Predictors of racial differences in weight loss: the PROPEL trial.

OBJECTIVE: Studies have consistently shown that African American individuals lose less weight in response to behavioral interventions, but the mechanisms leading to this result have been understudied. METHODS: Data were derived from the PROmoting Successful Weight Loss in Primary CarE in Louisiana (PROPEL) study, which was a cluster-randomized, two-arm trial conducted in primary care clinics. In the PROPEL trial, African American individuals lost less weight compared with patients who belonged to other racial groups after 24 months. In the current study, counterfactual mediation analyses among 445 patients in the intervention arm of PROPEL were used to determine which variables mediated the relationship between race and weight loss. The mediators included treatment engagement, psychosocial, and lifestyle factors. RESULTS: At 6 months, daily weighing mediated 33% (p = 0.008) of the racial differences in weight loss. At 24 months, session attendance and daily weighing mediated 35% (p = 0.027) and 66% (p = 0.005) of the racial differences in weight loss, respectively. None of the psychosocial or lifestyle variables mediated the race-weight loss association. CONCLUSIONS: Strategies specifically targeting engagement, such as improving session attendance and self-weighing behaviors, among African American individuals are needed to support more equitable weight losses over extended time periods.

Exercise-induced Changes in Central Adiposity During an RCT: Effect of Exercise Dose and Associations With Compensation.

CONTEXT: Exercise can decrease central adiposity, but the effect of exercise dose and the relationship between central adiposity and exercise-induced compensation is unclear. OBJECTIVE: Test the effect of exercise dose on central adiposity change and the association between central adiposity and exercise-induced weight compensation. METHODS: In this ancillary analysis of a 6-month randomized controlled trial, 170 participants with overweight or obesity (mean ± SD body mass index: 31.5 ± 4.7 kg/m2) were randomized to a control group or exercise groups that reflected exercise recommendations for health (8 kcal/kg/week [KKW]) or weight loss and weight maintenance (20 KKW). Waist circumference was measured, and dual-energy X-ray absorptiometry assessed central adiposity. Predicted weight change was estimated and weight compensation (weight change - predicted weight change) was calculated. RESULTS: Between-group change in waist circumference (control: .0 cm [95% CI, -1.0 to 1.0], 8 KKW: -.7 cm [95% CI, -1.7 to .4], 20 KKW: -1.3 cm [95% CI, -2.4 to -.2]) and visceral adipose tissue (VAT; control: -.02 kg [95% CI, -.07 to .04], 8 KKW: -.01 kg [95% CI, -.07 to .04], 20 KKW: -.04 kg [95% CI, -.10 to .02]) was similar (P ≥ .23). Most exercisers (82.6%) compensated (weight loss less than expected). Exercisers who compensated exhibited a 2.5-cm (95% CI, .8 to 4.2) and .23-kg (95% CI, .14 to .31) increase in waist circumference and VAT, respectively, vs those who did not (P < .01). Desire to eat predicted VAT change during exercise (ß = .21; P = .03). CONCLUSION: In the presence of significant weight compensation, exercise at doses recommended for health and weight loss and weight maintenance leads to negligible changes in central adiposity.

Effects of Episodic Food Insecurity on Psychological and Physiological Responses in African American Women With Obesity (RESPONSES): Protocol for a Longitudinal Observational Cohort Study.

