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Rating of perceived exertion (RPE) and respiratory exchange ratio (RER) have previously been associated with acute exercise compensation. This study examined adaptations in the RPE and RER with long-term exercise training in individuals who did (noncompensators) and did not (compensators) lose the expected amount of weight. Participants ( n = 110, 71.8% women, means ± SD; age 49 ± 12 yr) completed 24 wk of supervised exercise training at 65-85% V̇o 2peak to achieve a prescribed dose of 8 kcal·kg body wt -1 ·wk -1 (8 KKW) or 20 KKW. Participants were categorized as noncompensators ( n = 55) or compensators ( n = 55) based on the percent of expected weight loss (%EWL) achieved. Changes in RPE and RER during exercise over time (baseline, week 12 , week 24 ) were compared by weight compensation category. Individual %EWL in relation to RPE, RER, and training intensity (%V̇o 2peak ) was evaluated over the same time period. RPE and RER for a given workload decreased from baseline to week 12 and stabilized through week 24 , regardless of weight compensation (time P < 0.0001). Noncompensators had a higher RPE relative to heart rate, which was partly explained by higher %V̇o 2peak . RPE and %V̇o 2peak both positively predicted %EWL, independent of age, sex, and exercise dose. Training intensity and RPE were positively associated with weight loss on the individual level, warranting further investigation into self-selection in exercise-based programs. Understanding individual heterogeneity in training intensity and behavioral responses may improve future weight management efforts that involve exercise. NEW & NOTEWORTHY In sedentary individuals with overweight and obesity, achievement of expected weight loss from long-term exercise training was associated with individual adaptations in perceived exertion. Contrary to our hypothesis, those with higher relative perceived exertion achieved a larger proportion of their expected weight loss, which was partly explained by a higher self-selected exercise training intensity.

Objective: Food cravings are thought to be the result of conditioning or pairing hunger with consumption of certain foods., Methods: In a 2-year weight loss trial, subjects were randomized to one of four diets that varied in macronutrient content. The Food Craving Inventory (FCI) was used to measure cravings at baseline and at 6 and 24 months. Food intake was also measured at those time points. To measure free-living consumption of food items measured in the FCI, items on the FCI were matched to the foods consumed from the food intake assessments. Secondarily, the amount of food consumed on food intake assessments from foods on the FCI was analyzed., Results: Three hundred and sixty-seven subjects with overweight and obesity were included. There was an association between change from baseline FCI item consumption and change in cravings at months 6 (P < 0.001) and 24 (P < 0.05). There was no association between change from baseline amount of energy consumed per FCI item and change in cravings., Conclusions: Altering frequency of consuming craved foods is positively associated with cravings; however, changing the amount of foods consumed does not appear to alter cravings. These results support the conditioning model of food cravings and provide guidance on how to reduce food cravings., (© 2017 The Obesity Society.)

Background: Prepregnancy maternal obesity and excessive weight gain during pregnancy lead to significant morbidities in mothers and their children. Mothers who never return to their prepregnancy weight begin subsequent pregnancies at a greater weight and have a larger propensity for excess gestational weight gain and postpartum weight retention., Methods: In this pilot study, 40 postpartum women credentialed to receive postpartum women, infants, and children (WIC) service were randomized to usual care ("WIC Moms") or a personalized health intervention delivered via a SmartPhone ("E-Moms"). Assessments, including body weight, vital signs, circumferences, and body composition, were completed at week 0 (6-8 weeks postpartum), week 8, and week 16., Results: Results are presented as change from week 0 at 16. As per the completers analysis, body weight change was not different between the groups (WIC Moms vs. E-Moms; 1.8 ± 0.9 vs. -0.1 ± 0.9 kg; p = 0.10), neither was the change in percent body fat (1.7 ± 0.6 vs. 0.1% ± 0.6%; p = 0.90) or waist/hip ratio (-0.01 ± 0.01 vs. -0.02 ± 0.01 cm; p = 0.60). However, due to notable variability in intervention adherence as the study progressed, participants were classified post hoc as having low (<40% adherence), medium (40%-70% adherence), or high adherence (>70% adherence). Participants with high intervention adherence (n = 5) had a significant reduction in body weight (-3.6 ± 1.6 vs. 1.8 ± 0.9 kg; p = 0.005) and percent body fat (-2.5 ± 1.0 vs. 1.7% ± 0.6%; p = 0.001) when compared to WIC Moms., Conclusions: Overall, the E-Moms intervention was not able to decrease postpartum weight retention in women receiving WIC benefits compared to usual care received through the current WIC program. However, there is some evidence to suggest improved adherence to the intervention would improve weight management.

