Objective: The objective of this study was to compare physical activity energy expenditure (PAEE) and total daily energy expenditure (TDEE) in successful weight loss maintainers (WLM) with normal weight controls (NC) and controls with overweight/obesity (OC). Methods: Participants were recruited in three groups: WLM (n = 25, BMI 24.1 ± 2.3 kg/m²; maintaining ≥ 13.6‐kg weight loss for ≥ 1 year), NC (n = 27, BMI 23.0 ± 2.0 kg/m²; similar to current BMI of WLM), and OC (n = 28, BMI 34.3 ± 4.8 kg/m²; similar to pre–weight loss BMI of WLM). TDEE was measured using the doubly labeled water method. Resting energy expenditure (REE) was measured using indirect calorimetry. PAEE was calculated as (TDEE − [0.1 × TDEE] − REE). Results: PAEE in WLM (812 ± 268 kcal/d, mean ± SD) was significantly higher compared with that in both NC (621 ± 285 kcal/d, P < 0.01) and OC (637 ± 271 kcal/d, P = 0.02). As a result, TDEE in WLM (2,495 ± 366 kcal/d) was higher compared with that in NC (2,195 ± 521 kcal/d, P = 0.01) but was not significantly different from that in OC (2,573 ± 391 kcal/d). Conclusions: The high levels of PAEE and TDEE observed in individuals maintaining a substantial weight loss (−26.2 ± 9.8 kg maintained for 9.0 ± 10.2 years) suggest that this group relies on high levels of energy expended in physical activity to remain in energy balance (and avoid weight regain) at a reduced body weight.

Altered gut microbiota has been linked to obesity and may influence weight loss. We are conducting an ongoing weight loss trial, comparing daily caloric restriction (DCR) to intermittent fasting (IMF) in adults who are overweight or obese. We report here an ancillary study of the gut microbiota and selected obesity-related parameters at the baseline and after the first three months of interventions. During this time, participants experienced significant improvements in clinical health measures, along with altered composition and diversity of fecal microbiota. We observed significant associations between the gut microbiota features and clinical measures, including weight and waist circumference, as well as changes in these clinical measures over time. Analysis by intervention group found between-group differences in the relative abundance of Akkermansia in response to the interventions. Our results provide insight into the impact of baseline gut microbiota on weight loss responsiveness as well as the early effects of DCR and IMF on gut microbiota.

Objective: The objective of this study was to compare patterns of objectively measured moderate‐to‐vigorous physical activity (MVPA, ≥ 3.00 metabolic equivalents [METs]), light‐intensity physical activity (LPA, 1.50‐2.99 METs), and sedentary behavior (SB, < 1.50 METs) in successful weight loss maintainers (WLMs), normal weight controls (NC), and controls with overweight/obesity (OC).Methods: Participants (18‐65 y) were recruited in three groups: WLM (maintaining ≥ 13.6‐kg weight loss for ≥ 1 year, n = 30), NC (BMI matched to current BMI of WLM, n = 33), and OC (BMI matched to pre–weight loss BMI of WLM, n = 27). All participants wore the activPAL for 1 week.Results: Compared with OC and NC, WLM spent more awake time in total MVPA (WLM: 9.6 ± 3.9%, NC: 7.1 ± 2.1%, OC: 5.9 ± 2.0%; P < 0.01) and more time in sustained (≥ 10 min) bouts of MVPA (WLM: 39 ± 33, NC: 17 ± 14, OC: 9 ± 11 min/d; P < 0.01). Compared with OC, WLM and NC spent more awake time in LPA (WLM: 29.6 ± 7.9%, NC: 29.1 ± 8.3%, OC: 24.8 ± 6.7%; P = 0.04) and less awake time sedentary (WLM: 60.8 ± 9.3%, NC: 63.8 ± 9.5%, OC: 69.3 ± 7.5%; P < 0.01).Conclusions: Results provide additional data supporting the important role of MVPA in weight loss maintenance and suggest notable differences in LPA and SB between normal weight individuals and those with overweight/obesity. Increasing LPA and/or decreasing SB may be additional potential targets for weight management interventions.