BACKGROUND: Food insecurity is a risk factor for multiple chronic diseases, including obesity. Importantly, both food insecurity and obesity are more prevalent in African American women than in other groups. Furthermore, food insecurity is considered a cyclic phenomenon, with episodes of food adequacy (ie, enough food to eat) and food shortage (ie, not enough food to eat). More research is needed to better understand why food insecurity is linked to obesity, including acknowledging the episodic nature of food insecurity as a stressor and identifying underlying mechanisms. OBJECTIVE: The objective of this study is to investigate the episodic nature of food insecurity as a stressor via responses in body weight and psychological and physiological parameters longitudinally and do so in a health-disparate population-African American women. METHODS: We enrolled 60 African American women (food-insecure cohort: n=30, 50%; food-secure cohort: n=30, 50%) aged 18-65 years with obesity (BMI 30-50 kg/m2) to measure (1) daily body weight remotely over 22 weeks and (2) psychological and physiological parameters via clinic assessments at the beginning and end of the 22-week study. Furthermore, we are assessing episodes of food insecurity, stress, hedonic eating, and appetite on a weekly basis. We hypothesize that food-insecure African American women with obesity will demonstrate increased body weight and changes in psychological and physiological end points, whereas food-secure African American women with obesity will not. We are also examining associations between changes in psychological and physiological parameters and changes in body weight and performing a mediation analysis on the psychological parameters assessed at the study midpoint. Psychological questionnaires are used to assess stress; executive function, decision-making, and motivation; and affect and nonhomeostatic eating. Physiological measurements are used to evaluate the levels of cortisol, dehydroepiandrosterone-sulfate (DHEA-S), C-reactive protein, thyroid hormones, blood glucose, glycated hemoglobin, and insulin, as well as allostatic load. RESULTS: This study has completed participant recruitment (n=60). At the time of study enrollment, the mean age of the participants was almost 47 (SD 10.8) years, and they had a mean BMI of 39.6 (SD 5.31) kg/m2. All data are anticipated to be collected by the end of 2023. CONCLUSIONS: We believe that this is the first study to examine changes in body weight and psychological and physiological factors in food-insecure African American women with obesity. This study has significant public health implications because it addresses the cyclic nature of food insecurity to identify underlying mechanisms that can be targeted to mitigate the adverse relationship between food insecurity and obesity and reduce health disparities in minority populations. TRIAL REGISTRATION: ClinicalTrials.gov NCT05076487; https://clinicaltrials.gov/study/NCT05076487. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52193.

Validity of an Artificial Intelligence-Based Application to Identify Foods and Estimate Energy Intake Among Adults: A Pilot Study.

Background: The commercial application Openfit allows for automatic identification and quantification of food intake through short video capture without a physical reference marker. There are no known peer-reviewed publications on the validity of this Nutrition Artificial Intelligence (AI). Objectives: To test the validity of Openfit to identify food automatically and semiautomatically (with user correction), test the validity of Openfit at quantifying energy intake (kcal) automatically and semiautomatically, and assess satisfaction and usability of Openfit. Methods: During a laboratory-based visit, adults (7 male and 17 female), used Openfit to automatically and semiautomatically record provided meals, which were covertly weighed. Foods logged were identified as an "exact match," "far match," or an "intrusion" using Food and Nutrient Database for Dietary Studies (FNDDS) codes. Descriptive data were stratified by meal, food item, and FNDDS group, and presented with or without beverages. Bland-Altman analyses assessed errors over levels of energy intake. Participants completed a User Satisfaction Survey (USS) and the Computer Systems Usability Questionnaire (CSUQ). Open-ended questions were assessed with qualitative methods. Results: Exact matches, far matches, and intrusions were 46%, 41%, and 13% for automated identification, and 87%, 23%, and 0% for semiautomated identification, respectively. Error for automated and semiautomated energy estimates were 43% and 33% with beverages, and 16% and 42% without beverages. Bland-Altman analyses indicated larger error for higher energy meals. Overall mean scores were 2.4 for the CSUQ and subscale means scores ranged from 4.1 to 5.5. for the USS. Participants recommended improvements to Openfit's Nutrition AI, manual estimation, and overall app. Conclusion: Openfit worked relatively well for automatically and semiautomatically identifying foods. Error in automated energy estimates was relatively high; however, after excluding beverages, error was relatively low (16%). For semiautomated energy estimates, error was comparable to previous studies. Improvements to the Nutrition AI, manual estimation and overall application may increase Openfit's usability and validity.This trial was registered at clinicaltrials.gov as NCT05343585.

The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial.

