Predictors of long-term weight loss in adults with modest initial weight loss, by sex and race.
ABSTRACT Effective weight management interventions could reduce race-sex disparities in cardiovascular disease (CVD), yet little is known about factors associated with successful weight loss maintenance in race-sex subgroups. In the Weight Loss Maintenance trial (WLM), overweight/obese (BMI 25-45 kg/m(2)) adults who lost ≥4 kg in a 6-month behavioral weight loss intervention (phase I) were randomized into one of three 30-month maintenance interventions (phase II). To investigate predictors in subgroups, randomized groups were combined for this analysis. Of 1,685 phase I participants, 1,032 (61%) entered phase II, including 12% black men (BM), 26% black women (BW), 25% white men (WM), and 37% white women (WW). Weight change over the 36-month study ranged from -2.3% (95% confidence interval = -3.1 to -1.5%) in BW to -4.5% (95% confidence interval = -5.7 to -4.0%) in WM, the result of differential weight loss during phase I. Within race, men lost significantly more weight than women, but within sex group, weight loss did not differ significantly between races. Although participants regained weight during phase II, regain did not differ by race-sex group, and mean weight at the end of the study was significantly lower than phase I entry weight for each subgroup. In regression models, phase I weight loss predicted overall 36-month weight loss in all race-sex groups. Healthy dietary pattern at entry, improvement in dietary pattern, or both were predictive in three of four race-sex groups. Few other variables other than initial weight loss and dietary pattern were predictive. Future research should identify additional modifiable influences on long-term maintenance after a modest weight loss.
- SourceAvailable from: Kim Gans[Show abstract] [Hide abstract]
ABSTRACT: Obesity among Black women continues to exceed that of other women. Most weight loss programs created without reference to specific cultural contexts are less effective for Black than White women. Weight control approaches accessible to Black women and adapted to relevant cultural contexts are important for addressing this problem. This paper reports the final results of SisterTalk, the randomized controlled trial of a cable TV weight control program oriented toward Black women. A five group design included a comparison group and a 2 x 2 factorial comparison of a) interactive vs. passive programming and b) telephone social support vs no telephone support, with 12 weekly initial cable TV programs followed by 4 monthly booster videos. At baseline, 3, 8, and 12 months post randomization, telephone and in person surveys were administered on diet, physical activity, and physical measurements of height and weight were taken to calculate body mass index (BMI). Analysis of variance (ANOVA) was used to examine differences over time, and between treatment and comparison groups. Dose variables reflecting use of the TV/video and written materials were also assessed. At 3 months, BMI, weight, and dietary fat were significantly lower and physical activity significantly higher among women exposed to the Cable TV intervention compared to the wait-list comparison group. Significant dietary fat differences were still observed at 8 and 12 month evaluations, but not BMI or physical activity differences. Main effects were not observed for interactive programming or enhanced social support at any time point. Within the intervention group, higher watching of the TV series and higher reading of educational materials were both (separately) associated with significantly lower dietary fat. Cable TV was an effective delivery channel to assist Black women with weight control, increasing physical activity and decreasing dietary fat during an initial intervention period, but only dietary changes persisted Enhanced social support and the ability to interact with others during the show were not effective complementary intervention components as conducted in this trial. Future research to strengthen the ability of this approach to achieve long term effects may offer even more promising outcomes.International Journal of Behavioral Nutrition and Physical Activity 12/2013; 10(1):141. · 3.58 Impact Factor
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ABSTRACT: This study's purpose was to identify psychosocial predictors of weight loss maintenance in a multi-site clinical trial, following a group-based weight loss program. Participants (N = 1025) were predominately women (63 %) and 38 % were Black (mean age = 55.6 years; SD = 8.7). At 12 months, higher SF-36 mental health composite scores were associated with less weight regain (p < .01). For Black participants, an interaction existed between race and friends' encouragement for exercise, where higher exercise encouragement was related to more weight regain (p < .05). At 30 months, friends' encouragement for healthy eating was associated with more weight regain (p < .05), whereas higher SF-36 mental health composite scores were related to less weight regain (p < .0001). Perceived stress and select health-related quality of life indices were associated with weight regain; this relationship varied across gender, race, and treatment conditions. Temporal changes in these variables should be investigated for their impact on weight maintenance.Journal of Behavioral Medicine 04/2014; · 3.10 Impact Factor
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ABSTRACT: The New Nordic Diet (NND) has induced weight loss in a 26-week controlled intervention. We aim to investigate whether high compliance and satisfaction can be maintained after the active intervention is discontinued thereby maintaining the health effects. After 26 weeks of intervention with NND or Average Danish Diet (ADD), 147 participants (mean age 43 years and mean BMI 29.1 kg/m(2)) were followed for further 52 weeks. All participants were encouraged to follow NND but without further guidance. The study is registered with ClinicalTrials.gov, study id NCT01195610. One hundred and ten participants (75 %) completed the follow-up. Among participants previously randomised to NND (NND group), dietary compliance and satisfaction decreased from 4.3 to 3.0 and from 4.8 to 4.0, respectively (both p < 0.0001) (1-5 point scale). Among those originally randomised to ADD (ADD group), satisfaction with NND was significantly higher than with ADD during follow-up (3.3 vs. 2.5, p = 0.026). Weight losses during intervention of -6.2 kg and -3.0 kg were followed by regains of 4.6 kg (SE 0.5) and 1.1 kg (SE 0.7) for the NND group and ADD group, respectively [adjusted difference; mean (95 % CI): 1.8 kg (0.1-3.4), p = 0.041]. Across diet groups, every 1 score higher in compliance with NND was associated with 0.90 kg less body weight regain (p = 0.026) and those who increased physical activity regained 3.4 kg less compared to those who did not (p < 0.0001). NND provides higher satisfaction, and body weight regain is reduced with higher compliance with NND and increased physical activity.European Journal of Nutrition 03/2014; · 3.13 Impact Factor
VOLUME 20 NUMBER 9 | sEptEMBER 2012 | www.obesityjournal.org
intervention and Prevention
nature publishing group
The obesity epidemic is a contributing factor in health dis-
parities. Overweight and obesity are more prevalent in non-
Hispanic black adults (74%) compared to non-Hispanic whites
(67%), with the highest rates in black women (BW) (78%)
(1). Disparities in obesity prevalence are likely to contribute
to disparities in the prevalence and severity of hypertension,
diabetes mellitus type 2, and dyslipidemia (2,3). These dispari-
ties in cardiovascular disease (CVD) risk factors contribute to
excess rates of stroke and heart failure in blacks (3). Effective
treatment of obesity with particular attention to at-risk
demographic groups would improve the public health and
reduce CVD disparities.
