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Dietary restriction (DIET) and aerobic exercise (AEX) interventions may impact energy balance differently. Our aim was to describe the effects of weight loss interventions via DIET or AEX on measures of energy balance.Adults with overweight or obesity were randomized to 12 weeks of DIET or AEX with similar calorie deficit goals. A study day was conducted before and after the intervention to assess subjective and hormonal (ghrelin, peptide-YY, glucagon-like peptide-1) appetite responses to a control meal,Forty-four individuals were included (age: 37 ± 9 years, body mass index: 30.6 ± 3.1 kg/mAEX did not result in compensatory alterations in appetite

Background: To compare the acute and chronic effects of frequent, short physical activity (PA) bouts spread throughout the day to a time-matched intervention consisting in a single continuous daily bout of PA on glucose control and potential underlying mechanisms in adults at risk of developing type 2 diabetes (T2D). Methods: BURST2D is a single-center, parallel-group, randomized controlled trial, in which sedentary adults with overweight/obesity and pre-diabetes (18-45 y, BMI: 25-40 kg/m2, fasting glucose: 100-125 mg/dL or 2h glucose: 140-199 mg/dL or HbA1c: 5.7-6.4%) will be randomly assigned to one of two 3-month PA interventions: BREAK, nine bouts of 5-min brisk walking performed every hour for nine consecutive hours (45-min/d total), 5 days/wk; ONE, one continuous 45-min bout of brisk walking, 5 days/wk. Primary outcomes will be daily glycemic mean and variability, fasting glucose and HbA1c, postprandial plasma glucose and insulin, glucose kinetics, and content of skeletal muscle proteins related to insulin signaling and glucose uptake. Secondary outcomes will be whole-body insulin sensitivity, 24-h total substrate oxidation, postprandial triglycerides, daily PA and sedentary behavior (SB) patterns, knowledge and attitude towards PA and SB, barriers and facilitators to intervention compliance, self-perceived appetite, mood, and sleep. Outcomes will be assessed at baseline and after one month and/or three months of intervention. Conclusions: This study will establish the acute and chronic effects of breaking up SB, independent of increases in PA, on glucose control and underlying mechanisms in adults with pre-diabetes. Results will advance the science of T2D prevention. Trial registration: This study is registered with the ClinicalTrials.gov, registry number NTC05041491.

BACKGROUND It remains unclear how inpatient physical activity after major abdominal surgery affects outcomes. Accelerometer research may provide further evidence for postoperative mobilization. OBJECTIVE We aimed to summarize the current literature evaluating the impact of accelerometer-measured postoperative physical activity on outcomes after major abdominal surgery. METHODS We searched PubMed and Google Scholar in October 2021 to conduct a systematic review. Studies were included if they used accelerometers to measure inpatient physical behaviors immediately after major abdominal surgery, defined as any nonobstetric procedures performed under general anesthesia requiring hospital admission. Studies were eligible only if they evaluated the effects of physical activity on postoperative outcomes such as postoperative complications, return of gastrointestinal function, hospital length of stay, discharge destination, and readmissions. We excluded studies involving participants aged RESULTS We identified 15 studies. Risk of bias was high in 14 (93%) of the 15 studies. Most of the studies (11/15, 73%) had sample sizes of CONCLUSIONS Although observational studies show strong associations between postoperative physical activity and outcomes after major abdominal surgery, RCTs have not proved the benefit of mobility-enhancing interventions compared with usual care. The overall risk of bias was high, and we could not synthesize specific recommendations for postoperative mobilization. Future research would benefit from improving study design, increasing methodologic rigor, and measuring physical behaviors beyond step counts to understand the impact of postoperative mobilization on outcomes after major abdominal surgery.

OBJECTIVE Mathematical equations that predict resting energy expenditure (REE) are widely used to derive calorie prescriptions during weight-loss interventions. Although such equations are known to introduce group- and individual-level error into REE prediction, their validity has largely been assessed in weight-stable populations. Therefore, this study sought to characterize how weight change affects the validity of commonly used REE predictive models throughout a 12-month weight-loss intervention. METHODS Changes in predictive error of four models (Mifflin-St-Jeor, Harris-Benedict, Owen, and World Health Organization/Food and Agriculture) were assessed at 1-, 6-, and 12-month time points in adults (n = 66, 76% female, aged 18-55 years, BMI = 27-45 kg/m2 ) enrolled in a randomized clinical weight-loss trial. RESULTS All equations experienced significant negative shifts in bias (measured - predicted REE) toward overprediction from baseline to 1 month (p < 0.05). Three equations showed reversal of bias in the positive direction (toward underprediction) from baseline to 12 months (p < 0.05). Early changes in bias were correlated with decreased fat-free mass (p ≤ 0.01). CONCLUSIONS Changes in body composition and mass during a 12-month weight-loss intervention significantly affected REE predictive error in adults with overweight and obesity. Weight history should be considered when using mathematical models to predict REE during periods of weight fluctuation.

