Behavioral Weight Loss Program Research Articles

Behavioral Weight Loss: A Promising Treatment for Obesity in Adults with HIV.

Obesity and chronic disease are growing problems among people living with HIV (PLWH) across the globe. While a variety of treatments have been developed to address cardiovascular and metabolic disease among PLWH, few treatments have focused on helping PLWH and obesity lose weight. In the general population, behavioral weight loss interventions (i.e., diet, physical activity, and behavior therapy) are the first-line treatment for adults for whom weight loss is recommended. However, little research has tested whether the benefits of these programs translate to PLWH. This paper highlights the key components of behavioral weight loss programs, their outcomes in the general population and in the few studies of PLWH, and suggestions for tailoring these programs for PLWH. Behavioral weight loss programs are a strong potential treatment for reducing the burden of obesity among PLWH and merit future research attention.

Association of Weight Loss Interventions With Changes in Biomarkers of Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) affects about 25% of adults worldwide and is associated with obesity. Weight loss may improve biomarkers of liver disease, but its implications have not been systematically reviewed and quantified. To estimate the association of weight loss interventions with biomarkers of liver disease in NAFLD. MEDLINE, Embase, PsycINFO, CINAHL, Cochrane, and Web of Science databases along with 3 trial registries were searched from inception through January 2019. Randomized clinical trials of people with NAFLD were included if they compared any intervention aiming to reduce weight (behavioral weight loss programs [BWLPs], pharmacotherapy, and surgical procedures) with no or lower-intensity weight loss intervention. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Two independent reviewers screened the studies, extracted the data, and assessed the risk of bias using the Cochrane tool. Pooled mean differences or odds ratios (ORs) were obtained from random-effects meta-analyses. Blood, radiologic, and histologic biomarkers of liver disease. Twenty-two studies with 2588 participants (with a mean [SD] age of 45 [14] years and with approximately 66% male) were included. Fifteen studies tested BWLPs, 6 tested pharmacotherapy, and 1 tested a surgical procedure. The median (interquartile range) intervention duration was 6 (3-8) months. Compared with no or lower-intensity weight loss interventions, more-intensive weight loss interventions were statistically significantly associated with greater weight change (-3.61 kg; 95% CI, -5.11 to -2.12; I2 = 95%). Weight loss interventions were statistically significantly associated with improvements in biomarkers, including alanine aminotransferase (-9.81 U/L; 95% CI, -13.12 to -6.50; I2 = 97%), histologically or radiologically measured liver steatosis (standardized mean difference: -1.48; 95% CI, -2.27 to -0.70; I2 = 94%), histologic NAFLD activity score (-0.92; 95% CI, -1.75 to -0.09; I2 = 95%), and presence of nonalcoholic steatohepatitis (OR, 0.14; 95% CI, 0.04-0.49; I2 = 0%). No statistically significant change in histologic liver fibrosis was found (-0.13; 95% CI, -0.54 to 0.27; I2 = 68%). Twelve studies were at high risk of bias in at least 1 domain. In a sensitivity analysis of the 3 trials at low risk of bias, the estimates and precision of most outcomes did not materially change. The trials, despite some heterogeneity, consistently showed evidence of the association between weight loss interventions and improved biomarkers of liver disease in NAFLD in the short to medium term, although evidence on long-term health outcomes was limited. These findings appear to support the need to change the clinical guidelines and to recommend formal weight loss programs for people with NAFLD.

A Gender- and Culturally Sensitive Weight Loss Intervention for Hispanic Men: Results From the Animo Pilot Randomized Controlled Trial.

