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OUTCOMES OF BEHAVIORAL WEIGHT LOSS TREATMENT: A COMPARISON OF
MIDDLE-AGED AND OLDER ADULTS
LAUREN MARI GIBBONS
A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
UNIVERSITY OF FLORIDA
O 2007 Lauren Mari Gibbons
I would like to acknowledge many people for their contributions to this proj ect. I would
especially like to thank my advisor and mentor, Dr. Michael Perri, for his guidance, insight, and
support over the past two years. I would also like to thank the staff and fellow graduate students
of the Treatment of Obesity in Underserved Rural Settings (TOURS) lab, who have been
invaluable sources of knowledge and friendship.
Finally, I am forever indebted to my family and friends for their unwavering support and
encouragement. Eric Rossen is deserving of special thanks for reviewing and revising this
TABLE OF CONTENTS
ACKNOWLEDGMENTS .............. ...............3.....
LIST OF TABLES ............_...... ...............6...
LIST OF FIGURES .............. ...............7.....
AB S TRAC T ......_ ................. ............_........8
1 INTRODUCTION ................. ...............9.......... ......
Obesity ................ ...............10.......... ......
Preval ence ................. ...............10.................
Aging Trends ............... .. ... .. ... .... .......... .............1
Associated Comorbidities and Risk Factors ............................. ............... 12.....
Associated Risk Factors and Comorbidities over the Lifespan ................. ................. .12
Psychosocial Consequences of Obesity ................. ...............13................
Economic Consequences of Obesity .............. .....................14
Obesity and M ortality ................. ...............14................
Behavioral Weight Loss Treatment ................. ...............16................
Weight Loss: Beneficial Health Outcomes .............. ...............16....
Hypertension .............. ...............16....
Diabetes ................... .... ............ ................ .............1
Health-Related Quality of Life (HrQoL) .............. ...............19....
Adherence to Diet and Activity Recommendations ................. ........... ...........20
Weight Loss: Negative Outcomes ................ ...............21................
Specific Aims and Hypotheses ................ ...............23................
2 MATERIALS AND METHODS .............. ...............25....
Research Methods and Procedures ................ ...............25................
Participants .............. ...............25....
Procedure ................. ........... ...............26.......
The TOURS Intervention .............. ...............27....
M measures ................. ............ ...............28.......
Design and Statistical Analyses ................. ...............31................
Primary Aims............... ...............32..
Secondary Aims............... ...............33..
3 RE SULT S .............. ...............3 5....
Demographic Characteristics by Age ................ ...............35........... ...
Pretreatment Metabolic Risk Factors by Age ................. ...............35......___ ..
Primary Aims................ ...............36.
Within-Group Analyses............... ...............36
Weight change ................. ...............36.................
Metabolic risk factors ................. ...............36........... ....
Equivalence Testing .............. ...............37....
Weight change ................. ...............37.................
Adverse events .............. ...............38....
Secondary Aims............... ...............39..
Dietary Intake .............. ...............3 9....
Adherence ................. ...............40.................
Physical Fitness ............... ..... ...............41.
Health-Related Quality of Life ................. ...............42................
Physical Functioning ............... .. ........... ........ ...............42.......
Role Limitations due to Physical Health Problems............... ...............43
Social Functioning............... ..............4
Bodily Pain .................. ...............44.................
General M ental Health .............. ... ......... ..............4
Role Limitations due to Emotional Problems .............. ...............44....
V itality .................. ........... ...............44.......
General Health Perceptions ................. ......... ...............45......
4 DI SCUS SSION ............. ...... .__ ...............56..
Primary Aims............... ...............56..
Secondary Aims.................. ...............58
Dietary Intake and Adherence ............. ...... .__ ...............58..
Physical Fitness ............... ..... ...............59.
Health-Related Quality of Life ............. ...... .__ ...............60..
Lim stations ............. ...... ._ ...............61...
Clinical Implications............... ..............6
LIST OF REFERENCES ............. ...... .__ ...............65..
BIOGRAPHICAL SKETCH .............. ...............77....
LIST OF TABLES
2-1 Baseline demographic characteristics of the sample of 298 women ........._._... ...............34
3-1 Baseline demographic characteristics of older and middle-aged participants ..................46
3-2 Pretreatment metabolic risk factors of older and middle-aged participants ......................46
3-3 Physical functioning by age, adjusted for race/ethnicity (PP) .............. .....................4
3-4 Role limitations due to physical health problems by age, adjusted for race/ethnicity
(PP ) .............. ...............47~~~~
3-5 Vitality by age, adjusted for race/ethnicity (PP) ................. ...............47..............
LIST OF FIGURES
3-1 Within-group changes in weight in older participants, adjusted for race/ethnicity (PP,
n = 45) ................ ...............48................
3-2 Within-group changes in weight in older participants, adjusted for race/ethnicity
(ITT, n = 56) ................. ...............48.......... .....
3-3 Within-group changes in risk factors in older participants, adjusted for race/ethnicity
(PP, n = 45)............... ...............49..
3-4 Within-group changes in risk factors in older participants, adjusted for race/ethnicity
(ITT, n = 56) .............. ...............50....
3-6 Daily caloric intake by age, adjusted for race/ethnicity (PP, n = 45) ............... .... ........._..52
3-7 Daily caloric intake by age, adjusted for race/ethnicity (ITT, n = 56) .............. ...............52
3-8 Physical fitness by age, adjusted for race/ethnicity (PP, n = 45) .............. ...................53
3-9 Physical fitness by age, adjusted for race/ethnicity (ITT, n = 56)............... ..................53
3-10 Physical functioning by age, adjusted for race/ethnicity (PP) ................... ...............5
3-11 Role limitations due to physical health problems by age, adjusted for race/ethnicity
(PP ) .............. ...............54~~~~
3-12 Vitality by age, adjusted for race/ethnicity (PP) ......._.__ ... .... .__ ............... .....5
Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science
OUTCOMES OF BEHAVIORAL WEIGHT LOSS TREATMENT: A COMPARISON OF
MIDDLE-AGED AND OLDER ADULTS
Lauren Mari Gibbons
Chair: Michael G. Perri
Controversy exists regarding whether weight loss treatment is advisable for older obese
adults. Epidemiological studies have found that weight loss in elderly individuals is associated
with adverse health outcomes. However, weight loss may be a consequence, not a cause, of
disease and declining health. Further, much research substantiates the numerous positive health
outcomes resulting from weight loss in obese individuals, though research on older populations
is lacking. Thus, we sought to examine the response of elderly, obese women to a lifestyle
treatment for weight loss and to compare outcomes to those of a group of middle-aged women.
All participants completed a 6-month lifestyle intervention for weight loss followed by 1
year of extended care. Results indicated that elderly women lost equivalent amounts of weight as
compared to middle-aged women (M~= 9.5%, SD = 5.5% and M~= 10%, SD = 5.8%,
respectively) at 6 months. Additionally, elderly women experienced significant improvements in
blood pressure, glycemic control, and inflammation. The proportion of older women reporting a
musculoskeletal adverse event during active treatment (23%) was neither significantly different
than, nor equivalent to, the proportion of middle-aged women reporting an injury (18%).
Additional studies are needed to evaluate potential negative outcomes of weight loss treatment in
Obesity is associated with numerous health problems including diabetes, hypertension,
dyslipidemia, osteoarthritis (Must et al., 1999), and all-cause mortality (Manson et al., 1995).
Additionally, the prevalence and severity of many obesity-related health conditions and
metabolic risk factors increases with age (Villareal, Apovian, Kushner, & Klein, 2005).
However, excess weight in elderly persons (65 years and older) may also protect against bone
loss, osteoporosis, and hip fracture (Felson, Zhang, Hannan, & Anderson, 1993; Rossner, 2001).
Further, several epidemiological studies have demonstrated that weight loss in older adults is
related to increased mortality, disability, functional limitation and institutionalization (Thomas,
2005; Wallace & Schwartz, 2002). These studies, however, have typically failed to control for a
number of confounding variables such as weight status prior to weight loss, intentionality of
weight loss, underlying disease or pathology, and smoking status. Thus, at present, it remains
unclear whether intentional weight loss in older, obese adults can produce significant
improvements in health, and whether these benefits outweigh potential risks of weight loss
For obese middle-aged and young adults, the benefits of behavioral weight loss treatment
generally outweigh potential risks. Lifestyle interventions are typically recommended as the first
line of treatment due to their minimal risk and the significant improvements in health that even
moderate weight losses can produce (Wadden & Osei, 2002). However, it is largely unknown
whether obese, older adults experience a similar profile of positive and negative effects from
behavioral weight loss interventions, as the maj ority of research has been conducted using
younger and middle-aged adults (Villareal et al., 2005). At present, few studies have examined
the effects of behavioral weight loss treatment in older adults (Rossner, 2001; Zamboni, Mazzali,
Zoico, & Harris, 2005), both in terms of potential improvements in health parameters as well as
adverse events. Thus, the current study examines both the beneficial and adverse consequences
of weight loss treatment in older adults and whether these effects are comparable to those
experienced by middle-aged adults.
According to reports from the National Health and Nutrition Examination Survey
(NHANES), the prevalence of obesity in the United States had increased at an alarming rate over
the past several decades, from 13.4% in 1960-1962 to 30.9% in 1999-2000 (Flegal, Carroll,
Kuczmarski, & Johnson, 1998). Current estimates from the most recent NHANES data suggest
that overall, 32.2% of adults in the United States are obese (Ogden et al., 2006). While the
obesity epidemic has impacted virtually all segments of the population, certain sub-groups are
disproportionately affected. Women, ethnic and racial minorities, those of low socio-economic
status, and those who live in rural counties all display higher rates of obesity than the overall
population (Flegal, Carroll, Ogden, & Johnson, 2002; Hedley et al., 2004; Sobal, Troiano, &
Prevalence of obesity also differs by age. Data from the 2003-2004 NHANES suggest that
obesity is less prevalent among younger adults (age 20 to 39) than in middle aged adults (40 to
59 years) or adults 60 and older. While 28.5% of younger adults were obese, 36.8% of middle-
aged adults and 31.0% of adults over 60 were obese (Ogden et al., 2006). Women between 40
and 59 years of age were nearly three times more likely to be obese than women 20 to 39 years
of age (OR: 2.95, 95% CI: 2.55-3.42), as were women between 60 and 79 (OR: 2.95, 95% CI:
2.57-3.39). However, women 80 years and above were not at greater risk for obesity than
women under 40 (OR: 1.20, 95%CI 0.93-1.56; Ogden et al., 2006). These data suggests that
although the highest rates of obesity are seen among middle-aged adults, obesity is a significant
problem among older adults as well, affecting nearly one-third of individuals over 60 years of
age. Nonetheless, the bulk of research related to obesity and weight loss has typically excluded
persons over 65 years of age.
