Weight Loss with an AI-Powered Digital Platform for Lifestyle Intervention.

BACKGROUND: Lifestyle intervention remains the cornerstone of weight loss programs in addition to pharmacological or surgical therapies. Artificial intelligence (AI) and other digital technologies can offer individualized approaches to lifestyle intervention to enable people with obesity to reach successful weight loss. METHODS: SureMediks, a digital lifestyle intervention platform using AI, was tested by 391 participants (58% women) with a broad range of BMI (20-78 kg/m2), with the aim of losing weight over 24 weeks in a multinational field trial. SureMediks consists of a mobile app, an Internet-connected scale, and a discipline of artificial intelligence called Expert system to provide individualized guidance and weight-loss management. RESULTS: All participants lost body weight (average 14%, range 4-22%). Almost all (98.7%) participants lost at least 5% of body weight, 75% lost at least 10%, 43% at least 15%, and 9% at least 20%, suggesting that this AI-powered lifestyle intervention was also effective in reducing the burden of obesity co-morbidities. Weight loss was partially positively correlated with female sex, accountability circle size, and participation in challenges, while it was negatively correlated with sub-goal reassignment. The latter three variables are specific features of the SureMediks weight loss program. CONCLUSION: An AI-assisted lifestyle intervention allowed people with different body sizes to lose 14% body weight on average, with 99% of them losing more than 5%, over 24 weeks. These results show that digital technologies and AI might provide a successful means to lose weight, before, during, and after pharmacological or surgical therapies.

Predictors of Mental Health Outcomes in a Multidisciplinary Weight Management Program for Class 3 Obesity.

This study aimed to examine the potential predictors of improvement in mental health outcomes following participation in an intensive non-surgical outpatient weight management program (WMP) in an Australian public hospital. This was a retrospective cohort study of all adults with Class 3 obesity (BMI ≥ 40 kg/m2) who enrolled in the WMP from March 2018 to June 2021. The participants completed the Eating Disorder Examination Questionnaire Short Version (EDE-QS), Kessler-10 Psychological Distress Scale, and 36-Item Short-Form Survey (SF-36) at baseline and 12-month follow-up. A total of 115 patients completed 12 months in the WMP and were included in the study, with 76.5% being female, a mean ± SD age at baseline of 51.3 ± 13.8 years, a weight of 146 ± 26 kg, and a BMI of 51.1 ± 8.6 kg/m2. The participants lost an average of 8.6 ± 0.2 kg over 12 months, and greater weight loss at follow-up was significantly associated with improved global EDE-QS scores, psychological distress, and improved mental health quality of life. However, improvements in most mental health outcomes were not predicted by weight loss alone. Notably, a lower eating disorder risk at baseline was associated with less psychological distress at follow-up and greater weight loss at follow-up. Our results also found an association between reduced psychological distress and reduced binge eating frequency. These findings support the inclusion components of obesity interventions that target the psychological correlates of obesity to support improved outcomes in people with Class 3 obesity. Future studies should aim to identify which aspects of the WMP helped improve people's psychological outcomes.

What could be the reasons for not losing weight even after following a weight loss program?

INTRODUCTION: Approximately four million people worldwide die annually because of obesity. Weight loss is commonly recommended as a first-line therapy in overweight and obese patients. Although many individuals attempt to lose weight, not everyone achieves optimal success. Few studies point out that weight loss eventually slows down, stagnates or reverses in 85% of the cases. RESEARCH QUESTION: What could be the reasons for not losing weight even after following a weight loss program? METHODS: A scoping review of the literature was performed using weight loss-related search terms such as 'Obesity,' 'Overweight,' 'Lifestyle,' 'weight loss,' 'Basal Metabolism,' 'physical activity,' 'adherence,' 'energy balance,' 'Sleep' and 'adaptations. The search involved reference tracking and database and web searches (PUBMED, Science Direct, Elsevier, Web of Science and Google Scholar). Original articles and review papers on weight loss involving human participants and adults aged > 18 years were selected. Approximately 231 articles were reviewed, and 185 were included based on the inclusion criteria. DESIGN: Scoping review. RESULTS: In this review, the factors associated with not losing weight have broadly been divided into five categories. Studies highlighting each subfactor were critically reviewed and discussed. A wide degree of interindividual variability in weight loss is common in studies even after controlling for variables such as adherence, sex, physical activity and baseline weight. In addition to these variables, variations in factors such as previous weight loss attempts, sleep habits, meal timings and medications can play a crucial role in upregulating or downregulating the association between energy deficit and weight loss results. CONCLUSION: This review identifies and clarifies the role of several factors that may hinder weight loss after the exploration of existing evidence. Judging the effectiveness of respective lifestyle interventions by simply observing the 'general behavior of the groups' is not always applicable in clinical practice. Each individual must be monitored and advised as per their requirements and challenges.

