Molecular Transducers of Physical Activity Consortium (MoTrPAC): Human Studies Design and Protocol.

Physical activity, including structured exercise, is associated with favorable health-related chronic disease outcomes. While there is evidence of various molecular pathways that affect these responses, a comprehensive molecular map of these molecular responses to exercise has not been developed. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) is a multi-center study designed to isolate the effects of structured exercise training on the molecular mechanisms underlying the health benefits of exercise and physical activity. MoTrPAC contains both a pre-clinical and human component. The details of the human studies component of MoTrPAC that include the design and methods are presented here. The human studies contain both an adult and pediatric component. In the adult component, sedentary participants are randomized to 12 weeks of Control, Endurance Exercise Training, or Resistance Exercise Training with outcomes measures completed before and following the 12 weeks. The adult component also includes recruitment of highly active endurance trained or resistance trained participants who only complete measures once. A similar design is used for the pediatric component; however, only endurance exercise is examined. Phenotyping measures include weight, body composition, vital signs, cardiorespiratory fitness, muscular strength, physical activity and diet, and other questionnaires. Participants also complete an acute rest period (adults only) or exercise session (adults, pediatrics) with collection of biospecimens (blood only for pediatrics) to allow for examination of the molecular responses. The design and methods of MoTrPAC may inform other studies. Moreover, MoTrPAC will provide a repository of data that can be used broadly across the scientific community.

Effectiveness and safety of drugs for obesity.

Recent publicity around the use of new antiobesity medications (AOMs) has focused the attention of patients and healthcare providers on the role of pharmacotherapy in the treatment of obesity. Newer drug treatments have shown greater efficacy and safety compared with older drug treatments, yet access to these drug treatments is limited by providers' discomfort in prescribing, bias, and stigma around obesity, as well as by the lack of insurance coverage. Now more than ever, healthcare providers must be able to discuss the risks and benefits of the full range of antiobesity medications available to patients, and to incorporate both guideline based advice and emerging real world clinical evidence into daily clinical practice. The tremendous variability in response to antiobesity medications means that clinicians need to use a flexible approach that takes advantage of specific features of the antiobesity medication selected to provide the best option for individual patients. Future research is needed on how best to use available drug treatments in real world practice settings, the potential role of combination therapies, and the cost effectiveness of antiobesity medications. Several new drug treatments are being evaluated in ongoing clinical trials, suggesting that the future for pharmacotherapy of obesity is bright.

The Microbiome, Epigenome, and Diet in Adults with Obesity during Behavioral Weight Loss.

Obesity has been linked to the gut microbiome, epigenome, and diet, yet these factors have not been studied together during obesity treatment. Our objective was to evaluate associations among gut microbiota (MB), DNA methylation (DNAme), and diet prior to and during a behavioral weight loss intervention. Adults (n = 47, age 40.9 ± 9.7 years, body mass index (BMI) 33.5 ± 4.5 kg/m2, 77% female) with data collected at baseline (BL) and 3 months (3 m) were included. Fecal MB was assessed via 16S sequencing and whole blood DNAme via the Infinium EPIC array. Food group and nutrient intakes and Healthy Eating Index (HEI) scores were calculated from 7-day diet records. Linear models were used to test for the effect of taxa relative abundance on DNAme and diet cross-sectionally at each time point, adjusting for confounders and a false discovery rate of 5%. Mean weight loss was 6.2 ± 3.9% at 3 m. At BL, one MB taxon, Ruminiclostridium, was associated with DNAme of the genes COL20A1 (r = 0.651, p = 0.029), COL18A1 (r = 0.578, p = 0.044), and NT5E (r = 0.365, p = 0.043). At 3 m, there were 14 unique MB:DNAme associations, such as Akkermansia with DNAme of GUSB (r = -0.585, p = 0.003), CRYL1 (r = -0.419, p = 0.007), C9 (r = -0.439, p = 0.019), and GMDS (r = -0.559, p = 0.046). Among taxa associated with DNAme, no significant relationships were seen with dietary intakes of relevant nutrients, food groups, or HEI scores. Our findings indicate that microbes linked to mucin degradation, short-chain fatty acid production, and body weight are associated with DNAme of phenotypically relevant genes. These relationships offer an initial understanding of the possible routes by which alterations in gut MB may influence metabolism during weight loss.