Although the NHANES data are cross-sectional and therefore not indicative of age-related
weight change, several large longitudinal studies have described a fairly robust pattern of weight
gain over time. Epidemiological studies indicate that body weight and body mass index (BMI)
tends to increase gradually throughout adult life, peaking between 50 and 59 years of age and
remaining stable or declining slightly after age 60 (Grinker, Tucker, Vokonas, & Rush, 1995).
Other data from longitudinal studies suggest that mean body weight remains relatively stable
after age 60 (Fogelhorn, Kujala, Kapiro, & Sarna, 2000; Grinker et al., 1995; Rissanen,
Heliovaara, & Aromaa, 1988). However, cohort effects and premature mortality in obese
younger and middle-aged adults might lead to a general underestimate of mean BMI for the
population of older adults.
Although weight may remain stable or even decline slightly after age 60, body
composition changes continually with age. There is a considerable reduction in lean body mass
and an increase in fat mass after age 20 (Beaufrere & Morio, 2000). After age 30, lean body
mass decreases by approximately 0.3 kg per year (Baumgartner, Heymsfield, & Roche, 1995).
Additionally, there is a relative increase in intra-abdominal fat with age, which is associated with
increased risk of insulin resistance and metabolic diseases (Beaufrere & Morio, 2000). Thus,
weight stability in old age may mask substantive changes in body composition. These changes
in body composition, specifically an increase in intra-abdominal fat and a reduction in lean body
mass, may place older adults at greater risk for metabolic disorders as well as injury and
Associated Comorbidities and Risk Factors
Evidence supporting the link between obesity and increased morbidity and mortality
continues to accrue. Obesity correlates with a heightened risk of several diseases and health
conditions such as hypertension (Brown et al., 2000; Mokdad et al., 2003), dyslipidemia (Brown
et al., 2000), type 2 diabetes (Colditz, Willet, Rotnitsky, & Manson, 1995; National Task Force
on the Prevention and Treatment of Obesity, 2000), coronary heart or cardiovascular disease
(Gregg et al., 2005; Manson et al., 1990), stroke (Cooper et al., 2000), osteoarthritis (Hart &
Spector, 1993), sleep apnea and other respiratory problems (Vgontzas et al., 1994), as well as
endometrial, breast, prostate, pancreatic and colon cancers (Dumitrescu & Cotarla, 2005;
Freedland & Aronson, 2005; Garfinkel, 1985; Lowenfels, Sullivan, Fiorianti, & Maisonnueve,
Associated Risk Factors and Comorbidities over the Lifespan
The prevalence of most obesity-related comorbidities and metabolic risk factors (e.g.,
hypertension, diabetes, cardiovascular disease, osteoarthritis) increases with age (Villareal,
Banks, Siener, Sinacore, & Klein, 2004; Villareal et al., 2005; Klein et al., 2004). Nearly 90% of
men and women over 50 years of age will develop hypertension at some point in their lifetime
(Vasan et al., 2002). The odds for developing the Metabolic Syndrome, a constellation of
weight-related risk factors including excess abdominal fat, insulin-resistance, dyslipidemia and
hypertension, are 4.9 and 5.8 times higher for women and men over 65 years of age,
respectively, as compared to young adults (Park et al., 2003). Fasting blood glucose increases
with age, by approximately one to two mg/dL each decade (Kahn, Schwartz, Porte, & Abrass,
1991). Higher incidences of type 2 diabetes and glucose intolerance have historically been
attributed solely to aging, but are likely compounded by a greater degree of abdominal obesity
and physical inactivity in older adults (Villareal et al., 2005). Obesity has been implicated in the
pathogenesis of arthritis, the leading cause of physical disability in older adults (Villareal et al.,
2005). By age 65, over two-thirds of women suffer from osteoarthritis, as well as 58% of men
(Cicuttini & Spector, 1995). Obesity in older adults is also etiologically related to urinary
incontinence (Mommsen & Foldspang, 1994) and cataracts (Glynn, Christen, Manson,
Bernheimer, & Hennekens, 1995).
The link between obesity and related diseases and risk factors is not wholly consistent
across the lifespan. Longitudinal studies have found that obesity is related to heightened risk of
coronary heart disease, fatal and nonfatal myocardial infarction, and cardiovascular disease
mortality in older men, but not older women (Dey & Lissner, 2003; Stevens et al., 1998).
Additionally, obesity has been implicated as a protective factor against bone loss in older adults
(Rossner, 2001), as well as contributing to reduced risk of osteoporosis and hip fracture (Felson
et al., 1993).
In sum, the constellation of weight-related diseases and risk factors is more severe in older
adults, suggesting that they may be in great need of weight loss treatment to ameliorate some of
these negative health risks. However, excess weight in older adults has been linked to certain
positive health benefits such as reduced bone loss and risk of hip fractures. Thus, additional
research is needed to determine whether the benefits of weight loss treatment outweigh potential
risks in older adults.
Psychosocial Consequences of Obesity
Obese individuals report higher levels of depression, anxiety and lower quality-of-life than
their normal weight counterparts (Fontaine & Barofsky, 2001; Wadden, Womble, Stunkard, &
Anderson, 2002). Aging is related to a decline in physical functioning, largely due to reduced
muscle mass and increased joint disease and arthritis (Ensrud et al., 1994; Jordan et al., 1996).
Obesity appears to exacerbate this age-related decline in physical functioning, and has been
implicated as a cause of frailty in older adults (Blaum, Xue, Michelon, Semba, & Fried, 2005).
Additionally, obesity has been associated with significant impairment in health-related quality of
life in older individuals (Villareal et al., 2004).
Economic Consequences of Obesity
Obesity and related comorbidities impose a substantial financial burden on the U.S.,
approximately 10% of the nation' s healthcare expenditures are related to obesity, representing
nearly 80 billion dollars each year (Finkelstein, Fiebelkorn, & Wang, 2003; Thompson,
Edelsberg, Colditz, Bird, & Oster, 1999). The costs associated with obesity rise with increasing
BMI, and the relative rise in cost is substantially greater with age (Wee et al., 2005). In other
words, aging compounds the relationship between health care costs and obesity, perhaps due to
the greater severity and prevalence of weight-related health conditions with age. Adults over 65
years of age, though comprising only 15% of the population, account for more than one-third of
all healthcare expenditures in the U.S. (Spillman & Lubitz, 2000). This number is expected to
rise due to increased longevity and the growing number of elderly persons in the population
(Spillman & Lubitz, 2000). The expanding prevalence of obesity in elderly populations could
also exacerbate these rising healthcare costs. Whether weight loss treatment for older adults can
provide a significant cost offset remains unknown.
Obesity and Mortality
Obesity is related to marked reductions in life expectancy (Fontaine, Redden, Wang,
Westfall, & Allison, 2003). The number of excess annual deaths attributable to obesity range
from 111,909 (Flegal, Graubard, Williamson, & Gail, 2005) to 414,000 (Mokdad, Marks, Stroup,
& Gerberding, 2004). Although smoking has been found to be responsible for the greatest level
of mortality, accounting for 18. 1% of total US deaths in 2000, poor diet and physical inactivity
were responsible for 16.6% of deaths in 2000, and may soon overtake tobacco as the leading
cause of death in the U.S. (Mokdad et al., 2004). Results from the Framingham Heart Study
demonstrated that adults of normal weight lived six to seven years longer than adults who were
obese at age 40 (Peeters et al., 2003). Further, reviews of data from the National Health and
Nutrition Examination Surveys found that extreme obesity (BMI above 45 kg/m2) in individuals
between 20 and 30 years of age was associated with a minimum of eight years of life lost for
women and 13 years of life lost for men (Fontaine et al.,2003).
Epidemiological research suggests that mortality risk begins to increase with BMIs over 25
kg/m2, and climbs precipitously with BMIs over 30 kg/m2 (Troiano, Frongillo, Sobal, &
Levitsky, 1996). For most age groups, the lowest risk of mortality occurs for individuals in the
normal body weight range (20 to 24.9 kg/m2), With obese persons standing a 50% to 100%
greater risk of all-cause mortality than their normal weight counterparts (Troiano et al., 1996).
Underweight is also associated with greater mortality risk, creating a U or inverse J-shaped curve
between BMI and mortality (Calle, Thun, Petrelli, Rodriguez, & Heath, 1999; World Health
Obesity and mortality across the lifespan. Although the relationship between body mass
index and mortality is well established, some research suggests that the nature and strength of
this relationship is not uniform across the lifespan. The relationship between high BMIs and
mortality weakens over the lifespan (Stevens et al., 1998), such that BMIs in the overweight
range are actually associated with the lowest risk of mortality in older adults (Durazo-Arvizu,
McGee, Cooper, Liao, & Luke, 1998; Heiat, Vaccarino, & Krumholz, 2001). These
epidemiological studies have often failed to control for confounding effects of smoking or
underlying disease pathology which could contribute to lower body weights in older adulthood
(Losonczy et al., 1995). Additionally, a survival bias may play a role, whereby individuals
sensitive to the negative health consequences of obesity may have died at younger ages, resulting
in older age cohorts that are more resistant to obesity-related comorbidities (National Heart,
Lung, and Blood Institute, 1998). Thus, at present, it remains unclear whether excess weight
increases mortality risk in older adults, and subsequently, whether weight loss treatment should
be recommended to older persons.