The mainstay of contemporary obesity treatment is life-
style behavior change; i.e., reducing calorie intake, improving
diet quality, and increasing physical activity (PA) (4). Weight
loss interventions targeting these behaviors have shown con-
siderable short-term (6 month) success (5,6). However, such
interventions have generally been less effective in blacks, par-
ticularly in BW (6–8). In addition, relatively little data are avail-
able concerning race–sex differences in longer term weight
loss interventions and on predictors of weight regain after
predictors of Long-term Weight Loss
in Adults With Modest Initial Weight Loss,
by sex and Race
Laura P. Svetkey1,2, Jamy D. Ard3,4, Victor J. Stevens5, Catherine M. Loria6, Deb Y. Young7, Jack F. Hollis5,
Lawrence J. Appel8, Phillip J. Brantley9, Betty M. Kennedy10, Shiriki K. Kumanyika11, Bryan C. Batch1,12,
Leonor Corsino1,12, Lillian F. Lien1,12 and William M. Vollmer5; for the Weight Loss Maintenance
Collaborative Research Group
Effective weight management interventions could reduce race–sex disparities in cardiovascular disease (CVD), yet
little is known about factors associated with successful weight loss maintenance in race–sex subgroups. In the Weight
Loss Maintenance trial (WLM), overweight/obese (BMI 25–45 kg/m2) adults who lost ≥4 kg in a 6-month behavioral
weight loss intervention (phase I) were randomized into one of three 30-month maintenance interventions (phase
II). To investigate predictors in subgroups, randomized groups were combined for this analysis. Of 1,685 phase I
participants, 1,032 (61%) entered phase II, including 12% black men (BM), 26% black women (BW), 25% white men
(WM), and 37% white women (WW). Weight change over the 36-month study ranged from −2.3% (95% confidence
interval = −3.1 to −1.5%) in BW to −4.5% (95% confidence interval = −5.7 to −4.0%) in WM, the result of differential
weight loss during phase I. Within race, men lost significantly more weight than women, but within sex group, weight
loss did not differ significantly between races. Although participants regained weight during phase II, regain did not
differ by race–sex group, and mean weight at the end of the study was significantly lower than phase I entry weight
for each subgroup. In regression models, phase I weight loss predicted overall 36-month weight loss in all race–sex
groups. Healthy dietary pattern at entry, improvement in dietary pattern, or both were predictive in three of four
race–sex groups. Few other variables other than initial weight loss and dietary pattern were predictive. Future research
should identify additional modifiable influences on long-term maintenance after a modest weight loss.
Obesity (2012) 20, 1820–1828. doi:10.1038/oby.2011.88
1Sarah W. Stedman Nutrition and Metabolism Center, Duke University Medical Center, Durham, North Carolina, USA; 2Duke Hypertension Center, Division of Nephrology,
Department of Medicine, Duke University Medical Center, Durham, North Carolina, USA; 3Department of Nutrition Sciences, University of Alabama at Birmingham,
Birmingham, Alabama, USA; 4Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA; 5Health Science Programs, Center for Health
Research, Kaiser Permanente Northwest, Portland, Oregon, USA; 6National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA; 7Department of Epidemiology and
Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA; 8Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins
Medical Institutions, Baltimore, Maryland, USA; 9Department of Behavioral Medicine, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA; 10Louisiana
School Boards Association, Baton Rouge, Louisiana, USA; 11Department of Epidemiology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania
School of Medicine, Philadelphia, Pennsylvania, USA; 12Department of Medicine, Division of Endocrinology, Nutrition and Metabolism, Duke University Medical Center,
Durham, North Carolina, USA. Correspondence: Laura P. Svetkey (email@example.com)
Received 27 August 2010; accepted 14 March 2011; advance online publication 28 April 2011. doi:10.1038/oby.2011.88
obesity | VOLUME 20 NUMBER 9 | sEptEMBER 2012 1821
intervention and Prevention
significant initial weight loss. Perhaps most important, little
is known concerning factors associated with successful long-
term weight control in each of these demographic subgroups.
