JUNE 2018 Volume 25 Number 6 PAGE 2 Polypharmacy involving opioid, psychotropic, and central nervous system depressant medications, period prevalence and association with suicidal ideation, active component, U.S. Armed Forces, 2016 Richard P. Eide III, MD, MPH; Shauna Stahlman, PhD, MPH PAGE 10 Variations in the incidence and burden of illnesses and injuries among non-retiree service members in the earliest, middle, and last 6 months of their careers, active component, U.S. Armed Forces, 2000 Colby C. Uptegraft, MD; Shauna Stahlman, PhD, MPH PAGE 18 Diagnoses of eating disorders, active component service members, U.S. Armed Forces, 2013 Valerie F. Williams, MA, MS; Shauna Stahlman, PhD, MPH; Stephen B. Taubman, PhD PAGE 26 Brief report: Department of Defense midseason vaccine effectiveness estimates for the 2017 influenza season Lisa Shoubaki, MPH; Angelia A. Eick-Cost, PhD, ScM; Anthony W. Hawksworth, BS; Zheng Hu, MS; LeeAnne Lynch, MPH; Christopher A. Myers, PhD; Susan Federinko, MD, MPH PAGE 29 Letter to the Editor NIAID CE/CME
Page 2 is report uses routinely collected data in the Defense Medical Surveillance System (DMSS) to explore the period prevalence of polypharmacy among the active component U.S. military in 2016. e period prevalence across the Department of Defense was 10.8% and was highest for the Army (14.5%) and lowest for the Marine Corps (7.4%). Furthermore, a case control study was conducted to explore the potential association between polypharmacy and incident suicidal ideation (SI). ere was an increased adjusted odds of inci dent SI within 12 months following polypharmacy exposure, with adjusted odds ratios ranging from 1.53 (95% CI, 1.38.71) to 3.06 (95% CI, 2.00 4.70), depending on the number of qualifying polypharmacy criteria. Impor tant limitations to the current analysis are discussed. Results suggest that it would be prudent to screen for SI during the polypharmacy clinical encoun ter, particularly for persons with any of the mental health disorders consid ered in this report. Inclusion of Department of Defense Suicide Event Report (DoDSER) data along with medically coded SI in future surveillance would increase the sensitivity of identifying incident cases of SI. Polypharmacy Involving Opioid, Psychotropic, and Central Nervous System Depressant Medications, Period Prevalence and Association with Suicidal Ideation, Active Component, U.S. Armed Forces, 2016 Richard P. Eide III, MD, MPH (MAJ, USA); Shauna Stahlman, PhD, MPH olypharmacy is an ill-dened term with at least 24 unique denitions in the medical literature. 1,2 For exam ple, polypharmacy can refer to the simulta neous use of multiple prescription drugs to treat an individual for one or more medical conditions. Polypharmacy also can be used to describe an individuals pattern of exces sive healthcare utilization for the purpose of obtaining prescription drugs. Polypharmacy poses the potential threat of harm from the cumulative impact of drug eects on vari ous human tissues, interactions between one or more drugs, side eects, or a combi nation of all these. Between 1999 and 2012, the prevalence of polypharmacy increased from 8.4% to an estimated 15% of U.S. adults aged 20 years and older. 3 Concerns about polypharmacy have historically focused on adults years of age 4-10 ; however, recent research shows that polypharmacy among younger adults, such as the active duty mili tary where the overall average age in 2016 was 28.5 years, 11 is a growing problem. 12-14 According to a cross-sectional analysis of 311,400 Veterans Health Administration (VHA) beneciaries during 2010, polypharmacy aected 8.4% of Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF) veterans. 15 For the purposes of this report, poly pharmacy was dened (see Methods for complete denition) according to Defense Health Agency 16 guidance used to screen Military Health System (MHS) benecia ries with potentially high-risk medication use to target interventions (e.g., referral to a clinical pharmacist). 17 is guidance was derived from the 2015 U.S. Army Oce of the Surgeon General (OTSG) Policy Memo 15-039, 18 which focused on polypharmacy associated with psychotropic drugs and cen tral nervous system depressants (CNSDs) from seven broad categories. Psychotro pic medications (e.g., stimulants, antide pressants, antipsychotics) act directly on the central nervous system to aect mood, cognition, or perception; CNSDs (opioids, anxiolytics, anticonvulsants, and hypnotics [sleep aids]) down-regulate central nervous system function and some have the poten tial to suppress function of the respiratory center in the brainstem. e use of multiple psychotropic and/or CNSD medications, especially with the addition of an opioid, is a type of polypharmacy with potential for multiple adverse events 19,20 including overdose, 21,22 which can result in delirium, respiratory suppression, or death. 23-26 Oen these adverse events are unintentional 27-31 ; however, the authors of the previously cited VHA study found that veterans with polypharmacy (dened as ve or more concurrent prescriptions) had odds of sui cide-related behavior that were nearly four times higher (adjusted odds ratio [AOR] 3.94; 99% CI, 3.58.33) than veterans with out polypharmacy aer controlling for exist ing mental illness. 15 Suicide is one of the top 10 leading causes of death in the U.S. 32 and the overall age-adjusted rate of suicide increased 24% between 1999 and 2014. 33 Since the outset of the war in Afghanistan in 2001, the Depart ment of Defense (DoD) has experienced a dramatic rise in suicide rates. 34 e Army sustained the largest increase in suicide rate, from 8.7 per 100,000 persons in 2001 to 24.4 This article provides continuing education (CE) and continuing medical education (CME) credit. Please see information at the end of the article. CE/CME
Page 3 per 100,000 persons in 2015, 35,36 surpassing the ageand sex-adjusted U.S. civilian rate for the rst time in 2008 35 and only recently declining to a level comparable to the civilian rate. 36 Over the same period, the DoD has made signicant eorts to better understand suicide within the ranks to inform policy and develop a comprehensive strategy to combat and prevent suicide. For example, the DoD developed a standardized web-based report ing tool (DoD Suicide Event Report [DoD SER]), 37 which has been in use since 2008. In addition, the services have conducted largescale research projects, including collabora tion with the National Institutes of Health, as was done for the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). 38 Furthermore, in 2011, the Defense Suicide Prevention Oce 39 was established to lead and coordinate preven tion activities across the DoD. As a result of these eorts, many characteristics of fatal 40-42 and non-fatal 43-45 suicidal behaviors among U.S. military personnel over the past 16 years have been described. Suicidal ideation (SI) is considered an important outcome that can predict more serious suicidal behavior. 43,44,46 Life time prevalence of SI has been estimated at approximately 14% among active compo nent Army personnel. 43 Recent analysis of more than 10,000 cases of medically docu mented SI among active component Army personnel between 2006 and 2009 found that the highest risks of SI were associated with enlisted service members with less than 2 years of service, females, and those with a recent mental health diagnosis. 47 Addition ally, an examination of 2015 DoDSER data by the Army Public Health Center found that 13% of SI cases met criteria for any polypharmacy (using the same denition from OTSG Policy Memo 15-039) at the time of reporting. 48 e current level of polypharmacy across the DoD is not well established. is report examines the prevalence of polyphar macy among active component U.S. service members in 2016 and explores the potential association between polypharmacy involv ing opioids, and other drugs aecting the central nervous system, and SI that is inde pendent of existing psychiatric illness and military and demographic characteristics. METHODS All data used to identify polypharmacy and SI were derived from records routinely maintained in the Defense Medical Surveil lance System (DMSS). ese records include both ambulatory encounters and hospital izations of active component members of the U.S. Armed Forces in military and civilian (if reimbursed through the MHS) treatment facilities. In addition, these data contain administrative records for all prescriptions written for service members at military treat ment facilities or through civilian purchased care. For the purpose of these analyses, pre scriptions were limited to one for each drug name per day per service member. Prevalence of polypharmacy in 2016 was based on the referent population of all individuals serving in the active com ponent on 30 June 2016. e surveillance period was 1 January 2016 through 31 December 2016. e surveillance popula tion included all individuals who served in an active component of the Army, Navy, Air Force, or Marine Corps who were in ser vice on 30 June 2016. Prescription drug data in DMSS were grouped into the seven cat egories according to U.S. Food and Drug Administrationestablished pharmaco logic class and included opioids, stimulants, antidepressants, antipsychotics, anxiolytics (including mood stabilizers), anticonvul sants (including muscle relaxants), and hyp notics. 49 Polypharmacy was derived from OTSG Policy Memo 15-039 18 (Figure) and dened using the following criteria: Group A: four or more prescriptions all within 30 days of one another for any drug (including antibiotics, antihypertensives, statins, etc.) where at least one is an opioid; or Group B: four or more prescriptions all within 30 days of one another from among the seven cat egories of psychotropic or CNSD medica tions listed above; or Group C: three or more emergency room (ER) visits during the sur veillance period, each within 7 days of an opioid prescription. Of note, for eciency, the group C inclusion criteria deviate from OTSG Policy Memo 15-039 by limiting anal ysis to the surveillance period (calendar year 2016) rather than any consecutive 12-month interval that has case-dening (e.g., third) ER visit associated with an opioid prescrip tion in 2016. Additionally, persons who met polypharmacy criteria were further grouped into strata consisting of those meeting cri teria for only one group as low (i.e., only group A, B, or C), those meeting criteria for two groups but not three as moderate (e.g., groups A and B but not C), and those meet ing criteria for all three groups as high. Prior incident mental health diagno ses were dened according to Armed Forces FIGURE. Criteria for