Behavioral Weight Loss Treatment
Behavioral or lifestyle weight loss treatments seek to modify eating and activity patterns
through a variety of cognitive-behavioral strategies (Wadden, Crerand, & Brock, 2005). These
strategies typically include self-monitoring through the use of daily food and activity records,
setting calorie and activity goals (e.g., a deficit of 500-1000 kcal/day combined with 30 min/day
of moderate physical activity), performance feedback, reinforcement, stimulus control, and
cognitive restructuring (Wadden & Foster, 1992). Reviews of randomized trials demonstrate that
lifestyle interventions, typically delivered in 15 to 24 weekly group sessions, produce an average
weight loss of 8.5 kg (Jeffery et al., 2000; Perri & Fuller, 1995; Wadden et al., 2005), or
approximately 5-10% of initial body weight, post-treatment (Perri & Corsica, 2002; Wilson,
1994; Wing, 2002). Reductions of this magnitude can have beneficial effects on a variety of
weight-related health conditions and risk factors (National Heart, Lung, and Blood Institute,
Weight Loss: Beneficial Health Outcomes
Moderate weight losses of 5% to 10% of initial body weight have been shown to reduce
blood pressure, even without concomitant dietary sodium reduction. Two long-term studies
demonstrated 21% to 34% reduction in risk of hypertension with only 4% to 5% weight losses
among 30 to 54 year old men and women with high blood pressure (TOHP Collaborative
Research Group, 1992; 1997). A recent meta-analysis of 25 randomized controlled trials
reported that a mean weight loss of 5. 1 kg produces reductions of 4.4 mm Hg and 3.6 mm Hg in
systolic and diastolic blood pressure, respectively (Neter, Stam, Kok, Grobee, & Geleijnse,
2003). In addition, modest weight losses of 5% to 10% initial body weight are sufficient to
reduce blood pressure to normal levels among obese individuals if the weight loss is maintained
over the long term, even if participants remain significantly obese (Mertens &Van Gaal, 2000).
Generally, low to moderate weight losses (5% to 10% initial body weight) have been effective in
lowering blood pressure and reducing the risk of hypertension.
Among older populations (60 to 80 years), the treatment of hypertension results in
substantial health benefits including the prevention of stroke, heart failure and other coronary
events (MacMahon & Rodger, 1993). The Trial of Nonpharmacologic Interventions in the
Elderly (Whelton et al., 1998) reported that participants assigned to the weight loss condition
experienced a 30% reduction in combined incidence of hypertension, stroke, transient ischemic
attack, congestive heart failure, and arrhythmia, but this effect was largely driven by reductions
in hypertension risk. Presently, it is unclear whether the reductions in blood pressure and
hypertension risk seen in older adults completing weight loss programs are comparable to those
achieved by middle-aged or younger adults.
The effects of weight loss on lipid profile have been enumerated by a substantial body of
research. A meta-analysis by Dattilo and Kris-Etherton (1992) indicated that a weight loss of
only one kg decreases serum cholesterol values by 2.28 mg/dL, LDL cholesterol by 0.91 mg/dL,
and triglycerides by 1.54 mg/dL. A weight loss of approximately ten pounds (4.5 kg) can reduce
LDL cholesterol by 5% to 10% (Fletcher et al., 2005). Additionally, the American Heart
Association (AHA) recently suggested that lifestyle interventions encouraging diets low in
saturated fat and cholesterol can lower LDL cholesterol by approximately 11% to 15% (Fletcher
et al., 2005). In persons over 65 years of age, LDL-lowering therapies have been effective in
reducing the risk of coronary heart disease, and therapeutic lifestyle changes are recommended
as the first line of therapy for older individuals (National Cholesterol Education Program, 2001),
though it is unclear whether older adults experience similar reductions in risk as compared to
middle-aged or younger samples.
Several studies have documented improvements in diabetic risk after participation in
behavioral weight loss treatment. A meta-analysis of randomized controlled trials of lifestyle
interventions and type 2 diabetes risk found that the one-year incidence of diabetes was reduced
by approximately 50% (RR 0.55, 95% CI 0.44-0.69) in participants receiving a lifestyle
intervention as compared to control groups (Yamaoka & Tango, 2005). The Finnish Diabetes
Prevention Study (Tuomilehto et al., 2001) randomized 522 middle-aged overweight, glucose
impaired individuals to an intensive lifestyle intervention or control group. After a follow-up of
approximately three years, the intervention group, who had lost an average of 4.7% initial body
weight, had a 58% reduced risk of diabetes as compared to the control group. After a mean
follow-up of seven years, there was a slightly reduced, but still significant relative risk reduction
of 43% in the intervention group as compared to the control group (Lindstroom et al., 2006). The
Diabetes Prevention Program (DPP), a randomized clinical trial of over 3200 obese men and
women at high risk for developing type 2 diabetes, demonstrated a 58% reduced incidence of
diabetes in individuals receiving an intensive lifestyle intervention for weight loss (Diabetes
Prevention Program Research Group, 2002). Interestingly, intensive lifestyle intervention was
significantly more effective at reducing the incidence of diabetes with increasing age of
participants (Diabetes Prevention Program Research Group, 2006). The incidence of diabetes
per 100 person years was 6.3 in the young group (25-44 years), 4.9 in the middle-aged group
(45-59 years), and 3.3 in the oldest group (60-85 years) receiving intensive lifestyle treatment.
By contrast, in the placebo arm, there was no difference in diabetic incidence by age (11.0 in the
young group, 10.8 in the middle-aged group, and 10.3 in the oldest group). This pattern of
results suggests that lifestyle interventions for weight loss may produce greater reductions in
diabetic risk among older adults as compared to middle-aged or younger samples, however more
research is needed.
Health-Related Quality of Life (HrQoL)
Weight loss has been associated with significant improvements in health-related quality of
life (HrQoL; Fine et al., 1999), a set of constructs related to physical, psychological, and social
functioning, and general well-being. For example, a study of persons participating in a Weight
Watchers program reported that those who had lost approximately 6.1 kg demonstrated
significant improvements on the Physical Functioning, Role Limitations due to Physical Health
Problems, and General Mental Health subscales of the SF-36 than individuals in the control
condition (Rippe et al., 1998). However, a recent meta-analysis of 34 randomized controlled
trials of weight loss treatment demonstrated little improvement in HrQoL, as measured by over a
dozen different generic and disease-specific instruments (Maciej ewski, Patrick, & Williamson,
There is a paucity of research on health related quality of life and weight change in older
adults. The Arthritis, Diet, and Activity Promotion Trial (ADAPT), a study of 316 overweight
and obese older adults with knee osteoarthritis, described significant improvements in HrQoL,
particularly with regards to physical health and functioning, after an 18-month combined diet and
exercise intervention that produced a mean weight loss of 4.4% (Rejeski et al., 2002). Another
study including 2364 older men and women (over 60 years of age) in Spain, described a
significant decrement in the domains of role limitations due to emotional functioning and self-
perceived general mental health (Leon-Munoz et al., 2005). These results are in contrast to the
positive pattern of HrQoL improvements typically seen with weight loss treatment among
younger or middle-aged samples. At present, no studies have compared changes in health-related
quality of life between elderly and middle-aged obese individuals undergoing weight loss
treatment. Further, given the varied results among existing studies, the impact of intentional
weight loss on HrQoL remains unclear.
Adherence to Diet and Activity Recommendations
Facilitating adherence to medical and behavioral interventions is critical to outcome
effectiveness (Vitolins, Rand, Rapp, Ribisl, & Sevick, 2000). However, adherence to treatment
is a challenge across all age groups. Research on adherence among samples of older men and
women undergoing weight loss treatment has produced conflicting results. Serdula et al. (1999)
reported that most people trying to lose weight do not follow the recommendations to reduce
caloric intake and increase leisure-time physical activity. In this study, older individuals
attempting to lose weight were less likely than younger persons to follow national guidelines
suggesting a minimum of 150 minutes per week of physical activity (Serdula et al., 1999).
Conversely, older adults in the DPP reported greater weight loss and levels of recreational
activity, were more likely to achieve the exercise goal of 150 minutes per week, and more likely
to reach the weight loss goal of 7% as compared to younger participants (Diabetes Prevention
Program Research Group, 2006). At the final visit, 63% of participants over 65 years of age met
the weight loss goal as compared to 27% of participants under 45 years of age (Diabetes
Prevention Program Research Group, 2002). There were no reported differences in caloric
intake, but older participants were more likely to complete self-monitoring records (Diabetes
Prevention Program Research Group, 2002). Additionally, with increasing age, the lifestyle
intervention arm of the DPP was significantly more effective than the metformin condition,
suggesting that older participants were able to adhere quite well to dietary and activity
There is little research with regards to levels of adherence, dietary intake and physical
activity in older individuals participating in behavioral weight loss programs. Studies comparing
the response of elderly and younger participants to lifestyle interventions are also lacking. The
few existing studies that report on adherence to eating and activity recommendations offer
conflicting results with regards to the response of older participants. Thus, more research is
needed related to older individuals' adherence to diet and activity recommendations.
Weight Loss: Negative Outcomes
Weight loss in older adults has been associated with a variety of negative outcomes, such
as the loss of lean muscle mass and bone mineral density, which may be particularly detrimental
for older adults (Gregg & Williamson, 2002). Indeed, weight loss between middle- and old-age
has been associated with doubling of relative risk of hip fracture and loss of mobility (Ensrud,
Cauley, Lipschutz, & Cummings, 1997; Langlois et al., 1998; Launer, Harris, Rumpel, &
Madans, 1994). Although these particular results are confounded by a failure to account for
intentionality of weight loss, a more recent observational study of over 1300 older men reported
a significant increase in hip bone loss even among obese men who were trying to lose weight
(Ensrud et al., 2005). A similar pattern was observed in a study of older obese women, whereby
modest intentional weight loss was an independent risk factor for hip fracture in later life
(Ensrud et al., 2003).
Weight loss in elderly persons has also been linked to greater mortality risk. For example,
a study of nearly 5,000 older adults found that weight losses of 5% or more over three years were
associated with a substantial increase in mortality rates (Hazard ratio (HR) = 1.67, 95% CI =
1.29-2. 15) over a four year follow up period (Newman et al., 2001). Hypothesized mechanisms
for this finding include adverse effects of weight loss on lean body mass and subsequent hip
fractures or injury, nutritional deficits from long-term caloric restriction, or underlying disease
pathology (e.g., depression, gastrointestinal disorders, cancer) or weight-related comorbidities
(Knudtson, Klein, Klein, & Shankar, 2005; Wallace & Schwartz, 2002).
Although unintentional weight loss is more frequently linked to morbidity and mortality
(Gregg, Gerzoff, Thompson, & Williamson, 2004; Yang, Fontaine, Wang, & Allison, 2003),
some studies have also demonstrated a relationship between intentional weight loss and
increased mortality (Newman et al., 2001; Yaari & Goldbourt, 1998), leading some researchers
to argue that weight loss may not be beneficial for older adults, even if they are overweight
(Newman et al., 2001; Thomas, 2005). However, these studies have typically failed to control
for premorbid health status or disease; other research has established no discernable link between
mortality and voluntary weight loss. For example, a large study of intentional weight loss and
mortality among over 5,200 older adults reported no increase in 5-year cumulative mortality risk
in men, and a reduction in risk for women who voluntarily lost 4.4 kg, as compared to
participants who were weight stable or described an unintentional weight loss (Diehr et al.,
1998). Even thought weight loss treatment can produce a host of improvements in metabolic risk
factors, it may be that for older adults, these reductions occur too late in life to have a significant
impact on health and longevity. At present, the relationship between intentional weight loss and
mortality risk in older obese adults remains unclear.
