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The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk.

When a hypocaloric, low-fat diet is prescribed, intake of currently consumed foods can decrease, foods naturally low in fat and/or added sugar may increase, or fat- or sugar-modified foods may increase.To examine food group intake change and its relation to reductions in energy and fat intake and weight during a lifestyle intervention.Secondary cohort analysis.One hundred sixty-nine participants (aged 52.0±8.6 years, body mass index 34.9±4.5, 92% white, 97.6% non-Hispanic, and 56.8% women) with complete data at 0 and 6 months collected in a research setting.From three 24-hour telephone dietary recalls, 165 food groups from Nutrition Data System for Research software were coded into 25 larger food groups assessing intake of higher-fat and/or added-sugar food groups vs naturally lower-fat and/or added-sugar food groups and into 17 larger food groups assessing intake of nonmodified vs fat- and/or sugar-modified food groups.Repeated measures analyses of covariance (intervention group: covariate) assessed changes from 0 to 6 months. Hierarchical regressions examined changes in food group intake and changes in energy intake, percent energy from fat intake, and weight from 0 to 6 months.Significant reductions (P0.05) in intake of high-fat and/or high-added-sugar food groups (Higher-Fat Dairy; Higher-Fat Eggs; Higher-Fat Fats; Higher-Fat Fruit; Higher-Fat Meat; Nonmodified Higher-Fat Fats, Oils, and Sweets; Nonmodified Higher-Fat Sugar-Sweetened Fats, Oils, and Sweets; Nonmodified Regular-Fat Dairy; and Nonmodified Regular-Fat Sugar-Sweetened Dairy) occurred. Decreases in the Higher-Fat Meat group were significantly (P0.05) related to decreases in energy intake, percent energy from fat intake, and weight.When a hypocaloric, low-fat diet is prescribed, reductions in high-fat and/or high-added-sugar food groups occur. Targeting reductions in high-fat meats may improve outcomes.

BACKGROUND Since many successful dieters regain the weight they lose, programs that teach maintenance skills are needed. We developed a maintenance program based on self-regulation theory and tested the efficacy of delivering the program face to face or over the Internet. METHODS We randomly assigned 314 participants who had lost a mean of 19.3 kg of body weight in the previous 2 years to one of three groups: a control group, which received quarterly newsletters (105 participants), a group that received face-to-face intervention (105), and a group that received Internet-based intervention (104). The content of the programs in the two intervention groups was the same, emphasizing daily self-weighing and self-regulation, as was the frequency of contact with the groups. The primary outcome was weight gain over a period of 18 months. RESULTS The mean (��SD) weight gain was 2.5��6.7 kg in the face-to-face group, 4.7��8.6 kg in the Internet group, and 4.9��6.5 kg in the control group, with a significant difference between the face-to-face group and the control group (2.4 kg; 95% confidence interval [CI], 0.002 to 10.8; P=0.05). The proportion of participants who regained 2.3 kg or more over the 18-month period was significantly higher in the control group (72.4%) than in the face-to-face group (45.7%; absolute difference, 27%; 95% CI, 14 to 39; P

OBJECTIVE: To examine the effect of experimental changes in children’s sleep duration on self-reported food intake, food reinforcement, appetite-regulating hormones, and measured weight. METHODS: Using a within-subjects, counterbalanced, crossover design, 37 children, 8 to 11 years of age (27% overweight/obese) completed a 3-week study. Children slept their typical amount at home for 1 week and were then randomized to either increase or decrease their time in bed by 1.5 hours per night for 1 week, completing the alternate schedule on the third week. Primary outcomes were dietary intake as assessed by 24-hour dietary recalls, food reinforcement (ie, points earned for a food reward), and fasting leptin and ghrelin. The secondary outcome was child weight. RESULTS: Participants achieved a 2 hour, 21 minute difference in the actigraph defined sleep period time between the increase and decrease sleep conditions (P < .001). Compared with the decrease sleep condition, during the increase condition, children reported consuming an average of 134 kcal/day less (P < .05), and exhibited lower fasting morning leptin values (P < .05). Measured weights were 0.22 kg lower during the increase sleep than the decrease sleep condition (P < .001). There were no differences in food reinforcement or in fasting ghrelin. CONCLUSIONS: Compared with decreased sleep, increased sleep duration in school-age children resulted in lower reported food intake, lower fasting leptin levels, and lower weight. The potential role of sleep duration in pediatric obesity prevention and treatment warrants further study.

Current literature emphasizes poor long-term weight loss maintenance (WTLM) outcomes, and the need for inexpensive, practical solutions for effective WTLM is evident. Individuals successful at WTLM utilize similar behaviors but in varying amounts and combinations, seemingly choosing behaviors that best fit their preferences. Researchers have attempted to identify characteristics of individuals that may predict successful WTLM in order to develop flexible WTLM treatments based on individuals' lifestyle and preferences. The purpose of this analysis was to examine sex differences in WTLM outcomes and to identify potential behaviors related to WTLM success. In a 12-month study targeting WTLM, weight-reduced middle-aged and older men and women (n=39) were assigned behavioral goals for body weight, fruit and vegetable intake, water consumption, and physical activity and were asked to daily self-monitor body weight and these behaviors. Sex difference in clinically significant WL ≥5% WL) at 12 months was determined. A growth curve model assessed interactions of sex and WTLM predictors, and a crisp set qualitative comparative analysis (QCA) characterized individuals' weight changes and behaviors. No sex difference was found in clinically significant WL or in the interaction of sex and behaviors on weight change; however, QCA evidence suggests men and women may approach WTLM with different behaviors. Additionally, QCA findings suggest weight change in the first 3 months of WTLM may determine success at 12-months. WTLM treatments should provide more intensive support during the transition period from WL to WTLM. Future research in predictors of WTLM, particularly within the context of sex, is essential. Master of Science