Background. Hispanic males have the highest rates of overweight and obesity compared with men of all other racial/ethnic groups. While weight loss can significantly reduce obesity-related health risks, there is limited research examining effective gender- and culturally tailored behavioral weight loss programs for Hispanic men. Objective. To assess the feasibility and preliminary efficacy of a 12-week gender- and culturally sensitive weight loss intervention (GCSWLI) as compared with a waist-list control (WLC) in sedentary, Hispanic males with overweight/obesity. Method. Fifty Hispanic males (age: 43 years [SD = 11]; BMI: 34 ± 5 kg/m2; 58% Spanish monolingual) were randomized to one of two groups: GCSWLI (n = 25) or WLC (n = 25). GCSWLI participants attended weekly in-person individual sessions with a bilingual, bicultural Hispanic male lifestyle coach, and were prescribed a daily reduced calorie goal and 225 minutes of moderate-intensity physical activity per week. The WLC were asked to maintain their usual diet and physical activity habits for 12 weeks. GCSWLI participants continued with 12 additional weeks of follow-up including biweekly phone calls with lifestyle coaches. Results. At Week 12, the mean weight loss in the GCSWLI was -6.3 kg (95% confidence interval [CI; -8.1, -4.4]) compared with -0.8 kg (95% CI [-2.5, 0.9]) for the WLC (difference = -5.5 kg, 95% CI [-8.0, -2.9], p < .01). At Week 24, weight loss in the GCSWLI was maintained. Conclusions. The GCSWLI appears to be a feasible strategy to engage Hispanic males in short-term weight loss. Our pilot study indicates preliminary evidence of efficacy, though confirmation of these findings is needed in a larger study.

Lessons Learned from the POUNDS Lost Study: Genetic, Metabolic, and Behavioral Factors Affecting Changes in Body Weight, Body Composition, and Cardiometabolic Risk.

This paper reviews the genetic and non-genetic factors that provided predictions of, or were associated with, weight loss and other metabolic changes in the POUNDS Lost clinical trial of weight loss. This trial randomized 811 individuals who were overweight or obese to one of four diets that contained either 15% or 25% protein and 20% or 40% fat in a 2× 2 factorial design. A standard behavioral weight loss program was available for all participants who were followed for 2years with an 80% completion rate. Nineteen genes and five genetic risk scores were used along with demographic, behavioral, endocrine, and metabolic measurements. Genetic variations in most of the genes were associated with weight loss, but this association often varied with the dietary assignment. A number of demographic and behavioral factors, including attendance at behavioral sessions and food cravings were predictive of weight changes. A high baseline level of free triiodothyronine or free thyroxine predicted the magnitude of weight loss. Several perfluoroakyl compounds predicted more rapid weight regain. Genetic evidence from POUNDS Lost provides guidance toward selection of a personalized weight loss diet and improvement in metabolic profile. There is still room for additional research into the predictors of weight loss.

Differences in Sleep Quality and Adherence to Energy Intake and Physical Activity Recommendations during an 18-Month Behavioral Weight Loss Intervention

PURPOSE: Long-term adherence to EI and PA recommendations during a behavioral weight loss interventions is difficult. It is possible that short sleep duration and/or poor sleep quality makes adherence to these recommendations challenging. In this analysis, we explored the association between sleep duration and sleep quality and adherence to EI and PA recommendations during an 18-month behavioral weight loss intervention. METHODS: Adults (n=104, age: 18-55 years, BMI: 27-42 kg·m-2) were enrolled in a behavioral weight loss program. Participants were prescribed a calorie-restricted diet (1200-1900 kcals/day) and were instructed to complete ≥300 min of moderate to vigorous physical activity (MVPA) per week. In this post-hoc analysis, participants were grouped based on adherence to EI (measured using 3-day food records) and PA (measured using the SenseWear armband) recommendations at 18-months. Adherence to the EI recommendation was defined eating ≤ individually prescribed calories determined using a validated prediction equation at 18 months. Adherence to the PA recommendation was defined as accumulating ≥300 min/week of MVPA in bouts of ≥10 min at 18 months. Sleep duration, sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency were calculated at baseline and 18 months using the armband. RESULTS: Individuals who were adherent to both the EI and PA recommendations had significantly lower WASO at baseline (65.7±11.2 min) compared to non-adherent individuals (82.9±49.1 min; p<0.05). Individuals who were adherent to only the EI recommendation had significantly lower WASO (61.0±30.7 min) at baseline compared to those who did not meet the EI recommendation (81.5±44.0 min; p<0.05). Individuals who were adherent to only the PA recommendation had significantly lower SOL (37.0±21.1 min) at baseline compared to individuals who did not meet the PA recommendation (44.2±28.4 min; p<0.05). There were no differences in sleep duration or sleep efficiency between any of the groups. CONCLUSIONS: Sleep quality at the beginning of an 18-month weight loss intervention may influence adherence to EI and PA recommendations during the behavioral intervention. Future behavioral weight loss interventions may be improved by focusing on improving sleep quality in addition to EI and PA.