Identification of minimum thresholds for dietary self-monitoring to promote weight-loss maintenance.

OBJECTIVE: Reduced schedules of dietary self-monitoring are typically recommended after the end of behavioral weight-loss programs; however, there exists little empirical evidence to guide these recommendations. METHODS: We explored potential thresholds for dietary self-monitoring during a 9-month maintenance period following a 3-month weight-loss program in 74 adults with overweight or obesity (mean [SD] age = 50.7 [10.4] years, BMI = 31.2 [4.5] kg/m2) who were encouraged to self-monitor weight, dietary intake, and physical activity daily and report their adherence to self-monitoring each week via a study website. RESULTS: Greater self-monitoring was correlated with less weight regain for thresholds of ≥3 days/week, with the largest benefit observed for thresholds of ≥5 to ≥6 days/week (all p < 0.05); significant weight gain was observed for thresholds of ≥1 to ≥2 days/week, whereas no change in weight was observed for thresholds of ≥3 to ≥4 days/week, and weight loss was observed with thresholds of ≥5 or more days/week. CONCLUSIONS: Results demonstrate that self-monitoring at least 3 days/week may be beneficial for supporting long-term maintenance, although greater benefit (in relation to weight loss) may be realized at thresholds of 5 to 6 days/week. Future research should investigate whether individuals who were randomized to self-monitor at these different thresholds demonstrate differential patterns of weight-loss maintenance.

Assessing the role of biomarker feedback in a 12-week community weight management programme among overweight men: A pilot study.

BACKGROUND: The primary objective of this study was to examine the feasibility of recruitment, retention, and delivery of biomarker feedback among men partaking in Shape Up, a physical activity for health programme. Secondarily, it explored the potential effects of biomarker feedback on participants' adherence and motivation levels. METHODS: In this two-arm non-randomised pilot study, 46 men (mean±SD age 46.0±8.6 years) participating in the 12-week Shape Up programme were assigned to a control group or biomarker feedback group. Biomarker feedback consisted of 3 blood test panels: at baseline, 12 weeks, and 24 weeks (follow-up), each with a doctor's report. Both groups completed questionnaires (Short Active Lives Survey [SALS], Treatment Self-Regulation Questionnaire [TSRQ], and EQ-5D-5L) to gauge levels of motivation and engagement. The mean difference was calculated between baseline and programme end. Recruitment, retention, and attendance rates were determined. RESULTS: Mean recruitment (approach-to-consent), retention, and attendance rates were 96.3%, 92.3%, and 83.7% in the control group, and 85.2%, 86.2%, and 81.5% in the biomarker feedback group, respectively. Of biomarker feedback group participants, 86.4% attended their 12-week blood test and 45.5% attended their follow-up blood test. The mean 12-week differences (95% CI) for the control group and biomarker feedback group were 138.1 (2.7, 273.5) and 467.3 (249.4, 685.2) for active minutes per week, 0.2 (-0.8, 1.2) and 0.4 (0.0, 0.8) for autonomous TSRQ domains, 0.2 (-0.3, 0.8) and 0.8 (0.1, 1.4) for controlled TSRQ domains, and 19 (12.7, 26.5) and 27.2 (19.8, 34.6) for EQ-5D-5L scores, respectively. CONCLUSION: Biomarker feedback was well-received by participants and deemed feasible, with high recruitment and retention rates for the duration of the 12-week programme. Biomarker feedback may affect aspects of motivation but did not appear to influence adherence to the programme. Biomarker data may provide additional evidence of programme efficacy. Important design considerations are provided for definitive larger-scale trials.