Such information could help us to design more effective inter-
ventions for specific populations. To this end, we report the
extent and predictors of weight loss maintenance both overall
and in race–sex subgroups in the Weight Loss Maintenance
Methods and Procedures
WLM was a National Heart, Lung and Blood Institute-sponsored mul-
ticenter randomized controlled trial designed to test strategies for sus-
tained weight loss in a diverse population with CVD risk factors (9,10).
The study included an initial weight loss phase (phase I) in which 1,685
participants all received a 6-month intensive behavioral intervention.
In phase II, 1,032 participants who lost at least 4 kg in phase I were ran-
domly assigned to one of three 30-month behavioral maintenance con-
ditions: a self-directed control condition without further intervention
(SD), monthly personal counseling intervention (PC), or an interactive
internet-based technology intervention (IT). WLM was approved by
the institutional review board at each participating institution, and all
participants provided written informed consent.
Participants were overweight or obese adults (BMI 25–45 kg/m2) who
were taking medication for hypertension and/or dyslipidemia. Exclusion
criteria included medical conditions that precluded full participation in
the study; weight loss of >9 kg in the last 3 months; recent use of weight
loss medications; history of weight loss surgery; and diabetes mellitus.
Because this analysis focuses on weight change over the full 36-month
study, only participants who lost at least 4 kg in phase I and were eligible
for phase II are included here.
Data collection occurred before the start of phase I (study entry), at
randomization into phase II, and every 6 months thereafter for 30
months. Measurements were obtained by trained, certified staff masked
to treatment assignment.
Weight was measured using a calibrated digital scale with the par-
ticipant wearing light, indoor clothes without shoes. Height was meas-
ured once at entry using a wall-mounted stadiometer. Dietary intake
was assessed by the Block Food Frequency Questionnaire (FFQ) (11),
and summarized using the Healthy Eating Index (HEI) (12,13). The HEI
ranges from 0 to 100, with higher scores indicating better diet quality.
To assess PA, participants wore a calibrated, triaxial accelerometer
(RT3; Stayhealthy, Monrovia, CA) for at least 10 h/day for at least 4 days
including one weekend day, and results were used to estimate total weekly
minutes of moderate-to-vigorous PA (MVPA) (14,15).
Participants also completed questionnaires to assess demographic
characteristics, medication usage, reported difference between current
weight and desired weight (in pounds), prior weight loss history, and
other health and behavior variables. In addition, they completed ques-
tionnaires measuring psychosocial variables including the following.
Social Support and Exercise and Social Support for Eating Habits were
assessed by 13- and 18-item surveys, respectively, that use self-report
to assess participants’ perceptions of social support for exercise and
healthy eating, respectively. Specifically, participants report how often
their friends or family members (separately rated) supported their exer-
cise and healthy eating behaviors during the previous three 3 months.
Responses are on a 5-point Likert scale and responses of each of four
surveys (exercise or eating habits, friends or family) are summed, yielding
friends-support and family support scores. These surveys have demon-
strated adequate internal consistency (α = 0.76–0.85) (16).
Health-related quality of life was assessed with the 36-item self-report
SF-36 questionnaire (17). The SF-36 is a generic (rather than disease-
specific) measure appropriate for the general population. Norms-based
scoring yields two composite scale t-scores (physical and mental health)
and eight subscale t-scores related to functional health and well-being.
Participants respond to questions formatted on a Likert scale. Excellent
internal consistency has been demonstrated on the two composite scales
(α = 0.90), and the eight subscales have displayed adequate internal con-
sistency (α = 0.80) (17).
Patient Health Questionnaire Depression Scale (PHQ-8) (18) is a self-
administered questionnaire consisting of eight of the nine criteria for
Major Depressive Disorder (suicidality is omitted). Participants respond
to questions using a Likert scale, and these values are summed to obtain a
total depression score. Rohyans and Pressler reported adequate internal
consistence (α = 0.83) (19).
Perceived Stress Scale (20) is a self-report measure that assesses the
degree to which participants find their lives to be uncontrollable, unpre-
dictable, and overloading. Participants respond to items assessing stress-
ful thoughts and perceptions within the last month. The response format
is a 5-point Likert. Good internal consistency and test–retest reliability
(α = 0.85) has been established (20).