Triggers of Lapse and Relapse of Diet and Exercise in Behavioral Weight Loss.

This study aimed to (1) develop instruments to evaluate situations that lead to lapse and relapse in diet and exercise and (2) prospectively investigate when and which psychosocial situations predict failure to lose weight in a clinical trial of intentional weight loss. Participants were 469 individuals with overweight or obesity participating in a behavioral weight loss program (age: mean=53.6years, SD=11.4; BMI: mean=35.7kg/m2 , SD=6.5). The Cronbach alphas for the Diet Lapse and Relapse Triggers Scale and the Exercise Lapse and Relapse Triggers Scale were 0.93 and 0.91, respectively. Subscale alphas ranged from 0.60 to 0.96. Lapse and relapse were assessed at 3 and 9months for associations with weight loss at 12months. At 9months, diet triggers were negative emotional states (beta=0.11, P=0.02) and urges (beta=0.14, P=0.01). Predicted social situations showed the opposite (beta=-0.09, P=0.02). Exercise subscales were all nonsignificant. Findings suggest the ongoing importance of addressing negative emotional states and the contributing influence of urges. The novel finding that participants whose difficulties arise in social situations may do better over time requires further study.

Change in behavioral exercise program-associated self-regulation enhances self-regulation-induced eating improvements across levels of obesity severity

Architects of behavioral weight-loss programs require improved understandings of psychosocial correlates of healthy eating behaviors to improve overwhelmingly poor outcomes. Exercise might benefit eating changes through a transfer of self-regulatory skill improvements. However, related research is minimal, and degrees of obesity might influence the utilization and efficacy of self-regulatory processes. Women of Class 1 obesity (body mass index [BMI] = 30–34.9 kg/m2; n = 53), Class 2 obesity (BMI = 35–39.9 kg/m2; n = 41), and Class 3 obesity (BMI ≥ 40 kg/m2; n = 53) enrolled in a community-based cognitive-behavioral weight-management program were assessed over 6 months on changes in exercise, self-regulation for both exercise and eating, and the consumption of fruits/vegetables and sweets. Within-group improvements were all significant, with the greater self-regulation changes consistent with lower degrees of obesity. Within serial multiple mediation analyses, the hypothesized path from exercise change→self-regulation for exercise change→self-regulation for eating change→eating behavior change was supported in both the prediction of changes in fruit/vegetable intake and sweets consumption. However, the direct effect of increased exercise on improved eating was not significant. BMI score or obesity class did not significantly moderate embedded relationships among variables. Findings suggested weight-loss programs incorporate supported exercise, and dedicate high proportions of their curricula to the development of self-regulatory skills.

Effect of Obesogenic Medications on Weight-Loss Outcomes in a Behavioral Weight-Management Program.

Objective:We aimed to evaluate a possible association between the use of obesogenic medications and inadequate weight loss in a behavioral weight management program.Methods:This is a case-control, single-center, study of 666 adult patients within Veterans Health Administration health system that participated in the MOVE! behavioral weight loss program. We divided our cohort into responders (n=150), patients who achieved ≥5% total weight loss by the end of MOVE! program, and non-responders (n=516), <5% totalResults:Approximately 62% (n = 411) of patients entering MOVE! had a prescription for obesogenic medications. Obesogenic medication use was associated with worse weight loss outcomes, and participants were 37% less likely to achieve a clinically meaningful (≥5% total weight loss) outcome at the end of the MOVE! program (odds ratio, 0.633; 95% CI, 0.427–0.937; adjusted P = 0.022). Patients who received 3 or more medications n=72) had the greatest difficulty achieving 5% weight loss compared to the control group (odds ratio, 0.265; 95% CI, 0.108–0.646; adjusted P = 0.003).Conclusions:The use of provider-prescribed obesogenic medications was associated with worse weight loss outcomes in a behavioral weight loss program. Closer scrutiny of patient medications is necessary to help improve outcomes of weight loss treatments.

