metrics. Initiative Title : Advanced Tactical Athlete Conditioning Proponent : MEDCOM/25th ID Description/Comments : Provides tools (train-the-trainer) and information necessary to lead Soldiers through a tactical, battle-focused approach to PT. Includes high-intensity aquatic training, tactical agility physical training, combat core conditioning, interval speed training, and running form analysis. The USAPHC is conducting program evaluation. Initiative Title : Military Power, Performance and Prevention Proponent : MEDCOM/US Army Medical Department Center and School Description/Comments : This program measures multiple performance metrics such as mobility, power, and balance and injury surveillance in 2/75th Ranger Battalion, 1st Special Forces, a Stryker brigade and a support brigade from the 2nd ID. The goal is to identify those performance metrics that are predictive of injury. A special and unique feature of the initiative is the use of technology as a leveraging tool for the assessment and data collection. Figure 3. Human performance optimization and injury prevention initiatives tracked by the Of ce of The Surgeon General.57

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October – December 2013 15THE ARMY MEDICAL DEPARTMENT JOURNAL Strengths 1. Current doctrine provided in Field Manual 7-2239 to guidelines established by the American College of Sports Medicine and the National Strength and Conditioning Association and has been validated by peerreviewed, published research. 2. Numerous intrinsic injury risk factors have been identi ed via evidence-based and peer-reviewed research ndings. 3. Innovative research efforts and public health practices occur with the US Army Medical Command (Medical Research and Material Command and USAPHC) that prioritizes HPO/IP research, surveillance, and evaluation. 4. Many examples of human performance optimization and injury prevention initiatives currently ongoing across the Army. 5. Increasing senior leader awareness with regard to the impact of musculoskeletal injuries on military readiness and national security. 6. Current and future science and technology advances hold great promise with regard to human performance optimization and injury prevention research. Weaknesses 1. The incidence rate for musculoskeletal injuries remains unacceptably high. 2. Lack of physical training/injury prevention subject matter experts organic to the military personnel system. 3. The main proponent for physical readiness training (US Army Physical Fitness School) is not resourced adequately, particularly with personnel. 4. Poor synchronization, integration, and communication of human performance optimization/injury prevention efforts across Army commands and operators, health practitioners, researchers, and leaders. 5. Implementation of physical training doctrine is unevenly applied across the Army. 6. Validated and accepted performance metrics do not exist with regard to human performance optimization/ injury prevention. 7. HPO/IP initiatives have not been systematically applied or researched across the War ghter’s entire lifecycle or within Army Reserve or National Guard units. Opportunities 1. Soldier Medical Readiness Campaign. 2. Performance Triad Campaign. 3. Establishment of a Defense Health Agency. 4. Master tness trainers. 5. Current and future science and technology advances hold great promise with regard to human performance optimization and injury prevention research. 6. Increasing senior leader awareness with regard to the impact of musculoskeletal injuries on military readiness and national security. 7. Military health and tness outreach to society’s youth. 8. Revise manner in which HPO/IP is assessed. Establish metrics of performance and effectiveness. Threats 1. Commercialized HPO/IP entities (CrossFit, etc) are becoming increasingly popular among Soldiers and have not been supported by evidence-based research. 2. Shrinking budgets can negatively impact research and development budgets and HPO/IP resource allocation. 3. Excessive and increasing external loads (load carriage). 4. Increasing societal trends for declining activity levels and tness. Increased obesity. 5. Lack of Uni ed Joint Medical/Research Command. Figure 4. Strengths, weaknesses, opportunities and threats analysis for current Army HPO/IP initiatives.

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16 http://www.cs.amedd.army.mil/amedd_journal.aspxon governance to achieve certain ef ciencies on “shared services” across the DoD. The workshop categorized the major issues/challenges to achieving HPO as (1) organizational, (2) communication, (3) scienti c, and (4) operational, based upon the type of strategic action required to resolve identi ed obstacles within DoD.60 With regard to organizational issues, existing policies should be reviewed with guidance to ensure consistency of HPO approaches in response to new research and technological developments.60 Another important related issue involves operational translation and dissemination of knowledge and research results to commanders and War ghters.60 The workshop recommended the establishment of a joint center for HPO to translate knowledge and research into the DoD standard of Doctrine, Organization, Training, Material, Leadership, Personnel, and Facilities.60 The Human Performance Resource Center at CHAMP is an online (http://hprc-online.org/about-us/about-hprc) clearinghouse and information repository that serves to translate and disseminate timely, accurate, scienti cally based HPO information to commanders, War ghters, medical personnel, and researchers, some key examples of which are shown in Figure 5. STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY SourceComments Field Manual 7-22: Army Physical Readiness Training39 (October 2012) Supersedes discontinued Training Circular 3-22.20: Army Physical Readiness Training (August 2010) Technical Bulletin Med 592: Prevention and Control of Musculoskeletal Injuries Associated with Physical Training18 (May 2011) First medical technical bulletin dedicated to disseminating evidence-based guidance for controlling MSIs. Consortium for Health and Military Performance and American College of Sports Medicine Consensus Paper on Extreme Conditioning Programs in Military Personnel53This peer-reviewed scienti c manuscript is the product of a joint workshop addressing extreme conditioning programs held September 13-14, 2010, at USUHS, Bethesda, MD. American Journal of Preventive Medicine January 2010, Volume 38 (Supplement 1) This supplement contains 25 peer-reviewed articles from the Joint Services Physical Training Injury Prevention Working Group which include systematic reviews.3,4,7,8,10,49,50Military Medicine (Supplement: Total Force Fitness for the 21st Century: A New Paradigm), August 2010, Volume 175(8)60This supplement contains 15 peer-reviewed articles from the 2006 joint service workshop “Human Performance Optimization in DoD: Charting a Course for the Future” hosted by USUHS, Bethesda, MD. War ghter Nutrition: Current Opportunities and Advanced Technologies Report From a Department of Defense Workshop55This peer-reviewed article is the product of a joint DoD conference which concluded that nutritional optimization represents an integral and proactive approach to prevent illness, injury, and performance degradation throughout all phases of military service. Physiological Employment Standards III: Physiological Challenges and Consequences Encountered During International Military Deployments23This peer-reviewed article was the result of an Invited Keynote Presentation at the 1st Australian Conference on Physiological and Physical Employment Standards, 28 November 28, 2012 in Canberra, Australia. It provides a comprehensive overview of the physiological effects of deployment with a particular focus on physical tness and injuries. Human Performance Resource Center: A DoD initiative under the Force Health Protection and Readiness Program (http://hprc-online.org/about-us/about-hprc) A website sponsored by the CHAMP at USUHS that translates and disseminates accurate, scienti callybased HPO information to commanders, War ghters, medical personnel, and researchers.Figure 5. Key authoritative military physical readiness sources for Army senior leaders.

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October – December 2013 17THE ARMY MEDICAL DEPARTMENT JOURNAL Communication remains a large barrier to the achievement of HPO. A common concern is that commanders and clinicians in the eld are typically unaware of current HPO information and research efforts. Operators at the highest levels often do not have adequate visibility of research results and existing biomedical solutions. There are also concerns about valid and reliable information from military research reaching the War ghter, but rather the War ghter gathers his information from unsubstantial commercial venues.60 Consequently, opportunities for military scientists to regularly interact with operators about evidence and development of scienti c ndings should be encouraged. Future communication efforts should focus on coordination within and across services. Ideally, organizations that conduct HPO research need to be teamed with representatives from acquisition, medical personnel, and operational units from the eld to discuss current research, to identify opportunities for cooperation, and to determine future HPO needs.60The scienti c issues raised by the workshop centered on the need to develop operationally relevant and standardized metrics to meet joint military requirements.53 The development of these metrics was considered the single most important issue for research and application of HPO.60 Accepted, reliable, and valid metrics that relate to combat effectiveness for all of the above capabilities are limited and remain an area for which joint consensus is needed, particularly for measures of performance and measures of effectiveness. Ideally, research efforts should consider the War ghter through his/her entire life cycle as an integrated program of preparation, training, and monitoring from accession to retirement/ separation.60From an operational perspective, collaboration between operators and medical researchers is essential for developing and elding feasible, acceptable, and suitable HPO approaches.60 Options for maintaining functional tness, performance nutrition, cognitive and psychological readiness throughout predeployment, deployment/ engagement, and postdeployment/ redeployment timelines are desired and critically needed.60 The HPO programming should preserve human capital by addressing service member weaknesses, injury and disease prevention, physical readiness training, maximizing sleep quality, and other factors affecting performance.60The vision moving forward is to have HPO conceived as a joint, interagency, combined and coalition effort that creates an interdisciplinary center for investigating HPO in operational settings as well as establishing translational research and education agendas that address barriers and approaches to optimal performance. Developing effective communication netrworks that cross research, medical and operational boundaries is critical to the success of this effort.60 The recommended course of action is to provide HPO functionality by establishing a uni ed Joint Medical Research Program with a core HPO function. The speci c objectives of such an option would be to: (1) advocate for HPO within DoD; (2) coordinate and integrate DoD extramural and intramural HPO medical research; (3) align HPO initiatives to DoD priorities; (4) collaborate with line HPO research functions to ensure synergy toward common endpoints; (5) establish HPO standards, (6) establish a clearinghouse function; (7) continue to leverage the Health Affairs HPO IPT as a community of interest; 8) recommend HPO policy and doctrine to Assistant Secretary of the Army (Health Affairs).60 A concerted and integrated strategic HPO effort will serve to: (1) enhance the mental and physical resilience of the War ghter; (2) reduce injury and illness or facilitate more rapid recovery if injury does occur; (3) provide seamless information and knowledge transfer from the laboratory to line; (4) improve the human weapon system’s ability to accomplish the mission; and (5) allow the United States to remain at the leading/cutting edge in this area.60 With the sanctioning of CHAMP and their educational arm, the Human Performance Resource Center at the USUHS as a Defense Center of Excellence (Figure 5), and the establishment of the Health Affairs Human Performance Optimization Health Sciences Advisory Committee, many of the recommendations are being realized. ALTERNATIVE SCENARIOS FOR HPO/IP On February 19, 2013, the Strategy Innovation Of ce of USAPHC conducted an alternative exercise considering possible future scenarios with over 20 subject matter experts from the USAPHC Epidemiology and Disease Surveillance and the Health Promotion and Wellness Portfolios, and CHAMP. The purpose of this exercise was to brainstorm and develop narratives for different future HPO/IP scenarios based upon alternative political, economic, organizational, operational, environmental, scienti c, technological, and social assumptions. Figure 6 depicts 2 key variables that would potentially in uence future HPO/IP scenarios: (1) the use of scienti c, evidence-based best practices; and (2) the extent to which senior leadership supports, prioritizes, and implements scienti c innovative, synchronized, and integrated HPO/IP policy changes. Of the 4 possible alternative scenarios represented in Figure 6, two were chosen to script narratives for the best case, most desired scenario (Resilient, Dominant War ghter ) and the worst case (Injured, Nondeployable War ghter ) projected to occur unless appropriate strategies are implemented. These scenarios are discussed below.

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18 http://www.cs.amedd.army.mil/amedd_journal.aspxScenario 1: Resilient, Dominant WarfighterAs the military becomes smaller, senior leadership will prioritize and place a greater emphasis on preservation of the force by focusing on proven preventive and public health practices. A more selective screening process will be used to recruit new military trainees based on established baseline physical and cognitive requirements to perform military occupations and duties. Better predictive models and analytics will yield better placement of Soldiers in military occupational specialties. The military prioritizes investment in research and development. Technological advances in materiel science and further re nement of exoskeletons result in lighter external loads. Biosensor technologies provide great insight for training physiology and recovery and are used as important adjuncts to planning physical training. A detailed cost-bene t analysis indicates that signi cant cost savings can result from embedding medical, physical tness, and nutritional subject matter experts into operational units. Deliberate and detailed physiological studies on women in the military will identify risk mitigation and HPO/IP strategies to protect against increased MSI risk. When data systems are integrated and able to communicate with one another, the information gathered is used to re ne models predicting risk; new models are applied to pre-identify injuries and negative outcomes before they occur. The HPO/IP and human systems are given the same attention as weapons systems. The military strategically partners with leading nonpro t HPO/IP organizations (eg, the American College of Sports Medicine, National Strength and Conditioning Association) to assist in disseminating credible and validated HPO/IP information. Logically extending from the MFT course, additional occupational specialties or additional skill identi er dedicated toward HPO/IP are implemented. Identi ers exist for units and Soldiers to engage in healthy behaviors, which lead to improved HPO/IP efforts. The HPO/ STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY Anecdotal and/or historical precendence drives HOP/IP doctrine and policy “Science-Light” Senior leadership fails to prioritize HPO/IP programs. “Strategic Complacency” Desired Status Current Status Current Status Projected Status Senior leadership implements innovative HOP/IP policy changes. “Strategic Action” 3. “War ghter Cannot Carry His Load.” HPO/IP efforts in the military are not supported by evidence-based science. 2. “Walking Wounded War ghter” Status quo: MSIs continue to degrade the military’s human capital. 4. “Injured, Nondeployable War ghter” Severe MSI epidemic degrades the US military as national instrument of power. 1. “Resilient, Dominant War ghter” Integrated and synchronized HPO/IP efforts establish strategic dominance. Scienti c, evidence-based best practices drive HPO/IP doctrine and policy. “Science-Plus” Figure 6. Conceptual alternative future scenario framework port rays 2 major variables: the vertical axis depicts the extent to which HPO/IP practices in the Army are supported by scienti c evidence-based best practices (Science Plus vs Science Light). The horizontal axis depicts the extent to which senior leadership supports, prioritizes, and implements innovative, synchronized, and integrated HPO/IP policy changes (Strategic Action vs Strategic Complacency). Each quadrant uses a pairing of these 4 states to frame a scenario, examine possible strategic intervention measures, and explore potential strategic outcomes: 1. Resilient, Dominant War ghter; 2. Walking Wounded War ghter; 3. War ghter Cannot Carry His Load; and 4. Injured, Nondeployable War ghter. The narratives for the best case (Resilient, Dominant War ghter) and worst case (Injured, Nondeployable War ghter) scenarios are presented in the text.

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October – December 2013 19THE ARMY MEDICAL DEPARTMENT JOURNAL IP efforts are individualized and exploit the latest scienti c and technological breakthroughs. Additionally, military environments are redesigned and organized to take advantage of the latest HPO/IP scienti c and technological breakthroughs. Dining facility administration centers employ dietary specialists to ensure quality throughout all food venues on bases. Science is embraced by senior Army leadership, and HPO/IP science advisors are embedded in major Army commands to facilitate policy decisions governing the health and tness of Soldiers. A joint DoD HPO/IP center is created to ensure a rapid process for systemic reviews and increased research funding for HPO/IP translational research. Research is communicated effectively and in a timely fashion to the operational force. The military becomes the worldwide leader in HPO/IP, resulting with the emergence of resilient and dominant War ghters who effectively project our military power and act as deterrents to hostile action from our adversaries.Scenario 2: Injured, Nondeployable WarfighterWith the downsizing of the military and further budget cuts, a danger exists that preventive medicine, public health, and HPO/IP research initiatives will be forsaken. Fewer medical assets, allied health professionals, and other HPO/IP enablers (MFTs, health promotion of cers, resiliency and wellness centers, and so forth) will be available in the personnel inventory. Fewer resources result in the military experiencing a technology lag, which leads to a decline in personal protective equipment development and, consequently, a continued increase in external loads Soldiers are required to carry. A moderate “brain drain” occurs in the military research and development community as research budgets shrink further to marginalize HPO/IP research efforts. As scienti c conference attendance restrictions are sustained, military scientists lose relevance and expertise resulting in more scientists leaving government service. Increased use of drones and alternate technologies changes the dynamics of the ghting force. Commanders become less interested in maintaining military physical readiness as the nature of warfare becomes more technological, while there is a focus shift from physical to cognitive performance. The associated increase in physical health problems and degradation of individual health lead to more injuries and chronic disease; this ampli es behavioral health concerns as a result of increased cognitive trauma and stress. Long-term health care and long-term disability costs rise, which overwhelms the federal budget and results in diminished quality of care. The societal trends for decreased tness continue. The implosion of obesity and the medically un t results in even higher injury rates halting progress toward a system for health. Implementation of validated science-based best-practices is lost in a cacophony of messages, marketing, and voices, many driven by non-DoD “pseudo” HPO/IP subject matter experts motivated primarily by nancial pro t and/or personal gain. Confused and demoralized Soldiers obtain their HPO/IP information from unvetted sources available through the internet and companies catering to the military for pro t. The end result is a military characterized as injured and nondeployable. The military has compromised stamina and ceases to be an effective instrument of national political power. Seeking to exploit this vulnerability, other hostile nation states and nonstate actors provoke aggression to create internal and external con icts and “small wars.” CONCLUSION It is imperative for military leaders to understand that physical training-related MSIs are preventable when composite risk management principles are closely followed and pragmatic strategy and policy changes are considered. Figure 5 provides a list of some authoritative HPO/IP sources for military leaders reference as needed. The following recommendations are offered to establish a comprehensive, evidence-based approach to military HPO/IP60: Increase HPO/IP knowledge and expertise across the military. Implementation of additional occupational specialties or additional skill identi ers dedicated toward HPO/IP (ie, MFTs) could be productive. Implement/adapt evidence-based, proven physical training and injury prevention strategies based on preestablished priorities. Evaluate effectiveness of all implemented policies, procedures, and interventions/countermeasures on a continuous basis. Identify gaps in knowledge of human physical performance optimization and injury prevention, and target these gaps for research. Establish routine channels for disseminating information based on each public health and evidencebased decision-making process to ensure key stakeholders receive the information and training necessary to effectively reduce the impact of injuries on the health and readiness of military personnel. Use readily available military surveillance databases to identify the largest, most serious military injury problems.

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20 http://www.cs.amedd.army.mil/amedd_journal.aspx Commission systematic reviews of prevention and safety literature to determine what works for the largest, most serious military injury problems. Establish committees of medical and safety subject matter experts to routinely assess and prioritize both injury prevention research and program/policy implementation. As our military transforms and responds to current and emerging threats, it is increasingly clear that we must ensure optimal human performance of our military. By taking advantage of the science and applications of physical tness and injury prevention, we can leverage our increased understanding to reduce the risk of injuries with the optimal application of our physical and mental readiness processes, ensuring that we maintain our Soldiers as Army Strong. RELEVANCE TO PERFORMANCE TRIAD The Army Surgeon General has provided visionary guidance for Army Medicine to transform from a healthcare system to a system for health. The foundation for this is the Performance Triad of activity, nutrition, and sleep. LTG Horoho is particularly timely and insightful in her vision for Army Medicine following 12 years of war. The time is ripe for a paradigm shift, and this article highlights the many ongoing efforts within the DoD and Army that are indicative of a climate of change. In this article we provide a strategic vision for Army leadership and policy makers on a path for enhanced military physical readiness, which directly supports the Activity Line of Effort for the Performance Triad. By identifying, prioritizing, resourcing, and assigning proponency for HPO/IP solutions, we believe success can be realized. A continued dialogue and forging of partnerships with all relevant stakeholders will be critical for altering the mindset for behavior change to drive HPO/IP solutions and develop healthy and resilient War ghters. ACKNOWLEDGEMENTSThis article is based on a paper that was completed as part of a Strategic Research Project and in partial ful llment for the Masters Degree in Strategic Studies while Dr Nindl was a Department of the Army civilian in residence from 2011-2012 at the Army War College, Carlisle, PA. Particular recognition and appreciation for their support goes to Dr Thomas Williams (COL (Ret), USA), who served as the Strategic Research Project advisor, Professor Edward Filiberti (COL (Ret), USA), his academic advisor and Seminar 3 lead instructor, and Ms Julie Manta (COL (Ret), USA), civilian student advisor.REFERENCES1. Garamone J, Parrish K. Military strategy drives budget decisions, Dempsey says [internet]. American Forces Press Service December 9, 2011. Available at: http://www.defense.gov/News/News Article.aspx?ID=66419. Accessed August 29, 2013. 2. Garamone J. Panetta announces scal 2013 budget priorities [internet]. American Forces Press Service January 26, 2012. Available at: http://www. defense.gov/News/NewsArticle.aspx?ID=66940. Accessed August 29, 2013. 3. Ruscio BA, Jones BH, Bullock SH, et al. A process to identify military injury prevention priorities based on injury type and limited duty days. Am J Prev Med. 2010;38(suppl 1):S19-S33. 4. Hauret KG, Taylor BJ, Clemmons NS, Block SR, Jones BH. Frequency and causes of nonbattle injuries air evacuated from operations Iraqi Freedom and Enduring Freedom, U.S. Army, 2001-2006. Am J Prev Med. 2010;38(suppl 1):S94-S107. 5. Feuerstein M, Berkowitz SM, Peck CA Jr. Musculoskeletal-related disability in US Army personnel: prevalence, gender, and military occupational specialties. J Occup Environ Med. 1997;39(1):68-78. 6. Amoroso PJ, Canham ML. Chapter 4. Disabilities related to the musculoskeletal system: Physical Evaluation Board Data. Mil Med. 1999;164(suppl 8):1-73. 7. Hauret KG, Jones BH, Bullock SH, Canham-Chervak M, Canada S. Musculoskeletal injuries description of an under-recognized injury problem among military personnel. Am J Prev Med. 2010;38(suppl 1):S61-S70. 8. Jones BH, Canham-Chervak M, Canada S, Mitchener TA, Moore S. Medical surveillance of injuries in the U.S. Military: descriptive epidemiology and recommendations for improvement. Am J Prev Med. 2010;38(suppl 1):S42-S60. 9. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and injury prevention in military populations. Sports Med. 1999;27(2):111-125. 10. Schoomaker LE. The U.S. Army Medical Department commitment to injury reduction. Am J Prev Med. 2010;38(suppl 1):S217. 11. Quadrennial Defense Review. Washington, DC: US Dept of Defense; February 2010. Available at: http://www.defense.gov/qdr/images/QDR_as_ of_12Feb10_1000.pdf. Accessed August 29, 2013. 12. Joint Force Health Protection Concept of Operations. Ver 1.0. Washington, DC: US Dept of Defense; July 2007. Available at: http://pre.docdat.com/ docs/index-21211.html. Accessed August 29, 2013. STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

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October – December 2013 21THE ARMY MEDICAL DEPARTMENT JOURNAL13. Sample D. Army wants more Soldiers back on deployable status [internet]. Army News Service October 11, 2011. Available at: http://www.army.mil/ article/67037/. Accessed August 29, 2013. 14. Jones BH, Perrotta DM, Canham-Chervak ML, Nee MA, Brundage JF. Injuries in the military: a review and commentary focused on prevention. Am J Prev Med. 2000;18(suppl 3):71-84. 15. Atlas of injuries in the United States Armed Forces. Mil Med. 1999;164(suppl 8). 16. Army Medical Surveillance Activity. Absolute and relative morbidity burdens attributable to various illnesses and injuries, U.S. Armed Forces, 2012. MSMR. 2013;20(4):5-10. 17. Army Medical Surveillance Activity. Estimates of absolute and relative health care burdens attributable to various illnesses and injuries, U.S. Armed Forces, 2005. MSMR. 2006;12(3):16-22. Available at: http://www.afhsc.mil/viewMSMR? le=2006/ v12_n03.pdf#Article3. Accessed August 29, 2013. 18. Gilchrist J, Jones BH, Sleet DA, Kimsey CD. Exercise-related injuries among women: strategies for prevention from civilian and military studies. MMWR Recomm Rep. 2000;49(RR-2):15-33. 19. Technical Bulletin Med 592: Prevention and Control of Musculoskeletal Injuries Associated with Physical Training. Washington, DC: US Dept of the Army; May 2011. Available at: http://armypubs. army.mil/med/dr_pubs/dr_a/pdf/tbmed592.pdf. Accessed August 29, 2013. 20. Bell NS, Schwartz CE, Harford T, Hollander IE, Amoroso PJ. The changing pro le of disability in the U.S. Army: 1981-2005. Disabil Health J. 2008;1(1):14-24. 21. Nindl BC, Alemany JA, Kellogg MD, et al. Utility of circulating IGF-I as a biomarker for assessing body composition changes in men during periods of high physical activity superimposed upon energy and sleep restriction. J Appl Physiol. 2007;103(1):340-346. 22. Nindl BC, Barnes BR, Alemany JA, Frykman PN, Shippee RL, Friedl KE. Physiological consequences of U.S. Army Ranger training. Med Sci Sports Exerc. 2007;39(8):1380-1387. 23. Nindl BC, Castellani JW, Warr BJ, et al. Physiological employment standards III: physiological challenges and consequences encountered during international military deployments. Eur J Appl Physiol. February 2013 [epub]. 24. Nindl BC, Castellani JW, Young AJ, et al. Differential responses of IGF-I molecular complexes to military operational eld training. J Appl Physiol. 2003;95(3):1083-1089. 25. Nindl BC, Leone CD, Tharion WJ, et al. Physical performance responses during 72 h of military operational stress. Med Sci Sports Exerc. 2002;34(11):1814-1822. 26. Nindl BC, Rarick KR, Castellani JW, et al. Altered secretion of growth hormone and luteinizing hormone after 84 h of sustained physical exertion superimposed on caloric and sleep restriction. J Appl Physiol. 2006;100(1):120-128. 27. Nindl BC. Insulin-like growth factor-I, physical activity, and control of cellular anabolism. Med Sci Sports Exerc. 2010;42(1):35-38. 28. Nindl BC, Pierce JR. Insulin-like growth factor I as a biomarker of health, tness, and training status. Med Sci Sports Exerc. 2010;42(1):39-49. 29. Kraemer WJ, Adams K, Cafarelli E, et al. American College of Sports Medicine position stand. Pro-gression models in resistance training for healthy adults. Med Sci Sports Exerc. 2002;34(2):364-380. 30. Nindl BC, Sco eld DE, Strohbach CA, et al. IGFI, IGFBPs, and in ammatory cytokine responses during gender-integrated Israeli Army basic combat training. J Strength Cond Res. 2012;26 (suppl 2):S73-S81. 31. Cohen SP, Brown C, Kurihara C, Plunkett A, Nguyen C, Strassels SA. Diagnoses and factors associated with medical evacuation and return to duty for service members participating in Operation Iraqi Freedom or Operation Enduring Freedom: a prospective cohort study. Lancet. 2010;375(9711):301-309. 32. Koplan JP, Powell KE, Sikes RK, Shirley RW, Campbell CC. An epidemiologic study of the bene ts and risks of running. JAMA. 1982;248(23):3118-3121. 33. Knapik JJ, Hauret KG, Canada S, Marin R, Jones B. Association between ambulatory physical activity and injuries during United States Army Basic Combat Training. J Phys Act Health. 2011;8(4):496-502. 34. Jones BH, Cowan DN, Knapik JJ. Exercise, training and injuries. Sports Med. 1994;18(3):202-214. 35. Knapik JJ, Sharp MA, Canham-Chervak M, Hauret K, Patton JF, Jones BH. Risk factors for training-related injuries among men and women in basic combat training. Med Sci Sports Exerc. 2001;33(6):946-954. 36. Jones BH, Cowan DN, Tomlinson JP, Robinson JR, Polly DW, Frykman PN. Epidemiology of injuries associated with physical training among young men in the army. Med Sci Sports Exerc. 1993;25(2):197-203. 37. Jones BH, Bovee MW, Harris JM III, Cowan DN. Intrinsic risk factors for exercise-related injuries among male and female army trainees. Am J Sports Med. 1993;21(5):705-710.

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22 http://www.cs.amedd.army.mil/amedd_journal.aspx38. Pollock ML, Gettman LR, Milesis CA, Bah MD, Durstine L, Johnson RB. Effects of frequency and duration of training on attrition and incidence of injury. Med Sci Sports. Spring 1977;9(1):31-36. 39. Field Manual 7-22: Army Physical Readiness Training Washington, DC: US Dept of the Army; October 2012. Available at: http://armypubs.army. mil/doctrine/DR_pubs/dr_a/pdf/fm7_22.pdf. Accessed August 29, 2013. 40. Knapik JJ, Rieger W, Palkoska F, Van Camp S, Darakjy S. United States Army physical readiness training: rationale and evaluation of the physical training doctrine. J Strength Cond Res. 2009;23(4):1353-1362. 41. Knapik JJ, Hauret KG, Arnold S, et al. Injury and tness outcomes during implementation of physical readiness training. Int J Sports Med. 2003;24(5):372-381. 42. Knapik JJ, Bullock SH, Canada S, et al. In uence of an injury reduction program on injury and tness outcomes among soldiers. Inj Prev. 2004;10(1):37-42. 43. Knapik J, Darakjy S, Scott SJ, et al. Evaluation of a standardized physical training program for basic combat training. J Strength Cond Res. May 2005;19(2):246-253. 44. Harman EA, Gutekunst DJ, Frykman PN, et al. Effects of two different eight-week training programs on military physical performance. J Strength Cond Res. March 2008;22(2):524-534. 45. Kraemer WJ, Mazzetti SA, Nindl BC, et al. Effect of resistance training on women’s strength/power and occupational performances. Med Sci Sports Exerc. Jun 2001;33(6):1011-1025. 46. Grier T, Canham-Chervak M, McNulty V, Jones B. Extreme conditioning programs and injury risk in a U.S. Army brigade combat team. US Army Med Dep J October–December 2013:36-47. 47. National Strength and Conditioning Association Blue Ribbon Panel on Military Physical Readiness; 13-14 January, 2011; Key West, FL. 48. US Secretary of Defense. Memorandum: Reducing Preventable Accidents. Washington, DC: US Dept of Defense; May 19, 2003. Available at: http://www. defense.gov/news/May2003/U06916-03.pdf. Accessed August 29, 2013. 49. Bullock SH, Jones BH, Gilchrist J, Marshall SW. Prevention of physical training-related injuries recommendations for the military and other active populations based on expedited systematic reviews. Am J Prev Med. 2010;38(suppl 1):S156-S181. 50. Jones BH, Canham-Chervak M, Sleet DA. An evidence-based public health approach to injury priorities and prevention recommendations for the U.S. military. Am J Prev Med. 2010;38(suppl 1):S1-S10. 51. Hadeed M, Kuehl K, Elliot D, Sleigh A. Exertional rhadbomyolysis after cross t exercise program. Med Sci Sports Exerc. 2011;43(suppl 5):S152. 52. Smith MM, Sommer AJ, Starkoff BE, Devor ST. Cross t-based high intensity power training improves maximal aerobic tness and body composition. J Strength Cond Res. February 22, 2013 [epub]. 53. Bergeron MF, Nindl BC, Deuster PA, et al. Consortium for Health and Military Performance and American College of Sports Medicine consensus paper on extreme conditioning programs in military personnel. Curr Sports Med Rep. 2011;10(6):383-389. 54. Soldier Medical Readiness Campaign Plan 2011-2016 Washington, DC: US Army Medical Command; May 2011. Available at: http://www. armymedicine.army.mil/news/docs/SMR_CP_ Version_1.2.pdf. Accessed August 29, 2013. 55. Deuster PA, Weinstein AA, Sobel A, Young AJ. War ghter nutrition: current opportunities and advanced technologies report from a Department of Defense workshop. Mil Med. 2009;174(7):671-677. 56. Sell TC, Abt JP, Crawford K, et al. Warrior model for human performance and injury prevention: Eagle Tactical Athlete Program (ETAP) Part I. J Spec Oper Med. 2010;10(4):2-21. 57. Pendergrass T. Injury Prevention and Human Performance Optimization Initiatives Washington, DC: Of ce of The Army Surgeon General; 12 July 2011. 58. Performance Optimization (HPO) within DoD Paper presented at: 2007 Military Health System Conference; January 29 – February 1, 2007; Washington, DC. 59. Russell A, Bulkley B, Grafton C. Human Performance Optimization and Military Missions: Final Report, GS-10F-0297K. Washington, DC: Of ce of Net Assessment, US Dept of Defense; May 2005. 60. Deuster PA, O’Connor FG, Henry KA, et al. Human performance optimization: an evolving charge to the Department of Defense. Mil Med. 2007;172(11):1133-1137. 61. Mullen M. On total force tness in war and peace. Mil Med. 2010;175:1-2. 62. Jonas WB, Deuster PA, O’Connor FG, Macedonia C, eds. Total Force Fitness for the 21st Century: A New Paradigm. Alexandria, VA: Samueli Institute; August 2010 [featured in special supplement to Mil Med August 2010;175(8)]. Available at: http://www. dtic.mil/cgi-bin/GetTRDoc?AD=ADA528391. Accessed August 29, 2013. STRATEGIES FOR OPTIMIZING MILITARY PHYSICAL READINESS AND PREVENTING MUSCULOSKELETAL INJURIES IN THE 21ST CENTURY

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October – December 2013 23THE ARMY MEDICAL DEPARTMENT JOURNAL63. Philpott T. Three-branch plan for uni ed medical command rejected info [serial online]. Newport News Daily Press; December 17, 2006. Available at: http://www.military-quotes.com/forum/threebranch-plan-uni ed-medical-t30131.html. Accessed August 29, 2013. 64. Kumpula D. Joint Medical Command – Do it now [master’s thesis]. Carlisle Barracks, PA: US Army War College; 2005. Available at: http://www.dtic.mil/ cgi-bin/GetTRDoc?AD=ADA434405. Accessed August 29, 2013. 65. Smith AM, Lane DA, Zimble JA. Purple medicine: the case for a joint medical command. Naval War College Review. 2007;60(1):1-11. Available at: http:// www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA519521. Accessed August 29, 2013.AUTHORSDr Nindl is the Science Advisor for the US Army Institute of Public Health, US Army Public Health Command, Aberdeen Proving Ground, Maryland. Dr Williams is the Director of the Strategic Leader Resiliency Program at the Army War College, Carlisle, Pennsylvania. Dr Deuster is the Director for the Consortium for Health and Military Performance Defense Center of Excellence at the Uniformed Services University of the Health Sciences, Bethesda, Maryland. COL Butler is the Chief, Army Medical Specialist Corps and Specialist Corps Branch Chief (LTC/COL Assignments Of cer) at the Human Resources Command, Fort Knox, Kentucky. Dr Jones is the Manager of the Injury Program, Epidemiology and Disease Surveillance Portfolio, US Army Institute of Public Health, US Army Public Health Command, Aberdeen Proving Ground, Maryland.

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24 http://www.cs.amedd.army.mil/amedd_journal.aspxÂ…physical tness is not only one of the most important keys to a healthy body; it is the basis of dynamic and creative intellectual activity.President-Elect John F. Kennedy1Various groups representing a number of different perspectives (for example, operational, architectural, community, institutional, and individual resilience) have de ned the term resilience. For the purposes of this article, we de ne resilience as the ability to withstand, recover, and grow in the face of stressors and changing demands.2In recent reviews and papers on resilience, one factor that continues to appear as promoting and/or conferring resilience is physical tness3,4 and regular physical activity.5-7 Thus, we focus on the role of physical tness in overall individual resilience. The bene t of physical tness on resilience is in part based on the recognition that physical tness, achieved through physical activity and/or regular exercise, can induce positive physiologic and psychological bene ts, protect against the potential consequences of stressful events, and prevent many chronic diseases.8-11 After a brief historical overview of the health-promoting effects of exercise and physical activity, the following topics are discussed: the concept of hardiness and mental toughness and how they relate to resilience and physical tness; how physical tness promotes resilience; the clinical implications of a sedentary lifestyle; and the relevance of physical tness and resilience to Army MedicineÂ’s Performance Triad. Throughout this article, the terms physical activity and exercise are used interchangeably, depending on the literature, recognizing that exercise represents a planned, structured, and regular form of physical activity. HISTORICAL OVERVIEW The quest for physical tness has been unremitting, however, its importance and application have changed and/ or transitioned over time with both high and low points. Hunting and gathering for survival were the initial impetus for tness, which was later followed by the recognition that selected physical movements and activities were important for developing the body and preventing and curing diseases.12-14 In fact, the importance of regular exercise and physical activity has been touted for over 7,000 years.12,13 In China, the philosophical teachings of Confucius encouraged participation in regular physical activity, as physical inactivity was recognized as associated with certain diseases.12 The Chinese developed many perspectives on how to achieve and maintain health, and they deemed exercise essential for increasing strength, prolonging life, preventing and curing diseases, and minimizing the accumulation of fat.12 Quigong, Cong fou (later Kung Fu), and Tai-Chi were some of the gymnastic/movement forms developed in China sometime around 3,000 BC.12 Among the Greeks, Herodicus (circa 450 BC) was the rst to promote physical activity, and he even considered exercise a form of medicine. Nonetheless, Hippocrates is usually considered the father of exercise and medicine.13 These 2 Greeks were followed by Galen (129-210 AD)15 who was perhaps the most advanced, as he wrote not only about when to exercise, but he also described various types of exercises, identi ed qualities of exercise, speci c places to exercise, and factors to think about prior to exercise.13 Although the Physical Fitness: A Pathway to Health and ResiliencePatricia A. Deuster, PhD, MPH Marni N. Silverman, PhDABSTRACT Various groups representing a number of different perspectives (for example, operational, architectural, community, institutional, and individual resilience) use the term resilience We de ne resilience as the ability to withstand, recover, and grow in the face of stressors and changing demands. Physical tness is one pathway toward resilience because it is associated with many traits and attributes required for resilience. In addition, physical tness confers resilience because regular exercise and/or physical activity induces positive physiologic and psychological bene ts, protects against the potential consequences of stressful events, and prevents many chronic diseases. This article presents a brief historical overview of the health-promoting effects of exercise and physical activity, followed by a discussion on the concept of hardiness and mental toughness and how they relate to resilience and physical tness; how physical tness promotes resilience; the clinical implications of a sedentary lifestyle; and the relevance of physical tness and resilience to Army MedicineÂ’s Performance Triad.

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October – December 2013 25importance of exercise and physical tness diminished during various periods of time, such as after the fall of the Roman empire when the church became the dominant in uence,16 during the period of industrialization,12 and notably during the 1920s (often called the Roaring Twenties) when relaxation and enjoyment were key.12 However, the importance of exercise remains widely recognized. It is interesting to re ect on the comment of Edward Stanley, the 15th Earl of Derby, who stated in an address at Liverpool College on December 20, 1873 that:Those who think they have not time for bodily exercise will sooner or later have to nd time for illness.14It is discouraging to realize we have made little progress over the centuries. PERSONALITY TRAITS/ATTRIBUTES ASSOCIATED WITH RESILIENCE Although the term resilience, as it is used today, emerged from work on children living under conditions of deprivation,17-20 it is now applied to diverse disciplines5-7 and populations.21-24 Identifying how and why some individuals are seemingly able to bear up, and sometimes thrive, under adverse conditions with no observable negative physical or psychological outcomes, is a continuous quest.5-7,25-33 Personality traits associated with resilience include hardiness and mental toughness.9,34-46 The term hardiness, as consid ered by Kobasa et al,34,37-43 was typi ed by “interrelated orientations of commitment (vs alienation), control (vs powerlessness), and challenge (vs threat).”41 This original characterization was later re ned by Maddi,11 who proposed that hardiness is an attitude (or set of attitudes) and personality trait that helps an individual restructure stressors into growth opportunities rather than allowing them to be or become catastrophes. Bartone et al47,48 developed the dispositional hardiness scale to assess hardiness, and this scale has been used in a number of studies to relate hardiness characteristics in persons exposed to challenging occupations and experiences.45,49-52 Bonanno53 noted that hardiness is one of the pathways to resilience. Crust et al36 developed the model of mental toughness by applying the traits of hardiness to re ect the unique demands of sports and exercise; the trait of con dence was added to control, commitment, and challenge.35,36,44,46,54,55 As noted by Crust et al36:Mentally tough individuals are considered to be competitive, resilient to errors or stress, and have high selfcon dence and low anxiety.The literature clearly shows that both hardiness and mental toughness are highly related to resilience.28,56-58 In addition to the personality traits of hardiness and mental toughness, other psychological attributes and social-cognitive variables have been associated with resilience, including self-esteem, self-ef cacy and motivation.20,21,59-62 How do these closely associated traits or attributes relate to physical tness and physical activity? PERSONALITY TRAITS/ATTRIBUTES ASSOCIATED WITH PHYSICAL FITNESS Interestingly, regular physical activity and aerobic tness have been shown to be associated with speci c personality traits and psychological attributes63-72 associated with resilience. For example, anxiety and depression are inversely related to maximal aerobic capacity, a primary indicator of physical tness.73,74 Moreover, our unpublished data show a signi cant positive association between aerobic capacity and hardiness ( r =0.24), and an inverse relation with perceived stress ( r =-0.26) and trait anxiety ( r =-0.17). Of note, Skirka et al10 reported signi cantly higher hardiness scores, less perceived stress, and fewer psychological symptoms in varsity college athletes than college nonathletes, which further supports a strong association between regular exercise, aerobic tness, and hardiness. Furthermore, mental toughness, the personality trait associated with athletes and athletic competition, has been shown to mitigate the relationship between high stress and depressive symptoms.57Two determinants of physical activity, self-esteem and self-ef cacy, be they enduring traits or modi able attributes, are essential for resilience.65,66,75 Self-ef cacy generally re ects how self-con dent a person is with regard to undertaking a particular action under challenging situations,67,72,76,77 and self-esteem signi es ones sense of self-worth or personal value.68 Multiple studies have shown that children and young adults who participate in regular exercise score higher on measures of self-esteem and self-ef cacy67,70-72,76,78-80 and competitiveness81 compared to sedentary, untrained controls. Moreover, these two attributes are improved through regular physical activity.69,72 Netz et al72 conducted a meta-analysis of 36 studies examining how physical activity interventions affected well-being in healthy adults. Moderate intensity aerobic exercise was shown to be most bene cial and had a strong effect on self-ef cacy, in addition to conferring improvements in aerobic capacity and strength. Ekeland et al69 likewise conducted a systematic review of 12 studies to assess how exercise affected self-esteem in children and young people. They concluded that exercise has positive short-term effects on self-esteem and that it might be an important strategy for improving selfesteem. Interestingly, one hypothesis as to how physical activity enhances self-ef cacy and self-esteem is that it requires the application of self-management strategies (eg, thoughts, goals, plans, and acts) to achieve a goal.76

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26 http://www.cs.amedd.army.mil/amedd_journal.aspxSelf-management strategies require commitment, control, and motivation, and although each strategy is important, motivation appears to be key in terms of regular physical activity.70,78,82-85 Research has shown that motivation is very important with regard to commencing and maintaining participation in regular physical exercise.76,84 According to the literature, motivation is some force or stimulus that leads an individual to undertake a particular task or activity in which they have a speci c objective or derive personal meaning.78,82,83 Overall, these studies strongly suggest that personality traits (hardiness and mental toughness) and other attributes (self-esteem, self-ef cacy, motivation, self-management strategies) may contribute to the buffering effect of physical tness and how tness confers resilience. Further, one must be motivated to be committed, and possess self-ef cacy and self-esteem to accept a challenge. Clearly, strong relationships exist between and among hardiness or mental toughness, self-ef cacy, self-esteem, and motivation; all essential resources for resilience, and all associated with physical tness. PHYSICAL FITNESS AND STRESS RESILIENCE That physical tness is essential for health and well-being is not in question, as noted in the earlier historical overview. However, scienti c data documenting the essentiality of physical activity for health did not emerge until the late 1800s and early 1900s when epidemiological studies demonstrated that sedentary persons were more likely to have coronary heart disease than those who led active lifestyles.16,86-90 Since those rst studies, the literature has become replete with evidence that physical tness and regular exercise confer resilience and serve as a resistance resource in a variety of ways, including blunting stress reactivity in response to both physical and psychosocial stressors, conferring multiple physiologic and psychological bene ts, serving as a buffer against stress, and protecting against stress-related disorders and many chronic illnesses.57,74,78,91-95 A conceptual model of the personality traits and attributes associated with physical tness and resilience is presented in the Figure.Physical Fitness Blunts Stress Reactivity in Response to Both Physical and Psychosocial Stressors: Physiologic and Psychological BenefitsThe 2 main neuroendocrine/neural systems that mediate the stress response are the hypothalamic-pituitaryadrenal axis, with the resultant release of cortisol, and the sympathetic nervous system, which releases the catecholamines epinephrine (adrenaline) and norepinephrine. Activation of these stress systems mediates the ght or ight response, which entails the rapid mobilization of energy from storage sites to critical muscles and the brain (getting one ready for action, increasing alertness/arousal). Moreover, increased heart rate, blood pressure, and breathing rate facilitate the rapid transport of nutrients and oxygen to relevant parts of the body. Together, these stress systems orchestrate the physiologic and behavioral adaptations to stress. However, chronic activation can lead to dysregulation of multiple physiologic and behavioral systems, leading to maladaptive stress responses, including anxiety and depression.96,97Physical tness and aerobic tness have been related to a reduction in stress reactivity, physiologically and psychologically, for both physical and mental/psychosocial stress.65,98-107Interestingly, neuroendocrine and physiologic responses to exercise at the same absolute workload are signi cantly lower in physically t than un t persons.108-111 Additionally, physically active people show reduced sympathoadrenal reactivity to physical stressors.109,110 When untrained persons are enrolled in a regular exercise program for 8-12 weeks, their response to the same physical stress prior to beginning exercise training is signi cantly higher than after the training.112 Thus, when trained and untrained persons have to work at the same rate, the untrained person will experience signi cantly more stress than someone who is physically t and aerobically trained.108-110 Therefore, the higher the level of aerobic tness, the greater the ability to tolerate high workloads and be minimally stressed by low ones. Physical training also appears to confer protection against nonphysical stressors, mental and/or psychological.98,111,113,114 Rimelle et al115 documented signi cantly lower cortisol and heart rate responses to psychosocial PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE A conceptual model of the personality traits and attributes associated with physical tness and resilience and how physical tness confers resilience. Physical tness confers resilience because regular exercise/physical activity can protect against the potential consequences of stressful events and prevent many chronic and stress-related diseases/disorders. CVD indicates cardiovascular disease. Sedentary Low self-esteem Low self-ef cacy Anxious Depressed Lethargic Unsure/uncertain Timid Physically Un t (Aerobically un t / fat) Vulnerable Physically Fit (Aerobically t / lean) Resilient Physically active High self-esteem High self-ef cacy Motivated Hardy/mentally tough Committed Con dent Chronic / Stress-related Disorders anxiety, depression, cognitive dysfunction, pain and fatigue disorders, sleep disorders, obesity, CVD, metabolic syndrome, type 2 diabetes, osteoporosis, autoimmune disease, cancer Physical/Mental Resilience (-) (-) (-)