Initial weight loss intervention (phase I)
During phase I, a trained behavioral interventionist led 20-weekly
group sessions conducted over ~6 months. Intervention goals were
180 min/week of MVPA, reduced caloric intake, consumption of the
Dietary Approaches to Stop Hypertension (DASH) dietary pattern
which reduces CVD risk factors (21–24), and weight loss of ~1–2 lb/
week. The intervention was based on behavior change theory (25,26)
and incorporated behavior change tools such as self-monitoring,
goal-setting, social support, problem solving, relapse prevention, and
Maintenance interventions (phase II)
The goals of the internet-based technology intervention and personal
counseling interventions were maintenance of the phase I weight loss
(or loss of additional weight if desired), continued adherence to the rec-
ommended dietary pattern, and increasing MVPA to at least 225 min/
week. Both active interventions reinforced the behavioral theory and
tools of phase I. SD participants received lifestyle advice at randomiza-
tion and again after the 12-month data collection visit (10). Treatment
group results have been reported elsewhere (9). Briefly, the personal
counseling intervention was superior to SD for 30 months following
randomization. Internet-based technology intervention was superior
to SD through 24 months, but not at 30 months. We observed no sig-
nificant race–sex by treatment interactions and treatment effects were
modest. Therefore in this secondary analysis to identify correlates of
long-term weight loss within demographic subgroups, data from par-
ticipants in personal counseling intervention, internet-based technol-
ogy intervention, and SD have been combined.
The primary focus of this article is on predictors of weight change over
the entire 3-year period from study entry to the end of phase II. We
express weight change as a continuous variable (i.e., percent weight
change from entry) and as two dichotomous variables (whether weight
at end of study was (i) below entry weight and (ii) at least 5% below
entry weight). Based on effects on blood pressure (5,27) and diabetes
risk (28) shown in previous studies, we considered 5% weight loss to
be clinically significant on an individual basis. In order to assess poten-
tial determinants of weight loss maintenance (i.e., after initial weight
loss), we also evaluated the percent change in weight over the 30-month
period from randomization to the end of phase II. We also report
changes in diet and PA.
Participants randomized into phase II are included in this analy-
sis, stratified into four race–sex subgroups: Black men (BM), BW,
and non-BM and women. Ninety-eight percent of non-blacks were
VOLUME 20 NUMBER 9 | sEptEMBER 2012 | www.obesityjournal.org
intervention and Prevention
self-identified white, and therefore for purposes of this analysis,
non-blacks are referred to as white men (WM) and white women
We used multiple linear regression (continuous outcomes) or logistic
regression (binary variables) to compare weight change outcomes across
race–sex groups while adjusting for site and entry weight. Comparison
of weight changes during phase II also adjusted for weight change dur-
ing phase I.
We fit two reverse stepwise regression models to identify predictors
of 3-year percent weight change. The first included only baseline (study
entry) characteristics and phase I weight loss. The second included
baseline characteristics and change in diet and PA from entry to end
of the study. We fit these models both overall and within each race–sex
subgroup. To identify predictors of percent weight change during phase
II, we fit a reverse stepwise regression model that included entry char-
acteristics and changes in diet, PA, and psychosocial variables during
table 1 entry characteristics of randomized participants
Black men Black womenWhite men White women
N who started phase I196 540 355594
% who entered phase II62%49%72% 65%
N who started phase II121 267257387
Age in years, mean (s.d.)53 (9) 53 (9)58 (9) 57 (8)
BMI in kg/m2, mean (s.d.)34.4 (4.5) 35.3 (5.0)33.4 (4.2) 33.5 (4.9)
Weight in kg, mean (s.d.)108.3 (16.2) 94.8 (15.2)104.2 (15.3)89.5 (14.5)
Overweight (BMI 25–29.9), %20 17 24 28
Obese (BMI ≥30), % 808376 72
College degree or higher, %69 56 7256
Household income ≥$60 k/year, %7442 7154
On BP meds (%) 899483 84
Number of BP meds (among those on BP meds), mean (s.d.) 2.0 (0.9)1.9 (0.9) 1.8 (0.8)1.7 (0.8)
On lipid-lowering meds, % 4224 5341
Current smoker, %3535
QOL: mental, mean (s.d.)54.8 (6.8)53.0 (8.6) 53.7 (7.5)51.5 (9.3)
QOL: physical, mean (s.d.)51.2 (7.6)50.6 (8.0)51.5 (7.5)49.6 (8.0)
Social support for diet, mean (s.d.)
Encouragement from family20.5 (8.3)18.1 (8.8)18.9 (7.4)16.4 (7.0)
Discouragement from familya
14.7 (4.5)15.4 (5.4)13.9 (3.7)14.5 (4.8)
Encouragement from friends16.0 (6.9)17.7 (8.0)12.8 (5.2) 14.1 (5.6)
Discouragement from friendsa
13.7 (4.3)14.9 (5.1)12.7 (3.1)13.3 (3.5)
Social support for exercise score, mean score (s.d.)
Encouragement from family29.0 (10.9)27.2 (11.2)29.4 (9.5) 28.0 (10.3)
Encouragement from friends17.3 (8.2)19.4 (9.7) 14.5 (6.3)17.1 (8.2)
Perceived stress, mean (s.d.)3.7 (2.5)4.1 (2.8)3.4 (2.2)4.6 (2.8)
Depression score, mean (s.d.)2.5 (3.0)3.3 (3.7)3.1 (3.1) 4.4 (3.8)
Number of times participant previously lost ≥ 10 lbs, %
1–5 times6667 6961
6 or more times724 2034
Maximum amount of weight loss from previous attempts, %
≤20 lbs7557 5041
Difference between current weight
and “best weight for me,” mean lb (s.d.)