Weight loss (WL) differences between isocaloric high-carbohydrate and high-fat diets are generally small; however, individual WL varies within diet groups. Genotype patterns may modify diet effects, with carbohydrate-responsive genotypes losing more weight on high-carbohydrate diets (and vice versa for fat-responsive genotypes). We investigated whether 12-week WL (kg, primary outcome) differs between genotype-concordant and genotype-discordant diets. In this 12-week single-center WL trial, 145 participants with overweight/obesity were identified a priori as fat-responders or carbohydrate-responders based on their combined genotypes at ten genetic variants and randomized to a high-fat (n = 73) or high-carbohydrate diet (n = 72), yielding 4 groups: (1) fat-responders receiving high-fat diet, (2) fat-responders receiving high-carbohydrate diet, (3) carbohydrate-responders receiving high-fat diet, (4) carbohydrate-responders receiving high-carbohydrate diet. Dietitians delivered the WL intervention via 12 weekly diet-specific small group sessions. Outcome assessors were blind to diet assignment and genotype patterns. We included 122 participants (54.4 [SD:13.2] years, BMI 34.9 [SD:5.1] kg/m2, 84% women) in the analyses. Twelve-week WL did not differ between the genotype-concordant (-5.3 kg [SD:1.0]) and genotype-discordant diets (-4.8 kg [SD:1.1]; adjusted difference: -0.6 kg [95% CI: -2.1,0.9], p = 0.50). With the current ability to genotype participants as fat- or carbohydrate-responders, evidence does not support greater WL on genotype-concordant diets. ClinicalTrials identifier: NCT04145466.

Dietary intake during a pragmatic cluster-randomized weight loss trial in an underserved population in primary care.

BACKGROUND: Currently there are limited data as to whether dietary intake can be improved during pragmatic weight loss interventions in primary care in underserved individuals. METHODS: Patients with obesity were recruited into the PROPEL trial, which randomized 18 clinics to either an intensive lifestyle intervention (ILI) or usual care (UC). At baseline and months 6, 12, and 24, fruit and vegetable (F/V) intake and fat intake was determined. Outcomes were analyzed by repeated-measures linear mixed-effects multilevel models and regression models, which included random cluster (clinic) effects. Secondary analyses examined the effects of race, sex, age, and food security status. RESULTS: A total of 803 patients were recruited. 84.4% were female, 67.2% African American, 26.1% received Medicaid, and 65.5% made less than $40,000. No differences in F/V intake were seen between the ILI and UC groups at months 6, 12, or 24. The ILI group reduced percent fat at months 6, 12, and 24 compared to UC. Change in F/V intake was negatively correlated with weight change at month 6 whereas change in fat intake was positively associated with weight change at months 6, 12, and 24 for the ILI group. CONCLUSIONS: The pragmatic weight loss intervention in primary care did not increase F/V intake but did reduce fat intake in an underserved population with obesity. F/V intake was negatively associated with weight loss at month 6 whereas percent fat was positively correlated with weight loss throughout the intervention. Future efforts better targeting both increasing F/V intake and reducing fat intake may promote greater weight loss in similar populations. TRIAL REGISTRATION: NCT Registration: NCT02561221.

Initial weight loss and early intervention adherence predict long-term weight loss during the Promoting Successful Weight Loss in Primary Care in Louisiana lifestyle intervention.

OBJECTIVE: This study tested whether initial weight change (WC), self-weighing, and adherence to the expected WC trajectory predict longer-term WC in an underserved primary-care population with obesity. METHODS: Data from the intervention group (n = 452; 88% women; 74% Black; BMI 37.3 kg/m2 [SD: 4.6]) of the Promoting Successful Weight Loss in Primary Care in Louisiana trial were analyzed. Initial (2-, 4-, and 8-week) percentage WC was calculated from baseline clinic weights and daily at-home weights. Weights were considered adherent if they were on the expected WC trajectory (10% at 6 months with lower [7.5%] and upper [12.5%] bounds). Linear mixed-effects models tested whether initial WC and the number of daily and adherent weights predicted WC at 6, 12, and 24 months. RESULTS: Percentage WC during the initial 2, 4, and 8 weeks predicted percentage WC at 6 (R2 = 0.15, R2 = 0.28, and R2 = 0.50), 12 (R2 = 0.11, R2 = 0.19, and R2 = 0.32), and 24 (R2 = 0.09, R2 = 0.11, and R2 = 0.16) months (all p < 0.01). Initial daily and adherent weights were significantly associated with WC as individual predictors, but they only marginally improved predictions beyond initial weight loss alone in multivariable models. CONCLUSIONS: These results highlight the importance of initial WC for predicting long-term WC and show that self-weighing and adherence to the expected WC trajectory can improve WC prediction.

Learning about Our Vices from Devices: A Model of Individual Learning with an Application to Consumer Food Waste.