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October – December 2013 27THE ARMY MEDICAL DEPARTMENT JOURNAL stress in trained men compared to untrained men. Moreover, signi cantly greater calmness and better mood, and a trend toward lower state anxiety were noted in the trained relative to untrained men. In addition, others have noted blunted cortisol responses115 and reduced cardiovascular responses98,99,115 to psychological laboratory stressors in physically active as compared to less active persons. Webb et al111 administered a dual challenge of physical and mental stress and noted that low t participants had greater cortisol responses compared to high t individuals. Importantly, in a meta-review of 34 studies, Crews et al99 reported that aerobically t individuals had reduced responses to psychosocial stress in comparison to controls. These ndings are consistent with those from the Aerobics Center Longitudinal Study, which found a signi cant inverse dose-response relationship between aerobic tness and depressive symptomatology and a positive association between tness and emotional well-being.116In addition to cross-sectional studies, longitudinal studies have demonstrated positive effects of exercise training and regular physical activity, and negative effects of exercise withdrawal on mood and depressive symptoms.68,117-121 Nabkasorn et al117 studied adolescent females with depressive symptoms and noted signi cant decreases in total depressive score, as well as in 24-hour urinary cortisol and epinephrine excretion, following 8 weeks of physical training (jogging). Importantly, studies by Berlin et al118 and Weinstein et al121 demonstrated that when someone who exercises regularly is forced to withdraw from exercise for 2 weeks, negative mood increases signi cantly and correlates with decreases in tness.118,121 In addition, a reduction in parasympathetic nervous system activity, as measured by heart rate variability, predicted the development of negative mood after deprivation of exercise.121 These ndings are relevant to understanding both short-term exercise withdrawal and exercise initiation, and how they affect overall stress resilience and reactivity. Despite the multiple positive ndings, not all are consistent,65,122,123 particularly with regard to catecholamine release, with both blunted and augmented responses noted in highversus low t persons.112,123 Along those same lines, de Geus et al65 were unable to detect changes in psychological make-up (for example, personality traits of neuroticism, introversion, hostility, anger expression) or acute neurophysiologic reactivity (for example, heart rate, blood pressure, urinary catecholamine excretion, or cardiac beta-adrenergic drive) after 4 and 8 months of training. Thus, although the majority of studies support positive effects of regular exercise and aerobic tness, not all studies are consistent.Physical Fitness Serves as a Buffer against Stress and Stress-Related DisordersPhysical activity may provide a protective effect against stress-related disorders, as physically t persons appear to be less susceptible to life stressors, in particular with regard to illnesses: physical tness may serve as a buffer against stress,63,124,125 with stress being highly associated with various illnesses.20,34,73,124,126,127 A comprehensive review of the literature from 1982 to 2008 in which exercise was examined as a stress-buffer concluded that the majority of studies, both cross-sectional and prospective, found exercise to be an effective buffer, but the amount and type of exercise necessary for protection were not stated.93 The concept of stress buffering was rst proposed by Kobasa et al,34 and later by others9,11 who clearly showed that regular exercise and hardiness interact to decrease illness in the face of serious life stressors.34 Persons who scored high in hardiness and participated in regular exercise were usually more healthy than those high only in hardiness or exercise alone.34 Collectively, the data suggest that participation in leisure physical activity is important to the stress-buffering effect of exercise.128Physical tness and regular exercise also appear to buffer against depression 63,68,125,129-134 and anxiety.100,125,134-136 In fact, the bene cial effects of physical activity on positive mood are well recognized.83,137 Rethorst et al131 conducted a meta-analysis of all studies investigating the effects of exercise on depression, and 12 of 16 exercise treatment groups with clinically depressed patients were classi ed as “recovered” or “improved” after the treatment. Similarly, a number of prospective studies have demonstrated reductions in state anxiety.129,138 Manger et al129 had persons diagnosed with posttraumatic stress disorder (PTSD) undergo a 12-session aerobic exercise program and showed signi cant reductions in PTSD, anxiety, and depression following the intervention. Moreover, these positive results were stable over 1 month of follow-up.129 Finally, Wip i et al135 conducted a meta-analysis (based on 49 randomized, controlled trials) examining the effects of exercise on anxiety, and demonstrated clear reductions in anxiety among those who exercised compared to the respective control groups. Of interest was their nding that exercise was more effective in reducing anxiety relative to other anxiety-reducing treatments.135CLINICAL IMPLICATIONS OF A SEDENTARY LIFESTYLE The shortand long-term consequences of low physical tness and a sedentary lifestyle are clear. Physical inactivity serves a major role in the rising prevalence of obesity, cardiovascular disease (CVD), hypertension, type II diabetes mellitus (T2DM), metabolic syndrome, insulin resistance, hyperlipidemia, and breast and colon cancers,

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28 http://www.cs.amedd.army.mil/amedd_journal.aspxto name a few.91,94,95,116,139,140 Of course, excess energy intake also contributes to obesity,78,94,95, but lack of physical activity is the leading contributor91,94,95,116,139,140 and also the fourth leading cause of death worldwide.95 In contrast to a sedentary lifestyle, high aerobic tness is inversely related to obesity, metabolic syndrome, CVD, hypertension, and T2DM.74,141-145In addition to the major chronic diseases mentioned above, low aerobic tness has been associated with bromyalgia (FM),146,147 chronic fatigue syndrome (CFS),148,149 osteoarthritis,150-152 rheumatoid arthritis,150,153,154 and in ammatory muscle disorders.155,156 Low aerobic tness is also associated with elevations in serum C-reactive protein (CRP), a well-known marker of in ammation. Many studies have shown that maximal aerobic capacity is inversely related to CRP,142,157 and that exercise interventions, both aerobic and resistance in nature, reduce levels of CRP.157-159 However, not all studies showed a signi cant effect.160-162 A meta-analytic study by Kelley et al162 of 5 randomized controlled trials reported an approximately 3% reduction in CRP levels across the exercise groups, which was not signi cant. However, the studies that were negative found other positive bene ts of exercise, regardless of its effect on CRP. With regard to FM, exercise as an intervention has been shown to be bene cial, particularly in relation to pain management. Ellingson et al147 conducted a prospective study and emphasized how a sedentary lifestyle was likely deleterious for pain regulation in FM. Likewise, Curtis et al163 conducted a study wherein women with FM who engaged in a 75-minute yoga class twice weekly for 8 weeks reported reduced pain and catastrophizing, and increased acceptance of pain. Chronic fatigue syndrome is another debilitating disorder characterized by minimal physical activity during daily life and lower muscle strength and aerobic capacity compared to healthy sedentary subjects.149,154 As with FM, when persons with CFS are entered into a regular exercise program, signi cant bene ts in terms of physical capacity, quality of life, fatigue severity, and depressive symptomatology are reported.164,165 Interestingly, Heins et al166 reported that physical activity is intentionally limited in CFS patients, possibly because they expect negative bodily symptoms and catastrophize in such a way as to negatively affect their performance. This underscores the importance of the exercise-derived resilience resources self-ef cacy, self-esteem, and motivation, which, unfortunately, were not measured in the above studies. Overall, the clinical implications of a sedentary, physically inactive lifestyle are profound, and the literature clearly demonstrates that having a valid measure of physical tness, in particular aerobic tness, may be one of the best indicators of resilience, as well as longterm health and risk of chronic diseases. Most of the above mentioned chronic diseases/disorders are also associated with depression, anxiety, low self-ef cacy, and other barriers to critical resilience resources. Promoting regular physical activity in these populations has been shown to exert profound bene cial changes, and should be the key intervention for all such populations who are able to engage in regular physical activity. LIMITATIONS AND FUTURE DIRECTIONS Limitations of studies examining how physical tness contributes to resilience must be acknowledged. First, many studies examining reactivity to both physical and psychosocial stress did not quantify aerobic tness or regular physical activity. This is essential for being able to accurately interpret the results, as they may be important confounders. Secondly, the intimate relation between hardiness/mental toughness, and aerobic capacity/physical activity must be further evaluated to document their interrelationship. Certainly, the mental toughness model was speci cally developed for athletes who are physically t and have self-con dence, so one would expect them to have many resilience resources. However, what happens when they become injured? In addition, many people with chronic diseases are able to cope and are physically un t (they may be unable to engage in regular exercise), so physical tness is important, but not an absolute.23,24CONCLUSIONS Physical tness is associated with many traits and attributes required for resilience. As such, it is one pathway toward resilience. Promoting physical tness as a pathway to resilience is based on solid, scienti c evidence as noted in many ancient and current sources showing that physical tness blunts stress reactivity, confers physiologic and psychological bene ts, serves as a buffer against stress, and can protect against stress-related disorders and chronic illness. Perhaps the role of physical tness as a pathway to resilience was most eloquently stated by then President-Elect John F. Kennedy in 1960 when he said:Â…physical tness is not only one of the most important keys to a healthy body; it is the basis of dynamic and creative intellectual activity. Â…intelligence and skill can only function at the peak of their capacity when the body is healthy and strong; hardy spirits and tough minds usually inhabit sound bodies.1RELEVANCE TO THE PERFORMANCE TRIAD Physical activity is a key component of the Performance Triad and is clearly essential to optimal performance. PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE

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October – December 2013 29THE ARMY MEDICAL DEPARTMENT JOURNAL However, physical activity in the absence of adequate fueling (ie, healthy dietary patterns, appropriate timing and types of nutrients) and an adequate quantity and quality of sleep and recovery is not the solution. Excessive activity can lead to overtraining, musculoskeletal injuries, and similar problems. Only when physical activity is balanced with a healthy diet and restorative sleep will the bene ts described above be realized. ACKNOWLEDGMENTSThis research was supported by a grant from Comprehensive Soldier and Family Fitness (CSF2; HT9404-12-1-0017; F191GJ). We appreciate the support in preparation and review of this article by LTC Sharon A. McBride, MS, USA.REFERENCES1. Kennedy JF. The soft American. Sports Illustrated 1960;13(26):14-17. Available at: http:// sportsillustrated.cnn.com/vault/article/magazine/ MAG1134750/2/. Accessed August 15, 2013. 2. CJCS Instruction 3405.01: Chairman’s Total Force Fitness Framework Washington, DC: Of ce of the Chairman, Joint Chiefs of Staff; 2011. Available at: http://www.dtic.mil/cjcs_directives/cdata/unlim it/3405_01.pdf. Accessed July 24, 2013. 3. Baker DG, Nash WP, Litz BT, et al. Predictors of risk and resilience for posttraumatic stress disorder among ground combat Marines: methods of the Marine Resiliency Study. Prev Chronic Dis 2012;9:E97. 4. Meredith LS, Sherbourne CD, Gaillot S, et al. Psychological Resilience in the U.S. Military. Santa Monica, CA 90407-2138: Rand Corporation;2011. 5. Perna L, Mielck A, Lacruz ME, et al. Socioeconomic position, resilience, and health behaviour among elderly people. Int J Public Health 2012;57(2):341-349. 6. Skrove M, Romundstad P, Indredavik MS. Resilience, lifestyle and symptoms of anxiety and depression in adolescence: the Young-HUNT study. Soc Psychiatry and Psychiatr Epidemiol 8 2012. 7. Wells M, Avers D, Brooks G. Resilience, physical performance measures, and self-perceived physical and mental health in older Catholic nuns. J Geriatr Physical Ther Jul-2012;35(3):126-131. 8. Acevedo EO, Webb HE, Weldy ML, Fabianke EC, Orndorff GR, Starks MA. Cardiorespiratory responses of Hi Fit and Low Fit subjects to mental challenge during exercise. Int J Sports Med 2006;27(12):1013-1022. 9. Roth DL, Wiebe DJ, Fillingim RB, Shay KA. Life events, tness, hardiness, and health: a simultaneous analysis of proposed stress-resistance effects. J Pers Soc Psychol 1989;57(1):136-142. 10. Skirka N. The relationship of hardiness, sense of coherence, sports participation, and gender to perceived stress and psychological symptoms among college students. J Sports Med Phys Fitness 2000;40(1):63-70. 11. Maddi SR. On hardiness and other pathways to resilience. Am Psychol 2005;60(3):261-262; discussion 265-267. 12. Dalleck LC, Kravitz L. The history of tness. IDEA Health and Fitness Source 2002;20(2):26-33. 13. Berryman JW. Exercise is medicine: a historical perspective. Curr Sports Med Reports Jul-2010;9(4):195-201. 14. Fletcher GF. The history of exercise in the practice of medicine. J Med Assoc Georgia 1983;72(1):35-40. 15. Berryman JW. The tradition of the “six things nonnatural”: exercise and medicine from Hippocrates through ante-bellum America. Exerc Sport Sci Rev 1989;17:515-559. 16. MacAuley D. A history of physical activity, health and medicine. J R Soc Med 1994;87(1):32-35. 17. Herrman H, Stewart DE, Diaz-Granados N, Berger EL, Jackson B, Yuen T. What is resilience? Can J Psychiatry. Revue canadienne de psychiatrie 2011;56(5):258-265.18. Seligman ME. Building resilience. Harv Bus Rev 2011;89(4):100-106, 138. 19. Ong AD, Bergeman CS, Boker SM. Resilience comes of age: de ning features in later adulthood. J Pers 2009;77(6):1777-1804. 20. Yi JP, Vitaliano PP, Smith RE, Yi JC, Weinger K. The role of resilience on psychological adjustment and physical health in patients with diabetes. Br J Health Psychol 2008;13(Pt 2):311-325. 21. Howe A, Smajdor A, Stockl A. Towards an understanding of resilience and its relevance to medical training. Med Educ 2012;46(4):349-356. 22. Mertens VC, Bosma H, Groffen DA, van Eijk JT. Good friends, high income or resilience? What matters most for elderly patients? Eur J Public Health 2012;22(5):666-671. 23. Robottom BJ, Gruber-Baldini AL, Anderson KE, et al. What determines resilience in patients with Parkinson’s disease? Parkinsonism Relat Disord 2012;18(2):174-177. 24. West C, Stewart L, Foster K, Usher K. The meaning of resilience to persons living with chronic pain: an interpretive qualitative inquiry. J Clin Nurs 2012;21(9-10):1284-1292. 25. Jeffcott SA, Ibrahim JE, Cameron PA. Resilience in healthcare and clinical handover. Qual Saf Health Care 2009;18(4):256-260.

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34 http://www.cs.amedd.army.mil/amedd_journal.aspx141. Zeno SA, Deuster PA, Davis JL, Kim-Dorner SJ, Remaley AT, Poth M. Diagnostic criteria for metabolic syndrome: caucasians versus African-Americans. Metab Syndr Relat Disord 2010;8(2):149-156. 142. Zeno SA, Kim-Dorner SJ, Deuster PA, Davis JL, Remaley AT, Poth M. Cardiovascular tness and risk factors of healthy African Americans and caucasians. J Natl Med Assoc 2010;102(1):28-35. 143. Kuo LE, Abe K, Zukowska Z. Stress, NPY and vascular remodeling: implications for stress-related diseases. Peptides 2007;28(2):435-440. 144. Kim-Dorner SJ, Simpson-McKenzie CO, Poth M, Deuster PA. Psychological and physiological correlates of insulin resistance at fasting and in response to a meal in African Americans and whites. Ethn Dis 2009;19(2):104-110. 145. Kim-Dorner SJ, Deuster PA, Zeno SA, Remaley AT, Poth M. Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be used as surrogates for insulin resistance?. Metabolism 2010;59(2):299-304. 146. McLoughlin MJ, Stegner AJ, Cook DB. The relationship between physical activity and brain responses to pain in bromyalgia. J Pain 2011;12(6):640-651. 147. Ellingson LD, Shields MR, Stegner AJ, Cook DB. Physical activity, sustained sedentary behavior, and pain modulation in women with bromyalgia. J Pain 2012;13(2):195-206. 148. Puetz TW, Flowers SS, OÂ’Connor PJ. A randomized controlled trial of the effect of aerobic exercise training on feelings of energy and fatigue in sedentary young adults with persistent fatigue. Psychother Psychosom 2008;77(3):167-174. 149. Nijs J, Aelbrecht S, Meeus M, Van Oosterwijck J, Zinzen E, Clarys P. Tired of being inactive: a systematic literature review of physical activity, physiological exercise capacity and muscle strength in patients with chronic fatigue syndrome. Disabil Rehabil 2011;33(17-18):1493-1500. 150. Gualano B, Pinto AL, Perondi MB, et al. Therapeutic effects of exercise training in patients with pediatric rheumatic diseases. Rev Bra Reumatol 2011;51(5):490-496. 151. Semanik PA, Chang RW, Dunlop DD. Aerobic activity in prevention and symptom control of osteoarthritis. PM R 2012;4(suppl 5):S37-S44. 152. Stevenson JD, Roach R. The bene ts and barriers to physical activity and lifestyle interventions for osteoarthritis affecting the adult knee. J Orthop Surg Res 2012;7:15. 153. Baillet A, Zeboulon N, Gossec L, et al. Ef cacy of cardiorespiratory aerobic exercise in rheumatoid arthritis: meta-analysis of randomized controlled trials. Arthritis Care Res 2010;62(7):984-992. 154. Weinstein AA, Drinkard BM, Diao G, et al. Exploratory analysis of the relationships between aerobic capacity and self-reported fatigue in patients with rheumatoid arthritis, polymyositis, and chronic fatigue syndrome. PM R 2009;1(7):620-628. 155. Lundberg IE, Nader GA. Molecular effects of exercise in patients with in ammatory rheumatic disease. Nature Clin Pract Rheumatol. 2008;4(11):597-604. 156. Nader GA, Lundberg IE. Exercise as an antiin ammatory intervention to combat in ammatory diseases of muscle. Curr Opin Rheumatol 2009;21(6):599-603. 157. Thomson RL, Buckley JD, Moran LJ, et al. Comparison of aerobic exercise capacity and muscle strength in overweight women with and without polycystic ovary syndrome. BJOG 2009;116(9):1242-1250. 158. Arikawa AY, Thomas W, Schmitz KH, Kurzer MS. Sixteen weeks of exercise reduces C-reactive protein levels in young women. Med Sci Sports Exerc 2011;43(6):1002-1009. 159. Martins RA, Neves AP, Coelho-Silva MJ, Verissimo MT, Teixeira AM. The effect of aerobic versus strength-based training on high-sensitivity Creactive protein in older adults. Eur J Appl Physiol 2010;110(1):161-169. 160. Wong PC, Chia MY, Tsou IY, et al. Effects of a 12-week exercise training programme on aerobic tness, body composition, blood lipids and C-reactive protein in adolescents with obesity. Ann Acad Med Singapore 2008;37(4):286-293. 161. Stewart LK, Earnest CP, Blair SN, Church TS. Effects of different doses of physical activity on Creactive protein among women. Med Sci Sports Exerc 2010;42(4):701-707. 162. Kelley GA, Kelley KS. Effects of aerobic exercise on C-reactive protein, body composition, and maximum oxygen consumption in adults: a meta-analysis of randomized controlled trials. Metabolism 2006;55(11):1500-1507. 163. Curtis K, Osadchuk A, Katz J. An eight-week yoga intervention is associated with improvements in pain, psychological functioning and mindfulness, and changes in cortisol levels in women with bromyalgia. J Pain Res 2011;4:189-201. 164. Edmonds M, McGuire H, Price J. Exercise therapy for chronic fatigue syndrome. Cochrane Database Syst Rev [serial online]. 2004(3):CD003200. 165. Gordon BA, Knapman LM, Lubitz L. Graduated exercise training and progressive resistance training in adolescents with chronic fatigue syndrome: a randomized controlled pilot study. Clin Rehabil 2010;24(12):1072-1079.PHYSICAL FITNESS: A PATHWAY TO HEALTH AND RESILIENCE

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October – December 2013 35THE ARMY MEDICAL DEPARTMENT JOURNAL 166. Heins M, Knoop H, Nijs J, et al. In uence of symptom expectancies on stair-climbing performance in chronic fatigue syndrome: effect of study context. Int J Behav Med 2013;20(2):213-218.AUTHORSDr Deuster is Director and Professor, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr Silverman is Senior Scientist, Human Performance Laboratory, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

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36 http://www.cs.amedd.army.mil/amedd_journal.aspxSoldiers must maintain high levels of physical tness to endure demanding tasks, harsh deployment environments and military occupational specialty requirements. However, routine training required to maintain high levels of physical tness can result in musculoskeletal injuries, limited duty days, and signi cant health care costs.1-3 Studies have shown that injuries related to physical training (PT) account for 30% to 50% of all injuries in US Army Soldiers.4-6 An investigation examining injury incidence in light infantry Soldiers found that physical training caused 50% of all injuries, and 30% of these injuries were associated with running.4 Injuries caused approximately 10 times the number of limited duty days compared to illness. The investigators concluded that physical training is associated with a high number of injuries in infantry Soldiers.4 It has also been Extreme Conditioning Programs and Injury Risk in a US Army Brigade Combat TeamTyson Grier, MS Michelle Canham-Chervak, PhD Vancil McNulty, DPT Bruce H. Jones, MD, MPHABSTRACTContext: Brigades and battalions throughout the US Army are currently implementing a variety of exercise and conditioning programs with greater focus on preparation for mission-speci c tasks. An Army physical therapy clinic working with a light infantry brigade developed the Advanced Tactical Athlete Conditioning (ATAC) program. The ATAC program is a unique physical training program consisting of high-intensity aquatic exercises, tactical agility circuits, combat core conditioning, and interval speed training. Along with ATAC, battalions have also incorporated components of tness programs such as the Ranger Athlete Warrior program and CrossFit (Cross t, Inc, Santa Monica, CA) an extreme conditioning program (ECP).Objective: To determine if these new programs (ATAC, ECP) had an effect on injury rates and physical tness.Design: Surveys were administered to collect personal characteristics, tobacco use, personal physical tness training, Army physical tness test results, and self-reported injuries. Medical record injury data were obtained 6 months before and 6 months after the implementation of the new program. Predictors of injury risk were assessed using multivariate logistic regression. Odds ratios (OR) and 95% con dence intervals (CI) were reported.Results: Injury incidence among Soldiers increased 12% for overall injuries and 16% for overuse injuries after the implementation of the ATAC/ECPs. However, injury incidence among Soldiers not participating in ATAC/ECPs also increased 14% for overall injuries and 10% for overuse injuries. Risk factors associated with higher injury risk for Soldiers participating in ATAC/ECPs included: greater mileage run per week during unit physical training (OR (>16 miles per week 7 miles per week)=2.24, 95% CI, 1.33-3.80) higher body mass index (BMI) (OR (BMI 25-29.9BMI<25)=1.77, 95% CI, 1.29-2.44), (OR (BMI 30BMI<25)=2.72, 95% CI, 1.67-4.43) cigarette use (OR (smokernonsmoker)=1.80, 95% CI, 1.34-2.42) poor performance on the 2-mile run during the Army Physical Fitness Test (APFT) (OR ( 15.51 minutes 13.52 minutes)=1.76, 95% CI, 1.13-2.74) Injury risk was lower for those reporting resistance training (OR (<1 time per weeknone)=0.53, 95% CI, 0.31-0.92) (OR (1-2 times per weeknone)=0.50, 95% CI, 0.29-0.84) (OR ( 3 times per weeknone)=0.45, 95% CI, 0.24-0.85)Conclusions: Given that Soldiers participating in ATAC/ECPs showed similar changes in injury rates compared to Soldiers not participating in ATAC/ECPs, no recommendation can be made for or against implementation of ATAC/ECPs.

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October – December 2013 37shown that musculoskeletal injuries are a leading cause of hospitalization.7 In a study investigating hospitalizations for sports and Army physical training injuries, 11% of 120,430 hospital admissions over a 6-year period were attributed to sports or Army physical training injuries. This resulted in 29,435 total lost duty days, with an average of 13 days of limited duty per injury for male Soldiers and 11 days per injury for female Soldiers.3 These investigations indicate that physical training-related injuries have a considerable impact on the health and readiness of Soldiers. Previous research has identi ed a number of risk factors for injury in infantry Soldiers. In one study, higher risk of injury was associated with fewer sit-ups on the Army Physical Fitness Test (APFT) and slower 2-mile run times,8 while another study showed higher risk of injury was associated with smoking and a body mass index (BMI) of 25 or more.9 In an investigation of British infantry Soldiers, higher risk of injury was associated with younger age, previous lower limb injury, and previous back injury.10 More work to identify the most important risk factors among infantry Soldiers is needed. Only a few investigations have explored injury risk during the implementation of a new military tness program.11-15 In 3 investigations, Knapik et al compared Soldiers performing Army Physical Readiness Training (PRT) to Soldiers performing traditional Army physical training. Physical readiness training consists of calisthenics, movement drills, climbing drills, dumbbell exercises, interval training, and ability group long-distance running whereas traditional Army physical training consists primarily of warm-up and stretching exercises followed by calisthenics, push-ups, sit-ups, some sprint training, and group long-distance running. For all 3 studies, the adjusted risk of injury was 1.5 to 1.8 times higher in the groups performing traditional physical training compared to those performing PRT. It was also found that scores on the APFT were higher or similar for groups using the PRT program. Knapik et al concluded that the PRT program results in fewer injuries and equal or greater improvements in tness and military performance compared to traditional Army physical training.11-13,16In a US Air Force study, a new PT program implemented within the combat controller training pipeline was evaluated. The goal of this new PT program was to reduce overuse and overtraining injuries and transition from a traditional PT program to a functional PT program. For the new PT program, running mileage decreased by 50%, and long-distance runs were replaced with interval running and agility training. In addition, bodybuilding type resistance training (single joint) was replaced with functional strength training movements (multiple joint, standing exercises), and an athletic trainer was hired to visit the group twice per week. Investigators found that by replacing traditional training with the new functional training program, overall injuries decreased by 67%, and improvements were made in body composition, aerobic capacity, ventilatory threshold, upper body power, and graduation rates. The authors concluded that the new tness program decreased injury rates, increased tness performance and graduation rates, and suggested that other combat athletes would bene t from adopting these practices.14A variety of exercise and conditioning programs with greater focus on preparation for mission-speci c tasks are currently being implemented by various brigades and battalions throughout the US Army. As a result, Soldiers are transitioning from traditional Army PT to a more intensive, combat-focused PT program. Injury rates and risk factors associated with these programs are not well known. The purpose of this project was to examine physical training, tness, and injury rates, and to identify injury risk factors in a light infantry brigade beginning a new PT program incorporating elements of extreme conditioning programs (ECPs). METHODPopulationThe population consisted of Soldiers in a light infantry brigade combat team (N=1,393). The brigade combat team consisted of 2 infantry battalions, a cavalry battalion, a eld artillery battalion, a brigade support battalion (hereinafter referred to as Infantry A, Infantry B, Cavalry, Field Artillery, and Brigade Support), and a brigade special troops battalion. Rosters of unit members were requested and obtained through the brigade medical of cer. Roster information included each Soldier’s battalion.SurveysA survey was used to collect information from Soldiers about personal characteristics, tobacco use, unit and personal physical tness training, Army physical tness test results, and injuries. The survey was administered in September 2010, approximately 4 months after the new physical tness and conditioning programs began.InterviewsBattalion commanders were interviewed to obtain their views and opinions on physical training and tness. They were also asked about training equipment and injury prevention.

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38 http://www.cs.amedd.army.mil/amedd_journal.aspxExercise Instructor Certification and Programs Conducted by the Brigade Combat TeamSelected Soldiers from every battalion in the brigade combat team attended a 1-week certi cation class on the fundamentals of the Advanced Tactical Athlete Conditioning (ATAC) program. The ATAC Program consisted of workouts employing plyometrics, kettlebells, medicine balls, high-intensity water exercises, wrestling, ladder and cone agility drills, tire ipping, speed interval training, and cinderblock throwing. Some of the battalions also required their Soldiers to attend additional certi cation classes in exercise and tness performance involving other exercise programs such as CrossFit (CrossFit Inc, Washington, DC) and the Ranger Athlete Warrior program (RAW), developed within the US Army’s 25th Infantry Division. CrossFit is a core strength and conditioning program that aims to prepare athletes for any physical contingency. CrossFit consists of continuously varied, highintensity functional movements that generally fall into 3 categories: gymnastics, Olympic weightlifting, and metabolic conditioning or “cardio.”* There are 4 components to the RAW program: functional tness, performance nutrition, sports medicine, and mental toughness. The functional tness component of RAW consists of movement drills (before each PT session), muscular endurance workouts, heavy resistance workouts, power and power endurance workouts, endurance training workouts, movement skills training, hybrid drills, and recovery exercises (at the end of each workout).†CrossFit and RAW or parts of these exercise programs can also be classi ed as ECPs,17 which are characterized by high-volume, aggressive exercise workouts with a variety of high-intensity exercise repetitions and short rest periods between sets. Popular ECPs include P90X and Insanity (Beachbody LLC, Santa Monica, CA), and Gym Jones (Gym Jones LLC, Salt Lake City, UT).New Physical Training ProgramSoldiers began a new physical training program that incorporated ATAC and components of tness programs such as the RAW program and CrossFit.Army Physical Fitness Test ScoresThe APFT was used as a measure of physical tness. Self-reported scores from each Soldier’s most recent APFT were obtained from the surveys. Close correlations have been found between actual APFT scores and self-reported APFT scores.18 The APFT consisted of 3 events: a 2-minute maximal effort push-up event, a 2-minute maximal effort sit-up event, and a 2-mile run performed for time. Events were performed in accordance with instructions contained in F ield Manual 7-22: Army Physical Readiness Training.19 Performance metrics obtained included the number of push-ups and sit-ups successfully completed within separate 2-minute time periods. The performance measure for the run was the time taken to complete a 2-mile distance.Demographics and Injury Outcome MeasuresThe Armed Forces Health Surveillance Center (AFHSC) provided demographic data obtained from the Defense Manpower Data Center (DMDC). Demographics included date of birth, education level, marital status, race, and gender. Data on injuries treated in military treatment facilities or paid for by the Military Health System (purchased care) were obtained from the Defense Medical Surveillance System (DMSS). A brigade unit roster was provided to the AFHSC, which returned DMSS data containing visit dates and International Classi cation of Disease 9th Revision (ICD-9)‡ diagnosis codes for all inpatient and outpatient medical encounters captured electronically by the DMSS occurring between November 1, 2009 and October 28, 2010. Injuries were categorized into 3 groups—overall injury, overuse injuries, and traumatic injuries—using the primary ( rst) ICD-9 diagnosis code in a manner consistent with prior studies of military training injuries.20,21Overall injuries comprise all ICD-9 codes from the 800999 and 710-739 code series related to acute and chronic musculoskeletal injuries, including environmental injuries. Overuse injuries contain a subset of musculoskeletal injuries resulting from cumulative microtrauma due to repetitive motion, typically in the 710-739 ICD9 code series. This series indicates such diagnoses as stress fractures, stress reactions, tendonitis, bursitis, fasciitis, shin splints, and musculoskeletal pain (not otherwise speci ed). Traumatic injuries contain a subset of musculoskeletal injuries resulting from a strong sudden force or forces being applied to the body, including events such as a fall from a ladder, an automobile crash, or being struck by a bullet. These injuries are contained in the 800-999 ICD-9 code series.Data AnalysisThe IBM SPSS Statistics (V 18.0) application (IBM Corp, Chicago, IL) was used for statistical analysis. *CrossFit Forging Elite Fitness – http://www.cross t.com/cf-info/ what-cross t.html † RAW PT Program Manual – http://www.25idl.army.mil/pt/rawpt guide_bp.pdf ‡ http://www.cdc.gov/nchs/icd/icd9.htmEXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM

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October – December 2013 39THE ARMY MEDICAL DEPARTMENT JOURNAL Descriptive statistics (frequencies, distributions, means, SDs) were calculated for personal characteristics, physical training, and physical tness. Body mass index was calculated as weight in kilograms divided by height in meters squared (kg/m). The BMI was categorized according to the Centers for Disease Control and Prevention (CDC) classi cations for normal, overweight, and obese.22 Current cigarette smokers were identi ed as smoking at least 1 cigarette within the last 30 days, and smoking 100 or more cigarettes in their lifetime. To assess changes in injury rates preand postimplementation of the physical training programs, the McNemar test was used to compare injury incidence among Soldiers in the 6 months before the new programs were initiated (November 2009 to April 2010) with injury incidence in the 6 months following full implementation of the program (May 2010 to October 2010) for the overall, overuse, and traumatic injury categories. For each of the 2 periods, injury risk (percentage) for each category was calculated as: To investigate potential injury risk factors among Soldiers in the brigade, injury risk ratio and 95% CI, were calculated using the electronic medical record data on overall injuries occurring after the implementation of the new exercise programs. Potential injury risk factors included demographic characteristics obtained from AFHSC as well as health behavior, physical training, and physical tness data collected by survey. A backward-stepping multivariate logistic regression and a forced multivariate logistic regression model were used to assess key factors for association with injury risk in this population. Odds ratios and 95% CIs were calculated for each potential risk factor (independent variables). RESULTS The average age of Soldiers in the brigade was 26.85.9 years with a range of 18 to 52 years. A majority of the Soldiers were classi ed as overweight or obese (61%), white (62%), rank of E4 to E6 (61%), high school graduates (82%), and married (55%). The descriptive statistics are presented in Table 1. Due to the small number of Soldiers who participated in the ATAC program (n=87), the ATAC and ECP groups were combined in further analyses, comparing Soldiers who participated in ATAC/ ECPs with Soldiers who did not report participating in those programs. Using injuries recorded in the medical records, injury rates of Soldiers in units participating in ATAC/ECPs were compared to injury rates for Soldiers in units that did not participate. A total of 1,032 Soldiers reported that their units were participating in ATAC/ ECPs, while the other 340 Soldiers did not report participation. Soldiers were either exercising on their own time or were performing traditional PT. The baseline overall injury rates for Soldiers participating in ATAC/ ECPs and Soldiers who did not participate were 41% and 50%, respectively, as shown in Tables 2 and 3. After full implementation of the ATAC/ECPs, injury incidence increased by 12% and 16% for overall injuries number of Soldiers with 1 or more injuries total number of Soldiers 100% Table 1. Descriptive Statistics for Men and Women in the Light Infantry Brigade.VariableSubcategory of Variable MenM=1,248WomenW=145Men and WomenN=1,393n%Mn%Wn%N Gender Men1,24890% Women14510% Age <2337430%4632%42030% 23-2533327%4028%37327% 26-2925821%2819%28621% 30+28323%3121%31423% Body mass index 25 (normal)45037%8560%53540% 25-29 (overweight)59349%4935%64248% 30+ (obese)16113%75%16813% Rank E1-E333127%4430%37527% E4-E676962%8659%85561% E7-E9675%53%725% W1-W250.4%10.7%60.4% O1-O3726%96%816% O4-O640.3%00%40.3% Race White80364%6142%86462% Black18615%5337%23917% Hispanic13811%1510%15311% American Indian91%21%111% Asian1008%139%1138% Unknown121%11%131% Education Level No High School60.5%00%60.4% High School1,02182%11479%1,13582% Some College887%128%1007% Bachelor’s 988%1611%1148% Master’s 50.4%21%70.5% Unknown302%11%312% Marital Status Married69055%7652%76655% Single50641%5337%55940% Other524%1611%685% Battalion Infantry A44536%1510%46033% Infantry B15012%00%15011% Cavalry18515%118%19614% Field artillery20116%118%21215% Brigade support battalion 13511%7250%20715% Brigade special troops battalion 13211%3625%16812%

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40 http://www.cs.amedd.army.mil/amedd_journal.aspxand overuse injuries, respectively, for Soldiers who participated (Table 2). Injury incidence for Soldiers who did not participate increased by 14% for overall injuries and 10% for overuse injuries (Table 3). The absolute percentage change in overall injury incidence for the ATAC/ ECPs and no-ATAC/ECPs groups was an increase of 5% and 7%, respectively (Tables 2 and 3).Risk Factors for Men Participating in ATAC/ECPsTables 4 and 5 display the injury risk ratio variables for factors possibly associated with risk of injury. Since there were only 82 women participating in ATAC/ ECPs, the following analysis excluded women, except for initial comparisons of risk by gender. The number of responses may slightly vary between questions due to missing answers on some of the surveys. Higher risk of injury was associated with female gender; overweight or obese status; current smoking; and Infantry B, Cavalry, and Brigade Support battalions. An examination of physical training risk factors determined that injury risk was higher for Soldiers who participated in unit PT less than 5 times a week and ran more than 16 miles per week. Soldiers who performed resistance and agility training had a lower risk of injury. Analysis of APFT data indicated that those with lower performances on any of the 3 elements of the physical tness test (push-ups, sit-ups, 2-mile run) were at a higher risk of being injured.Multivariate Analysis of Injury Risk Factors Following Implementation of ATAC/ECPsTable 6 displays the results of a backward-stepping multivariate logistic regression analysis that examined unit PT and personal risk factors. Soldiers who were overweight, obese, used tobacco (cigarettes) and were in the Infantry B, Cavalry, or Brigade Support battalions were at a higher risk of injury. For unit PT, men who ran the greatest amount of miles per week were at a higher risk of injury, while men who performed any resistance training were at a lower risk of injury. Further analysis of total miles ran per week revealed that Soldiers who ran more than 16 miles per week during unit PT had identical 2-mile run time scores at 14.61.51 minutes compared to Soldiers who ran less than 16 miles per week during unit PT at 14.61.61 minutes. Table 7 displays the results of a multivariate logistic regression analysis examining components of the physical tness test controlling for age and battalion. Soldiers who performed poorly on the 2-mile run were at a higher risk of injury. COMMENT One of the major ndings of this investigation was the increase in overall injury incidence for Soldiers who did and did not participate in this new program after its Table 2. Comparison of Injury Incidence Before and After the Implementation of ATAC/ECPs (N=1,032).Injury Type Injury Incidence Before ATAC/ECP Injury Incidence After ATAC/ECP Absolute Change Change P (McNemar Test) Overall41%46%+5%+12%.02 Overuse32%37%+5%+16%.02 Traumatic19%18%-1%-5%.95ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program. Table 3. Comparison of Injury Incidence Before and After the Implementation of ATAC/ECPs on all Soldiers Who did not Participate in ATAC/ECPs (N=340).Injury Type Injury Incidence Before ATAC/ECP Injury Incidence After ATAC/ECP Absolute Change Change P (McNemar Test) Overall50%57%+7%+14%.05 Overuse42%46%+4%+10%.28 Traumatic22%23%1%+5%1.00ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program. Table 4. Personal Characteristics and Risk Factors for Injury Among Men Participating in ATAC/ECPs (N=1,032).VariableSubcategory of Variable NInjury After ATAC/ECP Risk Ratio (95%CI) After ATAC/ECP P GenderMen95045%1.00 Women8260%1.34 (1.11-1.63)<.01 Age <2430644%1.09 (0.88-1.38).43 24-2518546%1.15 (0.91-1.45).23 26-2920340%1.00 30+24048%1.21 (0.98-1.50).08 Body Mass IndexI <2534137%1.00 25-2946447%1.27 (1.07-1.51)<.01 30+11560%1.61 (1.31-1.98)<.01 Current Smoking Status Nonsmoker47039%1.00 Smoker44351%1.32 (1.14-1.53)<.01 Smokeless Status Nonsmokeless65543%1.00 Smokeless User29549%1.15 (0.99-1.33).07 Battalion Infantry A39438%1.00 Infantry B11652%1.38 (1.11-1.71)<.01 Cavalry13652%1.37 (1.11-1.69)<.01 Field artillery16342%1.13 (0.90-1.40).30 Brigade support battalion 8460%1.59 (1.28-1.97)<.01 Brigade special troops battalion 5746%1.21 (0.89-1.66).24ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program. EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM

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October – December 2013 41THE ARMY MEDICAL DEPARTMENT JOURNAL implementation. The increase in injury incidence was approximately the same for both groups. Overuse injuries also increased after the implementation of ATAC/ ECPs, while traumatic injuries showed little change. It has been stated that overuse injuries typically occur at the beginning of new exercise programs and account for a majority of the injuries incurred.23,24 Some of the common causes of overuse injuries include engaging in too much physical activity too soon, exercising too long, performing too much of one activity, and improper technique. Some studies have also found that the majority of injuries occurring in Army infantry Soldiers are attributed to physical tness and sports activities.6-10,25 However, the increase in overuse injuries was similar Table 5. Physical Training and Physical Fitness Risk Factors for Injury among Men Participating in ATAC/ECPs (n=950).VariableSubcategory of VariablenInjury After ATAC/ECP Risk Ratio (95% CI) After ATAC/ECP P Physical training at prior assignment Traditional PT76746%1.00 Extreme conditioning programs4743%0.93 (0.66-1.31).67 Combination ECP and traditional9339%0.85 (0.65-1.11).20 Other and/or traditional3639%0.85 (0.56-1.29).42 How often do you participate in unit PT? <5 times per week10959%1.00 5-7 times per week73042%0.72 (0.60-0.86)<.01 >7 times per week10445%0.77 (0.59-1.00).05 Does your unit perform cross-training/ extreme conditioning programs for PT? Extreme conditioning programs61045%1.00 ATAC and/or combination of ATAC/ other programs 34044%1.00 (0.86-1.16).96 How many times per week do you perform cross-training/ECP? <1 time per week6650%1.00 1-2 times per week40044%0.88 (0.67-1.15).36 3-4 times per week28643%0.86 (0.65-1.13).30 >4 times per week16745%0.90 (0.67-1.21).48 Estimated total miles per week ran (unit PT) 7 miles per week44539%1.00 7.01-9.00 miles per week6348%1.23 (0.92-1.63).19 9.0116 miles per week32044%1.14 (0.96-1.35).13 >16 miles per week8159%1.52 (1.23-1.89)<.01 Times per week performed sprint training No sprint training1553%1.00 <1 time per week16345%0.85 (0.52-1.41).56 1-2 times per week62044%0.82 (0.50-1.32).45 3 times per week14647%0.89 (0.54-1.47).65 Times per week of resistance training No resistance training10259%1.00 <1 time per week25448%0.82 (0.66-1.00).07 1-2 times per week45841%0.69 (0.57-0.84)<.01 3 times per week13041%0.69 (0.53-0.90)<.01 Times per week of agility drills No agility training11058%1.00 <1 time per week29745%0.78 (0.63-0.95)<.02 1-2 times per week43142%0.72 (0.59-0.87)<.01 3 times per week10641%0.70 (0.53-0.92)<.01 How often performed road marches No road marching2941%1.00 <1 time per month13455%1.32 (0.83-2.09).20 1 time per month14841%0.98 (0.61-1.58).93 2 times per month23748%1.15 (0.73-1.81).52 3 times per month15037%0.89 (0.55-1.43).63 >3 times per month23044%1.05 (0.66-1.66).83 Push-ups 20-56 repetitions20847%1.21 (0.97-1.50).09 57-67 repetitions22148%1.23 (0.99-1.52).06 68-76 repetitions23041%1.05 (0.84-1.31).69 77-111 repetitions23339%1.00 Sit-ups 19-61 repetitions22354%1.40 (1.14-1.72)<.01 62-69 repetitions21843%1.11 (0.89-1.39).36 70-78 repetitions22740%1.03 (0.82-1.30).78 79-109 repetitions22438%1.00 2-mile Run (minutes and fraction of a minute) 11.12-13.52 minutes23334%1.00 13.53-14.50 minutes22242%1.23 (0.98-1.56).08 14.51-15.50 minutes20444%1.27 (1.00-1.61).05 15.51-32.22 minutes20351%1.49 (1.18-1.86)<.01ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program.

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42 http://www.cs.amedd.army.mil/amedd_journal.aspxin both groups; therefore, no recommendations can be made for or against either program.Unit PT Injury Risk FactorsFor male Soldiers participating in ATAC/ECPs, those who ran greater distances, performed no resistance training, and served in either the Infantry B, Cavalry, or Brigade Support battalion were at a higher risk of injury. Male ATAC/ECPs participants who ran more miles per week during unit PT were at a higher risk of being injured than those who ran fewer miles per week. Other studies have also shown that risk of injury increases with miles run per week.26-28 As mentioned earlier, analysis of APFT scores indicated those who ran greater distances per week (16 miles or more) had an average 2-mile run time of 14.6 minutes (1.51 minutes), and those who ran fewer miles per week (less than 16 miles per week) had identical average 2-mile run times of 14.6 minutes (1.61 minutes). Based on these data, running more than 16 miles per week for unit PT increases injury risk and provides no additional aerobic performance bene ts. Soldiers performing resistance training with their unit at least once per week were at a lower risk of injury than were Soldiers in units that did not perform resistance training. In a US Air Force study, Walker et al found that replacement of a majority of the traditional long-distance running with interval running, agility training, and functional strength training decreased the overall injury rates by 67%, and trainees scored higher on nearly all of the measured tness parameters.14 Adding resistance training to an aerobic training program can also be bene cial in the completion of job tasks or mission requirements. It has been shown that endurance training concurrent with resistance training improves load-bearing performance29-32 and heavy lifting tasks,32 and increases both short-term and long-term endurance capacity in sedentary and trained individuals.33 In a meta-analysis, both strength training and concurrent training (combination of strength and endurance training) had larger effects on strength, 1.76 (95% CI, 1.34-2.18) and 1.44 (95% CI, 1.03-1.84) respectively, when compared to endurance training only (0.78, 95% CI, 0.36-1.19).34 The evidence suggests that implementation of a combined resistance and endurance training program will enable Soldiers to complete speci c mission tasks more effectively and with lower risk of injury than Soldiers who do not incorporate resistance training into their physical tness programs. Table 6. Unit PT and Personal Risk Factors for Injury Among Men Participating in ATAC/ECPs Using Multivariate Logistic Regression.Variable Subcategory of Variable nOdds Ratio (95% CI) P Body mass index (BMI) <25 3101.00 25-29.9 4141.77 (1.29-2.44)<.01 30+ 982.72 (1.67-4.43)<.01 Tobacco Nonsmoker 4301.00 Smoker 3921.80 (1.34-2.42)<.01 Battalion Infantry A3421.00 Infantry B1001.62 (1.01-2.61).05 Cavalry1281.87 (1.20-2.92)<.01 Field artillery1391.36 (0.89-2.08).15 Brigade support battalion 641.96 (1.09-3.54).03 Brigade special troops battalion 491.20 (0.62-2.32).60 Times per week performing resistance training No resistance training 801.00 <1 time per week 2180.53 (0.31-0.92).03 1-2 times per week 4090.50 (0.29-0.84).01 3 times per week 1150.45 (0.24-0.85).01 Estimated miles per week of running 7 miles a week 4011.00 7.01-9.00 miles a week 541.05 (0.57-1.94).87 9.01-16 miles a week 2901.00 (0.72-1.40).99 >16 miles a week 772.24 (1.33-3.80)<.01ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program. Variables entered into the model: Age How often do you participate in unit physical training? BMI Estimated total miles per week ran Current smoking status Agility Training Battalion Resistance Training Table 7. Physical Fitness Test Risk Factors for Injury Among Men Participating in ATAC/ECPs Using Multivariate Cox Regression.Variable Level of Variable n Odds Ratio (95%CI) P Push-ups20-56 repetitions1881.01 (0.62-1.63).97 57-67 repetitions2071.11 (0.71-1.72).50 68-76 repetitions2181.00 (0.66-1.50).99 77-111 repetitions2221.00 Sit-ups19-61 repetitions1991.53 (0.94-2.50).09 62-69 repetitions2051.03 (0.66-1.60).91 70-78 repetitions2130.92 (0.60-1.39).68 79-109 repetitions2181.00 2-mile Run (minutes and fraction of a minute) 11.12-13.52 minutes2261.00 13.53-14.50 minutes2171.42 (0.95-2.12).09 14.51-15.50 minutes1951.45 (0.95-220).08 15.51 minutes1971.76 (1.13-2.74).01Variables entered into the model: Age, battalion, push-ups, sit-ups, and 2-mile run. Note: controlled for age and battalion. ATAC indicates Advanced Tactical Athlete Conditioning program. ECP indicates extreme conditioning program. EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM

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October – December 2013 43THE ARMY MEDICAL DEPARTMENT JOURNAL Infantry A had the lowest injury incidence (38%) after the implementation of ATAC/ECPs. This battalion also had the youngest Soldiers, one of the lowest average BMIs, performed less running per week during unit PT, and performed the most sprint, resistance, and agility training per week in comparison to the other battalions. As previously mentioned, running more miles per week increases injury risk.26-28 In addition, injury risk is higher for recruits with lower levels of lowerextremity muscle strength or who lack a consistent lower-extremity weight training program.35,36 The Infantry A battalion’s unit PT program involved less running and more cross-training activities, likely contributing to its lower injury rates. Interviews of battalion commanders concerning their views regarding physical training and tness offered additional insights into the difference in injury rates. For example, the Infantry A battalion commander spent the largest amount of money on tness equipment for the unit and stated he considered mobility/agility to be the most important tness ability. In comparison, other commanders (including the Infantry B commander) rated endurance as the most important tness component. Upon examination of the 2 infantry groups (Infantry A and Infantry B), a difference in injury incidence of 15% was observed. Both commanders had also implemented an injury surveillance tracking system to collect injury metrics in their respective battalions. However, the Infantry A battalion reported its injury metrics every 3 weeks, whereas the Infantry B battalion collected them at the company level only and did not review or report them on a set schedule. Infantry A and Field Artillery, the 2 battalions with the lowest injury rates, ran the fewest miles per week for unit PT (10.1 miles and 9.2 miles, respectively), and both units tracked and reported their injury metrics at least once a month. Therefore, running fewer miles per week during unit PT and implementing an injury surveillance system11 in which metrics are reported at least monthly may have a positive in uence on lowering injury rates. In a consensus paper concerning military personnel involved with ECPs, Bergeron et al state that regular monitoring and accurate injury reporting may help reduce injury rates and optimize the physical tness bene ts of ECPs.17Soldier Injury Risk FactorsIn the current study, 62% of the men were considered either overweight or obese, which is similar to the US population, of which 64% of men aged 20 to 39 years are also considered either overweight or obese.37 Injury risk for men was higher for those with a BMI classifying them as overweight or obese. Other investigations have found that Soldiers with a higher BMI are at a greater risk of being injured. 9,25,38 In a study involving infantry Soldiers, Reynolds et al found that Soldiers with a BMI of 25 or higher were at 2.2 times greater risk of being injured.9 These ndings are similar to the results found in this evaluation (1.8 and 2.7 times greater risk of injury for overweight or obese Soldiers, respectively). According to the CDC, BMI is a fairly reliable indicator of body fatness for most people.24 Therefore, Soldiers with higher BMIs will most likely have larger amounts of excess body fat. Investigations examining excessive body fat have shown that it adversely affects performance on military tasks that require both aerobic and strength components.39-42 In a study investigating physical and physiological performance in Army Soldiers, Crawford et al found that Soldiers with 18% or less body fat performed signi cantly better on 7 of 10 tness tests, compared to Soldiers with body fat greater than 18%. The authors suggested that Soldiers who have an excess amount of body fat may possess musculoskeletal and physiological tness de cits, thereby decreasing military readiness and increasing risk for injury.39 In an investigation of active duty Navy personnel, Bohnker et al examined mean BMI and overall physical readiness test scores (outstanding, excellent, good, satisfactory, and fail). As physical tness test scores decreased, the mean BMI increased for both men and women.42 This trend was also observed in the current study (analysis performed on all men who completed the survey and had injury data). Soldiers with lower physical tness test results as examined by quartile also had higher average BMIs.43 Being overweight or obese may not only increase a Soldier’s risk of incurring an injury, but may also have an adverse effect on aerobic and strength performance. The data is presented in Table 8. Injury risk was higher in smokers than in nonsmokers. Previous studies have also demonstrated an increased general risk of injury in smokers compared to nonsmokers, and a de nable increased risk of musculoskeletal Table 8. Mean BMIs and Physical Fitness Test Scores Grouped by Quartiles of Poor to High Performance for Men.Mean BMIs for Fitness Variables nQ1Q2Q3Q4ANOVA Plow performance high performance2-mile run (mean BMI) 1,09128.2 BMI26.1 BMI25.2 BMI24.6 BMI<.01 Push-ups (mean BMI) 1,13726.6 BMI26.1 BMI26.1 BMI25.8 BMI.03 Sit-ups (mean BMI) 1,13427.0 BMI26.1 BMI25.7 BMI25.5 BMI<.01BMI indicates body mass index.