19.6 (11.5)23.5 (11.7)20.1 (10.5)23.5 (11.8)
BP, blood pressure; QOL, quality of life.
aCoded so that higher discouragement score means less discouragement.
obesity | VOLUME 20 NUMBER 9 | sEptEMBER 2012 1823
intervention and Prevention
both phase I and phase II. Given the large number of variables included
in the modeling process and our lack of a priori hypotheses regarding
interactions, no attempt was made to formally test (i.e., via interactions)
for differences in the models across race–sex subgroups.
One potential predictor (frequency of weighing) was self-reported
retrospectively at the end of the study. Given the limitations of
retrospective self-report, we calculated Pearson correlation coeffi-
cients between this variable and weight changes, but did not include
it in regression models.
In order to adjust for potential biases due to nonrandom loss to follow-
up, we used multiple imputation (29) to replace missing end of study
weights (for 68 individuals) and selected other measures. Only data miss-
ing due to participant death (N = 3) were not imputed; these individuals
are excluded from this analysis. The multiple imputation methodology
involves creating not just one, but several (in our case five) imputations so
that the analysis can properly reflect the added variability in our regres-
sion estimates that is due to the variation in the imputation process itself.
For the stepwise regression modeling, we used just one of the imputed
datasets to derive the final models, but all five imputation datasets to esti-
mate the parameters and their standard errors in those models. We also
performed the predictor analyses in those with follow-up data, without
imputing any missing data. All analyses were conducted using SAS, ver-
sion 9.1 (SAS Institute, Cary, NC), and all P values are two-sided. Unless
otherwise noted, we used LSMEANS to calculate model-based means
for the data in all figures and tables.
Approximately 12% of phase II participants were BM, 26% BW,
25% WM, and 37% WW (Table 1). Participants were middle-
aged, with blacks younger than whites. Mean BMI at entry
ranged from 33.4 kg/m2 in WM to 35.3 kg/m2 in BW. Most
participants were on antihypertensive medication, taking an
average of two medications. For both blacks and whites, the
discrepancy at entry between self-identified “best weight for
me” and measured weight was lower for men than women.
Final data collection was complete in 93% of BM, 91% of BW,
96% of WM, and 93% of WW.
Although by definition all phase II participants met the cri-
terion of phase I weight loss of at least 4 kg, phase I weight loss
was significantly greater in BM than BW, in WM than in WW,
and in both WM and WW than in their black counterparts
(Table 2). Following the initial weight loss (i.e., in phase II),
mean weight increased in each race–sex group, but remained
significantly lower than entry weight (Figure 1). Statistically
significant differences among race–sex subgroups were evident
at each time-point through 12 months. Percent weight change
from entry to end of study ranged from −2.3% (95% confi-
dence interval −3.1 to −1.5) in BW to −4.5% (95% confidence
interval −5.7 to −4.0) in WM. Within each race group, men
lost more weight than women (BM vs. BW, P = 0.02; WM vs.
WW, P < 0.001), but within each sex group, weight loss did not
differ significantly between races (BM vs. WM, P =0.25; BW
vs. WW, P = 0.06). The data displayed in Table 2 also dem-
onstrate that, despite these differences in weight change from
entry to end of study, weight change from randomization to
end of study (i.e., during phase II) did not differ significantly
across race–sex groups (P = 0.22). Over 65% of participants in
each race–sex group ended the study at or below their entry
weight, and a substantial proportion in each race–sex group
also maintained clinically significant weight loss (i.e., weight
≥5% lower than entry weight) through the end of the study
(Table 2). As with percent weight change from entry, these
dichotomous outcomes also varied significantly across the four
Table 3 shows attendance and behavioral measures of inter-
vention adherence for each race–sex subgroup. All subgroups
increased their MVPA in phase I, with near complete recidi-
vism in phase II. These changes did not differ significantly
table 2 Weight outcomes by race–sex subgroup
Black men Black womenWhite menWhite women
Mean (95% CI) % change during phase I−8.1 (−8.8, −7.3)* −7.7 (−8.1, −7.2)*−10.3 (−10.8, −9.8)* −8.7 (−9.1, −8.3)*<0.0001
Mean (95% CI) % change from entry
to end of study
−4.0 (−5.2, −2.8)*−2.3 (−3.1, −1.5)* −4.5 (−5.7, −4.0)*−3.3 (−4.0, −2.6)* 0.0002
Mean (95% CI) % change, from
randomization to end of study
4.8 (3.6, 6.1)* 6.3 (5.5, 7.1)*5.6 (4.7, 6.4)*6.1 (5.4, 6.8)* 0.22
Percentage of participants at or below
entry weight at end of study
Percentage of participants at least 5%
below entry weight at end of study
CI, confidence interval.
aThree degree-of-freedom P value for comparing race–sex groups based on linear regression (continuous data) or logistic regression (binary data) after adjusting for site,
entry weight, and (for % change from randomization).
*P ≤ 0.01 that change from entry weight ≠ 0, within subgroup.
−606 1218 2430
Time from randomization
Weight change, %
Figure 1 percent weight change from entry by race–sex subgroup over
time. Mean % with s.e. *P = 0.01; **P < 0.0001; P values for comparing
race–sex groups at each time-point adjusted for site and entry weight.