The proliferation of personal, household and workplace sensors and devices has created individual environments rich with purposeful and incidental feedback capable of altering behavior. We formulate an empirical learning model suitable for understanding individual behavioral responses in such environments. We estimate this model using data collected about the joint personal decisions of food selection, intake, and waste during a study in which users photographed their meal selections and plate waste over the course of a week with a cell phone. Despite neutral recruitment language and no expectation that participants would alter food intake in response to the assessment procedures, we found a substantial learning-by-doing effect in plate waste reduction as those who document greater plate waste in their captured photographs waste less on subsequent days. Further we identified that participants reduced plate waste by learning to eat more rather than by learning to reduce the amount of food selected.

A scalable, virtual weight management program tailored for adults with type 2 diabetes: effects on glycemic control.

BACKGROUND: The objective was to test the efficacy of a scalable, virtually delivered, diabetes-tailored weight management program on glycemic control in adults with type 2 diabetes (T2D). METHODS: This was a single arm, three-site clinical trial. Participants had baseline HbA1c between 7-11% and BMI between 27-50 kg/m2. Primary outcome was change in HbA1c at 24 weeks. Secondary outcomes were changes in body weight, waist circumference, the Diabetes Distress Scale (DDS), quality of life (IWQOL-L), and hunger (VAS). Generalized linear effects models were used for statistical analysis. RESULTS: Participants (n = 136) were 56.8 ± 0.8 y (Mean ± SEM), 36.9 ± 0.5 kg/m2, 80.2% female, 62.2% non-Hispanic white. Baseline HbA1c, weight, and total DDS score were 8.0 ± 0.09%, 101.10 ± 1.47 kg, and 2.35 ± 0.08, respectively. At week 24, HbA1c, body weight, and total DDS decreased by 0.75 ± 0.11%, 5.74 ± 0.50%, 0.33 ± 0.10 units, respectively (all p < 0.001). Also, at week 24, quality of life increased by 9.0 ± 1.2 units and hunger decreased by 14.3 ± 2.4 units, (both p < 0.0001). CONCLUSIONS: The scalable, virtually delivered T2D-tailored weight management program had favorable and clinically meaningful effects on glycemic control, body weight, and psychosocial outcomes.

Physical activity and weight loss in a pragmatic weight loss trial.

The purpose of this study was to determine the association between changes in physical activity and changes in body weight in a cluster-randomized weight loss trial conducted in an underserved population in Louisiana. This study reports analyses conducted in the intervention group only, which was a 24-month multi-component weight loss program delivered by health coaches embedded in primary care clinics. Physical activity was assessed at baseline and at 6, 12, and 24 months of follow-up and changes in body weight were expressed as percent weight change from baseline. Among the sample of 402 patients, percent changes in body weight (mean ± SE) across increasing tertiles of changes in walking between baseline and 24 months were -3.2 ± 1.0%, -5.5 ± 0.9%, and -7.3 ± 0.9%, respectively (p = 0.001). Changes in body weight across increasing tertiles of changes in moderate-to-vigorous-intensity activity between baseline and 24 months were -4.3 ± 1.0%, -5.0 ± 0.9%, and -7.0 ± 0.9%, respectively (p = 0.04). In conclusion, this multi-component intervention resulted in clinically significant weight loss, and greater increases in physical activity over the intervention period were associated with greater percent reductions in body weight. These results are consistent with those from other studies conducted primarily in non-underserved populations.

Assessing the Initial Validity of the PortionSize App to Estimate Dietary Intake Among Adults: Pilot and Feasibility App Validation Study.