Association Between a National Behavioral Weight Management Program and Veterans Affairs Health Expenditures.

OBJECTIVE: The association between participation in a behavioral weight intervention and health expenditures has not been well characterized. We compared Veterans Affairs (VA) expenditures of individuals participating in MOVE!, a VA behavioral weight loss program, and matched comparators 2 years before and 2 years after MOVE! initiation. METHODS: Retrospective cohort study of Veterans who had one or more MOVE! visits in 2008-2017 who were matched contemporaneously to up to 3 comparators with overweight or obesity through sequential stratification on an array of patient characteristics, including sex. Baseline patient characteristics were compared between the two cohorts through standardized mean differences. VA expenditures in the 2 years before MOVE! initiation and 2 years after initiation were modeled using generalized estimating equations with a log link and distribution with variance proportional to the standard deviation (gamma). RESULTS: MOVE! participants (n=499,696) and comparators (n=1,336,172) were well-matched, with an average age of 56, average body mass index of 35, and similar total VA expenditures in the fiscal year before MOVE! initiation ($9662 for MOVE! participants and $10,072 for comparators, standardized mean difference=-0.019). MOVE! participants had total expenditures that were statistically lower than matched comparators in the 6 months after initiation but modestly higher in the 6 months to 2 years after initiation, though differences were small in magnitude (1.0%-1.6% differences). CONCLUSIONS: The VA's system-wide behavioral weight intervention did not realize meaningful short-term health care cost savings for participants.

Furthering Scientific Inquiry for Weight Loss Maintenance: Assessing the Psychological Processes Impacted by a Low intensity Technology-Assisted Intervention (NULevel Trial).

BACKGROUND: NULevel was a randomized control trial to evaluate a technology-assisted weight loss maintenance (WLM) program in the UK. The program included: (a) a face-to-face goal-setting session; (b) an internet platform, a pedometer, and wirelessly connected scales to monitor and report diet, physical activity, and weight, and; (c) regular automated feedback delivered by mobile phone, tailored to participants' progress. Components were designed to target psychological processes linked to weight-related behavior. Though intervention participants showed increased physical activity, there was no difference in WLM between the intervention and control groups after 12 months (Sniehotta FF, Evans EH, Sainsbury K, et al. Behavioural intervention for weight loss maintenance versus standard weight advice in adults with obesity: A randomized controlled trial in the UK (NULevel Trial). PLoS Med. 2019; 16(5):e1002793. doi:10.1371/journal.pmed.1002793). It is unclear whether the program failed to alter targeted psychological processes, or whether changes in these processes failed to influence WLM. PURPOSE: We evaluate whether the program influenced 16 prespecified psychological processes (e.g., self-efficacy and automaticity toward diet and physical activity), and whether these processes (at 6 months) were associated with successful WLM (at 12 months). METHODS: 288 adults who had previously lost weight were randomized to the intervention or control groups. The control group received wireless scales and standard advice via newsletters. Assessments occurred in person at 0, 6, and 12 months. RESULTS: The intervention significantly altered 10 of the 16 psychological processes, compared with the control group. However, few processes were associated with WLM, leading to no significant indirect effects of the intervention via the processes on WLM. CONCLUSIONS: Changes in targeted processes were insufficient to support WLM. Future efforts may more closely examine the sequence of effects between processes, behavior, and WLM.

Many tools exist to help people lose weight, but it is common for people to regain that weight over time. Thus, understanding how to support the maintenance of weight loss remains a priority. The NULevel program was a 12-month weight loss maintenance (WLM) intervention for individuals who had recently lost weight. It promoted psychological factors, shown to be tied to weight-related behaviors, using face-to-face and technology-based (e.g., mobile phone feedback) elements. For example, the program encouraged making plans to improve lifestyles (e.g., exercise, better diet) and promoted people's confidence in these behaviors. However, the program was not more successful than a control condition in maintaining weight loss. We sought to understand why this occurred. We found that the program was indeed successful in influencing most of the psychological factors it targeted. Instead, it was the psychological factors that failed to predict WLM. Were the psychological factors insufficient to impact behavior? Or did the promoted behaviors fail to aid WLM? Future research should focus on answering such questions. Doing so would inform whether interventions should target different psychological factors to change behaviors, or choose different sets of behaviors to support WLM.