BM, black men; BW, black women; WM, white men; WW, white women.
VOLUME 20 NUMBER 9 | sEptEMBER 2012 | www.obesityjournal.org
intervention and Prevention
across race–sex groups. Dietary changes also showed improve-
ments in phase I, with about half of the improvement reversed
in phase II in all groups. In general, whites had greater dietary
improvement in phase I, but also greater recidivism in phase
II. Participants were asked at the final data collection visit to
retrospectively report their frequency of self-weighing dur-
ing the previous 30 days. Participants reported self-weighing
approximately once per week.
Table 4 shows the results of multivariate regression mod-
eling to determine associations of demographic, behavio-
ral, psychosocial, and physiological factors present at entry
or subsequently with percent weight change. For each sub-
group, phase I weight loss was strongly and positively associ-
ated with weight loss over the entire 3 years (model 1). Every
1% of weight loss during phase I was associated with 0.66%
weight loss over the entire 3-year period, with parameter
estimates ranging from 0.57 to 0.85% in the four race–sex
subgroups (data not shown; see Supplementary Methods
and Procedures for parameter estimates). Unexpectedly, the
presence at entry of social support for diet and/or exercise
was inversely associated with long-term weight loss in the
population overall and in both WM and WW. No other fac-
tors present at entry were consistently associated with long-
term weight loss.
When we replaced phase I weight loss with changes in diet
and MVPA from entry to end of study (model 2), we found
that a healthier dietary pattern (either at study entry or
improvements in the HEI over time) was predictive of long-
term weight loss in the study population overall and in BW,
WM, and WW. Increased MVPA over the course of the study
predicted improved weight loss only in the group overall and
in WM. In this model no factors were predictive of long-term
weight loss in BM.
In models performed without imputing missing data (data
not shown), predictors were similar, with some exceptions: in
the group overall, entry-level HEI was no longer significant in
model 1 but remained significant in model 2. In BW, entry-
level HEI remained significant in model 2 but change in HEI
was no longer significant in this model. In WM, entry-level
MVPA became significant in model 1, but change in MVPA
became marginally significant (P = 0.06) in model 2. Because
of the potential for bias due to nonrandom loss to follow-up, we
based our interpretation on the primary analysis with imputa-
tion of missing values (above).
Because it was based on retrospective reporting, we did not
include frequency of self-weighing in the models. However, in a
correlation analysis more self-reported weight monitoring was
associated with more weight loss from entry to end of study,
table 3 Intervention adherence measures
Black men Black women White menWhite women
Attendance at phase I groups,
number of groups
17.5 (0.2) 17.6 (0.1) 17.8 (0.1)17.9 (0.1)0.09
Food and PA records during phase I,
number of weeks records kept
14.0 (0.4) 13.8 (0.3)15.7 (0.3) 15.3 (0.2)
Physical activity, MVPA min/week Phase I entry147.1 (10.1)85.5 (6.8)161.7 (7.0) 100.3 (5.7)
Change during phase I37.9 (13.1) 60.1 (8.9) 53.9 (9.1)34.1 (7.4) 0.10
Change during phase II −29.6 (14.5) −40.1 (9.7)−47.9 (10.0) −32.6 (8.1)0.59
Fruits and vegetables,
Phase I entry 4.6 (0.3)5.1 (0.2) 5.2 (0.2)5.7 (0.1) 0.001
Change during phase I 3.3 (0.4)3.1 (0.2)3.8 (0.3) 4.2 (0.2) 0.01
Change during phase II−1.5 (0.4) −1.8 (0.2)−1.9 (0.2)−2.6 (0.2) 0.02
Dairy, servings/day Phase I entry0.77 (0.1)0.69 (0.1) 1.4 (0.1)1.4 (0.1)
Change during phase I0.3 (0.1)0.4 (0.1)0.4 (0.1)0.5 (0.1) 0.38
Change during phase II−0.1 (0.1)−0.2 (0.1)−0.2 (0.1)−0.3 (0.1) 0.06
%kcal fatPhase I entry 38.8 (0.7)38.4 (0.4)39.3 (0.5) 38.5 (0.4)0.39
Change during phase I−6.6 (0.7) −7.3 (0.5)−9.3 (0.5) −9.4 (0.4)0.001
Change during phase II 3.0 (0.7)2.8 (0.5)4.3 (0.5)4.4 (0.4) 0.03
Healthy Eating Index Phase I entry59.8 (1.1) 60.4 (0.7)61.9 (0.8) 64.9 (0.6)
Change during phase I 13.1 (1.1)12.4 (0.8) 15.8 (0.8)14.1 (0.6) 0.01
Change during phase II −6.0 (1.0)−5.8 (0.7) −5.8 (0.7)−6.4 (0.6) 0.77
Frequency of weighing, times/week Based on retrospective
2.7 (0.1)3.0 (0.1) 2.4 (0.1)2.6 (0.1)
MVPA, moderate-to-vigorous physical activity; PA, physical activity.
aThree degree-of-freedom P value for comparing race–sex groups based on linear regression after adjusting for site.
obesity | VOLUME 20 NUMBER 9 | sEptEMBER 2012 1825
intervention and Prevention
with correlation coefficients ranging from 0.21 to 0.25 across
the four race–sex subgroups (P < 0.05 for each subgroup).