Background: Weight loss induced only by exercise is frequently less than expected, possibly because of compensatory changes in energy intake and/or energy expenditure. The purpose of the Examination of Mechanisms (E-MECHANIC) of Exercise-Induced Weight Compensation trial is to examine whether increased energy intake and/or reduced spontaneous activity or energy expenditure (outside of structured exercise) account for the less than expected, exercise-associated weight loss., Methods/design: E-MECHANIC is a three-arm, 6-month randomized (1:1:1) controlled trial. The two intervention arms are exercise doses that reflect current recommendations for (1) general health (8 kcal/kg body weight per week (8 KKW), about 900 kcal/wk) and (2) weight loss (20 KKW, about 2,250 kcal/wk). The third arm, a nonexercise control group, will receive health information only. The sample will include a combined total of 198sedentary, overweight or obese (body mass index: ≥25 kg/m² to ≤45 kg/m²) men and women ages 18 to 65 years. The exercise dose will be supervised and tightly controlled in an exercise training laboratory. The primary outcome variables are energy intake, which will be measured using doubly labeled water (adjusted for change in energy stores) and laboratory-based food intake tests, and the discrepancy between expected weight loss and observed weight loss. Secondary outcomes include changes in resting metabolic rate (adjusted for change in body mass), activity levels (excluding structured exercise) and body composition. In an effort to guide the development of future interventions, the participants will be behaviorally phenotyped and defined as those who do compensate (that is, fail to lose the amount of weight expected) or do not compensate (that is, lose the amount of weight expected or more)., Discussion: In this study, we will attempt to identify underlying mechanisms to explain why exercise elicits less weight loss than expected. This information will guide the development of interventions to increase exercise-induced weight loss and maximize weight loss retention and related health benefits., Trial Registration: ClinicalTrials.gov ID: NCT01264406 (registration date: 20 December 2010).

Objective. Little is known about the impact of loneliness on physical health among elderly individuals with diabetes. Here, we examined the relationship of loneliness with disability, objective physical function, and other health outcomes in older individuals with type 2 diabetes and overweight or obesity. Method. Data are drawn from the Look AHEAD study, a diverse cohort of individuals (ages 61–92) with overweight or obesity and type 2 diabetes measured 5–6 years after a 10-year weight loss randomized, controlled trial. Results. Loneliness scores were significantly associated with greater disability symptoms and slower 4-meter gait speed (p s < 0.01). Loneliness did not differ across treatment arms. Discussion. Overall, these results extend prior findings relating loneliness to disability and decreased mobility to older individuals with type 2 diabetes and overweight or obesity. [ABSTRACT FROM AUTHOR]

Background Exercise is recommended for weight management, yet exercise produces less weight loss than expected, which is called weight compensation. The mechanisms for weight compensation are unclear. Objective The aim of this study was to identify the mechanisms responsible for compensation. Methods In a randomized controlled trial conducted at an academic research center, adults (n  = 198) with overweight or obesity were randomized for 24 wk to a no-exercise control group or 1 of 2 supervised exercise groups: 8 kcal/kg of body weight/wk (KKW) or 20 KKW. Outcome assessment occurred at weeks 0 and 24. Energy intake, activity, and resting metabolic rate (RMR) were measured with doubly labeled water (DLW; with and without adjustments for change in RMR), armband accelerometers, and indirect calorimetry, respectively. Appetite and compensatory health beliefs were measured by self-report. Results A per-protocol analysis included 171 participants (72.5% women; mean ± SD baseline body mass index: 31.5 ± 4.7 kg/m2). Significant (P  < 0.01) compensation occurred in the 8 KKW (mean: 1.5 kg; 95% CI: 0.9, 2.2 kg) and 20 KKW (mean: 2.7 kg; 95% CI: 2.0, 3.5 kg) groups, and compensation differed significantly between the exercise groups (P  = 0.01). Energy intake by adjusted DLW increased significantly (P  < 0.05) in the 8 KKW (mean: 90.7 kcal/d; 95% CI: 35.1, 146.4 kcal/d) and 20 KKW (mean: 123.6 kcal/d; 95% CI: 64.5, 182.7 kcal/d) groups compared with control (mean: −2.3 kcal/d; 95% CI: −58.0, 53.5 kcal/d). Results were similar without DLW adjustment. RMR and physical activity (excluding structured exercise) did not differentially change among the 3 groups. Participants with higher compared with lower compensation reported increased appetite ratings and beliefs that healthy behaviors can compensate for unhealthy behaviors. Furthermore, they increased craving for sweet foods, increased sleep disturbance, and had worsening bodily pain. Conclusions Compensation resulted from increased energy intake and concomitant increases in appetite, which can be treated with dietary or pharmacological interventions. Compensation was not due to activity or metabolic changes. This trial was registered at clinicaltrials.gov as NCT01264406. [ABSTRACT FROM AUTHOR]