Page 4 Health Surveillance Branch standardized health surveillance case denitions 50 and included: adjustment disorders, alcoholrelated disorders, anxiety disorders, bipolar disorders, depressive disorders, personality disorders, psychoses, post-traumatic stress disorder, schizophrenia, and substancerelated disorders. For the period prevalence calculation, individuals were considered to have an existing mental health diagnosis if it was diagnosed before the end of the surveil lance period (31 December 2016). A matched case-control design was used to explore the association between inci dent SI that occurred during 2016 and poly pharmacy in the preceding 12 months. e surveillance period for this component of the analysis was, therefore, 1 January 2015 through 31 December 2016. e surveillance population included all individuals who served in an active component of the Army, Navy, Air Force, or Marine Corps at any time during 2016 with evidence in DMSS of at least one existing mental health condition (dened above). An incident case of SI was dened as one inpatient encounter with a diagnosis of SI (ICD-10: R45.851) in the rst or second diagnostic position, two outpatient medical encounters within 180 days of each other with a diagnosis of SI in the rst or sec ond diagnostic position, or one outpatient medical encounter in a psychiatric or men tal healthcare specialty setting with a diag nosis of SI in the rst or second diagnostic position. Individuals who received a diagno sis of SI before 1 January 2016 were excluded as prevalent cases. Each individual could be counted as an incident case once during the surveillance period. Controls were sampled cumulatively from those in service at the time of the SI case diagnosis, assigned at a ratio of three controls per case (3:1), matched on age (within 1 year) and sex. Cases and controls were excluded if the service mem ber deployed within 12 months prior to the incident date of SI diagnosis. Analysis of matched groups was conducted by using conditional logistic regression to estimate the odds of SI among those with polypharmacy, compared to those without aer adjusting for potential confounders, including race/ ethnicity, military rank/grade, deployment history, marital status, education level, length of service, and military occupation. RESULTS Period prevalence of polypharmacy e percentages of polypharmacy over all and stratied by covariate subgroups are shown in Table 1 In 2016, a total of 139,249 individuals met any of the three criteria for polypharmacy, corresponding to an overall period prevalence of 10.8% across the active component military. e highest levels of polypharmacy were among Army members (14.5%) and the lowest levels were among those in the Navy (7.8%) or the Marine Corps (7.4%). e most common type of polypharmacy in 2016 was group A (those with four or more prescriptions, at least one opioid), accounting for 120,569 (86.6%) of the individuals. e highest-risk group (those who met all three criteria) accounted for only 976 (0.7%) of all individuals with polypharmacy. Overall, 54,860 (39.4%) of all persons who met at least one criterion for polypharmacy had been diagnosed with a mental health disorder at any point in time before the end of 2016. e conditional probability of having a prior mental health diagnosis and meeting criteria for group B was very high (3,196 of 3,727 = 85.8%), compared with that of group A (35.1%) and group C (22.3%). Covariate analysis showed that, on 30 June 2016, polypharmacy was most preva lent among active component service mem bers with the following characteristics: aged 35 years or older (14.9%), female (17.8%), senior enlisted (12.2%) or warrant ocer (13.4%) ranks, non-Hispanic black (13.3%), other/unknown marital status (16.3%), an educational attainment of either non-com pletion of high school (13.1%) or having completed some college (13.8%), 11 or more years of service (13.6%), multiple deploy ments (12.1%), working in a healthcare occupation (15.3%), and among those diag nosed with a mental health disorder (20.8%). Association with suicidal ideation e frequency distributions of the covariates among cases and controls are shown in Table 2 A total of 2,754 cases of incident SI were identied among ser vice members with existing mental health disorders in 2016. A total of 8,262 ageand sex-matched controls were randomly selected from all other service members who had been identied with a diagnosis of a mental health condition. e dierences between the distributions of service, rank, race/ethnicity, marital status, educational attainment, length of service, deployment history, and military occupation of cases and controls were statistically signicant (p<0.05). In particular, compared to ageand sex-matched controls, cases were more frequently in the Army, junior enlisted (E1 E4), and with less than 2 years of service. e adjusted odds ratios of polyphar macy exposure within 1 year prior to date of incident SI diagnosis are presented in Table 3 Among similar service members with existing mental health conditions, those diagnosed with incident SI in 2016 had higher adjusted odds of polypharmacy exposure in the preceding 12 months. e adjusted odds of incident SI were 53% higher for those classied in the low stra tum (AOR 1.53; 95% CI, 1.38.71), 120% higher for those in the moderate stratum (AOR 2.20; 95% CI, 1.92.53), and more than 200% higher for those service mem bers in the high stratum (AOR 3.06; 95% CI, 2.00.70). EDITORIAL COMMENT e rst part of this report examines the period prevalence of polypharmacy in active component military members dur ing 2016. e overall period prevalence of 10.8% across the active component mili tary is higher than the previous estimate of 8.4% from among OEF/OIF veterans in 2011. 15 However, it is dicult to compare these two studies that used dierent deni tions of polypharmacy. When compared to results from a study using the same deni tion as this report, the estimated prevalence of 14.5% among Army personnel observed in the current analysis was considerably higher than the previous estimate of 2.2% 7.6% from among active duty Army in combat brigades at Fort Campbell, KY, in 2012. 17 One possible explanation for this dierence is that the compositions of units with combat-specic missions dier from
Page 5 TABLE 1. 2 criteria a Total Total No. No. No. No. No. No. No. No. No. No. Total Sex Female Native 2 22 2 Service Army Navy Air Force 22 Never deployed Yes No a
Page 6 that of the Army overall and, over time, select for healthier soldiers who do not have deployment-limiting conditions. Soldiers with complex medical problems that limit deployment, who are more likely to require multiple medications and potentially meet criteria for polypharmacy, are less likely to serve in such a unit and thus the prevalence estimate would be lower. Furthermore, it is possible that the prevalence of prescription drug use and polypharmacy have increased since 2012. e observation that individuals in group B (those with multiple psychotro pic or CNSD drugs) had the highest con ditional probability of a comorbid mental health disorder is expected. Individuals who are prescribed multiple psychotropic drugs are more likely to have one or more mental health conditions for which these types of medications are clinically indi cated. Similarly, the fact that most (86.6%) of the polypharmacy exposure in this study arose from individuals meeting criteria for group A is not surprising as there are many more types of clinical situations for which sucient medications to satisfy the criteria for group A would be prescribed than there are for the other two groups. e observation that higher preva lence of polypharmacy exposure was found among individuals working in health care occupations echoes the observation that healthcare workers accounted for the highest rates of overall prescription drugs in 2014. 51 ese ndings highlight a trend seen in surveillance reports on low back pain, 52 acute respiratory illness, 53 alcoholrelated diagnoses, 54 and obstructive sleep apnea, 55 among others. A possible explana tion is that healthcare workers have easier access to medical treatment by virtue of working in the same facility. Alternatively, persons with medical needs may select for healthcare occupations that are generally less physically demanding than combatspecic or other support occupations. e second part of this report explores the association between incident SI and precedent polypharmacy exposure within 12 months. Polypharmacy was found to be associated with incident SI (AOR = 1.53 3.06), which supports similar ndings from a 2010 study of OEF/OIF veterans. 15 e strength of the association increased as TABLE 2. No. No. Sex Female 22 222 Service Army Navy Air Force Grade Never deployed armor 22
Page 7 more criteria for polypharmacy exposure were satised, although the CIs widen to reect the smaller sample sizes. is associ ation should be interpreted with some cau tion as there are limitations to this report. It is possible that this observation reects the inuence of confounding from some variable that was not included in this anal ysis such as nancial stress, recent loss of a loved one, baseline variations in accession standards by year of entry into the mili tary, or perhaps most importantly, the type or severity of the underlying mental health disorder. For example, individuals with more severe mental health disorders might be more likely to report SI to a healthcare provider and also more likely to be pre scribed more medications, which would confound association between polyphar macy and incident SI found in this report. e administrative data used for this analy sis have limited capacity to ascertain illness severity and future study should take this into consideration. Another limitation of the current anal ysis is that it did not account for dierences between individuals who meet polyphar macy criteria repeatedly (e.g., chronic pre scription use) compared with those who only meet criteria transiently (e.g., follow ing an acute injury or surgical procedure). e duration of polypharmacy exposure may serve as an indicator of conditions that are more chronic and that previous research has demonstrated increase the risk of suicidal behaviors. 56,57 erefore, poly pharmacy may have been misclassied in this analysis, which could have biased the observed association with SI toward null. Future studies should explore the dierence between chronic and acute polypharmacy on outcomes such as SI. Finally, this report did not capture medications dispensed in the deployed environment or aboard ship for the U.S. Navy, so the true period preva lence may have been underestimated. is report describes the ndings of an exploratory analysis of the prevalence of polypharmacy among active component service members of the U.S. Armed Forces. e observation of an independent asso ciation between incident SI and precedent polypharmacy in the previous year is con cerning. However, there are important lim itations to the current analysis that should TABLE 3. a OR AOR ref ref ref ref ref ref Service Army ref ref Navy Air Force ref ref ref ref Never deployed ref ref armor ref ref a
Page 8 be addressed in future studies before trying to infer a causal relationship. Nevertheless, it would be prudent to screen for SI during the polypharmacy clinical encounter, par ticularly for persons with any of the mental health disorders considered in this report. Inclusion of DoDSER data along with med ically coded SI in future surveillance would serve to increase the sensitivity of identify ing incident cases of SI. Author aliations: Walter Reed Army Insti tute of Research, Silver Spring, MD (MAJ Eide); Armed Forces Health Surveillance Branch, Defense Health Agency, Silver Spring, MD (Dr. Stahlman). Acknowledgments: e authors thank Dr. Saixia Ying for her invaluable assistance with data collection and analysis; COL (Dr.) P. Ann Loveless for project oversight, mentorship, and feedback; and Ms. Amaris urston for project coordination and main taining timeline. Disclaimer: Material has been reviewed by the Walter Reed Army Institute of Research. ere is no objection to its presentation and/ or publication. e opinions or assertions contained herein are the private views of the author(s), and are not to be construed as ocial, or as reecting the true views of the Department of the Army or the Department of Defense. e investigators have adhered to the policies for protection of human subjects as prescribed in AR 70-25. REFERENCES Res Social Adm Pharm. 2. Br J Clin Pharmacol. JAMA. Clin Interv Aging. Am J Geriatr Pharmacother. J Manag Care Pharm. Expert Opin Drug Saf. Intern Emerg Med. J Am Acad Nurse Pract. pharmacist. Drugs Aging. Work. J Am Osteopath Assoc. Subst Use Misuse. Drugs Real World Outcomes. ic. J Manag Care Spec Pharm. Pain Med. Clin Micro biol Infect. BMC Med. 22. Drug Des Devel Ther. CNS Drugs. PLoS One. disorder. World Psychiatry. Prim Care Companion CNS Disord. Ann Emerg Med. J Am Med Dir Assoc. Ann Emerg Med. Am J Med Sci. Samaras N, Chevalley T, Samaras D, Gold G. Ann Emerg Med. NCHS Data Brief NCHS Data Brief the U.S. military. Rand Health Q. U.S. Army. Mayo Clin Proc. Psychiatry. JAMA. JAMA Psychiatry.