In a large, diverse cohort of adults who successfully lost weight
during a 6-month intensive behavioral intervention, initial
(phase I) weight loss was a consistent predictor of long-term
weight loss in each race–sex group. Beyond initial weight loss,
we identified few additional predictors of long-term weight
loss either in the group overall or within race–sex subgroups.
In the group of BM, no potentially modifiable variables beyond
initial weight loss were associated with weight change from
entry to end of study. Nonetheless, in each subgroup, over 65%
ended the study at entry weight or lower, and over 34% ended
at least 5% below entry weight.
The study population is a particular strength of this study,
consisting of large numbers of both men and women, blacks
and whites. The eligibility criteria defined a population at high
risk of CVD events, and thus defined a population who may
derive the greatest CVD risk reduction from successful weight
loss. The focus on predictors of weight loss maintenance in
individuals who successfully lost weight during phase I is an
additional strength. Although predictors in this population
may not necessarily apply to all high-risk adults who are over-
weight/obese and attempt weight loss, they may generalize to
the substantial numbers who initiate weight loss and are suc-
cessful over the short term. Weight regain is common, with
presumed reversal of health benefits. Sustained weight control
is the ultimate goal of all weight loss interventions.
In BW as well as WM and WW, healthier eating habits
(i.e., similar to the DASH dietary pattern (21)) at entry, and
improvement in dietary pattern over time, were associated with
more weight loss over the entire 3 years, and with less weight
regain in phase II. Randomized trials of different dietary pat-
terns in weight loss interventions suggest that in general, diet
composition is not a strong determinant of weight loss (30,31).
However, in WLM, we stressed using the DASH dietary pat-
tern while restricting calories to lose weight because the DASH
dietary pattern also directly improves CVD risk factors inde-
pendent of weight loss (23,32). The association between higher
HEI score, which reflects a dietary pattern similar to DASH
(12) and weight loss maintenance suggests that individuals
who are adherent to recommendations concerning dietary pat-
tern may also be more adherent to recommendations concern-
ing caloric restriction (33). It also suggests that weight loss can
be maintained in the context of a dietary pattern consistent
with current dietary guidelines (34).
Surprisingly, MVPA was not related to either long-term
weight loss from entry to end of study or weight regain dur-
ing phase II, except in WM. Self-report data from a registry
of successful weight losers suggest that MVPA is a critical fac-
tor in long-term weight loss maintenance (35). However, these
registry data indicate an association between weight loss main-
tenance and high levels of MVPA (e.g., 225 min/week), and
table 4 Variables significantly associated with more weight loss from entry into phase I to end of study
Model 1. Variables associated with more weight loss, entry into phase I to end of study (model includes phase I weight loss)
Entry Phase I
More phase I
Black men0.18 (<0.001)———
Black women0.23 (<0.001)
White men0.27 (<0.001)—
White women 0.21 (<0.001)————
Model 2. Variables associated with more weight loss, from entry into phase I to end of study (model includes behavior change from entry
into phase I to end of study)
EntryChange from entry to end of study
HEI scoreIncrease in MVPA
Black men0.10 (0.02)———————
Black women0.08 (<0.001)
White men 0.19 (<0.001)——
White women 0.08 (<0.001)————
All models are based on backward selection and include the following variables measured at entry into phase I: age, weight, education, income, smoking status, treat-
ment for hypertension and/or dyslipidemia, quality of life, social support for diet and exercise, perceived stress, depression, weight loss history, perceived discrepancy
between current weight and desired weight, and participant’s expected weight loss during phase I. Model 1 also includes phase I weight change. Model 2 includes
change in physical activity (PA) and change in Healthy Eating Index (HEI) over the entire course of the study (i.e., from phase I entry to 30 months post-randomization),
but does not include phase I weight change.
Variables retained in model if P ≤ 0.10 but included in table only if P value in final model ≤0.05 (marked with √ ).
Coefficients based on 5-imputation datasets.
VOLUME 20 NUMBER 9 | sEptEMBER 2012 | www.obesityjournal.org
intervention and Prevention
the majority of WLM participants did not achieve this level
of activity. In addition, on average, there was almost complete
MVPA recidivism during phase II of WLM, so that MVPA at
the end of the study was similar to entry levels. Our data sug-
gest that the general adherence to a higher quality diet even
in the setting of lower levels of PA helped to maintain moder-
ate energy balance. However, it is possible that an even greater
proportion would have sustained this level of weight loss if
increased MVPA had been sustained. Future prospective trials
are needed to determine if increased adoption of current PA
recommendations leads to more sustained weight loss, and if
effects differ based on patient characteristics.
Observed associations between social support and weight
loss were complex and inconsistent across race–sex subgroups.