Behavioral and Cardiovascular Effects of a Behavioral Weight Loss Program for People Living with HIV.

We recently reported that a 12-week internet weight loss program produced greater weight losses than education control in overweight/obese people living with HIV (PLWH) (4.4kg vs 1.0kg; p < 0.05). This manuscript presents the changes in diet, physical activity, behavioral strategies, and cardio-metabolic parameters. Participants (N=40; 21 males, 19 females) were randomly assigned to an internet behavioral weight loss (WT LOSS) program or internet education control (CONTROL) and assessed before and after the 12-week program. Compared to CONTROL, the WT LOSS arm reported greater use of behavioral strategies, decreases in intake (- 681kcal/day; p = 0.002), modest, non-significant, increases in daily steps (+ 1079 steps/day) and improvements on the Healthy Eating Index. There were no significant effects on cardio-metabolic parameters. The study suggests that a behavioral weight loss program increases the use of behavioral strategies and modestly improves dietary intake and physical activity in PLWH. Further studies with larger sample sizes and longer follow-up are needed.Clinical Trials Registration: NCT02421406.

The association between negative affect and physical activity among adults in a behavioral weight loss treatment

IntroductionMany individuals engaged in behavioral weight loss make suboptimal increases in moderate-to-vigorous physical activity (MVPA). Theoretically, reductions in negative affect could reinforce MVPA. However, little work has been done investigating the association between facets of negative affect (e.g., average levels of negative affect, variability in negative affect) and MVPA among individuals attempting to increase MVPA as part of a behavioral weight loss attempt. MethodsParticipants (n = 139) provided data at month 6 of a year-long behavioral weight loss program (at which point the prescription for MVPA had reached the highest level). Participants wore an accelerometer and provided EMA ratings of affect over the same week. ResultsIndividuals engaged in more frequent and longer periods of MVPA had lower average negative affect and variability in negative affect across the assessment period. Lower negative affect one day predicted greater time spent in MVPA on the next day; lower variability in negative affect than one’s average level also predicted greater time spent in MVPA on the next day. Greater engagement in MVPA than one’s own mean on one day did not predict mean or variability in affect. DiscussionEngaging in MVPA over time may reduce negative affect, while lower negative affect may increase motivation to engage in MVPA. Importantly, day-to-day effects indicated that affect is an important acute predictor of MVPA behavior. It is possible that individuals, particularly those with higher negative affect or variability in negative affect, may benefit from the inclusion of skills to manage negative affect in programs prescribing physical activity.

Cost of behavioral weight loss programs implemented in clinical practice: The POWER trial at Johns Hopkins.

Obesity presents an important public health problem that affects more than a third of the U.S. adult population and that is associated with increased morbidity, mortality, and costs. Previously, we documented that two primary care-based weight loss interventions were clinically effective. To encourage the implementation of and reimbursement for these interventions, we evaluated their relative cost-effectiveness. We performed a cost analysis of the Practice-based Opportunities for Weight Reduction (POWER) trial, a three-arm trial that enrolled 415 patients with obesity from six primary care practices. Trial participants were randomized to a control arm, an in-person support intervention, or a remote support intervention; in the two intervention arms, behavioral interventions were delivered over 24 months, in two phases. Weight loss was measured at 6, 12, and 24 months. Using timesheets and empirical data, we evaluated the cost of the in-person and remote support interventions from the perspective of a health care system delivering the interventions. A univariate sensitivity analysis was conducted to evaluate uncertainty around model assumptions. All comparisons were tested using independent t-tests. Cost of the in-person intervention was higher at 6 months ($113 per participant per month and $117 per kg lost) than the remote support intervention ($101 per participant per month and $99 per kg lost; p < .001). Costs were also higher for the in-person support intervention at 24 months ($73 per participant per month and $342 per kg lost) than for the remote support intervention ($53 per participant per month and $275 per kg lost; p < .001). In the sensitivity analyses, cost ranged from $274/kg lost to $456/kg lost for the in-person support intervention and from $218/kg to $367/kg lost for the remote support intervention. A primary care weight loss intervention administered remotely was relatively more cost-effective than an in-person intervention. Expanding the scope of reimbursable programs to include other cost-effective interventions could help ensure that a broader range of patients receive the type of support needed.