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44 http://www.cs.amedd.army.mil/amedd_journal.aspxinjury.25,44-52 Also, among smokers themselves, the risk of injury has been shown to increase in direct relation to the number of cigarettes smoked per day.25,44,47 The relationship between tobacco use and injury may be due to a compromised ability to repair damaged tissues, thereby increasing susceptibility to the repetitive microtrauma that presumably causes overuse injuries.53 In one investigation, researchers showed that tibial fracture healing to clinical union took 24% longer in smokers compared to nonsmokers,54 while another study showed that smokers experienced impaired wound healing when compared to nonsmokers.55 Therefore, harsh deployment environments and military occupational specialty requirements may result in weakened tissues from training and overuse, which may result in a greater susceptibility to injury among smokers who maintain high levels of physical tness to meet demanding tasks. Injury risk for Soldiers with the slowest 2-mile run times was higher when compared to those showing the fastest 2-mile run times. Previous studies investigating run times during basic combat training have also found that slower run times place Soldiers at a higher risk of injury.8,21,45,56,57 The Soldiers with the slowest 2-mile run times would have lower aerobic capacities than those with the fastest 2-mile run times.58 Soldiers with lower aerobic capacities will likely experience greater physiological stress and/or fatigue during tasks such as running, cross-training, and calisthenics due to exercising at a higher percentage of their maximum aerobic capacity in comparison with Soldiers with greater tness levels. Soldiers of lower tness levels will not only be exercising at a higher percentage of their aerobic capacity to accomplish the same task as a more t Soldier, but they will also perceive tasks as more dif cult.59 The greater physiological stress and/or fatigue experienced may lead to a higher risk of injury. Studies on fatigue have demonstrated decrements in proprioceptive ability,60 a decrease in joint stability,61 alterations in muscle activity,60 changes in gait,62-66 balance,67,68 low-frequency fatigue,69 neuromuscular function,70 and ligament laxity.71CONCLUSION This project found similar increases in injury rates for units performing ATAC/ECPs and units not performing ATAC/ECPs. Therefore, no recommendations can be made for or against use of those programs. Risk factors associated with higher risk of injury following the start of a new exercise program included running longer distances during unit physical training, having a BMI of 25 or more, and smoking cigarettes. However, almost any level of resistance training appeared to produce a noticeable protective effect. A lower risk of injury was found for Soldiers who performed any resistance training compared to Soldiers who performed no resistance training. Soldiers should recognize the challenges and limitations of ECPs or exercise programs with ECP components and approach them with discretion. The goal of all tness programs should be to meet occupational and operational demands and expectations while minimizing injury risks. RELEVANCE TO PERFORMANCE TRIAD A key aspect of The Army Surgeon GeneralÂ’s Performance Triad is the promotion of optimal physical activity among Army Soldiers, family members, retirees, and civilians. Optimal physical activity involves incorporating regular physical activity into daily routines while also minimizing injury risk. Prevention of injury during physical activity is crucial to preserving Soldier and unit readiness. The results of this analysis suggest that injuries can be minimized by limiting longer running distances and adding resistance training to unit physical training. The results also suggest that injury risks were lower for nonsmokers, Soldiers with higher aerobic endurance, and Soldiers maintaining a healthy body weight. REFERENCES1. DoD Military Injury Prevention Priorities Working Group. Leading Injuries, Causes and Mitigation Recommendations. Washington, DC: Defense Safety Oversight Council, US Dept of Defense; 2006. Available at: http://www.dtic.mil/cgi-bin/ GetTRDoc?Location=U2&doc=GetTRDoc. pdf&AD=ADA458257. Accessed July 10, 2013. 2. Almeida SA, Williams KM, Shaffer RA, Luz JT, Badong E, Brodine SK. A Physical Training Program to Reduce Musculoskeletal Injuries in U.S. Marine Corps Recruits, Version 1.0 [Naval Health Research Center Technical Report No. NHRC072B]. San Diego, CA: Naval Health Research Center; May 1997. Available at: http://www.dtic.mil/ cgi-bin/GetTRDoc?AD=ADA326216. Accessed July 10, 2013. 3. Lauder TD, Baker SP, Smith GS, Lincoln AE. Sports and physical training injury hospitalizations in the Army. Am J Prev Med 2000;18(suppl 3):118-128. 4. Smith TA, Cashman TM. The incidence of injury in light infantry soldiers. Mil Med 2002;167(2):104-108.EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM

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October – December 2013 45THE ARMY MEDICAL DEPARTMENT JOURNAL5. Loringer K, Bedno S, Hauret K, Jones BH, Kao TC, Mallon T. Injuries from Participation in Sports, Exercise, and Recreation Activities Among Active Duty Service Members—Analysis of the April 2008 Status of Forces Survey of Active Duty Members Aberdeen Proving Ground, MD: US Army Public Health Command; 2011. Report No. 12-HF0DPT-08. Available at: http://www.dtic.mil/cgibin/GetTRDoc?Location=U2&doc=GetTRDoc. pdf&AD=ADA560733. Accessed July 11, 2013. 6. Tomlinson JP, Lednar WM, Jackson JD. Risk of injury in soldiers. Mil Med 1987;152(2):60-64. 7. Smith GS, Dannenberg AL, Amoroso PJ. Hospitalization due to injuries in the military. Evaluation of current data and recommendations on their use for injury prevention. Am J Prev Med. 2000;18(suppl 3):41-53. 8. Knapik JJ, Ang P, Reynolds K, Jones B. Physical tness, age and injury incidence in infantry soldiers. J Occup Med. 1993;35(6):598-603. 9. Reynolds K, Cosio-Lima L, Bovill M, Tharion W, Williams J, Hodges T. A comparison of injuries, limited duty days, and injury risk factors in infantry, artillery, construction engineers, and special forces soldiers. Mil Med. 2009;174(7):702-708. 10. Wilkinson DM, Blacker SD, Richmond VL, et al. Injuries and injury risk factors among British army infantry soldiers during predeployment training. Inj Prev 2011;17(6):381-387. 11. Knapik JJ, Bullock SH, Canada S, et al. In uence of an injury reduction program on injury and tness outcomes among soldiers. Inj Prev. 2004;10(1):37-42. 12. Knapik JJ, Darakjy S, Scott SJ, et al. Evaluation of a standardized physical training program for Basic Combat Training. J Strength Cond Res. 2005;19(2):246-253. 13. Knapik JJ, Hauret KG, Arnold S, et al. Injury and tness outcomes during implementation of physical readiness training. Int J Sports Med 2003;24(5):372-381. 14. Walker TB, Lennemann LM, Anderson V, Lyons W, Zupan MF. Adaptations to a new physical training program in the combat controller training pipeline. J Spec Oper Med 2011;11(2):37-44. 15. Hofstetter MC, Mder U, Wyss T. Effects of a 7-week outdoor circuit training program on Swiss Army recruits. J Strength Cond Res 2012;26(12):3418-3425. 16. Knapik JJ, Rieger W, Palkoska F, Van Camp S, Darakjy S. United States Army physical readiness training: rationale and evaluation of the physical training doctrine. J Strength Cond Res 2009;23(4):1353-1362. 17. Bergeron MF, Nindl BC, Deuster PA, et al. Consortium for Health and Military Performance and American College of Sports Medicine consensus paper on extreme conditioning programs in military personnel. Curr Sports Med Rep 2011;10(6):383-389. 18. Jones SB, Knapik JJ, Sharp MA, Darakjy S, Jones BH. Validity of self-reported physical tness test scores. Mil Med 2007;172(2):115-120. 19. Field Manual 7-22: Army Physical Readiness Training Washington, DC: US Dept of the Army; October 2012 20. Grier T, Knapik JJ, Swedler DI, Spiess A, Jones BH. Injury Prevention Effectiveness of Modi cations of Shoe Type Injuries and Risk Factors Associated with Pain and Discomfort in the US Army Band Fort Meyer, Virginia 2007-2008 [Injury Prevention Report No. 12-HF-05WC-07]. Aberdeen Proving Ground, MD: US Army Center for Health Promotion and Preventive Medicine; June 3, 2009. Available at: http://www.dtic.mil/cgi-bin/Get TRDoc?AD=ADA503988. Accessed July 11, 2013. 21. Knapik JJ, Swedler DI, Grier T, et al. Injury Reduction Effectiveness of Prescribing Running Shoes Based on Foot Shape in Basic Combat Training [USACHPPM Report No. 12-MA-05SB-08]. Aberdeen Proving Ground, MD: US Army Center for Health Promotion and Preventive Medicine; June 2008. Available at: http://www.dtic.mil/cgibin/GetTRDoc?Location=U2&doc=GetTRDoc. pdf&AD=ADA484214. Accessed August 5, 2013, 22. About BMI for Adults. Centers for Disease Control and Prevention website; 2011. Available at: http:// www.cdc.gov/healthyweight/assessing/bmi/adult_ bmi/index.html. Accessed September 5, 2012. 23. Settles DM, Brown TP. US Navy Pre-Entry Physical Training Plan. Pensacola, FL: Naval Service Training Command Of cer Development; 2002. Available at http://www.nrotc.navy.mil/pdfs/preconditioning.pdf. Accessed March 22, 2013. 24. Overuse injury: how to prevent training injuries. Mayo Clinic website. 2010. Available at: http:// www.mayoclinic.com/health/overuse-injury/ my01092. Accessed March 22, 2013. 25. Reynolds KL, Heckel HA, Witt CE, et al. Cigarette smoking, physical tness, and injuries in infantry soldiers Am J Prev Med 1994;10(3):145-150. 26. Koplan JP, Powell KE, Sikes RK, Shirley RW, Campbell CC. An epidemiologic study of the bene ts and risks of running. JAMA 1982;248(23):3118-3121. 27. Marti B, Vader JP, Minder CE, Abelin T. On the epidemiology of running injuries. The 1984 Bern Grand-Prix study. Am J Sports Med 1988;16(3):285-294.

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46 http://www.cs.amedd.army.mil/amedd_journal.aspx28. Samet JM, Chick TW, Howard CA. Running-related mortality: a community survey. Ann Sports Med 1982;1:30-34. 29. Kraemer WJ, Vescovi JD, Volek JS, et al. Effects of concurrent resistance and aerobic training on loadbearing performance and the Army physical tness test. Mil Med. 2004;169(12):994-999. 30. Kraemer WJ, Vogel JA, Patton JF, Dziados JE, Reynolds KL. The effects of various physical training programs on short duration, high intensity load bearing performance and the Army Physical Fitness Test. Technical Report. Natick MA: US Army Research Institute of Environmental Medicine; 1987. Report No. T30-87. 31. Kraemer WJ, Mazzetti SA, Nindl BC, et al. Effect of resistance training on womenÂ’s strength/power and occupational performances. Med Sci Sports Exerc. 2001;33(6):1011-1025. 32. Reynolds KL, Harman EA, Worsham RE, Sykes MB, Frykman PN, Backus VL. Injuries in women associated with a periodized strength training and running program. J Strength Cond Res. 2001;15(2):136-143. 33. Tanaka H, Swensen T. Impact of resistance training on endurance performance. A new form of cross training?. Sports Med 1998;25(3):191-200. 34. Wilson JM, Marin PJ, Rhea MR, Wilson SM, Loenneke JP, Anderson JC. Concurrent training: a meta-analysis examining interference of aerobic and resistance exercises. J Strength Cond Res. 2012;26(8):2293-2307. 35. Hoffman JR, Chapnik L, Shamis A, Givon U, Davidson B. The effect of leg strength on the incidence of lower extremity overuse injuries during military training. Mil Med 1999;164(2):153-156. 36. Rauh MJ, Macera CA, Trone DW, Shaffer RA, Brodine SK. Epidemiology of stress fractures and lower extremity overuse injuries in female recruits. Med Sci Sports Exerc. 2006;38(9):1571-1577. 37. Flegal KM, Carroll MD, Ogden CL, Curtin LR. Prevalence and trends in obesity among US adults, 1999-2008. JAMA. 2010;303(3):235-241. 38. Knapik JJ, Jones SB, Darakjy S, et al. Injuries and injury risk factors among members of the United States Army Band. Am J Ind Med 2007;50(12):951-961. 39. Crawford K, Fleishman K, Abt JP, et al. Less body fat improves physical and physiological performance in Army Soldiers. Mil Med 2011;176(1):35-43. 40. Harman EA, Frykman PN. The relationship of body size and composition to the performance of physically demanding military tasks. In: Marriott BM, Grumstrup-Scott J, eds. Body Composition and Physical Performance. Washington, DC: The National Academies Press; 1992:105-118. 41. Mattila VM, Tallroth K, Marttinen M, Pihlajamki H. Body composition by DEXA and its association with physical tness in 140 conscripts. Med Sci Sports Exerc 2007;39(12):2242-2247. 42. Bohnker BK, Sack DM, Wedierhold L, Malakooti M. Navy physical readiness test scores and body mass index (spring 2002 cycle). Mil Med 2005;170(10):851-854. 43. Grier T, Chervak M, McNulty V, Jones BH. Evaluation of the advanced tactical athlete conditioning and extreme conditioning programs in the 25th Infantry Division, Scho eld Barracks, Hawaii. Injury Prevention Report. Aberdeen Proving Ground, MD: United States Army Institute of Public Health; 2010. 44. Knapik JJ, Hauret KG, Jones BH. Primary Preven-tion of Injuries in Initial Entry Training. In: Lenhart MK, Lounsbury DE, North RB, eds. Textbook of Military Medicine: Recruit Medicine. Washington, DC: Borden Institute; 2006. 45. Knapik JJ, Sharp MA, Canham-Chervak M, Hauret K, Patton JF, Jones BH. Risk factors for training-related injuries among men and women in basic combat training. Med Sci Sports Exerc 2001;33(6):946-954. 46. Heir T, Eide G. Injury proneness in infantry conscripts undergoing a physical training programme: smokeless tobacco use, higher age, and low levels of physical tness are risk factors. Scand J Med Sci Sports. 1997;7:304-311. 47. Altarac M, Gardner JW, Popovich RM, Potter R, Knapik JJ, Jones BH. Cigarette smoking and exercise-related injuries among young men and women. Am J Prev Med. 2000;18(suppl 3):96-102. 48. Munnoch K, Bridger RS. Smoking and injury in Royal MarinesÂ’ training. Occup Med (Lond) 2007;57(3):214-216. 49. Knapik JJ, Swedler DI, Grier TL, et al. Injury reduction effectiveness of selecting running shoes based on plantar shape. J Strength Cond Res. 2009;23(3):685-697. 50. Dettori J, Reynolds K, Amoroso P, Barnes J, Westphal K, Lavin P. Smoking and injury risk among female US Army basic combat trainees. Presented at the Third International Conference for Injury Prevention and Control. Melbourne, Australia; 1996. 51. Reynolds K, Amoroso P, Dettori J. Association of tobacco use with injuries among infantry soldiers carrying loads on a 100-mile road march. Presented at the Third International Conference for Injury Prevention and Controls. Mebourne, Australia; 1996. 52. Grier TL, Knapik JJ, Canada S, Canham-Chervak M, Jones BH. Risk factors associated with selfreported training-related injury before arrival at the US Army Ordnance School. Public Health 2010;124(7):417-423.EXTREME CONDITIONING PROGRAMS AND INJURY RISK IN A US ARMY BRIGADE COMBAT TEAM

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October – December 2013 47THE ARMY MEDICAL DEPARTMENT JOURNAL53. Amoroso PJ, Reynolds KL, Barnes JA, White DJ. Tobacco and injuries: an annotated bibliography. Technical Report. Natick, MA: US Army Research Institute of Environmental Medicine; 1996. Report No. TN96-1. 54. Kyr A, Usenius J, Aarnio M, Kunnamo I, Avikainen V. Are smokers a risk group for delayed healing of tibial shaft fractures?. Ann Chir Gynaecol. 1993;82(4):254-262. 55. Jones JK, Triplett RG. The relationship of cigarette smoking to impaired intraoral wound healing: a review of evidence and implications for patient care. J Oral Maxillofac Surg 1992;50(3):237-249. 56. Jones BH, Bovee MW, Harris JM, Cowan DN. Intrinsic risk factors for exercise-related injuries among male and female Army trainees. Am J Sports Med 1993;21(5):705-710. 57. Hauret KG, Knapik JJ, Darakjy S, et al. Reduced injury risk in Army basic combat training with a standardized physical training program. Med Sci Sports Exerc 2004;36(5):S309. 58. Knapik JJ. The Army Physical Fitness Test (APFT): a review of the literature. Mil Med 1989;154(6):326-329. 59. Garcin M, Vautier JF, Vandewalle H, Monod H. Rating of perceived exertion (RPE) as an index of aerobic endurance during local and general exercise Ergonomics. 1988;41(8):1105-1114. 60. Rozzi SL, Lephart SM, Fu FH. Effects of muscular fatigue on knee joint laxity and neuromuscular characteristics of male and female athletes. J Athl Train. 1999;34(2):106-114. 61. Melnyk M, Gollhofer A. Submaximal fatigue of the hamstrings impairs speci c re ex components and knee stability. Knee Surg Sports Traumatol Arthrosc 2007;15(5):525-532. 62. Candau R, Belli A, Millet GY, Georges D, Barbier B, Rouillon JD. Energy cost and running mechanics during a treadmill run to voluntary exhaustion in humans. Eur J Appl Physiol Occup Physiol 1998;77(6):479-485. 63. Nyland JA, Shapiro R, Stine RL, Horn TS, Ireland ML. Relationship of fatigued run and rapid stop to ground reaction forces, lower extremity kinematics, and muscle activation. J Orthop Sports Phys Ther 1994;20(3):132-137. 64. Gerlach KE, White SC, Burton HW, Dorn JM, Leddy JJ, Horvath PJ. Kinetic changes with fatigue and relationship to injury in female runners. Med Sci Sports Exerc 2005;37(4):657-663. 65. LeBris R, Billat V, Auvinet B, Chaleil D, Hamard L, Barrey E. Effect of fatigue on stride pattern continuously measured by an accelerometric gait recorder in middle distance runners. J Sports Med Phys Fitness 2006;46(2):227-231. 66. Yoshino K, Motoshige T, Araki T, Matsuoka K. Effect of prolonged free-walking fatigue on gait and physiological rhythm. J Biomech 2004;37(8):1271-1280. 67. Johnston RB III, Howard ME, Cawley PW, Losse GM. Effect of lower extremity muscular fatigue on motor control performance. Med Sci Sports Exerc 1998;30(12):1703-1707. 68. Dickin DC, Doan JB. Postural stability in altered and unaltered sensory environments following fatiguing exercise of lower extremity joints. Scand J Med Sci Sports. 2008;18(6):765-772. 69. Baptista RR, Scheeren EM, Macintosh BR, Vaz MA. Low-frequency fatigue at maximal and submaximal muscle contractions. Braz J Med Biol Res 2009;42(4):380-385. 70. Wojtys EM, Wylie BB, Huston LJ. The effects of muscle fatigue on neuromuscular function and anterior tibial translation in healthy knees. Am J Sports Med. 1996;24(5):615-621. 71. Sakai H, Tanaka S, Kurosawa H, Masujima A. The effect of exercise on anterior knee laxity in female basketball players. Int J Sports Med. 1992;13(7):552-554.AUTHORSMr Grier is a Kinesiologist for the Injury Prevention Program of the Epidemiology and Disease Surveillance Portfolio, US Army Public Health Command, Aberdeen Proving Ground, Maryland. Dr Canham-Chervak is a Senior Epidemiologist for the Injury Prevention Program of the Epidemiology and Disease Surveillance Portfolio, US Army Public Health Command, Aberdeen Proving Ground, Maryland. MAJ McNulty is a Physical Therapy Staff Of cer for the Public Health Assessment Program of the Health and Wellness Portfolio, US Army Public Health Command, Aberdeen Proving Ground, Maryland. Dr Jones is a Program Manager for the Injury Prevention Program of the US Army Public Health Command, Aberdeen Proving Ground, Maryland.

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48 http://www.cs.amedd.army.mil/amedd_journal.aspxButte et al de ned physical activity (PA) as “any bodily movement produced by the contraction of skeletal muscle that increases energy expenditure above a resting level.”1 Investigators in the eld of PA monitoring have been interested in capturing the broad range of human behaviors encompassing “activity” and “inactivity.”1 This also includes PA in physically demanding occupations such as those in the military setting. An understanding of the amount, type, and intensity of PA is needed to help prevent injury while maintaining unit performance and morale.2 The US Army’s Performance Triad initiative seeks to improve Soldier readiness and resilience by improving Soldiers’ PA, nutrition, and sleep behaviors. An understanding of the present level of PA during Basic Combat Training (BCT) will help determine if those levels should be maintained or altered in order to meet guidelines for Soldier health and performance. Measurement tools used to assess PA have included subjective measures such as self-report questionnaires, logs, and diaries, as well as objective measures such as pedometers, accelerometers, heart rate monitors, and direct observation. Pedometers are small, lightweight, portable, nonintrusive, inexpensive devices that record daily step counts. More recently, researchers have used accelerometers to provide more detailed information about PA. Unlike pedometry, accelerometry allows for the characterization of PA intensity and duration. Direct observation is considered one of the most valid, reliable, and objective methods for assessing PA.3 However, direct observation is often viewed as labor-intensive and tedious. Consequently, it has not often been used to assess PA. Self-report techniques are the instruments of choice for assessing PA levels in large-scale epidemiological studies.4 This is because they are practical, easy Measuring Physical Activity During US Army Basic Combat Training: A Comparison of 3 MethodsJan E. Redmond, PhD Bruce S. Cohen, PhD Kathleen Simpson, MS Barry A. Spiering, PhD Marilyn A. Sharp, MSABSTRACT Background: An understanding of the demands of physical activity (PA) during US Army Basic Combat Training (BCT) is necessary to support Soldier readiness and resilience. The purpose of this study was to determine the agreement among 3 different PA measurement instruments in the BCT environment. Methods: Twenty-four recruits from each of 11 companies wore an ActiGraph accelerometer (Actigraph, LLC, Pensacola, FL) and completed a daily PA log during 8 weeks of BCT at 2 different training sites. The PA of one recruit from each company was recorded using PAtracker, an Army-developed direct observation tool. Information obtained from the accelerometer, PA log, and PAtracker included time spent in various types of PA, body positions, PA intensities, and external loads carried. Pearson product moment correlations were run to determine the strength of association between the ActiGraph and PAtracker for measures of PA intensity and between the PAtracker and daily PA log for measures of body position and PA type. The Bland-Altman method was used to assess the limits of agreement (LoA) between the measurement instruments. Results: Weak correlations ( r = -0.052 to r = 0.302) were found between the ActiGraph and PAtracker for PA intensity. Weak but positive correlations ( r = 0.033 to r = 0.268) were found between the PAtracker and daily PA log for body position and type of PA. The 95% LoA for the ActiGraph and PAtracker for PA intensity were in disagreement. The 95% LoA for the PAtracker and daily PA log for standing and running and all PA types were in disagreement; sitting and walking were in agreement. Conclusions: The ActiGraph accelerometer provided the best measure of the recruits’ PA intensity while the PAtracker and daily PA log were best for capturing body position and type of PA in the BCT environment. The use of multiple PA measurement instruments in this study was necessary to best characterize the physical demands of BCT.

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October – December 2013 49to administer, and incur a relatively low cost and low participant burden, but their validity may be in question.4,5 Self-report methods rely on the subject’s ability to recall and are prone to misrepresentation, including accurately recalling the time and intensity of the PA performed.4,5During BCT, new recruits learn basic soldiering skills and participate in physical readiness training between 5 AM and 7 AM. The recruits are often required to move on foot from one training activity to another. Multiple measurement instruments may be needed to characterize all of the demands of PA during BCT, including the amount, type, and intensity. On the other hand, only one measurement instrument may be required to characterize a speci c component of PA. Therefore, the purpose of this study was to determine the agreement between an ActiGraph accelerometer and PAtracker (direct observation) for characterizing PA intensity, and between the PAtracker and a daily PA log (self-report) for characterizing body position and PA type in the BCT environment. METHODSStudy OverviewData for this study was collected from recruits in 2 training battalions during separate BCT cycles. The rst iteration took place from June to August 2010, at Fort Jackson, South Carolina, during which recruits from 6 training companies were studied. The second iteration took place from July to September 2011, at Fort Sill, Oklahoma, during which recruits from 5 training companies were studied. The companies included in the study were determined based solely upon their availability. Prior to the start of the study, recruits in each training company were informed of the requirements and potential risks of participation. Recruits voluntarily signed an informed consent document approved by the Institutional Review Board of the US Army Research Institute of Environmental Medicine (USARIEM), Natick, Massachusetts. Investigators followed the policies for protection of human subjects as prescribed in Army Regulation 70-25 ,6 and the research was conducted in compliance with the provisions of 45 CFR Part 46, Protection of Human Subjects. Recruits were included in the study if they were at least 18 years of age, were assigned to a battalion for a 10-week BCT course, and were able to participate fully in all BCT activities.Physical Activity AssessmentActiGraph AccelerometerThe accelerometer used in this study was the ActiGraph GT3X triaxial accelerometer (Actigraph, LLC, Pensacola, FL) shown in Figure 1. This device is capable of sensing acceleration along the vertical, anterior-posterior, and mediolateral axes The accelerometer’s output is recorded in “counts,” which are the summation of the absolute values of the sampled changes in acceleration during a user-de ned time period.7 From the accelerometers, average daily time (minutes) each recruit spent in sedentary, light (<3 metabolic equivalent (MET)), moderate (3-6 MET), and vigorous (>6 MET) intensity activities was determined using the Freedson categories.7 Sedentary to light intensity activity is de ned as 0 to 1,951 counts per minute, moderate intensity PA is de ned as 1,952 to 5,724 counts per minute, and vigorous intensity PA is de ned as 5,725 or more counts per minute.7Within each training company, 24 recruits (Fort Jackson n=144, Fort Sill n=120) were out tted with an ActiGraph GT3X accelerometer. Each group of 24 recruits was comprised of 6 recruits in each of 4 platoons (6 recruits/platoon 4 platoons/company=24recruits/ company). When possible, at least one of the 6 recruits from each platoon was female. Research staff distributed the accelerometers to participants before the rst formation each morning (5 AM) and collected them immediately before or after the dinner meal (approximately 4 PM). Recruits wore the accelerometer in a pouch attached to a belt and placed over their left hip Monday through Saturday for 8 weeks. If a recruit became injured, ill, or was separated from the platoon for a portion of the day while wearing the accelerometer, the accelerometer was worn by another recruit from the same training company. Compliance checks were performed by research staff at morning formation and morning meal times to ensure the devices were being worn properly. Although 24 recruits wore the ActiGraph, accelerometer data was treated as unit data re ective of the PA performed by the entire company. Figure 1. The Actigraph accelerometer.

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50 http://www.cs.amedd.army.mil/amedd_journal.aspxDirect ObservationThe USARIEM and L-3 Communications Corporation (San Diego, CA) developed the PAtracker, a novel PA tracking software designed speci cally for direct observation in the BCT environment. The PAtracker software was installed on HTC smartphone devices (Figure 2), which allowed activities to be logged by selecting them from a predetermined menu on a touch-sensitive screen. The software automatically added a time stamp to each activity recorded. Activities were coded into the following operational de nitions: Time spent asleep versus awake. Time spent in the following body positions: lying, sitting, standing/on feet, and kneeling. Time spent in the following types of PA: cadence marching, calisthenics, combatives, crawling, lift/ carry, barracks chores/menial tasks, obstacles/ climbing, running, stationary, and walking. Physical activity was also classi ed by load carried (010 lbs, 10-25 lbs, 25-50 lbs, 50-75 lbs, >75 lbs) and PA intensity, including the categories of sedentary, light, moderate, and vigorous. The direct observation portion of this study employed the continuous duration recording method, which allowed trained observers to record changes in a recruitÂ’s PA behaviors when changes in activity occurred.8There were 6 observation teams at Fort Jackson and 5 observation teams at Fort Sill. Each team consisted of 3 to 6 observers who monitored and recorded a recruitÂ’s activities. Observers were recruited from the local area and completed 10 hours of training over 3 consecutive days to become familiar with the PAtracker device and the operational de nitions. Direct observation commenced at the beginning of each training day, and all activities during the day were recorded until the recruits returned to their barracks. The team observed a recruit in the designated platoon who was wearing an ActiGraph. If the designated recruit was not training that day, another recruit wearing the device was identi ed and followed. Although individual recruits in each company were observed, the direct observation data was treated as unit data re ective of the PA performed by the entire company.Self-Report Daily Physical Activity LogAt the end of each training day, all recruits wearing an ActiGraph completed a 24-hour PA recall log, as shown in Figure 3. Recruits were asked to report the amount of time they spent wearing the ActiGraph during the day and the amount of time they spent sleeping the night before. In addition, they were asked to report the amount of time they spent sitting, standing, walking/marching, running, performing chores or barracks maintenance, doing calisthenics/obstacle courses, carrying a load pack, and participating in moderate to vigorous intensity activities during the day. All times were recorded as hours and minutes.Statistical Analyses Pearson product moment correlations were run to determine the strength of association between the ActiGraph and PAtracker on measures of intensity and between the PAtracker and the daily PA log on measures of body position and PA type. Absolute agreement between the measurement instruments was assessed using the BlandAltman method9 to determine if similar values for PA intensity, body position, and type of PA had been captured between 2 measurement instruments. First, differences in average daily time spent in each PA intensity, body position, or type of PA as measured by each instrument (ActiGraph, vigorous; PAtracker, vigorous) were plotted against their mean (mean of the average daily time obtained while in vigorous activity as measured by Figure 2. The PAtracker application screen interface on a smartphone. MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING: A COMPARISON OF 3 METHODS

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October – December 2013 51THE ARMY MEDICAL DEPARTMENT JOURNAL the ActiGraph and PAtracker). The data were then analyzed for the presence of heteroscedasticity by plotting the absolute values of individual differences between the 2 measurement instruments versus the means between the 2 instruments for PA intensity, body position, and type of PA.9,10 Data were de ned as homoscedastic if R2 <0.1, or as heteroscedastic if R2 >0.1.9,10 Signi cant Pearson product-moment correlation coef cients were considered indicative of heteroscedastic data (the random error increased as the average daily time increased). If the data were heteroscedastic, the 95% ratio limits of agreement (LoA) was calculated as follows: 95% ratio LoA=(SD of the difference scoresaverage of the mean values) 1.96 If the data were homoscedastic, the 95% LoA was calculated as follows: 95% LoA=SD of the difference scores 1.96 The LoA indicates that the average daily time spent in PA intensity, the body position, or the type of PA obtained from the 2 measurement instruments will differ due to measurement error by no more than X average daily minutes (for LoA) or X % (for ratio LoA in either the positive or negative direction.11 Pearson correlations were performed with IBM SPSS Statistics (V 14.0) (IBM Corp, Chicago, IL) for Windows. Bland-Altman plots were performed with Microsoft Excel 2007. RESULTS Weak but positive Pearson correlations (association) ( r = -0.052 to r = 0.302) were found between the ActiGraph and PAtracker for average daily time spent in sedentary, moderate, and vigorous PA. Alternatively, the association was negative and weak for average daily time spent in light PA (Table 1). The 95% LoA analyses for intensity measurements between the ActiGraph and PAtracker were heteroscedastic. The ratio LoA are provided in Table 1. Weak but positive Pearson correlations (association) ( r = 0.033 to r = 0.268) were found between the PAtracker and daily PA log for body position and type of PA (Table 2). The 95% LoA analyses for the PAtracker and daily PA log for the body positions of standing and running were heteroscedastic (Table 2). The 95% LoA analyses 0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Sitting HoursMinutes0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Running HoursMinutes0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Load Carried HoursMinutes0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Walking/Marching HoursMinutes0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Chores Barracks Maintenance HoursMinutes Standing/Formations HoursMinutes0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Calisthenics/Obstacle and Con dence Courses HoursMinutes0 1 2 0 1 2 3 4 5 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 Carrying a Load/Pack HoursMinutesFIgure 3. Physical Activity Log.

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52 http://www.cs.amedd.army.mil/amedd_journal.aspxfor the body positions of walking and sitting were homoscedastic (Table 2). The mean bias line (31.7) and random error lines (259, -195) forming the 95% limits of agreement for sitting are presented in Figure 4. The mean bias line (74.0) and random error lines (196, -93) forming the 95% limits of agreement for walking are presented in Figure 5. COMMENT To our knowledge, this is the rst time the physical demands, including PA intensity, body position, and type of PA, of US Army BCT have been characterized in detail. The ndings in this study support the use of the ActiGraph as the instrument to measure PA intensity and the PAtracker and daily PA log to measure body position and PA type in the BCT environment. To date, no single eld measure of PA has proven valid, reliable, and logistically feasible over a wide range of population settings and uses.12Pearson product moment correlations are often used to interpret the degree of association between measurement tools, but not the agreement. A high correlation may suggest a strong association but does not imply close agreement between instruments, and may re ect the possibility of measurement bias.9,10 In this study, weak correlations were noted when comparing the use of the ActiGraph and PAtracker for measures of PA intensity, and the PA tracker and daily PA log for measures of body position and type of PA. These ndings suggest that the measurement instruments were quantifying the intensity of PA, body position, and type of PA in a similar manner and direction. However, the correlations provided no de nitive conclusions regarding the agreement between the measurement instruments for PA intensity, body position, and type of PA. Understanding the intensity of PA during the course of BCT is important for assessing its potential role in the incidence of musculoskeletal injuries and Soldier performance. The LoA method as proposed by Bland and Altman9 was used to assess agreement between the ActiGraph accelerometer and PAtracker for measures of PA intensity, and between the PAtracker and daily PA log for measures of body position and type of PA. How far apart the measurements can be without causing dif culties depends on the interpretation of method comparison and the sample size.9,10 The resulting 95% LoA indicates that for the measure of intensity, the random error increased as the average daily minutes spent in each intensity increased. More speci cally, there was disagreement between the ActiGraph and the PAtracker for all categories of intensity. The accelerometer provides an objective measure of movement including intensity and has been used as a criterion measure in studies validating other PA instruments, such as the self-report instruments.4 The PAtracker also provides an objective measure of intensity through direct observation. However, correctly categorizing PA intensity through direct observation may be highly dependent on the training and experience of the observer and the environment in which the PA is occurring. The PAtracker underreported for all categories of intensity except light, which was overreported. In this study, the ActiGraph accelerometer provided a better measure of PA intensity compared to the PAtracker. Table 1 Comparisons Between the Data Collected by the ActiGraph Accelerometer and PAtracker Regarding Time Spent in Various PA Intensities During Army Basic Combat Training.MeasureActiGraph Average Daily Min PAtracker Average Daily Min Difference Average Daily Min Pearson Correlation ( r ) Ratio LoA PAtrack Reporting Sedentary 445 93393 52 520 302 81 % Underreports Light 144 73295 139150 0 052143 % Overreports Moderate 93 2556 80 370 211 208 % Underreports Vigorous 37 197 1 14 300 077202 % Underreports Moderately Vigorous 131 3563 83 680 282 163 % UnderreportsPA indicates physical activity. LoA indicates limits of agreement.*P <. 01 Table 2 Comparisons Between the Data Collected by PAtracker and the PA log Regarding Daily Average Time Spent in Various Body Positions and PA Types During US Army Basic Combat Training.MeasurePAtracker Average Daily Min PA Log Average Daily Min Difference Average Daily Min Pearson Correlation ( r ) 95 % LoA (mins/day) Ratio LoA PA Log Reporting Stand 432 119180 57 2520 144 79 % Underreports Sit 255 108287 66320 186 227 3 Underreports Walk 78 69129 44510 198 145 0 Underreports Run 10 1336 16260 268 153 % Underreports Menial Chores 212 12726 14 1860 033209 % Underreports Calisthenics 29 2559 35300 150 177 % Overreports Carry Load 755 81139 66 6740 04065 % UnderreportsPA indicates physical activity. LoA indicates limits of agreement.*P <. 01 MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING: A COMPARISON OF 3 METHODS

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October – December 2013 53THE ARMY MEDICAL DEPARTMENT JOURNAL Disagreement was also observed between the PAtracker and daily PA log for both PA type and body position for some categories. The difference between the observer’s perception and a recruit’s recollection of time spent in various body positions and types of PA may have contributed to the lack of agreement between these 2 measurement instruments. The differences between interpretations of operational de nitions by an observer and a recruit may have also contributed to the disagreement. When compared with other PA studies that used one instrument alone, such as a pedometer for step counts or an accelerometer for intensity, the combined use of the PAtracker and daily PA log added to the characterization of PA in the BCT environment.13,14 The use of both of these measurement instruments provided greater detail regarding the amount of time a recruit spent in different body positions and PA types, possible contributing factors in the incidence of musculoskeletal injuries during BCT. A careful overview of the strengths and limitations of all available techniques is essential before an appropriate assessment method for a speci c research question is chosen.15 The method of choice for any environment should be accurate, precise, objective, simple to use, robust, time-ef cient, cause minimal intrusion into habitual activity patterns, be socially acceptable, allow continuous and detailed recording of usual activity patterns, and be applicable to large population groups.16 In this study, the ActiGraph accelerometer provided the best measure of a recruit’s PA intensity while the PAtracker and daily PA log were best at capturing body position and type of PA in the BCT environment. RELEVANCE TO PERFORMANCE TRIAD The Army Surgeon General’s Performance Triad initiative seeks to improve Soldier readiness and resilience by improving Soldiers’ PA, sleep, and nutritional health behaviors. The ability to assess the quantity as well as the quality of current PA demands (PA type, body position, PA intensity, and load carried), and recovery (rest and sleep) from PA are necessary Figure 4. Bland-Altman plots of time spent sitting each day between the PAtracker and PALog methods.Legend: Mean bias line (31.7) Random error lines (259, -195) 0 100 200 300 400 500 600 0 100 200 300 400 500 -500 -400 -300 -200 -100 600Average of the 2 Measurements (min/day)Difference of the 2 Measurements (min/day) Figure 5. Bland-Altman plots of time spent walking each day between the PAtracker and PALog methods.Legend: Mean bias line (74.0) Random error lines (196, -93) 0 50 100 150 200 250 300 0 100 200 300 -500 -400 -300 -200 -100Difference of the 2 Measurements (min/day)Average of the 2 Measurements (min/day)

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54 http://www.cs.amedd.army.mil/amedd_journal.aspx to ensure Soldier safety along with optimal health and performance. The ndings of this study suggest that in order to understand the current demands of PA in BCT, it is necessary to use a combination of self-report, direct observation, and electronic motion detection measurement instruments. ACKNOWLEDGEMENTThis study was funded by the US Army Medical Research and Materiel Command and the Defense Safety Oversight Council.REFERENCES1. Butte NF, Ekeland U, Westerterp KR. Assessing physical activity using wearable monitors: measures of physical activity. Med Sci Sports Exerc 2012;44(1)(suppl 1):S5-S12. 2. Wyss T, Mader U. Recognition of military speci c PA with body xed sensors. Mil Med 2010;175(11):858-864. 3. Malina RM, Bouchard C, Bar-Or O. Growth, Maturation, and Physical Activity. 2nd ed. Champaign, IL: Human Kinetics 2004:457-477. 4. Valanou EM, Bamia C, Trichopoulou A. Methodology of physical-activity and energy expenditure assessment: a review. J Public Health 2006;14:58-65. 5. Jacobs DR, Ainsworth BE, Hartman T, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc 1993;25(1):81-91. 6. Army Regulation 70-25: Use of Volunteers as Subjects of Research Washington, DC: US Dept of the Army; January 25, 1990. 7. Freedson PS, Melanson E, Sirard J. Calibration of the Computer Science and Applications, Inc. accelerometer. Med Sci Sports Exerc 1998;30(5):777-781. 8. McKenzie TL. Use of direct observation to assess physical activity. In: Welk GJ, ed. Physical Activity Assessment for Health-related Research Champaign, IL: Human Kinetics; 2002:179-195. 9. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307-310. 10. Bland, JM, Altman DG. Applying the right statistics: analyses of measurement studies. Ultrasound Obstet Gynecol 2003;22(1):85-93. 11. Atkinson G, Nevill AM. Statistical methods for assessing measurement error (reliability) in variables relevant to sports medicine. Sports Med 1998;26(4):217-238. 12. Wood TM. Issues and future directions in assessing physical activity: An introduction to the conference proceedings. Res Q Exerc Sport 2000;71:ii-vii. 13. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin R, Jones BH. Ambulatory physical activity during United States Army basic combat training. Int J Sports Med 2007;28(2):106-115. 14. Knapik JJ, Hauret KG, Canada S, Marin R, Jones B. Association between ambulatory physical activity and injuries during United States Army basic combat training. J Phys Act Health 2011;8(4):496-502. 15. Vanhees L, Lefevre J, Philippaerts R, Martens M, Huygens W, Troosters T, Beunen G. How to assess physical activity? How to assess physical tness?. Eur J Cardiovasc Prev Rehabil 2005;12(2):102-114. 16. Livingstone MB, Robson PJ, Wallace JM, McKinley M. How active are we? Levels of routine physical activity in children and adults. Proc Nutr Soc 2003;62(3):681-701.AUTHORSDr Redmond, Dr Cohen, Ms Simpson, and Ms Sharp are in the Military Performance Division of the US Army Research Institute for Environmental Medicine, Natick, Massachusetts. Dr Spiering is a Senior Physiologist for the Nike Sport Research Lab, Beaverton, Oregon.MEASURING PHYSICAL ACTIVITY DURING US ARMY BASIC COMBAT TRAINING: A COMPARISON OF 3 METHODS Articles published in the Army Medical Department Journal are indexed in MEDLINE, the National Library of MedicineÂ’s (NLMÂ’s) bibliographic database of life sciences and biomedical information. Inclusion in the MEDLINE database ensures that citations to AMEDD Journal content will be identi ed to researchers during searches for relevant information using any of several bibliographic search tools, including the NLMÂ’s PubMed service.

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October – December 2013 55Army Basic Combat Training (BCT) is a physically demanding, 10-week training program designed to develop basic soldiering skills and prepare recruits for the physical and mental rigors of military service.1-3 Depending on their military occupational specialty, Soldiers may be required to perform a number of tasks involving a high degree of physical effort during their military careers. Therefore, developing and maintaining a high level of physical tness among Soldiers is often regarded as a priority by the US Army.2 While BCT is designed to enhance the physical tness and military performance of the recruit, it also has the potential to produce less positive outcomes. To improve physical tness, the physical activity (PA) performed by recruits must be of the appropriate frequency, intensity, and duration.2,4 If the volume of physical training is too low, it results in little or no change in physical performance, but if the volume is too high, it can lead to injury.2 Previous studies show that as the amount of physical training increases, so does the risk of injuries in a number of populations, including runners,5-12 military recruits,3,13,14 and participants in sports and other leisuretime activities.15,16 Injury among recruits poses a problem for the military in that it can result in signi cant medical expenses, decrease the number of deployable Soldiers, and ultimately compromise military readiness.2,17,18 To improve the physical tness of Soldiers while also reducing the risk of injury, the Army Physical Fitness School, working with the Army Institute of Public Health, developed a training program known as Physical Readiness Training (PRT).2 The PRT program is a precise series of calisthenics, dumbbell drills, climbing drills, running, and other activities that are performed by recruits 3-6 times per week, typically between 5 AM and 7 AM.2 One of the major principles of PRT is that exercise intensity should increase progressively over time by increasing the number of repetitions of some exercises and/or the speed at which some exercises are performed Quantification of Physical Activity Performed During US Army Basic Combat TrainingKathleen Simpson, MS Barry A. Spiering, PhD Jan E. Redmond, PhD Ryan Steelman, MS Bruce S. Cohen, PhD Joseph J. Knapik, ScD Nathan R. Hendrickson, MS Marilyn A. Sharp, MSABSTRACT Purpose: During US Army Basic Combat Training (BCT), graduation requirements, including physical readiness training (PRT), are standardized across training sites. However, there are concerns that the standardization may not be closely followed. Therefore, the purpose of this study was to measure and compare physical activity (PA) performed by recruits at 2 Army BCT sites. Methods: Twenty-four recruits per company from 11 companies (n=144 at Fort Jackson, SC; n=120 at Fort Sill, OK) wore an accelerometer and completed a daily PA log. The PA of one recruit from each company was recorded using an Army-developed direct observation tool (PAtracker). Amounts of time spent in various activity types, intensities, body positions, and in carrying external loads were obtained from the accelerometer, PA log, and PAtracker. Independent samples t tests were used to compare PA percentage time (%T) across training sites. Repeated measures analysis of variance was used to examine weekly differences in time spent in moderate to vigorous intensity PA during morning PRT. Results: Physical activity was measured for 47 days at Fort Jackson and 44 days at Fort Sill. Differences in the percentage of time spent in various physical activities between the 2 sites ranged from 0.4% to 15.3% (2.0-93.7 minutes). At Fort Jackson, time spent in moderate to vigorous PA during PRT signi cantly increased each week for the rst 4 to 6 weeks of BCT. No difference was observed in PAtracker data between the 2 training sites in the percentage of time recruits spent in calisthenics (3.9%3.6% vs 3.8%3.0%, P =.700), and only a small difference was observed in percentage of time recruits spent running (1.2%1.7% vs 1.6%2.0%, P =.037).Conclusion: Army recruits at the 2 BCT sites spent similar amounts of time in each PA variable, regardless of the training site and measurement method.