Page 9 CE/CME is activity oers continuing education (CE) and continuing medical education (CME) credit to qualied professionals, as well as a certicate of participation to those desiring documentation. For more information, go to www.health.mil/msmrce Key points e highest levels of polypharmacy were among Army members and the lowest levels were among those in the Navy or the Marine Corps. On 30 June 2016, polypharmacy was most prevalent among active component service members with the following characteris tics: aged 35 years or older, female, senior enlisted or warrant ocer ranks, non-Hispanic black, other/unknown marital status, an educational attainment of either non-completion of high school or having completed some college, 11 or more years of service, multiple deployments, working in a healthcare occupation, and among those diagnosed with a mental health disorder. Among similar service members with existing mental health conditions, those diagnosed with incident suicide ideation (SI) in 2016 had higher adjusted odds of polypharmacy exposure in the preceding 12 months. e adjusted odds of incident SI were 53% higher for those classied in the low polypharmacy stratum (met one of the following criteria: had four or more prescriptions all within 30 days of one another for any drug [including antibiotics, antihypertensives, statins, etc.] where at least one was an opioid; or had four or more prescriptions all within 30 days of one another from among the seven categories of psychotropic or CNSD medications; or had three or more emergency room visits during the surveillance period, each within 7 days of an opioid prescription). e adjusted odds of incident SI more than doubled for service members in the moderate polypharmacy stratum (met two of the three criteria) and tripled among those in the high polypharmacy stratum (met all three criteria). Learning objectives 1. e reader will understand the period prevalence of polypharmacy involving opioid, CNS depressant, and psychotropic medica tions among active component service members in the U.S. military in 2016. 2. e reader will interpret the distribution of polypharmacy involving opioid, CNS depressant, or psychotropic medications by various demographic and service-related variables. 3. e reader will explain the association between polypharmacy and incident suicidal ideation among service members with men tal health disorders. Disclosures: MSMR sta authors, DHA J7, AnityCE/PESG, as well as the planners and reviewers of this activity have no nancial or nonnancial interest to disclose. JAMA Psychiatry. JAMA Psychiatry. Depress Anxi ety. Psychiatry. Arch Gen Psychiatry. U.S. Army Soldiers. Suicide Life Threat Behav. Ac MSMR. MSMR. MSMR. MSMR. MSMR. Curr Pain Headache Rep. Health Psychol Behav Med
Page 10 is report uses routinely collected data in the Defense Medical Surveillance System (DMSS) to characterize the incidence and burden of medical condi tions throughout the careers of service members separating from the active component of the U.S. Armed Forces between 1 October 2014 and 30 Sep tember 2015. ree surveillance periods between 30 September 2000 and 30 September 2015 were dened by each individuals time in service: early (rst 6 months), middle (middle 6 months), and late (last 6 months). Overall, sep arating service members were most oen aged 25 years (59.4%), male (84.0%), non-Hispanic white (64.0%), junior enlisted (52.4%), in the Marine Corps (33.1%), serving in a repair/engineering occupation (33.0%), and had never deployed (52.5%). e top ve burden of disease categories across surveillance periods by sex were very similar, including mental health dis orders, which exhibited similar upward trends across the three surveillance periods (males: 1.3%, 17.0%, and 35.6%; females: 1.8%, 15.1%, and 32.4%, respectively). e most common diagnoses exhibiting upward, downward, or bimodal trends by incidence rate dierences were mental health disorders, respiratory infections/diseases, and musculoskeletal diseases, respectively. Variations in the Incidence and Burden of Illnesses and Injuries Among Non-retiree Service Members in the Earliest, Middle, and Last 6 Months of Their Careers, Active Component, U.S. Armed Forces, 2000 Colby C. Uptegra, MD (Capt, USAF); Shauna Stahlman, PhD, MPH he burden and incidence of medical conditions among residents of the U.S. vary by age, sex, race/ethnic ity, socioeconomic status, insurance status, occupation, clinical setting, geographical region, and time. 1-7 Active component ser vice members (ACSMs) represent a unique subset of this population. Entrance into the U.S. Armed Forces requires a minimum level of health and tness among appli cants, 8 making ACSMs, at least upon entry, healthier than their civilian counterparts, a phenomenon known as the healthy sol dier eect. 9,10 Aer entry, occupational and readiness requirements expose ser vice members to numerous unique hazards not commonly found outside the military. e selection of healthy men and women for accession and the subsequent exposure prole of active service prevent the gener alization of civilian incidence and burden ndings to military populations. Military medical standards for acces sion are stricter than retention standards. For instance, potential recruits with symp tomatic hemorrhoids and/or abdominal wall hernias would likely not meet acces sion standards, but ACSMs with these con ditions, with rare exceptions, would not be medically separated. 8,11-13 However, ACSMs must continue to meet health and tness requirements to maintain their service eli gibility. ese requirements are updated periodically and vary across occupational class and branch of service. 8,11-13 e dis tinct occupations within each service expose ACSMs to unique work settings and environments, both in garrison and while deployed. For those ACSMs pursu ing career longevity and certain military occupations, there are disincentives for reporting medical conditions or seeking care. e development of post-accession medical conditions raises the possibility of adverse personnel actions such as medical evaluation boards and subsequent medi cal separation, duty location or deployment limitations, or career eld denial or termi nation, particularly special-duty occupa tions such as aviation and special forces. On the other hand, as ACSMs approach and prepare for retirement (ser vice of 20 or more years) or separation (ser vice of less than 20 years), there are positive incentives for reporting health issues and having them evaluated, treated if necessary, and documented in their health records. Service members who retire or separate with service-connected health conditions or disabilities are eligible for disability com pensation and health care for those condi tions through the Department of Veterans Aairs. 14 Because of the occupational dis incentives for healthcare-seeking behaviors and the pre-separation incentives for such behaviors, precise estimates of the bur den and incidence of medical conditions throughout service members careers are dicult to ascertain. Two previous studies characterized the incidence of illnesses and injuries immedi ately prior to retirement. Service members within 6 months of retirement were more likely than pre-retirees (12 months before retirement) to receive any medi cal diagnosis, particularly those diagnoses common among similarly aged Americans and compensable as service-connected dis abilities. 15 Additionally, 72.1% of retirees were diagnosed with a new medical condi tion within 6 months of retirement, and the number of illnesses and injuries, both new and old, diered by occupational group and
Page 11 rank. 16 However, these studies included only retirees, and, on average, about 17% of enlisted service members and ocers across all branches ever reach retirement eligibility. 17 e remaining 83% of ACSMs that separate from service tend to be younger, lower ranking, and less advanced in their careers than retirees. Although other dierences likely exist, these alone make separating service members a distinct subpopulation, warranting further study to better characterize illness and injury across the careers of ACSMs. Medical readiness is the core focus of the Military Health System. 18,19 Servicespecic databases that log readiness sta tistics indicate that deployment-limiting medical conditions are the main reasons why ACSMs are not deployable and thus not medically ready. 20-22 Characterization of the temporality of when medical con ditions occur throughout the career of ACSMs, stratied by demographic and military characteristics, may oer insight for preventive interventions to improve the health and medical readiness of service populations. e purpose of this study is to characterize the incidence and burden of medical conditions throughout the careers of separating service members. METHODS e surveillance population included all individuals who entered active military service aer 30 September 2000 and sep arated from the active component of the Air Force, Army, Marine Corps, or Navy between 1 October 2014 and 30 Septem ber 2015, and who had at least 48 months of continuous active service at the time of separation. ree surveillance periods were determined by the individuals dates of ser vice: early (rst 6 months), middle (middle 6 months), and late (last 6 months of ser vice). Retirees (service members with 240 or more months of active service) and ser vice members with any breaks in service during their careers (n = 9,585) or deploy ment days during any of the three surveil lance periods (n = 16,339) were excluded. For each individual in the study pop ulation, all illness and injury diagnoses (ICD-9: 000) that were recorded during inpatient and outpatient medi cal encounters in U.S. military medical facilities, and from purchased-care pro viders, were obtained from standardized medical records routinely maintained in the Defense Medical Surveillance System (DMSS). All ICD codes were grouped into 25 major burden of disease categories based on a modied version 23 of the Global Bur den of Disease Study. 24 is grouping was done to provide an overall estimate of the most common conditions aecting service men and women during the three dierent surveillance periods. To calculate the total hospitalizations and outpatient visits for each diagnosis, only three-digit ICD-9 codes in the rst diagnostic position were included, with no more than one encounter per three-digit ICD code per individual per day. e pro portion of total encounters for each burden of disease category was calculated by divid ing the total encounters for each category by the overall total number of encounters. ree-digit ICD-9 codes documented in any diagnostic position recorded for the rst time in an ACSMs career and during each surveillance period were considered incident (rst-time) occurrences. e total number of at-risk ACSMs for each surveil lance period was the number of service members in the study population not diag nosed with the respective ICD code prior to the start of the surveillance period. Inci dence rates (IRs) were calculated by divid ing the number of rst-time occurrences by the number of at-risk service members for each ICD code for each surveillance period. ree trends in IRupward, down ward, and bimodalwere chosen for anal yses. An upward trend was dened as an increase in IR between both the early and middle and middle and late surveillance periods. Diagnoses exhibiting an upward trend were ranked by the total dierence in the IR between the late and early surveil lance periods from largest to smallest. A downward trend was dened as a decrease in the IR between both the early and mid dle and middle and late surveillance peri ods. Diagnoses exhibiting a downward trend were ranked by the total dierence in the IR between the late and early surveil lance periods from largest to smallest. A bimodal trend was dened as a decrease in the IR between the early and middle sur veillance period and an increase between the middle and late period. Diagnoses exhibiting a bimodal trend in the IRs were ranked by the sum of the absolute value of the dierence between the early and middle surveillance period and the absolute value of the dierence between the middle and late period from largest to smallest. For all trends, results were stratied by sex. RESULTS e demographic and military charac teristics of the study population by time in service are shown in Table 1 Of the 45,363 total separating service members between 1 October 2014 and 30 September 2015 with at least 4 years of continuous active compo nent service, 32,597 (71.9%) separated with 4 years of active service, 10,040 (22.1%) with 8 years, and 2,726 (6.0%) with 12 years. Overall, separating service members were most oen aged 25 years (59.4%), male (84.0%), non-Hispanic white (64.0%), and junior enlisted (52.4%). e Marine Corps (33.1%) contributed more ACSMs to the study population than any of the other services. e occupational cat egory of repair/engineering was the most common (33.0%). Among all members of the study population, 52.5% had never deployed. Overall, females had more total encounters per service member in the early, middle, and late surveillance peri ods (5.0, 6.3, and 12.3, respectively) than males (3.0, 2.6, and 7.3, respectively) (data not shown) e proportions of total outpa tient and inpatient encounters by burden of disease major categories for each surveil lance period and sex are shown in the Fig ure e ve top-ranking burden of disease major categories in all surveillance periods in both sexes were very similar. Injuries/ poisonings, musculoskeletal diseases, and signs and symptoms were present in the ve top-ranking categories in both sexes across all three surveillance periods. Respiratory infections (males: 29.9%; females: 17.0%) were among the top-ranking diagnoses in the rst surveillance period but were