Psychological and behavioral responses to daily weight gain during behavioral weight loss treatment.

Self-weighing is consistently associated with more effective weight control. However, patterns show that participants disengage from their weight control behaviors following weight gain. Women with BMIs in the overweight/obese range (N = 50) enrolled in a long-term behavioral weight loss program completed ecological momentary assessment (EMA) surveys immediately after their daily weigh-ins. Nightly EMA surveys and self-monitoring data through Fitbit measured their weight control behavior that day. On days when participants gained weight (vs. lost or maintained), they reported more negative mood, more guilt/shame, and lower confidence in weight control. Motivation following daily weight gain depended on participants' overall satisfaction with their weight loss so far: more satisfied participants had marginally higher, but less satisfied participants had marginally lower motivation in response to daily weight gain. Greater guilt/shame and lower motivation after the weigh-in predicted less effective weight control behavior that day (e.g., lower likelihood of calorie tracking, fewer minutes of physical activity). Results demonstrate that even small weight gain is distressing and demoralizing for women in BWL programs, which can lead to goal disengagement. These findings have implications for future BWL interventions, including the potential utility of just-in-time adaptive interventions to promote more adaptive responses in the moments after weigh-ins.

Views, perceptions, and experiences of type 2 diabetes or weight management programs among minoritized ethnic groups living in high-income countries: A systematic review of qualitative evidence.

BACKGROUND: Prevalence of both obesity and type 2 diabetes can be higher in patients from certain ethnic groups, yet uptake and adherence to current support within these groups is lower, leading to widening health inequalities in high-income countries. OBJECTIVES: The main objective of this study is to understand the views, perceptions, and experiences of and barriers and facilitators in relation to the uptake and adherence to weight management and type 2 diabetes programs in minoritized ethnic groups in high-income countries. METHODS: CINAHL, MEDLINE, PsycINFO, Scopus, Academic Search Complete, and PubMed were searched for English language studies undertaken in community-dwelling adults residing in high-income countries, who are from a minoritized ethnic group within the country of study. RESULTS: Seventeen studies were synthesized using the JBI System for the Unified Management of the Assessment and Review of Information. From these studies, 115 findings were retrieved, and seven key themes were identified: (1) family health status and program education, (2) social support, (3) challenges, (4) cultural beliefs, (5) increased awareness and dietary changes, (6) impact of psychological evaluations, and (7) considerations for future. CONCLUSIONS: Nutritional considerations for type 2 diabetes mellitus and weight management programs in high-income countries should include social, habitual, economic, and conceptual components, which should include consideration of local ethnic and cultural norms and building community relationships while creating culturally tailored programs.

Identifying Preferred Features of Weight Loss Programs for Adults With or at Risk of Type 2 Diabetes: A Discrete Choice Experiment With 3,960 Adults in the U.K.

OBJECTIVE: To understand preferences for features of weight loss programs among adults with or at risk of type 2 diabetes in the U.K. RESEARCH DESIGN AND METHODS: We conducted a discrete choice experiment with 3,960 U.K. adults living with overweight (n = 675 with type 2 diabetes). Preferences for seven characteristics of weight loss programs were analyzed. Simulations from choice models using the experimental data predicted uptake of available weight loss programs. Patient groups comprising those who have experience with weight loss programs, including from minority communities, informed the experimental design. RESULTS: Preferences did not differ between individuals with and without type 2 diabetes. Preferences were strongest for type of diet. Healthy eating was most preferred relative to total diet replacement (odds ratio [OR] 2.24; 95% CI 2.04-2.44). Individual interventions were more popular than group interventions (OR 1.40; 95% CI 1.34-1.47). Participants preferred programs offering weight loss of 10-15 kg (OR 1.37; 95% CI 1.28-1.47) to those offering loss of 2-4 kg. Online content was preferred over in-person contact (OR 1.24; 95% CI 1.18-1.30). There were few differences in preferences by gender or ethnicity, although weight loss was more important to women than to men, and individuals from ethnic minority populations identified more with programs where others shared their characteristics. Modeling suggested that tailoring programs to individual preferences could increase participation by ∼17 percentage points (68% in relative terms). CONCLUSIONS: Offering a range of weight loss programs targeting the preferred attributes of different patient groups could potentially encourage more people to participate in weight loss programs and support those living with overweight to reduce their weight.