In sum, there is a small body of research to substantiate the claim that weight loss
treatment can produce metabolic benefits for older adults. Intentional weight loss in older obese
adults could also ameliorate weight-related diseases and conditions such as joint pain,
psychological symptoms and quality of life (Rossner, 2001), but could simultaneously present a
degree of risk with regards to musculoskeletal injury, bone and muscle loss. Additionally, it is
unknown whether older adults demonstrate similar levels of adherence to dietary and physical
activity recommendations during the course of lifestyle interventions as compared to younger or
middle-aged individuals (Rossner, 2001).
Specific Aims and Hypotheses
This study aims to describe the response of women 65 years and older to a lifestyle
intervention for weight loss and to compare their outcomes to those of a group of middle-aged
women (ages 50 to 59 years). The primary aims of the present study were to determine: (a) if
older obese women experience significant benefits (i.e., weight loss, reductions in metabolic risk
factors) from a lifestyle intervention for weight loss; (b) if behavioral weight loss treatment is
associated with negative outcomes (i.e., musculoskeletal injury) for older obese women; and (c)
if weight loss and adverse event outcomes are equivalent in older and middle-aged participants.
We hypothesized that older women would experience significant reductions in weight,
blood pressure (systolic), lipid profie (LDL-cholesterol), glycemic control (HbAlc), and
inflammation (C-reactive protein). We hypothesized that weight loss outcomes would be
equivalent in older and middle-aged participants. Additionally, we hypothesized that women in
the older age group would report similar levels of musculoskeletal adverse events as compared to
women in the middle-age group. No formal hypotheses with regards to metabolic risk factor
changes were postulated, as we did not anticipate having sufficient power to determine if older
and middle-aged participants would experience equivalent reductions in risk factors.
A secondary aim of this study was to describe and compare the responses of older and
middle-aged participants along several psychological and behavioral variables and outcomes
including: dietary intake, adherence, physical fitness and quality of life. As this aim was largely
exploratory, no a priori hypotheses are offered.
MATERIALS AND METHODS
Research Methods and Procedures
This study is a secondary analysis of data collected in the TOURS (Treatment of Obesity
in Underserved Rural Settings) proj ect. TOURS is a randomized controlled trial of behavioral
weight loss treatment in six medically underserved rural counties in Northern Florida (Perri et
Participants consisted of 298 women ranging from 50 to 75 years of age (M~= 59.3,
SD = 6.2 years). Among all participants, 75.5% classified their race/ethnicity as Caucasian,
20.5% as African American, 1.7% as Hispanic American, 2.0% as American Indian, and 0.3% as
Hawaiian. The mean pretreatment weight was 96.5 kg (SD = 14.9 kg), and mean baseline BMI
was 36.8 kg/m2 (SD = 5.0 kg/m2). Most of the sample (64.4%) completed at least 12 years of
education, with 43.3% reporting at least trade, vocational, or associate training. The majority of
participants were married (72.5%), and nearly half of women were employed full or part time
(47.3%). Over two-thirds of the sample (67.9%) reported a total household income of less than
$50,000. Additional baseline demographic characteristics can be seen in Table 2-1.
Although there was no upper limit placed on BMI, women who weighed in excess of
159 kg (350 lbs) were excluded to permit the use of a standard balance beam scale. Other
exclusion criteria included a history of prior health conditions likely to limit five-year life
expectancy (e.g., cancer within the past 5 years; serious infectious diseases; myocardial
infarction, cerebrovascular accident, or unstable angina within the previous 6 months; congestive
heart failure; chronic hepatitis; cirrhosis; irritable bowel syndrome; previous bariatric surgery, or
organ transplantation; musculoskeletal conditions that limit walking; chronic lung disease
limiting physical activity; serum creatinine > 1.5 mg/dL; anemia). Women with controlled
diabetes were allowed to enroll with the approval of their primary health care provider, but those
with a fasting blood glucose > 125 mg/dL at screening were excluded if not known to be
diabetic. Women with fasting serum triglycedrides > 400 mg/dL, or resting blood
pressure > 140/90 mmHg at screening were excluded, regardless of whether they were receiving
appropriate drug treatment. Exclusionary medications included antipsychotics, monoamine
oxidase inhibitors, systemic corticosteroids, antibiotics for HIV or TB, chemotherapeutic drugs,
or prescription weight-loss drugs. Women who reported a major psychiatric disorder, excessive
alcohol intake, or a weight loss in excess of ten pounds in the six months prior to screening were
not eligible to participate. Finally, women unable or unwilling to give informed consent, unable
to read English at a 5th grade level, or unwilling to accept random assignment were excluded
Participants were recruited using direct mailings, newspaper advertisements, and through
presentations at churches, community centers, and events. Interested individuals were screened
by telephone and scheduled for a baseline visit. At the baseline visit, the study was explained in
detail to eligible women, and informed consent was obtained. Additionally, participants
completed several questionnaires on demographic information, medical history, medication
inventory, dietary intake, physical activity, health-related quality of life, depressive symptoms,
and problem-solving skills. Participants' height, weight, abdominal circumference, resting heart
rate and blood pressure were taken, and blood was drawn and analyzed for metabolic profile.
The 6 Minute Walk Test (6MWT) was administered to assess functional mobility. A pre-start
visit was conducted within two weeks of the start of group sessions to ensure weight stability
prior to the initiation of treatment and to repeat the 6MWT. Participants who had gained or lost
in excess of4.5 kg underwent an additional blood-draw to ensure that their metabolic profile had
not changed from baseline. Measures were assessed at baseline, six, and 18 months.
The TOURS Intervention
All participants received a six-month lifestyle intervention (Phase I) carried out through
Cooperative Extension Offices in six rural counties in North Florida. These women were then
randomized to one of three follow-up programs (Phase II): an office-based (in-person)
maintenance program, a telephone-based maintenance program, or an education control
Phase I was comprised of 24 weekly group meetings (10 to 14 participants per group), 90
to 120 minutes in duration, designed to decrease caloric intake and increase moderate intensity
exercise to facilitate a safe and nutritionally sound weight loss of approximately 0.4 kg per week.
Participants were instructed to reduce their energy intake by 500 to 1000 kcal per day, maintain a
balanced diet consisting of no more than 25 to 30% of total kcal from fat, approximately 15%
from protein, and the remaining 60 to 65% from carbohydrates. Other dietary recommendations
included consuming at least five servings of fruits and vegetables per day, as well as three or
more servings of whole grains. Physical activity goals were set at 180 minutes per week of
moderate intensity (e.g., brisk walking) exercise, roughly 30 minutes per day on six days of the
week. Participants were given pedometers and instructed to strive for at least an additional 3000
steps per day above baseline levels.
In addition to targeting dietary and physical activity habits, Phase I included cognitive and
behavioral strategies for weight loss such as self-monitoring, goal-setting, self-reinforcement,
stimulus control, cognitive restructuring, and enhancing social support. Each session included a
weekly weigh in, review of progress towards goals, a discussion of nutrition and/or physical
activity, feedback from interventionists and other group members, and skills training related to
behavioral strategies for weight loss. Participants were encouraged to keep detailed, daily
records of their food intake and physical activity.
The TOURS intervention included segments tailored to the specific needs and issues of
women living in the rural south. Weekly cooking demonstrations were included to supplement
information provided on low-calorie, low-fat food preparation, with a special focus on Southern
Cooking. Additional lessons included strategies to enhance coping with stress and depression,
how to eat healthy outside of the home. The overall dietary obj ectives were consistent with the
Therapeutic Lifestyle Changes recommended in the Adult Treatment Panel III Report of the
National Cholesterol Education Program (2001), and the physical activity component of the
intervention follow guidelines set by the Surgeon General (US Department of Health and Human
Services, 1996) and the American College of Sports Medicine (2001).
Weight. Weight was measured to the nearest 0. 1 kilogram using a calibrated and certified
balance beam scale. Participants were dressed in light indoor clothing without shoes and with
pockets emptied when weight was taken. Percent weight change was calculated by subtracting
participants' weight at six and 18 months from month zero, and dividing by month zero weight.
Musculoskeletal adverse events. Participants were asked to report all adverse events
(AEs) experienced throughout the duration of the study. Adverse events were categorized for
review by a local Institutional Review Board (IRB) and by a specially constituted Data Safety
and Monitoring Board (DSMB). Additionally, all events were separately recorded as representing
a musculoskeletal injury or other type of adverse event. Musculoskeletal adverse events were
chosen because there is a slight increase risk of this type of injury with lifestyle treatment. In the
DPP, within the youngest group of participants (25-44 years), approximately 16% in the control
condition reported a musculoskeletal AE as compared to 20% in the lifestyle condition (Diabetes
Prevention Program Research Group, 2006). In the older participants (60-85 years), 26.7% of
individuals in the control group reported a musculoskeletal AE as compared to 28% in the
lifestyle intervention (Diabetes Prevention Program Research Group, 2006).
Blood pressure. Resting systolic and diastolic blood pressure were measured by a
Registered Nurse (RN), using a standardized protocol (Chobanian et al., 2003). Three blood
pressure readings were taken, spaced one minute apart, and the last two readings were averaged.
If large discrepancies were observed between the last two readings, an additional reading was
taken and mean values for the last three readings was used. In the present study, only systolic
blood pressure was examined due to its relation to cardiovascular disease risk (Prospective
Studies Collaboration, 2002; Vasan et al., 2001). It has been estimated that a 3 mm Hg reduction
in systolic BP could lead to reductions of 8% in stroke mortality and 5% in coronary heart
disease mortality (Stamler, 1991).
Blood analyses: LDL-Cholesterol, HbAlc, C-reactive protein. Blood samples were
drawn by the study RN and sent to Quest Diagnostics Clinical Laboratories to be analyzed for
lipid and metabolic profile. In the present study, lipid profile was measured using LDL-
cholesterol, due to its strong association with cardiovascular disease risk (National Cholesterol
Education Program, 2001). Lowering LDL-cholesterol can significantly reduce the risk of
stroke, coronary events, coronary artery procedures, and mortality (National Cholesterol
Education Program, 2001). Glycemic control, which is highly related to diabetic risk (American
Diabetes Association, 2001), was assessed via Hemoglobin Alc (HbAlc), which is a more
durable measure of glycemic control than fasting glucose (Centers for Disease Control and
Prevention, 2001). C-reactive protein is a marker of inflammation, which is associated with
atherosclerosis and cardiovascular disease (Libby, Ridker, Maseri, 2002).