Measuring individual circadian phase is important to diagnose and treat circadian rhythm sleep-wake disorders and circadian misalignment, inform chronotherapy, and advance circadian science. Initial findings using blood transcriptomics to predict the circadian phase marker dim-light melatonin onset (DLMO) show promise. Alternatively, there are limited attempts using metabolomics to predict DLMO and no known omics-based biomarkers predict dim-light melatonin offset (DLMOff). We analyzed the human plasma metabolome during adequate and insufficient sleep to predict DLMO and DLMOff using one blood sample. Sixteen (8 male/8 female) healthy participants aged 22.4 ± 4.8 years (mean ± SD) completed an in-laboratory study with 3 baseline days (9 h sleep opportunity/night), followed by a randomized cross-over protocol with 9-h adequate sleep and 5-h insufficient sleep conditions, each lasting 5 days. Blood was collected hourly during the final 24 h of each condition to independently determine DLMO and DLMOff. Blood samples collected every 4 h were analyzed by untargeted metabolomics and were randomly split into training (68%) and test (32%) sets for biomarker analyses. DLMO and DLMOff biomarker models were developed using partial least squares regression in the training set followed by performance assessments using the test set. At baseline, the DLMOff model showed the highest performance (0.91 R2 and 1.1 ± 1.1 h median absolute error ± interquartile range [MdAE ± IQR]), with significantly ( p < 0.01) lower prediction error versus the DLMO model. When all conditions (baseline, 9 h, and 5 h) were included in performance analyses, the DLMO (0.60 R2; 2.2 ± 2.8 h MdAE; 44% of the samples with an error under 2 h) and DLMOff (0.62 R2; 1.8 ± 2.6 h MdAE; 51% of the samples with an error under 2 h) models were not statistically different. These findings show promise for metabolomics-based biomarkers of circadian phase and highlight the need to test biomarkers that predict multiple circadian phase markers under different physiological conditions.

Identifying associations among circulating proteins, dietary intakes, and clinically relevant indicators of cardiometabolic health during weight loss may elucidate biologically relevant pathways affected by diet, allowing for an incorporation of precision nutrition approaches when designing future interventions. This study hypothesized that plasma proteins would be associated with diet and cardiometabolic health indicators within a behavioral weight-loss intervention.This secondary data analysis included participants (n = 20, mean [SD], age: 40.1 [9.5] years, BMI: 34.2 [4.0] kg/mA total of 16 plasma proteins were associated with ≥1 diet or health indicator at baseline (p 0.001); changes in 42 proteins were associated with changes in diet or health indicators from baseline to 3 months (p 0.005). Baseline tumor necrosis factor receptor superfamily member 10C (TNFRSF10C) was associated with intakes of dark green vegetables (r = -0.712), and fatty acid-binding protein 4 (FABP4) was associated with intakes of unsweetened coffee (r = -0.689). Changes in refined-grain intakes were associated with changes in scavenger receptor cysteine-rich type 1 protein M130 (CD163; r = 0.725), interleukin-1 receptor type 1 (IL1R-T1; r = 0.624), insulin (r = 0.656), and triglycerides (r = 0.648).Circulating cardiovascular disease-related proteins were associated with diet and cardiometabolic health indicators prior to and in response to weight loss.