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56 http://www.cs.amedd.army.mil/amedd_journal.aspx(progressive overload). Compared to traditional BCT physical training programs, PRT has been shown to result in the same or greater improvements in physical tness while causing fewer injuries.2,19 In addition to PRT, BCT recruits are also required to perform other physical activities such as obstacle course negotiation, ri e training, unarmed combat (combatives) training, drill and ceremony, land navigation, and road marches with rucksacks and other load-bearing equipment.1,3Although knowledge of the types of activities performed is available, information regarding the exposure of new recruits to PA (ie, the actual dose) at each of the 4 BCT sites is lacking. Additionally, although the graduation requirements of BCT are identical across training sites, battalions, and companies,20 the amount of time needed to teach speci c soldiering skills may vary. Finally, although doctrine requires that PRT and training for military skill development be standardized across BCT sites, there are concerns that the standardization may not be closely followed. Therefore, the purposes of this study were to (1) characterize and quantify the amount of PA actually performed by recruits during a BCT cycle at 2 of the Army’s 4 BCT sites, and (2) determine the intensity and types of physical training at the 2 locations. One of the principles of PRT is progressive overload (progressive, systematic increase in exercise intensity over days), so the average weekly intensity of physical training between 5 AM and 7 AM (when physical training was likely to be conducted) was examined. METHODSSubjectsData for this study were collected from recruits in 2 training battalions during separate 10-week BCT cycles. The rst iteration took place June to August 2010 at Fort Jackson, South Carolina, during which time recruits from 6 training companies were observed. The second iteration took place July to September 2011 at Fort Sill, Oklahoma, during which time recruits from 5 training companies were observed. Prior to the start of the study, the principal investigator informed the recruits in all training companies of the requirements and potential risks of participating in the study. Those who chose to volunteer signed an informed consent document approved by the Institutional Review Board of the US Army Research Institute of Environmental Medicine (USARIEM). The investigators followed the policies for protection of human subjects as prescribed in Army Regulation 70-25 ,21 as well as the provisions of 45 CFR Part 46, Protection of Human Subjects.22 Recruits were included in the study if they were at least 18 years of age, were assigned to one of the study battalions for the 10-week BCT course, and were able to fully participate in all the activities of BCT at the start of the investigation. ProceduresThe length of a typical BCT cycle is 10 weeks. In this study, study personnel spent the rst week of each BCT cycle recruiting volunteers and obtaining their consent. During the last week, recruits spent most of their time cleaning and turning in equipment, and practicing for graduation. Therefore, complete data was obtained for the majority of volunteers for the middle 8 weeks of their BCT cycle. Physical activity was assessed by 3 methods: instrumentation with an accelerometer, direct observation, and daily PA logs.AccelerometerThe accelerometer used in this study was the ActiGraph GT3X triaxial accelerometer (ActiGraph, LLC, Pensacola, FL). The accelerometer senses acceleration along 3 axes: vertical, anterior-posterior, and mediolateral. The accelerometer output is then recorded in “counts,” which are the summation of the absolute values of the sampled changes in acceleration measured during a user-de ned time period. The accelerometer has previously been shown to be a valid and reliable tool for measuring PA intensity among adults.23,24At the beginning of each BCT cycle, recruits received both written and verbal instructions on how to wear the accelerometer: over their left hip in a pouch on a belt, Monday through Saturday, during most of the BCT cycle. Since Sundays were typically reserved for religious observance and rest rather than training, recruits were not asked to wear the accelerometer on this day. If a recruit who had been selected to wear the accelerometer became injured, ill, or was separated from the platoon for a portion of the day (Monday–Saturday), that recruit was replaced with another from the same training company. Research staff performed compliance checks to ensure all volunteers wore the devices properly. Research staff distributed the accelerometers to participants before the rst formation each morning and collected them near the end of training each day, usually preceding the evening meal. This allowed for equipment accountability, data downloading, and battery recharge. From the accelerometers, daily time (minutes) each recruit spent in sedentary-, light(<3metabolic equivalent (MET)), moderate(3-6 MET), and vigorous-intensity (>6 MET) activities was categorized by means of the QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED DURING US ARMY BASIC COMBAT TRAINING

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October – December 2013 57THE ARMY MEDICAL DEPARTMENT JOURNAL Freedson categories, which de ne sedentary or light-intensity activity as 0 to 1,951 counts/minute, moderate PA as 1,952 to 5,724 counts/minute, and vigorous intensity PA as 5,725 or more counts/minute.25Direct ObservationThe direct observation portion of this study employed the continuous duration recording method. Trained observers recorded changes in a recruit’s PA as the change in activity occurred.24 A novel PA tracking software (PAtracker), designed speci cally for this type of direct observation and developed jointly by L3-Communications (San Diego, CA) and the USARIEM, was used in this study. The PAtracker software was installed on smartphone devices. Trained observers logged a recruit’s PA by selecting it from a predetermined menu on a touch-sensitive screen. The software automatically added a time stamp and recorded the data in each activity to a data le. Within the PAtracker software, PA was coded by body position, intensity, activity type, and external load. Body positions included kneeling, lying, sitting, and standing. Activity types included stationary, menial tasks, walking, calisthenics, cadence marching, combatives, running, obstacles/climbing, crawling, and lifting/carrying. Physical activity was also classi ed by intensity (sedentary, light, moderate, vigorous) and load carried (0-10 lbs, 10-25 lbs, 25-50 lbs, 50-75 lbs, or >75 lbs). Observers recruited from the local BCT geographic area were hired to perform the direct observation portion of this study. Prior to the start of the study, all observers completed training (10 hours over 3 consecutive days) on the use of the PAtracker device as well as the body positions, activity types, loads, and intensities they would observe during the study. Direct observation commenced at the beginning of each training day when recruits received their accelerometers, and all activities during the day were recorded. Within each company, a single recruit who was wearing an accelerometer was followed and observed by one trained observer. If this recruit was not training that day, another recruit wearing an accelerometer was identi ed and followed. Although individual recruits in each company were observed, the direct observation data were treated as unit data re ective of the PA performed by the entire company. Daily Physical Activity LogAt the end of each training day, all recruits wearing an accelerometer completed a daily PA log; they were asked to report the amount of time (hours:minutes) they spent wearing the accelerometer that day as well as the amount of time (hours : minutes) they spent sleeping during the night before. Regarding the time spent wearing the accelerometer that day, recruits were asked to account for how much of that time they spent sitting, standing, walking/marching, and running. Finally, recruits were asked to report the amount of time they spent doing chores or barracks maintenance, doing calisthenics/obstacle courses, and carrying a load. Upon the recruit’s completion of the PA log, a study investigator checked the questionnaire to ensure it had been completed properly and then clari ed any discrepancies by speaking with the recruit.Statistical AnalysesDescriptive statistics (mean SD) were calculated for all study variables. Independent sample t-tests were performed to examine differences between training sites in PA measured by the accelerometer, direct observation, and self-report PA Logs. Repeated measures analysis of variance was used to examine weekly differences in time spent in moderateto vigorous-intensity PA measured by the accelerometer while recruits performed PRT at each training site (between 5 AM and 7 AM). All statistical analyses were performed with IBM SPSS Statistics (V 14.0) software (IBM Corp, Chicago, IL) for Windows with P <.05 established as the level of statistical signi cance. RESULTS Within each of the 11 training companies included in this study, 24 recruits were out tted with an accelerometer and completed a daily PA log. This resulted in a total of 144 recruits at Fort Jackson and 120 recruits at Fort Sill. From each company, 6 recruits from each of 4 platoons totaled 24 recruits from each company (6 recruits/platoon 4 platoons/company=24 recruits/company). When possible, at least one of the 6 recruits from each platoon was a woman.AccelerometerThe Fort Jackson recruits wore the accelerometer a total of 47 days, and the recruits at Fort Sill wore it 44 days. Table 1 lists the cumulative time as well as the number of days that recruits from both training sites spent in each intensity category measured by the accelerometer. On average, recruits at Fort Jackson wore the accelerometer for a longer period of time each day than the recruits at Fort Sill (754.0 112.6 minutes/day vs 677.4 102.6 minutes/day, P <.001). Therefore, all accelerometer comparisons between the two training sites in this study were made using the average daily percentage of time. The exception was time spent in moderateto vigorous-intensity PA between 5 AM and 7 AM, which

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58 http://www.cs.amedd.army.mil/amedd_journal.aspxwas examined using average daily minutes. This variable was an exception because weekly changes were examined at each training site as opposed to being compared between the 2 training sites. Figure 1 shows the average daily percentage of time that recruits from each training site spent in each activity intensity over the course of the BCT cycle. Recruits at Fort Jackson spent a larger percentage of their time engaged in lightintensity activities (23.0% 10.4% vs 15.8% 2.0%, P <.001) and a smaller percentage of their time in sedentary activities (58.9% 10.6% vs 65.9% 4.9%, P <.001) when compared to recruits at Fort Sill. Additionally, recruits at both training sites spent most of their time (60% to 70%) in sedentary activities and less time (<10%) in vigorous activities. Figure 2 shows the average daily percentage of time that recruits at both training sites spent in moderateto vigorous-intensity activity between 5AM and 7AM, when recruits were likely participating in PRT. Over the course of BCT, recruits at Fort Jackson spent an average of 46.1 4.9 minutes/day while recruits at Fort Sill spent an average of 44.4 3.8 minutes/day participating in moderateto vigorous-intensity PA between 5AM and 7AM ( P=. 443). Repeated measures analysis of variance indicated that time spent in moderateto vigorous-intensity PA changed week to week at Fort Jackson ( P=. 009) but did not signi cantly change week to week at Fort Sill ( P=. 211). PAtrackerTable 2 shows the number of days trained observers followed and observed recruits using the PAtracker. Table 2 also lists the average daily time recruits from both training sites spent in each body position, activity type, intensity, and carrying various external loads, as measured with the PAtracker. Recruits were followed with the PAtracker an average of 783.4 135.3 minutes/day for 47 days at Fort Jackson and 708.9 128.5 minutes/day for 44 days at Fort Sill ( P <.001). As was the case with the accelerometer, the recruits at Fort Jackson were observed with the PAtracker for a longer period of time each day than were the recruits at Fort Sill. Therefore, all PAtracker comparisons between the 2 training sites in this study were made using the average daily percentage of time. The average daily percentage of time recruits at Fort Jackson and Fort Sill spent in each body position is shown in Figure 3A. Recruits at Fort Jackson spent a larger percentage of time sitting (38.6% 12.9% vs 30.9% 11.8%, P <.001) and a smaller percentage of time kneeling (1.2% 1.8% vs 1.9% 2.6%, P <.001) and standing QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED DURING US ARMY BASIC COMBAT TRAINING Table 1. Cumulative time recruits at both training sites spent in each Activity Intensity category measured by the ActiGraph during a Basic Combat Training cycle. Days represent the total number of days recruits spent in an intensity at least once.Fort JacksonFort Sill Days Recorded 4744 Total Time Recorded (minutes/hours) 28,256.21,458.5/5470.924.329,597.6596.2/493.39.9 DaysTime (minutes)Time (hours)DaysTime (minutes)Time (hours) Sedentary 4720,847.5702.7347.511.74419,667.71,558.6327.826.0 Light 478,193.6512.8136.68.5444,687.6217.378.13.6 Moderate 474,799.5360.880.06.0443,624.3357.660.46.0 Vigorous 471,602.0313.226.75.2441,827.4207.930.53.5 80% 70% 60% 50% 40% 30% 20% 10% 0% Fort Jackson Fort SillSedentary*Light*ModerateVigorousAverage Daily Percentage of TimeActivity Intensity Figure 1. Average daily percentage of time (SD) recruits spent in each activity intensity measured with the accelerometer.*Fort Jackson vs Fort Sill: P <.05

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October – December 2013 59THE ARMY MEDICAL DEPARTMENT JOURNAL (57.0% 12.6% vs 64.0% 12.2%, P <.001) compared with recruits at Fort Sill. Little difference was observed in the percentage of time recruits at both training sites spent lying down (2.9% 3.4% vs 3.1% 2.1%, P=. 951). Figure 3B shows the average daily percentage of time recruits at Fort Jackson and Fort Sill spent in each activity intensity category. Recruits at Fort Jackson spent a larger percentage of time sedentary (54.5% 18.1% vs 48.2% 22.6%, P=. 001) and a smaller percentage of time in light-intensity activities (36.5% 15.5% vs 44.1% 21.8%, P <.001) when compared to recruits at Fort Sill. Little difference was observed between the 2 training sites in terms of percentage of time spent in moderate(8.0% 11.9% vs 6.8% 7.3%, P=. 193) or vigorous(1.1% 2.3% vs 0.9% 1.9%, P=. 290) intensity activities. As was the case with the accelerometer, recruits at both training sites spent a large percentage of time (about 50%) in sedentary activities and a small percentage of time (about 1%) in vigorous-intensity activities. Figure 4 shows the average daily percentage of time recruits at both Fort Jackson and Fort Sill spent in different types of activities. Recruits at Fort Jackson spent a larger percentage of time engaging in combatives (1.6% 4.0% vs 0.4% 2.0%, P <.001), being stationary (55.1% 14.3% vs 41.8% 16.8%, P <.001), and walking (11.6% 8.5% vs 8.6% 9.7%, P <.001), and a smaller percentage of time cadence-marching (3.3% 3.3% vs 4.7% 4.0%, P <.001), completing obstacles (0.5% 2.1% vs 1.1% 4.0%, P=. 030), performing menial tasks (22.3% 15.0% vs 37.6% 17.9%, P <.001), and running (1.2% 1.7% vs 1.6% 2.0%, P=. 037) when compared to recruits at Fort Sill. Little difference was observed between the 2 training sites in terms of percentage of time recruits spent in calisthenics (3.9% 3.6% vs 3.8% 3.0%, P=. 700), crawling (0.2% 1.1% vs 0.1% 0.3%, P=. 102), and lifting/carrying (0.2% 0.9% vs 0.3% 0.8%, P=. 097). The average daily percentage of time recruits at both training sites spent carrying various external loads over the course of a BCT cycle is shown in Figure 5. Recruits at Fort Jackson spent a larger percentage of time carrying 0-10 lbs (84.0% 19.0% vs 79.6% 19.7%, P=. 011) and a smaller percentage of time carrying 25-50 lbs (3.5% 7.5% vs 9.7% 13.6%, P <.001) and 50-75 lbs (0.2% 1.2% vs 1.0% 3.2%, P <.001). Little difference was observed between the two training sites in terms of percentage of time recruits spent carrying 10-25 lbs (12.2% 16.6% vs 9.6% 14.8%, P=. 066) or greater than 75 lbs (0.1% 0.3% vs 0.2% 1.3%, P=. 064). Recruits at both training sites spent a large percentage of time (about 80%) carrying 0-10 lbs and a very small percentage of time ( 1%) carrying over 50 lbs.Physical Activity LogTable 3 lists the cumulative time (hours and minutes) recruits from both training sites reported sitting, standing, walking, running, participating in calisthenics, doing chores, and carrying loads, based on their daily PA logs. Recruits at Fort Jackson accounted for an average of 601.1 52.5 minutes/day for 47 days, while recruits at Fort Sill accounted for an average of 672.7 28.3 minutes/day for 44 days ( P <.001). Recruits at Fort Sill accounted for a longer period of time each day than recruits at Fort Jackson did. Therefore, all PA Log comparisons between the 2 training sites in this study were Average Time (minutes) During PRTTraining Week 70 75 60 65 50 55 40 45 30 35 20 25 15 10 8 7 6 5 4 3 29 Fort Jackson Fort Sill Figure 2. Average time (meanSD) by training week that recruits spent in moderate to vigorous intensity physical activity between 5 AM and 7 AM as measured with accelerometers.

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60 http://www.cs.amedd.army.mil/amedd_journal.aspxmade using the average daily percentage of time, with the exception of time spent sleeping each night. The average daily percentage of time recruits from both training sites reported sitting, standing, walking, and running is shown in Figure 6. Recruits at Fort Jackson reported spending a larger percentage of time sitting (48.7% 13.6% vs 42.2% 5.7%, P <.001) and walking (21.8% 8.7% vs 18.5% 2.7%, P <.001), and a smaller percentage of time standing (24.0% 7.3% vs 33.5% 4.8%, P <.001) and running (5.4% 3.2% vs 5.9% 1.5%, P=. 034) than recruits at Fort Sill. Over the course of BCT, recruits at Fort Jackson reported spending less time sleeping each night than recruits at Fort Sill (364.7 41.1 minutes/night vs 376.6 17.5 minutes/night, P <.001). Recruits at Fort Jackson also reported spending a larger percentage of time doing chores (4.5% 2.8% vs 3.8% 1.3%, P=. 002), performing calisthenics (10.0% 7.7% vs 8.6% 2.5%, P=. 006) and carrying loads (16.9% 12.8% vs 7.9% 2.4%, P <.001) than recruits at Fort Sill. COMMENT To the best of our knowledge, this study was the rst to characterize and quantify the amount of PA recruits actually perform during BCT conducted at 2 different training sites. The results of this study revealed that although there were some differences between the 2 sites in terms of the PA performed, these differences were QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED DURING US ARMY BASIC COMBAT TRAINING Table 2. Cumulative time recruits at both training sites spent in each body position, activity type, activity intensity, and carrying each external load, as measured by the PAtracker during a Basic Combat Training cycle. Days represent the total number of days recruits participated in each body position, activity type and intensity, and carried each load at least once.Fort JacksonFort Sill Days Observed 4744 Time Observed (minutes/hours) 36,463.28,444.3/607.7140.730,367.28,884.3/506.1148.1 DaysTime (minutes)Time (hours)DaysTime (minutes)Time (hours) Body Position Kneeling34409.2172.76.82.937602.5252.210.04.2 Lying371,071.8284.017.94.737943.0184.915.73.1 Sitting4713,187.21,193.8219.819.9449,374.11,056.5156.217.6 Standing/On Feet4719,216.3476.2320.37.94419,447.61,752.5324.129.2 Varying412,578.6344.243.05.7NANANA Activity Type Cadence March391,195.6325.019.95.4401,414.6210.323.63.5 Calisthenics381,391.9146.623.22.4391128.446.518.80.8 Combatives12559.6155.39.32.64113.575.91.91.3 Crawl763.475.21.11.3516.57.20.30.1 Lifting/Carrying1271.150.41.20.81397.862.81.61.0 Menial Tasks477925.0495.2132.18.34411,335.92,180.3188.936.3 Obstacle/Climbing7181.055.73.00.98302.438.85.00.6 Run33427.791.17.11.531479.758.88.01.0 Stationary4720,402.91,510.9340.025.24412,871.72,922.4214.548.7 Walk474,244.9720.970.712.0442,606.8435.243.47.3 Intensity Sedentary4719,995.72902.8333.348.44414,604.63,835.6243.463.9 Light4713,126.81325.2218.822.14413,506.03,380.0225.156.3 Moderate442,975.91333.249.622.2402,018.7238.133.64.0 Vigorous25360.6105.06.01.718238.0151.34.02.5 External Load 0-10 lbs4730,533.12282.2508.938.04424,323.4859.1405.414.3 10-25 lbs364,585.41461.476.424.4282,869.61,416.347.823.6 25-50 lbs191,266.6588.321.19.8302,796.2628.646.610.5 50-75 lbs470.057.01.20.97322.1226.85.43.8 >75 lbs38.011.20.10.2455.968.30.91.1

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October – December 2013 61THE ARMY MEDICAL DEPARTMENT JOURNAL small, for the most part, and likely have little practical importance. Furthermore, it appeared that the intensity and types of PA were similar at the 2 sites. Quantification of Physical ActivityThe major purpose of this study was to characterize and quantify the PA performed by recruits during the middle 8 weeks of BCT and determine whether or not there were differences in PA between the training sites. The PA performed by recruits was characterized and quanti ed using accelerometry, direct observation, and daily PA logs. Despite statistical signi cance, the differences in PA observed between the 2 BCT sites were small. The magnitude of the differences between sites can be appreciated by examining the range of differences (lowest and highest) in the amount of time recruits spent in various physical activities. From the accelerometer, the lowest difference was 7% (3.4 minutes) for sedentary activities, and the highest difference was 7.2% (67.8 minutes) for light-intensity activities. From the PAtracker, the lowest difference between the 2 training sites was 0.4% (2 minutes) for running, and the highest difference was 15.3% (93.7 minutes) for menial tasks. From the PA log, the lowest difference between the 2 training sites was 0.5% (7.2 minutes) for running and 9.0% (50.3 minutes) for carrying loads. This result suggests that Army BCT recruits spent similar amounts of time in each PA intensity, activity type, body position, and carrying various external loads at the 2 locations tested. Whether or Standing Sitting LyingKneeling *80% 70% 60% 50% 40% 30% 20% 10% 0% Fort Jackson Fort SillAverage Daily Percentage of TimeBody Position Sedentary Light ModerateVigorous80% 70% 60% 50% 40% 30% 20% 10% 0% Fort Jackson Fort SillAverage Daily Percentage of TimeIntensity Figure 3. Average daily percentage of time that recruits spent in various body positions (A) and intensities of physical activi ty (B) as measured with the PAtracker.*Fort Jackson vs Fort Sill: P <.05 A B Table 3. Cumulative time (meanSD) recruits at both training sites spent in various physical activities, as reported on the daily PA logs during a Basic Combat Training cycle. Days represent the total number of days recruits participated in each variable at least once.Fort JacksonFort Sill Days Self-reported 4744 Time Self-reported (minutes/hours) 28256.21458.5 / 470.924.329597.6596.2 / 493.39.9 DaysTime (minutes)Time (hours)DaysTime (minutes)Time (hours) Sit 4713,672.71,620.9227.927.04412,430.81,296.4207.221.6 Stand 476,848.0743.8114.112.4449,907.61,233.9165.120.6 Walk/March 476,204.51,204.6103.420.1445,506.4392.291.86.5 Run 471,531.0263.625.54.4441,752.8238.929.24.0 Sleeping 4717,140.7985.7285.716.44416,569.4567.7276.29.5 Chores/Maintenance 431,256.7323.420.95.4441,135.4321.518.95.4 Calisthenics/Obstacle Course 452,795.5669.046.611.2442,532.8473.742.27.9 Carrying Load 46 4,857.81,738.481.029.0442,336.0289.238.94.8

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62 http://www.cs.amedd.army.mil/amedd_journal.aspxnot this result applies to all BCT sites will need to be determined with future studies. In terms of intensity, the results of this study were the same regardless of the technique used to measure PA intensity (for example, accelerometer or direct observation). Recruits at both training sites spent a very large percentage of time sedentary (about 80%) and a very small percentage of time in vigorous-intensity activities (about 5%). Between the training sites, there was little difference in the percentage of time recruits spent in moderateor vigorous-intensity PA. These results further support the idea that the intensity of PA at each training site was similar. External loads carried by recruits were obtained from direct observation (PAtracker). Recruits from both training sites spent a very large percentage of time (roughly 80%) either unloaded or carrying very light loads (0-10 lbs) and a very small percentage of time carrying loads weighing over 50 lbs (1%-2%). During their military service, Soldiers may be expected to carry extremely heavy loads for long distances over various types of terrain.27 Current US Army doctrine recommends that Soldiers carry no more than QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED DURING US ARMY BASIC COMBAT TRAININGAverage Daily Percentage of TimeActivity Type Combatives Calisthentics Crawl Stationary Menial Tasks Cadence Obstacles/ Climbing Lift/ Carry Walk Run 80% 70% 60% 50% 40% 30% 20% 10% 0% Fort Jackson Fort Sill Figure 4. Average daily percentage of time that recruits spent in various activity types as measure with the PAtracker.*Fort Jackson vs Fort Sill: P <.05 External Load Fort Jackson Fort Sill80% 100% 120% 40% 20% 0% 60%0-10 lbs*>75 lbs 10-25 lbs25-50 lbs*50-75 lbs*Average Daily Percentage of TimeFigure 5. Average daily percentage of time that recruits spent in various activity types as measured with the PAtracker.*Fort Jackson vs Fort Sill: P <.05

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October – December 2013 63THE ARMY MEDICAL DEPARTMENT JOURNAL 48-72 lbs (or 30%-45% of their body weight) in the ghting load and approach march loads, respectively.28,29 Recruits at both training sites had some training in heavy loads, providing further evidence that the PA performed at each training site was similar. Using the daily PA log, recruits from both training sites reported getting an average of about 6 hours of sleep each night. Current Army doctrine mandates that recruits be given the opportunity to receive 7 hours of continuous sleep each night while in garrison unless they are scheduled for duty.20 The results of this study suggest that although they may be allowed the full 7 hours, BCT recruits at both training sites reported getting slightly less than the recommended amount of sleep. Additionally, the self-reported amount of sleep in this study is similar to the results of a previously published study in which US Military Academy cadets reported receiving an average of 5 hours and 40 minutes of sleep per night during the 6 weeks of cadet basic training.30 The current study’s ndings indicate that recruits received the same, or similar, amounts of recovery time regardless of the training site to which they were assigned. Physical Training Intensity and TypeThe second purpose of this study was to examine the intensity and types of physical training over the course of BCT. Intensity was examined to determine whether the principle of progressive training (progressive overload), one of the major principles of PRT, was being followed.31 The PRT program consists of a variety of standardized exercises (such as preparatory drills, conditioning drills, movement drills, climbing drills, interval running, long distance running, and exibility training) and is designed to progressively train Soldiers while reducing the risk of developing injuries.2,19 The results of this study show time spent in moderateto vigorous-intensity PA between 5AM and 7AM (when recruits were presumably engaged in PRT) tended to increase during the rst 4 weeks of BCT at Fort Jackson (Figure 2). Although there was no signi cant difference in the weekly moderateto vigorous-intensity activity at Fort Sill, the graph does show a gradual increase, the slope of which is much lower than that shown for Fort Jackson. This suggests some increase in exercise intensity but perhaps not enough to be consistent with the progressive overload principle. After week 4 (Fort Jackson) or week 7 (Fort Sill), the amount of time recruits spent in moderateto vigorous-intensity PA from 5 AM to 7 AM at both training sites tended to decrease. This decrease could be related to increased time spent in military operations (road marching, basic ri e marksmanship, land navigation, eld training exercises, etc). When physically demanding activity was scheduled, physical training was either reduced or was not conducted at all in the early morning. The more physically demanding operational soldiering tasks are generally conducted later in training. Over the course of the 8-week BCT monitoring period, the average daily percentage of time recruits spent engaging in calisthenics was not signi cantly different between the training sites. The average daily time spent running differed slightly; however, this difference was not large. Although we cannot determine from these data if the speci c drills of PRT were followed, it appears that the amount of time spent in these general activities was similar at the 2 sites. Strengths and LimitationsThis study was limited by the fact that recruits were only observed during the middle 8 weeks of training as opposed to the entire 10 weeks. Eliminated were the rst week of BCT, which consists mostly of classroom training; and the nal week, consisting primarily of cleaning equipment, completing paperwork, and preparing for graduation. We also did not monitor the evening activities of the recruits (after the evening meal, generally after 1800). Thus, we missed some of the activities performed by recruits, but previous observations suggested that there was little PA taking place in the evening hours.1,3 Fort Jackson Fort Sill50% 30% 40% 20% 60% 70% 10% 0% 80%Stand Walk Run Sit *Average Daily Percentage of TimeFigure 6. Average daily percentage of time that recruits spent sitting, standing, walking, and running as reported in the daily PA logs.*Fort Jackson vs Fort Sill: P <.05

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64 http://www.cs.amedd.army.mil/amedd_journal.aspxDue to limited personnel and resources, we were unable to instrument and observe all recruits in each training company. Therefore, the PA performed by the 24 recruits per company who were instrumented with an accelerometer and the 1 recruit per company who was followed and observed using the PAtracker was assumed to be representative of the PA performed by all recruits in each respective company. If a recruit wearing an accelerometer or being observed using the PAtracker was sick, injured, or not training with his or her company that day for any reason, that recruit was immediately replaced with another consented volunteer. Due to study design, a limitation to this process was the number of times recruits had to be replaced, which was not tracked. However, since recruits were immediately replaced, the appropriate number of accelerometers was always distributed, and one recruit per company was observed. Therefore, data was never lost due to attrition. This study also used multiple methods of measuring PA, including accelerometry, direct observation, and self-report questionnaires, all of which allowed study investigators to capture a good quality representation of the PA actually performed by recruits during BCT. Additionally, the standardization of activities during BCT enabled investigators to ensure that recruits lled out the daily PA log each day. RELEVANCE TO PERFORMANCE TRIAD The Army Surgeon GeneralÂ’s Performance Triad initiative seeks to improve Soldier readiness and resiliency by improving the activity, sleep and nutritional aspects of Soldier health behaviors. This study examined the activity and sleep aspects of the Performance Triad. Physical activity is an important variable to support health and improve performance. It is important to document the physical demands of the training program followed during BCT in order to ensure that the activities performed are suf cient for developing the SoldierÂ’s tness, but not so excessive that the demands lead to the development of musculoskeletal injuries, a key barrier to individual and unit readiness. Additionally, these data suggest recruits during BCT are meeting the minimum PA recommendations for healthy adults set forth by the American College of Sports Medicine.32In terms of sleep, these data suggest that recruits are receiving slightly less than the recommended 7-8 hours per night during BCT, despite being allotted 7 hours each night to devote to sleep. This lack of rest and recovery during BCT may adversely impact a recruitÂ’s ability to perform his or her job suf ciently and maintain adequate health and resiliency. ACKNOWLEDGEMENT is study was funded by the US Army Medical Research and Materiel Command and the Defense Safety Oversight Council.REFERENCES1. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin R, Jones BH. Ambulatory physical activity during United States Army basic combat training. Int J Sports Med. 2006;28:106-115. 2. Knapik JJ, Rieger W, Palkoska F, Van Camp S, Darakjy S. United States army physical readiness training: rationale and evaluation of the physical training doctrine. J Strength Cond Res. 2009;23(4):1353-1362. 3. Knapik JJ, Hauret KG, Canada S, Marin R, Jones B. Association between ambulatory physical activity and injuries during United States Army basic combat training. J Phys Act Health. 2011;8:496-502. 4. American College of Sports Medicine. The recommended quantity and quality of exercise for developing and maintaining cardiorespiratory and muscular tness, and exibility in healthy adults. Med Sci Sports Exerc. 1998;30:975-991. 5. Pollock ML, Gettman LR, Milesis CA, Bah MD, Durstine L, Johnson RB. Effects of frequency and duration of training on attrition and incidence of injury. Med Sci Sports Exerc. 1977;9:31-36. 6. Koplan JP, Powell KE, Sikes RK, Shirley RW, Campbell CC. An epidemiologic study of the bene ts and risks of running JAMA. 1982;248:3118-3121. 7. Jacobs SJ, Berson BL. Injuries to runners: a study of entrants to a 10,000-meter race. Am J Sports Med. 1986;14:151-155. 8. Blair SN, Kohl HW, Goodyear NN. Rates and risks for running and exercise injuries: studies in three populations. Res Q. 1987;58:221-288. 9. Marti B, Vader JP, Minder CE, Abelin T. On the epidemiology of running injuries. The 1984 Bern Grand-Prix study. Am J Sports Med. 1988;16:285-294. 10. Walter SD, Hart LE, McIntosh JM, Sutton JR. e Ontario cohort study of running-related injuries. Arch Intern Med. 1989;149:2561-2564. 11. Koplan JP, Rothenberg RB, Jones EL. e natural history of exercise: a 10-yr follow-up of a cohort of runners. Med Sci Sports Exerc. 1995;27:1180-1184. QUANTIFICATION OF PHYSICAL ACTIVITY PERFORMED DURING US ARMY BASIC COMBAT TRAINING

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October – December 2013 65THE ARMY MEDICAL DEPARTMENT JOURNAL12. Colbert LH, Hootman JM, Macera CA. Physical activity-related injuries in walkers and runners in the aerobics center longitudinal study. Clin J Sport Med. 2000;10:259-263. 13. Almeida SA, Williams KM, Sha er RA, Brodine SK. Epidemiological patterns of musculoskeletal injuries and physical training. Med Sci Sports Exerc. 1999; 31:1176-1182. 14. Jones BH, Cowan DN, Tomlinson JP, Robinson JR, Polly DW, Frykman PN. Epidemiology of injuries associated with physical training among young men in the Army. Med Sci Sports Exerc. 1993;25:197-203. 15. Carlson SA, Hootman JM, Powell KE, et al. Selfreported injury and physical activity levels: United States 2000-2002. Ann Epidemiol. 2006;16:712-719. 16. Schneider S, Seither B, Tonges S, Schmitt H. Sports injuries: population based representative data on incidence, diagnosis, sequelae, and high risk groups. Br J Sports Med. 2006;40:334-339. 17. Knapik JJ, Graham B, Cobbs J, ompson D, et al. Technical Report No. 12-HF-OF6F-11. e SoldierAthlete Initiative: Program Evaluation of the E ectiveness of Athletic Trainers and Musculoskeletal Action Teams in Initial Entry Training, Fort Leonard Wood, June 2010-December 2011 Aberdeen Proving Ground MD: US Army Institute of Public Health; 2012. 18. Scott SJ, Feltwell DN, Knapik JJ, Barkley CB, Hauret KG, Bullock SH, Evans RK. A multiple intervention strategy for reducing femoral neck stress injury and other serious overuse injuries in United Stated Army basic combat training. Mil Med. 2012;177(9):1081-1089. 19. Knapik JJ, Hauret KG, Arnold S, Canham-Chervak M, Mans eld AJ, et al. Injury and tness outcomes during implementation of physical readiness training. Int J Sports Med. 2003;24:372-381. 20. TRADOC Regulation 350-6: Enlisted Initial Entry Training (IET) Policies and Administration Fort Monroe, VA: US Army Training and Doctrine Command; November 2012. 21. Army Regulation 70-25: Use of Volunteers as Subjects of Research. Washington, DC: US Dept of the Army; January 25, 1990. 22. US National Archives and Records Administration. Code of Federal Regulations Title 45. Public Welfare. 2009. 23. Welk GJ, Schaben JA, Morrow JR. Reliability of accelerometry-based activity monitors: a generalizability study. Med Sci Sports Exerc. 2004;36(9):1637-1645. 24. Crouter SE, Churilla JR, Bassett DR. Estimating Energy Expenditure using Accelerometers. Eur J Appl Physiol. 2006;98:601-612. 25. Freedson PS, Melanson E, Sirard J. Calibration of the computer science and applications, Inc. accelerometer. Med Sci Sports Exerc. 1998;30(5):777-781. 26. McKenzie TL. Use of direct observation to assess physical activity. In: Welk GJ, ed. Physical Activity Assessment For Health-Related Research. Champaign, IL: Human Kinetics; 2002:179-195. 27. Harmon EA, Gutekunst DJ, Frykman PN, Nindl BC, Alemany JA, Mello RP, Sharp MA. E ects of two di erent eight-week training programs on military physical performance. J Strength Cond Res. 2008;22(2):524-534. 28. Field Manual 21-18: Foot Marches. Washington, DC: US Dept of the Army; June 1990. 29. Knapik J, Reynolds K. Load carriage in military operations: a review of historical, physiological, biomechanical, and medical aspects In: Friedl KE, Santee WR, eds. Military Quantitative Physiology: Problems and Concepts in Military Operational Medicine. Fort Sam Houston, TX: e Borden Institute; 2012:303-338. 30. Miller NL, Shattuck LG. Sleep patterns of young men and women enrolled at the United States Military Academy: results from year 1 of a 4-year longitudinal study Sleep. 2005;28(7):837-841. 31. McArdle WD, Katch FI, Katch VL. Exercise Physiology: Energy, Nutrition and Human Performance. Philadelphia, PA: Lea & Febiger; 1991. 32. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor tness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-1359.AUTHORSMs Simpson, Dr Redmond, Dr Cohen, Mr Hendrickson, and Ms Sharp are in the Military Performance Division of the US Army Research Institute for Environmental Medicine, Natick, Massachusetts. Dr Spiering is a Senior Physiologist for the Nike Sport Research Lab, Beaverton, Oregon. Dr Knapik and Mr Steelman are at the US Army Institute of Public Health, US Army Public Health Command, Aberdeen Proving Ground, Maryland.

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66 http://www.cs.amedd.army.mil/amedd_journal.aspxNutrition is a critical element for sustaining Soldier health and performance. Nutritional tness is de ned as the availability and consumption of quality food in appropriate quantities to ensure mission performance and protect against disease.1 Accordingly, the dietary behaviors and intake patterns of a Soldier form the basis of his/ her nutritional tness. Optimal nutrition supports health, an ideal body composition, positive psychological and cognitive status,2-4 and physical readiness.5,6 This is of particular importance since military personnel are often subjected to physical and environmental extremes that demand optimal cognitive, psychosocial, and physical performance.7,8 Thus, an appropriate body composition, high tness, good health, and adequate substrates to fuel cognitive and physical activities can positively impact individual performance and force readiness.9 A healthy diet is a key countermeasure for individuals to ensure optimal body weight and adequate fuels for cognitive and physical activity.10,11Dietary choices and habits affect every aspect of life: physical performance,5,6 cognitive performance,4,12 sleep,13,14 mood,7 and overall health.15-17 The protective effects of fruit and vegetable consumption from diseases have been investigated extensively, yet based on the 2011 Military Survey of Health Related Behaviors, only 11.2% and 12.9% of military personnel met the US Dietary Goals of 3 or more servings of fruits and vegetables per day, respectively.18 These numbers, which are lower than those from the 2008 survey19 and the Healthy Nutrition as a Component of the Performance Triad: How Healthy Eating Behaviors Contribute to Soldier Performance and Military ReadinessDianna L. Purvis, PhD Cynthia V. Lentino, MS Theresa K. Jackson, PhD, MPH Kaitlin J. Murphy, MS Patricia A. Deuster, PhD, MPHABSTRACTObjective: Nutrition is a critical element of Soldier health and performance. Food choices, meal timing, and dietary intake behaviors contribute to nutritional tness. The objectives of this study were to describe Soldier dietary behaviors and quantify the association between healthy eating behaviors and demographic, lifestyle, and psychosocial factors.Methods: The Comprehensive Soldier and Family Fitness Global Assessment Tool (GAT) assesses emotional, social, family, and spiritual tness. In 2012, 57 pilot questions were added to the GAT to create a physical dimension that included nutrition assessments. Participants included 13,858 Active Duty, Reserve, and National Guard Soldiers: 83% male; 85% enlisted; a mean age of 289 years. A Healthy Eating Score (HES-5) was calculated from 5 questions assessing frequency of fruit, vegetable, whole grain, dairy, and sh intake (Cronbach =0.81). Associations between HES-5 and other dietary habits, physical activity patterns, and GAT psychosocial dimension scores were examined.Results: Soldiers who ate breakfast regularly (6 times/week or more), drank 7 servings or more of water/day, and met weekly exercise recommendations were more likely to be in the highest HES-5 quartile than those who did not. Those who passed their Army Physical Fitness Test (APFT) in the top quartile were also more likely to report high HES-5 scores than those who failed ( P <.001). Soldiers with healthy anthropometric measures and the highest emotional, social, family, and spiritual tness scores were also more likely to be in the top HES-5 quartile than those with unhealthy measures and with the lowest tness scores ( P <.001).Conclusion: The HES-5 may be a useful index for characterizing dietary intake behaviors. Healthy dietary intake behaviors are associated with all dimensions of health, physical tness, and psychosocial status.

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October – December 2013 67People 2010 objectives of 75% or more for fruits and 50% or more for vegetables, are also signi cantly lower than those reported for the civilian sector.20 Conversely, excess energy intakes above daily requirements may lead to weight gain, increased adiposity, and adverse health consequences.21,22 A poor diet and the inappropriate use of dietary supplements (DS) can negatively impact human performance and health outcomes.5,6,23,24This study examined lifestyle habits—nutrition behaviors, sleep quality, psychosocial status, health habits, and physical activity—in US Army Soldiers through the introduction of a set of questions added to the Global Assessment Tool (GAT) as part of the Comprehensive Soldier and Family Fitness (CSF2) program, and characterized differences between the healthiest and least healthy eaters. The objectives of this study were (1) to describe Soldiers’ dietary practices using a brief healthy eating score and (2) to evaluate the association between demographic and lifestyle factors affecting performance (eg, sleep quality, physical activity, and various psychosocial measures) with self-reported dietary behaviors. METHODS The CSF2 GAT, an annual requirement for all Soldiers, consists of 105 questions and was developed in part by Seligman et al25 and others26 to assess tness in 4 psychosocial dimensions: emotional, social, family, and spiritual tness.27,28 In 2012, the CSF2 program introduced a physical dimension by adding 57 pilot questions to assess nutrition behaviors, sleep quality, DS use, physical tness, and other lifestyle behaviors. During 2 weeks in July 2012, anyone completing the GAT was directed to the expanded GAT. Upon GAT completion, respondents were informed that physical domain answers would not be included in their overall GAT score, and they were given the option to consent to the use of their GAT responses for further study. The Uniformed Services University of the Health Sciences Institutional Review Board concluded that a full review was not required for this investigation. This study was not classi ed as human subjects research since the CSF2 program provided data stripped of identi cation elements to the Consortium for Health and Military Performance per an established data use agreement.PopulationA total of 14,850 participants completed the CSF2 GAT physical domain pilot questions and consented for their data to be used for further study. Three family members, 599 Department of Defense (DoD) civilians, and 390 participants with missing data were excluded from analyses. Hence, we are reporting data from 13,858 Active Duty, Reserve, and National Guard Soldiers.MeasuresNutrition BehaviorsNutrition behaviors were assessed in the pilot physical GAT domain by means of a 5-question Healthy Eating Score (HES-5). The HES-5 was modi ed from the US Department of Agriculture’s (USDA) Healthy Eating Index.29-32 The Healthy Eating Index, developed in 2005 (HEI-2005) to evaluate if an individual is meeting the 2005 Dietary Guidelines for Americans,31,32 assesses 12 food components (fruit, vegetables, grains, milk/dairy, meat and beans, sh, oils, fats, sodium, and added sugar). The HEI-200529-32 responses are summed for an overall score ranging from 0-100 points,31,32 and the index has been modi ed to assess special populations.33 Since the GAT nutrition behavior questions assessed respondents’ Table 1. Healthy Eating Score-5. Over the last 30 days, how often did you eat/drink the following foods/beverages? (Note: Only a few examples of each category are listed to remind you of the types of foods—many more are possible.)3 or More Times per Day Twice per Day Once per Day3 to 6Times per Week1 or 2Times per Week Rarely or Never FRUIT: fresh, frozen, canned or dried, or 100% fruit juices 543210 VEGETABLES: fresh, frozen, canned, cooked or raw: dark green vegetables (broccoli, spinach, most greens), orange vegetables (carrots, sweet potatoes, winter squash, pumpkin), legumes (dry beans, chick peas, tofu), starchy vegetables (corn, white potatoes, green peas), and other (tomatoes, cabbage, celery, cucumber, lettuce, onions, peppers, green beans, cauliflower, mushrooms, summer squash, etc) 543210 WHOLE GRAINS: rye, whole-wheat, or heavily seeded bread; brown or wild rice; whole-wheat pasta or crackers; oatmeal; corn tacos 543210 DAIRY: regular/whole fat milk; lowor reduced-fat milk (2%, 1%, 0.5% or skim), yogurt, cottage cheese, low-fat cheese, frozen low-fat yogurt, soy milk, or other calcium-fortified foods (orange juice, soy/rice milk, breakfast cereals, etc) 543210 FISH: tuna, salmon, or other nonfried fish 555530Note. Questions and scoring that comprise the Healthy Eating Score-5. Scores were totaled for a range of 0 to 25.

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68 http://www.cs.amedd.army.mil/amedd_journal.aspxdaily intake of fruits, vegetables, whole grains, dairy, and sh, the HEI-2005 was modi ed to create the HES-5. The consumption of health-promoting foods assessed by the HES-5 (Table 1) is typically de cient in military populations, and their consumption does not meet national guidelines.18,19,34 Each HES-5 question represented a subscale score ranging from 0-5, with 5 indicating that the respondent met the USDA dietary recommendation for that measure.35 Thus, the total possible value of HES-5 ranged from 0 to 25. A Cronbach analysis of the 5 subscale scores was used to determine HES-5 reliability36,37; the analysis yielded an internal consistency reliability coef cient of 0.81. Classi cations for Cronbach va ry, but values less than 0.60 are generally considered unacceptable, 0.70 minimally acceptable, and 0.80 very good.37Respondents’ HES-5 scores were then partitioned into quartiles for subsequent analyses. The top quartile consisted of HES-5 scores from 20 to 25, or above the 75th percentile. Scores in the third quartile ranged from 17 to 19, those in the second quartile from 13 to 16, and scores of 12 or lower comprised the lowest quartile, representing the lowest 25th percentile.Additional Physical Domain MeasuresThe GAT physical dimension assessed a variety of lifestyle measures that were dichotomized to indicate healthy versus less healthy behaviors. These measures included the number of days per week on which respondents ate breakfast (6 or more days per week versus 5 or fewer days per week), whether the respondent usually consumed a recovery snack (de ned as a snack eaten within 60 minutes of strenuous exercise and classi ed as yes or no), water intake (7 or more glasses per day versus 6 or fewer glasses per day), consumption of health-promoting supplements (ie, multivitamins and/or mineral supplements with 6 or more ingredients; or single-ingredient supplements such as calcium or iron; classi ed as yes or no), consumption of additional supplements (ie, omega-3 supplements, protein powders; classi ed as yes or no), and consumption of sodas (diet and/or regular; classi ed as yes or no for any soda consumption). Two questions from the Pittsburgh Insomnia Rating Scale (PIRS-2)38,39 were used to assess sleep quality; responses were summed based on scoring guidelines,38 and a threshold of 5 or higher distinguished good sleepers from poor sleepers. This cutoff, although different from the typical PIRS-2 threshold, was established in conjunction with the scale’s authors to yield a more speci c rather than sensitive classi cation of poor sleepers.40 Respondents further answered questions related to their perceived health, weight, and alcohol intake. The 3 speci c questions were: 1. How do you consider your general health? (excellent, good, fair, poor, don’t know; classi ed as “excellent and good” or “fair and poor”) 2. In thinking about your weight, do you consider yourself to be underweight, about the right weight, overweight, obese, don’t know? (classi ed as “about the right weight” versus “overweight or obese”) 3. Have you exceeded 5 alcoholic drinks on any single occasion during the past 3 months? (yes or no). Soldiers’ physical activity was assessed by asking how many times per week they participated in aerobic activity for at least 20 minutes, and the frequency with which they participated in strength or resistance exercise. Responses were classi ed as “met national guidelines” or “failed to meet national guidelines” for both aerobic and strength training, based on the American College of Sports Medicine and Centers for Disease Control and Prevention exercise recommendations.41 Further, each participant entered his or her most recent raw numbers for push-ups, sit-ups, and timed run from the Army Physical Fitness Test (APFT). Based on this information, an additional variable was created to indicate whether the respondent passed or failed his or her APFT based on Army standards.42 A respondent failed the APFT if he or she scored less than 60 in any event. To distinguish top APFT performers, those Soldiers who passed the APFT were additionally placed into quartiles based on the distribution of scores. Lastly, participants self-reported their height in inches, weight in pounds, and waist circumference in inches. Each Soldier’s body mass index (BMI) ((weight in kg)/ (height in m)2) was calculated and classi ed as healthy or unhealthy using 27.5 kg/m2 as the upper limit for a healthy BMI per Army Regulation 600-9 .43 Waist circumference was classi ed as healthy or unhealthy using 35 inches or below as healthy values for females, and 40 inches or below as healthy values for males.44GAT DimensionsThe CSF2 provided composite scores for each original GAT dimension (emotional, social, family, spiritual). Each composite score ranged from 1 to 5, with higher scores indicating higher levels of resilience in each dimension.27,28 Subscores for each dimension were further classi ed into quartiles for subsequent analyses.Statistical AnalysesThe IBM SPSS Statistics software package for Windows, Version 20.0 (IBM Corp, Chicago, IL) was used for all analyses. Using frequency tables and descriptive NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 69THE ARMY MEDICAL DEPARTMENT JOURNAL statistics, the analysis team reviewed data to remove outliers and con rm assumptions for parametric tests. Individual indicators on the HES-5 were examined rst to measure the extent that Soldiers are currently meeting national nutrition guidelines. Next, HES-5 means and standard deviations for various demographic subgroups were calculated. The HES-5 quartiles (the dependent variable, designated as highest [Q4] versus lowest [Q1]) were assessed to characterize the differences in the most healthy and least healthy eaters; binary logistic regression models were used to calculate the odds of being in the highest HES-5 quartile versus the lowest quartile for a variety of predictors. Demographic independent variables included age, gender, active duty status, enlistment status, and marital status. Lifestyle independent variables included dietary behaviors (breakfast, hydration, soda intake, DS use) and physical activity, APFT scores, BMI, waist circumference, and GAT tness dimensions. Reference groups were the “less healthy” as compared to the “more healthy” group. Regarding the 4 original GAT dimensions, only the highest and lowest quartiles were compared, and the lowest quartile served as the reference group. For the APFT analysis, Soldiers who passed the test in the top quartile were compared to those who failed. To adjust for in ated type I error rates associated with multiple binary analyses, a Bonferroni adjustment was applied, ie, the standard type I error rate ( P =.05) was divided by 17 (the total number of logistic regression analyses) to achieve a signi cance level set at P <.003. RESULTSGeneral CharacteristicsDemographic characteristics of the study population and mean HES-5 scores are summarized in Table 2. Subjects were predominately male (83%) and enlisted (85%) with a mean age of 289 years, and mean BMI of 26.64 kg/m2.Dietary RecommendationsFigure 1 shows that 38.7% of participants met the US Dietary Guidelines for fruit intake (at least 2 servings per day); 22.2% met the vegetable recommendation (at least 2 servings per day for females and 3 servings for males); and 16.8% met the whole grain recommendation of at least 3 servings per day. Overall, only 17.3% met the dairy recommendation of at least 3 daily servings, whereas 46.6% met the sh recommendation of at least 2 to 3 servings per week.Healthy Eating Score and Dietary BehaviorsMeans for the HES-5 quartiles are presented in Table 2. The mean HES-5 for this sample was 15.73.4, and persons in the highest HES-5 quartile had a mean of 22.11.8 compared to those in the lowest quartile who had a mean of 8.63.0. Overall, of cers (OR 1.48; 95% CI, 1.29-1.70; P <.001), and single, divorced, or legally separated persons (OR 1.21; 95% CI, 1.10-1.33; P <.001) had greater odds of being in the highest HES-5 quartile when compared to enlisted and married Soldiers. No signi cant associations were noted between highest/lowest HES-5 quartile membership and gender (reference group: male [OR Table 2. Study Sample Demographic Characteristics (N= 13,858 ).FrequenciesHES-5 MeanSD Age, MeanSD (years) 28.29.2 Years Range 17.0-61.0 Age Groups 17 to 29 66.9%15.93.4 30 and over 33.1%15.15.3 Gender Female 16.7%15.65.5 Male 83.3%15.75.3 Army Duty Status National Guard/Reserve 47.4%15.55.4 Active Duty 52.6%15.85.3 Service Category Enlisted 84.9%15.55.5 Officers 14.6%16.394.7 Marital Status Married 49.0%15.55.2 Single/Divorced/Legally Separated 51.0%15.85.4 Army Physical Fitness Test n=9,845 Failed 13.7%15.05.6 Passed 86.3%16.05.3 BMI Categories n=11,119 Underweight (<18.4 kg/m2) 0.5%15.15.1 Normal/Healthy (18.5-27.5 kg/m2) 65.3%15.05.3 Overweight (27.6-29.9 kg/m2) 16.9%15.65.3 Obese (>30 kg/m2) 17.3%15.15.5 BMI, MeanSD (kg/m2) 26.64.0 BMI Range 13.4-56.3 Waist Circumference n=5,855 Healthy 90.9%16.095.3 Unhealthy 9.1%15.285.3 HES-5 Quartiles*Low HES-5 Quartile 1 25.98.63.0 Quartile 2 26.014.41.2 Quartile 3 22.217.80.8 High HES-5 Quartile 4 25.922.11.8Note: Data are represented as means standard deviation (SD) for continuous variables and as a percentage for categorical variables. Percentages within characteristic groups may not total 100% due to missing data.*HES-5 (Healthy Eating Score-5); High HES-5 is defined as a total 20 out of 25 or above the 75th percentile; a low HES-5 received a score of 12 or below (lower 25th percentile).