Dietary intake. The Block 98 Food Frequency Questionnaire is a revised version of a
previously validated survey (Block et al., 1986) that asks respondents to estimate consumption of
a wide variety of foods. Scoring yields estimates of daily caloric intake, macro- and micro-
nutrient intake, as well as intake by specific food groups (e.g., fruits, vegetables, grains, etc.).
Estimated daily caloric intake was extracted for months zero, six, and 18.
Adherence. Participants were asked to complete food and activity records throughout
the study, on a daily basis during Phase I and at least three times per week during the 12 months
of extended care. Self-monitoring of dietary intake and physical activity levels is arguably the
most critical component of behavioral weight loss treatment (Brownell, 2000; Wing, 1998). The
total number of food records kept is a better predictor of successful weight loss outcome than the
actual content of dietary records (Streit, Stevens, Stevens, & Rossner, 1991). As such, in the
present study, the total number of daily records completed was used as a proxy for adherence to
Physical fitness. The 6 Minute Walk Test (6MWT) is a performance-based measure of
physical Sitness that can be used in populations with low exercise capacity (e.g., elderly persons,
those with functional limitations), for whom rigorous fitness tests such as treadmill exercise tests
would be inappropriate (Peeters & Mets, 1996). Participants were asked to walk along a course
marked by colored tape for six minutes, and instructed to cover as much ground as possible.
Distance covered was measured to the nearest foot. Participants completed this task twice at pre-
start and the first 6MWT results were discarded due to known practice effects. The 6MWT has
demonstrated high levels of reliability in populations with low exercise capacity (Kervio, Carre,
& Ville, 2003) as well as convergent evidence of validity, as suggested by a strong correlation
with peak oxygen uptake during maximal exercise testing (r = .68; Zugck et al., 2000).
Health-related quality of life. Health-related quality of life was assessed using the
Medical Outcomes Survey Short-Form 36 Health Survey (SF-36; Ware, Kosinski, & Keller,
1994), which assesses eight constructs related to quality of life including Physical Functioning,
Role Limitations due to Physical Health Problems, Social Functioning, Bodily Pain, General
Mental Health, Role Limitations due to Emotional Problems, Vitality and General Health
Perceptions. The SF-36 has demonstrated excellent psychometric properties in a number of
research studies (Fontaine & Barofsky, 2001; Jenkinson, Wright, & Coulter, 1994; Ware et al.,
1994) and with a wide range of populations, including obese adults (Fontaine & Barofsky, 2001).
Design and Statistical Analyses
The data analyses were performed using both a per-protocol (PP) and an intention-to-treat
(ITT) approach. Use of only treatment completers (per-protocol) is consistent with a recent
CONSORT statement regarding appropriate use of equivalence testing (Piaggio, Elboume,
Altman, Pocock, & Evans, 2006). Use of ITT analyses in equivalence testing can increase the
risk of type I error, as it suppresses observed mean differences between groups. All randomized
participants were included in the ITT analyses. For participants who were lost to follow-up,
baseline or last known values were substituted for missing data at six and 18 months. Use of this
"worst case" scenario is consistent with the findings from long-term studies of weight loss that
show a reliable return to baseline weights over time (Kramer, Jeffery, Forster, & Snell, 1989;
Stalonas, Perri, & Kerzner, 1984). Extrapolating from these findings, use of an ITT approach
assumes that treatment non-completers will similarly evidence a return to baseline values of
other variables of interest including metabolic risk factor levels, dietary intake and composition,
physical fitness, and quality of life.
Descriptive statistics are reported as means and standard deviations (SDs). Two change
scores were calculated for each participant, for each variable of interest. Phase I change score
represents pre- to post-treatment, where month six values were subtracted from month zero
values. Net change scores (pre-treatment to long-term follow-up), were calculated as month 18
values subtracted from month zero values.
To determine if older obese women experience significant benefits from a lifestyle
intervention for weight loss, we conducted a series of mixed between-within ANOVAs to
examine within-group changes over time for weight and metabolic risk factors (i.e., systolic
blood pressure, LDL-cholesterol, HbAlc, C-reactive protein) from month zero to month six and
month 18. To adjust for multiple tests, family-wise type I error was constrained to a = .05.; thus,
using a Bonferroni correction, the criterion for significance for individual tests was set at a = .01.
Margins of equivalence (A) for weight and the proportion of each group (older women and
middle-aged women) reporting a musculoskeletal adverse event were set a priori based on the
smallest value that would represent a clinically significant difference, as determined by reviews
of the literature. Weight outcomes for older and middle-aged participants were regarded as
equivalent if the difference between group means (using a 95% CI of the difference) was less
than or equal to 2.5%. That is to say, if the 95% Cl of the difference was wholly contained
within the margins of equivalence (A 2.5%), we rej ect the null hypothesis that the groups differ
by more than this minimally clinically significant amount at a = .05. Similarly, the proportions
of each group reporting a musculoskeletal adverse event were regarded as equivalent if the
95% Cl of the difference was contained within LA (+.04). The mean difference in percent weight
change between older and middle-aged groups was obtained from analysis of variance.
Confidence Intervals of the difference in proportions of older and middle-aged women reporting
a musculoskeletal AE were calculated using methods described by Newcombe (1998).
To evaluate our secondary aims, which included comparing older and middle-aged women
on a variety of behavioral and psychological variables, we conducted a series of mixed between-
within ANOVAs. Criterion variables included: daily caloric intake, distance covered during the
6MWT, and health-related quality of life. Additionally, one-way ANOVAs were used to
compare levels of adherence (measured as the number of daily food records completed) between
age groups. Family-wise error was again constrained to oc = .05 and Bonferroni corrections were
applied to control the risk of type I error.
All statistical analyses were conducted using SPSS statistical software (version 13.0 for
Windows Graduate Student Version).
Table 2-1. Baseline demographic characteristics of the sample of 298 women
Age (years) 59.3 6.2
Weight (kg) 96.5 14.9
BMI (kg/m2) 36.8 5.0
Percent of Sample
African American 20.5%
Hispanic American 1.7%
American Indian 2.0%
< 12 years 36.6%
Trade/vocational training 43.3%
Bachelor's degree 10.4%
Post-B achel or' s 9.7%
Full- or part-time 47.3%
Not working 8.7%
More than 1 category 11.1%
< $10,000 6.0%
Don't know/Didn't report 2.0%
Demographic Characteristics by Age
Older women (i.e., women between 60 and 75 years of age; n = 56) in this study were
more likely to be Caucasian, X2(1) = 4.6, p < .05, Cramer' s V= 0.21, and less likely to be
employed, X2(1) = 57.2, p < .001, Cramer' s V= 0.64, than middle-aged women (i.e., women
between 50 and 59 years of age; n = 162). Older women weighed significantly less than middle-
aged women at baseline, t(216) = 2.28, p < .025, r = .15, but this difference was not clinically
significant, and both groups fell in the Class II obesity range (BMI 35 to 39.9 kg/m2) at
pretreatment. Additional comparisons of demographic characteristics by age can be seen in
Previous analyses of the TOURS data have suggested that Caucasian women and African-
American women respond differently to treatment in terms of magnitude of weight loss, changes
in metabolic risk factors and a number of behavioral variables (Rickel et al., 2006). The older
age group was comprised of a significantly greater proportion of Caucasian women, thus
race/ethnicity was included as a covariate in all subsequent analyses of variance, and equivalence
testing was conducted separately for Caucasian and African-American women. However, given
that the older age group contained only six African-American women, we did not have enough
power to perform formal tests of equivalence with this sub-sample. Thus, only descriptive
statistics are provided.
Pretreatment Metabolic Risk Factors by Age
Older women did not differ from middle-aged women on any metabolic risk factor at
pretreatment with the exception of systolic blood pressure, which was higher in the older group,
t(216) = -3.60, p < .001, r = .24. Pretreatment metabolic risk factors by age can be seen in Table
Using a per-protocol approach (i.e., treatment completers; n = 45), we conducted a one-
way repeated measures ANOVA to examine within-group changes in weight, while controlling
for race/ethnicity. The proportion of older women who completed the study (80%) was not
significantly different than the proportion of middle-aged women (73%), X2(1) = 1.2, p = .26.
Bonferroni-adjusted pair-wise comparisons of the estimated marginal means indicated that older
women evidenced a significant reduction in weight from pretreatment to month
six, t(42) = 13.08, p < .001, r = .90. This weight loss was largely maintained at month 18,
t(42) = 6.06, p < .001, r = .68 (Figure 3-1). Using an ITT approach (n = 56), substituting
baseline values for missing data, older women also demonstrated a significant reduction in
weight from pretreatment to month six, t(53) = 3.95, p < .01, r = .48; as well as pretreatment to
month 18, t(53) = 3.17, p < .01, r = .40 (see Figure 3-2).
Metabolic risk factors
Using a per-protocol approach, older women experienced significant reductions in
systolic blood pressure from month zero to month six, t(28) = 4. 14, p < .01, r = .62, and
maintained these improvements at month 18, t(28) = 2.98, p < .02, r = .49. Changes in LDL
cholesterol were not significant over time. HbAlc was significantly reduced from month zero to
months six, t(28) = 4. 14, p < .01, r = .62; and from month zero to month 18, t(28) = 4.21,
p < .001, r = .62. C-reactive protein was also significantly reduced from month zero to months
six, t(28) = 2.72, p < .04, r = .46; these changes were maintained at month 18, t(28) = 3.28,
p < .01, r = .53. Figure 3-3 illustrates the changes in metabolic risk factors over time using a
Using an ITT approach, a similar pattern of results emerged. Older women (n = 56) also
evidenced significant reductions in systolic blood pressure from month zero to month six,
t(53) = 3.95, p < .001, r = .48; as well as month zero to month 18, t(53) = 3.17, p < .01, r = .40.
Changes in LDL cholesterol were not significant over time. HbAlc declined from month zero to
months six, t(53) = 4.07, p < .001, r = .49; these changes were maintained at month 18,
t(53) = 4.06, p < .001, r = .49. Similarly, C-reactive protein decreased from pretreatment to
month six, t(53) = 3.37, p < .005, r = .42, as well as from pretreatment to month 18, t(53) = 3.81,
p < .001, r = .46. Figure 3-4 illustrates the changes in metabolic risk factors over time using an
Equivalence testing was conducted using a 95% Cl of the difference between group means
(older women vs. middle-aged women) for weight change and the proportion of participants
reporting a musculoskeletal adverse event. Margins of equivalence were set a priori, based on
previous literature. A weight change of 2.5% was determined to be the smallest amount that
would represent a clinically meaningful change, and thus groups would be regarded as equivalent
if the 95% Cl of the difference was less than or equal to this margin. The margin of equivalence
for musculoskeletal adverse events was set at 4%. Thus, if the proportion of older and middle-
aged women reporting musculoskeletal AE differed by 4% or less, using a 95% Cl of the
difference, we would regard the groups as equivalent.