PURPOSE This study aimed to determine if energy intake and appetite regulation differ in response to an acute bout of resistance exercise (REx) versus aerobic exercise (AEx). METHODS Physically inactive adults (n = 24, 35% ± 2% body fat, 50% female) completed three conditions: AEx (walking at 65%-70% heart rate max for 45 min), REx (1 set to failure of 12 exercises), and sedentary control (SED). Each condition was initiated in the postprandial state (35 min after breakfast). Appetite (visual analog scale for hunger, satiety, and prospective food consumption) and hormones (ghrelin, peptide YY (PYY), and glucagon-like peptide-1 (GLP-1)) were measured before and 30, 90, 120, 150, and 180 min after a standardized breakfast. Area under the curve was calculated using the trapezoid method. Ad libitum energy intake was evaluated at a lunch meal after the 180-min measurements. RESULTS No differences in ad libitum energy intake (REx, 991 ± 68; AEx, 937 ± 65; SED, 944 ± 76 kcal; P = 0.50) or appetite ratings (all, P > 0.05) were detected. The area under the curve for ghrelin, PYY, and GLP-1 were all lower after REx versus AEx (ghrelin: 130,737 ± 4928 for REx; 143,708 ± 7500 for AEx (P = 0.006); PYY: 20,540 ± 1177 for REx, 23,812 ± 1592 for AEx (P = 0.001); and GLP-1: 1314 ± 93 for REx, 1615 ± 110 for AEx (P = 0.013)). Neither exercise condition significantly differed from SED. CONCLUSIONS Acute REx lowers both orexigenic (ghrelin) and anorectic (PYY and GLP-1) gut peptides compared with acute AEx. Ad libitum energy intake did not increase compared with SED in either exercise condition, indicating both exercise modalities have appetite and energy intake suppressing effects. Future work is needed to determine if exercise of differing modalities influences chronic appetite regulation.

OBJECTIVE Identifying predictors of weight loss and clinical outcomes may increase understanding of individual variability in weight loss response. We hypothesized that baseline multiomic features, including DNA methylation (DNAme), metabolomics, and gut microbiome, would be predictive of short-term changes in body weight and other clinical outcomes within a comprehensive weight loss intervention. METHODS Healthy adults with overweight or obesity (n = 62, age 18-55 years, BMI 27-45 kg/m2 , 75.8% female) participated in a 1-year behavioral weight loss intervention. To identify baseline omic predictors of changes in clinical outcomes at 3 and 6 months, whole-blood DNAme, plasma metabolites, and gut microbial genera were analyzed. RESULTS A network of multiomic relationships informed predictive models for 10 clinical outcomes (body weight, waist circumference, fat mass, hemoglobin A1c , homeostatic model assessment of insulin resistance, total cholesterol, triglycerides, C-reactive protein, leptin, and ghrelin) that changed significantly (P

Appetite is a determinant of dietary intake and is impacted by sex hormones, exercise, and body composition among individuals without chronic conditions. Whether appetite is altered by exercise in the context of estrogen suppression and cancer survivorship is unknown. This randomized cross-over study compared appetite and ad libitum energy intake (EI) after acute resistance exercise (REx) versus sedentary (SED) conditions and in relation to body composition and resting metabolic rate (RMR) in breast cancer survivors (BCS). Physically inactive premenopausal females with previous stage I-III estrogen receptor-positive breast cancer completed a single bout of REx or SED 35 min after a standardized breakfast meal. Appetite visual analog scales and hormones (ghrelin and peptide-YY [PYY]) were measured before and 30, 90, 120, 150, and 180 min post-meal and expressed as area under the curve (AUC). EI was assessed from ad libitum EI from a buffet-type meal after 180 min. Body composition (dual X-ray absorptiometry) and RMR (indirect calorimetry) were measured in a separate visit. Sixteen BCS were included (age: 46 ± 2 y, BMI: 24.9 ± 1.0 kg/m

Objective The purpose of this study was to determine whether suppression of ovarian function (gonadotropin-releasing hormone agonist [GnRHAG ]) for 24 weeks in premenopausal women approaching menopause causes changes in body composition and a decline in free-living physical activity energy expenditure (PAEE) and whether endurance exercise training attenuates the changes. Methods Premenopausal women who were approaching menopause (mean [SD]: age 46 [3] years, BMI 26.3 [4.8] kg/m2 ) were randomized to 24 weeks of GnRHAG (n = 14), GnRHAG + Exercise (n = 11), or placebo (n = 9). Endurance exercise was performed 4 days per week with the goal of expending 200 to 300 kcal per session. Primary outcome measurements included body composition by dual-energy x-ray absorptiometry, total daily energy expenditure (TDEE), and PAEE by doubly labeled water, and resting energy expenditure (REE) by indirect calorimetry. Results Changes in TDEE, PAEE, REE, or body composition were not different between groups. However, within the GnRHAG group, fat mass increased (mean [SE]: total 1.7 [0.4] kg, trunk 0.9 [0.2] kg, leg 0.6 [0.2] kg) and fat-free leg mass decreased (mean [SE]: -0.4 [0.2] kg) significantly. Conclusions In premenopausal women approaching menopause, ovarian hormone suppression resulted in increased adiposity without alterations in TDEE, PAEE, or REE.