The equity impact of brief opportunistic interventions to promote weight loss in primary care: secondary analysis of the BWeL randomised trial

BackgroundGuidelines recommend that clinicians should make brief opportunistic behavioural interventions to patients who are obese to increase the uptake of effective weight loss programmes. The objective was to assess the effect of this policy on socioeconomic equity.MethodsOne thousand eight hundred eighty-two consecutively attending patients with obesity and who were not seeking support for weight loss from their GP were enrolled in a trial. Towards the end of each consultation, GPs randomly assigned participants to one of two 30-s interventions. In the active intervention (support arm), the GP offered referral to a weight management group. In the control intervention (advice arm), the GP advised the patient that their health would benefit from weight loss. Agreement to attend a behavioural weight loss programme, attendance at the programme and weight loss at 12 months were analysed by socioeconomic status, measured by postcode using the Index of Multiple Deprivation (IMD).ResultsMean weight loss was 2.43 kg (sd 6.49) in the support group and 1.04 kg (sd 5.50) for the advice only group, but these effects were moderated by IMD (p = 0.039 for the interaction). In the support arm, weight loss was greater in higher socioeconomic groups. Participants from lower socioeconomic backgrounds were more likely to accept the offer and equally likely to attend a weight loss referral but attended fewer sessions. Adjusting for these sequentially reduced the gradient for the association of socioeconomic status with weight loss from + 0.035 to − 0.001 kg/IMD point. In the advice only arm, 10% took effective action to promote weight loss. The decision to seek support for weight loss outside of the trial did not differ by socioeconomic status, but weight loss among deprived participants who used external support was greater than among more affluent participants (p = 0.025).ConclusionParticipants’ responses to GPs’ brief opportunistic interventions to promote weight loss differed by socioeconomic status and trial arm. In the support arm, more deprived people lost less weight because they attended fewer sessions at the programme. In the advice arm, more deprived people who sought and paid for support for weight loss themselves lost more weight than more affluent people who sought support.Trial registrationThis trial is registered with the ISRCTN registry, number ISRCTN26563137. Date of registration: January 3, 2013; date of first participant recruited: June 4, 2014

Executive Function, Eating Behavior, and Preoperative Weight Loss in Bariatric Surgery Candidates: An Observational Study

Background: Individual differences in executive function may influence eating behavior, weight loss (WL), and WL maintenance in obesity treatment. Executive function, which designates top-down cognitive control processes, has been related to eating behaviors which may impact weight, and has been found to be predictive of WL in both behavioral WL programs and after bariatric surgery. Currently, we lack knowledge on the role of executive function in the period before bariatric surgery. If executive function impacts eating behavior and WL in the preoperative period, it may be a target for clinical attention in this stage. Objectives: We aimed to examine the relationship between objective performance-based measures of executive function, eating patterns, and WL in the preoperative period. Method: Baseline data in an ongoing observational longitudinal study of bariatric surgery patients were used. Eighty patients completed neuropsychological testing and self-report questionnaires 4 weeks prior to surgery. Results: We found that working memory predicted WL before surgery and inhibitory control predicted adherence to dietary recommendations. Conclusion: Our study indicates that executive function may play a role in short-term WL and dietary adherence prior to surgery, suggesting that executive function in the preoperative period deserves an extended research focus.

The relationship of weight suppression to treatment outcomes during behavioral weight loss.