Among treatment completers, older Caucasian women (n = 44) lost a mean of 9.5%
(SD =5.5%) initial body weight from pretreatment to month six, which was not significantly
different than the 10.0% (SD = 5.8%) weight loss achieved by middle-aged Caucasian women
(n = 103). The 95% CI of the difference (-1.6 to 2.5) was contained within the margin of
equivalence (12.5%), thus older and middle-aged Caucasian women lost equivalent amounts of
weight from pretreatment to month six. At long-term follow up, older women had lost a mean of
7.6% (SD = 8.9%) body weight, again, not significantly different than the 8.4% (SD = 8.9%)
weight loss evidenced by middle-aged women. However, the groups were not equivalent with
respect to weight loss at month 18, as the 95% CI of the difference exceeded the margin of
equivalence (95% CI: -2.7 to 4.3).
Older African-American women lost a mean of 7.9% body weight from month zero to
month six, as compared to 6.6% for the middle-aged African-American women. At long-term
follow up, there was a trend for older African-American women to maintain a greater weight loss
than middle-aged African-American women; the older women los 9.0% body weight as
compared to 5.0% for the middle-aged women, F(1,42) = 2.3, p = .14, a difference that may have
reached significance with a larger sample size.
During active treatment (month zero to six), 23% of older Caucasian women reported at
least one musculoskeletal adverse event, as compared to 18% of middle-aged Caucasian women.
The 95% Cl of the difference in proportions, calculated according to the methods described by
Newcombe (1998), was -20.6% to 7.2%, well outside the margin of equivalence (14%). The
proportion of older women reporting a musculoskeletal AE over the course of the entire study
(month zero to 18) was 47%, as compared to 36% of middle-aged Caucasian women, X2(1) = 1.7,
p = .19. Again, the 95% Cl of the difference in proportions fell outside the margin of
equivalence (95% CI: -27.3 to 5.2).
During active treatment, 11% of older African-American women reported a
musculoskeletal AE, as compared to 26% of middle-aged women. At long-term follow up, 42%
of middle-aged African-American women had reported at least one adverse event, as compared
to only 1 1% of older African-American women. There was a trend for older African-American
women to be less likely to report a musculoskeletal AE overall than middle-aged African-
American women, X2(1) = 3.1, p < .08, a difference that may have reached significance with a
larger sample size.
To further investigate the risk of musculoskeletal injury, we divided all participants into
Hyve-year age cohorts. The occurrence of musculoskeletal AEs by fiye year age cohorts can be
seen in Figure 3-5. Although there were no significant differences in the occurrence of
musculoskeletal injury by age, 56% of Caucasian participants over 70 years of age (n = 16)
reported at least one adverse event over the course of the study as compared to 37% of Caucasian
women ages 50 to 69 years (n = 209), X2(1) = 2.25, p = .13. Again, this difference may have
reached significance with a larger sample of women over 70 years of age.
Prior to conducting analyses, basal metabolic rate (BMR) at baseline was calculated
according to the Harris-Benedict equation (Equation 3-1), where BMR is expressed in kcal/day,
height in cm, and weight in kg (Arciero et al., 1993).
BMR = (1.8*Height) + (9.6*Weight) (4.7*Age) + 655 (3-1)
Potentially invalid observations on the FFQ, defined as individuals who reported daily
caloric intakes less than 56% of BMR or greater than 144% of BMR, respectively (values outside
two SDs from the mean), were removed from the data. Using these cutoffs, there were 60 invalid
observations at month zero, 42 at month six, and 41 at month 18. There were no differences by
age. This method of screening for biologically implausible energy intake values is consistent
with that reported by Huang, Roberts, Howarth, & McCrory (2005), although they suggest an
even more stringent cutoff of + 1.4 SDs, which would have substantially reduced the sample size.
Finally, daily caloric intake values were logarithmically transformed to approximate a normal
distribution. Daily caloric intake at pretreatment, month six and month 18 for older and middle-
aged treatment completers can be seen in Figure 3-6.
Among treatment completers, we conducted a mixed between-within ANOVA with two
between-subj ects factors (age group and ethnicity) and one within-subj ects factor (daily caloric
intake). Baseline BMR values were included as a covariate in order to control for energy needs.
Mauchly's test indicated that the assumption of sphericity had been broken, thus Greenhouse-
Geisser corrected degrees of freedom are reported (E = .91). There was no within-group main
effect of caloric intake over time, F(1.8,164.3) = 0.06, ns. The between-group effect of age was
not significant, F(1,90) = 0.28, ns. There was no age by time interaction, indicating that older
and middle-aged participants did not experience differential reductions in caloric intake over the
course of the study.
The intention-to-treat analysis yielded a similar pattern of results (see Figure 3-7).
Mauchly's test indicated that the assumption of sphericity was violated, thus Greenhouse-Geisser
corrected degrees of freedom are reported (E = .89). The main effect of caloric intake over time
was not significant, F(1.8,274.8) = 0.01, ns. The main between-group effect of age was not
significant, F(1,154) = 0.09, ns. The age by time interaction was not significant.
Controlling for race/ethnicity, no differences emerged related to the number of food
records completed during Phase I (month zero to six) of treatment between middle-aged and
older participants, F(1,217) = 1.15, p > .05, r = .08. During Phase II (month six to 18) however,
older women completed a significantly greater number of daily food records, F(1,217) = 4.69,
p < .03, r = .30. On average, middle-aged women completed 116 daily food records in Phase I
and 73 food records in Phase II. By comparison, older women completed 125 food records in
Phase I and 106 food records in Phase II.
Among treatment completers, a mixed between-within ANOVA was conducted with two
between-subj ects factors (age group and ethnicity) and one within-subj ects factor (distance
covered in the 6MWT). The main within-group effect of physical fitness over time was not
significant. There was a significant between-group effect of age, F(1,153) = 31.8, p < .001,
whereby older participants were less physically fit at all time points as compared to middle-aged
participants (pretreatment, t(152) = 5.0, p < .001, r = .3 8; six months, t(152) = 5.1, p < .001,
r = .38; 18 months, t(152) = 5.2, p < .001, r = .39). Mean distances covered in the 6MWT by age
can be seen in Figure 3-8. Bonferroni-adjusted pair-wise comparisons indicated that older
women experienced a significant increase in physical fitness from pretreatment to month six,
t(152) = 2.6, p < .03, r = .21. These gains were also apparent at month 18, t(152) = 2.5, p < .04,
r = .20. Middle-aged women also experienced significant improvement in physical fitness from
pretreatment to months six and 18, t(152) = 5.9, p < .001, r = .43, and t(152) = 6. 1, p < .001,
r =.44, respectively.
Using an ITT analysis, the main within-group effect of physical fitness over time was not
significant (see Figure 3-9). There was a significant between-group difference by age,
F(1,212) = 35.8, p < .001, by which older adults were less physically fit at all time points. There
was no age by time interaction effect.
Health-Related Quality of Life
A series of mixed between-within ANOVAs were conducted for each of the eight
subscales on the SF-36 with two between-subj ects factors (age group and ethnicity) and one
within-subjects factor (subscale of the SF-36). Notably, higher scores on the subscales indicate
better perceived health status.
Among treatment completers, Mauchly's test indicated that the assumption of sphericity
was violated (p < .005), thus Greenhouse-Geisser corrected degrees of freedom are reported
(E = .93). There was no main within-group effect of Physical Functioning over time. However,
analyses indicated a significant between-group effect of age, F(1,173) = 6.0, p < .02, as well as a
significant age by time interaction, F(1.9,323.1) = 3.1, p < .05. Means, t-statistics, and
Bonferroni-adjusted probability values can be seen in Table 3-3. At pretreatment, there was no
difference in reported physical functioning between middle-aged and older adults. However,
older adults reported lower degrees of physical functioning than middle-aged participants at six
and 18 months. Additionally, middle-aged participants reported a significant improvement in
physical functioning from pretreatment to month six, t(173) = 4.5, p < .001, r = .32. Older
women did not demonstrate a significant improvement in physical functioning at any time point.
Changes in Physical Functioning by age can be seen in Figure 3-10.
Similar results were observed with an ITT analysis. Mauchly's test indicated that the
assumption of sphericity was violated (p < .005), thus Greenhouse-Geisser corrected degrees of
freedom are reported (E = .93). The analysis indicated no main within-group effect of Physical
Functioning over time. There was a significant between-group effect of age, F(1,215) = 5.7,
p < .02, as well as a significant age by time interaction, F(1.9, 401.2) = 3.9, p < .025.
Bonferroni-adjusted pair-wise comparisons indicated that older women describe significantly
worse physical functioning at six and 18 months than middle-aged women, t(215) = 2.9,
p < .005, r = .19, and t(215) = 2.7, p < .01, r = .18, respectively. While middle-aged women
demonstrated an improvement in physical functioning from pretreatment to month six,
t(215) = 4.8, p < .001, r = .31, older women did not demonstrate an improvement in physical
functioning over time.
Role Limitations due to Physical Health Problems
Among treatment completers, there was no significant main effect of role limitations over
time. There was a significant main between-group effect of age, F(1,173) = 13.0, p < .001, as
well as a significant age by time interaction, F(2,346) = 3.0, p < .05. Means, t-statistics, and
Bonferroni-adjusted probability values can be seen in Table 3-4. At pretreatment, there was no
difference in role limitations due to physical health problems between middle-aged and older
women. However, older women reported a greater degree of role limitations due to physical
health problems than middle-aged participants at six and 18 months. Additionally, older women
demonstrated a significant increase in role limitations due to physical health problems from
pretreatment to month 18, t(173) = 4.0, p < .001, r = .29. Changes in Role Limitations due to
Physical Health Problems by age can be seen in Figure 3-11.