Objective This study aimed to perform a preliminary investigation of the impact of combined hormonal contraceptive (CHC) use on weight loss during an 18-month behavioral weight-loss trial. Methods Adults (n = 170; 18-55 years; BMI 27-42 kg/m2 ) received a weight-loss intervention that included a reduced-calorie diet, a progressive exercise prescription, and group-based behavioral support. Premenopausal women (n = 110) were classified as CHC users (CHC, n = 17) or non-CHC users (non-CHC, n = 93). Changes in weight were examined within groups using a linear mixed model, adjusted for age and randomized group assignment. Results At 6 M, weight was reduced from baseline in both CHC (mean, -6.7 kg; 95% CI: -9.8 to -3.7 kg) and non-CHC (-9.1 kg; -9.1 to -6.4 kg). Between 6 and 18 M, CHC regained weight (4.9 kg; 0.9 to 8.9 kg), while weight remained relatively unchanged in non-CHC (-0.1 kg; -1.8 to 1.6 kg). At 18 M, weight was relatively unchanged from baseline in CHC (-1.8 kg; -7.3 to 3.6 kg) and was reduced from baseline in non-CHC (-7.9 kg; -10.2 to -5.5 kg). Conclusions In this secondary data analysis, CHC use was associated with weight regain after initial weight loss. Prospective studies are needed to further understand the extent to which CHC use influences weight loss and maintenance.

To examine the association between indices of sleep quantity and quality with dietary adherence, physical activity adherence, and weight loss during a behavioral weight loss intervention.Adults (n = 156) with overweight and obesity (40 ± 9 years, 84% female, BMI: 34.4 ± 4.2 kg/mMean weight loss was 7.7 ± 5.4, 8.4 ± 7.9, and 7.1 ± 9.0 kg at 6, 12, and 18 months, respectively. Lower sleep efficiency, higher wake after sleep onset (WASO), more awakenings, and higher sleep onset latency (SOL) were significantly associated with attenuated weight loss (p 0.05). Lower sleep efficiency, more awakenings, and higher SOL remained significantly associated with blunted weight loss after adjustment for covariates (p 0.05). Later waketime, longer time in bed, longer sleep duration, higher WASO, more awakenings, and higher SOL were associated with lower odds of achieving ≥300 min/wk of moderate-to-vigorous physical activity, adjusted for covariates (FDR p 0.05).Future studies should evaluate whether incorporating strategies to improve sleep health within a behavioral weight loss intervention leads to improved adherence to diet and physical activity recommendations and enhanced weight loss.NCT01985568.

Background: An urgent need exists for evidence-based dietary guidance early in life, particularly regarding protein intake. However, a significant knowledge gap exists in the effects of protein-rich foods on growth and development during early complementary feeding.Methods: This is a randomized controlled trial of infant growth and gut health (primary outcomes). We directly compare the effects of dietary patterns with common protein-rich foods (meat, dairy, plant) on infant growth trajectories and gut microbiota development (monthly assessments) during early complementary feeding in both breast- and formula-fed infants. Five-month-old infants (up to n = 300) are randomized to a meat-, dairy-, plant-based complementary diet or a reference group (standard of care) from 5 to 12 months of age, with a 24-month follow-up assessment. Infants are matched for sex, mode of delivery and mode of feeding using stratified randomization. Growth assessments include length, weight, head circumference and body composition. Gut microbiota assessments include both 16S rRNA profiling and metagenomics sequencing. The primary analyses will evaluate the longitudinal effects of the different diets on both anthropometric measures and gut microbiota. The secondary analysis will evaluate the potential associations between gut microbiota and infant growth.Discussion: Findings are expected to have significant scientific and health implications for identifying beneficial gut microbial changes and dietary patterns and for informing dietary interventions to prevent the risk of overweight and later obesity, and promote optimal health.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT05012930.