The role of physical activity in the regulation of body weight: The overlooked contribution of light physical activity and sedentary behaviors.

The role of physical activity (PA) in the regulation of body weight is still a major topic of debate. This may be because studies have essentially focused on the effects of moderate/vigorous PA (MVPA) on body weight while overlooking the other components of PA, namely, light-intensity PA (LPA, daily life activities) and sedentary behaviors (SB, too much sitting). In this review, we will (i) describe the history of changes in PA behaviors that occurred with modernization; (ii) review data from cross-sectional and longitudinal studies that examined the associations between PA, SB, and measures of obesity; (iii) review interventional studies that investigated the effects of changes in PA and SB on body weight and adiposity; and (iv) discuss experimental studies that addressed potential biological mechanisms underlying the effects of PA and SB on weight regulation. Overall recent findings support the importance of considering all components of PA to better understand the regulation of energy balance and suggest an important role for LPA and SB in addition to MVPA on body weight regulation. Longitudinal large-scale rigorous studies are needed to advance our knowledge of the role of PA/SB in combating the obesity epidemic.

Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight-loss intervention: A pilot study.

OBJECTIVE: 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. METHODS: This secondary data analysis included participants (n = 20, mean [SD], age: 40.1 [9.5] years, BMI: 34.2 [4.0] kg/m2 ) who completed a 1-year behavioral weight-loss intervention. Cardiovascular disease-related plasma proteins, diet, and cardiometabolic health indicators were evaluated at baseline and 3 months. Associations were determined via linear regression and integrated networks created using Visualization Of LineAr Regression Elements (VOLARE). RESULTS: A 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). CONCLUSIONS: Circulating cardiovascular disease-related proteins were associated with diet and cardiometabolic health indicators prior to and in response to weight loss.

Comparison of weight loss induced by daily caloric restriction versus intermittent fasting (DRIFT) in individuals with obesity: study protocol for a 52-week randomized clinical trial.

BACKGROUND: The standard of care for treating overweight and obesity is daily caloric restriction (DCR). While this approach produces modest weight loss, adherence to DCR declines over time and weight regain is common. Intermittent fasting (IMF) is an alternative dietary strategy for reducing energy intake (EI) that involves >60% energy restriction on 2-3 days per week, or on alternate days, with habitual intake on fed days. While numerous studies have evaluated IMF as a weight loss strategy, there are several limitations including lack of a standard-of-care DCR control, failure to provide guideline-based behavioral support, and failure to rigorously evaluate dietary and PA adherence using objective measures. To date, only three longer-term (52-week) trials have evaluated IMF as a weight loss strategy. None of these longer-duration studies reported significant differences between IMF and DCR in changes in weight. However, each of these studies has limitations that prohibit drawing generalizable conclusions about the relative long-term efficacy of IMF vs. DCR for obesity treatment. METHODS: The Daily Caloric Restriction vs. Intermittent Fasting Trial (DRIFT) is a two-arm, 52-week block randomized (1:1) clinical weight loss trial. The two intervention arms (DCR and IMF) are designed to prescribe an equivalent average weekly energy deficit from baseline weight maintenance energy requirements. Both DCR and IMF will be provided guideline-based behavioral support and a PA prescription. The primary outcome is change in body weight at 52 weeks. Secondary outcomes include changes in body composition (dual-energy x-ray absorptiometry (DXA)), metabolic parameters, total daily energy expenditure (TDEE, doubly labeled water (DLW)), EI (DLW intake-balance method, 7-day diet diaries), and patterns of physical activity (PA, activPAL device). DISCUSSION: Although DCR leads to modest weight loss success in the short-term, there is wide inter-individual variability in weight loss and poor long-term weight loss maintenance. Evidence-based dietary approaches to energy restriction that are effective long-term are needed to provide a range of evidence-based options to individuals seeking weight loss. The DRIFT study will evaluate the long-term effectiveness of IMF vs. DCR on changes in objectively measured weight, EI, and PA, when these approaches are delivered using guideline-based behavioral support and PA prescriptions.

Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention.