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70 http://www.cs.amedd.army.mil/amedd_journal.aspx1.03; 95% CI, 0.91-1.16; P =.64]) or active duty status (reference group: Reserve or National Guard [OR 1.12; 95% CI, 1.02-1.23; P =.02]). Additional results presented in Figure 2 indicate that those Soldiers who were younger, ate breakfast at least 6 times per week, and ate a postexercise recovery snack were more likely to be in the top HES-5 quartile when compared to older Soldiers and those who did not engage in those behaviors. Figure 2 also indicates that Soldiers with healthy anthropometric measures had greater odds of being in the highest HES-5 quartile than Soldiers without healthy anthropometric measures. Moreover, those Soldiers who considered themselves to be “about the right weight” were more likely be in the highest HES-5 quartile when compared to those who considered themselves as overweight or obese (OR 2.15; 95% CI, 1.94-2.40; P <.001). The DS intake data are shown in Figure 3. Many respondents (40%) reported regular use of health-promoting supplements such as a multivitamin/mineral. Soldiers who reported taking a health-promoting supplement at least once a week were more likely to be in the top HES5 quartile than those who did not. Similarly, those who took an omega-3 fatty acid supplement once a week and a protein supplement at least once a week had greater odds of being in the top HES-5 quartile than Soldiers who did not take these supplements. Soldiers who reported taking a performance-enhancing or bodybuilding product (other than a protein powder) at least once a week were 2 times as likely to be in the top HES-5 quartile when compared to those who did not take these Health Promoting Omega-3 Fatty Acid 2.76 2.51-3.03 3.79 3.40-4.20 2.96 2.67-3.28 Odds Ratio 0 1 2 3 4 5 OR 95% CI Protein PowdersFigure 3. Dietary Supplements. The relative odds of having a high HES-5 and taking a supplement at least once a week (versus less than once a month or never), when compared to low HES-5. All categories are dichotomous. High HES-5 is de ned as a total 20 out of 25; a low HES-5 received a score of 12 or lower ( P <.003). Healthy Eater Healthy Waist Sizec OR 1.56 CI, 1.22-2.00 Exercise Recovery SnackbOR 3.1 CI, 2.80-3.40 Age 18-29aYearsOR 1.46 CI, 1.32-1.61 BreakfastfOR 4.2 CI, 3.8-4.70 7 Water Servings/ Daye OR 7.19 CI, 5.05-6.98 Healthy BMId OR 1.35 CI, 1.20-1.50Figure 2. Relative odds of being in the highest HES-5 quartile versus the lowest HES-5 quartile for several indicators. High HES-5 is de ned as a total 20 out of 25 or above the 75th percentile; a low HES-5 received a score of 12 or below (lower 25th percentile). *P <.003. All reported odds ratios are independent and did not control for other factors.aReference group: 30 years or older.bReference group: those who did not regularly consume a recovery snack.cReference group: waist circumference larger than 35 in for women; larger than 40 in for men.dReference group: greater than 27.5 kg/m2.eReference group: consumption of 6 or less glasses of water per day.fReference group: consumption of breakfast 5 or less times per week. 38.7% 50% 40% 30% 20% 10% 0% Vegetables Fruit Whole Grains Dairy Fish 22.2% 16.8% 17.3% 46.6%Figure 1. Percentages of Soldiers meeting US Dietary Guidelines by category. Overall, less than half me t the dietary guidelines for fruit (2 servings/day), vegetables (2-3 servings/day), whole grains (3 servings/day), dairy (3 servings/day), and sh (2-3 servings/week). NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 71THE ARMY MEDICAL DEPARTMENT JOURNAL products (OR 2.06; 95% CI, 1.82-2.32; P <.001). Approximately one fth (21%) of the total population reported taking all 3 supplements (health-promoting, omega-3, and protein powder), and the majority of this group was classi ed as being in the highest HES-5 quartile. Soldiers who consumed all three of these supplements experienced 4 times the odds of being in the highest HES5 group versus the lowest HES-5 group when compared with those who did not consume all 3 supplements (OR 4.04; 95% CI, 3.56-4.60).Other Lifestyle BehaviorsApproximately 60% of respondents drank regular and/ or diet sodas, and 23.1% of respondents reported binge drinking, as de ned by exceeding 5 alcoholic drinks on any single occasion during the previous 3 months. Both behaviors were signi cantly associated with membership in high/low HES-5 quartiles. Soldiers who consumed diet or regular soda (OR 0.56; 95% CI, 0.51-0.61; P <.001) were less likely to be in the highest HES-5 quartile than those who did not consume soda. Soldiers who self-reported binge drinking were less likely to be in the highest HES-5 quartile than Soldiers who did not binge drink (OR 0.57; 95% CI, 0.51-0.64; P <.001). Sleep was also related to a Soldier’s likelihood of being in the highest or lowest HES-5 quartile. When compared to “poor” sleepers (de ned as 5 or more on the PIRS-2), Soldiers who were classi ed as “good” sleepers had 4 times the odds of being in the highest HES-5 quartile (OR 4.38; 95% CI, 3.85-4.98; P <.001). A relationship between self-reported health status and being a “healthiest” or “least healthy” eater was also observed. Respondents who considered their health to be “good” or “excellent” had 3 times the odds of being in the highest HES5 quartile when compared to respondents whose health was “fair” or “poor” (OR 3.37; 95% CI, 2.98-3.82; P <.001).Physical ActivityRespondents’ self-reported frequency of physical activity and its results were analyzed based on the American College of Sports Medicine and Centers for Disease Control and Prevention exercise recommendations. A total of 28.5% of respondents met cardiovascular recommendations, 66.8% met strength-training recommendations, 86.3% passed their APFT overall, and 20.5% passed their APFT in the top quartile. Figure 4 illustrates for each HES-5 quartile the percentage of respondents who met the physical activity recommendations as well as the number of respondents who passed their APFT in the top quartile. When compared to Soldiers who did not meet physical activity recommendations, those who engaged in cardiovascular exercise for at least 20 minutes, 5 days per week were more likely to be in the highest than the lowest HES quartile (OR 3.23; 95% CI, 2.90-3.60; P <.001), as were those who participated in resistance training at least 2 days per week (OR 3.60; 95% CI, 3.24-3.99; P <.001). Finally, we compared the likelihood of being in the HES-5 high/low quartile among Soldiers who failed their APFT and those who passed in the highest quartile. Those who passed their APFT in the highest quartile had more than twice the odds of being in the highest HES quartile versus the lowest HES quartile when compared to those who failed their APFT ([n=3,413] OR 2.53; 95% CI, 2.08-3.08; P <.001).Healthy Eating Score and GAT DimensionsFigure 5 characterizes the percentage of respondents who scored in the top quartile of the CSF2 Figure 4. Physical tness and nutrition. Percentage of Soldiers in each HES-5 quartile who met the Center for Disease Control and the American College of Sports Medicine recommendations for cardiovascular exercise and resistance training or passed the Army Physical Fitness Test (APFT) in the Top Quartile. Healthy Eating Score Qualities 50% 80% 90% 70% 60% 0% 10% 40% 30% 20% Cardio Activity Strength Training APFT in Top Quartile Low HES-5 High HES-5

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72 http://www.cs.amedd.army.mil/amedd_journal.aspxdimensions—emotional, social, family, and spiritual— in each of the HES-5 quartiles. High GAT dimension scorers were signi cantly more likely to be high HES-5 scorers: Emotional Fitness: OR 7.03; 95% CI, 6.08-8.13 (n=3,688) Social Fitness: OR 4.72; 95% CI, 4.10-5.44 (n=3,698) Family Fitness: OR 2.99; 95% CI, 2.99-2.59 (n=3,222) Spiritual Fitness: OR, 4.16; 95% CI, 3.65-4.75 (n=4,046) COMMENT Poor nutritional/dietary habits degrade mission readiness while contributing to other health disorders9 and affect all domains of performance. Nutrition is thus deemed an essential component of Total Force Fitness.45 Accordingly, dietary behavior assessment questions were included in the new GAT physical dimension along with other lifestyle questions relating to performance. This study characterized nutritional behaviors of 13,858 Soldiers and examined their interrelationships with other lifestyle behaviors. We showed that dietary behaviors could be characterized by the HES-5. The HES-5 was strongly associated with a number of health-promoting nutritional behaviors: those with healthier BMIs and waist circumferences, who performed better on the APFT, and who had better psychosocial pro les were also more likely to have the highest HES-5 scores. Although the bene cial effects of fruit and vegetable consumption are well known, only 38.7% of participants met fruit intake recommendations, and 22.2% met vegetable recommendations. These ndings are consistent with health behavior studies reporting suboptimal fruit and vegetable intake in military personnel.18,19 Even fewer Soldiers met the guidelines of eating at least 3 servings per day of whole grains (16.8%) and dairy (17.3%). Importantly, a higher percentage (46.6%) met the recommendation of at least 2-3 weekly servings of sh, which may re ect the Warriors’ focus on tuna as a quick, inexpensive protein. Although it will require further exploration, this is a reasonable hypothesis. Our sample did report higher intakes of key food groups than were noted in the 2011 Health Related Behaviors Survey of Active Duty Military Personnel18 where only 12.9%, 11.2% and 12.7% of all military personnel met the intake guidelines for vegetables, fruit, and whole grains, respectively. Of interest is why the percentage of Soldiers meeting the recommendations is higher in the present study than in previous survey ndings. This could be related to differences in assessment tools, sample population differences, or ongoing and emerging DoD and Army initiatives targeting nutritional tness. Further study might reveal the differential effect of these varying campaigns on health outcomes among the military services. The HES-5 was created to assess overall nutrition. In our military population, high HES-5 scores were strongly associated with a number of key health promoting nutritional behaviors. Those who consumed breakfast at least 6 times per week, 2 snacks daily, 7 or more servings of water daily, and a snack within 60 minutes of strenuous exercise were more likely to have high HES5 scores than Soldiers who did not consume breakfast, adequate water, or recovery snacks. These behaviors have been shown to in uence health and performance. Studies have shown that consumption of breakfast and snacks is associated with lower stress, improved cognitive function, and fewer injuries and accidents at work,46 along with lower values for BMI and waist circumference.47 Consistent with those ndings, Soldiers with a healthy BMI and with a healthy waist circumference were more likely to have high HES-5 scores than Figure 5. Global Assessment Tool (GAT) Fitness Dimensions and Nutrition. Percentage of each HES-5 quartile scoring in the highest quartile of the GAT psychological dimensions. Healthy Eating Score Qualities Low HES-5 High HES-5 Emotional Social Family Spiritual 5% 0% 15% 10% 40% 35% 30% 25% 20% NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 73THE ARMY MEDICAL DEPARTMENT JOURNAL those with an unhealthy BMI and waist circumference. Furthermore, Deshmukh-Taskar et al48 indicated that breakfast consumption was associated with more favorable cardiometabolic risk pro les than skipping breakfast. Additionally, carbohydrates, a usual constituent of snacks and meals, enhanced physical and cognitive performance in Soldiers engaged in sustained and intense physical activities.4,5 Together, these ndings demonstrate the in uence of dietary behaviors on multiple aspects of health and performance. Critical components of performance are hydration, (re-) fueling, and recovery. Adequate hydration plays a key role in physical performance, particularly in the heat,49,50 and those with high HES-5 scores were much more likely to consume recommended amounts of water. Likewise, proper fueling and adequate sleep and rest are essential.51-56 Res et al53 found that protein consumption prior to sleep improved physical recovery after training. Thus, appropriate nutrient timing, such as consuming a postworkout snack, can improve performance, delay fatigue,6,57 refuel depleted muscular energy stores,6,51 accelerate recovery, decrease muscle soreness following prolonged exercise training, and may positively effect health outcomes.58 Additional bene ts of regular nutrient timing include improved morale, stimulation of muscle protein synthesis, and protection against training injuries.51,58 It appears that Soldiers may understand this concept in that those who consumed a snack within a short time after strenuous training were also more likely to have high HES-5 scores. More effort should be focused on making this simple nutritional strategy known and ensuring appropriate recovery meals are available. One question and component of the HES-5 related to the frequency of sh intake, in particular, to sh containing omega-3 fatty acids, such as salmon, tuna, and mackerel. Research has suggested that omega-3 fatty acids may be cardioprotective,59 and the Food and Drug Administration announced in October 2000 a quali ed health claim for dietary supplements containing omega-3 fatty acids and reduced risk of CHD.60 Omega-3s also appear to serve an important role in brain health.3,61,62 Speci cally, Kang and Gleason61 concluded that increasing omega-3 intake may be one way to manage depression. Levant et al62 reported that omega-3 fatty acids may regulate neurobiological substrates of depression, including serotonergic and dopaminergic transmission and the expression of brain-derived neurotrophic factors in the hippocampus. Johnston et al63 reported that blood levels of omega-3 were signi cantly below what is considered optimal in a sample of deployed Soldiers with mild depression. Although data are somewhat inconsistent regarding the bene ts of omega-3s for brain/mental health,64 continuing assessment of this nutrient will help inform targeted strategies and interventions designed to improve cognitive performance, mood, and general brain health. Noteworthy is that in addition to a large proportion meeting the US Dietary Guidelines for sh, 33.3% of study participants reported weekly intake of an omega-3 supplement. Whether this level of intake re ects the widespread discussion of omega-3s throughout the DoD remains to be determined. Beverage intake, particularly with regard to sodas, is a key dietary behavior that can in uence energy balance and consequently, BMI and waist circumference. Of note, those who avoided drinking either diet or regular sodas were more likely to have high HES-5. Sugary beverages likely contribute to excess energy consumption and increased obesity,65 decreased satiety,66 and increased risk of developing type 2 diabetes and heart disease.67-69 Whereas arti cial sweeteners may impair neural appetite regulation mechanisms, data also suggest that prolonged consumption may lead to increased body weight, obesity, and metabolic syndrome.70-72 Interestingly, in our study, 65.8% of those with an unhealthy waist circumference consumed either diet or regular sodas compared to only 34.2% of those who consumed neither type of soda beverage. Clearly, beverage intake behaviors are important to consider with regard to healthy body mass and health. Further investigations into how these dietary behaviors contribute to health and performance could inform the development of targeted campaigns and educational strategies to enhance positive dietary behaviors. Dietary supplement use by military members is high,9,73,74 and supplements are universally available at the commissaries and exchanges of all military installations, as well as at convenience and package stores, retail stores, and some tness centers. Approximately 40% of our respondents reported regular multivitamin use, which is similar to the 2011 Health Related Behaviors Survey of Active Duty Military Personnel18 where 37.2% of military personnel reported daily use. In addition, those who took one or more supplements per week (healthpromoting, omega-3 fatty acids, and protein powders) were also more likely to have high HES-5 than those who did not. Although we cannot determine the motivation for supplement use in this population, previous research suggests individuals consumed supplements to improve or maintain overall health.75 Supplement users also tended to have lower BMIs, frequent physical activity, and moderate alcohol intake, all of which are re ected in our research population.

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74 http://www.cs.amedd.army.mil/amedd_journal.aspxMost supplement users received their vitamins and minerals from food alone when compared to nonusers.76,77 Our research showed the majority of persons using health-promoting supplements were also the healthiest eaters. Therefore, one important message to disseminate throughout the Army is that supplements should not replace or make up for a poor quality diet. Unfortunately, popular media cater to War ghters by claiming such products will enhance performance, maximize muscle strength, and build muscle. This is a particular concern given the many manufacturing violations found in half of the rms inspected during the US Food and Drug Administration investigation.78 An ongoing DoD initiative, Operation Supplement Safety, informs providers and War ghters about safe supplement use. Due to the diverse environments and extreme physical demands of military service, War ghters must maintain a higher level of physical tness and greater physical work capacity than the civilian population.79 In particular, lower levels of cardiovascular tness, as measured by run times, have been consistently and strongly associated with injury risk in both military men and women.80,81 In this study, Soldiers who met aerobic exercise recommendations had more than 3 times the odds of being the healthiest eater than those who did not. Further, those who met the strength training recommendations had similar odds of being a healthy eater. Importantly, Soldiers who passed their APFT in the top quartile of those who passed were also more likely to be in the top HES-5 quartile than those who failed their APFT. The APFT measures tness components twice a year and ensures our Soldiers are prepared to meet the physical demands of the mission and minimize the likelihood of injury.79,82 The relationship between nutrition and exercise may be bidirectional. Brodney et al83 studied physically t and un t men and women and subsequently reported that those with higher tness levels consumed diets that were closer to meeting national dietary recommendations than the diets of their lesser t peers. Of key concern to a military population is suf cient dietary intake that supports energy expenditure of sustained physical activity. Strong associations between high HES-5 and GAT emotional, social, family, and spiritual dimension scores were found. Those in the top quartiles for these GAT dimensions were signi cantly more likely to score in the highest HES-5 quartile. These ndings highlight the holistic complexity of human performance and are consistent with previous reports suggesting that optimal nutritional tness can assist in enhancing multiple CSF dimensions.1,51,52,54-56Several limitations exist with this study. First, although the sample size is large, the data are self-reported. The limitations of using self-reported data are well documented: respondents tend to under-report weight and over-report height84 and waist circumference,85 and they also misreport their physical activity.86 Secondly, individuals who chose to have their data used for research purposes may have different characteristics than those who did not, which may affect the ability to generalize these results. Next, the relationships between HES-5 and scores on emotional, social, family, and spiritual tness are not suf ciently granular to characterize speci c dimension components. Further research is needed to clarify the contribution of dietary behaviors to emotional, social, family, and spiritual tness. All of the logistic regression analyses examined the relationship between HES-5 and only one other variable at a time. Future analyses should utilize multivariate modeling to determine the relative importance of these predictors. Finally, due to limited question number, the HES-5 included only 5 components of the diet, unlike the HEI-2005 which encompasses 12 items.31 Future studies should consider additional dietary patterns. In summary, the relationship of dietary behaviors and multiple domains of human performance within the context of overall lifestyle habits and psychosocial health in a military population were examined. We found that the HES-5 is a useful index with which to characterize eating behaviors in a military population and that healthy eaters were more likely to engage in a constellation of appropriate dietary and activity behaviors and more likely to score well on the APFT. RELEVANCE TO PERFORMANCE TRIAD The Performance Triad components—nutrition, sleep, and activity—are intricately interrelated. An exquisite interplay exists between them: (1) sleep quality (and duration) affects nutrition through alterations in metabolism, cognitive decrements, and appetite4,53,87-90; (2) nutrition affects sleep,4,91,84,85 physical performance, recovery and fatigue51-56; and (3) physical tness affects appetite mechanisms, social health, sleep, cognitive performance, and mood.79,92-96 A recent review96 hypothesized that eating behavior and physical activity may share a common neurocognitive link since active individuals have an improved regulation of hunger and satiety mechanisms. Clearly, these relationships are critical to optimize health and performance and should be investigated and promoted as a holistic system. This study provides data regarding differences in nutrition behaviors and other lifestyle habits that highlight the need to provide education regarding the positive performance NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 75THE ARMY MEDICAL DEPARTMENT JOURNAL bene ts of good dietary behaviors and to provide targeted resources for ensuring optimal nutrition. The HES-5 may be a useful index for characterizing dietary intake behaviors and would be a valuable index with which to measure nutrition behaviors in future Performance Triad interventions. ACKNOWLEDGEMENTSThis research was supported by a grant from Comprehensive Soldier and Family Fitness (CSF2; HT9404-12-1-0017; F191GJ). The authors appreciate the support and the review of this manuscript by LTC Daniel T. Johnston and LTC Sharon A. McBride, and gratefully acknowledge Josh Kazman for statistical support and Preetha Abraham for graphic assistance.REFERENCES1. Montain SJ, Carvey CE, Stephens MB. Nutritional Fitness. Mil Med 2010;175(suppl 1):65-72. 2. McClung JP, Karl JP, Cable SJ, et al. Randomized, double-blind, placebo-controlled trial of iron supplementation in female soldiers during military training: effects on iron status, physical performance, and mood. Am J Clin Nutr 2009;90(1):124-131. 3. Parletta N, Milte CM, Meyer BJ. Nutritional modulation of cognitive function and mental health. J Nutr Biochem 2013;24(5):725-743. 4. Lieberman HR. Nutrition, brain function and cognitive performance. Appetite 2003;40(3):245-254. 5. Montain SJ, Young AJ. Diet and physical performance. Appetite 2003;40(3):255-267. 6. Rodriguez NR, Di Marco NM, Langley S. American College of Sports Medicine position stand. Nutrition and athletic performance. Med Sci Sports Exerc 2009;41(3):709-731. 7. Askew EW. Environmental and physical stress and nutrient requirements. Am J Clin Nutr 1995;61(suppl 3):631S-637S. 8. Bedno SA, Li Y, Han W, et al. Exertional heat illness among overweight U.S. Army recruits in basic training. Aviat Space Environ Med 2010;81(2):107-111. 9. Deuster PA, Weinstein AA, Sobel A, Young AJ. War ghter nutrition: current opportunities and advanced technologies report from a Department of Defense workshop. Mil Med 2009;174(7):671-677. 10. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA 2012;307(5):491-497. 11. Naghii MR. The importance of body weight and weight management for military personnel. Mil Med 2006;171(6):550-555. 12. Schmitt JA. Nutrition and cognition: meeting the challenge to obtain credible and evidence-based facts. Nutr Rev 2010;68 (suppl 1):S2-5. 13. Hanlon EC, Van Cauter E. Quanti cation of sleep behavior and of its impact on the cross-talk between the brain and peripheral metabolism. Proc Natl Acad Sci USA. 2011;108 (suppl 3):15609-15616. 14. Knutson KL, Van Cauter E, Zee P, Liu K, Lauderdale DS. Cross-sectional associations between measures of sleep and markers of glucose metabolism among subjects with and without diabetes: the Coronary Artery Risk Development in Young Adults (CARDIA) Sleep Study. Diabetes Care 2011;34(5):1171-1176. 15. He FJ, Nowson CA, Lucas M, MacGregor GA. Increased consumption of fruit and vegetables is related to a reduced risk of coronary heart disease: meta-analysis of cohort studies. J Hum Hypertens 2007;21(9):717-728. 16. Ness AR, Powles JW. Fruit and vegetables, and cardiovascular disease: a review. Int J Epidemiol 1997;26(1):1-13. 17. Steinmetz KA, Potter JD. Vegetables, fruit, and cancer prevention: a review. J Am Diet Assoc 1996;96(10):1027-1039. 18. Barlas FM, Higgins WB, P ieger JC, Diecker K. 2011 Department of Defense Survey of Health Related Behaviors Among Active Duty Military Personnel Fairfax, VA: ICF International; February 2013. Available at: http://www.murray.senate. gov/public/_cache/ les/889efd07-2475-40ee-b3b0508947957a0f/final-2011-hrb-active-duty-surveyreport.pdf. Accessed August 27, 2013. 19. Bray RM, Pemberton MR, Hourani LL, et al. 2008 Department of Defense Survey of Health Related Behaviors Among Active Duty Military Personnel Research Triangle Park, NC: RTI International; 2009. Available at: http://www.tricare.mil/ tma/2008HealthBehaviors.pdf. Accessed August 27, 2013. 20. US Department of Health and Human Services. Healthy People 2010: Understanding and Improving Health 2nd ed. Washington, DC: U.S. Government Printing Of ce; 2000. 21. Haslam DW, James WPT. Obesity. Lancet 2005;366(9492):1197-1209. 22. WHO/FAO Expert Consultation on Diet, Nutrition and the Prevention of Chronic Diseases Diet, Nutrition and the Prevention of Chronic Diseases [WHO Technical Report Series, No 916]. Geneva, Switzerland: World Health Organization; 2003. Available at: http://www.who.int/dietphysicalactiv ity/publications/trs916/en/. Accessed February 5, 2013.

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Breakfast eating pattern and its association with dietary quality indices and anthropometric measurements in young women in Isfahan. Nutrition 2013;29(2):420-425. NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 77THE ARMY MEDICAL DEPARTMENT JOURNAL48. Deshmukh-Taskar P, Nicklas TA, Radcliffe JD, O’Neil CE, Liu Y. The relationship of breakfast skipping and type of breakfast consumed with overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome in young adults. The National Health and Nutrition Examination Survey (NHANES): 1999-2006. Public Health Nutr October 3, 2012:1-10. [epub] 49. Armstrong LE, Casa DJ, Millard-Stafford M, Moran DS, Pyne SW, Roberts WO. American College of Sports Medicine position stand. Exertional heat illness during training and competition. Med Sci Sports Exerc 2007;39(3):556-572. 50. Sawka MN, Burke LM, Eichner ER, Maughan RJ, Montain SJ, Stachenfeld NS. American College of Sports Medicine position stand. Exercise and uid replacement. Med Sci Sports Exerc 2007;39(2):377-390. 51. Beelen M, Burke LM, Gibala MJ, van Loon LJ. Nutritional strategies to promote postexercise recovery. Int J Sport Nutr Exerc Metab 2010;20(6):515-532. 52. Hausswirth C, Le Meur Y. Physiological and nutritional aspects of post-exercise recovery: speci c recommendations for female athletes. Sports Med 2011;41(10):861-882. 53. Res PT, Groen B, Pennings B, et al. Protein ingestion before sleep improves postexercise overnight recovery. Med Sci Sports Exerc 2012;44(8):1560-1569. 54. Shirreffs SM, Sawka MN. Fluid and electrolyte needs for training, competition, and recovery. J Sports Sci 2011;29 (suppl 1):S39-S46. 55. Slater G, Phillips SM. Nutrition guidelines for strength sports: sprinting, weightlifting, throwing events, and bodybuilding. J Sports Sci 2011;29 (suppl 1):S67-S77. 56. Stellingwerff T, Maughan RJ, Burke LM. Nutrition for power sports: middle-distance running, track cycling, rowing, canoeing/kayaking, and swimming. J Sports Sci 2011;29 (suppl 1):S79-S89. 57. Beelen M, Burke LM, Gibala MJ, van Loon LJ. Nutritional strategies to promote postexercise recovery. Int J Sport Nutr Exerc Metabol 2010;20(6):515-532. 58. Flakoll PJ, Judy T, Flinn K, Carr C, Flinn S. Postexercise protein supplementation improves health and muscle soreness during basic military training in Marine recruits. J Appl Physiol 2004;96(3):951-956. 59. Harris WS, Von Schacky C. The Omega-3 Index: a new risk factor for death from coronary heart disease?. Prev Med 2004;39(1):212-220. 60. US Food and Drug Administration. FDA announces quali ed health claims for omega-3 fatty acids [internet]. September 8, 2004. Available at: http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/2004/ucm108351.htm. Accessed June 28, 2013. 61. Kang JX, Gleason ED. Omega-3 fatty acids and hippocampal neurogenesis in depression. CNS Neurol Disord Drug Targets 2013;12(4):460-465. 62. Levant B. N-3 (omega-3) polyunsaturated fatty acids in the pathophysiology and treatment of depression: pre-clinical evidence. CNS Neurol Disord Drug Targets 2013;12(4):450-459. 63. Johnston DT, Deuster PA, Harris WS, Macrae H, Dretsch MN. Red blood cell omega-3 fatty acid levels and neurocognitive performance in deployed U.S. servicemembers. Nutr Neurosci. 2013;16(1):30-38. 64. Sinn N, Milte C, Howe PR. Oiling the brain: a review of randomized controlled trials of omega-3 fatty acids in psychopathology across the lifespan. Nutrients 2010;2(2):128-170. 65. McGuire S. Accelerating progress in obesity prevention: solving the weight of the nation. Adv Nutr 2012;3(5):708-709. 66. Pan A, Hu FB. Effects of carbohydrates on satiety: differences between liquid and solid food. Curr Opin Clin Nutr Metab Care 2011;14(4):385-390. 67. de Koning L, Malik VS, Kellogg MD, Rimm EB, Willett WC, Hu FB. Sweetened beverage consumption, incident coronary heart disease, and biomarkers of risk in men. Circulation 2012;125(14):17351741, S1731. 68. Fung TT, Malik V, Rexrode KM, Manson JE, Willett WC, Hu FB. Sweetened beverage consumption and risk of coronary heart disease in women. Am J Clin Nutr 2009;89(4):1037-1042. 69. Malik VS, Popkin BM, Bray GA, Despres JP, Willett WC, Hu FB. Sugar-sweetened beverages and risk of metabolic syndrome and type 2 diabetes: a metaanalysis. Diabetes Care 2010;33(11):2477-2483. 70. Swithers SE, Davidson TL. A role for sweet taste: calorie predictive relations in energy regulation by rats. Behav Neurosci 2008;122(1):161-173. 71. Yang Q. Gain weight by “going diet?” Arti cial sweeteners and the neurobiology of sugar cravings: neuroscience 2010. Yale J Biol Med 2010;83(2):101-108. 72. Nettleton JA, Lutsey PL, Wang Y, Lima JA, Michos ED, Jacobs DR Jr. Diet soda intake and risk of incident metabolic syndrome and type 2 diabetes in the Multi-Ethnic Study of Atherosclerosis (MESA). Diabetes Care 2009;32(4):688-694. 73. Deuster PA, Sridhar A, Becker WJ, Coll R, O’Brien KK, Bathalon G. Health assessment of U.S. Army Rangers. Mil Med 2003;168(1):57-62. 74. Bovill ME, Tharion WJ, Lieberman HR. Nutrition knowledge and supplement use among elite U.S. Army soldiers. Mil Med 2003;168(12):997-1000.

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78 http://www.cs.amedd.army.mil/amedd_journal.aspx75. Bailey RL, Gahche JJ, Miller PE, Thomas PR, Dwyer JT. Why US adults use dietary supplements. JAMA Intern Med 2013;173(5):355-361. 76. Bailey RL, Fulgoni VL, 3rd, Keast DR, Dwyer JT. Dietary supplement use is associated with higher intakes of minerals from food sources. Am J Clin Nutr 2011;94(5):1376-1381. 77. Bailey RL, Fulgoni VL III, Keast DR, Dwyer JT. Examination of vitamin intakes among US adults by dietary supplement use. J Acad Nutr Diet 2012;112(5):657-663. 78. Tsouderos T. Dietary supplements: manufacturing troubles widespread, FDA inspections show. Chicago Tribune [serial online]. June 30, 2012. Available at: http://articles.chicagotribune.com/2012-06-30/ news/ct-met-supplement-inspections-20120630_1_ dietary-supplements-inspections-american-herbalproducts-association. Accessed August 27, 2013. 79. Roy TC, Springer BA, McNulty V, Butler NL. Physical Fitness. Mil Med 2010;175(suppl 1):14-20. 80. Jones BH, Knapik JJ. Physical training and exercise-related injuries. Surveillance, research and injury prevention in military populations. Sports Med 1999;27(2):111-125. 81. Rauh MJ, Macera CA, Trone DW, Shaffer RA, Brodine SK. Epidemiology of stress fracture and lower-extremity overuse injury in female recruits. Med Sci Sports Exerc 2006;38(9):1571-1577. 82. Lohi JJ, Huttunen KH, Lahtinen TM, Kilpelainen AA, Muhli AA, Leino TK. Effect of caffeine on simulator ight performance in sleep-deprived military pilot students. Mil Med 2007;172(9):982-987. 83. Brodney S, McPherson RS, Carpenter RS, Welten D, Blair SN. Nutrient intake of physically t and un t men and women. Med Sci Sports Exerc 2001;33(3):459-467. 84. Elgar FJ, Stewart JM. Validity of self-report screening for overweight and obesity. Evidence from the Canadian Community Health Survey. Can J Public Health 2008;99(5):423-427. 85. Bigaard J, Spanggaard I, Thomsen BL, Overvad K, Tjonneland A. Self-reported and technician-measured waist circumferences differ in middle-aged men and women. J Nutr 2005;135(9):2263-2270. 86. Helmerhorst HJ, Brage S, Warren J, Besson H, Ekelund U. A systematic review of reliability and objective criterion-related validity of physical activity questionnaires. Int J Behav Nutr Phys Act 2012;9:103. 87. Afaghi A, O’Connor H, Chow CM. High-glycemicindex carbohydrate meals shorten sleep onset. Am J Clin Nutr 2007;85(2):426-430. 88. Peuhkuri K, Sihvola N, Korpela R. Diet promotes sleep duration and quality. Nutr Rev 2012;32(5):309-319. 89. Knutson KL, Spiegel K, Penev P, Van Cauter E. The metabolic consequences of sleep deprivation. Sleep Med Rev 2007;11(3):163-178. 90. St-Onge MP, Roberts AL, Chen J, et al. Short sleep duration increases energy intakes but does not change energy expenditure in normal-weight individuals. Am J Clin Nutr 2011;94(2):410-416. 91. Energy drink consumption and its association with sleep problems among U.S. service members on a combat deployment – Afghanistan, 2010. MMWR. Morb Mortal Wkly Rep. 2012;61(44):895-898. 92. Barbour KA, Blumenthal JA. Exercise training and depression in older adults. Neurobiol Aging 2005;26 (suppl 1):119-123. 93. Cramer SR, Nieman DC, Lee JW. The effects of moderate exercise training on psychological wellbeing and mood state in women. J Psychosom Res 1991;35(4-5):437-449. 94. De Moor MH, Beem AL, Stubbe JH, Boomsma DI, De Geus EJ. Regular exercise, anxiety, depression and personality: a population-based study. Prev Med 2006;42(4):273-279. 95. Driver HS, Taylor SR. Exercise and sleep. Sleep Med Rev 2000;4(4):387-402. 96. Joseph RJ, Alonso-Alonso M, Bond DS, PascualLeone A, Blackburn GL. The neurocognitive connection between physical activity and eating behaviour. Obes Rev 2011;12(10):800-812.AUTHORSDr Purvis is Director, Strategic Operations and Special Projects, Consortium for Health and Military Performance, Dept of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Ms Lentino and Ms Murphy are Research Associates, Consortium for Health and Military Performance, Dept of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr Jackson is a Public Health Scientist, Public Health Assessment Program, Army Institute of Public Health, US Army Public Health Command, Aberdeen Proving Ground, Maryland. Dr Deuster is Director and Professor, Consortium for Health and Military Performance, Dept of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.NUTRITION AS A COMPONENT OF THE PERFORMANCE TRIAD: HOW HEALTHY EATING BEHAVIORS CONTRIBUTE TO SOLDIER PERFORMANCE AND MILITARY READINESS

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October – December 2013 79NUTRITIONAL DEFICIENCIES IN THE TRAINING ENVIRONMENT Unhealthy eating habits and nutritional de ciencies are an increasing concern among Army personnel. Current literature shows that poor nutrition can affect susceptibility to injury and affect the Soldiers’ ability to carry out their missions.1-4 Overweight or obesity status, which may result from poor nutrition, degrades combat readiness because it puts Soldiers at risk for attrition, for other health problems, and has also increased the number of recruits who are ineligible to serve because of their body fat composition.5According to the 2008 Survey of Health Related Behaviors for military personnel, only 17% of women and 14% of men reported consuming the USDA-recommended servings of fruits and vegetables per day.6 This mirrors the general population of the United States: fewer than 25% of Americans eat fruits and vegetables 5 or more times per day.7 This suggests the majority of military personnel are not consuming the recommended nutrients for the average adult.8 Furthermore, Soldiers usually require increased dietary energy intake, especially during training as they maintain high levels of physical activity.1 Soldiers expending more energy than they consume have a negative energy balance which results in chronic undernourishment.9 This is a concern because a diet lacking critical nutrients has a negative effect on health, injury, physical performance, and recovery from illness.1,9-11 For example, Wentz et al found that insuf cient nutrient intake and The Importance of Leadership in Soldiers’ Nutritional Behaviors: Results from the Soldier Fueling Initiative Program Evaluation eresa K. Jackson, PhD, MPH, CHES Sabriya D. Dennis, MS COL Sonya J. Cable, SP, USA Linda T. Vo, MPH, CHES Wana K. Jin, MPH Trish J. Prosser, PhD Ayanna Robinson, MPH Jess A. Rawlings, MSABSTRACT Introduction: Improving Soldiers’ nutritional habits continues to be a concern of the US Army, especially amidst increasing obesity and high injury rates. This study examines leadership in uence on nutritional behaviors within the context of the Soldier Fueling Initiative, a program providing nutrition education and improved dining facility menus to Soldiers in Basic Combat Training (BCT) and Advanced Individual Training (AIT).Methods: A mixed methods design using surveys (N=486) and focus groups (N=112) was used to collect data at Fort Jackson, SC, and Fort Eustis, VA, in 2011.Results: Survey results showed 75% of Soldiers in BCT believed their drill sergeant was helpful in making performance-enhancing food choices, and 86% agreed their drill sergeant believed it is important to eat for performance. Soldiers in AIT perceived their cadre as less helpful than their BCT drill sergeants and agreed less frequently that the AIT cadre believed it was important to eat for performance ( P <.05). These measures of leader in uence were signi cantly associated with nutritional attitudes and behaviors in both BCT and AIT. Focus groups revealed 5 key themes related to cadre in uence and nutrition behavior (listed in order of most to least frequent): (1) cadre in uence food choices through consequences related to selection, (2) cadre teach Soldiers how to eat, (3) cadre rush Soldiers to eat quickly to return to training, (4) cadre in uence choice through example but often do not make healthy choices, and (5) cadre have no in uence on food choices.Comment : Leaders in uence most Soldiers’ nutrition practices within the training environment, particularly within BCT. Given that leader in uence can impact Soldiers’ attitudes and behaviors, it is critical that military leaders become knowledgeable about optimal nutrition practices to disseminate appropriate information to their Soldiers, avoid reprimand associated with trainees’ food choices, reinforce key messages associated with nutrition programming, and lead by example in their own food choices.

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80 http://www.cs.amedd.army.mil/amedd_journal.aspxchronic undernourishment were linked to increased rates of stress fractures in military recruits.4Poor nutrition can also cause Soldiers to become overweight or obese. Approximately 51% to 61% of military personnel are overweight, and 12% are classi ed as obese.12 Soldiers are required to maintain weight-forheight standards and to remain below a certain body fat percentage. There are reports of Soldiers using unhealthy means such as laxatives or sauna/rubber suits to meet those weight standards and avoid attrition based on body fat status.5 Overweight and less t individuals also take longer to acclimatize to heat and are less tolerant of heat, which can affect mission readiness in hot climates.13THE SOLDIER FUELING INITIATIVE The Soldier Fueling Initiative (SFI) was designed to establish a fueling standard in initial military training (IMT) and improve Soldiers’ nutritional status. The SFI encompasses Department of Defense nutritional standards, performance nutrition education, menu development, and preparation and serving standards in order to optimize IMT Soldier tness and performance.14 The program includes 2 primary areas of implementation: Food Service Operations and Performance Nutrition Education. The food service operation component of SFI consists of Go for Green labeling, performance-focused dining facility (DFAC) menus, and Fit Pick vending within Advanced Individual Training (AIT). Go for Green labeling is a nutritional recognition tool that provides pointof-decision prompts and allows Soldiers to make quick assessments of the menu options as they move through the food lines. Food items labeled in green are considered to be high performance and should be eaten often; items labeled in amber are moderate performance foods that should be eaten occasionally, and items labeled in red are performance-limiting and should only be consumed on rare occasions.14The performance nutrition education component consists of a one-hour training course within the rst 2 weeks of basic combat training (BCT). During this course, Soldiers receive information on the importance of eating for performance, utilizing the Go for Green labels in DFACs, and understanding how their bodies use food for fuel. The course, presented in a lecture format, is typically conducted by a drill sergeant or other cadre member. As a part of nutrition education, leaders receive SFI training on nutrition fundamentals, appropriate nutrition messaging, and instructing the trainees’ nutrition education course. LEADER AND PEER INFLUENCE ON HEALTH BEHAVIORS Throughout this article, the term “leader” refers to drill sergeants in BCT and to cadre members in AIT. Leaders are included in the SFI program delivery because leader and peer in uence has the potential to play a role in improving the nutritional status of new recruits. The social ecological model (SEM) asserts that multiple levels of in uence (individual, interpersonal, organizational, community, and policy) affect health behaviors.15 Interpersonal relationships, such as those with family, friends, and teachers, play a role in shaping one’s health behaviors. Bandura’s Social Cognitive Theory (SCT) also proposes that learning and behavior change occur through interactions with an individual’s social environment.16,17 One construct of SCT is observational learning, whereby people observe a behavior and then replicate it. Studies have also shown that this type of modeling is more effective when the observers consider the models to be similar to themselves.18Health promotion programs frequently use opinion leaders to affect behavior change, and programs that use peer opinion leaders are generally more effective than those that do not.19 This type of in uence has been used in church-based health promotion studies in which pastors communicate health messages to their congregants.20-22 Similarly, in the case of new Army recruits, a drill sergeant or other peers may serve as opinion leaders and role models that in uence eating habits. In Glover and colleagues’ study, drill sergeant candidates stated that mentorship and role modeling were an important part of training new recruits.23 These leaders believe they have a strong in uence on BCT Soldiers and try to lead by example. With regard to nutrition, drill sergeants stated they avoid eating unhealthy foods in front of Soldiers.23SOLDIER FUELING INITIATIVE PROGRAM EVALUATION OVERVIEW In 2011, the Army Institute of Public Health (AIPH), in collaboration with the IMT Center of Excellence (CoE), initiated a program evaluation of the SFI. The purposes of the SFI program evaluation were to better understand in uences of Soldiers’ nutrition within the training environment, determine effectiveness and reception of program components, provide strategies for program improvement, and inform subsequent phases of the SFI evaluation. The evaluation was guided by 6 primary evaluation questions: 1. What do Soldiers eat in IMT, and what guides their food choices? 2. What is the reach (use and awareness) of the SFI? THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

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October – December 2013 81THE ARMY MEDICAL DEPARTMENT JOURNAL 3. Is the SFI implemented as intended? 4. What are Soldier perceptions regarding the SFI? 5. What is the SFI’s effect on nutrition knowledge, perceptions regarding eating for performance, and eating habits? 6. To what extent might any healthy behaviors obtained in IMT be sustained? A subelement of evaluation Question 1 included a speci c examination of leader in uence on trainees’ nutrition behaviors. Speci cally, the evaluation team assessed the following: To what extent are Army leaders helpful or unhelpful in making performance-enhancing food selections? To what extent do Soldiers perceive that leaders think it is important to eat for performance? What effect do leaders have on Soldiers’ food selection? How does leader in uence on nutrition practices vary across different phases of Army training? To date, no studies have speci cally examined how trainees’ perceptions of their leaders affect their nutritional attitudes and behavior in IMT, either positively or negatively. Given the potential for leaders to serve as an in uence on nutrition practices, it is critical to understand how, if at all, training leaders help their Soldiers choose healthy, performance-oriented foods or hinder them from making such choices. METHODS Prior to data collection, both the US Army Public Health Command Public Health Review Board and the Center for Accessions Research Institutional Review Board (I RB) reviewed and approved this evaluation. The study used both quantitative (survey) and qualitative (focus group) methods among Soldiers in BCT and AIT. A mixed methods design combining both quantitative and qualitative methods is bene cial because it leads to more robust data than a singular method.24,25Power AnalysesThe IMT CoE Experimentation and Analysis Element identi ed 6 companies of Soldiers at Fort Jackson, SC, and 2 companies of Soldiers at Fort Eustis, VA, to participate in the evaluation. The IMT CoE established operational orders to facilitate data collection during October thru November 2011. A total of 598 Soldiers (319 BCT Soldiers and 279 AIT Soldiers) participated in the evaluation. The IRB waived written consent for surveys because consent forms would have been the only record of study participation; however, Soldiers were given a consent brie ng prior to data collection and were informed that their participation was completely voluntary. Soldiers within the focus groups provided written informed consent. Table 1 provides an overview of how the sample participated in data collection efforts. All BCT surveys (n=247) were administered to Soldiers at Fort Jackson in October 2011. The AIT surveys were administered at Fort Eustis (November 2011, n=239) where the SFI had recently been implemented. A priori power analyses revealed this sample was of suf cient size to detect small to moderate effects between groups. The AIPH team also conducted focus groups (methodology described below) with a convenience sample of BCT Soldiers (n=72) and AIT Soldiers (n=40) at Fort Jackson in October 2011. Survey Methods The AIPH team distributed anonymous short paper questionnaires to Soldiers in both BCT and AIT. Response rates for the participating companies were nearly 100% (likely because leaders encouraged Soldiers to participate), surveys were short (less than 10 minutes to complete), data collection was anonymous, and the topic was lowto no-risk. The questionnaires asked about a variety of constructs including demographics; use and perceived helpfulness of various SFI program components (eg, Go for Green labels, nutrition education); changes in weight, lean muscle mass, physical performance, and mental performance over time; nutrition behaviors (eg, frequency of eating lean protein, fruits, vegetables, low fat dairy); and general attitudes about nutrition and eating for performance. The surveys also contained questions designed to assess Soldiers’ perceived level of leader helpfulness (1=not at all helpful, 5=very helpful) in making performance-enhancing food choices and the extent to which Soldiers agreed that IMT leaders believed it was important to eat for performance (1=strongly disagree, 5=strongly agree). Table 1. Participation in Soldier Fuel ing Initiative Program Evaluation by Initial Military Training Class Type, Site, and Source of Data Collected.Data source Surveys(N=486)Focus Groups(N=112)Basic Combat Training (N=319) All Soldiers from 3 companies at Fort Jackson, SCn=247 Sample of Soldiers from 1 company at Fort Jackson, SCn=72 Advanced Individual Training (N=279) All Soldiers from 2 companies at Fort Eustis, VAn=239 Sample of Soldiers from 2 companies at Fort Jackson, SCn=40