An ITT analysis revealed a similar pattern of results. As Mauchly's test indicated that the
assumption of sphericity was not met (p < .04), Greenhouse-Geisser corrected degrees of
freedom are reported (E = .97). There was no significant within-group effect of role limitations
over time. There was a significant between-group effect of age, F(1,214) = 12.1i, p < .001,
although Levene's test indicated a violation of the assumption of homogeneity of variances, thus
any between-group effects should be interpreted with caution. Bonferroni-adjusted pair-wise
comparisons of the estimated marginal means suggested that older women report a significantly
greater degree of role limitations at six and 18 months than middle-aged participants
(t(214) = 3.2, p < .002 and t(214) = 3.5, p < .001, respectively). Additionally, there was a
significant age by time interaction, F(1.9,414.9) = 4.5, p < .015. Middle-aged women
demonstrated no change in role limitations over the course of the study, while older women
actually worsened from pretreatment to month six (t(214) = 2.4, p < .05, r = .16, and
t(214) = 4.1, p<.001, r =.27, respectively).
There were no significant within- or between-group effects on the Social Functioning
sub scale of the SF-36 using both a PP and ITT analysis.
There were no significant within- or between-group effects on the Bodily Pain subscale of
the SF-36 using both a PP and ITT analysis.
General Mental Health
There were no significant within- or between-group effects on the General Mental Health
sub scale of the SF-36 using both a PP and ITT analysis.
Role Limitations due to Emotional Problems
There were no significant within- or between-group effects on the Role Limitations due to
Emotional Problems sub scale of the SF-36 using both a PP and ITT analysis.
Using only treatment completers, there was no significant main within-group effect of
vitality over time. However, there was a significant age by time interaction, F(2,346) = 3.5,
p < .03. Means, t-statistics, and Bonferroni-adjusted probability values can be seen in Table 3-5.
Bonferroni-adjusted pair-wise comparisons suggest that at pretreatment, older women reported
significantly higher levels of vitality than middle-aged participants, t(173) = 2.4, p < .01, r = .18.
However, older women did not demonstrate any improvement in vitality over time. By contrast,
middle-aged participants reported a significant increase in vitality from pretreatment to months
six and 18, t(172) = 7.0, p < .001, r = .47, and t(172) = 2.7, p < .02, r = .20, respectively.
Changes in Vitality by age can be seen in Figure 3-10.
An ITT analysis of the Vitality sub scale indicated no significant main or interaction
General Health Perceptions
There were no significant main or interaction effects on the General Health Perceptions
sub scale of the SF-36 using both a PP and ITT analysis.
Table 3-1. Baseline demographic characteristics of older and middle-aged participants
Older (65-74 years) Middle-aged (50-59 years)
n = 56 n = 162
Age (years) 69.1* 2.9 54.6* 2.7
Weight (kg) 92.3* 14.7 97.5* 14.5
BMI (kg/m2) 35.7* 4.3 37.0* 5.1
Percent of Sample
Caucasian 83.9%* 69.1%*
African American 12.5% 25.9%
Hispanic American 1.8% 1.2%
American Indian 0.0% 3.7%
Hawaiian 1.8% 0.0%
< 12 years 51.8% 27.8%
Trade/vocational training 41.1% 45.7%
Bachelor's degree 3.6% 13.6%
Post-B achel or' s 3.6% 13.0%
Full- or part-time 10.7%** 69.1%**
Retired 55.4% 5.6%
Not working 8.9% 6.2%
More than 1 category 19.6% 9.9%
Note: p<.05, ** p<.001
Table 3-2. Pretreatment metabolic risk factors of older and middle-aged participants
Older (65-74 years) Middle-aged (50-59 years)
n = 56 n = 162
M SD MSD
Systolic BP (mm Hg) 129.5* 8.2 24.5* 9.1
LDL-cholesterol (mg/dL) 116.0 27.4 122.4 29.0
HbAlc (%) 6.1 0.7 5.9 0.7
C-reactive protein (mg/dL) 5.2 6.0 6.3 5.6
18 observed for
Table 3-3. Physical functioning by age, adjusted for race/ethnicity (PP)
Middle-aged Older M~ean
(n 18) (n =38) Difference
Month 0 78.3 76.7 1.5 3.3 0.46 0.643
Month 6 85.6** 78.0** 7.8 2.6 3.00 0.003
Month 18 80.6* 70.8* 9.8 3.8 2.56 0.011
Note: Significant within-group changes from month zero to six for middle-aged women were
observed, p <.001.
Table 3-4. Role limitations due to physical health problems by age, adjusted for race/ethnicity
Middle-aged Older M~ean
(n 18) (n =38) Difference
Month 0 87.8 83.6 4.2 4.6 0.90 0.368
Month 6 87.8* 71.6* 16.2 5.3 3.06 0.003
Month 18 79.1** 58.3** 20.8 6.5 3.17 0.002
Note: Significant within-group changes from month zero to month 18 for older women were
observed, p <.001.
Table 3-5. Vitality by age, adjusted for race/ethnicity (PP)
Middle-aged Older M~ean
(n =118) (n =38) Difference S
Month 0 57.1* 64.8* 7.7 3.2
Month 6 67.5 67.6 0.1 3.2
Month 18 61.6 63.8 2.2 3.4
Note: Significant within-group changes from month zero to months six and
middle-aged participants, p < .001 and p < .02, respectively.
Figure 3-1. Within-group changes in weight in older participants, adjusted for race/ethnicity (PP,
n = 45). Significant within-group changes were observed, p < .001.
Figure 3-2. Within-group changes in weight in older participants, adjusted for race/ethnicity
(ITT, n = 56). Significant within-group changes were observed, p < .01.
SSystolic BP (mm Hg)
+ C-reactive protein (mg/dL)
Month 0 Month 6 Month 18 Month 0 Month 6 Month 18
Figure 3-3. Within-group changes in risk factors in older participants, adjusted for race/ethnicity (PP, n = 45). A) Systolic blood
pressure. B) LDL-cholesterol. C) C-reactive protein. D) HbAlc.
Systolic BP (mm Hg) A
SC-reactive protein (mg/dL)
3.5 -- 13.3
Figure 3-4. Within-group changes in risk factors in older participants, adjusted for race/ethnicity (ITT, n = 56). A) Systolic blood
pressure. B) LDL-cholesterol. C) C-reactive protein. D) HbAlc
O Month 0-6
Il Month 0- 18
(n = 91)
(n = 71)
(n = 80)
(n = 36)
70 and over
(n = 20)
Figure 3-5. Proportion of participants reporting a musculoskeletal adverse event by age.
Figure 3-6. Daily caloric intake by age, adjusted for race/ethnicity (PP, n = 45). No significant
within- or between-group differences were observed.
Figure 3-7. Daily caloric intake by age, adjusted for race/ethnicity (ITT, n = 56). No significant
within- or between-group differences were observed.
- -5 Older
Figure 3-8. Physical Sitness by age, adjusted for race/ethnicity (PP, n = 45). All within-group
changes significant from pretreatment to months six and 18, p < .001; all between-
group differences significant, p < .001.
- r-- -Older
Figure 3-9. Physical Sitness by age, adjusted for race/ethnicity (ITT, n = 56). All between-group
differences significant, p < .001.
t 10 Miiddle-aged
Figure 3-10. Physical functioning by age, adjusted for race/ethnicity (PP). Significant within-
group changes from month zero to six for middle-aged women were observed,
t 10 -- Mddle-aged
- -5 Older
' + ,
Figure 3-11. Role limitations due to physical health problems by age, adjusted for race/ethnicity
(PP). Significant within-group changes from month zero to month 18 for older
women were observed, p < .001.
Figure 3-12. Vitality by age, adjusted for race/ethnicity (PP). Significant within-group changes
from month zero to months six and 18 observed for middle-aged participants,
p < .001 and p < .02, respectively.
The present study examined both the positive and negative outcomes of a lifestyle
intervention for weight loss in a sample of older and middle-aged adults, and whether these
outcomes were comparable between age groups. With regards to our primary aims, older women
achieved significant reductions in weight and metabolic risk factors from pre- to post-treatment
and at long-term follow-up. Older women who completed treatment lost a mean of 9.5% initial
body weight at six months, and maintained a 7.6% loss at 18 months. This group of women also
experienced a significant reduction in systolic blood pressure from pre- to post-treatment (M~=
6.3 mm Hg, SD = 12.2 mm Hg), and largely maintained this decrease at 18 months (M~= 4.6 mm
Hg, SD = 12.1 mm Hg). Additionally, older women showed significant reductions in HbAlc
from month zero to month six (M~= 0.2%, SD = 0.5%) and from month zero to month 18 (M~=
0.3%, SD = 0.4%). C-reactive protein also decreased significantly from month zero to month six
(M~= 2.0%, SD = 4.2%) and month zero to month 18 (M~= 2.7%, SD = 4.6%). There was no
significant within-group change over time in LDL-cholesterol levels. Results are consistent with
previous research demonstrating marked reductions in weight and metabolic risk factors among
older adults participating in lifestyle interventions (Diabetes Prevention Program Research
Group, 2002; 2006; Lindstroom et al., 2006; MacMahon & Rodger, 1993; Tuomilehto et al.,
2001; Whelton et al., 1998; Yamaoka & Tango, 2005).
In the present study, 23% of older Caucasian women reported at least one musculoskeletal
injury during active treatment, and 47% reported this type of adverse event over the course of the
18-month intervention. These proportions were not significantly different than the 18% of
middle-aged women reporting an injury during active treatment and 36% reporting an injury
throughout the 18 month study. The Diabetes Prevention Program Research Group (2006)
described a similar pattern of results for participants in the lifestyle condition, by which
participants between 60 and 85 years of age reported 28 musculoskeletal adverse events per 100
person-years, in contrast to 25 to 40 year old participants, who reported 20 musculoskeletal AEs
per 100 person-years. This difference did not reach statistical significance.
When we further categorized the sample into five-year age increments, 56% of Caucasian
women over 70 years of age reported at least one musculoskeletal injury throughout the 18
months, as compared to only 37% of Caucasian participants 50 to 69 years of age. Given that
only 16 women fell into the above 70 age range, we did not have enough power to examine
differences in the proportion of women over 70 reporting a musculoskeletal injury, as compared
to younger age groups. However, this discrepancy warrants further investigation regarding the
safety of behavioral weight loss treatment for older adults.
Equivalence Testing. We found support for our hypothesis that older and middle-aged
women lose equivalent amounts of weight from pre- to post-treatment. Among treatment
completers, older Caucasian women lost a mean of 9.5% initial body weight at six months,
which was statistically equivalent to the 10.0% weight loss achieved by middle-aged Caucasian
women. At 18 months, the difference between older and middle-aged participants exceeded the
margin of equivalence, thus we were unable to determine equivalence, likely due to the small
sample size of older adults. A comparison of middle-aged and older African-American women
revealed a trend for older women to lose more weight than middle-aged women from
pretreatment to month 18 (9.0% initial body weight as compared to 5.0%, respectively). Given
that there were only six African-American women over 65 years of age, this difference in weight
loss may have reached significance with larger samples.