BACKGROUND/OBJECTIVES: 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. METHODS: Adults (n = 156) with overweight and obesity (40 ± 9 years, 84% female, BMI: 34.4 ± 4.2 kg/m2) participated in an 18-month behavioral weight loss intervention which prescribed a reduced calorie diet (1200-1800 kcal/d) and increased physical activity (300 min/wk). Body weight, indices of sleep (SenseWear armband; SWA), energy intake (EI, 3-day food records), and moderate-to-vigorous physical activity (SWA) were measured at baseline, 6, 12, and 18 months. Linear mixed effects models examined the association between sleep and weight change over time. Additional models were adjusted for covariates including age, BMI, sex, race, ethnicity, study completion, randomization, EI, and physical activity. Secondary analyses examined the association between sleep and adherence to diet and physical activity recommendations. RESULTS: Mean 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). CONCLUSIONS: 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. CLINICAL TRIALS IDENTIFIER: NCT01985568.

Short-Term Adaptations in Skeletal Muscle Mitochondrial Oxidative Capacity and Metabolic Pathways to Breaking up Sedentary Behaviors in Overweight or Obese Adults.

Breaking up sedentary behavior with short-frequent bouts of physical activity (PA) differentially influences metabolic health compared with the performance of a single-continuous bout of PA matched for total active time. However, the underlying mechanisms are unknown. We compared skeletal muscle mitochondrial respiration (high-resolution respirometry) and molecular adaptations (RNA sequencing) following 4-day exposure to breaks vs. energy-matched single-continuous PA bout in inactive adults with overweight/obesity. Participants (9M/10F, 32.2 ± 6.4 years, 30.3 ± 3.0 kg/m2) completed three 4-day interventions of a randomized cross-over study: SED, sedentary control; MICRO, 5 min brisk walking each hour for 9 h; ONE: 45 min/d continuous brisk walking bout. Fasted muscle biopsies were collected on day 5. Mitochondrial coupling in the presence of lipid-associated substrates was higher after ONE (4.8 ± 2.5) compared to MICRO (3.1 ± 1.1, p = 0.02) and SED (2.3 ± 1.0, p = 0.001). Respiratory rates did not differ across groups with carbohydrate-associated substrates. In pathways associated with muscle contraction transcription signaling, ONE and MICRO similarly enhanced Oxidative Phosphorylation and Sirtuin Signaling expression (p < 0.0001, for both). However, ONE (p < 0.001, for all), but not MICRO, had greater pathway enrichment, including Ca++, mTOR, AMPK, and HIF1α signaling, than SED. Although breaking up sedentary behavior triggered skeletal muscle molecular adaptations favoring oxidative capacity, it did not improve mitochondrial function over the short term.

Effect of Morning and Evening Exercise on Energy Balance: A Pilot Study.

The purpose of this study was to evaluate the feasibility and acceptability of randomizing adults with overweight and obesity (BMI 25-40 kg/m2) to morning (06:00-10:00) or evening (15:00-19:00) aerobic exercise. Participants completed four exercise sessions per week in the morning (AM, n = 18) or evening (PM, n = 15). The exercise program was 15 weeks and progressed from 70 to 80% heart rate maximum and 750-2000 kcal/week. Bodyweight, body composition, total daily energy expenditure (TDEE), energy intake (EI), sleep, sedentary behavior (SB), non-exercise physical activity (NEPA), and maximal aerobic capacity were assessed at baseline and week 15. Study retention was 94% and adherence to the supervised exercise program was ≥90% in both groups. Weight change was -0.9 ± 2.8 kg and -1.4 ± 2.3 kg in AM and PM, respectively. AM and PM increased TDEE (AM: 222 ± 399 kcal/day, PM: 90 ± 150 kcal/day). EI increased in AM (99 ± 198 kcal/day) and decreased in PM (-21 ± 156 kcal/day) across the intervention. It is feasible to randomize adults with overweight and obesity to morning or evening aerobic exercise with high levels of adherence. Future trials are needed to understand how the timing of exercise affects energy balance and body weight regulation.

Physiology of physical inactivity, sedentary behaviours and non-exercise activity: insights from the space bedrest model.