Pilot study of a virtual weight management program for Duchenne muscular dystrophy.

INTRODUCTION/AIMS: Young people with Duchenne muscular dystrophy (DMD) are at increased risk of obesity. Weight management is important to families; however, several barriers exist. This pilot study aimed to investigate the feasibility and acceptability of a co-designed weight management program for DMD. METHODS: The Supporting Nutrition and Optimizing Wellbeing Program (SNOW-P) was a single-arm diet and behavior weight management intervention delivered via weekly telehealth/phone visits over 6 weeks to young people with DMD and obesity (body mass index (BMI) ≥95th percentile) and their caregivers. Using an online survey, caregivers of boys with DMD were consulted on the structure and topics delivered in SNOW-P. Primary outcomes were feasibility and acceptability; secondary outcomes were weight, physical function, and quality of life at 6- and 12-weeks follow-up. RESULTS: Of nineteen eligible participants, eight were enrolled (median age 11.4 years, range 4.9-15.8), and seven completed the program. Visit attendance was high (88%-100%); most participants reported high satisfaction and that participation was easy. Suggested changes included online and visual DMD-specific resources. At 6-weeks, median change in weight z-scores was -0.01 (IQR: -0.23, 0.17) indicating that on average, weight gain tracked as expected for age. Waist circumference measured by caregivers lacked accuracy and the completion rate of caregiver-reported secondary outcome measures (e.g., food diaries) was low. DISCUSSION: A co-designed, telehealth/phone weight management program appeared to be feasible and acceptable in a small group of boys with DMD. An adapted, hybrid telehealth and face-to-face program is recommended for efficacy testing.

Effectiveness of a telehealth-delivered clinician-supported exercise and weight loss program for hip osteoarthritis - protocol for the Better Hip randomised controlled trial.

BACKGROUND: Hip osteoarthritis (OA) is a leading cause of chronic pain and disability worldwide. Self-management is vital with education, exercise and weight loss core recommended treatments. However, evidence-practice gaps exist, and service models that increase patient accessibility to clinicians who can support lifestyle management are needed. The primary aim of this study is to determine the effectiveness of a telehealth-delivered clinician-supported exercise and weight loss program (Better Hip) on the primary outcomes of hip pain on walking and physical function at 6 months, compared with an information-only control for people with hip OA. METHODS: A two-arm, parallel-design, superiority pragmatic randomised controlled trial. 212 members from a health insurance fund aged 45 years and over, with painful hip OA will be recruited. Participants will be randomly allocated to receive: i) Better Hip; or ii) web-based information only (control). Participants randomised to the Better Hip program will have six videoconferencing physiotherapist consultations for education about OA, prescription of individualised home-based strengthening and physical activity programs, behaviour change support, and facilitation of other self-management strategies. Those with a body mass index > 27 kg/m2, aged < 80 years and no specific health conditions, will also be offered six videoconferencing dietitian consultations to undertake a weight loss program. Participants in the control group will be provided with similar educational information about managing hip OA via a custom website. All participants will be reassessed at 6 and 12 months. Primary outcomes are hip pain on walking and physical function. Secondary outcomes include measures of pain; hip function; weight; health-related quality of life; physical activity levels; global change in hip problem; willingness to undergo hip replacement surgery; rates of hip replacement; and use of oral pain medications. A health economic evaluation at 12 months will be conducted and reported separately. DISCUSSION: Findings will determine whether a telehealth-delivered clinician-supported lifestyle management program including education, exercise/physical activity and, for those with overweight or obesity, weight loss, is more effective than information only in people with hip OA. Results will inform the implementation of such programs to increase access to core recommended treatments. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Registry (ACTRN12622000461796).

Evaluating the Implementation of the Connect for Health Pediatric Weight Management Program.