Results did not support our hypothesis regarding the equivalence of musculoskeletal injury
between middle-aged and older women. The difference in proportions of middle-aged and older
women reporting this type of adverse event during active treatment and over the course of the
entire study exceeded our specified margin of equivalence (+4%). Post-hoc power analyses
suggested we would have needed over 800 participants per group to determine equivalence, even
if we had used a wider 10% margin. Further, beyond rejecting our hypothesis that older and
middle-aged women experience comparable rates of injury, it appears that older Caucasian
women may be at greater risk for injury than middle-aged Caucasian women. This increased risk
may be particularly pronounced for women over 70 years of age, 56% of whom reported at least
one musculoskeletal adverse event during the 18 month study. However, given limits in power,
we could not examine differences between five-year age cohorts.
Dietary Intake and Adherence
There were no significant within-group changes in caloric intake over the course of the study,
nor were there differences between older and middle-aged participants. These findings are
consistent with results from the DPP, whereby there was no significant difference in daily caloric
intake between participants over 65 years of age and those under 45 (Diabetes Prevention
Program Research Group, 2006). There was a difference, however, in the number of daily food
records completed between older and younger participants, such that older individuals were more
likely to complete self-monitoring records than younger participants (Diabetes Prevention
Program Research Group, 2004). In the present study, there were no differences between older
and middle-aged participants with regards to the number of daily food records completed during
active treatment. However, consistent with results reported in the DPP, older women completed
a significantly greater number of daily food records than middle-aged participants during Phase
II of the study (106 and 73, respectively). It may be that older individuals have fewer competing
demands (e.g., full-time employment, child care), and therefore have more time to devote to a
lifestyle intervention program. Additionally, due to the greater number and degree of health
problems in older adults, elderly individuals may be more motivated to make lifestyle changes to
improve their health.
Physical Sitness, as measured by the 6MWT, improved for both older and middle-aged
participants from month zero to months six and 18. Additionally, middle-aged women
performed significantly better than older women on the 6MWT at each assessment. Results are
consistent with previous research demonstrating an inverse relationship between age and
physical Sitness as measured by the 6MWT (Enright et al., 2006). Further, some research has
found that older adults may be less likely to use physical activity as a tool for weight loss. For
example, in an analysis of data from the Behavioral Risk Factor Surveillance System (BRFSS),
Serdula et al. (1999) reported that the likelihood of utilizing physical activity for weight loss
decreased with age. It may be that older adults are less willing to engage in exercise and activity
prescriptions throughout the course of behavioral weight loss treatment for fear of injury, or lack
of opportunity to participate in programmed activities such as group sports. However, other
research has demonstrated the opposite pattern of results. In the DPP, older participants (60 to
85 years of age) were more likely to meet the exercise goal of 150 minutes per week than
participants between 25 and 40 years of age (Diabetes Prevention Program Research Group,
2006). However, while older participants in the DPP spent more time exercising, younger
participants may have spent a greater proportion of time in higher intensity activities. These
trends may result in parallel increases in physical Sitness among younger and older participants,
as we found in the present study. However, neither the intensity of physical activity nor physical
fitness levels were reported in the DPP.
Health-Related Quality of Life
Analyses of Health-Related Quality of Life (HrQoL), as measured by the SF-36, indicated
that older women did not experience significant improvements in various domains of HrQoL
over the course of the study, whereas middle-aged women experienced several significant
improvements. In the domain of Physical Functioning, middle-aged participants experienced a
significant improvement over time, while older adults reported no change. Additionally, older
women reported lower degrees of Physical Functioning at every assessment point, as compared
to middle-aged participants. Further, in the domain of Role Limitations due to Physical Health
problems, older women scored higher than middle-aged women at each assessment point.
Additionally, older women reported a significant increase in Role Limitations due to Physical
Health Problems over time, while middle-aged women described no change in this domain over
the course of the study. Somewhat unexpectedly, older women reported higher levels of Vitality
at pretreatment than middle-aged women. However, middle-aged women reported significant
increases in this domain over the course of the study, while older participants did not experience
significant changes over time. No changes over time were noted for middle-aged or older
women in the domains of Social Functioning, Bodily Pain, General Mental Health, Role
Limitations due to Emotional Problems, or General Health Perceptions. Generally, it appears
that weight loss treatment was not effective in improving various domains of health-related
quality of life for older women. In fact, older women experienced a significant increase in role
limitations due to physical problems over the course of the study. By contrast, middle-aged
participants demonstrated significant improvements in the domains of Physical Functioning and
Previous research on HrQoL in older adults undergoing weight loss treatment has
produced conflicting results. In contrast to our findings, a study of older adults with knee
osteoarthritis described significant improvements in HrQoL after an 18-month lifestyle
intervention producing a mean weight loss of 4.4% initial body weight (Rej eski et al., 2002).
Yet, a prospective, observational study of 23 54 adults in Spain described significant decrements
in the domains of Role Limitations due to Emotional Functioning and General Mental Health
among individuals who were obese at baseline and lost weight over two years (Leon-Munoz et
As we have no control group of older women not undergoing a lifestyle intervention, we
cannot determine whether the increase in role limitations due to physical health problems is
related to participation in weight loss treatment, or a natural consequence of aging. Further, we
cannot say whether older obese women not receiving weight loss treatment may actually
demonstrate a decline in HrQoL. Thus, it is possible that participation in the lifestyle program
may prevent or slow a natural age-related decline in HrQoL. At this point, it remains unclear
whether a lifestyle intervention for weight loss can facilitate positive changes in HrQoL for older
There are several limitations to the present study. First, we had a relatively small sample
of older women, offering limited power to detect small differences in a variety of outcomes.
Further, equivalence testing typically requires samples approximately 10% larger than those
needed for traditional difference testing (Djulbegovic & Clarke, 2001). Subsequently, we did not
have enough power to use equivalence testing on metabolic risk factor outcomes. A post-hoc
power analysis indicated that we would have needed over 800 women per group to determine
equivalence with respect to musculoskeletal injury, even if we had broadened the margin of
equivalence to 10%.
A second limitation of this study was the lack of an untreated control group of older
women. Although there appeared to be a slight increase in risk of musculoskeletal injury for
older women, we cannot determine if this increase was related to participation in the study, or the
consequence of typical aging. Future research should compare the rate of musculoskeletal injury
in older women not undergoing weight loss treatment to those participating in the lifestyle
program to clarify if this type of treatment is associated with greater risk of injury in older adults.
Additionally, individuals with serious health conditions (e.g., uncontrolled diabetes or
hypertension) were excluded from participation in the study. The inclusion of relatively healthy
women may have implications with regard to the magnitude of changes seen across metabolic
risk factor outcomes. That is to say, there may be a floor effect by which participants without
significantly elevated risk factors can achieve only incremental reductions, whereas persons with
more severe health conditions have more potential to improve. There is some evidence to
suggest that obese individuals with more severe metabolic risk factors experience greater degrees
of change over the course of weight loss treatment than relatively healthy individuals. For
example, McLaughlin et al., (2001) compared insulin-resistant and insulin-sensitive obese
women undergoing four months of a caloric-restricted diet plus sibutramine. Though insulin-
resistant and insulin-sensitive women did not differ with regards to weight loss, insulin-resistant
women achieved significant reductions in metabolic risk factors such as LDL-cholesterol and
plasma triglyceride concentrations, while insulin-sensitive women did not.
Further, given that the severity of weight-related risk factors and diseases is typically
compounded with age, the exclusion of older women with serious health conditions at baseline
may have resulted in a sample of older women that is not representative of the larger population
of women over 65 years of age. This would limit the generalizability of our results to older
women with greater metabolic abnormalities. Generalizability is also limited by the exclusion of
men, younger age groups, as well as the under-representation of older racial/ethnic minority
Our is also limited by the potential confound of medication changes over the course of the
study. For example, some participants may have experienced reductions in blood pressure or
cholesterol such that their physicians discontinued or lowered their medication. Alternatively,
metabolic risk factors may have worsened for some participants, warranting the initiation of, or
increase in medication use. There is no reason to believe that these changes would occur
differentially for middle-aged and older participants, but future analyses of the TOURS data
should include an examination of this issue.
Finally, given that the adverse event data in this study are based on self-reports, results are
subj ect to potential biases. It is possible that older adults were more attentive to the occurrence
of relatively minor injuries, or more willing to report an injury than middle-aged participants.
An increased vulnerability to injury, or an increased vigilance, or both may contribute to a
greater likelihood of reported adverse events among older participants (Weingart et al., 2005).
As there were no measures of muscle mass or bone density, we could not assess potentially
important changes in body composition that may place older adults at risk of injury. Future
studies examining the safety of weight loss treatment for older adults should include measures of
body composition in order to explore potential mechanisms by which older adults may be at
increased risk for musculoskeletal adverse events.
Our study has important clinical implications with regards to the safety and efficacy of
behavioral weight loss interventions for older adults. Overall, it appears that older women can
achieve significant improvements in health over the course of behavioral weight loss treatment.
Results of the present study indicate that older women may be at greater risk for adverse
consequences during participation in a lifestyle intervention for weight loss than middle-aged
women. Thus, lifestyle interventions including older adults should take particular precautions to
educate participants about safe ways to achieve exercise goals and avoid injury. Future research
should also explore ways to prevent muscle and bone loss during weight loss treatment, such as
the addition of strength or resistance training to physical activity programs.
In sum, it appears that older, obese women can experience substantial benefits over the
course of a lifestyle intervention, including significant reductions in weight, blood pressure,
glycemic control, and inflammation. However, the occurrence of negative outcomes potentially
associated with participation in a lifestyle intervention for weight loss, namely musculoskeletal
injury and decrements in health-related quality of life, warrant further exploration in older adults.
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Lauren Mari Gibbons was born on April 30, 1981, in Boston, Massachusetts. She grew up
in Weston, Massachusetts, where she graduated from Weston High School in 1999. In 2003, she
earned her B.A. from the University of Pennsylvania, with distinction in Psychology. After
graduation, she worked as a research coordinator for 2 years at the University of Pennsylvania' s
School of Medicine. In 2005, Lauren enrolled in the Clinical and Health Psychology program at
the University of Florida. While at the University of Florida, she completed a number of
research proj ects prior to graduating with her M. S. degree in May, 2007.