BACKGROUND: Accurately assessing dietary intake can promote improved nutrition. The PortionSize app (Pennington Biomedical Research Center) was designed to quantify and provide real-time feedback on the intake of energy, food groups, saturated fat, and added sugar. OBJECTIVE: This study aimed to assess the preliminary feasibility and validity of estimating food intake via the PortionSize app among adults. METHODS: A total of 15 adults (aged 18-65 years) were recruited and trained to quantify the food intake from a simulated meal by using PortionSize. Trained personnel prepared 15 simulated meals and covertly weighed (weigh back) the amount of food provided to participants as well as food waste. Equivalence tests (±25% bounds) were performed to compare PortionSize to the weigh back method. RESULTS: Participants were aged a mean of 28 (SD 12) years, and 11 were female. The mean energy intake estimated with PortionSize was 742.9 (SD 328.2) kcal, and that estimated via weigh back was 659.3 (SD 190.7) kcal (energy intake difference: mean 83.5, SD 287.5 kcal). The methods were not equivalent in estimating energy intake (P=.18), and PortionSize overestimated energy intake by 83.5 kcal (12.7%) at the meal level. Estimates of portion sizes (gram weight; P=.01), total sugar (P=.049), fruit servings (P=.01), and dairy servings (P=.047) from PortionSize were equivalent to those estimated via weigh back. PortionSize was not equivalent to weigh back with regard to estimates for carbohydrate (P=.10), fat (P=.32), vegetable (P=.37), grain (P=.31), and protein servings (P=.87). CONCLUSIONS: Due to power limitations, the equivalence tests had large equivalence bounds. Though preliminary, the results of this small pilot study warrant the further adaptation, development, and validation of PortionSize as a means to estimate energy intake and provide users with real-time and actionable dietary feedback.

Mediators of weight change in underserved patients with obesity: exploratory analyses from the Promoting Successful Weight Loss in Primary Care in Louisiana (PROPEL) cluster-randomized trial.

BACKGROUND: Intensive lifestyle interventions (ILIs) stimulate weight loss in underserved patients with obesity, but the mediators of weight change are unknown. OBJECTIVES: We aimed to identify the mediators of weight change during an ILI compared with usual care (UC) in underserved patients with obesity. METHODS: The PROPEL (Promoting Successful Weight Loss in Primary Care in Louisiana) trial randomly assigned 18 clinics (n = 803) to either an ILI or UC for 24 mo. The ILI group received an intensive lifestyle program; the UC group had routine care. Body weight was measured; further, eating behaviors (restraint, disinhibition), dietary intake (percentage fat intake, fruit and vegetable intake), physical activity, and weight- and health-related quality of life constructs were measured through questionnaires. Mediation analyses assessed whether questionnaire variables explained between-group variations in weight change during 2 periods: baseline to month 12 (n = 779) and month 12 to month 24 (n = 767). RESULTS: The ILI induced greater weight loss at month 12 compared with UC (between-group difference: -7.19 kg; 95% CI: -8.43, -6.07 kg). Improvements in disinhibition (-0.33 kg; 95% CI: -0.55, -0.10 kg), percentage fat intake (-0.25 kg; 95% CI: -0.50, -0.01 kg), physical activity (-0.26 kg; 95% CI: -0.41, -0.09 kg), and subjective fatigue (-0.28 kg; 95% CI: -0.46, -0.10 kg) at month 6 during the ILI partially explained this between-group difference. Greater weight loss occurred in the ILI at month 24, yet the ILI group gained 2.24 kg (95% CI: 1.32, 3.26 kg) compared with UC from month 12 to month 24. Change in fruit and vegetable intake (0.13 kg; 95% CI: 0.05, 0.21 kg) partially explained this response, and no variables attenuated the weight regain of the ILI group. CONCLUSIONS: In an underserved sample, weight change induced by an ILI compared with UC was mediated by several psychological and behavioral variables. These findings could help refine weight management regimens in underserved patients with obesity.This trial was registered at clinicaltrials.gov as NCT02561221.

Effects of acute arginine supplementation on neuroendocrine, metabolic, cardiovascular, and mood outcomes in younger men: A double-blind, placebo-controlled trial.