Physical inactivity, i.e. not reaching the recommended level of physical activity (PA), and sedentary behaviours (SB), i.e. sitting time, have been associated with increased risk for common metabolic diseases. Recent epidemiological data suggest that high volumes of SB are detrimental to metabolic health, even in the presence of regular exercise, i.e. moderate/vigorous PA. This suggests that the health effects of SB are independent from those of exercise. However, experimentally testing this hypothesis is complicated because of the difficulty in disassociating SB from PA. Bedrest studies, a traditional space science model, can offer new insights. In some bedrest studies, an exercise training protocol has been used to counteract the harmful effects of inactivity. While bedrest induces an inactive and sedentary state, exercise with bedrest represents a unique model of sedentary yet physically active people. Here, we review bedrest studies with and without exercise training. Although exercise training prevents the loss of muscle mass and function, even large volumes of exercise are not sufficient to fully counteract the negative metabolic adaptations triggered by inactivity. This observation supports the existence of independent adverse health effects of SB, but also the potential benefits of non-exercise activity, i.e. daily living light PA. We gathered available data to examine the complex relationships between exercise, non-exercise activity, SB and health outcomes. Given the large amount of SB in modern societies, the sole promotion of exercise, i.e. moderate/vigorous PA may be insufficient, and promotion of light PA may be a complimentary approach to improve health.

Predictors of long-term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis.

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 < 0.01). Maintainers demonstrated greater increases in device-measured physical activity, autonomous motivation for exercise, diet self-efficacy, cognitive restraint, and engagement in weight management behaviors and greater reductions in barriers for exercise, disinhibition, and depressive symptoms over 24 months versus regainers (p < 0.05). CONCLUSION: Maintainers and regainers appear to be distinct trajectories that are associated with specific sociodemographic, behavioral, and psychosocial factors. Study results suggest potential targets for more tailored, multifaceted interventions to improve obesity treatment outcomes.

The Gut Microbiota during a Behavioral Weight Loss Intervention.

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.

Weight and body composition changes affect resting energy expenditure predictive equations during a 12-month weight-loss intervention.

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.

A Randomized Controlled Trial of Ovarian Suppression in Premenopausal Women: No Change in Free-Living Energy Expenditure.

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.

Circadian Rhythm of Substrate Oxidation and Hormonal Regulators of Energy Balance.

OBJECTIVE: The circadian system provides an organism with the ability to anticipate daily food availability and appropriately coordinate metabolic responses. Few studies have simultaneously assessed factors involved in both the anticipation of energy availability (i.e., hormones involved in appetite regulation) and subsequent metabolic responses (such as energy expenditure and substrate oxidation) under conditions designed to reveal circadian rhythmicity. METHODS: Eight healthy adults (four females; age: 28.0 ± 2.3 years; BMI: 24.3 ± 2.9 kg/m2 ) participated in a 26-hour constant routine protocol involving continuous wakefulness with constant posture, temperature, dim light, and hourly isocaloric snacks. Indirect calorimetry was performed every 3 hours for measurement of energy expenditure and substrate oxidation. Subjective hunger was obtained hourly using questionnaires. Saliva and plasma were obtained hourly to assess melatonin (circadian phase marker) and hormones (leptin, ghrelin, and peptide YY). RESULTS: Fat and carbohydrate oxidation was highest in the biological evening and morning, respectively. Subjective hunger ratings peaked during the middle of the biological day. Significant circadian rhythms were identified for ghrelin and peptide YY with peaks in the biological evening and morning, respectively. CONCLUSIONS: These findings support a role for the circadian system in the modulation of nutrient oxidation, subjective measures of appetite, and appetitive hormones.

Sex Differences in Adipose Tissue Function.

Regional adipose tissue distribution differs between men and women. Differences in the accumulation of adipose tissue as well as the regulation of secretion of a number of products from adipose tissue are under the control of sex steroids, which act through a wide variety of mechanisms, both direct and indirect, to tailor metabolism to the unique needs of each sex. A fuller understanding of sex-based differences in adipose tissue function may help with tailored strategies for disease prevention and treatment and provide insights into fundamental differences in the processes that regulate nutrient homeostasis and body weight.

Impact of Combined Hormonal Contraceptive Use on Weight Loss: A Secondary Analysis of a Behavioral Weight-Loss Trial.

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.

Appetite-Related Responses to Overfeeding and Longitudinal Weight Change in Obesity-Prone and Obesity-Resistant Adults.