Many adults enter behavioral weight loss (BWL) programs at a weight below their highest lifetime weight. The discrepancy between highest lifetime weight and current weight is known as weight suppression (WS). Research has yet to characterize WS during BWL or investigate its relation to weight loss outcomes or treatment acceptability. Adults (N = 272) in a 12-month BWL program were assessed. WS was calculated by subtracting measured baseline weight from self-reported highest lifetime weight. Participants with higher WS lost significantly less weight than those with lower WS during treatment, although they still had clinically meaningful weight losses (e.g., participants with WS above the median: 7.8kg; participants with WS below the median: 12.0kg). WS was unrelated to weight losses at 24-month follow-up. Controlling for weight loss, treatment acceptability was unrelated to WS. BWL appears appropriate for those with high WS, but future research should aim to improve outcomes in this group.

Two‐Year Results of Think Health! ¡Vive Saludable!: A Primary Care Weight‐Management Trial

ObjectiveThink Health! ¡Vive Saludable! evaluated a moderate-intensity lifestyle behavioral weight loss program in primary care over 2 years of treatment. Final analyses examined weight change trajectories by treatment group and attendance.MethodsAdult primary care patients (n=261; 84% female; 65% black; 16% Hispanic) were randomly assigned to Basic Plus (moderate-intensity; counseling by primary care clinician and a lifestyle coach) or (Basic; clinician counseling only). Intent-to-treat analyses used all available weight measurements from data collection, treatment, and routine clinical visits. Linear mixed-effects regression models adjusted for treatment site, gender, and age, and sensitivity analyses evaluated treatment attendance and the impact of loss to follow up.ResultsModel-based estimates for 24-month weight change from baseline were mean [95% CI] −1.34 kg [−2.92, 0.24] in Basic Plus and −1.16 kg [−2.70, 0.37] in Basic (net difference − 0.18 kg [−2.38, 2.03] p=0.874). Larger initial weight loss in Basic Plus was attenuated by a ~0.5 kg rebound at 12-to-16 months. Each additional coaching visit was associated with a 0.37 kg greater estimated 24-month weight loss (p=0.01).ConclusionsThese findings in mostly black and Hispanic female primary care patients suggest that strategies to improve treatment attendance may improve weight loss resulting from moderate-intensity counseling.

The role of group cohesion in a group-based behavioral weight loss intervention.

Behavioral weight loss interventions are often delivered in groups. Group cohesion may enhance program attendance and, thereby, weight loss. In this secondary analysis, our goals were to: (1a) assess whether group cohesion measured early in a behavioral weight loss intervention predicts program attendance and weight loss outcomes and, if so, (1b) explore whether attendance mediates the link between group cohesion and weight loss; (2) characterize the association between change in group cohesion and weight loss throughout the intervention. Veterans (n=324) initiated a 16-week, group-based behavioral weight loss program involving biweekly in-person group visits. In linear regression models, early group cohesion was unrelated to group attendance or weight loss. Although group cohesion significantly increased during the intervention, this change was not associated with weight loss. These findings are consistent with the limited literature; however, they are inconsistent with theoretical assertions and clinical observations of the influence of group factors on outcomes.

"Last Supper" Predicts Greater Weight Loss Early in Obesity Treatment, but Not Enough to Offset Initial Gains.

Background: Many participants experience clinically significant fluctuations in weight before beginning a behavioral weight loss program. Pre-treatment weight gain, often referred to as the “last supper” effect, may limit total weight loss from the time of the pre-treatment screening visit and could be an indicator that a participant will respond poorly to behavioral intervention.Methods: Data were from the weight loss phase of a two-phase weight loss maintenance trial, in which 178 participants with obesity (screening BMI = 40.5 ± 6.0 kg/m2, 87.6% female; 71.3% black) were provided with a 14 week lifestyle intervention that included a meal replacement diet. Participants were categorized as having gained >1.15%, remained weight stable, or lost >1.15% of initial weight between the pre-treatment screening visit and the first treatment session (48.7 ± 29.4 days). We first examined whether the weight change groups differed in baseline eating characteristics (e.g., emotional eating, self-regulation, craving frequency) using one-way ANCOVAs. Linear mixed models were then used to compare weight change groups on total weight loss from the screening visit to week 14 and in-treatment weight loss from weeks 1 to 14.Results: Nearly half of the sample (48.9%) gained >1.15% of initial weight during the pre-treatment period (+2.5 ± 1.2%); 41.0% remained weight stable (+0.2 ± 0.6%); and 10.1% lost >1.15% of initial weight (-2.2 ± 0.9%). There were no significant differences between the groups in baseline eating characteristics. As measured from the screening weight, the weight-gain group had a lower total loss of 6.8%, compared to 7.8% in the weight stable group (p = 0.02) and 9.0% in the weight-loss group (p = 0.003). The weight-gain group lost more weight in the first 4 weeks of treatment, but in-treatment losses did not differ among the groups at week 14.Conclusion: Pre-treatment weight gain was not an indicator of a poor response to a behavioral weight loss intervention and was associated with greater weight loss early in treatment. However, weight gain during the pre-treatment period may limit the total weight loss that participants achieve from the time that they first enroll in a weight loss program.