This article describes geospatial datasets and exemplary data across five environmental domains (walkability, socioeconomic deprivation, urbanicity, personal safety, and food outlet accessibility). The environmental domain is one of four domains (behavioral, biological, environmental and psychosocial) in which the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project suggested measures to help explain variation in responses to weight loss interventions. These data are intended to facilitate additional research on potential environmental moderators of responses to weight loss, physical activity, or diet related interventions. These data represent a mix of publicly and commercially available pre-existing data that were downloaded, cleaned, restructured and analyzed to create datasets at the United States (U.S.) block group and/or census tract level for the five domains. Additionally, the resource includes detailed methods for obtaining, cleaning and summarizing two datasets concerning safety and the food environment that are only available commercially. Across the five domains considered, we include component as well as derived variables for three of the five domains. There are two versions of the National Walkability Index Dataset (one based on 2013 data and one on 2019 data) consisting of 15 variables. The Neighborhood Deprivation Index dataset contains 18 variables and is based on the US Census Bureau's 5-year American Community Survey (ACS) data for 2013–2017. The urbanicity dataset contains 11 variables and is based on USDA rural-urban commuting (RUCA) codes and Census Bureau urban/rural population data from 2010. Personal safety and food outlet accessibility data were purchased through commercial vendors and are not in the public domain. Thus, only exemplary figures and detailed instructions are provided. The website housing these datasets and examples should serve as a valuable resource for researchers who wish to examine potential environmental moderators of responses to weight loss and related interventions in the U.S.

Evidence in humans is equivocal in regards to whether resting energy expenditure (REE) decreases to a greater extent than predicted for the loss of body mass with weight loss, and whether this disproportionate decrease in REE persists with weight-loss maintenance. We aimed to1) determine if a lower-than-predicted REE is present in a sample of successful weight-loss maintainers (WLMs) and 2) determine if amount of weight loss or duration of weight-loss maintenance are correlated with a lower-than-predicted REE in WLMs. Participants (18–65 y old) were recruited in 3 groups: WLMs (maintaining ≥13.6 kg weight loss for ≥1 y, n = 34), normal-weight controls [NCs, body mass index (BMI; in kg/m²) similar to current BMI of WLMs, n = 35], and controls with overweight/obesity (OCs, BMI similar to pre–weight-loss maximum BMI of WLMs, n = 33). REE was measured (REE_m) with indirect calorimetry. Predicted REE (REE_p) was determined via 1) a best-fit linear regression developed with the use of REE_m, age, sex, fat-free mass, and fat mass from our control groups and 2) three standard predictive equations. REE_m in WLMs was accurately predicted by equations developed from NCs and OCs (±1%) and by 3 standard predictive equations (±3%). In WLMs, individual differences between REE_m and REE_p ranged from −257 to +163 kcal/d. A lower REE_m compared with REE_p was correlated with amount of weight lost (r = 0.36, P < 0.05) but was not correlated with duration of weight-loss maintenance (r = 0.04, P = 0.81). We found no consistent evidence of a significantly lower REE than predicted in a sample of long-term WLMs based on predictive equations developed from NCs and OCs as well as 3 standard predictive equations. Results suggest that sustained weight loss may not always result in a substantial, disproportionately low REE. This trial was registered at clinicaltrials.gov as NCT03422380.

Long-term (≥12 months) randomized trials evaluating the efficacy of intermittent fasting (IMF) as a dietary weight loss strategy are limited. Furthermore, no studies have compared IMF versus daily caloric restriction (DCR) when both interventions are provided in the context of a guidelines-based behavioral weight loss program. To compare the effects of 4:3 IMF versus DCR on changes in weight at 12 months, with comprehensive behavioral support provided to both groups. Randomized clinical trial. (ClinicalTrials.gov: NCT03411356). Denver, Colorado, and surrounding metropolitan area. Adults aged 18 to 60 years with body mass index (BMI) of 27 to 46 kg/m². The IMF group was instructed to restrict energy intake by 80% on 3 nonconsecutive days per week, with ad libitum intake (no restriction) the other 4 days (4:3 IMF). The DCR group was instructed to reduce daily energy intake by 34% to match the weekly energy deficit of 4:3 IMF. Both groups received a high-intensity comprehensive behavioral weight loss program that included group-based behavioral support and a recommendation to increase moderate-intensity physical activity to 300 minutes per week. The primary outcome was change in body weight (in kilograms) at 12 months. Of the 165 (4:3 IMF, n = 84; DCR, n = 81) randomly assigned participants (mean age, 42 years [SD, 9]; mean BMI, 34.1 kg/m² [SD, 4.4]; 73.9% female), 125 completed the trial. In an intention-to-treat analysis, 4:3 IMF showed greater reductions in weight than DCR at 12 months (mean difference, 2.89 kg [95% CI, 5.65 to 0.14 kg]; P = 0.040). Limited generalizability. Compared with DCR, 4:3 IMF resulted in modestly greater weight loss among adults with overweight or obesity enrolled in a 12-month, high-intensity, comprehensive behavioral weight loss program. National Institute of Diabetes and Digestive and Kidney Diseases.