OBJECTIVES: Arginine is an amino-acid supplement and precursor for nitric-oxide synthesis, which affects various biologic processes. The objective of this study was to determine the effects of arginine supplementation on growth hormone (GH) and metabolic parameters. METHODS: Thirty physically active, healthy men (age 18-39 y; body mass index: 18.5-25 kg/m2) were randomized in a double-blind, placebo-controlled, crossover trial. Arginine (10 g) and placebo (0 g) beverages were consumed after an overnight fast. Blood samples were collected at baseline and 1.5, 3.0, and 24 h after supplementation. The primary outcomes were serum GH and metabolomics. Also, amino acids, glucose, insulin, triacylglycerols, thyroid hormones, testosterone, cortisol, dehydroepiandrosterone, and mood state were assessed. Individuals with detectable increases in GH were analyzed separately (responders: n = 16; < 0.05 ng/mL at 1.5 h). Repeated-measure analyses of variance estimated the treatment effects at each timepoint. RESULTS: Arginine levels increased at 1.5 h (146%) and 3.0 h (95%; P ≤ 0.001) and GH (193%) and thyroid-stimulating hormone (TSH; 10%) levels at 24 h (P < 0.05) after arginine versus placebo consumption. Arginine versus placebo increased glucose levels at 1.5 h (5%) and 3.0 h (3%; P ≤ 0.001). Arginine versus placebo did not affect other dependent measures, including mood state (P > 0.05), but changes in the urea, glutamate, and citric-acid pathways were observed. Among responders, arginine versus placebo increased GH at 1.5 h (37%), glucose at 1.5 h (4%) and 3.0 h (4%), and TSH at 24 h (9%; P < 0.05). Responders had higher levels of benzoate metabolites at baseline and 1.5 h, and an unknown compound (X-16124) at baseline, 1.5 h, and 24 h that corresponds to a class of gut microbes (P < 0.05). CONCLUSIONS: Arginine supplementation modestly increased GH, glucose, and TSH levels in younger men. Responders had higher benzoate metabolites and an unknown analyte attributed to the gut microbiome. Future studies should examine whether the increased prevalence of these gut microorganisms corresponds with GH response after arginine supplementation.

Comparison of weight loss data collected by research technicians versus electronic medical records: the PROPEL trial.

BACKGROUND/OBJECTIVES: Pragmatic trials are increasingly used to study the implementation of weight loss interventions in real-world settings. This study compared researcher-measured body weights versus electronic medical record (EMR)-derived body weights from a pragmatic trial conducted in an underserved patient population. SUBJECTS/METHODS: The PROPEL trial randomly allocated 18 clinics to usual care (UC) or to an intensive lifestyle intervention (ILI) designed to promote weight loss. Weight was measured by trained technicians at baseline and at 6, 12, 18, and 24 months. A total of 11 clinics (6 UC/5 ILI) with 577 enrolled patients also provided EMR data (n = 561), which included available body weights over the period of the trial. RESULTS: The total number of assessments were 2638 and 2048 for the researcher-measured and EMR-derived body weight values, respectively. The correlation between researcher-measured and EMR-derived body weights was 0.988 (n = 1 939; p < 0.0001). The mean difference between the EMR and researcher weights (EMR-researcher) was 0.63 (2.65 SD) kg, and a Bland-Altman graph showed good agreement between the two data collection methods; the upper and lower boundaries of the 95% limits of agreement are -4.65 kg and +5.91 kg, and 71 (3.7%) of the values were outside the limits of agreement. However, at 6 months, percent weight loss in the ILI compared to the UC group was 7.3% using researcher-measured data versus 5.5% using EMR-derived data. At 24 months, the weight loss maintenance was 4.6% using the technician-measured data versus 3.5% using EMR-derived data. CONCLUSION: At the group level, body weight data derived from researcher assessments and an EMR showed good agreement; however, the weight loss difference between ILI and UC was blunted when using EMR data. This suggests that weight loss studies that rely on EMR data may require larger sample sizes to detect significant effects. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number NCT02561221.

Intraclass correlation coefficients for weight loss cluster randomized trials in primary care: The PROPEL trial.

The aim of this study was to compute intra-class correlations (ICCs) for weight-related and patient-reported outcomes in a cluster randomized clinical trial (cRCT) for weight loss. Baseline and follow-up data from the Promoting Successful Weight Loss in Primary Care in Louisiana (PROPEL) cRCT were used in this analysis. ICCs were computed for baseline and follow-up measures, and changes in body weight, cardiometabolic risk factors and health-related and weight-related quality of life at 6, 12, 18 and 24 months. Baseline ICCs ranged from 0 for PROMIS measures of anxiety and fatigue to 0.055 for total cholesterol (median = 0.019). The ICCs were higher for changes and decreased over time during follow-up. The ICCs for changes were highest in the pooled sample (intervention and usual care combined) followed by the intervention and usual care groups, respectively. The results demonstrated significant ICCs for several outcomes in a weight loss cRCT. The ICCs differed in magnitude depending on whether baseline versus longitudinal data were used, whether data were combined across treatment arms or were considered separately, and varied across the follow-up period. All these factors must be considered when choosing an ICC to inform sample size estimates for future weight loss cRCTs conducted in primary care settings.