Importance: Adoption of primary care interventions to reduce childhood obesity is limited. Progress in reducing obesity prevalence and eliminating disparities can be achieved by implementing effective childhood obesity management interventions in primary care settings. Objective: To examine the extent to which implementation strategies supported the uptake of research evidence and implementation of the Connect for Health pediatric weight management program. Design, Setting, and Participants: This quality improvement study took place at 3 geographically and demographically diverse health care organizations with substantially high numbers of children living in low-income communities in Denver, Colorado; Boston, Massachusetts; and Greenville, South Carolina, from November 2019 to April 2022. Participants included pediatric primary care clinicians and staff and families with children aged 2 to 12 years with a body mass index (BMI) in the 85th percentile or higher. Exposures: Pediatric weight management program with clinician-facing tools (ie, clinical decision support tools) and family-facing tools (ie, educational handouts, text messaging program, community resource guide) along with implementation strategies (ie, training and feedback, technical assistance, virtual learning community, aligning with hospital performance metrics) to support the uptake. Main Outcomes and Measures: Primary outcomes were constructs from the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) Framework examined through parent, clinician, and leadership surveys and electronic health record data to understand the number of children screened and identified, use of the clinical decision support tools, program acceptability, fidelity to the intervention and implementation strategies, and program sustainability. Results: The program screened and identified 18 333 children across 3 organizations (Denver Health, 8480 children [46.3%]; mean [SD] age, 7.97 [3.31] years; 3863 [45.5%] female; Massachusetts General Hospital (MGH), 6190 children [33.8%]; mean [SD] age, 7.49 [3.19] years; 2920 [47.2%] female; Prisma Health, 3663 children [20.0%]; mean [SD] age, 7.33 [3.15] years; 1692 [46.2%] female) as having an elevated BMI. The actionable flagging system was used for 8718 children (48%). The reach was equitable, with 7843 children (92.4%) from Denver Health, 4071 children (65.8%) from MGH, and 1720 children (47%) from Prisma Health being from racially and ethnically minoritized groups. The sites had high fidelity to the program and 6 implementation strategies, with 4 strategies (67%) used consistently at Denver Health, 6 (100%) at MGH, and 5 (83%) at Prisma Health. A high program acceptability was found across the 3 health care organizations; for example, the mean (SD) Acceptability of Intervention Measure score was 3.72 (0.84) at Denver Health, 3.82 (0.86) at MGH, and 4.28 (0.68) at Prisma Health. The implementation strategies were associated with 7091 (39%) uses of the clinical decision support tool. The mean (SD) program sustainability scores were 4.46 (1.61) at Denver Health, 5.63 (1.28) at MGH, and 5.54 (0.92) at Prisma Health. Conclusions and Relevance: These findings suggest that by understanding what strategies enable the adoption of scalable and implementation-ready programs by other health care organizations, it is feasible to improve the screening, identification, and management of children with overweight or obesity and mitigate existing disparities.

Effect of planned pauses versus continuous energy restriction on weight loss and attrition: a systematic review.

OBJECTIVE: The objective of this study was to investigate whether pausing a weight loss program for a defined period of time could enhance weight loss and reduce attrition. METHODS: Five databases and two trial registries were searched from inception to July 2023. Randomized-controlled trials of adults with overweight and/or obesity were included if they compared planned-pause interventions with continuous energy restriction (CER), usual care, or a minimal intervention. To be included, the weight loss intervention must have incorporated a pause of at least 1 week. Pooled mean differences for weight change and risk ratios for attrition were calculated using random-effects meta-analyses. RESULTS: Nine intervention arms (N = 796 participants, 77% female) were included. Pooled results did not detect a significant difference in weight change between planned pauses and CER interventions at the end of the active intervention at a median 26 weeks (planned pauses vs. CER mean: -7.09 vs. -7.0 kg; mean difference: -0.09 kg; 95% CI: -1.10 to 0.93) or at final follow-up at a median 52 weeks (planned pauses vs. CER mean: -6.91 vs. -6.19 kg; mean difference: -0.72 kg; 95% CI: -2.92 to 1.48). There was no difference in attrition between planned pauses and CER interventions at the end of the active intervention (risk ratio: 1.20, 95% CI: 0.82 to 1.75) or at final follow-up (risk ratio: 1.04, 95% CI: 0.89 to 1.22). CONCLUSIONS: Planned pauses were consistently found to be no more or less effective than CER for weight loss or attrition.