Background: Synonymous with increased use of mobile phones has been the development of mobile health (mHealth) technology for improving health, including weight management. Behavior change theory (eg, the theory of planned behavior) can be effectively encapsulated into mobile phone-based health improvement programs, which is fostered by the ability of mobile phones and related devices to collect and transmit objective data in near real time and for health care or research professionals and clients to communicate easily. Objective: To describe SmartLoss, a semiautomated mHealth platform for weight loss. Methods: We developed and validated a dynamic energy balance model that determines the amount of weight an individual will lose over time if they are adherent to an energy intake prescription. This model was incorporated into computer code that enables adherence to a prescribed caloric prescription determined from the change in body weight of the individual. Data from the individual are then used to guide personalized recommendations regarding weight loss and behavior change via a semiautomated mHealth platform called SmartLoss, which consists of 2 elements: (1) a clinician dashboard and (2) a mobile phone app. SmartLoss includes and interfaces with a network-connected bathroom scale and a Bluetooth-connected accelerometer, which enables automated collection of client information (eg, body weight change and physical activity patterns), as well as the systematic delivery of preplanned health materials and automated feedback that is based on client data and is designed to foster prolonged adherence with body weight, diet, and exercise goals. The clinician dashboard allows for efficient remote monitoring of all clients simultaneously, which may further increase adherence, personalization of treatment, treatment fidelity, and efficacy. Results: Evidence of the efficacy of the SmartLoss approach has been reported previously. The present report provides a thorough description of the SmartLoss Virtual Weight Management Suite, a professionally programmed platform that facilitates treatment fidelity and the ability to customize interventions and disseminate them widely. Conclusions: SmartLoss functions as a virtual weight management clinic that relies upon empirical weight loss research and behavioral theory to promote behavior change and weight loss. [ABSTRACT FROM AUTHOR]

Background: Intensive lifestyle interventions (ILIs) are the first-line approach to effectively treat obesity and manage associated cardiometabolic risk factors. Because few people have access to ILIs in academic health centers, primary care must implement similar approaches for a meaningful effect on obesity and cardiometabolic disease prevalence. To date, however, effective lifestyle-based obesity treatment in primary care is limited. We examined the effectiveness of a pragmatic ILI for weight loss delivered in primary care among a racially diverse, low-income population with obesity for improving cardiometabolic risk factors over 24 months.Methods: The PROPEL trial (Promoting Successful Weight Loss in Primary Care in Louisiana) randomly allocated 18 clinics equally to usual care or an ILI and subsequently enrolled 803 (351 usual care, 452 ILI) adults (67% Black, 84% female) with obesity from participating clinics. The usual care group continued to receive their normal primary care. The ILI group received a 24-month high-intensity lifestyle-based obesity treatment program, embedded in the clinic setting and delivered by health coaches in weekly sessions initially and monthly sessions in months 7 through 24.Results: As recently demonstrated, participants receiving the PROPEL ILI lost significantly more weight over 24 months than those receiving usual care (mean difference, -4.51% [95% CI, -5.93 to -3.10]; P<0.01). Fasting glucose decreased more in the ILI group compared with the usual care group at 12 months (mean difference, -7.1 mg/dL [95% CI, -12.0 to -2.1]; P<0.01) but not 24 months (mean difference, -0.8 mg/dL [95% CI, -6.2 to 4.6]; P=0.76). Increases in high-density lipoprotein cholesterol were greater in the ILI than in the usual care group at both time points (mean difference at 24 months, 4.6 mg/dL [95% CI, 2.9-6.3]; P<0.01). Total:high-density lipoprotein cholesterol ratio and metabolic syndrome severity (z score) decreased more in the ILI group than in the usual care group at both time points, with significant mean differences of the change of -0.31 (95% CI, -0.47 to -0.14; P<0.01) and -0.21 (95% CI, -0.36 to -0.06; P=0.01) at 24 months, respectively. Changes in total cholesterol, low-density lipoprotein cholesterol, triglycerides, and blood pressure did not differ significantly between groups at any time point.Conclusions: A pragmatic ILI consistent with national guidelines and delivered by trained health coaches in primary care produced clinically relevant improvements in cardiometabolic health in an underserved population over 24 months. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02561221. [ABSTRACT FROM AUTHOR]