Page 12 EDITORIAL COMMENT is report examines the diagnos tic trends across three time points in the careers of service members separating from the active component between 1 October 2014 and 30 September 2015. Several com parisons can be made to previous studies on overall disease burdens and common diagnoses in recruits and retiring service members. Crowded living conditions 25 and the stressful environment of military train ing, 26-29 make recruit populations particu larly susceptible to respiratory infections. 30 erefore, the observed encounter bur den of respiratory infections in the rst 6 months of service and the downward trend in related three-digit ICD-9 codes across surveillance periods is consistent with expectations and prior ndings. Addition ally, the commonality of musculoskeletal conditions, including other and unspeci ed disorders of joint (ICD-9: 719), other disorders of so tissues (ICD-9: 729), and disorders of muscle ligament and fascia (ICD-9: 728), in both the rst 6 months and last 6 months of service (bimodal trend) is not surprising. Two factors are likely con tributing to this nding. First, in the initial 6 months of service, recruits during basic training are particularly prone to inju ries and musculoskeletal conditions 31-34 ; this increased risk is especially evident for females, 34-36 which might also explain the greater proportionate encounter bur den for injuries/poisonings and musculo skeletal disorders among females during the rst 6 months (38.4%) versus among males (29.5%). During the last 6 months of service, ACSMs are encouraged to report chronic conditions during separation/ retirement physicals as documentation of service-connected conditions increases their likelihood of both obtaining disability compensation 14 through the Department of Veterans Aairs (VA) and accessing VA healthcare. 37 Conversely, during the mid dle 6 months of service, other than being older and having more time in service than the rst 6 months of service, there are not any strong risk factors or VA entitlement incentives for seeking care or reporting these conditions. TABLE 1. characteristics a No. Sex Female Native Service Army Navy Air Force a not among the ve top-ranking diagno ses thereaer. Additionally, mental health disorders exhibited similar upward trends across the three surveillance periods rep resenting one-third of total encounters in both sexes in the last period (males: 1.3%, 17.0%, and 35.6%; females: 1.8%, 15.1%, and 32.4%, respectively). Although the distributions of the major burden of disease categories in the surveillance periods were broadly similar for males and females, several dierences emerged. Injuries/poisonings remained consistent at 15.5% across the rst and middle surveillance period and then fell to 6.6% among males but showed a consistent decline across surveillance periods among females (15.0%, 7.9%, and 4.2%, respec tively). Musculoskeletal disorders peaked at 24.3% in the middle surveillance period for males but peaked at 23.4% in the rst period for females. e all other cate gory (the proportion of total encounters for all major burden categories ranked 6th through 25th for each surveillance period) was also slightly larger among females than among males across all periods (males: 23.2%, 24.8%, and 16.1%; females: 25.4%, 31.8%, and 23.2%, respectively). Tables 2a and 2b show the 10 top-rank ing diagnoses exhibiting upward, down ward, or bimodal trends across the three surveillance periods, by IR dierences, among males and females, respectively. For upward trends, mental health disor ders were the most common type of diag nosis in the 10 top-ranking diagnoses for both sexes, and musculoskeletal conditions were more common in females than males. However, it should be noted that the sub stantial increase in the incidence rates of adjustment reaction over time was largely driven by diagnoses of posttraumatic stress disorder (ICD-9: 309.81), which increased from 1.1% to 17.9% of the total 309.* diag noses among males and from 3.1% to 16.4% among females from the rst to last period (data not shown) e downward-trending top 10 list comprised mostly respiratory infections/diseases, and injuries/poison ings were more common in females than males. Lastly, for bimodal trends, muscu loskeletal conditions were the most com mon conditions for both sexes in their top 10 lists.
Page 13 Mental health disorders dramatically increased in total encounter burden and were the most common diagnoses exhibit ing upward trends in incidence across the careers of those separating from the U.S. Armed Forces. e types of mental health disorders exhibiting upward trends in this study for both sexesadjustment reac tion (ICD-9: 309), anxiety, dissociative, and somatoform disorders (ICD-9: 300), and depressive disorder, not elsewhere classied (ICD-9: 311)also were among the most common incident mental health disorder categories including adjustment disorders, depressive disorders, and anxi ety disorders among all service members during this time period. 38 ese upward trends in incidence seem counter to trends observed in the civilian population in which most mental health disorders occur during childhood or adolescence. 39 How ever, most (94.2%) of the surveillance pop ulation in this study were aged 17 years, so this nding might not be surprising, especially as most of the more common disorders diagnosed during military ser vice (e.g., mood disorders, other anxiety disorders, and substance use disorders) 38 are diagnosed aer age 18. 39 Additionally, military service has many unique stress ors, 40-51 particularly combat and trauma exposure, 40-42,44,47-49 which might explain these trends. Two MSMR studies published in 2010 both found a pronounced increase in the incidence rates of illness and injury-related diagnoses within 6 months of retirement, compared to 12 months before retire ment. 15,16 However, mental health con ditions were neither among the 18 most frequent illnesses/injuries diagnosed among retirees 16 nor in the top 25 diag noses by incident rate dierences when comparing retirees versus pre-retirees or retirees versus retirement eligible. 15 ese are striking dierences compared to this studys nding of a growing pro portionate encounter burden across time in service and upward trends in mental healthrelated ICD codes for separating service members. ere are several poten tial reasons for this dierence. First, this study did not distinguish between vol untarily separating service members and those being medically separated. Many mental health conditions, especially those lasting longer than a year, requiring treat ment, and/or impacting duty, do not meet retention standards, 11-13 and mental health disorders have been found to be the leading category of discharge diagnoses in men and the second leading category in women. 52 Service members reaching retirement are likely among the healthiest overall ser vice members across time, and this could be the reason for the observed dierences between the two populations. e ndings of this report should be interpreted in light of several important limitations. First, because this study did not focus on a single disease or subset of diseases, it would not have been feasible to FIGURE. a a total three disease major U.S. Armed a Females
Page 14 TABLE 2 a a c d code First No. of cases No. of cases Last No. of cases Other disorders of ear 222 diseases Respiratory diseases other chest symptoms a c d
Page 15 TABLE 2 b a c d code First No. of cases No. of cases Last No. of cases eases Respiratory diseases 2 other chest symptoms Respiratory diseases a c d
Page 16 apply or develop case denitions for every possible diagnosis. However, for many conditions, a single ICD-9 code may not represent a true or nal diagnosis, and many encounters might have been screen ing encounters or have been coded incor rectly. ese possibilities represent a source of misclassication bias. Second, trends were dened in absolute terms (i.e., any change between periods), rather than by relative or minimum percent changes, and dening trends dierently likely would have produced a dierent set of results. Another limitation is that the study population consisted only of those service members separating in a specic 1-year window. ose separating in 1 year might be dierent in terms of demographic char acteristics and health from those separat ing in another year. For instance, the time frame chosen for this study, October 2014 through September 2015, is 5 years fol lowing one of the worst recessions in U.S. history and the drawdown of forces in Iraq and Afghanistan. e individuals who chose to leave military service during this studys surveillance window might be con siderably dierent from those who le dur ing other time periods; thus, ndings from this study may not be generalizable to pre vious or future separating service mem bers. Additionally, the surveillance periods were only 6 months in length. Although the length of this period might not be of par ticular concern for males because of their larger sample size, this short time frame might not have captured a representative picture of disease in the relatively smaller sample of females. Findings were strati ed only by sex while many other potential confounders likely exist such as age, race/ ethnicity, branch of service, military rank/ grade, and military occupation. Lastly, ser vice members who were deployed dur ing any of the surveillance windows were excluded to allow for equal surveillance opportunity across the three time periods. However, this exclusion may have intro duced selection bias given that service members who deploy tend to be healthier than those who do not deploy. 53 is study appears to be one of the rst to examine diagnostic trends over specied time points during the careers of individual service members, and several trends were identied that could oer opportunities for preventive interventions. Compared to prior studies, separating service mem bers seem to be dierent from those retir ing with respect to the incidence of medical conditions prior to leaving service. Volun tarily separating service members without disability have more diculty accessing VA healthcare than retiring individuals or those who are medically separated. 37 If fur ther studies show a signicant burden of disease among voluntarily separating ser vice members who are not accessing VA healthcare, this nding could warrant a review of the transition and compensation process when separating service members move from active duty to civilian life. Author aliations: Department of Pre ventive Medicine and Biostatistics, Uni formed Services University of the Health Sciences, Bethesda, MD (Capt Uptegra); Armed Forces Health Surveillance Branch, Defense Health Agency, Silver Spring, MD (Dr. Stahlman). Acknowledgments: e authors thank COL (Dr.) P. Ann Loveless for her project guidance and mentorship; CDR (Dr.) Shawn Clau sen, Dr. Margaret Venuto, and Dr. D. Wil liam White for their thoughtful insights; Dr. Saixia Ying for fullling this project's data request; and Ms. Amaris urston for her administrative support. Disclaimer: e contents of this publication are the sole responsibility of the authors and do not necessarily reect the views, asser tions, opinions, or policies of the Uniformed Services University of the Health Sciences (USU), the Department of Defense (DoD), or the Departments of the Army, Navy, or Air Force. Mention of trade names, com mercial products, or organizations does not imply endorsement by the U.S. Government. REFERENCES 2. EMBO Reports mortality. Am J Epidemiol. N Engl J Med. MSMR. MSMR. 22.