Background Combined estrogen and progestin hormonal contraceptives (CHCs, including combined oral contraceptives, hormonal patches, or vaginal rings) expose women to supraphysiologic levels of reproductive hormones, which in turn suppress endogenous estrogen and progesterone. Sustained elevations of synthetic estrogen/progestin or suppression of endogenous hormones in CHC users may lead to altered dietary intake and/or patterns of physical activity (PA). Previously, we reported that CHC use was associated with higher energy intake (EI) and weight regain over 1 year after weight loss in women with overweight and obesity enrolled in a behavioral weight loss program, suggesting a potential impact of CHCs on energy balance in the weight reduced state. The aim of this secondary data analysis was to compare dietary intake and PA in weight-stable women with overweight or obesity using CHCs to non-CHC users. Methods Pre-menopausal women with overweight or obesity (n=269, age 18-55 years, BMI 27-45kg/m2) enrolled in 3 different interventional weight loss trials were categorized as CHC users (CHC, n=48) or non-CHC controls (CON, n=221). Fat mass (FM) and lean mass (LM) were measured with DXA. Self-reported dietary energy and macronutrient intake was obtained from either 3-day (n=178) or 7-day (n=91) written diet diaries and analyzed using Nutrition Data System for Research (NDSR) software. Healthy eating index (HEI) scores for diet quality were calculated in a subset (CHC=17, CON=84) of participants using variables available in NDSR output files. Additionally, average daily step counts were measured over 1 week in a subset (CHC=27, CON=143) of participants using the activPAL device. Results Age was lower in CHC users (mean±SD; CHC 35.3±9.0 vs. CON 39.4±7.6 years, p Conclusion Daily steps tended to be lower in CHC users compared to controls, while differences in self-reported dietary intake were not observed. Future studies that are done in larger samples over a greater range of BMI and with more detailed measures of PA timed to the menstrual cycle are needed to explore the extent to which CHC use may impact energy balance in women. Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m., Sunday, June 12, 2022 1:06 p.m. - 1:11 p.m.

Every year, 2 million women reach menopause in the United States, and they may spend 40% or more of their life in a postmenopausal state. In the years immediately preceding menopause—known as the menopause transition (or perimenopause)—changes in hormones and body composition increase a woman’s overall cardiometabolic risk. In this narrative review, we summarize the changes in weight, body composition, and body fat distribution, as well as the changes in energy intake, energy expenditure, and other cardiometabolic risk factors (lipid profile, glucose metabolism, sleep health, and vascular function), that occur during the menopause transition. We also discuss the benefits of lifestyle interventions in women in the earlier stages of menopause before these detrimental changes occur. Finally, we discuss how to include perimenopausal women in research studies so that women across the life-span are adequately represented.

The doubly labeled water (DLW) method is the gold standard methodology for determination of free-living, total daily energy expenditure (TEE). However, there is no single accepted approach for either the sampling protocols (daily vs. two-point, in which samples are collected after dosing and at the end of the measurement period) or the calculations used in the determination of the rate of carbon dioxide production (rCO2) and TEE. Moreover, fluctuations in natural background abundances introduce error in the calculation of rCO2 and TEE. The advent of new technologies makes feasible the possibility of including additional isotope measures (17O) to account for background variation, which may improve accuracy. Sixteen subjects were studied for 7 consecutive days in a whole-room indirect calorimeter (IC) with concurrent measurement of TEE by DLW. Daily urine samples were obtained and isotope ratios were determined using off-axis integrated cavity output spectroscopy (OA-ICOS). We determined the best combination of approaches for estimating dilution spaces and elimination rates and calculated average daily volume of carbon dioxide production (VCO2) using six different published equations. Using this best combination, multi-point fitting of isotope elimination rates using the daily urine samples substantially improved the average precision (4.5% vs. 6.0%) and accuracy (−0.5% vs. −3.0%) compared with the two-point method. This improvement may partly reflect the less variable day-to-day chamber measurements of energy expenditure. Utilizing 17O measurements to correct for errors due to background isotope fluctuations provided additional but minor improvements in precision (4.2% vs. 4.5%) and accuracy (0.2% vs. 0.5%). This work shows that optimizing sampling and calculation protocols can improve the accuracy and precision of DLW measurements.