A Randomized Controlled Trial to Address Consumer Food Waste with a Technology-aided Tailored Sustainability Intervention.

There is growing concern whether pro-environmental behavioral interventions can generate sufficient reductions in carbon emissions to address climate change. While many have suggested enhanced tailoring of interventions to increase effect sizes, and while individual tailoring is common among health interventions, little is known about how individual tailoring may impact effect sizes for pro-environmental behavioral interventions. Using a novel technology-aided delivery and measurement approach, we conduct a randomized controlled trial featuring an individually tailored intervention focused on reducing the amount of food wasted by participants over approximately one week in their normal living conditions. We find large significant effects for the focal area of food wasted during dining (a 79% reduction), a null effect on food wasted over all household stages (preparation, dining and clean outs), and desirable or null effects for critical antecedent (e.g., waste during preparation, continued purchases of fresh produce), concurrent (e.g., food selection and consumption), and attendant behaviors (e.g., waste from storage clean outs, avoiding waste deposits in landfills).

Effect of 8 weeks of supervised overfeeding on eating attitudes and behaviors, eating disorder symptoms, and body image: Results from the PROOF and EAT studies.

The physiological and metabolic effects of experimental overfeeding have been extensively studied, yet only few studies have assessed overfeeding effects on eating behaviors and psychological constructs. We analyzed two 8-week overfeeding studies, the PROOF Study (N = 25; 16 males; 16 African American; 24.1 years; 25.1 kg/m2, inpatient) and the EAT Study (N = 35; 29 males; 20 White; 26.7 years; 25.5 kg/m2, free-living). In both studies, participants were overfed 40% above baseline (daily) energy requirements for eight weeks, consuming all meals under direct supervision. We assessed eating attitudes and behaviors, eating disorder symptoms, and body image via validated questionnaires and visual analog scales at baseline, week (W) 4, and W8, and at two (PROOF: W16-Post, W24-Post) and three (EAT: W12-Post, W20-Post, W32-Post) follow-up visits, respectively. Hunger, desire to eat, and food cravings (carbohydrates, total cravings) decreased during overfeeding in both studies (all Cohen's d effect sizes ≥0.3, all p ≤ .048). Depressive symptoms and fear of fatness increased in both studies (all Cohen's d ≥ 0.4, p ≤ .020), though they were still within normal limits (t-scores ~43-49). Body dissatisfaction increased in both studies during overfeeding (all Cohen's d ≥ 0.4, all p ≤ .044) and remained increased during follow-up (PROOF: W16-Post, Cohen's d = 0.9, p = .004; EAT: W12-Post and W20-Post, all Cohen's d ≥ 0.4, all p ≤ .037). Overfeeding was associated with some deleterious effects, though most returned to baseline during follow-up. However, increases in body dissatisfaction remained up to three months post-overfeeding, highlighting the need to address body image disturbance among people who experience weight gain, even if much of the gained weight is subsequently lost. TRIAL REGISTRATION: The PROOF Study (ClinicalTrials.gov Identifier NCT00565149); the EAT Study (ClinicalTrials.gov Identifier NCT01672632).

Preference, Expected Burden, and Willingness to Use Digital and Traditional Methods to Assess Food and Alcohol Intake.

We conducted an online survey to examine the preference, expected burden, and willingness of people to use four different methods of assessing food and alcohol intake such as food/drink record, 24-h recall, Remote Food Photography Method© (RFPM, via SmartIntake® app), and a novel app (PortionSize®) that allows the in-app portion size estimation of foods/drinks by the user. For food (N = 1959) and alcohol (N = 466) intake assessment, 67.3% and 63.3%, respectively, preferred the RFPM/SmartIntake®, 51.9% and 53.4% preferred PortionSize®, 48.0% and 49.3% the food records, and 32.9% and 33.9% the 24-h recalls (difference in preference across all methods was p < 0.001 for food and alcohol intake). Ratings of burden and preference of methods were virtually superimposable, and we found strong correlations between high preference and low expected burden for all methods (all ρ ≥ 0.82; all p < 0.001). Willingness (mean (SD)) to use the RFPM/SmartIntake® (food: 6.6 (2.0); alcohol: 6.4 (2.4)) was greater than PortionSize® (food: 6.0 (2.2); alcohol: 6.0 (2.4); all p < 0.001) and 24-h recalls (food: 6.1 (2.2); alcohol: 5.7 (2.7); p < 0.001), but not different from food records (food: 6.6 (2.0); alcohol: 6.5 (2.3); all p ≥ 0.33). Our results can be used in conjunction with existing data on the reliability and validity of these methods in order to inform the selection of methods for the assessment of food and alcohol intake.