Page 17 MSMR. War Med. N Engl J Med. J R Army Med Corps. cise. J Appl Physiol. Clin Microbiol Rev. Am J Or thop (Belle Mead NJ). Am J Prev Med. factors. Mil Med. J Athl Train. Med Sci Sports Exerc. Mil Med. MSMR. Curr Opin Psychiatry. to care. N Engl J Med. J Clin Psychol. Am J Pub lic Health. Hosp Community Psychiatry. J Health Econ. Clin Psychol Rev. DSM-IV JAMA Psychia try. J Psychiatr Res. Am J Public Health. J Womens Health (Larchmt). Demogra phy. Fam Relat. Am J Psychia try. Popul Health Metr.
Page 18 During 2013, a total of 1,788 active component service members received incident diagnoses of one of the eating disorders: anorexia ner vosa (AN), bulimia nervosa (BN) or other/unspecied eating disorder (OUED). e crude overall incidence rate of any eating disorder was 2.7 cases per 10,000 person-years. Of the case-dening diagnoses, OUED and BN accounted for 46.4% and 41.8% of the total incident cases, respectively. e overall incidence rate of any eating disorder among women was more than 11 times that among men. Overall rates were highest among service members in the youngest age groups (29 years or younger). Crude annual incidence rates of total eating disorders increased steadily between 2013 and 2016, aer which rates decreased slightly. Results of the current study suggest that service members likely experience eating disorders at rates that are com parable to rates in the general population, and that rates of these disorders are potentially rising among service members. ese ndings underscore the need for appropriate prevention and treatment eorts in this population. Diagnoses of Eating Disorders, Active Component Service Members, U.S. Armed Forces, 2013 Valerie F. Williams, MA, MS; Shauna Stahlman, PhD, MPH; Stephen B. Taubman, PhD ating disorders are characterized by signicant and persistent distur bances of eating that are associated with increased psychopathology, serious physical health problems, impaired psy chosocial functioning, and reduced qual ity of life. 1-3 Moreover, eating disorders represent a considerable economic burden in terms of work productivity loss, health care resource utilization, and healthcare costs. 4,5 e International Classication of Diseases, Tenth Revision, Clinical Modi cation (ICD-10) includes four broad cat egories of eating disorder types: anorexia nervosa (AN), bulimia nervosa (BN), other eating disorders, and eating disor ders, unspecied. Both the types of con ditions included in these categories and the diagnostic criteria for the specic dis orders have changed over time. e diag nostic criteria for these conditions draw on the American Psychiatric Associa tion Diagnostic and Statistical Manual of Mental Disorders (DSM-V) classication and are summarized in Table 1 6 Eating disorders are not associated with loss of appetite, are non-organic in origin (i.e., not caused by a known physical illness), and are not directly attributable to other mental disorders. 6 e prevalence of eating disorders is generally elevated among young females 7,8 and in high-income countries, 9,10 possibly attributable to sociocultural and economic factors. In the U.S., eating disorders aect members of all race/ethnicity groups. 2,11 Estimates of the prevalence of these disor ders in the general population vary widely, depending on study methods and popula tions. 12 In a nationally representative U.S. sample, lifetime prevalence estimates of AN and BN were 0.9% and 1.5% among women, and 0.3% and 0.5%, respectively, among men. 2 Published studies of the prevalence of eating disorders among U.S. military members have used a variety of assess ment methods and have yielded a range of estimates. 13-23 Studies of U.S. military pop ulations that diagnosed eating disorders using clinical interviews reported preva lence estimates that are generally com parable to or higher than those obtained from studies of the U.S. general popula tion, with approximately 5%% of ser vice women and 0.1% of service men diagnosed with an eating disorder. 15,16,22 Studies that employed validated eating disorder screening instruments in military populations have described prevalence estimates for AN, BN, and eating disorder not otherwise specied (EDNOS) of 1.1%, 8.1%.5%, and 36.0%.8% among women, respectively, and 2.5%, 6.8%, and 40.8% among men. 13,14,18 Lower estimates were obtained from a study of U.S. service members based on eating disorder diag noses recorded during hospitalizations and outpatient healthcare encounters (AN, BN, and EDNOS: 0.25%, 0.79%, and 0.72%, respectively, among women, and 0.01%, 0.02%, and 0.03% among men). 21 By current Department of Defense (DoD) policy, a diagnosis of AN, BN, or an unspecied eating disorder lasting lon ger than 3 months and occurring aer age 13 is medically disqualifying for acces sion into military service. 24 Moreover, service members aected by eating dis orders that are unresponsive to treatment and/or interfere with the satisfactory per formance of their military duties may be referred to a medical evaluation board and may possibly be separated from service. 25 Among military populations, several factors could increase risk of developing an eating disorder. Military members are subject to strict service-specic regula tions regarding physical tness and weight requirements and their lifestyles are reg imented. 26 It is well recognized that fac tors that increase emphasis on weight and
Page 19 shape elevate the risk of eating disorders among both women and men. 27 Service members exposure to potentially trau matic experiences and their relatively high rates of mental health disorders also may put them at increased risk of developing eating disorders. 28,29 In addition, given the increase in the annual prevalence of diag noses of clinical overweight among U.S. active component service members during 2011, 30 eating-disordered behaviors may develop as service men and women attempt to lose or control their weight. Finally, the changing demographics in the military (women are a rapidly grow ing segment of U.S. military populations) further highlight the need for continued investigation of eating disorders among service member populations. In 2014, the MSMR reported the over all and annual incidence rates of AN, BN, and EDNOS among active component service members during 2004. 31 at report documented that, through out the 10-year period, annual incidence rates declined slightly for each disorder and for all three types combined. e cur rent report updates this earlier work by describing the incidence of diagnoses of AN, BN, and other/unspecied eating disorders among active component ser vice members during 2013. METHODS e surveillance period was 1 Janu ary 2013 through 31 December 2017. e surveillance population consisted of active component service members of the U.S. Army, Navy, Air Force, or Marine Corps who served at any time during the surveil lance period. All data used to determine incident eating disorderspecic diagnoses were obtained from electronic records rou tinely maintained in the Defense Medical Surveillance System (DMSS). ese records document both hospitalizations and ambu latory encounters of active component ser vice members of the U.S. Armed Forces in xed (i.e., not deployed or at sea) medi cal facilities of the Military Health System (MHS) and civilian treatment facilities in the purchased care system. In the current study, an incident case of one of the three eating disorders of inter est (AN, BN, or other/unspecied eating disorders [OUEDs]) was dened by the presence of any qualifying ICD-9 or ICD10 diagnosis code in the 1st or 2nd diag nostic position of a hospitalization record or in the 1st diagnostic position of a record of an outpatient medical encounter. 