Introduction Exercise can cause a decrease in serum ionized calcium (iCa) concentration, which stimulates parathyroid hormone (PTH) secretion and activates bone resorption. We postulated that dermal Ca loss during cycling exercise is the major determinant of the serum iCa, PTH, and bone resorption (C-terminal telopeptide of type 1 collagen [CTX]) responses. Methods To investigate this, women (n = 13) and men (n = 12) age 18 to 45 yr performed the same exercise bout under cool (18°C) and warm (26°C) conditions. Exercise was 60 min of cycling at ~75% of peak aerobic power. Sweat samples were obtained during exercise using a skin patch method, and blood samples were obtained before and during exercise and during 60 min of recovery. Results Sweat volume and estimated sweat Ca loss were 50% higher for the warm condition than the cool condition. Despite this, there were no differences between thermal conditions in the changes (mean, 95% confidence interval [95% CI]) in iCa (cool, -0.07 mg·dL; 95% CI, -0.16 to 0.03); warm, -0.07 mg·dL; 95% CI, -0.20 to 0.05), PTH (cool, 34.4 pg·mL; 95% CI, 23.6-45.2; warm: 35.8 pg·mL; 95% CI, 22.4-49.1), or CTX (cool, 0.11 ng·mL; 95% CI, 0.08-0.13; warm, 0.15 ng·mL; 95% CI, 0.11-0.18). Adjusting for exercise-related shifts in plasma volume revealed a marked decline in vascular iCa content in the first 15 min of exercise (cool, -0.85 mg·dL; 95% CI, -1.01 to -0.68; warm, -0.85 mg·dL; 95% CI, -1.05 to -0.66), before substantial sweat Ca loss had occurred. Conclusions This indicates that dermal Ca loss was not the primary trigger for the increases in PTH and CTX during exercise. Further research is necessary to understand the causes and consequences of the disruption in Ca homeostasis during exercise and specifically the extravascular shift in iCa.

Many adults cite exercise as a primary strategy for losing weight, yet exercise alone is modestly effective for weight loss and results in variable weight loss responses. It is possible that some of the variability in weight loss may be explained by the time of day that exercise is performed. Few studies have directly compared the effects of exercise performed at different times of the day (i. e., morning versus evening exercise). Results from these existing studies are mixed with some studies demonstrating superior weight and fat mass loss from morning exercise, while other studies have found that evening exercise may be better for weight management. Exercise timing may alter modifiable lifestyle behaviors involved in weight management, such as non-exercise physical activity, energy intake, and sleep. The purpose of this review is to summarize evidence for and against time-of-day dependent effects of exercise on weight management. Although limited, we also review studies that have examined the effect of exercise timing on other lifestyle behaviors linked to body weight regulation. While exercise at any time of day is beneficial for health, understanding whether there is an optimal time of day to exercise may advance personalized treatment paradigms for weight management.

BACKGROUND: Individuals with overweight or obesity commonly underreport energy intake (EI), but it is unknown if the tendency to underreport persists in formerly obese individuals who lose significant weight and maintain their weight loss over long periods of time. OBJECTIVE: Assess the accuracy of self-reported EI in successful weight loss maintainers (WLM) compared with controls of normal body weight (NC) and controls with overweight/obesity (OC). METHODS: Participants for this case-controlled study were recruited in 3 groups: WLM [n = 26, BMI (in kg/m(2)) 24.1 ± 2.3; maintaining ≥13.6 kg weight loss for ≥1 y], NC (n = 33, BMI 22.7 ± 1.9; similar to current BMI of WLM), and OC (n = 32, BMI 34.0 ± 4.6; similar to pre–weight loss BMI of WLM). Total daily energy expenditure (TDEE) was measured over 7 d using the doubly labeled water (DLW) method, and self-reported EI was concurrently measured from 3-d diet diaries. DLW TDEE and self-reported EI were compared to determine accuracy of self-reported EI. RESULTS: WLM underreported EI (median, interquartile range) (–605, –915 to –314 kcal/d) to a greater degree than NC (–308, –471 to –68 kcal/d; P < 0.01) but not more than OC (–310, –970 to 18 kcal/d; P = 0.21). WLM also showed a greater degree of relative underreporting (–25.3%, –32.9% to –12.5%) compared with NC (–14.3%, –19.6% to –3.1%; P = 0.02) but not OC (–11.2%, –34.1% to –0.7%; P = 0.16). A greater proportion of WLM was classified as underreporters (30.8%) than NC (9.1%; P = 0.05) but not OC (28.1%; P = 1.00). CONCLUSIONS: WLM underreported EI in both absolute and relative terms to a greater extent than NC but not OC. These findings call into question the accuracy of self-reported EI in WLM published in previous studies and align with recent data suggesting that WLM rely less on chronic EI restriction and more on high levels of physical activity to maintain weight loss. This trial was registered at clinicaltrials.gov as NCT03422380.