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82 http://www.cs.amedd.army.mil/amedd_journal.aspxFocus Group MethodsThe evaluation team conducted 6 BCT focus groups based on strata by gender (male and female) and performance (high, average, and low performance based on physical tness test scores). The team conducted 4 AIT focus groups on gender strata only (ie, 2 groups of men, 2 groups of women). The structured focus groups assessed Soldiers’ experiences within the dining facilities, SFI effect on eating behavior, barriers to SFI implementation, and suggestions for program improvement. The BCT and AIT focus group guides consisted of 10 open-ended questions each. To speci cally gauge how leaders affected their nutrition behaviors, moderators asked participants, “how do Army cadre in uence your eating?” A trained AIPH facilitator led each focus group, and a note-taker took extensive notes throughout the session. Each focus group was audio-recorded. Before the focus group or interview began, the facilitator explained the purpose and procedure of the focus group, encouraged open discussion within the group, informed the participants that their participation and comments would remain anonymous, and asked for verbal consent to audio-record the session. Subcontractors transcribed the focus groups’ audio recordings verbatim and omitted any identifying information.Data AnalysesAll survey data were managed and analyzed using the IBM SPSS Statistics (V 21.0) application (IBM Corp, Chicago, IL). The analysis team generated frequencies and descriptive statistics on perceived leader helpfulness and Soldiers’ level of agreement that leaders believe it is important to eat for performance. Chi square and independent t tests were used to examine differences in these measures between BCT and AIT Soldiers. Measures of leader in uence were then additionally correlated with other constructs of interest in the evaluation, listed in Table 2, by means of Pearson product-moment correlations. Type I error rates ( P values) of .05 or lower designated statistically signi cant relationships for all analyses. The AIPH qualitative analysis group, which consisted of three, 2-analyst teams, used NVivo 9 qualitative data analysis software (QSR International Proprietary Ltd, Doncaster, Australia) for focus group data management and analysis. The analysis group used a team-based coding and constant-comparison approach, which consists of an iterative process of revising the codebook to re ect emerging themes and applying the codes systematically across teams.26 In order to achieve coding reliability, the analysts of each team reviewed, discussed, and established consensus on each code, and each team reviewed the work of another team. The team then summarized results and extracted example quotes to illustrate each theme for reporting. RESULTSSurvey ResultsA total of 486 Soldiers completed the survey, of whom 398 (82%) were male, and 87 (18%) were female. The average age of respondents was 21.3 4.5 years. Additional survey sample demographics are included in Table 3. Perceived helpfulness of leaders in making performance-enhancing food choices was signi cantly associated with Soldiers’ level of agreement that their leader believed it was important to eat for performance in both BCT ( r =0.343, P <.01) and AIT ( r =0.470, P <.01). Although measures are correlated, moderate effect sizes indicate they are measures of two distinct concepts; therefore, results from each construct are reported independently. PERCEIVED LEADER HELPFULNESS OF IN MAKING PERFORMANCE-ENHANCING FOOD CHOICES The majority of BCT Soldiers (75%) responded that their leader was somewhat or very helpful in choosing performance-enhancing foods while the majority of AIT Soldiers (56%) were neutral (Table 4). Observed differences between BCT and AIT were statistically signi cant ( 2=125.365, df=4, P <.0001). In both BCT and AIT, this perceived level of helpfulness was signi cantly associated with several constructs related to nutrition (Table 5). In BCT, as perceived helpfulness increased, frequency of use of Go for Green labels ( r =0.173, P <.001), frequency of selecting performance-oriented food choices ( r =0.169, P <.001), and positive attitude toward eating for performance ( r =0.131, P <.05) also increased. In AIT, as perceived helpfulness increased, frequency of use of Go for Green labels ( r =0.154, P <.05), frequency of selecting “green” items from the DFAC ( r =0.135, P <.05), frequency of selecting performance-oriented food choices ( r =0.255, P <.05), level of perceived knowledge about eating for physical performance ( r =0.146, P <.05), level of perceived knowledge about eating for cognitive performance ( r =0.178, P <.001), and positive attitude toward eating for performance ( r =0.225, P <.001) also increased. Level of leader helpfulness was not associated with frequency of selecting green, amber, or red items from the DFAC in BCT or frequency of selection of amber, red, or performance-limiting foods in AIT. THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

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October – December 2013 83THE ARMY MEDICAL DEPARTMENT JOURNAL SOLDIERS’ LEVEL OF AGREEMENT THAT LEADERS BELIEVE IT IS IMPORTANT TO EAT FOR PERFORMANCE Eighty-six percent of BCT Soldiers and 45% of AIT Soldiers agreed or strongly agreed with the statement that their leaders believe it is important to eat for performance (Table 4). Observed differences between BCT and AIT were statistically signi cant ( 2=146.445, df=4, P <.0001). As level of agreement with this statement increased, frequency of using Go for Green labels ( r =0.276, P <.001), frequency of selecting “green” items from the DFAC ( r =0.179, P <.001), frequency of selecting performance-oriented food choices ( r =0.383, P <.001), and positive attitude toward eating for performance ( r =0.268, P <.001) also increased in BCT (Table 5). Within AIT, as agreement with this statement increased, frequency of selecting performance-oriented food choices ( r =0.235, P <.001), level of perceived Table 2. Key Constructs of Interest Within the Soldier Fueling Initiative Program Evaluation.Construct of InterestOperationalizationCharacteristics of Construct Frequency of use of Go for Green labels in the DFAC How frequently do you use “Go for Green” labeling when considering food choices in the DFAC? Responses: every meal (5); once a day (4); a few times a week (3); about once a week (2); never (1) Higher score=higher frequency of use. Analyses run independently for BCT and AIT. Frequency of selection of food with red labels, amber labels, and green labels in the DFAC How frequently do you select each of the following in the DFAC? Food with green labels; food with amber labels; food with red labels Responses for each variable: 3+ times a day (5); 1-2 times a day (4); a few times per week (3); about once a week (2); rarely/never (1); I don’t know (user missing) Higher score=higher frequency of selection. Analyses run separately for each classification of labels. Analyses run independently for BCT and AIT. Frequency of selecting performance-oriented food choices in BCT and AIT Composite measure of the following items: How frequently do you select each of the following in the DFAC? Lean meats and proteins; low fat dairy; fruits (fresh, canned, dried); vegetables (hot line or salad bar) Responses for each variable: 3+ times a day (5); 1-2 times a day (4); a few times per week (3); about once a week (2); rarely/never (1); I don’t know (user missing) Responses summed across the 4 categories of foods (range: 4-20). Higher scores=Higher frequency of selection of performance-oriented choices. Cronbach =0.572 for BCT and 0.680 for AIT. Analyses run independently for BCT and AIT. Frequency of selecting performance-limiting food choices in AIT Composite measure of the following items: How frequently do you select each of the following in the DFAC? Fried foods; sweets; snack foods; sugary drinks; energy drinks Responses for each variable: 3+ times a day (5); 1-2 times a day (4); a few times per week (3); about once a week (2); rarely/never (1); I don’t know (user missing) Responses summed across the 5 categories of foods (range: 5-25). Higher scores=Higher frequency of selection of performance-limiting choices in AIT. Cronbach =0.689 for AIT. Analysis for AIT only. Level of perceived knowledge regarding eating for performance To what extent do you agree or disagree with each of the following statements? I know what to eat to optimize my cognitive performance. I know what to eat to optimize my physical performance. Strongly disagree (1); Disagree (2); Not sure (3); Agree (4); Strongly agree (5) Analyses run independently for each category of knowledge. Analysis for AIT only. Positive attitude toward eating for performance in BCT/AIT Composite measure of the following items: To what extent do you agree or disagree with each of the following statements? I made a signi cant effort to eat for performance in BCT/AIT. Eating quality foods is essential to optimal performance in BCT/AIT. I will strive to eat for performance during my career as a Soldier. In order to perform as a Soldier, I need to think like an athlete. Strongly disagree (1); Disagree (2); Not sure (3); Agree (4); Strongly agree (5) Responses summed across the 4 items (range: 5-20). Higher scores = Higher level of agreement with positive attitudes toward eating for performance in BCT or AIT. Cronbach =0.698 for BCT and 0.804 for AIT.

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84 http://www.cs.amedd.army.mil/amedd_journal.aspxknowledge about eating for physical performance ( r =0.254, P <.001), level of perceived knowledge about eating for cognitive performance ( r =0.263, P <.001), and positive attitude toward eating for performance ( r =0.336, P <.001) also increased. Level of agreement with this statement was not associated with frequency of selecting amber or red items from the DFAC in BCT or frequency of use of Go for Green labels, frequency of selection of green, amber or red items from the DFAC, or frequency of selection of performance-limiting food choices in AIT.Focus Group ResultsSeventy-two Soldiers participated in the BCT focus groups, of whom 37 (51%) were male and 35 (49%) were female. Forty Soldiers participated in the AIT focus groups, and the proportion of men and women was equivalent. Results of the 10 focus groups revealed 5 key themes related to leader in uence on eating behavior within the training environment: 1. Leaders in uence food choices through consequences related to selection. THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION Table 3. Demographic Characteristics of Soldier Fueling Initiative Program Evaluation Survey Sample in Basic Combat Training and Advanced Individual Training.CharacteristicBCT N=247 AIT N=239 Total N=486 Gender [n(percentage of N)]a,bMale 170 (69.1%)228 (95.4%)398 (82.1%) Female 76 (30.9%)11 (4.6%)87 (17.9%) Age (meanSD, year)c21.94.9220.73.9621.34.50 Weight category [n(percentage of N)]b,dUnderweight 1 (0.4%)3 (1.3%)4 (0.8%) Normal weight 144 (59.3%)171 (72.2%)315 (65.6%) Overweight 92 (37.9%)58 (24.5%)150 (31.3%) Obese 6 (2.5%)5 (2.1%)11 (2.3%) BMI [meanSD, kg/m2]e24.42.5623.73.0024.02.81a. Gender distribution differed significantly across BCT ad AIT (2=55.15, df=1, P <.001) b. All percentages reported are valid percentages. c. Mean age differed significantly across BCT and AIT ( t = 2.7963, df=479, P <.01) d. Weight category distribution differed significantly across BCT and AIT (2=11.04, df=3, P =.0115) ; Category: underweight ( BMI <18.5) normal weight (18.5-24.9) overweight (25.0-29.9) obese (>30.0) .27e. Mean BMI differed significantly across BCT and AIT ( t =2.7545, df=478, P <.01) Table 4. Frequency distribution of responses to the st atements: “To what extent is your leader helpful or unhelpful in making performance-enhancing food choices?” (1=very unhelpful, 5=very helpful) and “My drill sergeant/cadre members believe(s) it's important to eat for performance.” (1=strongly disagree, 5=strongly agree) (N=486).BCT (N=247) n (percentage of N)fAIT (N=239) n (percentage of N)fTotal (N=486) n (percentage of N)fPlease rate the extent to which your leadera is helpful or unhelpful in making performance-oriented choices.bVery unhelpful 5 (2.1%)28 (11.9%)33 (6.9%) Somewhat unhelpful 7 (2.9%)15 (6.4%)22 (4.6%) Neutral 49 (20.2%)132 (56.2%)181 (37.9%) Somewhat helpful 74 (30.5%)38 (16.2%)112 (23.4%) Very helpful 108 (44.4%)22 (9.4%)130 (27.2%) Mean SDc4.120.9673.051.043.591.138 Level of agreement or disagreement that leaders believe it is important to eat for performance.dStrongly disagree 1 (0.4%)11 (4.6%)12 (2.5%) Disagree 6 (2.4%)22 (9.3%)28 (5.8%) Not Sure 27 (11.0%)98 (41.4%)125 (25.9%) Agree 62 (25.3%)80 (33.8%)142 (29.5%) Strongly agree 149 (60.8%)26 (11.0%)175 (36.3%) MeanSDe4.440.8153.370.9603.911.036a. Leader refers to drill sergeants in the BCT survey and to cadre in the AIT survey. b. Level of helpfulness or unhelpfulness response distributions differed significantly across BCT and AIT (2=125.365, df=4, P <.0001) c. Mean level of helpfulness differed significantly between BCT and AIT ( t =11.6597, df=476, P <.0001) d. Level of agreement or disagreement response distributions differed significantly across BCT and AIT (2=146.445, df=4, P <.0001) e. Mean level of agreement differed significantly between BCT and AIT ( t =13.2067, df=480, P <.0001) f. All percentages reported are valid percentages.

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October – December 2013 85THE ARMY MEDICAL DEPARTMENT JOURNAL 2. Leaders teach Soldiers how to eat. 3. Leaders rush Soldiers to eat quickly in order to return to training. 4. Leaders in uence choice through example but often do not make the healthy choice. 5. Leaders have no in uence on food choices. Table 6 provides an overview of the number of focus groups in which each theme emerged, the total number of times that Soldiers within the 10 groups made a comment consistent with each theme, and direct quotes that exemplify the theme. When asked how leaders in uenced their eating habits, Soldiers within 9 of the 10 focus groups made 25 references to having experienced negative consequences as a result of their food choices, including the amounts of food and the types of food they selected. The consequences included being forced to eat, being punished with physical activity (eg, doing push-ups), and psychological repercussions such as being made to feel guilty or humiliated. In all 10 of the focus groups, Soldiers mentioned their leaders taught them how to eat. Most (n=18) of the 19 references within this theme suggested cadre instructed the Soldiers to select the healthiest food options, except in one BCT group. In this instance the Soldier expressed his drill sergeant instructed him that it did not matter what he ate as long as he could keep up his physical performance. In all 6 of the BCT focus groups and one AIT focus group, Soldiers talked about their leaders rushing them to eat and nish their meals in a minimum amount of time. The Soldiers also discussed not having the time to taste their food or not being able to eat enough food in the allowed time period to keep them full until the next meal. Five of the Soldier focus groups referenced the fact that their leaders led by example but were not always effective role models for eating in the DFACs or eating healthy foods. A number of the Soldiers complained that cadre members would purchase fast food and eat it in front of the AIT and BCT Soldiers. Soldiers perceived this as hypocritical. Soldiers in 3 groups made a total of 4 references that their leaders did not in uence the way the Soldiers ate in any capacity. These Soldiers stated that they were not concerned with repercussions and that they would eat whatever they wanted to eat regardless of what their cadre told them to do. COMMENT Although there were a few references in the focus groups that leaders do not affect eating practices, both survey and focus group results suggest BCT drill sergeants and AIT cadre in uence most Soldiers’ nutrition practices within IMT to some extent. Overall, two-thirds of the survey sample agreed or strongly agreed that their leaders believed it is important to eat for performance, and more than half reported their leaders were helpful or very helpful in making performance-enhancing food choices. This is consistent with past research in similar populations demonstrating leaders’ in uence on health behaviors (eg, among college athletes who look to trainers and coaches for nutrition information).28-30 Focus group results suggest Soldiers nd it particularly useful when cadre members teach them how and what to eat to optimize their performance, especially as it relates to the day’s activities or the Army Physical Fitness Test (APFT). Various studies have used skill building as part of an intervention to improve dietary habits, and Table 5. Pearson product-moment correlation coef cients of perceived level of leadera helpfulness in making performanceenhancing food choices and level of agreement that leaders believe it is impo rtant to eat for performance with various additional constructs of interest to the Soldier Fueling Initiative program evaluation.Perceived level of leader helpfulness in making performance-enhancing food choices Level of agreement that leaders believe it is important to eat for performance BCTN=247AITN=239BCTN=247AITN=239Frequency of using Go for Green labels 0.173b0.154c0.276c0.014 Frequency of selecting "green" items from the DFAC 0.100 0.135c0.179c0.115 Frequency of selecting "amber" items from the DFAC -0.0200.100-0.0080.100 Frequency of selecting "red" items from the DFAC -0.0350.096-0.0940.096 Frequency of selecting performance-oriented food choices 0.169b0.255c0.383c0.235cFrequency of selecting performance-limiting food choices 0.0560.070 Level of perceived knowledge regarding eating for physical performance 0.146c0.254cLevel of perceived knowledge regarding eating for cognitive performance 0.178b0.263cAttitude toward eating for performance in BCT or AIT 0.131c0.225b0.268c0.336ca. Leader refers to drill sergeants in the BCT survey and to cadre in the AIT survey. b. Correlation is statistically significant at P <.001. c. Correlation is statistically significant at P <.05

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86 http://www.cs.amedd.army.mil/amedd_journal.aspxthese tangible skills may be more useful than knowledge alone.28,29 Moreover, Bandura asserts, “Motivation is enhanced by helping people to see how habit changes are in their self-interest and the broader goals they value highly.”17 The IMT leaders are encouraged not only to educate their Soldiers on nutrition, but also to build skills regarding how to eat for performance and use motivational tactics to drive the desired behavior.31-33Signi cant differences existed in Soldiers’ perceptions of leader in uence between BCT and AIT. Three times as many BCT Soldiers as AIT Soldiers reported their leaders were helpful or very helpful in making performance-enhancing food choices, and nearly twice as many BCT Soldiers as AIT Soldiers agreed that leaders believe it is important to eat for performance. While there are several potential explanations for this nding, THE IMPORTANCE OF LEADERSHIP IN SOLDIERS’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION Table 6. Themes emerging from focus groups conducted with Initia l Military Training Soldiers when asked, “How do Army cadre members in uence your eating?”ThemeNumber of groups in which theme was mentioned (N=10) Total number of references to the theme within the group Examples of Soldier quotes for each theme Leaders influence food choices through consequences related to selection 925 … we get yelled at because we don’t eat everything on our plate so that makes us eat a whole bunch more and stuff ourselves. BCT participant If they see certain people they’ll heckle certain people in the cafeteria… They never tell us we can’t eat anything, they’re just going to make you feel like dirt. You know, “are you sure you should be eating that, fatty? You failed your PT and do you really need that?” BCT participant [My Drill Sergeant] figured 44 push-ups a person for one piece of cake. BCT participant Leaders teach Soldiers how to eat 1019 Even though they had to pay for meals, [the Drill Sergeants] would eat with us, and they would be like, ‘You know, I see you getting that cheeseburger right there. You know you got a PT test coming up.’ They would, you know, influence us drastically. AIT participant Now, in basic, I had a Drill Sergeant and he was really, really healthy, working out, eating healthy, and so, he told us kidney beans, wheat bread, stuff like that was healthier. AIT participant Leaders rush Soldiers to eat quickly in order to return to training 719 Oh yeah. What they say, ‘eat now, taste it later. AIT participant …we'll go to sit down and even though we just sat down, he'll be like, “Alright you got three minutes to eat everything on your plate” when we just sat down with a full plate of food. BCT participant I believe the Drill Sergeants … try to rush you out sometimes depending on what we got going so you won't get all of the food we would like to get. BCT participant They tell you, “You don’t need to taste it. You can just throw it up and taste it later.” BCT participant Leaders influence choice through example but often do not make the healthy choice 514 I was riding with a Drill Sergeant the other day and I was with one of my battle buddies, they had to go somewhere, and the Drill Sergeant stopped by Taco Bell and I'm thinking to myself “What now?” BCT participant … why would you take advice from somebody that's picking on you and then brings you Burger King, orders Pizza Hut… Eating the chocolate cake… you know, it’s kind of hypocritical. BCT participant I just hate the fact that they eat the stuff that we're supposedly not allowed to in front of us like Skittles. BCT participant Leaders have no influence on food choices 34 I actually just learned to kind of ignore the Drill Sergeants when it comes to food because honestly they just give you a hard time. BCT participant The Drill Sergeants, they could say something, but unless it’s physically something I can’t eat, I’m going to eat it anyway. BCT participant

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October – December 2013 87THE ARMY MEDICAL DEPARTMENT JOURNAL the disparity warrants additional research. Within BCT, drill sergeants are involved in instructing the Performance Nutrition Education course, which may increase the extent to which Soldiers perceive them as information brokers or resources related to nutrition information. Furthermore, Soldiers within BCT are under more direct supervision and may spend more time with their drill sergeants than Soldiers in AIT spend with their cadre because of the nature of the training type and phase of IMT.34 The physical demands of BCT may also be higher than those of AIT, possibly in uencing the extent to which BCT leaders emphasize the need to eat for performance or to consider the day’s duties when making food choices. That said, proper nutrition is essential for cognitive performance in addition to physical performance.35-38 Although the duties and demands of AIT may differ from those of BCT, it will be important for AIT cadre and military leaders who are responsible for Soldiers in more cognitively demanding roles to showcase the relationship between nutrition and the ability to perform intellectually as well as physically. As levels of perceived helpfulness of leaders in making performance enhancing food choices and agreement that leaders believe it is important to eat for performance increased, so too did a variety of relevant SFI outcomes. For example, Soldiers who reported higher levels of leader helpfulness in making performanceenhancing food choices also reported higher frequency of use of Go for Green labels, higher frequency of selecting performance-oriented food choices, a greater positive attitude and commitment toward eating for performance, and higher levels of self-reported knowledge regarding what to eat for physical and cognitive performance. Correlation coef cients with these outcomes indicated small to moderate effect sizes suggesting that in addition to leader in uence, there are other factors that affect nutritional attitudes and behavior. This is consistent with ecological models of health behavior which assert there are numerous in uences to behavior.15 Despite small to moderate effect sizes, these ndings suggest if leaders develop strategies to improve their helpfulness in assisting Soldiers to make performance-enhancing choices and communicate to their Soldiers that they believe it is important to eat for performance, it could be expected that Soldiers will experience at least slight improvements in their nutritional attitudes and behaviors. Survey ndings suggest leader in uence is most relevant for positive behaviors (eg, frequency of use of Go for Green labels, frequency of selecting performanceenhancing choices, positive attitudes toward nutrition) and has no signi cant association with negative behaviors (eg, selecting “red” foods from the DFAC in BCT or AIT, selecting performance-limiting food selections in AIT). In other words, data suggest that even as helpfulness and perceptions that eating for performance is important to their leaders increased, Soldiers’ consumption of performance-limiting choices did not decrease. This sentiment was echoed in a few focus group quotes stating that Soldiers were going to eat what they wanted despite what their leaders said. Focus groups further revealed that the most common theme associated with cadre effect on nutrition was that military leaders often issue consequences associated with negative food choices within IMT, and BCT in particular. Previous literature suggests punishment in the form of ostracism may lead to negative emotional and psychological reactions which can impair one’s ability to self-regulate and self-monitor, which are required elements for controlled eating.39 Because positive role modelling may be a better method for improving diet than punishment or attempts to control another person’s diet, IMT leaders should be cautioned against controlling choices or using punishment to guide Soldiers’ food selection and, rather, should be encouraged to model and support desired behaviors.40 Based on ndings from this evaluation, this strategy is receiving increased emphasis within the IMT Drill Sergeants School. Recent research reports drill sergeant candidates believe they are role models for Soldiers and try to avoid eating certain foods in front of their Soldiers.23 Our ndings suggest Soldiers perceive leaders are examples in the area of nutrition; however, Soldiers indicated that their leaders did not always serve as the most effective role models in this area. This may be further re ected by survey results indicating that nearly a third of Soldiers in IMT did not agree that their leaders believed it was important to eat for performance. There were several references to leaders going to fast food establishments, and some Soldiers commented that leaders were hypocritical regarding nutrition because they would eat the foods they told Soldiers not to eat. The importance of effective role models in observational learning is a key aspect of several health behavior theories, the Social Cognitive Theory in particular.17 Therefore, leaders are encouraged to demonstrate positive nutrition practices for their Soldiers and to engage in the behaviors they want to see in their Soldiers. Lastly, focus groups revealed that Soldiers in BCT were frequently rushed to consume as much food as possible in as short a period of time as possible in order to return to physical training. Studies of children and school lunches have shown that eating speed is related to the loss of control with regard to food intake as well as obesity.41 Insuf cient time allocated for meals may lead to overeating. The importance of physical training within

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88 http://www.cs.amedd.army.mil/amedd_journal.aspxIMT, and BCT in particular, is indisputable. However, it is equally important for Soldiers to develop positive nutritional practices and habits during training. Initial Military Training leaders must prepare Soldiers for future success by providing them with a reasonable amount of time in which to eat during BCT, as mealtime provides Soldiers with the opportunity to refuel for performance. Conclusions from this study are limited because it used only self-report data at one point in time. No causal inferences can be made between any constructs of interest. e study used a convenience sample from only 2 locations (one BCT and one AIT) with a relatively small sample size, so results cannot be generalized to the entire training community or the military as a whole. Analyses did not control for demographic di erences between BCT and AIT, and some constructs (eg, selection of performance-limiting choices, perceived level of knowledge regarding what to eat for physical and cognitive performa nce) were only measured on the AIT survey, so no comparisons could be made with BCT Soldiers. To the best of our knowledge, this is the rst study using a mixed-methods design to examine the in uence of leadership on nutrition practices within the Army. Findings from this investigation suggest the need for additional study, particularly in the areas of variation in leader in uence in different environments (eg, training versus operational), the effect of consequences for performance-limiting choices on food selection within the military, and the effectiveness of strategies designed to increase leadersÂ’ helpfulness and improve their attitudes regarding the importance of eating for performance in order to change not only their own behaviors and attitudes but those of their Soldiers as well. RELEVANCE TO THE PERFORMANCE TRIAD The Army Performance Triad is designed to promote activity, nutrition, and sleep within the Army Family. This study suggests Army leaders have the potential to affect SoldiersÂ’ nutritional attitudes and behaviors and may be likely to in uence activity and sleep behaviors as well. When designing and implementing strategies and tactics as part of the Performance Triad, Army leaders must be included as a target audience for program messaging (ie, an intervention group), and they could also be used as key opinion leaders to disseminate information and model positive behaviors for Soldiers. RECOMMENDATIONS The Army should do the following to ensure leaders are prepared to support positive nutrition practices within the Triad: Provide up-to-date information to leaders so they are knowledgeable regarding healthy, performanceoriented nutrition practices. Previous research indicated some leaders are not as knowledgeable as they would like to be about nutrition.23 Emphasize that leaders should demonstrate a personal commitment to positive habits because their Soldiers look to them as role models; it is important that leaders not only tell Soldiers what to do but also model that behavior themselves. Instruct leaders on how to be helpful to Soldiers with regard to nutrition, and provide them with tools and techniques (other than reprimand) to guide Soldiers to desired behaviors. Leaders should do the following to optimize performance-oriented nutrition choices among their Soldiers: Deliver additional education in both AIT and in the operational environment to continue the momentum initiated in BCT, and help AIT and operational Soldiers understand how to eat for performance and sustain energy if their activities are less physically demanding than in BCT. Learn, remember, and reinforce key concepts associated with programming to send consistent messages; approach programming with a positive attitude. Routinely emphasize the importance of nutrition for both cognitive and physical performance. Lead by example by selecting healthy foods and modeling positive nutritional habits. Avoid reprimand and punishment associated with selections such as dessert or nutrient-poor foods; reinforce performance-oriented food choices instead. Offer speci c suggestions to Soldiers about how best to eat for the dayÂ’s activities. Assist Soldiers in making the connection between nutrition and outcomes that are meaningful to them (eg, APFT performance) in order to motivate them to make performance-oriented choices. In addition to APFT performance, previous literature suggests appearance, health, and meeting military weight standards are additional important motivators for healthy eating in the military.42 Serve as a resource to subordinate Soldiers by becoming knowledgeable about nutrition and by identifying additional resources to which Soldiers can be directed for additional information. Although these recommendations and the ndings from this study are focused solely on nutrition, many of them have the potential to translate across activity and sleep. When either reinforcing or changing behavior within a military community is attempted, leadership engagement, role modeling, and commitment are likely to make a positive difference. THE IMPORTANCE OF LEADERSHIP IN SOLDIERSÂ’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

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October – December 2013 89THE ARMY MEDICAL DEPARTMENT JOURNAL REFERENCES1. Karl JP, Lieberman HR, Cable SJ, Williams KW, Young AJ, McClung JP. Randomized, double blind, placebo-controlled trial of iron supplementation in female Soldiers during military training: effects on iron status, physical performance and mood. Am J Clin Nutr 2009;90(1):124-131. 2. Andersen NE, Karl JP, Cable SJ, et al. Vitamin D status in female military personnel during combat training. J Int Soc Sports Nutr 2010;7:38. 3. Jones BH, Thacker SB, Gilchrist J, Kimsey CD Jr, Sosin DM. Prevention of lower extremity stress fractures in athletes and soldiers: A systematic review. Epidemiol Rev 2002;24(2):228-247. 4. Wentz L, Lui PY, Haymes E, Illich JZ. Females have greater incidence of stress fractures than males in both military and athletic populations: a systematic review. Mil Med 2011;176(4):420-430. 5. Stewart T, May S, Allen HR, et al. Development of an internet/population-based weight management program for the US Army. J Diabetes Sci Technol 2008;2(1):116-126. 6. Deuster PA, Weistein AA, Sobel A, Young AJ. War ghter nutrition: current opportunities and advanced technologies report from a department of defense workshop. Mil Med. 2009;174(7):671-677. 7. Guide to Community Preventive Services. Promoting good nutrition [internet]. Available at: http:www.thecommunityguide.org/nutrition/index. html [updated March 29, 2012]. Accessed May 28, 2013. 8. Department of Defense. 2008 Department of Defense Survey of Health Related Behaviors among Active Duty Military Personnel. Research Triangle Park, NC: RTI International; 2009. 9. Skiller B, Booth C, Coad R, Forbes-Ewan C. Assessment of nutritional status and fatigue among Army recruits during Army common recruit training course; Part A: catering services and diet. Defence Science and Technology Organisation, Victoria (Australia) CBRN Defence Centre. 2005.Available at: http://handle.dtic.mil/100.2/ADA447856. Accessed May 28, 2013. 10. Aoi W, Naito Y, YoshikawaT. Exercise and functional foods. Nutr J 2006;5:15. 11. Henderson NE, Knapik JJ, Shaffer SW, McKenzie TH, Schneider GM. Injuries and injury risk factors among men and women in US Army combat medic advanced individual training. Mil Med 2000;165(9):647-652. 12. Smith TJ, Sigrist LD, Bathalon GP, McGraw S, Karl JP, Young AJ. Ef cacy of a meal-replacement program for promoting blood lipid changes and weight and body fat loss in US Army Soldiers. J Am Diet Assoc. 2010;110(2):268-273. 13. Bedno SA, Li Y, Han W, et al. Exertional heat illness among overweight US Army Recruits in basic training. Aviat Space Environ Med 2010;81(2):107-111. 14. US Army Food Program. Implementation Guide for Initial Military Training Soldier Fueling Initiative Available at: http://www.quartermaster.army. mil/jccoe/Operations_Directorate/QUAD/nutri tion/Implementation_Guide_January_2012.pdf [updated January 30, 2012]. Accessed May 31, 2013. 15. McLeroy KR, Bibeau D, Steckler A, Glanz K. An ecological perspective on health promotion programs. Health Educ Q 1988;15(4):351-377. 16. Bandura A. Self-ef cacy: toward a unifying theory of behavioral change. Psychol Rev 1977;804:191-215. 17. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31:143-164. 18. Schunk DH. Peer models and children’s behavioral change. Rev Educ Res 1987;57(2):149-174. 19. Valente TW, Pumpuang, P. Identifying opinion leaders to promote behavior change. Health Educ Behav. 2007;34:881-896. 20. Campbell MK, Hudson MA, Resnicow K, Blakeney N, Paxton A, Baskin M. Church-based health promotion interventions: evidence and lessons learned. Annu Rev Public Health 2007;28:213-234. 21. Peterson J, Atwood JR, Yates B. Key elements for church-based health promotion programs: outcome-based literature review. Public Health Nurs 2002;19(6):401-11. 22. Lumpkins CY, Greiner KA, Daley C, Mabachi NM, Neuhaus K. Promoting Healthy Behavior from the Pulpit: Clergy share their perspectives on effective health communication in the African American church [epub ahead of print]. J Relig Health 2011. Available at: http://link.springer.com/article/10.100 7%2Fs10943-011-9533-1. Accessed May 28, 2013. 23. Glover S, Williams E, Kresslein J, et al. Fort Jackson Identifying Health Barriers Project: Soldier Health Promotion to Examine and Reduce Health Disparities (SHPERHD). Fort Detrick, MD: US Army Medical Research and Materiel Command; 2012. 24. Creswell JW, Fetters MD, Ivankova NV. Designing a mixed methods study in primary care. Ann Fam Med 2004;2(1):7-12. 25. Curry LA, Nembhard IM, Bradley EH. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation 2009;119(10):1442-1452.

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90 http://www.cs.amedd.army.mil/amedd_journal.aspx26. MacQueen KM, McLellan E, Kay K, Milstein B. Codebook development for team-based qualitative analysis. Cult Anthropol Meth 1998;10:31-36. 27. NHLBI Obesity Education Initiative Working Group. The Practical Guide. Identi cation, Evaluation, and Treatment of Overweight and Obesity in Adults. NIH Publication Number 00-4084. Bethesda, MD: National Institutes of Health; 2000:1. 28. Torres-McGehee TM, Pritchett KL, Zippel D, Minton DM, Cellamare A, Sibilia M. Sports nutrition knowledge among collegiate athletes, caches, athletic trainers, and strength and conditioning specialists. J Athl Train. 2012;47(2):205-211. 29. Jacobson BH, Sobonya C, Ransone J. Nutrition practices and knowledge of college varsity athletes: a follow-up. J Strength Cond Res. 2001;15(1):63-68. 30. Shif ett B, Timm C, Kahanov L. Understanding of athletesÂ’ nutritional needs among athletes, coaches and athletic trainers. Res Q Exerc Sport. 2002;73(3):357-362. 31. Carpenter RA, Finley C, Barlow CE. Pilot test of a behavioral skill building intervention to improve overall diet quality. J Nutr Educ Behav 2004;36(1):20-24. 32. Ball K, McNaughton SA, Le H, Andrianopoulos N, Inglis V, McNeilly B, et al. ShopSmart 4 Health Protocol of a skills-based randomised controlled trial promoting fruit and vegetable consumption among socioeconomically disadvantaged women. BMC Public Health 2013;14(13):466. 33. Fisher JD, FisherW A. The information-motivation-behavioral skills model. In: DiClemente R, Crosby R, Kegler R, eds. Emerging Promotion Research and Practice. San Francisco, CA: Josey Bass Publishers; 2005:40-70. 34. United States Army Training Centers. Initial Entry Training Family Handbook. Available at: http:// www.jackson.army.mil/sites/bct/docs/2 [revised January 2010]. Accessed June 6, 2013. 35. Brown JL, Pollitt E. Malnutrition, poverty and intellectual development. Sci Am 1996;274(2):38-43. 36. Isaacs E, Oates J. (2008). Nutrition and cognition: assessing cognitive abilities in children and young people. Eur J Nutr. 2008;47(3):4-24. 37. Donohoe RT, Benton D. Cognitive functioning is susceptible to the level of blood glucose. Psychopharmacology (Berlin). 1999;145(4):378-385. 38. Turner J. Your Brain on Food: a nutrient rich diet can protect cognitive health. J Am Soc Aging 2011;35(2):99-106. 39. Salvy SJ, Bowker JC, Nitecki LA, Kluczynski MA, Germeroth LJ, Roemmich J N. Impact of simulated ostracism on overweight and normal-weight youthsÂ’ motivation to eat and food intake. Appetite 2011;56(1):39-45. 40. Scaglioni S, Salvioni M, Galimberti C. In uence of parental attitudes in the development of childrenÂ’s eating behaviour. Br J Nutr. 2008;99: S22-S25. 41. Zandian M, Ioakimidis I, Bergstrom J, et al. Children eat their school lunch too quickly: an exploratory study of the effect on food intake. BMC Public Health 2012;12(1):351-358. 42. Sigrist LD, Anderson JE, Auld GW. Senior military of cersÂ’ educational concerns, motivators and barriers for healthful eating and regular exercise. Mil Med. 2005;170(10):841-845.AUTHORSDr Jackson, Ms Jin, Ms Robinson, Ms Dennis, Ms Vo, Dr Prosser, and Mr Rawlings are with the Health Promotion and Wellness Portfolio, Public Health Assessment Program, Army Institute of Public Health, US Army Public Health Command, Aberdeen Proving Ground, Maryland. COL Cable is with the Initial Military Training Center of Excellence, Fort Eustis, Virginia.THE IMPORTANCE OF LEADERSHIP IN SOLDIERSÂ’ NUTRITIONAL BEHAVIORS: RESULTS FROM THE SOLDIER FUELING INITIATIVE PROGRAM EVALUATION

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October – December 2013 91The Dietary Guidelines for Americans (DGAs) provide comprehensive nutrition recommendations that promote a healthy diet and body weight, thereby reducing the risk for chronic disease. The DGAs, released by the United States Department of Agriculture (USDA) and the Department of Health and Human Services, are revised every 5 years to re ect new scienti c ndings. The 2010 DGAs1 focus on choosing foods that are nutrient dense (food that contains the highest concentration of nutrients per unit of energy). The 2010 DGAs speci cally recommend limiting the intake of sodium, saturated fat, dietary cholesterol, trans fat, added sugars, re ned grains, and alcohol; and increasing the intake of vegetables, fruits, whole grains, low-fat dairy, lean protein, seafood, oils, potassium, dietary ber, calcium, and vitamin D. Individual adherence to the DGAs can be quanti ed using a scoring rubric known as the healthy eating index (HEI). The HEI controls for the energy intake of a diet and measures diet quality.2-4 The rst HEI score was released in 1995 and subsequently updated in 2005 to re ect the revised DGAs. The HEI has been used to evaluate diet quality in the American adult population using data from the National Health and Nutrition Examination Survey (NHANES).5 For example, one report indicates that individuals in the highest quartile of HEI scores (meanSE of the mean=69.90.13) were less likely to be obese or overweight, have elevated blood pressure, metabolic syndrome, and decreased high-density lipoprotein when compared to those in the lowest quartile of HEI scores (33.60.10).6 These data suggest that the HEI may be an appropriate tool to identify those with a poor diet who may bene t the most from nutrition interventions. The data also demonstrate that lower HEI scores are associated with chronic disease risk in older adults. Prior studies that assessed the intake of speci c nutrients in military populations have revealed dietary inadequacies that may affect Soldier performance and risk for injury.7-9 However, comprehensive studies detailing total diet quality of meals consumed by military personnel Assessment of Dietary Intake Using the Healthy Eating Index During Military TrainingLaura J. Lutz, MS, RD Erin Gaffney-Stomberg, PhD, RD Jenna L. Scisco, PhD COL Sonya J. Cable, SP, USA J. Philip Karl, MS, RD Andrew J. Young, PhD James P. McClung, PhDABSTRACTObjective: The objectives of this study were to use the healthy eating index (HEI) as a tool to characterize diet quality in Soldiers (n=135) during basic combat training (BCT), and to assess the effects of BCT on diet quality by comparing HEI scores before and after the training period.Methods: HEI scores were calculated from a 110-item semiquantitative food frequency questionnaire. Soldiers were then divided into tertiles (high, medium, and low) of diet quality based upon HEI scores at the start of BCT.Results: No relationships between pre-BCT total HEI score and age, sex, racial background, or physical activity were observed. The odds of being a smoker were 4.75 times higher for those in the low HEI tertile and 3.03 times higher for those in the medium HEI tertile when compared to those in the high HEI tertile (95% CI, 1.67, 13.48 and 1.04, 8.82 respectively). Diet quality improved in the medium and low HEI tertiles over the course of BCT, as total HEI scores increased by 22% and 46% respectively ( P <.05) with time in these groups. Although different at the start of BCT, HEI scores were similar between the medium and high HEI tertiles at the end of BCT.Conclusion: Study ndings suggest that the BCT dining environment elicits positive changes in diet quality for Soldiers who enter military training with lower diet quality, and the HEI appears to be a useful tool to identify military personnel with lower diet quality at the start of training. This may provide the opportunity to target interventions such as diet counseling and education in an effort to improve Soldier health and performance.

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92 http://www.cs.amedd.army.mil/amedd_journal.aspxwithin garrison environments are limiting. As such, the objective of this study was to characterize the diet quality of Soldiers, using the HEI, during basic combat training (BCT), the 9 to 10 week initial Army training course for enlisted personnel. In addition, the effect of BCT on diet quality was assessed by comparing HEI scores before and after the training period. METHODSVolunteersThis study was approved by the Human Use Review Committee at the US Army Research Institute of Environmental Medicine and was conducted at Fort Jackson, South Carolina. Human volunteers participated in this study after providing their free and informed voluntary consent. Investigators adhered to US Army Regulation 70-25 10 and US Army Medical Research and Materiel Command Regulation 70-25 ,11 both of which provide guidance on the participation of volunteers in research. The data presented in this manuscript were collected in conjunction with a study that assessed the prevalence of cardiometabolic risk in Army recruits.12A total of 209 US Army recruits (118 male, 91 female) volunteered to participate in this study. Volunteers were excluded if they reported implausible energy intake (<300 or >4,500 kcal/day for women and <800 or >5,000 kcal/day for men), or if they were missing data at the end of BCT due to separation from their unit or withdrawal from the study. In total, 135 volunteers (76 male, 59 female) were included in the nal analyses. The baseline demographics of the study population are presented in Table 1. Dietary intake and background information were collected from the volunteers at the beginning and end of BCT. In their studies, Knapik et al13,14 describe BCT as a 9 to 10 week course consisting of both physical and military-speci c training.Healthy Eating Index ScoreThe HEI is the composite of 12 component scores and ranges from 0 to 100, with a score of 100 indicating perfect compliance with the DGAs. The 9 adequacy components are: Total fruit Whole fruit Total grains Whole grains Total vegetables Dark green and orange vegetables and legumes Meat and beans Milk Oils The 3 moderation components are: Sodium Saturated fat Calories from solid fats, alcoholic beverages, and added sugars (SoFAAS) The HEI scores were calculated from a 110-item, semiquantitative, Block 2005 food frequency questionnaire (FFQ) (NutritionQuest, Berkeley, CA).15,16 The fulllength, 3-month version of the validated FFQ was used, having been adapted from the full-length, 12-month version by the omission of seasonality questions about fruit consumption. During the second administration of the FFQ, volunteers were instructed to provide data regarding dietary intake during the BCT period only. Volunteers self-reported dietary intake by completing the FFQ at the beginning of BCT, capturing their intake over the 3 months prior to entering the Army, and completing it again at the end of BCT, capturing their dietary intake during BCT. The food list on the FFQ was developed from NHANES 1999-2002 dietary recall data, and volunteers recorded both the quantity of food items consumed and the frequency of their consumption. The total daily energy and nutrient intake and the number of daily servings within food groups were calculated by NutritionQuest (Berkeley, CA) using the USDAÂ’s Food and Nutrient Database for Dietary Studies v.1.017 and the MyPyramid Equivalents Database 2.0.18ASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING Table 1. Demographic Characteristics at Baseline. HEI TertilesHigh (n=45) Medium (n=45) Low (n=45) HEI Score Pre ( P <.01)73.16.260.33.446.94.4 Age (yr) (meanSD) ( P =.50) 23.85.923.15.122.35.1 Sex ( P =.68)Male 232627 Female 221918 Racial Background ( P =.55)White 253027 Black/AfricanAmerican 8811 Other 1277 Activity ( P =.19)Less than 20 minutes per day 141222 More than 20 minutes per day 313322 Smoker* ( P <.01)Yes 61419 No 393026HEI indicates Healthy Eating Index. *Smoker defined as smoking more than every other day over the past 30 days.

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October – December 2013 93THE ARMY MEDICAL DEPARTMENT JOURNAL Twelve HEI component scores and total HEI scores were determined according to the HEI guidelines.2-4 Methods for scoring the HEI components appear in Table 2. Higher scores indicate increased consumption of adequacy components (consume more of) and decreased consumption of moderation components (consume less of), indicating a greater level of dietary quality.Statistical AnalysisChanges in HEI total and component scores were analyzed as secondary outcomes in a trial powered to characterize the prevalence of cardiometabolic risk during BCT.12 For the present analysis, change in the HEI total score was considered the primary outcome of interest. Post-hoc power calculations were therefore completed using the HEI total score or change in the HEI total score as the dependent variable. For all statistical analyses, volunteers were divided into equal tertiles based on their baseline HEI score. One-way analysis of variance (ANOVA) with Bonferroni corrections was used to determine differences between HEI tertiles for age. The 2 test was used to determine differences in categorical variables across HEI tertiles, and logistic regression was used to determine odds ratios and 95% con dence intervals (CIs). Mixed model ANOVA was used to determine within (time) and between (group) tertile differences in HEI scores. Signi cance for all analyses was assumed when P <.05. All statistical analyses were completed after normality was assessed using the IBM SPSS Statistics (V 20.0) application (IBM Corp, Chicago, IL). RESULTS Baseline HEI scores, indicative of dietary intake prior to BCT, did not differ according to age, sex, race, or physical activity (Table 1). However, those volunteers with low diet quality were more likely to be smokers than nonsmokers ( P <.05). Speci cally, the odds of being a smoker were 4.75 times higher for those in the low HEI tertile and 3.03 times higher for those in the medium HEI tertile when compared to those in the high HEI tertile (95% CI, 1.67, 13.48, and 1.04, 8.82 respectively). Diet quality improved in the medium and low HEI tertiles over the course of BCT, as total HEI scores increased ( P <.05) with time in these groups. In fact, total post-BCT HEI scores were similar between the medium and high HEI tertiles at the end of BCT as shown in Table 3. Total HEI scores did not change over the course of BCT in those volunteers categorized in the high tertile at the start of training. Analysis of the 12 components of the HEI indicate that saturated fat, SoFAAS, oils, total fruit, whole fruit, total grain, whole grain, and total vegetable component scores improved ( P <.05), and sodium scores declined ( P <.05) during BCT for volunteers in the low tertile. Over the course of BCT, volunteers in the medium tertile demonstrated similar improvements ( P <.05) in component scores as those in the low tertile, except for a lack of improvement in the oil component. Volunteers beginning BCT in the high tertile demonstrated improvements ( P <.05) in the whole fruit, total grain, and whole grain components and a decrement ( P <.05) in the oil component over the course of BCT. COMMENT The objectives of this study were to use the HEI as a tool for assessing dietary quality in military personnel and to assess changes in diet quality during training. The major nding was that diet quality improved in Soldiers beginning BCT with the lowest diet quality. These ndings indicate that the HEI may be used as a tool for identifying military personnel with low diet quality for nutrition interventions, and that dietary quality may improve during the course of initial military training for Soldiers who come into the military with poor eating habits. Consistent with previous ndings in US adults, we report diminished diet quality in smokers as compared to nonsmokers.3 However, unlike previous studies in civilian populations using NHANES data,19 we did not observe better diet quality in women than men. This may be due to the limited sample size of the current study or Table 2. HEI Component Scoring Rubric.ComponentaScore Range Standard for the Maximum ScorebStandard for the Minimum ScorebTotal fruit0-50.8 cup equiv.0 cup equiv. Whole fruit0-50.4 cup equiv.0 cup equiv. Total vegetables0-51.1 cup equiv0 cup equiv. Dark green and orange vegetables and legumes0-50.4 cup equiv.0 cup equiv. Total grains0-53.0 oz equiv.0 oz equiv. Whole grains0-51.5 oz equiv.0 oz equiv. Milk0-101.3 cup equiv.0 cup equiv. Meat and beans0-102.5 oz equiv.0 oz equiv. Oils0-1012 grams0 grams Saturated fatc0-107% of total energy 15% of total energy Sodiumc0-100.7 grams 2.0 grams Calories from solid fats, alcoholic beverages, and added sugars0-2020% of total energy 50% of total energyHEI indicates Healthy Eating Index. a. Defined per HEI guidelines.2b. Per 1000 kcal, unless percentage of energy. c. Receive scores of 8 for intakes that reflect Dietary Guidelines for Americans recommendations.