32 Casedening diagnoses were AN (ICD-9: 307.1; ICD-10: F50.0*), BN (ICD-9: 307.51; ICD10: F50.2), and OUED (ICD-9: 307.50, 307.59; ICD-10: F50.8, F50.81, F50.89, F50.9) (Table 1) 32 e incidence date was considered the date of the rst hospitaliza tion or outpatient medical encounter that included a case-dening diagnosis of an eating disorder. For summary purposes, each aected service member could be counted as a case of only one of the three types of eating dis orders once during the surveillance period. To this end, if a service member received more than one eating disorderspecic diagnosis, AN and BN were prioritized over OUED. If an individual received diagnoses of both AN and BN, the diagnosis recorded rst was prioritized over subsequent diag noses. Individuals were classied as OUED cases only if they were not diagnosed with either AN or BN. Service members with case-dening diagnoses before the start of the surveillance period were excluded from the incidence analysis because they were not considered at risk of incident (i.e., rstever) diagnoses of eating disorders. Prevalence of the diagnoses of each of the three types of eating disorder was esti mated for each year in the 5-year surveil lance period. e numerator for prevalence calculations consisted of those individuals identied as incident cases of an eating dis order in a given year or in a previous year and who also had a healthcare encounter for any eating disorder type during that year. e denominator for prevalence cal culations consisted of the total number of active component service members who served at least 1 day of the given year. Prev alence estimates were calculated for each of the three eating disorders of interest (AN, BN, and OUED) as the number of preva lent cases per 10,000 active component ser vice members. RESULTS During the 5-year surveillance period, a total of 1,788 active component service members received incident diagnoses of eating disorders, for a crude overall inci dence rate of 2.7 cases per 10,000 personyears (p-yrs) (Table 2) Of the case-dening diagnoses, OUED and BN accounted for 46.4% and 41.8% of the total incident cases, respectively. Less than one-eighth (11.9%) of the total incident cases of eating disor der were attributable to AN. In regard to all eating disorders, more than two-thirds (67.5%) of incident cases aected females, and the overall incidence rate among women (11.9 cases per 10,000 p-yrs) was more than 11 times that among men (1.0 per 10,000 p-yrs) (Table 2) Crude over all incidence rates of AN, BN, and OUED among women were 15.7, 15.5, and 8.3 times the rates among men, respectively. e distributions of incident diagno ses of the three types of eating disorders by demographic characteristics are pre sented in Table 3 For both sexes, overall incidence rates were highest among service members in the youngest age groups (29 years or younger) and rates decreased with increasing age. Compared to their respec tive female counterparts, overall rates were highest among non-Hispanic white ser vice women (15.8 cases per 10,000 p-yrs), Marine Corps members (20.4 cases per 10,000 p-yrs), junior enlisted or junior o cers (16.0 and 11.4 cases per 10,000 p-yrs, respectively), and those in combat-specic occupations (17.2 cases per 10,000 p-yrs). Of note, the overall incidence rate of all eat ing disorders among female Marine Corps members was nearly twice that among female Army members. Among men, over all rates were highest among Hispanic ser vice members, those of other/unknown race/ethnicity and non-Hispanic white ser vice members (1.3, 1.3, and 1.1 cases per 10,000 p-yrs, respectively), compared to those in other race/ethnicity groups (Table 3) Relative to their respective male counter parts, rates of diagnoses of all eating disor ders for men were highest among Army or Marine Corps members (1.2 and 1.1 cases per 10,000 p-yrs, respectively), enlisted ser vice members (1.2 and 1.1 cases per 10,000
Page 20 TABLE 1. a Eating disorder ICD-9 code ICD-10 code Restricting type: Binge-eating/purging type: Other eating disorders Binge eating disorder c c a Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) c
Page 21 p-yrs for E1E4 and E5E9, respectively), and those in healthcare occupations (2.3 cases per 10,000 p-yrs). Crude annual incidence rates of total eating disorders increased steadily from 2.3 cases per 10,000 p-yrs in 2013 to a peak of 3.3 cases per 10,000 p-yrs in 2016 (44.7% increase), aer which rates decreased to 2.9 cases per 10,000 p-yrs in 2017 (Figure 1) Annual rates of OUED remained stable during 2013 at 0.9 cases per 10,000 p-yrs and then increased to a peak of 1.8 cases per 10,000 p-yrs in 2016. Crude rates of diagnoses of BN decreased slightly dur ing the surveillance period, from 1.2 cases per 10,000 p-years in 2013 to 0.9 cases per 10,000 p-yrs in 2017. Annual rates of AN increased slightly from 0.2 cases per 10,000 p-years in 2013 to 0.4 cases per 10,000 p-yrs in 2017. Of note, the crude annual incidence rate of OUED converged with that of BN in 2015, aer which annual rates of OUED exceeded those of BN (Figure 1) e increasing trend in crude annual rates of total eating disorders during 2013 was driven largely by increases in OUED among service members of both sexes dur ing this period (Figure 2 Figure 3) Among male service members, the annual rates of incident diagnoses of BN and AN were relatively stable during the 5-year surveil lance period. Among service women, crude annual rates of BN declined during the period, with the greatest decrease occur ring between 2015 and 2017. Rates of AN among service women increased slightly during the period (Figure 3) e general pattern of period preva lences of OUED, BN, and AN among active component service members by year during the surveillance period was broadly similar to that observed for the annual incidence rates of these eating disorder types (Figure 4) e peak prevalences for women were as follows: AN, 3.7 cases per 10,000 active component service women in 2016; BN, 10.3 cases per 10,000 in 2014; and OUED, 13.2 cases per 10,000 in 2016. For men, the peak prevalences were as follows: AN, 0.22 cases per 10,000 active component service men in 2016 and 2017; BN, 0.64 cases per 10,000 in 2016; and OUED, 1.5 cases per 10,000 in 2016 (data not shown) TABLE 2. TABLE 3. disorders, total No. Rate a No. Rate a No. Rate a No. Rate a Female Total RR, rate ratio a Females No. Rate a No. Rate a RR Total 2 Other Service Army Navy Air Force RR, rate ratio a
Page 22 enEDITORIAL COMMENTResults of the current analysis indi cate that crude annual incidence rates of total eating disorders increased by 44.7% between 2013 and 2016 followed by a slight decrease in 2017. Sex-stratied rates showed that the increasing trend in annual rates of total eating disorders during this period was driven largely by increases in OUED among service members of both sexes. Previous MSMR results showed that crude annual rates of BN were consistently higher than rates of EDNOS and AN.31 However, in the current study, the crude annual rate of OUED (category most similar to EDNOS category) converged with that of BN in 2015. From that point through 2017, crude annual rates of OUED exceeded those of BN. e increase in OUED rates observed in the current analysis is likely due, at least in part, to adjustments to the classication of eating disorders made in the ICD-10 coding system. In the previous MSMR report, all diagnoses used the ICD-9 classication system in which binge eating disorder (BED) was not specically described but was included in the EDNOS category.31 On 1 October 2015, code F50.8 (other eating disorders) was added to the ICD-10 coding system. Subsequently, on 1 October 2016, F50.8 was changed to a parent code and codes F50.81 (BED) and F50.89 (other specied eating disorder) were added to the coding system. Another important adjustment was to clarify the body weight criterion for AN. Previously, minimal normal body weight was dened as a body weight less than 85% of that expected. Currently, the criterion is signicantly low body weight in the con text of what is minimally expected for age, sex, developmental trajectory, and physical health (Table 1).6 In addition, the amenor rhea criterion under AN was removed.6 For BN, the minimum frequency of binge eat ing episodes and inappropriate compensatory behavior was reduced from twice a week to once a week.6Results of several U.S. studies indicate that BED is one of the most common eat ing disorders among both sexes.2,33,34 In a U.S. nationally representative sample, life time prevalence estimates for BED were 3.5% among women and 2.0% among men.2 e increase in crude annual inci dence rates of OUED among both sexes and their peak in 2016 broadly coincides with the shi to the ICD-10 classication system. Results of some studies suggest that there have been increases in the prev alence of total eating disorders and of AN over time.35,36 e reasons for this reported increase in prevalences is unclear, but the change in the diagnostic coding of BED and the relaxation of the criteria for AN FIGURE 1. 2.32.9 1.2 0.9 0.91.70.20.40.0 1.02.0 3.04.0 5.0 2013 2014 2015 2016 2017p 000,01 rep etar ecnedicnI -yrs Tot al eating disorders Bulimia nervosa Ot her/ uns pec ifi ed ea ting disorders Anorexia nervosa 0.30 0.830.330.270.040.12 0.00.51.0 1.5 2.0 2013 2014 2015 2016 2017p 000,01 rep etar ecnedicnI -yrs Other/unspecified eating disorders Bulimia nervosa Anorexia nervosa FIGURE 2.