Associations Among Stress, Internalized Weight Stigma, Emotional Eating, and Body Composition in Active-Duty Service Members Enrolling in a Randomized Controlled Trial of a Weight Management Program.

BACKGROUND: Obesity is a critical public health concern with particular relevance to US military personnel. Stress and internalized weight stigma ("stigma") may contribute to and maintain obesogenic processes and behaviors, including emotional eating. In this secondary cross-sectional analysis, we examined (1) associations among stress and stigma with emotional eating and body fat percentage (BF%), (2) whether stress explains the association between stigma and emotional eating, and (3) whether emotional eating explains associations between stress and stigma with BF%. METHOD: Active-duty military service members (N = 178) completed BF% assessment and questionnaires assessing stress, stigma, and emotional eating. RESULTS: Structural equation modeling path analyses showed that stress and stigma were both significantly associated with emotional eating (b = 0.35, p < 0.001 and b = 0.23, p < 0.001, respectively) and with BF% (b = 0.38, p < 0.001 and b = 0.29, p < 0.001, respectively) such that individuals who reported higher stress and stigma tended to report more emotional eating and had higher BF%. Stress partially explained the association between internalized weight stigma and emotional eating, and emotional eating partially explained the relationship between stress and BF% but did not significantly mediate the association between stigma and BF%. CONCLUSION: Greater stress and internalized weight stigma were associated with more emotional eating and higher BF%; however, emotional eating only partially explained the association between stress and BF%. Results highlight the importance of interventions targeting stress management skills, but additional research is needed to identify mechanisms that explain the association between stigma and BF%.

Cost-effectiveness of goal-directed and outcome-based financial incentives for weight loss in low-income populations: the FIReWoRk randomized clinical trial.

BACKGROUND: The Financial Incentives for Weight Reduction (FIReWoRk) clinical trial showed that financial incentive weight-loss strategies designed using behavioral economics were more effective than provision of weight-management resources only. We now evaluate cost-effectiveness. METHODS: Cost-effectiveness analysis of a multisite randomized trial enrolling 668 participants with obesity living in low-income neighborhoods. Participants were randomized to (1) goal-directed incentives (targeting behavioral goals), (2) outcome-based incentives (targeting weight-loss), and (3) resources only, which were provided to all participants and included a 1-year commercial weight-loss program membership, wearable activity monitor, food journal, and digital scale. We assessed program costs, time costs, quality of life, weight, and incremental cost-effectiveness in dollars-per-kilogram lost. RESULTS: Mean program costs at 12 months, based on weight loss program attendance, physical activity participation, food diary use, self-monitoring of weight, and incentive payments was $1271 in the goal-directed group, $1194 in the outcome-based group, and $834 in the resources-only group (difference, $437 [95% CI, 398 to 462] and $360 [95% CI, 341-363] for goal-directed or outcome-based vs resources-only, respectively; difference, $77 [95% CI, 58-130] for goal-directed vs outcome-based group). Quality of life did not differ significantly between the groups, but weight loss was substantially greater in the incentive groups (difference, 2.34 kg [95% CI, 0.53-4.14] and 1.79 kg [95% CI, -0.14 to 3.72] for goal-directed or outcome-based vs resources only, respectively; difference, 0.54 kg [95% CI, -1.29 to 2.38] for goal-directed vs outcome-based). Cost-effectiveness of incentive strategies based on program costs was $189/kg lost in the goal-directed group (95% CI, $124/kg to $383/kg) and $186/kg lost in the outcome-based group (95% CI, $113/kg to $530/kg). CONCLUSIONS: Goal-directed and outcome-based financial incentives were cost-effective strategies for helping low-income individuals with obesity lose weight. Their incremental cost per kilogram lost were comparable to other weight loss interventions.

Small Monetary Incentives Lead to Greater Adherence in a Weight Loss Program.