How Accurate are Recalls of Self-Weighing Frequency? Data from a 24-Month Randomized Trial.

BackgroundSelf-weighing is an important component of self-monitoring during weight loss. However, methods of measuring self-weighing frequency need to be validated. This analysis compared self-reported to objective weighing frequency.MethodsData came from a 24-month RCT. Participants received 12 months of a behavioral weight loss program and were randomly assigned to: 1) daily self-weighing, 2) weekly weighing, or 3) no weighing (excluded from analysis). Objective weighing frequency was measured by Wi-Fi enabled scales and self-reported weighing frequency was assessed every 6 months by questionnaire. Objective weights were categorized to match the scale of the self-report measure.ResultsAt 12 months, there was 80.8% agreement between self-reported and objective weighing frequency (weighted kappa = 0.67, p < 0.001). At 24 months, agreement decreased to 48.5% (kappa = 0.27, p < 0.001). At both time points where disagreements occurred, self-reported frequencies were generally greater than objectively assessed weighing. Both self-reported and objectively assessed weighing frequency were associated with weight loss at 12 and 24 months (p’s < 0.001).ConclusionsSelf-reported weighing frequency is modestly correlated with objective weighing frequency; however, both are associated with weight change over time. Objective assessment of weighing frequency should be used to avoid overestimating actual frequency.

Measuring social support for healthy eating and physical activity in obesity.

This study sought to investigate the psychometric properties of two commonly used measures of social support in obesity, namely, the Social Support for Eating Habits (SSEH) and Social Support for Physical Activity (SSPA) scales. Cross-sectional and longitudinal study design. Participants were 200 adults with obesity taking part in a 12-month cognitive behavioural weight loss programme. At pre-treatment, participants completed the SSEH and SSPA as well as measures of social support, motivation, self-efficacy, and health-related quality of life to assess concurrent validity. Predictive validity was assessed in terms of baseline SSEH and SSPA scores predicting post-treatment weight while controlling for pre-treatment weight. Factor analysis supported a two-factor solution for both the SSEH ('Encouragement' and 'Discouragement') and SSPA ('Participation' and 'Punishment') scales, with each subscale demonstrating acceptable internal consistency. While the results provided some support for the concurrent validity of the SSEH Discouragement and SSPA Participation subscales, there was mixed support for the SSEH Encouragement subscale and poor support for the SSPA Punishment subscale. No support was found in terms of predictive validity. The findings question the validity of the SSEH and SSPA scales in obesity, with behaviours deemed to be supportive in non-obese populations not necessarily perceived as such by people with obesity. The development of a psychometrically sound measure of social support in the obesity context is needed. Statement of contribution What is already known on this subject? Social support is a robust predictor of positive health outcomes. There is mixed support for the association between social support and weight-related outcomes in obesity. Discrepant findings may be due to social support measures of questionable reliability and validity in obesity. What does this study add? The SSEH and SSPA scales have questionable validity in obesity. Behaviours deemed to be supportive by family and friends may not be perceived as such by individuals with obesity. A psychometrically sound measure of social support in the obesity context is needed.

Sa1873 - Genetic Polymorphisms Related to Cholesterol Metabolism Predict Response to a Behavioral Weight Loss Program

Sa1873 - Genetic Polymorphisms Related to Cholesterol Metabolism Predict Response to a Behavioral Weight Loss Program