Page 23 are generally cited as the major reasons for such increases in prevalence over time.12,37e overall incidence rate of AN diag noses among women documented here (1.6 cases per 10,000 p-yrs) is comparable to the range of rates cited in Hsus review (0.14 to 5.0 cases per 10,000 young women per year); however, prevalence estimates among female service members for AN and BN were much lower.38 e estimates of prevalence yielded by the current analy sis are otherwise consistent with the pub lished literature with respect to age group and sex dierences and the relative frequencies of the three diagnostic catego ries examined. Both the incidence rates and prevalence estimates in the current analysis are lower than many published estimates from military and civilian pop ulations.39 However, most of these studies used data from non-military populations and/or employed estimation methods dif ferent from those used here. Given that DoD standards preclude entrance into military service for individ uals with diagnosed eating disorders, it is plausible that the incidence and prevalence of these conditions among service mem bers are lower than in the civilian popula tion because eating disorders commonly have their onsets during adolescence (before the age of eligibility for military accession). Nevertheless, the current anal ysis documents that there are hundreds of new cases of eating disorders diagnosed each year among active component service members; there are likely many other ser vice members whose conditions went med ically undetected. e published literature documents that, at least in certain select populations, abnormal eating behaviors occur with surprising frequency among military personnel.13-23 Barlett and Mitch ells systematic review summarizes the lit erature regarding eating disorders among military and veteran men and women.39Subgroup-specic results of the cur rent analysis are consistent with ndings in the published literature on eating dis orders. As expected, based on studies in the U.S. civilian and military populations, incidence rates among women were con siderably higher than those among men. Female service members accounted for 68% of all diagnosed eating disorders, even though women account for only 15.9% of active component service members.40 Similar to results found in rep resentative samples of military service members,21,23 overall incidence rates of total eating disorders were highest among non-Hispanic white service members, those in the youngest age groups (29 years or younger), and Marine Corps members. Results of the current study must be interpreted in the context of several analysis limitations. First, the reliance on FIGURE 3. FIGURE 4. 6.2 4.0 4.0 6.0 1.1 1.8 0.0 1.0 2.0 3.0 4.05.06.07.08.09.010.0 20132014201520162017p 000,01 rep etar ecnedicnI -yrs Bulimia nervosa Other/ uns pecifi ed eating disorders Anorexia nervosa 3.34.02.2 3.1 2.01.80.47 0.77 0.01.0 2.0 3.0 4.0 5.0 6.0 2013 2014 2015 2016 2017 srebmem ecivres 000,01 rep sesac fo .oN Total eating disorders Other/uns pecified eating disor ders Bulimia nervosa Anorexia nervosa
Page 24 diagnoses from records of service mem bers medical encounters undoubtedly resulted in underestimates of the true inci dence and prevalence of eating disorders among the surveillance population. Per sons with eating disorders generally avoid seeking medical care, at least initially, either because they do not believe they have a medical problem or because they are embarrassed about their behaviors. 33 Individuals with BN or OUED (including BED) are better able to conceal their eat ing disorders because their body weights and appearances are not suggestive of dis ordered eating, and their binge eating and compensatory behaviors usually take place in private. 33 Service members with these disorders may not have the diagnoses doc umented in their medical records unless they seek assistance for or experience a serious complication of their conditions. Another limitation of the current analysis is related to the implementa tion of MHS GENESIS, the new elec tronic health record for the MHS. During 2017, medical data from sites that were using MHS GENESIS are not available in DMSS. ese sites include Naval Hospital Oak Harbor, Naval Hospital Bremerton, Air Force Medical Services Fairchild, and Madigan Army Medical Center. erefore, medical encounter and person-time data for individuals seeking care at one of these facilities during 2017 were excluded from the analysis. Among military personnel, there is reason to believe that some concealment of eating disorders is motivated by con cerns that discovery and formal diagnosis may inuence deployment, promotion, 41 or even retention. 19 Because of the emaciation that follows extreme weight loss in AN, ser vice members with this eating disorder are more likely to be noticed by their families, friends, and/or military colleagues and per suaded to seek medical attention. Among active component service members, deteri oration of not only physical appearance but also duty performance may serve as triggers for supervisors to refer persons with AN for medical evaluation. 19 However, because such medical scrutiny likely follows many months or a few years of weight loss, diag noses of AN oen are documented long aer the onset of the disorder. When AN persists, the debilitating eects have adverse impacts on the physi cal and mental health and social and occu pational activities of those aected. In addition, AN that persists or recurs is life threatening. Manos et al. cite studies that estimate crude 10-year mortality rates of 3.3%.6% and 20-year rates of 15% 20%. 19 Recognition and treatment of AN is essential. In the U.S. Armed Forces, where periodic measurement of service members height and weight is common, the detec tion of a body mass index (BMI) of less than 17.5 kg/m 2 should indicate the need for further evaluation. Because service members aected by BN or OUED usually have BMIs that are in or near the normal range, their appearances may not be indicative of their abnormal eating behaviors. Potential com plications of BN and OUED that may lead those aected to seek medical care include the consequences of overeating and vomit ing as well as overuse of laxatives, diuret ics, and enemas. An extended period of repeated, induced vomiting may result in erosion of dental enamel by the exposure of the teeth to stomach acid. 19 Although mortality is a much less frequent outcome of BN and OUED than AN, purging and metabolic abnormalities may be associ ated with potentially fatal events such as esophageal tears, gastric ruptures, and car diac arrhythmias. 42 Because individuals with eating disorders are at elevated risk of psychiatric comorbidity, 1 it is important for military healthcare providers to be vig ilant for eating disorder symptoms among service members aected by mental health disorders, especially among those in the accession phase of military service. 43 Results of the current study suggest that service members likely experience eating disorders at rates that are compara ble to rates in the general population, and that rates of these disorders are potentially rising among military members. ese ndings underscore the need for appro priate prevention and treatment eorts in this population. At stake are the health, well-being, and military operational eec tiveness of aected service members and their units. REFERENCES Arch Womens Ment Health 2. Biol Psychiatry. Clin Psychol Rev Psychol Med Int J Eat Disord Diagnostic and Statis tical Manual of Mental Disorders, Fifth Edition (DSM-5) Psychosom Med. Curr Psychiatry Rep. Med Gen Med. Biol Psychiatry N Engl J Med. Shanghai Arch Psychiatry. Mil Med. Mil Med Mil Med Med Sci Sports Exerc cadets. Mil Med. Mil Med.
Page 25 Recruit Medi cine Textbooks of Military Medicine Mil Med. Eat Disord. 22. dets. Mil Med. hort. Amer J Epidemiol. Ac Mil Med Int J Eat Disord Mil Med Int J Eat Disord MSMR MSMR J Abnorm Psychol Int J Eat Disord PloS One. disorders. Int J Eating Disord. J Eat Disord. Psychiatr Clin North Am Int J Eat Disord. tary. Mil Med N Engl J Med. Mil Med.
Page 26 he 2017 inuenza season has been a topic of interest in the media and among the general public due to concerns about the protective nature of the 2017 inuenza vaccine. During the Southern Hemispheres winter inu enza season in mid-2017, Australias over all inuenza vaccine eectiveness (VE) was surprisingly low at 33% (95% CI, 17% 46%). 1 More specically, Australia reported an inuenza A(H3) VE of 10% (95% CI, -16%%), which was not statistically sig nicantly dierent from zero. 1 ese nd ings prompted concerns about the prospect of a similarly low VE during the subsequent inuenza season in the Northern Hemi sphere, as Australia and the U.S. selected identical vaccine strains. e Department of Defense (DoD) conducts VE analy ses to determine the extent of matching between the recommended seasonal vac cine and the circulating strain. is article reports the results of DoD VE mid-season estimates determined by the Armed Forces Health Surveillance Branch (AFHSB) Air Force (AFHSB-AF) satellite at the U.S. Air Force School of Aerospace Medicine; Naval Health Research Center (NHRC); and the AFHSB. METHODS e AFHSB-AF satellite branch is a sentinel site-based program that requests weekly submissions of six to 10 specimens accompanied by a completed question naire from each site. Vaccination status was veried through immunization records obtained from the Air Force Complete Immunization Tracking Application, medi cal records from the Aeromedical Services Information Management System, or selfreported data from the questionnaire. Indi viduals were considered to be vaccinated if they were vaccinated at least 14 days prior to symptom onset. ose who were vacci nated less than 14 days prior to symptom onset were excluded from the study. NHRCs population included civil ians who sought care at outpatient clinics near the U.S.Mexico border through the febrile respiratory illness program.Vaccina tion status was obtained through medical record reviews and self-report, if available. 2 NHRC classied cases and controls to have been vaccinated if symptom onset started 14 days aer receiving the vaccine. 2 AFHSBs VE study used data obtained via the Defense Medical Surveillance Sys tem and Navy and Marine Corps Public Health Center. e high vaccination rate is attributable to the fact that annual inu enza vaccination is required for service members. 2 All three VE estimates were derived using a test-negative case-control study design although each organization utilized dierent study populations (i.e., AFHSBAF satellite, DoD dependent data; NHRC, civilians near the U.S.Mexico border; AFHSB, active component service mem ber data). All studies calculated crude and adjusted VE using odds ratios (ORs) and 95% CIs obtained from multivariable logistic regression models (Table) Statis tical data analyses were performed using SAS version 9.4 (2013, SAS Institute, Cary, NC). VE was calculated as (1OR) 100. AFHSB-AFs adjustment variables were age group, time period, and geographic region. NHRCs only adjustment variable was age group. AFHSBs adjustment variables were age group, sex, month of illness, and 5-year Brief Report Department of Defense Midseason Vaccine Effectiveness Estimates for the 2017 2018 Influenza Season Lisa Shoubaki, MPH; Angelia A. Eick-Cost, PhD, ScM; Anthony W. Hawksworth, BS; Zheng Hu, MS; LeeAnne Lynch, MPH; Christopher A. Myers, PhD; Susan Federinko, MD, MPH (Lt Col, USAF) vaccination status. For summary purposes, vaccine eects were considered statistically signicant if 95% CIs around point esti mates of VE did not include zero. Inactivated inuenza vaccine was the only vaccine type analyzed, because the live, attenuated inuenza vaccine was not rec ommended or used during the 2017 season. Cases were laboratory-conrmed inuenza positives and controls were inu enza test negatives. Inuenza positives from the AFHSB-AF satellite and NHRC were conrmed through reverse transcrip tion polymerase chain reaction (RT-PCR) and/or viral culture, while AFHSB used RT-PCR and/or viral culture as well as pos itive rapid tests, excluding individuals with rapid test negatives. RESULTS From 1 October 2017 through 10 Feb ruary 2018, the AFHSB-AFs VE study included 1,160 cases and 1,383 controls, with 36% and 47% having been vaccinated, respectively. Overall, the adjusted VE was 51% (95% CI, 41%%). e adjusted VE for inuenza A(H3N2) was low at 37% (95% CI, 22%%) (Figure) Inuenza A(H1N1) pdm09 and inuenza B had higher adjusted VE estimates of 79% (95% CI, 67%%) and 60% (95% CI, 49%%), respectively (Figure) Adjusted VE estimates were simi lar among children (aged 2 years) and adults (data not shown) From 13 November 2017 through 8 January 2018, the NHRCs VE study included 201 cases and 114 controls, with 13% and 24% having been vaccinated, respectively. For the NHRCs study, the overall adjusted VE was 55% (95% CI,