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94 http://www.cs.amedd.army.mil/amedd_journal.aspxto differences between military personnel and civilians in terms of diet quality in the demographic included in the population sampled. The HEI scores improved during BCT for those who began their military service with lower scores. This may indicate that when exposed to a military dining environment with a variety of food choices, Soldiers are inclined to choose and may prefer healthier food options. In support of this hypothesis, we observed improvements in saturated fat, whole fruit, total and whole grain, and total vegetable intake in both the medium and low tertiles of volunteers throughout the course of BCT. Similarly, previous studies have demonstrated that when military dining facility services were altered to promote healthy diet options, such as healthy food options at the beginning of service lines and implementing the Go for Green method of rating the nutritional composition of food items, caloric and total fat intake were reduced and customer satisfaction improved as compared to the control dining facilities.20 Nutrition education strategies may also underlie improvements in diet quality. The Soldier Fueling Initiative, which provides nutrition education during BCT and highlights the consumption of nutrient dense foods in garrison dining facilities, was implemented prior to this study and may have contributed to the observed improvement in diet quality. Given the ndings of the current study, it is possible that the HEI can be used as a tool for the evaluation of initiatives aimed at improving the nutrient quality of dining options within military environments. Pasiakos et al12 previously reported improvements in lipid pro les, fasting glucose, and insulin sensitivity during BCT in this cohort. These favorable effects may be partially attributable to the improved diet quality during BCT observed in this study, as well as the physical activity encountered during BCT. Previous studies in older cohorts have demonstrated that if those with low HEI scores continue to consume poor diets, unfavorable outcomes such as overweight, obesity, and an unhealthy lipid pro le may result.6 Future studies should focus on possible relationships between HEI scores and biomarkers of chronic disease risk in military populations, which may be predictive of longer-term health outcomes. Similarly, identifying areas of the diet with the lowest component scores may add focus to nutrition education programs aimed at improving overall diet quality in young people, including military personnel, thereby establishing positive dietary habits and preventing the negative effects of poor diet later in life. ASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING Table 3 : HEI Total and Component Score (meanSD) Before and After BCT.HEI Tertiles High (n=45) Medium (n=45) Low (n=45) Effect HEI ScoreT,G,TxG Pre-BCT 73 1 6 2 60 3 3 4a46 9 4 4a,bPost-BCT 75 5 8 8 73 8 8 2c68 6 7 4a,b,cSodiumT,G,TxG Pre-BCT 3 2 1 93 3 2 34 1 2 5 Post-BCT 2 8 2 0 2 4 1 6c2 2 1 7cSaturated FatT,G,TxG Pre-BCT 7 1 2 2 5 1 2 9a4 1 3 3aPost-BCT 7 6 2 3 7 2 2 3c6 9 2 2cCalories from Solid Fats, Alcoholic Beverages, and Added Sugars T,G,TxG Pre-BCT 15 9 3 1 9 5 4 6a4 1 3 8a,bPost-BCT 14 9 3 3 14 6 3 1c13 3 2 2a,cOilsG,TxG Pre-BCT 7 8 2 47 0 2 2 5 6 2 5a,bPost-BCT 6 7 2 2c7 0 2 5 6 6 2 3cMilk Pre-BCT 6 4 3 06 2 2 75 7 2 9 Post-BCT 5 9 2 95 5 2 65 4 2 8 Total FruitT,G,TxG Pre-BCT 4 4 1 03 8 1 5 2 6 1 3a,bPost-BCT 4 5 0 9 4 3 1 1c3 9 1 4cWhole FruitT,G,TxG Pre BCT 4 3 1 0 3 5 1 5a2 3 1 2a,bPost BCT 4 8 0 5c4 5 1 1c4 4 1 1cTotal GrainT,TxG Pre-BCT 4 0 1 04 1 1 03 7 1 1 Post-BCT 4 5 0 7c4 5 0 9c4 7 0 5cWhole GrainT,G,TxG Pre-BCT 2 3 1 51 7 1 2 1 0 1 0a,bPost-BCT 3 1 1 4c3 2 1 4c2 8 1 3cMeat and Beans Pre-BCT 9 7 1 19 9 0 49 7 1 0 Post-BCT 9 8 0 79 8 0 79 7 0 9 Dark Green and Orange Vegetables and LegumesT,G Pre-BCT 3 6 1 62 5 1 61 4 1 2 Post-BCT 4 2 2 44 0 2 42 7 1 7 Total VegetablesT,G,TxG Pre-BCT 3 9 1 2 3 3 1 1a2 4 1 0a,bPost-BCT 3 8 1 2 3 9 1 2c3 6 1 1cHEI indicates Healthy Eating Index. BCT indicates basic combat training. Effects: T main effect of time G main effect of group TxG time by group interaction Notes: a. Different ( P <. 05 ) from High b. Different ( P <. 05 ) from Medium c. Different ( P <. 05 ) from Pre-BCT

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October – December 2013 95THE ARMY MEDICAL DEPARTMENT JOURNAL Strengths of this study include the longitudinal design and the use of a validated FFQ to collect dietary intake data. Weaknesses include the small sample size in comparison to larger studies, such as NHANES, conducted in civilian populations. Further, dietary intake was not collected for a full year; therefore, seasonal variation in nutritional intake may not have been captured. Future studies should include larger populations of military personnel in both training and permanent duty assignments and should follow Soldiers for longer periods to determine if improvements in their diet quality are sustained. Similarly, biomarker data may be used in conjunction with the HEI to demonstrate the effects of diet quality on indicators of nutritional status and disease risk. RELEVANCE TO THE PERFORMANCE TRIAD This study suggests that the BCT dining environment elicits positive changes in diet quality for Soldiers entering military training with lower diet quality. The HEI appears to be a useful tool to identify military personnel with low diet quality at the start of training and may be a valuable tool for evaluating nutrition initiatives within the Performance Triad Program, The US Army Surgeon General’s strategy to improve the wellness, individual performance, and resilience of the Army community through proper activity, nutrition, and sleep. The identi cation of military personnel with low diet quality early in their careers may provide the opportunity to target interventions such as diet counseling and education in an effort to improve Soldier health and performance over the course of a military career and beyond. ACKNOWLEDGEMENTThe authors have no potential con icts of interest. This project was funded by the US Army Medical Research and Materiel Command. The study sponsor had no role in study design, collection, analysis, and interpretation of data; writing the report, nor the decision to submit the report for publication.REFERENCES1. Dietary Guidelines for Americans, 2010 7th ed. Washington, DC: US Dept of Agriculture, US Dept of Health and Human Services; 2010. Available at: http://www.cnpp.usda.gov/DGAs2010-PolicyDocument.htm. Accessed July 5, 2013. 2. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB, Basiotis PP. Development and evaluation of the Healthy Eating Index-2005: Technical Report Alexandria, VA: Center for Nutrition Policy and Promotion, US Dept of Agriculture; 2007. Available at: http://www.cnpp.usda.gov/publications/ hei/hei-2005/hei-2005technicalreport.pdf. Accessed July 5, 2013. 3. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB. Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc 2008;108(11):1854-1864. 4. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet Assoc 2008;108(11):1896-1901. 5. About the National Health and Nutrition Examination Survey. Hyattsville, MD: Centers for Disease Control and Prevention National Center for Health Statistics; 2013. Available at: http://www.cdc.gov/ nchs/nhanes/about_nhanes.htm. Accessed July 5, 2013. 6. Nicklas TA, O’Neil CE, Fulgoni VL III. Diet quality is inversely related to cardiovascular risk factors in adults. J Nutr 2012;142(12):2112-2118. 7. McClung JP, Karl JP, Cable SJ, Williams KW, Nindl BC, Young AJ, Lieberman HR. Randomized, double-blind, placebo-controlled trial of iron supplementation in female soldiers during military training: effects on iron status, physical performance, and mood. Am J Clin Nutr 2009;90(1):124-131. 8. Karl JP, Lieberman HR, Cable SJ, Williams KW, Young AJ, McClung JP. Randomized, double-blind, placebo-controlled trial of an iron-forti ed food product in female soldiers during military training: relations between iron status, serum hepcidin, and in ammation. Am J Clin Nutr 2010;92(1):93-100. 9. Lutz LJ, Karl JP, Rood JC, Cable SJ, Williams KW, Young AJ, McClung JP. Vitamin D status, dietary intake, and bone turnover in female soldiers during military training: a longitudinal study. J Int Soc Sports Nutr 2012;9(1):38. 10. Army Regulation 70-25: Use of Volunteers as Subjects of Research Washington, DC: US Dept of the Army: January 1990. 11. USAMRMC Regulation 70-25: Use of Human Subjects in Research, Development, Testing and Evaluation Fort Detrick, MD: US Army Medical Research and Materiel Command; April 1990 [amended July 2003]. 12. Pasiakos SM, Karl JP, Lutz LJ, et al. Cardiometabolic risk in US Army recruits and the effects of basic combat training. PLoS ONE 2012;7(2):e31222. 13. Knapik JJ, Sharp MA, Darakjy S, Jones SB, Hauret KG, Jones BH. Temporal changes in the physical tness of US Army recruits. Sports Med 2006;36(7):613-634. 14. Knapik JJ, Darakjy S, Hauret KG, Canada S, Marin R, Jones BH. Ambulatory physical activity during United States Army basic combat training. Int J Sports Med 2007;28(2):106-115.

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96 http://www.cs.amedd.army.mil/amedd_journal.aspxASSESSMENT OF DIETARY INTAKE USING THE HEALTHY EATING INDEX DURING MILITARY TRAINING15. Block G, Hartman AM, Dresser CM, Carroll MD, Gannon J, Gardner L. A data-based approach to diet questionnaire design and testing. Am J Epidemiol 1986;124(3):453-469. 16. Block G, Woods M, Potosky A, Clifford C. Validation of a self-administered diet history questionnaire using multiple diet records. J Clin Epidemiol 1990;43(12):1327-1335. 17. USDA Food and Nutrient Database for Dietary Studies, 1.0. Beltsville, MD: Food Surveys Research Group, Agricultural Research Service, US Dept of Agriculture; 2004. Available at: http://www.ars. usda.gov/Services/docs.htm?docid=12082. Accessed July 5, 2013. 18. Bowman SA, Friday JE, Moshfegh A. MyPyramid Equivalents Database 2.0 for USDA Survey Foods, 2003-2004. Beltsville, MD: Food Surveys Research Group, Agricultural Research Service, US Dept of Agriculture; 2008. Available at: http://www.ars. usda.gov/Services/docs.htm?docid=17563. Accessed July 5, 2013. 19. Ervin RB. Healthy Eating Index-2005 total and component scores for adults aged 20 and over: National Health and Nutrition Examination Survey, 2003-2004. Natl Health Stat Report 2011;13(44):1-9. 20. Crombie AP, Funderburk LK, Smith TJ, et al. Effect of modi ed foodservice practices in military dining facilities on ad libitum nutritional intake of US Army soldiers. J Acad Nutr Diet 2013;113(7):920-927.AUTHORSMs Lutz is a project manager for the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA. Ms Gaffney-Stomberg is a research fellow with the Oak Ridge Institute for Science and Education Program and is currently located with the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA. Dr Scisco is a principal investigator for the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA. COL Cable is the Chief of the Human Dimensions Division at the Initial Military Training Center of Excellence, Fort Eustis, VA. Mr Karl is a project manager for the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA. Dr Young is chief of the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA. Dr McClung is a principal investigator for the Military Nutrition Division of the United States Army Research Institute of Environmental Medicine, Natick, MA.

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October – December 2013 97THE ARMY MEDICAL DEPARTMENT JOURNAL

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98 http://www.cs.amedd.army.mil/amedd_journal.aspxSleep, in addition to nutrition and physical activity, is a component of the Performance Triad because sleep habits among the military are problematic,1-5 and inadequate sleep is prevalent in the Army.6-8 With regard to the Performance Triad, sleep is perhaps more dif cult to control than activity and nutrition. Soldiers are at a heightened risk for diminished sleep quality as a result of dangerous working environments, loud noise exposure, and unpredictable hours.9,10 Effective sleep practices and habits that contribute to quality nighttime sleep and daytime alertness, is essential for high quality sleep.11 The phenomenon of poor sleep is occurring in parallel with the global increase in obesity and metabolic syndrome,12,13 as well as increases in depression, anxiety, and other mental health issues.8,14-19 Interestingly, poor sleep behaviors have also been associated with a pro-in ammatory state.20-24Many epidemiological and meta-analytic studies suggest these observed relationships may be bidirectional and possibly confounded by other issues.13,20,25 For example, psychological state is in uenced by and directly in uences sleep quality.26-29 Moreover, sleep-induced disturbances in circadian rhythms have been shown to affect selected endocrine parameters13,30,31 and metabolic pathways.12,13,32 Importantly, compromised sleep habits, in terms of duration and quality, may lead to insulin resistance and immunologic alterations; whereas, depression, anxiety, and life stressors can interfere with sleep duration and quality to create a vicious cycle.12,13,30-32 Finally, exercise and nutritional habits can directly in uence sleep quality and duration,5,20,33-38 in either negative or positive directions. Exercise and sleep interact bidirectionally as well. Military trainees who experienced lack of sleep due to night missions, coupled with early Sleep as a Component of the Performance Triad: The Importance of Sleep in a Military PopulationCynthia V. Lentino, MS Dianna L. Purvis, PhD Kaitlin J. Murphy, MS Patricia A. Deuster, PhD, MPHABSTRACT Objec ve: Sleep habits among military populations are problematic. Poor sleep hygiene occurs in parallel with the global increase in obesity and metabolic syndrome and contributes to a decrease in performance. The extent of sleep issues needs to be quanti ed to provide feedback for optimizing war ghter performance and readiness. This study assessed various health behaviors and habits of US Army Soldiers and their relationship with poor sleep quality by introducing a set of new questions into the Comprehensive Soldier and Family Fitness (CSF2) Global Assessment Tool (GAT). Methods: Subjects included 14,148 US Army Active, Reserve, and National Guard members (83.4% male) who completed the GAT, a self-report questionnaire that measures 4 tness dimensions: social, family, emotional, and spiritual. Approximately 60 new questions, including ones on sleep quality, within the fth CSF2 dimension (physical) were also answered. A sleep score was calculated from 2 questions validated in the Pittsburgh Insomnia Rating Scale (0 to 6). Results: Poor sleepers (5-6) were signi cantly ( P <.001) more likely than good sleepers (0-1) to consider themselves in fair or poor health, be overweight or obese, and score in the lowest quartile of the emotional, social, family, and spiritual tness dimensions. Additionally, poor sleepers were signi cantly ( P <.001) less likely to have a healthy body mass index and waist circumference, eat breakfast 6 or more times a week, meet aerobic exercise and resistance training recommendations, and pass their Army Physical Fitness Test in the top quartile. Conclusion: This study examined sleep quality in a group of military personnel and indicated signi cant associations between quality of sleep and physical performance, nutritional habits, measures of obesity, lifestyle behaviors and measures of psychosocial status. Targeted educational interventions and resources are needed to improve sleep patterns based on behaviors that can be most easily modi ed.

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October – December 2013 99morning wake-up calls, reported a diminished ability to perform daily physical training and a decline in physical tness and marksmanship testing scores.3 Weekly, moderate physical activity improves self-reported sleep quality and can result in shortened sleep latency, fewer awakenings after sleep onset, longer sleep duration, and better overall sleep ef ciency.31,39The concerns about insuf cient sleep in the military have led researchers to quantify the extent of the sleep issues in order to target educational and behavioral practices to improve sleep patterns. Thus, we conducted an investigation, in collaboration with the Army’s Comprehensive Soldier and Family Fitness program (CSF2), to assess various health behaviors and habits of US Army Soldiers. New questions were incorporated into the online Global Assessment Tool (GAT), which all nondeployed Soldiers are required to complete once per year. Family members of Soldiers and all Department of Defense (DoD) civilians may also take the GAT. The intent of the questions was to determine gaps in Soldier knowledge and behaviors relating to physical tness, nutritional habits, and sleep quality, then provide feedback to help them modify health behaviors and access resources to do so. The study examined sleep quality in Soldiers who completed the pilot launch of new GAT questions. Speci cally, we asked about sleep quality and examined how it was related to overall emotional, spiritual, social, family, physical, and nutritional tness. METHODS This pilot study was conducted using a sample population of 14,850 Soldiers and DoD civilians during a 2-week period in July 2012. Currently, the annual GAT measures health in 4 psychosocial dimensions: emotional, social, family, and spiritual. Approximately 60 pilot questions were added to the GAT to assess lifestyle behaviors in the physical dimension. After completion of the GAT, respondents were informed that the physical dimension questions were for validation purposes and would not be scored. Respondents were then given the option to consent for use of their GAT responses for research purposes. Per an established data use agreement, personal identifying information was removed from the CSF2 data (thus waiving the requirement for Institutional Review Board approval), which was then provided to researchers for analysis.PopulationThe total number of participants was 14,850. The following were excluded from analyses: 599 DoD civilians, 3 family members, and 100 with missing sleep data. Therefore, the analyses presented herein are for 14,148 Active, Reserve, and National Guard members.MeasuresMeasures included the GAT, which was developed in part by Seligman et al40 and others.41 The details of its evaluation and reliability were previously described.41,42 The GAT’s overall purpose is to assess a Soldier’s emotional, social, spiritual, and family tness with 105 questions. Each dimension yields an overall score based on responses to the questions, and the scores are aggregated into quartiles. For the purposes of this study, the fth dimension (physical tness) was added, and pilot questions were incorporated to represent this new dimension assessment. Questions for the physical tness dimension included items related to nutritional habits and behaviors, physical activity patterns, sleep quality, and other lifestyle behaviors. Participants were asked to report their height and weight, and the body mass index (BMI) (weight [kg]/[height (m)]2) was calculated from their self-reported data. The cutoff was 27.5 kg/m2 as speci ed by Army Regulation 600-9 .43 A healthy waist circumference was de ned as 35 inches or less for females and 40 inches or less for males.44 Sleep quality was subjectively assessed by self-report, and an overall score was calculated from responses to the short version of the Pittsburgh Insomnia Rating Scale, which had previously been validated.45,46 The 2 questions and responses were: 1. In the past week, how much were you bothered by lack of energy because of poor sleep? (not at all bothered, slightly bothered, moderately bothered, severely bothered) 2. Over the past week, how would you rate your satisfaction with your sleep? (excellent, good, fair, poor) Each answer choice was assigned a score of 0 to 3. Hence, the sum total score ranged from 0 to 6; we considered scores of 0 or 1 as good sleep, 2 to 4 as moderate sleep, and 5 or 6 as poor sleep quality. Although the author of the Pittsburgh Insomnia Rating Score indicated that a total score of 2 or more would identify someone with presumed problems, we further divided the group to look at those with self-reported sleep issues. In addition to calculating a sleep-quality score, a Healthy Eating Score (HES-5) was developed based on the US Department of Agriculture’s (USDA) Healthy Eating Index,47-50 but modi ed by using 5 questions assessing daily intake of fruit, vegetable, whole grain, dairy, and sh.51 Other nutrition questions included the number of days per week breakfast is consumed and the inclusion of recovery snacking, whether or not a snack is consumed within 60 minutes of strenuous exercise.

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100 http://www.cs.amedd.army.mil/amedd_journal.aspxPhysical activity information was captured by asking Soldiers the number of times per week they participated in aerobic activity for at least 20 minutes and strength or resistance exercise, based on the American College of Sports Medicine (ACSM) and Centers for Disease Control and Prevention (CDC) exercise recommendations.52 Additionally, participants provided their most recent Army Physical Fitness Test (APFT) score, which included number of push-ups, sit-ups, and run time. Finally, participants were asked to respond to several questions relating to health, perceived body image, and alcohol habits. Speci cally, they were asked to answer the following 3 questions: 1. How do you consider your general health? (excellent, good, fair, poor, donÂ’t know) 2. In thinking about your weight, do you consider yourself to be: underweight, about the right weight, overweight, obese, donÂ’t know? 3. Have you exceeded 5 alcoholic drinks on any single occasion during the past 3 months? (yes or no) Internal consistency for the subsets of questions was measured using Cronbach .53 The values were the following: HES-5=0.810; sleep=0.807; and physical activity=0.793. The GAT dimensions had Cronbach results of 0.724, 0.802 and 0.860 for the social, family, and emotional dimensions respectively, based on the current data. A Cronbach greater than 0.80 is regarded as good, above 0.70 is acceptable, and below 0.60 is unacceptable.53 The pilot questions will be validated through a collaborative study between CSF2 and the Consortium for Health and Military Performance at the Uniformed Services University of the Health Sciences.Statistical AnalysisThe IBM SPSS (V 20.0) for Windows (IBM Corp, Chicago, IL) application was used to perform all statistical analyses. Frequency tables and descriptive statistics were reviewed to remove outliers and con rm assumptions for parametric tests. Binary logistic regression was used to obtain odds ratios (OR) and 95% con dence intervals (CI) to compare the relationships between sleep quality and nutrition, exercise, and lifestyle behaviors. For this purpose, poor sleepers were considered the reference group, and independent variables were either categorical (gender, active duty status, enlistment status, marital status) or categorized into groups (age, dietary behaviors, physical activity, APFT scores, BMI, waist circumference) based on quartiles or other appropriate classi cations and/or dichotomized; as noted above, responses to the 4 psychosocial GAT dimensions were grouped into quartiles. A separate multiple linear-regression model was also used to predict poor sleep, with demographic variables, HES-5, APFT total score, and the 4 dimensions of the GAT. Due to the high number of statistical analyses, the P value was set at the .0025 signi cance level. This was based on dividing the P value of .05 by the 25 logistic regressions conducted. RESULTSGeneral Characteristics and Sleep StatusThe overall characteristics of the sample are presented in Table 1. The distribution of poor, moderate, and good sleepers did not differ as a function of age (OR 1.0; 95% CI, 0.92-1.10; P =.93). However, women were 1.4 times more likely to be poor sleepers than men (OR 1.40; 95% CI, 1.24-1.57; P <.001). Additionally, those on active duty were 1.69 times more likely to be poor sleepers than those in the National Guard or Army Reserve (OR 1.69; 95% CI, 1.55-1.85; P <.001). Moreover, enlisted personnel were 1.74 times more likely to be poor sleepers than of cers (OR 1.74; 95% CI, 1.53-1.99; P <.001).Dietary Patterns and Sleep StatusOn average, poor sleepers were 50% less likely to meet the USDA dietary recommendations for the following: fruit (OR 0.48; 95% CI, 0.43-0.52; P<. 001); vegetables (OR 0.53; 95% CI, 0.47-0.59; P<. 001); whole grains (OR 0.45; 95% CI, 0.43-0.52; P<. 001); dairy (OR 0.48; 95% CI, 0.42-0.54; P<. 001); and sh (OR 0.58; 95% CI, 0.530.63; P<. 001). Each of the dietary recommendations was used to create a HES-5 score. Figure 1 indicates that only 17.4% of the poor sleepers were also healthy eaters as de ned by the HES-5 (a score of 20 out of 25). Overall, poor sleepers were 77.2% less likely to be a healthy eater (OR 0.23; 95% CI, 1.40-1.68; P<. 001) than good sleepers. Table 2 captures additional dietary behaviors showing that poor sleepers were more likely to drink soda and less likely to eat breakfast regularly, or consume a snack within 60 minutes after a strenuous exercise session. Physical Fitness and SleepFrequency of physical activity was assessed and respondents met recommendations if they engaged in at least 20 minutes of aerobic exercise 5 days per week (71.5%), and at least 2 days per week of resistance training (66.8%). Figure 2 illustrates the percentages of each sleep group who met the recommendations and how many passed their APFT in the top quartile. Soldiers were less likely to be poor sleepers if they met aerobic exercise recommendations (OR 0.54; 95% CI, 0.49-0.60; P<. 001), participated in regular resistance training (OR 0.52; 95% CI, 0.47-0.57; P<. 001), or passed their APFT in the top quartile (OR 0.53; 95% CI, 0.45-0.64; P<. 001). SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD: THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION

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October – December 2013 101THE ARMY MEDICAL DEPARTMENT JOURNALHealth Self-Assessments and Sleep Approximately 42% of respondents provided their waist circumference. The mean (SD) waist circumference for women was 30.23.7 inches and 34.43.6 inches for men. Odds ratios to predict healthy anthropomorphic measurements are included in Table 3. Although selfreported, the correlation between waist circumference and BMI was 0.673 ( P<. 001). Answers to the health selfassessments are also presented in Table 3. Remarkably, poor sleepers were 25.7% less likely to have a healthy BMI, 50.0% less likely to have a healthy waist circumference, and 17 times more likely to consider themselves to be in fair or poor health. GAT DimensionsFigure 3 presents sleep quality category by the 4 GAT psychosocial dimensions. As noted, those who were poor sleepers were signi cantly more likely to score in the lowest quartile relative to the other sleep categories. A dose-related response was clearly noted, such that 19% to 35% in the good sleep group, 54% to 59% in the moderate, and 72% to 85% of the poor sleep group scored in the lowest quartiles. Table 4 documents the Table 1 Demographic characteristics of the study sample population (N=14,148).Frequencies Sleep Score MeanSDAge meanSD, years 27 7 8 3 Years range (min-max) 17 61 Age Group17 to 2966 9 % 2 4 1 730 and over 33 1 % 2 5 1 6Gender Female 16 6 % 2 6 1 6 Male 83 4 % 2 4 1 6Army Status Active Duty 52 6 % 2 6 1 7 National Guard/Reserve 47 4 % 2 3 1 6Enlisted StatusEnlisted85 3 % 2 5 1 7Officers 14 7 % 2 1 1 5Marital Status Married 49 0 % 2 5 1 7 Single/divorced/legally separated 50 9 % 2 4 1 6Army Physical Fitness Testn= 10 054 Failed 13 7 % 2 6 1 7 Passed 86 3 % 2 3 1 6BMI Categoriesn= 11 545 Underweight (< 18 4 kg/m2)0 5 % 2 4 1 6Normal/healthy ( 18 5 27 5 kg/m2)65 3 % 2 4 1 6Overweight ( 27 6 29 9 kg/m2) 16 9 % 2 5 1 6 Obese (> 30 kg/m2) 17 3 % 2 7 1 7 BMI MeanSD, kg/m2 26 6 4 03 Range 13 4 56 3 Waist Circumferencen= 6 012 Healthy 90 9 % 2 4 1 6Unhealthy 9 1 % 2 8 1 7Sleep Categories Good sleepers32 9 % 0 6 0 5Moderate sleepers 41 8 % 2 5 0 5 Poor sleepers *25 3 % 4 7 0 78Note: Data are represented as meanSD for continuous variables and as a percentage for categorical variables. Percentages within characteristic groups may not add up to 100 % due to missing data.*Poor sleepers are defined by a total score of 5 or 6 on the Pittsburgh Insomnia Rating Scale2 BMI indicates body mass index. Figure 1. Percentage of healthy eaters in each sleep category. A healthy eater received a score of 20 out of 25 on the Healthy Eating Scale-5. Poor sleepers are de ned by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6; a moderate sleeper scored a 2, 3, or 4; and a good sleeper received a score of 0 or 1. Sleep Category Good Moderate Poor 30% 0% 5% 10% 15% 20% 25% 35% 40%Healthy Eaters Table 2. Logistic Regression of Poor Sleepers and Dietary Behaviors.Good Sleepers( n= 4 658)Moderate Sleepers( n= 5 915)Poor Sleepers *( n= 3 575)OR( P <.001)95 % CIDrinks either diet soda or regular soda (%n) 54 7 % 59 1 % 61 7 % 1 351 24 1 48 Breakfast at least 6 times per week (%n) 52 9 % 40 8 % 31 2 % 0 400 37 0 44 Consumes 2 or more snacks per day (%n) 45 6 % 44 4 % 41 1 % 0 830 76 0 91 Recovery snack (%n) 54 4 % 49 3 % 43 9 % 0 660 6 0 72Note. Data are represented as percentages for the categorical variables.*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6 and used as the reference group; a moderate sleeper scored a 2, 3, or 4; a good sleeper received a score of 0 or 1 OR indicates odds ratio between poor and good sleepers. CI indicates confidence intervals.

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102 http://www.cs.amedd.army.mil/amedd_journal.aspxORs and CIs for the likelihood the poor sleepers would score in the lowest quartile of each dimension compared to the good sleepers. Most notably, when compared to the good sleep quality group, poor sleepers were 23.0 times more likely to score in the lowest quartile of emotional tness. Sleep Prediction ModelA step-wise multiple linear regression model was used to predict poor sleep. The following variables were allowed to be incorporated: age, gender, active duty, enlisted, and married Soldiers, HES-5, APFT total score, and 4 GAT dimensions. Although age and spiritual tness were initially included in the model, no statistically signi cant associations were found. Table 5 shows the nal model and the contribution of each variable entered. Overall, 22.7% of the variance in predicting sleep quality could be explained by this model. Emotional tness contributed the most with 13.8%, and HES-5 accounted for 5.1% of the total explained variance. COMMENT The adverse health consequences of poor sleep quality and inadequate quantity are receiving increasing attention. Both are strongly affected by lifestyle behaviors and daily nutrition and tness habits. In particular, poor sleep quality has been associated with disturbed or dysfunctional neuroendocrine13,30,31 and metabolic12,13,32 pathways, depression, anxiety, obesity, cardiovascular risk, and multiple life stressors.12,13,30-32 Although these health issues are well recognized, few have examined the relationship between sleep quality and the combination of multiple health components in a single sample. This study examined subjective sleep quality in a group of military personnel and indicated signi cant associations between quality of sleep and physical performance, nutritional habits, measures of obesity, lifestyle behaviors, and, importantly, measures of psychosocial status. In particular, poor sleepers by selfreport were signi cantly more likely to score in the lowest quartile for emotional, social, and family tness; have poorer performance on the APFT; and participate less frequently in healthy exercise Table 3. Logistic Regression of Poor Sleepers and Health Self-assessment.Good Sleepers Moderate Sleepers Poor Sleepers OR( P <. 001 ) 95 % CI Healthy BMI ( 18 5 to 27 5 kg/m2) ( n= 3 782 ) ( n= 4 839 ) ( n= 2 924 ) 68 0 % 65 7 % 61 2 % 0 740 67 0 82 Healthy waist circumference†n= 2 022 n= 2 484 n= 1 506 93 2 % 91 3 % 87 2 % 0 500 40 0 63 Consider their health to be “fair” or “poor” n= 4 650 n= 5 896 n= 3 506 4 8 % 18 7 % 46 0 % 17 014 64 19 77 Consider themselves to be “overweight” or “obese” n= 4 337 n= 5 438 n= 3 200 23 8 % 34 1 % 45 1 % 2 602 .38 2 90 Exceeded 5 alcoholic drinks on any single occasion during the past 3 months n= 4 658 n= 5 915 n= 3 575 16 7 % 24 % 29 7 % 2 101 89 2 34Note: Data are represented as percentages of n for the categorical variables.*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6 and used as the reference group; a moderate sleeper scored a 2, 3, or 4; a good sleeper received a score of 0 or 1 .†Healthy waist circumference is defined as 35 inches or less for women and 40 inches or less for men. OR indicates odds ratio between poor and good sleepers. CI indicates confidence intervals. BMI indicates body mass index. Good PoorSoldiers in Study Aerobic Activity Strength Training Passed APFT in Top Quartile Sleep Category 60% 0% 10% 20% 30% 40% 50% 70% 80% Moderate Figure 2. Percentage of Soldiers in each sleep category who met the Centers for Disease Control and Prevention and the American College of Sports Medicine recommendations for aerobic exerci se (at least 20 minutes, 5 days per week) and resistance training (2 days per week), or passed the Army Physical Fitness Test in the top quartile. Poor sleepers are de ned by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6; a moderate sleeper scored a 2, 3, or 4; and a good sleeper received a score of 0 or 1. SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD: THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION

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October – December 2013 103THE ARMY MEDICAL DEPARTMENT JOURNAL and dietary behaviors than good sleepers. Additionally, poor sleepers were signi cantly more likely to have larger waist circumferences and higher BMI than good sleepers. The current data support several consistent associations between poor sleep quality and health in a large sample of military persons. A key nding was the dose-related relationship between sleep quality and emotional, social, and family health. Importantly, emotional health, as measured by the Army GAT, was highly dependent on sleep quality, with poor sleepers being 23 times more likely to have scored in the lowest quartile for emotional health. Ribeiro et al54 evaluated the severity of depressive symptoms, hopelessness, posttraumatic stress disorder diagnoses, anxiety disorders, and drug and alcohol abuse symptoms in a sample of military personnel. Their results suggested that after controlling for all other symptoms, insomnia may possibly predict suicide risk. In other military speci c populations, sleep problems proved to be an important mediator for developing posttraumatic stress disorder or depression.3,6 A strong association between sleep quality and perception of stress has also been demonstrated.8 In addition, Collen et al1 found that hypersomnia, sleep fragmentation, obstructive sleep apnea syndrome, and insomnia were common among persons with mild traumatic brain injury from blast and blunt trauma injuries. Minkel et al29 noted that the psychological threshold for perceiving stress was lowered by poor sleep quality, and Eliasson et al8 reported that perception of stress was inversely related to sleep quality. Of note is the nding of Mauss et al55 that the ability to regulate negative emotions is impaired in persons with poor sleep quality. In addition to perception of stress, sleep quality appears to signi cantly affect cognitive performance.26,56,57 Whether this performance decrement in association with sleep quality is confounded by perceived stress remains to be determined. The strong association between sleep quality and emotional health observed in this study was coupled with comparable associations for both social and family health: self-reported poor sleepers were 14.5 and 6.7 times more likely to have scored in the lowest quartile for social and family health respectively. These ndings are supported by previous work.58,59 In particular, Ailshire et al58 demonstrated that strained family relationships were associated with troubled sleep; whereas, supportive family relationships were related to highquality sleep. Although not directly related to sleep, Table 4. Logistic Regression Predicting Likelihood of Poor Sleepers Scoring in the Bottom Quartile of Global Assessment Tool (GAT) DimensionsGAT Fitness Dimensions Good Sleepers (n=2,575) Moderate Sleepers (n=2,475) Poor Sleepers (n=1,984) OR( P <. 001 ) 95% CI Emotional19.3%54.5%84.6%23.0019.64-26.85 Social24.1%54.4%82.2%14.4712.47-16.79 Family 28.1%52.6%72.4%6.715.83-7.72 Spiritual 35.1%59.5%74.9%5.524.86-6.26Note: Data are represented as percentages of n for the categorical variables.*Poor sleepers are defined by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6 and used as the reference group; a moderate sleeper scored a 2, 3, or 4; a good sleeper received a score of 0 or 1.†Healthy waist circumference is defined as 35 inches or less for women and 40 inches or less for men. OR indicates odds ratio between poor and good sleepers. CI indicates confidence intervals. BMI indicates body mass index. Figure 3. Percentage of each sleep category scoring in the lowest quartile for the Global Assessment Tool psychological dimensions. Poor sleepers are de ned by a total Pittsburgh Insomnia Rating Scale-2 score of 5 or 6; a moderate sleeper scored a 2, 3, or 4; a good sleeper received a score of 0 or 1. Good Sleep Category Poor Emotional Social Family Spiritual 60% 0% 10% 20% 30% 40% 50% 70% 80% 90% ModerateLowest Quartile of Dimensions

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104 http://www.cs.amedd.army.mil/amedd_journal.aspxPollock et al60 found that close and exible family relationships are linked to low individual perceived stress levels. Together these data clearly show the remarkable interplay among sleep quality, stress, relationships, and overall psychosocial functioning. Sleep impacts other daily activities in addition to psychological and social functioning. This study found a strong association between sleep quality and dietary and physical activity habits. In particular, poor sleep quality was related to larger waist circumferences and higher BMIs, greater participation in adverse alcohol-related behaviors, and poorer performance on military-related tasks. Speci cally, poor sleepers were less likely to meet the USDA dietary guidelines and CDC and ACSM exercise guidelines, eat breakfast on a regular basis, engage in positive eating habits, and more likely to drink sugarladen sodas. These ndings are also consistent with the literature.36,38,61-63 For example, Gerber et al found that participants who reported higher tness levels exhibited lower insomnia scores and had a higher perceived sleep quality.52 Golley et al36 reported that both late bedtime and late wakeup times were related to poor diet quality, independent of sleep duration. Cheng et al64 noted a signi cant association between poor sleep quality and skipping breakfast in undergraduate female students, which is indicated in our nding that poor sleepers were more likely to skip breakfast. Although the research to date on breakfast and performance is derived primarily from young, school-age children, it is apparent that consuming breakfast is associated with enhanced attention and cognitive performance relative to not eating breakfast.65-69 Of particular interest are the recent ndings of Deshmukh-Taskar et al70 showing that consumption of breakfast was associated with more favorable cardiometabolic risk pro les in adults 20 to 39 years of age when compared to skipping breakfast. Likewise, Narang et al71 have indicated that adolescents who scored the highest on measures of sleep disturbances were signi cantly more likely to have cardiovascular risk factors and hypertension than those who scored the lowest. Studies have also shown a relationship between sleep and successful weight loss. For example, Chaput et al72 found that more fat mass was lost over the course of a weightreduction program by those who reported good sleep quality prior to starting the program. Consistent with that work, Thomson et al73 found that participants who reported better subjective sleep quality were more likely to be successful with weight loss. This is not unexpected as Kim et al62 examined dietary patterns in association with sleep duration and concluded that both habitual short sleepers and very long sleepers typically did not eat during conventional eating hours—they had disrupted eating patterns with snacks being dominant over meals. Of note, both unconventional eating hours and snack dominance were re ective of a low quality diet, that is, lower intakes of fruits and vegetables and higher intakes of sweets and fat as a percentage of energy.62 Together these reports demonstrate the close interrelationship between sleep and dietary habits and the in uence on overall health. The limitations of this study must be acknowledged. First, only 2 sleep questions were used, unlike the Pittsburgh Sleep Quality Index which has 20 questions.12,74,75 However, the 2 questions were global and re ective of perceived sleep quality. Moreover, the percent of persons self-reporting poor sleep was what had been anticipated. Thus, the results are most likely accurate given the large sample size. Secondly, the relationships between sleep and scores on emotional and social health do not allow any determination of the key components of either speci c dimension. However, the strength of the relationships demonstrates a clear interaction between sleep quality and emotional and social health. Further research will be necessary to re ne the relative contribution of the factors discussed herein. Finally, the information on dietary patterns is not as granular as might be desired, but again the trends were quite strong, so these data will allow for further examination of speci c patterns in the future. RELEVANCE TO PERFORMANCE TRIAD In summary, this study is one of the rst to examine self-reported sleep quality within the context of overall lifestyle patterns and self-reported psychosocial health in a military population. Poor sleepers were more likely to be poor eaters, engage in less healthy dietary and Table 5. Stepwise Multiple Regression Analysis-Predicting Poor Sleep.Final Variables in Model R RR Change Standardized Coef cient P Value 1Active Duty 0.1070.0110.0110.063.00 2Enlisted Status 0.1270.0160.0050.020.03 3Gender 0.1320.0170.0010.040.00 4Married 0.1360.0180.0010.029.01 5HES-5 0.2620.0680.051-0.104.00 6APFT Total Score 0.2730.0740.006-0.086.00 7Emotional Fitness 0.4610.2120.138-0.277.00 8Social Fitness 0.4730.2230.011-0.121.00 9Family Fitness 0.4770.2260.004-0.073.00Note: A stepwise multiple linear regression model was used to predict poor sleep using the following variables: Age Active duty Married APFT total score Gender Enlisted HES-5 4 GAT dimensions SLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD: THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION

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October – December 2013 105THE ARMY MEDICAL DEPARTMENT JOURNAL lifestyle behaviors, and score in the lowest quartiles with respect to emotional and social health. It further validates the central and essential relationships among physical activity, nutrition, and sleep—they fully support the concept of the Performance Triad. The results underscore the need to provide education on the health consequences of poor sleep habits and supportive resources for ensuring suf cient high quality sleep. However, this should be done in an integrative fashion so as to include information on nutrition and physical tness, as they are intertwined and must be considered as a whole. ACKNOWLEDGEMENTSThis research was supported by a grant from Comprehensive Soldier and Family Fitness (CSF2; HT9404-121-0017; F191GJ). We appreciate the support in preparation and review of this article by LTC Daniel T. Johnston and LTC Sharon A. McBride. We also gratefully acknowledge Josh Kazman for statistical support and Preetha Abraham for graphic assistance.REFERENCES1. Collen J, Orr N, Lettieri CJ, Carter K, Holley AB. Sleep disturbances among soldiers with combat-related traumatic brain injury. Chest 2012;142(3):622-630. 2. Crowley SK, Wilkinson LL, Burroughs EL, et al. Sleep during basic combat training: a qualitative study. Mil Med 2012;177(7):823-828. 3. Macera CA, Aralis HJ, Rauh MJ, Macgregor AJ. Do sleep problems mediate the relationship between traumatic brain injury and development of mental health symptoms after deployment?. Sleep 2013;36(1):83-90. 4. Mackowiak PA, Billings FT III, Wasserman SS. Sleepless vigilance: “Stonewall” Jackson and the duty hours controversy. Am J Med Sci 2012;343(2):146-149. 5. Energy drink consumption and its association with sleep problems among US service members on a combat deployment–Afghanistan, 2010. MMWR Morb Mortal Wkly Rep 2012;61(44):895-898. 6. Luxton DD, Greenburg D, Ryan J, Niven A, Wheeler G, Mysliwiec V. Prevalence and impact of short sleep duration in redeployed OIF soldiers. Sleep 2011;34(9):1189-1195. 7. Capaldi VF II, Guerrero ML, Killgore WD. Sleep disruptions among returning combat veterans from Iraq and Afghanistan. Mil Med 2011;176(8):879-888. 8. Eliasson A, Kashani M, Dela Cruz G, Vernalis M. Readiness and associated health behaviors and symptoms in recently deployed Army National Guard soldiers. Mil Med 2012;177(11):1254-1260. 9. Seelig AD, Jacobson IG, Smith B, et al. Sleep patterns before, during, and after deployment to Iraq and Afghanistan. Sleep 2010;33(12):1615-1622. 10. Peterson AL, Goodie JL, Satter eld WA, Brim WL. Sleep disturbance during military deployment. Mil Med 2008;173(3):230-235. 11. Schaefer EW, Williams MV, Zee PC. Sleep and circadian misalignment for the hospitalist: a review. J Hosp Med 2012;7(6):489-496. 12. Kazman JB, Abraham PA, Zeno SA, Poth M, Deuster PA. Self-reported sleep impairment and the metabolic syndrome among African Americans. Ethn Dis 2012;22(4):410-415. 13. Lucassen EA, Rother KI, Cizza G. Interacting epidemics? Sleep curtailment, insulin resistance, and obesity. Ann N Y Acad Sci 2012;1264(1):110-134. 14. Applewhite L, Keller N, Borah A. Mental health care use by soldiers conducting counterinsurgency operations. Mil Med 2012;177(5):501-506. 15. Pompili M, Rihmer Z, Gonda X, Sera ni G, Sher L, Girardi P. Early onset of action and sleep-improving effect are crucial in decreasing suicide risk: the role of quetiapine XR in the treatment of unipolar and bipolar depression. Riv Psichiatr 2012;47(6):489-497. 16. Spelman JF, Hunt SC, Seal KH, Burgo-Black AL. Post deployment care for returning combat veterans. J Gen Intern Med 2012;27(9):1200-1209. 17. Vijayalakshmy P, Hebert C, Green S, Ingram CL. Integrated multidisciplinary treatment teams; a mental health model for outpatient settings in the military. Mil Med 2011;176(9):986-990. 18. Cho HJ, Lavretsky H, Olmstead R, Levin MJ, Oxman MN, Irwin MR. Sleep disturbance and depression recurrence in community-dwelling older adults: a prospective study. A J Psychiatry 2008;165(12):1543-1550. 19. Halbauer JD, Ashford JW, Zeitzer JM, Adamson MM, Lew HL, Yesavage JA. Neuropsychiatric diagnosis and management of chronic sequelae of war-related mild to moderate traumatic brain injury. J Rehabil Res Dev 2009;46(6):757-796. 20. O’Connor MF, Irwin MR. Links between behavioral factors and in ammation. Clin Pharmacol Ther 2010;87(4):479-482. 21. Irwin MR. In ammation at the intersection of behavior and somatic symptoms. Psychiatr Clin North Am 2011;34(3):605-620. 22. Irwin MR, Carrillo C, Olmstead R. Sleep loss activates cellular markers of in ammation: sex differences. Brain Behav Immun 2010;24(1):54-57. 23. Irwin MR, Wang M, Ribeiro D, et al. Sleep loss activates cellular in ammatory signaling. Biol Psychiatry 2008;64(6):538-540.

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106 http://www.cs.amedd.army.mil/amedd_journal.aspxSLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD: THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION24. Motivala SJ, Sarfatti A, Olmos L, Irwin MR. In ammatory markers and sleep disturbance in major depression. Psychosom Med 2005;67(2):187-194. 25. Nicassio PM, Ormseth SR, Kay M, et al. The contribution of pain and depression to self-reported sleep disturbance in patients with rheumatoid arthritis. Pain 2012;153(1):107-112. 26. Alhola P, Polo-Kantola P. Sleep deprivation: Impact on cognitive performance. Neuropsychiatr Dis Treat 2007;3(5):553-567. 27. Czeisler CA. Impact of sleepiness and sleep de ciency on public health–utility of biomarkers. J Clin Sleep Med 2011;7(suppl 5):S6-S8. 28. Liberalesso PB, D’Andrea KF, Cordeiro ML, Zeigelboim BS, Marques JM, Jurkiewicz AL. Effects of sleep deprivation on central auditory processing. BMC Neurosci 2012;13:83. 29. Minkel JD, Banks S, Htaik O, et al. Sleep deprivation and stressors: evidence for elevated negative affect in response to mild stressors when sleep deprived. Emotion 2012;12(5):1015-1020. 30. Mong JA, Baker FC, Mahoney MM, et al. Sleep, rhythms, and the endocrine brain: in uence of sex and gonadal hormones. J Neurosci 2011;31(45):16107-16116. 31. Weeks SR, McAuliffe CL, Durussel D, Pasquina PF. Physiological and psychological fatigue in extreme conditions: the military example. PM R 2010;2(5):438-441. 32. Hung HC, Yang YC, Ou HY, Wu JS, Lu FH, Chang CJ. The association between self-reported sleep quality and metabolic syndrome. PLoS One 2013;8(1):e54304. 33. Uchida S, Shioda K, Morita Y, Kubota C, Ganeko M, Takeda N. Exercise effects on sleep physiology. Front Neurol 2012;3:48. 34. Yamanaka Y, Hashimoto S, Tanahashi Y, Nishide SY, Honma S, Honma K. Physical exercise accelerates reentrainment of human sleep-wake cycle but not of plasma melatonin rhythm to 8-h phase-advanced sleep schedule. Am J Physiol Regul Integr Comp Physiol 2010;298(3):R681-R691. 35. Grandner MA, Jackson NJ, Gerstner JR, Knutson KL. Dietary nutrients associated with short and long sleep duration: data from a nationally representative sample. Appetite 2013;64:71-80. 36. Golley RK, Maher CA, Matricciani L, Olds TS. Sleep duration or bedtime? Exploring the association between sleep timing behaviour, diet and BMI in children and adolescents. Int J Obes (Lond) 2013;37(4):546-551. 37. St-Onge MP. The role of sleep duration in the regulation of energy balance: effects on energy intakes and expenditure. J Clin Sleep Med 2013;9(1):73-80. 38. St-Onge MP, Roberts AL, Chen J, et al. Short sleep duration increases energy intakes but does not change energy expenditure in normal-weight individuals. Am J Clin Nutr 2011;94(2):410-416. 39. Gebhart C, Erlacher D, Schredl M. Moderate exercise plus sleep education improves self-reported sleep quality, daytime mood, and vitality in adults with chronic sleep complaints: a waiting list-controlled trial. Sleep Disord 2011:809312 [epub Nov 24 2011]. 40. Seligman ME. Building resilience. Harv Bus Rev 2011;89(4):100-106, 138. 41. Peterson C, Park N, Castro CA. Assessment for the US Army comprehensive soldier tness program: the global assessment tool. Am Psychol 2011;66(1):10-18. 42. Firth KM, Smith K. A survey of multidimensional health and tness indexes. Mil Med 2010;175(suppl 1):110-117. 43. Army Regulation 600-9: The Army Weight Control Program Washington, DC: US Dept of the Army; November 2006: Available at: http://www.apd. army.mil/pdf les/r600_9_x.pdf. Accessed February 23, 2013. 44. Lemieux S, Prud’homme D, Bouchard C, Tremblay A, Despres JP. A single threshold value of waist girth identi es normal-weight and overweight subjects with excess visceral adipose tissue. Am J Clin Nutr Nov 1996;64(5):685-693. 45. Moul DE, Mai E, Shablesky M, et al. The 2-item and 20-item versions of the Pittsburgh Insomnia Rating Scale (PIRS): design methods and initial modeling. Paper presented at: Annual Meeting of the World Psychiatric Association; November 29, 2009; Melbourne, Australia. 46. Moul DE, Pilkonis P, Miewald J, Carey T, Buysse D. Preliminary study of the test-retest reliability and concurrent validities of the Pittsburgh Insomnia Rating Scale (PIRS). Sleep 2002;25:A246-A247. 47. Guenther PM, Reedy J, Krebs-Smith S, Reeve B, Basiotis PP. Development and Evaluation of the Healthy Eating Index-2005: Technical Report Alexandria, VA: Center for Nutrition Policy and Promotion, US Department of Agriculture; 2007. Available at: http://www.cnpp.usda.gov/publica tions/hei/hei-2005/hei-2005technicalreport.pdf. Accessed August 1, 2013. 48. Guenther PM, Reedy J, Krebs-Smith SM. Development of the Healthy Eating Index-2005. J Am Diet Assoc 2008;108(11):1896-1901. 49. Guenther PM, Reedy J, Krebs-Smith SM, Reeve BB. Evaluation of the Healthy Eating Index-2005. J Am Diet Assoc 2008;108(11):1854-1864.