If anything, contrary to expectation, our data suggest that
entry-level social support from family and friends may have
inhibiting effects on long-term weight loss efforts. However,
cause and effect cannot be determined from this study. It may
be that the social support questionnaires used in this study do
not adequately detect nuances of the social interactions that
affect long-term behavior change. Alternatively, higher levels
of social support at entry may identify people who rely more
heavily on social support and who therefore may be more vul-
nerable to weight regain if the support wanes over time, com-
pared to those with lower levels of social support at entry who
nonetheless succeed at initial weight loss. In addition, because
our social support measures assessed support for PA and
dietary behaviors rather than social support for maintaining
weight loss, it may not have been the ideal assessment tool.
And finally, in a study of African Americans, Kumanyika et al.
reported that involving family/friend partners in a weight loss
program was favorable to success only when the family/friend
partners also lost weight or attended personal counseling ses-
sions with the participant (36). Gorin et al. reported a similar
finding in a primarily white population (37). More research
is needed to correctly specify appropriate social support for
weight loss maintenance.
Our finding that self-weighing is associated with weight loss
maintenance must be interpreted with caution since it is based
on retrospective self-report. However, it is consistent with
other evidence that self-monitoring in general is associated
with greater weight control. For example, in WLM, self-mon-
itoring of diet and MVPA was associated with phase I weight
loss (6), and observational studies have suggested a similar
effect for self-monitoring of weight. Future research should
prospectively establish the effectiveness of self-weighing and
the optimal frequency of weight self-monitoring for sustained
The absence of significant predictors in BM is likely due to
several factors, including the lower power in this relatively
small subgroup, which was less than half the size of the other
race–sex groups. It is also likely that we did not measure other
variables of particular relevance in this subgroup. In addition,
there is little data on the reliability and validity of some of our
potential predictors in race–sex subgroups, although what
little data exist suggest comparable reliability in blacks and
whites (16,38–40). Some observational studies have reported
better weight loss maintenance in blacks than whites and have
identified some predictors that may apply to this subgroup as
well as others (41–43). Although observational data provide
clues to other potentially useful variables or assessment instru-
ments, it is also possible that predictors of weight loss mainte-
nance in observational studies differ from those for some or all
subgroups of clinical trial participants, who by definition meet
particular eligibility criteria and are exposed to a particular
intervention. It is important to note that although we did not
identify predictors of maintenance in BM, they were nonethe-
less successful at maintaining weight loss over the course of
the study, with 71.9% remaining below entry weight and 34.5%
remaining at least 5% below entry weight.
Our lack of assessment of either environmental variables
(such as food marketing and the built environment) or of
family context is a limitation of the study that may have been
particularly relevant to blacks. In an ancillary study to WLM,
Samuel-Hodge found that family emotional involvement and
family cohesion were associated with greater phase I weight
loss in blacks but not in whites (44). The role of family in long-
term maintenance is unknown. The broader social context
may also play a role in all subgroups: the majority of adults in
America are overweight or obese (45), and social norms may
both influence and be influenced by the prevalence of obes-
ity. (46). For example, the fact that most social interaction is
likely to be with other overweight/obese individuals may make
weight loss more challenging. Understanding the influence of
environmental, family, and social context on weight loss efforts
overall and within race–sex subgroups can potentially improve
behavioral intervention strategies.
A key finding was that a substantial proportion of each
race–sex subgroup maintained a clinically significant amount
of weight loss over 3 years. Though the weight loss was mod-
est, this finding is consistent with weight loss in the Lifestyle
Intervention arm of the Diabetes Prevention Project (7). Even
relatively modest weight loss leads to substantial improvements
in cardiovascular risk factors. For example, 5% weight loss in
a high-risk population leads to a 58% reduction in diabetes
incidence (7), a 42% reduction in hypertension incidence (47),
and an estimated 13% reduction in 10-year risk of coronary
heart disease (48). Given the high CVD risk of the WLM par-
ticipants (based on presence of risk factors), the proportion of
participants with sustained weight loss suggests the potential
for significant reduction in morbidity and mortality.
These results must be generalized with caution: the WLM
participants successfully lost at least 4 kg during phase I of the
study. Therefore, strictly speaking, the results of this analysis are
only generalizable to high-risk adults who have already achieved
weight loss. Predictors in this population may or may not gener-
alize to all adults who are overweight/obese. However, large num-
bers of overweight/obese individuals achieve short-term weight
loss, and our results can inform strategies for helping them to
sustain that weight loss. However, we recognize that sustaining
weight loss over 3 years after initial weight loss, as in WLM, may
not be long enough for optimal health outcomes (49).
obesity | VOLUME 20 NUMBER 9 | sEptEMBER 2012 1827
intervention and Prevention
In summary, this analysis suggests that intervention strat-
egies for achieving and sustaining clinically significant long-
term weight loss in diverse populations should focus on
achieving greater initial weight loss and eating a healthy diet
such as the DASH dietary pattern. Future research should
clarify the potential for MVPA and self-monitoring to improve
weight loss maintenance, and should identify other modifiable
factors that promote long-term weight management in general
and in each race–sex subgroup.
supplementary material is linked to the online version of the paper at http://
the Weight Loss Maintenance trial was sponsored by National Heart, Lung,
Blood Institute grants 5-U01 HL68734, 5-U01 HL68676, 5-U01 HL68790,
5-U01 HL68920, and 5-HL68955.
the authors declared no conflict of interest.
© 2011 The Obesity Society
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