Page 27 17%%). For inuenza A(H3N2), VE was 52% (95% CI, 9%%). For inuenza B, VE was 63% but not statistically signi cant (95% CI, -5%%) (Figure) From 1 December 2017 through 10 February 2018, the AFHSBs study included 2,926 cases and 2,557 controls, with 89% and 90% having been vaccinated, respec tively. Aer adjustment, VE for active com ponent service members was statistically signicant at 19% (95% CI, 3%%). For inuenza A(H3N2) and inuenza B, the adjusted VE estimates were 27% (95% CI, -9%%) and 25% (95% CI, -8%%), respectively (Figure) ; neither adjusted VE estimate was statistically signicant. EDITORIAL COMMENT Overall, adjusted VE estimates for DoD studies were moderately protective for the dependent population. e AFHSB-AF sat ellites overall adjusted VE was statistically signicant and conferred moderate to high protection; NHRCs adjusted VE was statis tically signicant overall and was moder ately protective for inuenza A(H3N2); and AFHSBs active component adjusted VE was statistically signicant overall and provided some protection. All of the VE studies had limitations. For example, specimens were obtained from those seeking care at a medical treatment facility or meeting the inuenza-like illness case denition; therefore, less severe cases that did not seek medical attention were not included in the analyses. Individuals included in the DoD studies were younger than the general population, so VE could not be analyzed for older, higher-risk pop ulations. Active component members are a highly immunized population, which may have a negative impact on VE estimates due to methodologic validity (i.e., limited unvac cinated controls) and biologic eects (i.e., repeated vaccination). Lower sample size could have contributed to the reduction of statistical power in some DoD analyses. e Centers for Disease Control and Prevention (CDC) reported lower VE at 36% (95% CI, 27%%), compared with all DoD studies with a dependent popu lation. e CDCs adjusted VE for inu enza A(H3N2) was low at 25% (95% CI, 13%%), 67% (95% CI, 54%%) for inuenza A(H1N1)pdm09, and 42% (95% CI, 25%%) for inuenza B. 3 Midseason results for the CDC did not closely match DoD midseason VE estimates. is dier ence in VE estimates may be due, at least in part, to dierences in the types of inu enza vaccine used in DoD and in civilian populations. More than half of the inu enza vaccine purchased and administered by the DoD was derived from cell culture propagation rather than from egg propa gation. 3 A rapid decline of VE for the vac cine component inuenza A(H3N2) that was egg-propagated has been seen in the past few years. 4 Zost et al. reported that the current circulating inuenza A(H3N2) viruses possess a new glycosylation site in antigenic site B of the hemagglutinin, and that the current egg-adapted A(H3N2) component of the vaccine does not have this mutation, which is hypothesized to TABLE. Population Cases Controls a No. of cases No. of Overall 2 Overall Overall a
Page 28 diminish antigenicity. 5 Additional research is needed to assess whether VE against cir culating A(H3N2) viruses varies by vaccine propagation type. Author aliations: Defense Health Agency/ Armed Forces Health Surveillance Branch Air Force Satellite, U.S. Air Force School of Aero space Medicine, Wright-Patterson AFB, OH (Ms. Shoubaki, Lt Col Federinko); Armed Forces Health Surveillance Branch, Silver Spring, MD (Dr. Eick-Cost, Ms. Hu, Ms. Lynch); Naval Health Research Center, San Diego, CA (Dr. Myers, Mr. Hawksworth). Acknowledgments: e authors thank the DoD Global Respiratory Pathogen Surveil lance Program and its sentinel site partners, the Navy and Marine Corps Public Health Center, and the Centers for Disease Con trol and Prevention Border Infectious Dis ease Surveillance Program in San Diego and Imperial Counties, CA, which collected samples and case data from participating outpatient clinics. Disclaimer: Dr. Myers is an employee of the U.S. Government. is work was prepared as part of his ocial duties. Title 17, U.S.C. provides that copyright protection under this title is not available for any work of the U.S. Government. Title 17, U.S.C. denes a U.S. Government work as work prepared by a military service member or employee of the U.S. Government as part of that persons o cial duties. Report No. 18-XX was supported by Armed Forces Health Surveillance Branch under work unit no. 60805. e views expressed in this article are those of the authors and do not necessarily reect the ocial policy or posi tion of the Department of the Navy, Depart ment of Defense, or the U.S. Government. REFERENCES Euro Surveill 2. MSMR MMWR Morb Mortal Wkly Rep PLoS Pathog Proc Natl Acad Sci USA FIGURE. 200 150 10 0 50 0 5 0 100 150 VE ( % ) Ov e r a ll A FH S B A F D ep en de nts ( 1 160; 1 383) Flu t y pe s t udy s i t e pop ul a t i on ( no of cases; no of contr ol s) Ov e r a ll A FH SB A c t iv e c o m ponent s e rvic e m e m ber s ( 2 926; 2 557) A ( H 3N 2) A FH S B A F D ep en de nt s ( 610; 1 383) A ( H 3N 2) NHRC B o r der c iv il ian s ( 156; 114) I n f lue n z a B A FH S B A F D ep en de nts ( 39 0; 1,383) 7 9 % ( 6 786) 6 0 % ( 4970) 2 7 % ( 950) 5 2 % ( 975) 37% ( 2 249) 1 9 % ( 333) A dj VE ( 95% C I ) I n f lue n z a B NHRC B o r der c iv il ian s ( 41; 114) A ( H3N2) A FH SB Act iv e c om po ne nt s er v ic e m e m bers ( 30 1; 2, 55 7) A ( H1N1) A FH S B A F D ep en de nts ( 15 3; 1,383) 6 3 % ( -587) 2 5 % ( -848) I nf luenz a B A FH SB A c t iv e c om po ne nt s er v ic e m em bers ( 38 3; 2, 55 7) 5 1 % ( 4 1 59) Ov e r a ll NHRC B o r der c iv il ian s ( 201; 114) 5 5 % ( 1 775)
Page 29 MSMRs Invitation to ReadersMedical Surveillance Monthly Report (MSMR) invites readers to submit topics for consideration as the basis for future MSMR reports. e MSMR editorial sta will review suggested topics for feasibility and compatibility with the journals health surveillance goals. As is the case with most of the analyses and reports produced by Armed Forces Health Surveillance Branch sta, studies that would take advantage of the healthcare and personnel data contained in the Defense Medical Surveillance System (DMSS) would be the most plausible types. For each promising topic, Armed Forces Health Surveillance Branch sta members will design and carry out the data analysis, interpret the results, and write a manuscript to report on the study. is invitation represents a willingness to consider good ideas from anyone who shares the MSMRs objective to publish evidence-based reports on subjects relevant to the health, safety, and well-being of military service members and other beneciaries of the Military Health System (MHS). In addition, the MSMR encourages the submission for publication of reports on evidence-based estimates of the incidence, distribution, impact, or trends of illness and injuries among members of the U.S. Armed Forces and other beneciaries of the MHS. Information about manu script submissions is available at www.health.mil/MSMRInstructions. Please email your article ideas and suggestions to the MSMR Editor at firstname.lastname@example.org. Letter to the Editorothe Editor : As both a former member of the Armed Forces Epidemiological Board and the Defense Health Board and as an investiga tor who has studied the prevalence of hepa titis C virus (HCV) among recruits, I was interested to read the brief report by Taylor and colleagues in the December 2017 issue of the MSMR.1 It was a little surprising to read the authors statement that . . the prevalence among military recruits accessioning into the U.S. Air Force has not been described. May I respectfully remind the authors that in 2000, a manuscript titled -Year Fol low-up of Hepatitis C Virus Infection in Healthy Young Adults was published in the Annals of Internal Medicine ? e manuscript reported studies of serum samples for hepatitis C antibody from more than 8,000 military recruits at the Fort Francis E. War ren Air Force Base obtained between 1948 and 1954.2 ose authors described 0.2% of the tested recruits as having positive HCV studies by ELISA and by recombinant immunoblot assay. Because these sera were drawn upon entrance into the Air Force, one could not determine how many of this population subsequently contracted HCV either while on active duty or aer their military career. However, of the 17 recruits in the latter report with a positive antibody test for HCV, only one (5.9%) had died of liver disease 42 years aer the original phlebotomy. Such data are required from larger and more recent cohorts to complete this important natural history evaluation even if there are newer (and expensive) therapeutic approaches to individuals with hepatitis C infections. e reported cohort represents an opportunity for the authors of the brief report to identify and to carry out a mean ingful comparison between the two cohorts and also to plan/attempt long-term followup for their recently identied cohort as the resulting data would have both prac tical and public health implications for the Services, and especially for Veterans Administration healthcare programs. Data from identied cohorts of military person nel can provide important information for the future. is aspect was recently empha sized in a special supplement of Military Medicine in October 2015 and is important for more than only hepatitis infections.3 I hope that the authors can take these factors into consideration. Edward L. Kaplan, MD Author aliation: Professor Emeritus, Department of Pediatrics, University of Min nesota Medical School, Minneapolis, MN enREFERENCES MSMR. 2. Ann Intern Med. Military Medicine Mil Med.
MEDICAL SURVEILLANCE MONTH LY REPORT MSMR, in continuous publication since 1995, is produced by the Armed Forces Health Surveillance Branch (AFHSB). e MSMR provides evidence-based estimates of the incidence, distribution, impact, and trends of illness and injuries among U.S. military members and associated populations. Most reports in the MSMR are based on summaries of medical administrative data that are routinely provided to the AFHSB and integrated into the Defense Medical Surveillance System for health surveillance purposes. Archive: P ast issues of th e MSMR a re available as downloadable PDF les a t ww w. health.mil/MSMRArchives. Online Subscriptions: Submit subscription requests at www.health.mil/MSMRSubscribe. Editorial Inquiries: Call (301) 319-3240 or send email to: dha.ncr.health-surv.mbx. email@example.com. Instructions for A uthors: Information about article submissions is provided a t www. health.mil/MSMRInstructions. Al l materia l in th e MSMR i s in th e pub lic doma in an d ma y b e use d an d reprinted without permission. Citation formats are available at ww w.health.mil/MSMR. Opinions and assertions expressed in the MSMR should not be construed as reecting ocial views, policies, or positions of the Department of Defense or the United States Government. Follow us: www.facebook.com/AFHSBPAGE http://twitter.com/AFHSBPAGE ISSN 2158-0111 (print) ISSN 2152-8217 (online) Chief, Armed Forces Health Surveillance Branch COL Douglas A. Badzik, MD, MPH (USA) Editor Francis L. ODonnell, MD, MPH Contributing Editors Leslie L. Clark, PhD, MS Shauna Stahlman, PhD, MPH Writer/Editor Valerie F. Williams, MA, MS Managing/Production Editor Elizabeth J. Lohr, MA Data Analysis Stephen B. Taubman, PhD Saixia Ying, PhD Layout/Design Darrell Olson Editorial Oversight Col Dana J. Dane, DVM, MPH (USAF) COL P. Ann Loveless, MD, MS (USA) CDR Shawn S. Clausen, MD, MPH (USN) Mark V. Rubertone, MD, MPH