OBJECTIVE: Appetite responses to 3 days of overfeeding (OF) were examined as correlates of longitudinal weight change in adults classified as obesity prone (OP) or obesity resistant (OR). METHODS: OP (n = 22) and OR (n = 30) adults consumed a controlled eucaloric and OF diet (140% of energy needs) for 3 days, followed by 3 days of ad libitum feeding. Hunger and satiety were evaluated by visual analog scales. Ghrelin and peptide YY (PYY) levels were measured during a 24-hour inpatient visit on day 3. Body weight and composition were measured annually for 4.0 ± 1.3 years. RESULTS: Dietary restraint and disinhibition were greater in OP than OR (mean difference: 3.5 ± 1.2 and 3.3 ± 0.9, respectively; P < 0.01) participants, and disinhibition was associated with longitudinal weight change (n = 48; r = 0.35; P = 0.02). Compared with the eucaloric diet, energy intake fell significantly in OR participants following OF (P = 0.03) but not in OP (P = 0.33) participants. Twenty-four-hour PYY area under the curve values increased with OF in OR (P = 0.02) but not in OP (P = 0.17) participants. Furthermore, changes in PYY levels with OF correlated with measured energy intake (r = -0.36; P = 0.01). CONCLUSIONS: Baseline disinhibition and PYY responses to OF differed between OP and OR adults. Dietary disinhibition was associated with 5-year longitudinal weight gain. Differences in appetite regulation may underlie differences in propensity for weight gain.

Antiobesity Medication Use in 2.2 Million Adults Across Eight Large Health Care Organizations: 2009-2015.

OBJECTIVE: The aim of this study was to examine the prescribing patterns and use of antiobesity medications in a large cohort of patients using data from electronic health records. METHODS: Pharmacy- and patient-level electronic health record data were obtained on 2,248,407 adults eligible for weight-loss medications from eight geographically dispersed health care organizations. RESULTS: A total of 29,964 patients (1.3% of total cohort) filled at least one weight-loss medication prescription. This cohort was 82.3% female, with median age 44.9 years and median BMI 37.2 kg/m2 . Phentermine accounted for 76.6% of all prescriptions, with 51.7% of prescriptions being filled for ≥ 120 days and 33.8% filled for ≥ 360 days. There was an increase of 32.9% in medication days for all medications in 2015 compared with 2009. Higher prescription rates were observed in women, black patients, and patients in higher BMI classes. Of 3,919 providers who wrote at least one filled prescription, 23.8% (n = 863) were "frequent prescribers" who wrote 89.6% of all filled prescriptions. CONCLUSIONS: Weight-loss medications are rarely prescribed to eligible patients. Phentermine accounted for > 75% of all medication days, with a majority of patients filling it for more than 4 months. Less than one-quarter of prescribing providers accounted for approximately 90% of all prescriptions.

The Impact of Timing of Exercise Initiation on Weight Loss: An 18-Month Randomized Clinical Trial.

OBJECTIVE: This study aimed to evaluate the impact of timing of exercise initiation on weight loss within a behavioral weight loss program. METHODS: Adults with overweight or obesity (N = 170; age 18-55 years; BMI 25-42 kg/m2 ; 83.5% women) were enrolled in an 18-month behavioral weight loss program consisting of a reduced-calorie diet, exercise, and group-based support. The standard group (STD) received a supervised exercise program (progressing to 300 min/wk of moderate-intensity aerobic exercise) during months 0 to 6. The sequential group (SEQ) was asked to refrain from changing exercise during months 0 to 6 and received the supervised exercise program during months 7 to 12. On completion of supervised exercise, both groups were instructed to continue 300 min/wk of moderate-intensity exercise for the study duration. RESULTS: At 6 months, the STD group exhibited greater reductions in body weight (-8.7 ± 0.7 kg) compared with the SEQ group (-6.9 ± 0.6 kg; P = 0.047). Between 6 and 18 months, the STD group regained more weight (2.5 ± 0.8 kg vs. 0.0 ± 0.8 kg; P = 0.02). At 18 months, there were no between-group differences in changes in weight (STD: -6.9 ± 1.2 kg; SEQ: -7.9 ± 1.2 kg), fat mass, lean mass, physical activity, or attrition. CONCLUSIONS: Both immediate and delayed exercise initiation within a behavioral weight loss program resulted in clinically meaningful weight loss at 18 months. Thus, timing of exercise initiation can be personalized based on patient preference.