Background Substantial interindividual variability in response to behavioral weight loss interventions remains a critical challenge in obesity treatment. An improved understanding of the complex factors that contribute to this variability may improve obesity treatment outcomes. Objective To identify weight change trajectories during a behavioral weight loss intervention and to explore differences between trajectory groups in sociodemographic, biologic, behavioral, and psychosocial factors. Methods Adults (n = 170, 40 ± 9 years, BMI 34 ± 4 kg/m2, 84% female) participated in an 18‐month behavioral weight loss intervention. Weight was measured at 0, 3, 6, 9, 12, 15, 18, and 24 months. Among participants with at least two weights after baseline (n = 140), clusters of longitudinal trajectories of changes in weight were identified using a latent class growth mixture model. The association between baseline factors or changes in factors over time and trajectory group was examined. Results Two weight change trajectories were identified: “weight regainers” (n = 91) and “weight loss maintainers” (n = 49). Black participants (90%, 19/21) were more likely than non‐Black participants to be regainers versus maintainers (p

Summary The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (, Graphical Abstract, Highlights 5,756 doubly labeled water (DLW) measures highlight variation from calculation equation We derive here new equations for calculating CO2 production when using DLW These equations outperform previous equations in validation studies We recommend these equations should be adopted in future studies using DLW in humans, Speakman et al. use a large database of doubly labeled water measurements to show the choice of equation for the calculation of energy expenditure introduces significant variation into the final estimate. They then derive new equations that outperform previous equations in validation studies against chamber calorimetry.

Purpose of Review This paper presents a review of the current literature in support of a model explaining the relationships between sleep health and risk for type 2 diabetes in adolescents. Recent Findings Short sleep duration is associated with risk of developing obesity in youth. Sleep restriction increases energy expenditure, but also increases hunger, appetite, and food intake, causing positive energy balance, impacting appetite-regulating hormones, and leading to increased eating late at night. Insufficient sleep may lead to reduced physical activity and greater sedentary behaviors. In addition, short sleep duration is associated with reduced insulin sensitivity. The cumulative negative consequences of insufficient sleep increase risk for type 2 diabetes. Applications to clinical care, public policy, and future research are discussed. Summary Insufficient sleep in adolescence increases risk for type 2 diabetes directly through impact on insulin sensitivity and indirectly through increased dietary intake, sedentary activity, and weight gain.

Objective The objectives of this study were to describe sitting, standing, and stepping patterns for people with lower limb amputation (LLA) and to compare sitting, standing, and stepping between people with dysvascular LLA and people with traumatic LLA. Methods Participants with dysvascular or traumatic LLA were included if their most recent LLA was at least 1 year earlier, they were ambulating independently with a prosthesis, and they were between 45 and 88 years old. Sitting, standing, and stepping were measured using accelerometry. Daily sitting, standing, and stepping times were expressed as percentages of waking time. Time spent in bouts of specified durations of sitting (90 minutes), standing (0–1, 1–5, and >5 minutes), and stepping (0–1, 1–5, and >5 minutes) was also calculated. Results Participants (N = 32; mean age = 62.6 [SD = 7.8] years; 84% men; 53% with dysvascular LLA) spent most of the day sitting (median = 77% [quartile 1 {Q1}–quartile 3 {Q3} = 67%–84%]), followed by standing (median = 16% [Q1–Q3 = 12%–27%]) and stepping (median = 6% [Q1–Q3 = 4%–9%]). One-quarter (median = 25% [Q1–Q3 = 16%–38%]) of sitting was accumulated in bouts of >90 minutes, and most standing and stepping was accrued in bouts of Conclusion Participants had high daily volumes of long durations of sitting. Further, these individuals accumulated most physical activity in bouts of Impact High levels of sedentary behavior and physical inactivity patterns may place people with LLA at greater mortality risk relative to the general population. Interventions to minimize sedentary behaviors and increase physical activity are potential strategies for improving poor outcomes of physical therapy after LLA.