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October – December 2013 107THE ARMY MEDICAL DEPARTMENT JOURNAL50. Weinstein SJ, Vogt TM, Gerrior SA. Healthy Eating Index scores are associated with blood nutrient concentrations in the third National Health And Nutrition Examination Survey. J Am Diet Assoc 2004;104(4):576-584. 51. Purvis D, Lentino CV, Jackson TK, Murphy KJ, Deuster PA. Nutrition as a component of the Performance Triad: How healthy eating behaviors contribute to Soldier performance and military readiness. US Army Med Dep J October-December 2013:66-78. 52. Garber CE, Blissmer B, Deschenes MR, et al. American College of Sports Medicine position stand. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor tness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc 2011;43(7):1334-1359. 53. DeVellis RF. Scale development: theory and applications. In: Bickman L, Rog DJ, eds. Applied Social Research Methods Series. Vol 26. Washington, DC: Sage; 2012. 54. Ribeiro JD, Pease JL, Gutierrez PM, et al. Sleep problems outperform depression and hopelessness as cross-sectional and longitudinal predictors of suicidal ideation and behavior in young adults in the military. J Affect Disord 2012;136(3):743-750. 55. Mauss IB, Troy AS, Lebourgeois MK. Poorer sleep quality is associated with lower emotion-regulation ability in a laboratory paradigm. Cogn Emot 2012;27(3):567-576. 56. Gerber M, Brand S, Holsboer-Trachsler E, Puhse U. Fitness and exercise as correlates of sleep complaints: is it all in our minds? Med Sci Sports Exerc 2010;42(5):893-901. 57. Chang-Quan H, Bi-Rong D, Yan Z. Association between sleep quality and cognitive impairment among Chinese nonagenarians/centenarians. J Clin Neurophysiol 2012;29(3):250-255. 58. Ailshire JA, Burgard SA. Family relationships and troubled sleep among US adults: examining the in uences of contact frequency and relationship quality. J Health Soc Behav 2012;53(2):248-262. 59. Kim H, Rose K. Sleep disturbances in family caregivers: an overview of the state of the science. Arch Psychiatr Nurs 2011;25(6):456-468. 60. Pollock E, Kazman J, Deuster P. Family functioning and stress in African American families: a strength based approach. J Black Psychol. In press. 61. Haghighatdoost F, Karimi G, Esmaillzadeh A, Azadbakht L. Sleep deprivation is associated with lower diet quality indices and higher rate of general and central obesity among young female students in Iran. Nutrition 2012;28(11-12):1146-1150. 62. Kim S, DeRoo LA, Sandler DP. Eating patterns and nutritional characteristics associated with sleep duration. Public Health Nutr 2011;14(5):889-895. 63. Hitze B, Bosy-Westphal A, Bielfeldt F, et al. Determinants and impact of sleep duration in children and adolescents: data of the Kiel Obesity Prevention Study. Eur J Clin Nutr 2009;63(6):739-746. 64. Cheng SH, Shih CC, Lee IH, et al. A study on the sleep quality of incoming university students. Psychiatry Res 2012;197(3):270-274. 65. Maffeis C, Fornari E, Surano MG, et al. Breakfast skipping in prepubertal obese children: hormonal, metabolic and cognitive consequences. Eur J Clin Nutr 2012;66(3):314-321. 66. Wesnes KA, Pincock C, Scholey A. Breakfast is associated with enhanced cognitive function in schoolchildren. An internet based study. Appetite 2012;59(3):646-649. 67. Pivik RT, Tennal KB, Chapman SD, Gu Y. Eating breakfast enhances the ef ciency of neural networks engaged during mental arithmetic in schoolaged children. Physiol Behav 2012;106(4):548-555. 68. Kral TV, Heo M, Whiteford LM, Faith MS. Effects on cognitive performance of eating compared with omitting breakfast in elementary schoolchildren. J Dev Behav Pediatr 2012;33(1):9-16. 69. Liu J, Hwang WT, Dickerman B, Compher C. Regular breakfast consumption is associated with increased IQ in kindergarten children. Early Hum Dev 2013;89(4):257-262. 70. Deshmukh-Taskar P, Nicklas TA, Radcliffe JD, O’Neil CE, Liu Y. The relationship of breakfast skipping and type of breakfast consumed with overweight/obesity, abdominal obesity, other cardiometabolic risk factors and the metabolic syndrome in young adults. The National Health and Nutrition Examination Survey (NHANES): 19992006. Public Health Nutr October 2, 2012 [epub]. 71. Narang I, Manlhiot C, Davies-Shaw J, et al. Sleep disturbance and cardiovascular risk in adolescents. CMAJ 2012;184(17):E913-E920. 72. Chaput JP, Tremblay A. Sleeping habits predict the magnitude of fat loss in adults exposed to moderate caloric restriction. Obes Facts 2012;5(4):561-566. 73. Thomson CA, Morrow KL, Flatt SW, et al. Relationship between sleep quality and quantity and weight loss in women participating in a weightloss intervention trial. Obesity (Silver Spring) 2012;20(7):1419-1425. 74. Buysse DJ, Reynolds CF III, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res 1989;28(2):193-213.

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108 http://www.cs.amedd.army.mil/amedd_journal.aspxSLEEP AS A COMPONENT OF THE PERFORMANCE TRIAD: THE IMPORTANCE OF SLEEP IN A MILITARY POPULATION 75. Carpenter JS, Andrykowski MA. Psychometric evaluation of the Pittsburgh Sleep Quality Index. J Psychosom Res 1998;45(1):5-13.AUTHORSMs Lentino is a Research Associate, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr Purvis is Director, Strategic Operations and Special Projects, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Ms Murphy is a Research Associate, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland. Dr Deuster is Professor and Director, Consortium for Health and Military Performance, Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland.

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October – December 2013 109SLEEP IS A PHYSIOLOGICAL REQUIREMENT Like the need for food, water, and air, the need for sleep is physiologically based. However, sleep differs from other basic physiological needs in several key respects. The most salient of these is the fact that sleep is not actually necessary to sustain human life. Although there are limits to the duration of time that life can be sustained in the absence of food, water, or air, there is no known limit to the number of hours/days/weeks that humans can go without sleep. In a series of studies conducted at the University of Chicago in the early 1980s, Retschaffen and colleagues1 reported that rats that were totally deprived of sleep died within 2-3 weeks. At the time those studies were published, the mechanism by which total sleep loss effected death in the rats was not clear. It was subsequently shown that preceding death, sleep-deprived rats display transmigration of bacteria from the gut that results in widespread extraintestinal infection/septic load.2 Similar effects of sleep loss have not been observed in any other species, including humans (and notably, neither humans nor rats can volitionally go without sleep for more than a few days, meaning that nonvolitional behavioral methods or pharmacological methods must then be used to maintain wakefulness). Accordingly, there are no known instances in which a human death has been directly attributed to sleep deprivation. Of course, there are numerous instances in which insuf cient sleep has indirectly resulted in death: for example, the Automobile Association of America estimates that between 1999 and 2008 sleepiness was a contributing factor in 16.5% of traf c fatalities (approximately 69,300 deaths) in the United States.3 And it is clear that insuf cient sleep exacts an enormous economic toll as well, with yearly costs resulting from home and industrial accidents, errors, and inef ciencies estimated to cost the US economy hundreds of billions of dollars per year.4 But there is no evidence that sleep subserves any physiological function that is directly necessary for sustaining life. Patients with a rare prion disease called fatal familial insomnia experience total insomnia for several months before eventually succumbing; however, it is likely that these deaths are the result of other aspects of the disorder (for example, the large thalamic lesions that also characterize the disorder).5 Also, patients can be kept alive in a coma for decades, and coma is not sleep. In fact, some patients with a diagnosis of vegetative state/unresponsive wakefulness syndrome show no discernible evidence of sleep.6This is not to say that sleep plays no role in the maintenance of health. Over the past 2 decades, evidence that chronic sleep disturbance is associated with mood disorder,7 impaired immune function,8 age-related cognitive decline,9 metabolic syndrome/obesity/diabetes,10 heart The Challenge of Sleep Management in Military OperationsNancy J. Wesensten, PhD Thomas J. Balkin, PhDABSTRACT It has long been known that short-term (days) insuf cient sleep causes decrements in mental effectiveness that put individuals at increased risk of committing errors and causing accidents. More recently, it has been discovered that chronic poor sleep (over years) is associated with a variety of negative health outcomes (metabolic syndrome, obesity, degraded behavioral health). Implementing an effective sleep health program is, therefore, in the best interests of active duty personnel and their families both in the shortand long-term. Like managing physical activity or nutrition, effectively managing sleep health comes with its unique set of challenges arising from the fact that individuals who routinely do not obtain suf cient sleep are generally desensitized to feeling sleepy and are poor at judging their own performance capabilities—and individuals cannot be compelled to sleep. For these reasons, an optimally effective sleep health program requires 3 components: (1) a rigorous, evidence-based sleep education component to impart actionable knowledge about optimal sleep amounts, healthy sleep behaviors, the known bene ts of sleep, the shortand long-term consequences of insuf cient sleep, and to dispel myths about sleep; (2) a nonintrusive device that objectively and accurately measures sleep to empower the individual to track his/her own sleep/wake habits; and (3) a meaningful, actionable metric re ecting sleep/ wake impact on daily effectiveness so that the individual sees the consequences of his/her sleep behavior and, therefore, can make informed sleep health choices.

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110 http://www.cs.amedd.army.mil/amedd_journal.aspxTHE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS disease,11 and even cancer12 has steadily accrued. The exact mechanism(s) by which sleep exerts its in uence on these disorders is not known. Also unknown is whether sleep disturbance exerts a direct causal or indirect in uence. Compared to food, air, or water—resources obtained from the environment that when removed lead to death in a relatively quick and straightforward manner— sleep (a wholly internal phenomenon that depends on the presence of no particular environmental resources) is less critical for actual survival. For example, sleep is not critical for vegetative processes needed to maintain viability of individual brain cells. Nevertheless, sleep does play a crucial role in day-today functioning: it promotes and sustains waking brain (speci cally, neocortical) processes that constitute and/ or facilitate mass action-potential-dependent functions ranging from basic consciousness/alertness to higherorder mental abilities including situation awareness, problem-solving, memory, and creativity.13-15 The importance of sleep to higher-order mental abilities is illustrated in Figure 1, which depicts the effects of 24 hours of total sleep deprivation on regional brain metabolic activity. Among the cortical regions most metabolically degraded by sleep loss is the prefrontal cortex (blue areas located in the frontal portion of the brain), the brain region responsible for mediating the highest-order cognitive functions.17 A translation of such higher-order mental abilities into operationally relevant capabilities is presented in the Table. In short, sleep is a process that not only occurs in the brain, it is also a process that undoubtedly confers unique bene ts to the brain itself. PUBLIC AWARENESS OF THE IMPORTANCE OF SLEEP Partly as a result of concerted efforts by organizations such as the National Institutes of Health,19,20 the Centers for Disease Control and Prevention,21 and the National Sleep Foundation,22 and partly as a result of the discovery that sleep disorders (most notably obstructive sleep apnea) are prevalent in United States, awareness of the importance of sleep has rapidly expanded within the general population over the past several decades. In fact, the term sleep apnea, rst coined in the scienti c medical literature in 1976,23 is now a widely used and understood part of the American lexicon. Also, the possible role of insuf cient sleep in highly publicized incidents including the nuclear reactor near-meltdown at Three Mile Island on March 28, 1979 (for which the causal human error occurred in the early morning hours24), the explosion of the space shuttle Challenger on January 28, 1986 (for which the serious aw in decision-making also occurred during early morning hours, prior to launch25), the nuclear reactor meltdown at Chernobyl on April 26, 1986 (for which standard opinion is that operator error was the root cause of the disaster26), and more recently the 2009 Colgan Air Flight 3407 crash near Buffalo, NY (for which the sequence of errors that ultimately led to the crash are consistent with de cits in higher-order cognitive abilities degraded by insuf cient sleep, perhaps most notably a degraded ability to rapidly recognize a failed course of action and adjust accordingly27) have heightened awareness of the importance of adequate sleep, particularly for those engaged in occupations for which lapses in attention or judgment can have disastrous consequences. HOW MUCH SLEEP? Sleep experts are often asked by leaders, “What is the minimum amount of sleep that my Soldiers need to remain effective?” This question re ects the tacit calculation that Soldier productivity during all hours spent asleep is zero, and productivity for all hours spent awake is greater than zero. Viewed this way, it makes sense to maximize the number of hours that troops spend awake and minimize the number of hours that they spend asleep each day. However, the problem with this calculation becomes clear if one substitutes “mental agility” or “situational awareness” for sleep. The question then becomes “what is the minimum amount of mental agility/situational awareness that my Soldiers need to remain effective?” From both a physiological and practical standpoint, the answer is “more is always better.” There are 2 reasons for this. First, as discussed Figure 1. Characterization of brain metabolic activity after 24 hours of total sleep deprivation. Darkest shades of blue indicate areas of greatest metabolic deactivation compared to baseline (normal alertness). Adapted from Thomas et al.16

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October – December 2013 111THE ARMY MEDICAL DEPARTMENT JOURNAL previously, sleep promotes waking mental acuity: the more sleep that is obtained, the better the individual is able to maintain situational awareness, anticipate and solve problems, generate creative and appropriate solutions, etc. In battle eld situations, even the smallest “edge” in reaction time, situation awareness, and problem solving could be critical to mission success. Second, more sleep is always better because it ensures not only that sleep debt is not incurred acutely, but it also helps ensure that more long-term, subtle sleep debt, which becomes apparent under conditions of chronic insuf cient sleep, does not accrue. It is this latter situation which is less appreciated but far more insidious and potentially problematic. Stated another way, the more sleep a Soldier obtains on a regular basis, the more resilient that Soldier becomes to the effects of subsequent sleep loss. In effect, the Soldier establishes a “sleep reserve”28 that can be tapped days (and perhaps even weeks) later to better sustain alertness and performance when subsequently faced with the challenge of sleep loss resulting from high tempo of operations (OPTEMPO), continuous operations, etc. For example, Rupp et al29 showed that volunteers who were allowed 10 hours time in bed per night (TIB) for 7 nights performed better during a subsequent sleep restriction challenge of 3 hours TIB than volunteers who were allowed 7 hours TIB for 7 nights prior to the same 3-hour TIB challenge. The data is presented in Figure 2. Critically, the difference between the groups grew as the sleep restriction challenge continued across days, and recovery was faster in the 10-hour prior TIB group (that is, less recovery sleep was needed to restore alertness and performance to baseline levels). These ndings reveal the long time constant associated with sleep’s bene cial effects. It may be that these enduring, slowly accumulating bene cial (or, in the case of insuf cient sleep, deleterious) effects underlie the relationship between sleep and general health, relationships that Operationally Relevant Capability Impacted by Sleep.MOST IMPACTEDALSO IMPACTEDLESS IMPACTED Acquiring, assigning priorities, allocating, and using resources Anticipating and solving problems Managing and exploiting change Acting decisively under pressure Establishing position Requesting fire Coordinating squad tactics Monitoring environment (vigilance) Attending to preventive maintenance Loading magazines Lifting Digging, etc. Adapted from Chapter 4, Field Manual 6-22.5 .18 Study Day 7 nights of 1 0 hrs prior TIB 7 nights of 7 hrs prior TIB 3 Hrs TIB 3 Hrs TIB 3 Hrs TIB 3 Hrs TIB 3 Hrs TIB 3 Hrs TIB 3 Hrs TIB 7 or 10 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 0 8 6 4 2 10 Mean Estimated LapsesFigure 2. Objective performance during a sleep restriction challenge of 3 hours time in bed (TIB) for 7 nights. For the 7 nights immediately preceding the 3-hour TIB challenge, one group was allowed 10-hours TIB per night and the other was allowed approximately 7-hours TIB per night. Although performance in both groups deteriorated across the 3-hour TIB challenge, the rate of performance deterioration was slower, and recovery was faster, in the 10-hour TIB group. Adapted from Rupp et al.29

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112 http://www.cs.amedd.army.mil/amedd_journal.aspxTHE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS may only become apparent over years. Little is known about the in uence of prior sleep history. In controlled laboratory studies published to date, prior sleep history has been recorded only for approximately a week. Also, our study was the only one in which prior sleep history was manipulated. The in uence of sleep history may be greater than the magnitude shown in results from crosssectional studies,30 that is, the extent to which sleep can be banked may be greater than that shown in our relatively short-term (7 days of banking) study. Ideally, future longitudinal studies will be conducted in which volunteers’ daily sleep amounts are tracked over weeks, months, and/or years, and compared against sensitive and relevant metrics of neurobehavioral performance, physical health, behavioral health, etc. Although more sleep is always better in terms of alertness and performance, it is not invariably the case that sleep opportunity should always be maximized during military operations. Because recuperative bene ts do not accrue linearly during sleep,32 within every operational situation there is a point at which extra sleep provides diminishing returns: an in ection point at which the amount of recuperation (mental acuity/resilience) that is gained by extending sleep duration is outweighed by the short-term bene ts (in terms of work/productivity) that can be realized by having the Soldier remain awake performing his or her duties. Thus, just as carrying too much fuel, food, and ammunition for a particular mission can exact costs in terms of ef ciency or effectiveness, it is possible that too much time allocated for sleep could cut into military effectiveness by inef ciently cutting into the number of hours of productive wakefulness. In reality, the likelihood of a scenario in which too much time is allotted for sleep during a military operation is low. With the generally high OPTEMPO of military operations, the problem has been (and will likely remain) ensuring that nominally adequate time is allotted for sleep. In practice, this not only means allotting adequate time for sleep itself, but additionally allotting adequate time for other activities (calling home, for example) for which military personnel will invariably sacri ce sleep, if forced to choose between the two. Therefore, the primary target of opportunity, the lynchpin of success for a sleep/alertness management program, will be a change in behavior in which each person conscientiously and voluntarily optimizes sleep during whatever time(s) he has available. In order to achieve this, it will rst be necessary to get “buy-in” (through reeducation) to the simple truth that in the operational environment, Soldiers not only put themselves at risk, but also potentially endanger their fellow Soldiers by foregoing sleep for nonessential waking activities. It will also be necessary to educate the larger Army family regarding the relationship between optimal sleep and everyday functioning, including but not limited to better on-the-job performance, better motivation to maintain a tness program, better school performance, and improved mood. WHAT DRIVES OUR SLEEP BEHAVIOR? This change in behavior and attitude is neither simple nor straightforward because when left to our own devices, we as individuals and as a society rarely opt to maximize sleep duration, and thus optimize next-day alertness and performance. Instead, we seem to choose sleep durations that strike an implicitly self-selected balance between engagement in competing waking activities (both work-related activities and recreational pastimes such as watching television, playing video games, etc) and the physiological need/desire to sleep, resulting in an objectively less-than-optimal (but subjectively tolerable and sustainable) level of chronic, mild sleep restriction. There is a good explanation for why we do not obtain more sleep: over days/weeks (and also months and years) of insuf cient sleep, individuals become inured to the feeling of sleepiness, the primary mechanism by which the brain communicates the need for sleep. When asked how they feel, individuals with untreated obstructive sleep apnea will often reply that they feel normally alert, even though they cannot maintain wakefulness under nonstimulating situations such as sitting in meetings, watching television, and sometimes even while driving a vehicle under monotonous conditions. By all objective criteria, these individuals are pathologically sleepy (unable to maintain wakefulness for more than a few minutes when subjected to a nonstimulating environment), yet they do not consider themselves to be excessively sleepy. It is as though over months or years of insuf cient sleep, their set-point or threshold for subjective sleepiness has substantially increased. Similarly, in one study, Belenky et al33 showed that this habituation to subjective sleepiness occurs within a few days of switching from an 8-hour TIB schedule to a 3-hour TIB schedule. Notably, subjective sleepiness did not track objective performance, which continued to degrade across sleep restriction (Figure 3). The abrupt transition from 8 hours TIB to 3 hours TIB may not mimic realworld conditions in which individuals may volitionally increase total recuperative sleep time (TrST) over time, but a similar lack of correspondence between performance and subjective alertness was evident in both the 5-hour and 7-hour TIB groups in which the TIB decrement was not so drastic.

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October – December 2013 113THE ARMY MEDICAL DEPARTMENT JOURNALFigure 3. Objective performance (panel A—mean reciprocal reaction time on a simple one-choice reaction time task) and subjective alertness (panel B—responses on the Stanford Sleepiness Scale) across days on different nightly sleep schedules. Adapted from Belenky et al.33TIB indicates time in bed per night. RT indicates reaction time. Study Day 9 Hrs TIB 7 Hrs TIB 5 Hrs TIB 3 Hrs TIB 3.75 2.25 2.75 3.25 4.25 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 3, 5, 7, or 9 Hrs TIB Mean Reciprocal Reaction Time( 1/RT 1 000) Panel A Study Day 9 Hrs TIB 7 Hrs TIB 5 Hrs TIB 3 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 8 Hrs TIB 3, 5, 7, or 9 Hrs TIB 1.0 6.0 2.0 3.0 4.0 5.0 7.0 Panel B Mean Sleeping Score(Range 1-7) No longer ghting sleep; sleep onset soon; having dream-like thoughts Feeling active, vital, alert, or wide awake

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114 http://www.cs.amedd.army.mil/amedd_journal.aspxTHE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS Stated another way, we generally fail to appreciate the deleterious effect of insuf cient sleep on our own performance. We suffer few (if any) identi able day-to-day negative consequences of insuf cient sleep. We may nod off during an afternoon brie ng, not appreciating that this is a cardinal sign of insuf cient sleep, but most of us have no objective marker (such as productivity at work) against which the effect of insuf cient sleep can be quanti ed and tracked. Serious consequences of day-to-day, commonly experienced levels of sleepiness, such as fatal automobile crashes, are relatively infrequent even among young adults, for whom traf c accidents are a leading cause of death. News stories on high-pro le, sleepiness-related accidents may fail to resonate because they typically focus on workers in high-risk professions, such as transportation workers. Likewise, news stories and emerging information about the long-term health consequences of inadequate sleep may not resonate with young adults, simply because the potential for such problems seems too remote. Consequently, a campaign to improve sleep health in the military family requires 3 components: (1) an aggressive education component, (2) an accurate, objective personal sleep assessment tool, and (3) the means to translate the objectively-measured sleep data into a relevant effectiveness prediction. EDUCATION COMPONENT Myths, misinterpretations/misrepresentations of fact and old wives’ tales regarding sleep are common. This situation is magni ed by nearly universal access to the internet, where misinformation can be rapidly disbursed among and perpetuated by millions of people. Self-identi ed “experts” who appear on television and radio talk shows and sensationalize research ndings or disseminate misinformation unwittingly compound the problem. Therefore, a campaign to change sleep behavior starts with education to ensure that our active duty military personnel and their families receive accurate (nonsensationalized) and timely information about the currently known bene ts of sleep and consequences of insuf cient sleep. Education is required to dispel beliefs based in myth, misinformation, and/or outdated information. For example, it is widely held, even among some sleep experts, that naps should be curtailed or limited in duration to avoid “sleep inertia” (degraded alertness and performance upon awakening). This myth appears to be rooted in a non–peer-reviewed report in which the authors incorrectly extrapolated the transition through sleep stages that occurs within the con nes of a wellcontrolled laboratory environment to real-world conditions. It also appears to be based on a publication in which the duration of sleep inertia was estimated to be up to 4 hours, an overestimation based on the known improvement in performance, even in totally sleep-deprived individuals, that occurs across the day as a result of the circadian alertness signal.* The desired outcome of an educational effort is that military leaders appreciate the role of sleep in mission success and consequently prioritize sleep in the missionplanning process, and individual Soldiers and their family members likewise understand the importance of sleep and also choose to prioritize it: they voluntarily devote maximum free time to sleep and voluntarily minimize sleep-stealing activities such as video games. ACCURATE, OBJECTIVE SLEEP ASSESSMENT The second component for behavior change is an objective and accurate sleep assessment tool to quantify and track the behavior of interest, in this case, sleep. For the vast majority of individuals (nonclinical settings), the key sleep parameter is TrST per 24 hours. The timing of sleep within the 24-hour period affects TrST in a predictable way: during a daytime sleep period, individuals awaken frequently, although they may not remember these awakenings, which may last only a few seconds to a few minutes. Daytime “sleep fragmentation” or degraded “sleep quality” is caused by the brain’s circadian alertness signal* and/or from light, noise, or other environmental disruptions. Time spent awake, no matter how brief, reduces TrST within a given period allocated for sleep. That is, sleep quality and sleep quantity are actually the same.34 It was previously thought that sleep “continuity” or “fragmentation” was a parameter of sleep that was independent of other sleep metrics such as amount of time spent in the various sleep stages, which sum to total sleep time. However, results of numerous studies aimed at determining the basis of sleep continuity led to the same conclusion: there is no evidence that sleep continuity or sleep fragmentation are measurable factors contributing independently to recuperation during sleep.34Currently, the technology best suited for objectively tracking relevant sleep parameters in the operational environment is wrist actigraphy. This mature and wellvalidated technology35 is based on the observable fact that normal, healthy humans move their wrists more frequently during wakefulness (even when in engaged in sedentary activities like watching television) than during sleep. Wrist movement data are detected by an *The circadian alertness signal is the alertness-enhancing output from the suprachiasmatic nucleus that increases from morning to peak in the late evening, and then decreases across the night to trough near the normal wake time.

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October – December 2013 115THE ARMY MEDICAL DEPARTMENT JOURNAL accelerometer contained within the actigraph and then scored for sleep or wake using a sleep/wake scoring algorithm. Modern wrist actigraphs are “wear-and-forget” wristwatch-like devices that contain suf cient memory to record wrist movement activity continuously for 4-6 weeks at a time. For some actigraphs, the sleep/wakescoring algorithm resides on a microprocessor in the actigraph and sleep/wake is automatically scored. Realtime information regarding amount of time spent sleeping over the last few hours or days can be displayed on the actigraph face. A limitation of actigraphy is that sleep stages cannot be distinguished from one another. In particular, the lightest stage of sleep (N1) which appears to have no recuperative value is indistinguishable from deeper stages of sleep that have been clearly linked to recuperation. In normal sleepers, this limitation is almost inconsequential since normal individuals do not spend appreciable amounts of time in stage N1 (and almost none at all if they carry a sleep debt). However, in certain patient populations who experience numerous awakenings (and consequently more stage N1), their total recuperative sleep may be overestimated, and less sensitive actigraphs will overestimate recuperative sleep to a greater extent than more sensitive devices.36,37 However, for purposes of improving sleep health by increasing time spent asleep (which is the primary issue), actigraphy provides a useful, objective, and cost-effective means of measuring the amount of sleep obtained over days/ weeks/months in a large number of individuals. That is, it provides individuals with a means to gauge the bene ts of implementing behaviors and habits that promote healthy sleep (see “Ten Effective Sleep Habits” on the facing page). ESTIMATED MENTAL EFFECTIVENESS: AN ACTIONABLE METRIC Accurately measuring TrST is important. Translating this TrST into an actionable metric is of far greater practical value (for example, knowing how much gas is in your vehicle’s tank is useful, but not as useful as knowing how far you can drive on that amount of gas). In this respect, the effects of insuf cient sleep are akin to those of blood pressure, dif cult to self-assess and thus appropriately manage without an external, objective, quanti able measure against which the success or failure of management efforts can be gauged. In terms of “sleep miles per gallon,” mental effectiveness is a key actionable metric because, as discussed above, the main function of sleep is to support mental effectiveness, which in turn underlies success in military operations and in daily living. At the group (squad, platoon, etc) level, such information is valuable to planners for immediate and future resource allocation. At the individual Soldier level, effectiveness feedback is valuable for providing the individual with an objective estimate of the extent to which his or her sleep/wake schedule is affecting mental performance, an estimate that may deviate substantially from what the wearer perceives to be his or her current mental effectiveness. Commercial entities (most notably the airline industry) currently use effectiveness prediction models as part of prospective fatigue risk management programs. The most widely used model was developed by the Department of Defense (DoD).38-45 The Federal Aviation Administration recently determined that effectiveness models (and speci cally the DoD model) have undergone suf cient evaluation to be used in aviation fatigue risk management decisions. The US Naval Safety Center uses the DoD effectiveness model to retrospectively analyze the potential role of fatigue (insuf cient sleep and circadian factors) in mishap investigations, and the USAF Air Mobility Command uses model predictions as a component of its aviation operational risk management matrix. For these types of applications, sleep/wake is not measured directly but is estimated based on ight schedule, travel across time zones, etc. Fatigue mitigation strategies also can be modeled. For example, the effectiveness bene t realized by obtaining a 30-minute in ight nap (for operations in which in ight napping is allowed) can be modeled, and the resulting effectiveness used as the basis for informed decision-making. SLEEP, MENTAL EFFECTIVENESS, AND LONG-TERM PERFORMANCE TRIAD GOALS In the short term, the goal of the Performance Triad is to “improve individual performance and resilience through improved sleep, activity, and nutrition discipline.”46 As outlined above, mental effectiveness serves as the objective marker of sleep health. But what is the long-term goal that can be subserved by improved sleep (and thereby improved mental effectiveness)? As Army Surgeon General LTG Patricia Horoho stated, We will continue to encourage members of the Army Family to incorporate health-promoting behaviors and decisions into their everyday lives. The success will be measured by the improvement in health and the reduction of disease and injury among Army team members.47As noted earlier, although the exact mechanism(s) by which sleep promotes long-term health are not yet clear, mounting evidence indicates a link between chronic poor sleep and a myriad of behavioral and physical

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116 http://www.cs.amedd.army.mil/amedd_journal.aspxTHE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS health ailments. Regardless of mechanism, the implication is clear: improving sleep health is a “win-win,” both in the short-term and the long-term. SUMMARY AND CONCLUSIONS One goal of an effective sleep education effort is to ensure that leaders understand the importance of sleep and, as a consequence of this understanding, provide adequate daily sleep opportunities for their personnel during military operations, to the extent possible within the constraints of mission requirements and exigencies. Also, it is critical that Soldiers and their families appreciate the importance of sleep for overall health so that they are motivated to actually use their time wisely to optimize the amount of sleep obtained on a daily basis. With respect to the latter, the use of technologies such as wrist actigraphy and effectiveness prediction models will prove invaluable for tracking and maintaining the desired behaviors, ultimately resulting in a healthier, more effective, and more productive military. Ten Effective Sleep Habits1.Create a quiet, dark, comfortable sleeping environment. Cover windows with darkening drapes or shades (dark trash bags work as well), or wear a sleep mask to block light. Minimize disturbance from environmental noises with foam earplugs or use a room fan to muf e noise. If you can, adjust the room temperature to suit you. If you cannot, use extra blankets to stay warm. Use a room fan both to muf e noise and keep you cool. 2.Use the bedroom only for sleep and intimacy. Remove the TV, computer, laptop, and other electronic distractions from your bedroom. Do not eat or drink in bed. Keep discussions or arguments out of the bedroom. 3.Stop caffeine consumption at least 6 hours before bedtime. Caffeine promotes wakefulness and disrupts sleep. 4.Do not drink alcohol before bed. Alcohol initially makes you feel sleepy, but disrupts and lightens your sleep several hours later. In short, alcohol reduces the recuperative value of sleep. Nicotine, and withdrawal from nicotine in the middle of the night, also disrupts sleep. If you need help quitting drinking or using nicotine products, see your healthcare provider for options. 5.Complete your exercise by early evening. Exercising is great, just be sure to nish at least 3 hours before bedtime so that you have plenty of time to wind down. 6.Do not go to bed hungry. A light bedtime snack (eg, milk and crackers) can be helpful, but do not eat a large meal close to bedtime. And empty your bladder just before you go to bed so that the urge to urinate does not disrupt your sleep. 7.Maintain a consistent, regular routine that starts with a xed wakeup time. Start by setting a xed time to wake up, get out of bed, and get exposure to light each day. Pick a time that you can maintain during the week and on weekends, then adjust your bedtime to target 7-8 hours of sleep. 8.Get out of bed if you cannot sleep. Only go to bed (and stay in bed) when you feel sleepy. Do not try to force yourself to fall asleep; it will tend to make you more awake, making the problem worse. If you wake in the middle of the night, give yourself about 20 minutes to return to sleep. If you do not return to sleep within 20 minutes, get out of bed and do something relaxing. Do not return to bed until you feel sleepy. 9.Nap wisely Napping can be a good way to make up for poor or reduced nighttime sleep, but too much napping can cause problems falling asleep or staying asleep at night. If you need to nap for safety reasons such as driving, try to do so in the late morning or early afternoon, perhaps right after lunch, to take the edge off your sleepiness. 10.Move the clock from your bedside. If you tend to check the clock two or more times during the night, and if you worry that you are not getting enough sleep, cover the clock face or turn it around so that you cannot see it (or remove the clock from the bedroom entirely). The Ten Effective Sleep Habits were assembled by the Army Surgeon General’s Performance Triad Sleep Working Group.

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October – December 2013 117THE ARMY MEDICAL DEPARTMENT JOURNAL ACKNOWLEDGEMENTSThe authors gratefully acknowledge members of The Army Surgeon General’s Performance Triad Sleep Work Group: COL Steven Lewis (lead), AMEDDC&S; LTC Stephen Franco, US Army Training and Doctrine Command; Dr James Cartwright, US Army Public Health Command; COL William Frey, San Antonio Military Medical Center; LTC Christopher Lettieri, Walter Reed National Military Medical Center; and Dr Christine O’Riley, Landstuhl Regional Medical Center. The ideas presented in this paper were shaped and re ned through weekly discussions with the Sleep Working Group.REFERENCES1. Rechtschaffen A, Bergmann BM, Everson CA, Kushida CA, Gilliland MA. Sleep deprivation in the rat: X. Integration and discussion of the ndings. Sleep 1989;12(1):68-87. 2. Everson CA, Toth LA. Systemic bacterial invasion induced by sleep deprivation. Am J Physiol Regul Integr Comp Physiol 2000;278(4):R905-R916. 3. Tefft BC. The prevalence and impact of drowsy driving [internet]. Washington, DC: AAA Foundation for Traf c Safety; 2010. Available at: https://www.aaafoundation.org/sites/default/ files/2010DrowsyDrivingReport.pdf. Accessed August 13, 2013. 4. Functional and economic impact of sleep loss and sleep-related disorders. In: Colten HR, Altevogt BM, eds. Sleep Disorders and Sleep Deprivation: An Unmet Public Health Problem Washington, DC: National Academies Press; 2006: chptr 4. Available at: http://www.ncbi.nlm.nih.gov/books/ NBK19958/. Accessed August 13, 2013. 5. Xie WL, Shi Q, Xia SL, et al. Comparison of the pathologic and pathogenic features in six different regions of postmortem brains of three patients with fatal familial insomnia. Int J Mol Med 2013;31(1):81-90. 6. Cologan V, Drouot X, Parapatics S, Delorme A, Gruber G, Moonen G, Laureys S. Sleep in the unresponsive wakefulness syndrome and minimally conscious state. J Neurotrauma 2013;30(5):339-346. 7. Ohayon MM, Roth T. Place of chronic insomnia in the course of depressive and anxiety disorders. J Psychiatr Res 2003;37(1):9-15. 8. Rogers NL, Szuba MP, Staab JP, Evans DL, Dinges DF. Neuroimmunologic aspects of sleep and sleep loss. Semin Clin Neuropsychiatry 2001;6(4):295-307. 9. Jelicic M, Bosma H, Ponds RW, Van Boxtel MP, Houx PJ, Jolles J. Subjective sleep problems in later life as predictors of cognitive decline. Report from the Maastricht Ageing Study (MAAS). Int J Geriatr Psychiatry 2002;17(1):73-77. 10. Van Cauter E, Spiegel K, Tasali E, Leproult R. Metabolic consequences of sleep and sleep loss. Sleep Med 2008;9(suppl 1):S23-S28. 11. Sands-Lincoln M, Loucks EB, Lu B, et al. Sleep duration, insomnia, and coronary heart disease among postmenopausal women in the women’s health initiative. J Womens Health (Larchmt) 2013;22(6):477-486. 12. Sigurdardottir LG, Valdimarsdottir UA, Mucci LA, et al. Sleep disruption among older men and risk of prostate cancer. Cancer Epidemiol Biomarkers Prev 2013;22(5):872-879. 13. Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol 2005;25(1):117-129. 14. Goel N, Rao H, Durmer JS, Dinges DF. Neurocognitive consequences of sleep deprivation. Semin Neurol 2009;29:320-339. 15. Poe GR, Walsh CM, Bjorness TE. Cognitive neuroscience of sleep. Prog Brain Res 2010;185:1-19. 16. Thomas M, Sing H, Belenky G, et al. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. J Sleep Res 2000;9(4):335-352. 17. Damasio AR. On some functions of the human prefrontal cortex. Ann N Y Acad Sci 1995:769:241-251. 18. Field Manual 6-22.5: Combat and Operational Stress Control Manual for Leaders and Soldiers Washington, DC: US Dept of the Army; March 2009: chap 4. 19. NIH: sleep disorders information [internet]. Washington, DC: National Institutes of Health. Available at: http://www.nhlbi.nih.gov/health/public/sleep/. Accessed August 13, 2013. 20. NIH: brain basics, understanding sleep [internet]. Washington, DC: National Institutes of Health; [updated May 21, 2007]. Available at: http://www. ninds.nih.gov/disorders/brain_basics/understand ing_sleep.htm#dynamic_activity. Accessed August 13, 2013. 21. CDC: sleep and sleep disorders [internet]. Atlanta, GA: Centers for Disease Control and Prevention; [reviewed May 3, 2012]. Available at: http://www. cdc.gov/sleep/. Accessed August 13, 2013. 22. National Sleep Foundation (US): sleep is vital to our health & well being [internet]. Arlington, VA: National Sleep Foundation; 2013. Available at: http://www.sleepfoundation.org/. Accessed August 13, 2013. 23. Guilleminault C, Tilkian A, Dement WC. The sleep apnea syndromes. Ann Rev Med 1976;27: 465-484.

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118 http://www.cs.amedd.army.mil/amedd_journal.aspx24. Report of The President’s Commission on The Accident at Three Mile Island Washington, DC: US Government Printing Of ce; October 30, 1979. Available at: http://www.threemileisland.org/down loads/188.pdf. Accessed August 13, 2013. 25. R eport of the Presidential Commission on the Space Shuttle Challenger Accident Washington, DC: US Government Printing Of ce; June 6, 1986. Available at http://history.nasa.gov/rogersrep/genindex. htm. Accessed August 14, 2013. 26. S tang E. Chernobyl-system accident or human error? Radiat Prot Dosimetry. 1996;68(3-4):197-201. 27. Sumwalt RL. The anatomy of an accident: Colgan Air ight 3407 [internet]. February 12, 2010. Available at: http://www.ntsb.gov/doclib/speeches/sumwalt/SCAA-100212.pdf. Accessed August 14, 2013. 28. S taff RT. Reserve, brain changes, and decline. Neuroimaging Clin N A 2012;22(1):99-105, 29. R upp TL, Wesensten NJ, Bliese PD, Balkin TJ. Banking sleep: realization of bene ts during subsequent sleep restriction and recovery. Sleep 2009;32(3):311-321. 30. Lentino CV, Purvis DL, Murphy KJ, Deuster PA. Sleep as a component of the performance triad: the importance of sleep in a military population. US Army Med Dep J October-December 2013:97-107. 31. B elenky G. Sleep, sleep deprivation, and human performance in continuous operations. Paper presented at: Joint Services Conference on Professional Ethics; 30-31 January 1997; Washington, DC. Available at: http://isme.tamu.edu/JSCOPE97/Belenky97/Belen ky97.htm. Accessed August 14, 2013. 32. H arrison Y, Horne JA. Long-term extension to sleep–are we really chronically sleep deprived?. Psychophysiology 1996;33(1);22-30. 33. Be lenky G, Wesensten NJ, Thorne DR, et al. Patterns of performance degradation and restoration during sleep restriction and subsequent recovery: a sleep dose-response study. J Sleep Res 2003;12(1):1-12. 34. We sensten NJ, Balkin TJ, Belenky G. Does sleep fragmentation impact recuperation? A review and reanalysis. J Sleep Res 1999;8(4):237-245. 35. Ma rtin JL, Hakim AD. Wrist actigraphy. Chest 2011;139(6):1514-1527. 36. Mo ntgomery-Downs HE, Insana SP, Bond JA. Movement toward a novel activity monitoring device. Sleep Breath 2012;16(3):913-917. 37. Ru pp TL, Balkin TJ. Comparison of Motionlogger Watch and Actiwatch actigraphs to polysomnography for sleep/wake estimation in healthy young adults. Behav Res Methods 2011;43(4):1152-1160. 38. Balkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. System and method for predicting human cognitive performance using data from an actigraph. US patent 6 241 686. June 5, 2001. 39. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method for predicting human cognitive performance. US patent 6 419 629. July 16, 2002. 40. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. System and method for predicting human cognitive performance using data from an actigraph. US patent 6 527 715. March 4, 2003 41. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method and system for predicting human cognitive performance. US patent 6 530 884. March 11, 2003. 42. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method and system for predicting human cognitive performance. US patent 6 553 252. April 22, 2003. 43. Balkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method and system for predicting human cognitive performance. US patent 6 740 032. May 25, 2004. 44. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method and system for predicting human cognitive performance using data from an actigraph. US patent 6 743 167. June 1, 2004. 45. Ba lkin TJ, Belenky GL, Hall SW, et al, inventors. US Government [Dept of the Army], assignee. Method and system for predicting human cognitive performance. US patent 7 766 827. August 3, 2010. 46. Abdullah SP. Performance triad to lead Army medicine to system for health [internet]. Washington DC: US Dept of the Army; January 7, 2013. Available at: http://www.army.mil/article/93893. Accessed August 14, 2013. 47. Bermudez A. Surgeon General de nes end state of performance triad roll out [internet]. Washington DC: US Dept of the Army; February 27, 2013. Available at: http://www.army.mil/article/97318. Accessed August 14, 2013.AUTHORSDr Wesensten is a Research Psychologist in the Behavioral Biology Branch, Center for Military Psychiatry and Neurosciences Research, Walter Reed Institute of Research, Silver Spring, Maryland. Dr Balkin is a Supervisory Psychologist and Chief of the Behavioral Biology Branch, Center for Military Psychiatry and Neurosciences Research, Walter Reed Institute of Research, Silver Spring, Maryland. THE CHALLENGE OF SLEEP MANAGEMENT IN MILITARY OPERATIONS

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October – December 2013 119THE ARMY MEDICAL DEPARTMENT JOURNALThe headquarters and primary instructional facility of the Army Medical Department Center and School, Fort Sam Houston, Texas.

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SUBMISSION OF MANUSCRIPTS TO THE ARMY MEDICAL DEPARTMENT JOURNAL The United States Army Medical Department Journal is published quarterly to expand knowledge of domestic and international military medical issues and technological advances; promote collaborative partnerships among the Services, components, Corps, and specialties; convey clinical and health service support information; and provide a professional, high quality, peer reviewe d print medium to encourage dialogue concerni ng health care issues and initiatives. REVIEW POLICY All manuscripts will be reviewed by the AMEDD Journal Â’s Editorial Review Board and, if re quired, forwarded to the appropriate subject matter expert for further review and assessment. IDENTIFICATION OF POTENTIAL CONFLICTS OF INTEREST 1. Related to individual authorsÂ’ commitments: Each author is responsible for the full disclosure of all financial and personal relationships that might bias the work or information presented in the manuscript. To prevent ambiguity, authors must state explicitly whether potential conflicts do or do not exist. Auth ors should do so in the manuscript on a conflict-of-interest notification section on the title page, pr oviding additional detail, if necessary, in a cover letter that accompanies the manuscript. 2. Assistance: Authors should identify Individuals who provide writing or other assistance and disclose the funding source for this assistance, if any. 3. Investigators: Potential conflicts must be disclosed to study participants. Authors must clearly state whether they have done so in the manuscript. 4. Related to project support: Authors should describe the role of the study sponso r, if any, in study design; collection, analysis, and interpretation of data; writing the repo rt; and the decision to submit the report for publication. If the supporting source had no such involvement, the authors should so state. PROTECTION OF HUMAN SUBJECTS AND ANIMALS IN RESEARCH When reporting experiments on human subjects, authors must indi cate whether the procedures follo wed were in accordance with the ethical standards of the responsible co mmittee on human experimentation (institution al and national) and with the Helsinki Declaration of 1975, as revised in 2000. If doubt exists whether the research was conducted in accordance with the Helsinki Declaration, the authors must explain the rationale for their approach and demonstrate that the institutional review body explicitly approved the doubtful aspects of the study. When reporting experiments on animals, authors should indicate whether t he institutional and national guide for the care and use of laboratory animals was followed. INFORMED CONSENT Identifying information, including names, initials, or hospital numbers, should no t be published in written descriptions, photographs, or pedigrees unless the informat ion is essential for scientific purposes and the patient (or parent or guardian) g ives written informed consent for publ ication. Informed consent for th is purpose requires that an identifiable patient be shown the manuscript to be published. Authors should disclose to these patients whether any potential id entifiable material might be available via the Internet as well as in pr int after publication. Patient consent should be written and archived, either with t he Journal the authors, or both, as dictat ed by local regulations or laws. GUIDELINES FOR MANUSCRIPT SUBMISSIONS 1. Manuscripts may be submitted either via email (preferred) or by regular mail. Mail submissions should be in digital format (preferably an MS Word document on CD/DVD) with one printe d copy of the manuscript. Ideally, a manuscript should be no longer than 24 double-spaced pages. However, exceptions will always be considered on a case-by-case basis. 2. The American Medical Association Manual of Style governs formatting in the preparation of text and references. All articles should conform to those guidelines as cl osely as possible. Abbreviati ons/acronyms should be limited as much as possible. Inclusion of a list of article acronyms an d abbreviations can be very helpful in the review process and is strongly encouraged. 3. A complete list of references cited in the article must be provided with the manuscript, with the following required data: Reference citations of published articles must include the auth orsÂ’ surnames and initials, arti cle title, publication title, year of publication, volume, and page numbers. Reference citations of books must includ e the authorsÂ’ surnames and initials, b ook title, volume and/or edition if appropriate, place of publ ication, publisher, year of copyright, and specific page numbers if cited. Reference citations for presentations, unp ublished papers, conferences, symposia, etc, must include as much identifying information as possible (l ocation, dates, presente rs, sponsors, titles). 4. Either color or black and white imagery may be submitted with the manuscr ipt. Color produces the best print reproduction quality, but please avoid excessive use of multiple colors and shading. Digital graph ic formats (JPG, TIFF, GIF) are preferred. Editable versions with data sets of any Excel charts and graphs must be included. Charts/graphs embedded in MS Word cannot be used. Prints of photographs are acceptable. If at all possible, please do not send photos embedded in PowerPoint or MS Word. Images submitted on slides, negatives, or copies of X-ray film will not be published. For clarity, please mark the top of each photographic print on the back. Tape captions to the back of photos or submit them on a separate sheet. Ensure captions and photos are indexed to each other. Clearly indicate th e desired position of each photo within the manuscript. 5. The authorsÂ’ names, ranks or academic/certification credenti als, titles or positions, current unit of assignment, and contac t information must be included on the title page of the manuscript. Submit manuscripts to: EDITOR, AMEDD JOURNAL AHS CDD BLDG 4011 2377 GREELEY RD STE T FORT SAM HOUSTON, TX 78234-7584 DSN 471-6301 Comm 210-221-6301 Email: amedd.journal@amedd.army.mil

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