PURPOSE: Understand how weekly monetary incentives for dietary tracking and/or weight loss impact 6-month weight loss behavioral adherence. DESIGN: Secondary analysis of participants randomized to one of four conditions in a behavioral weight loss intervention: incentives for dietary tracking, incentives for weight loss, both, or none. SETTING: Participants were asked to self-weigh at least twice weekly, log food and drink in a mobile application five days weekly, and attend bi-weekly, group-based classes. SAMPLE: Data from (n = 91) adults with obesity who completed a 24-week behavioral weight loss intervention of whom 88% were female and 74% Non-Hispanic White, were analyzed. MEASURES: Non-adherence to weight and dietary self-monitoring was defined as the second week of not meeting criteria. Class attendance was also tracked. ANALYSIS: Kaplan-Meier analyses were used to examine differences across the four conditions. RESULTS: Participants incentivized for dietary self-monitoring had an average 15.8 weeks (SE:1.2) until the first non-adherent week compared to 5.9 weeks (SE:0.8) for those not incentivized for dietary self-monitoring (P < .01). Those incentivized for weight loss had an average 18.0 weeks (SE:1.02) of self-weighing until the first non-adherent week compared to 13.5 weeks (SE:1.3) for those not incentivized for weight loss (P = .02). No difference in class attendance was observed. CONCLUSIONS: Incentivizing behaviors associated with weight loss improved adherence to those behaviors and does not appear to spill over to non-incentivized behaviors.

Preoperative medically supervised weight loss programs and weight loss outcomes following bariatric surgery - a prospective analysis.

BACKGROUND: Prior to undergoing bariatric surgery, many insurance companies require patients to attend medically supervised weight management visits for 3-6 months to be eligible for surgery. There have been few studies that have looked specifically at the relationship between medically supervised weight management visit attendance and postoperative outcomes, and the current literature reports discrepant findings. OBJECTIVES: This project aimed to better characterize the relationship between preoperative medically supervised weight management visit attendance and postoperative weight loss outcomes by examining weight loss up to 5 years postbariatric surgery, and by stratifying findings according to the type of surgery undergone. SETTING: University Hospital. METHODS: Participants were recruited during presurgical bariatric surgery clinic visits at a bariatric and metabolic weight loss center. As part of standard of care all participants were required to participate in monthly medically supervised weight management visits before surgery. Participants who completed bariatric surgical procedures participated in postsurgical follow-up at 3 weeks, 3 months, 6 months, and then annually for 5 years. Weight outcomes measured were percentage of total weight lost. RESULTS: The results do not indicate a significant association between number of group visits attended and percent total weight loss at 1 month, 3 months, 6 months, 1 year, 2 years, 3 years, 4 years, or 5 years postbariatric surgery. CONCLUSIONS: These data do not suggest a relationship between engagement in a medically supervised weight loss program prior to bariatric surgery and weight loss after surgery in either the short- or the long-term.

Non-nutritive sweetened beverages versus water after a 52-week weight management programme: a randomised controlled trial.

BACKGROUND/OBJECTIVE: Sugar-sweetened beverages are a substantial source of dietary sugar that can contribute to weight gain and the risk of type 2 diabetes. Dietary guidelines recommend non-nutritive sweetened (NNS) beverages to reduce sugar consumption, however, there is a need for long-term randomised controlled trials on their use. We aimed to compare the effects of NNS beverages and water on body weight during weight loss and maintenance in a behavioural weight management programme. METHODS: In this parallel-group, open-label, controlled equivalence trial, adults with a BMI of 27-35 kg/m2 who regularly consumed cold beverages were randomised 1:1 to water or NNS beverages. Participants underwent a group behavioural weight management programme comprising weekly (during the 12-week weight-loss phase) then monthly (during the 40-week weight-maintenance phase) meetings. The primary endpoint was weight change at week 52 (equivalence: two-sided P > 0.05). Secondary endpoints included changes in anthropometrics, cardiometabolic risk factors, appetite and activity levels. RESULTS: Of 493 participants randomised (water: n = 246; NNS beverages: n = 247), 24.1% were NNS-naïve. At week 52, water and NNS beverages were non-equivalent, with significantly greater weight loss in the NNS beverages group. Participants consuming water maintained a weight loss of 6.1 kg over 52 weeks versus 7.5 kg with NNS beverages (difference [90% CI]: 1.4 kg [-2.6, -0.2]; p < 0.05). CONCLUSIONS: During a 52-week behavioural weight management programme, water and NNS beverages were non-equivalent, with weight loss maintained to a statistically greater extent with NNS beverages compared with water. However, this difference was not clinically significant. CLINICAL TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov: NCT02591134.