Weight loss in primary care: A pooled analysis of two pragmatic cluster-randomized trials.

OBJECTIVE: The aim of this study was to report the results of five weight-loss interventions in primary care settings in underserved patients and to compare the level of pragmatism across the interventions using the Pragmatic Explanatory Continuum Indicator Summary (PRECIS-2) tool. METHODS: Data from 54 primary care clinics (2,210 patients) were pooled from the Promoting Successful Weight Loss in Primary Care in Louisiana (PROPEL) and Rural Engagement in Primary Care for Optimizing Weight Reduction (REPOWER) cluster-randomized trials. Clinics were randomized to one of five comparators: PROPEL usual care, PROPEL combination of in-clinic and telephone visits, REPOWER in-clinic individual visits, REPOWER in-clinic group visits, or REPOWER telephone group visits. RESULTS: At 24 months, weight loss (kilograms) was -0.50 (95% CI: -1.77 to 0.76), -3.05 (-4.10 to -2.01), -4.30 (-5.35 to -3.26), -4.79 (-5.83 to -3.75), and -4.80 (-5.96 to -3.64) in the PROPEL usual care, REPOWER in-clinic individual visits, REPOWER telephone group visits, REPOWER in-clinic group visits, and PROPEL in-clinic and telephone visits arms, respectively. At 24 months, percentage of weight loss was -0.360 (-1.60 to 0.88), -3.00 (-4.02 to -1.98), -4.23 (-5.25 to -3.20), -4.67 (-5.69 to -3.65), and -4.69 (-5.82 to -3.56), respectively, in the five arms. The REPOWER in-clinic individual visits intervention was the most pragmatic and reflects the current Centers for Medicare and Medicaid Services funding model, although this intervention produced the least weight loss. CONCLUSIONS: Clinically significant weight loss over 6 months in primary care settings is achievable using a variety of lifestyle-based treatment approaches. Longer-term weight-loss maintenance is more difficult to achieve.

Meal composition during an ad libitum buffet meal and longitudinal predictions of weight and percent body fat change: The role of hyper-palatable, energy dense, and ultra-processed foods.

BACKGROUND: Foods that increase obesity risk are ubiquitous in the US food environment. Such foods may be the target of hedonic eating, which may facilitate weight gain and lead to obesity. The study tested whether meal composition during an ad libitum buffet meal was associated with 1-year weight and percent body fat changes among healthy younger adults without obesity. Hyper-palatable foods (HPF) were the study focus; comparisons were conducted with high energy dense (HED) and ultra-processed foods (UPF). DESIGN: Younger adults without obesity (N = 82; 43% male; mean age 26.8) completed an ad libitum buffet meal and provided body composition measurements at baseline and 1-year follow up. Multiple regression models tested associations between the proportion of the target food consumed (HPF, HED, or UPF) during the ad libitum meal and 1) weight change and 2) percent body fat change. The proportion of HPF was characterized by HPF group, specifically carbohydrate and sodium (CSOD) foods or fat and sodium (FSOD) foods. RESULTS: Participants who consumed a greater proportion of CSOD HPF in their ad libitum buffet meals had significantly greater weight change (b = 0.354, p = .003) and percent body fat change (b = 0.247, p = .036) at 1-year follow up. In contrast, no significant associations were found between the proportion of FSOD HPF, HED, or UPF consumed and anthropometric outcomes (p values = .099-.938). CONCLUSIONS: Eating a greater proportion of hyper-palatable CSOD foods ad libitum appears to be a pattern of hedonic eating, which may increase an individual's risk for weight and body fat gain in early adulthood.