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.

Temporal patterns of physical activity in successful weight loss maintainers.

BACKGROUND/OBJECTIVES: Individuals successful at weight loss maintenance engage in high amounts of physical activity (PA). Understanding how and when weight loss maintainers accumulate PA within a day and across the week may inform PA promotion strategies and recommendations for weight management. METHODS: We compared patterns of PA in a cohort of weight loss maintainers (WLM, n = 28, maintaining ≥13.6 kg weight loss for ≥1 year, BMI 23.6 ± 2.3 kg/m2), controls without obesity (NC, n = 30, BMI similar to current BMI of WLM, BMI 22.8 ± 1.9 kg/m2), and controls with overweight/obesity (OC, n = 26, BMI similar to pre-weight loss BMI of WLM, 33.6 ± 5.1 kg/m2). PA was assessed during 7 consecutive days using the activPALTM activity monitor. The following variables were quantified; sleep duration, sedentary time (SED), light-intensity PA (LPA), moderate-to-vigorous intensity PA (MVPA), and steps. Data were examined to determine differences in patterns of PA across the week and across the day using mixed effect models. RESULTS: Across the week, WLM engaged in ≥60 min of MVPA on 73% of days, significantly more than OC (36%, p < 0.001) and similar to NC (59%, p = 0.10). Across the day, WLM accumulated more MVPA in the morning (i.e., within 3 h of waking) compared to both NC and OC (p < 0.01). WLM engaged in significantly more MVPA accumulated in bouts ≥10 min compared to NC and OC (p < 0.05). Specifically, WLM engaged in more MVPA accumulated in bouts of ≥60 min compared to NC and OC (p < 0.05). CONCLUSIONS: WLM engage in high amounts of MVPA (≥60 min/d) on more days of the week, accumulate more MVPA in sustained bouts, and accumulate more MVPA in the morning compared to controls. Future research should investigate if these distinct patterns of PA help to promote weight loss maintenance.

Examining the Role of Exercise Timing in Weight Management: A Review.

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.

The effects of exercise session timing on weight loss and components of energy balance: midwest exercise trial 2.

BACKGROUND/OBJECTIVES: Circadian physiology has been linked to body weight regulation and obesity. To date, few studies have assessed the association between exercise timing and weight related outcomes. The aim of this secondary analysis was to explore the impact of exercise timing (i.e., 24 h clock time of exercise session) on weight loss and components of energy balance. SUBJECTS/METHODS: Overweight/obese (BMI 25.0-39.9 kg/m2), physically inactive, young adults (~51% female) completed a 10-month supervised exercise program (400 or 600 kcal/session for 5 days/week) or served as non-exercise controls (CON). Participants were categorized based on the time of day in which they completed exercise sessions (Early-Ex: >50% of sessions completed between 7:00 and 11:59 am; (n = 21), Late-Ex: >50% of sessions completed between 3:00 and 7:00 pm; (n = 25), Sporadic-Ex: <50% of sessions completed in any time category; (n = 24), and CON; (n = 18)). Body weight, energy intake (EI; digital photography), and non-exercise physical activity (NEPA; accelerometer) were assessed at baseline, 3.5, 7, and 10 months. Total daily energy expenditure (TDEE; doubly labeled water), was assessed at baseline and 10 months. RESULTS: At month 10, weight loss was significantly greater in both Early-EX (-7.2 ± 1.2%; p < 0.001) and Sporadic-EX (- 5.5 ± 1.2%; p = 0.01) vs CON (+0.5 ± 1.0%), and Early-EX vs Late-EX (-2.1 ± 1.0%; p < 0.001). There were no between group differences for change in TDEE, EI, and non-exercise energy expenditure (P > 0.05). A significant group × time interaction (p = 0.02) was observed for NEPA (counts/min), however, after adjusting for multiple comparisons, group effects were no longer significant. CONCLUSIONS: Despite minimal differences in components of energy balance, Early-EX lost significantly more weight compared with Late-Ex. Although the mechanisms are unclear, the timing of exercise may be important for body weight regulation.

Validation of the doubly labeled water method using off-axis integrated cavity output spectroscopy and isotope ratio mass spectrometry.

When the doubly labeled water (DLW) method is used to measure total daily energy expenditure (TDEE), isotope measurements are typically performed using isotope ratio mass spectrometry (IRMS). New technologies, such as off-axis integrated cavity output spectroscopy (OA-ICOS) provide comparable isotopic measurements of standard waters and human urine samples, but the accuracy of carbon dioxide production (V̇co2) determined with OA-ICOS has not been demonstrated. We compared simultaneous measurement V̇co2 obtained using whole-room indirect calorimetry (IC) with DLW-based measurements from IRMS and OA-ICOS. Seventeen subjects (10 female; 22 to 63 yr) were studied for 7 consecutive days in the IC. Subjects consumed a dose of 0.25 g H218O (98% APE) and 0.14 g 2H2O (99.8% APE) per kilogram of total body water, and urine samples were obtained on days 1 and 8 to measure average daily V̇co2 using OA-ICOS and IRMS. V̇co2 was calculated using both the plateau and intercept methods. There were no differences in V̇co2 measured by OA-ICOS or IRMS compared with IC when the plateau method was used. When the intercept method was used, V̇co2 using OA-ICOS did not differ from IC, but V̇co2 measured using IRMS was significantly lower than IC. Accuracy (~1-5%), precision (~8%), intraclass correlation coefficients ( R = 0.87-90), and root mean squared error (30-40 liters/day) of V̇co2 measured by OA-ICOS and IRMS were similar. Both OA-ICOS and IRMS produced measurements of V̇co2 with comparable accuracy and precision compared with IC.

Accumulated physical activity and the association with obesity, fitness, and cardiometabolic risk factors in healthy adults.

OBJECTIVE: This study examined the prevalence of ≥150 min/wk of moderate-to-vigorous physical activity (MVPA) using different criteria for bout length and to examine associations with measures of obesity, cardiorespiratory fitness, and cardiometabolic risk factors in healthy adults with overweight or obesity. METHODS: Baseline data from healthy adults (N = 375; age [mean ± SD] = 45.2 ± 7.7 years; BMI = 32.3 ± 3.8 kg/m2 ) enrolled in a behavioral weight-loss intervention were examined cross-sectionally. Categorization was by objectively measured MVPA as follows: 1) LOW-MVPA: <150 min/wk (n = 122, 32.5%); 2) MVPA-NON-BOUTED: ≥150 min/wk in bouts < 10 min (n = 72, 19.2%); 3) MVPA-COMBINED: ≥150 min/wk with a combination of bouts < 10 and ≥10 min (n = 50, 13.3%); and 4) MVPA-BOUTED: ≥150 min/wk with bouts ≥ 10 min (n = 131, 34.9%). RESULTS: Weight, BMI, and waist circumference were higher in the LOW-MVPA category versus the other categories. Body fatness was significantly lower in the MVPA-BOUTED category compared with the LOW-MVPA category (p < 0.05). Differences by category for cardiorespiratory fitness and cardiometabolic risk factors were limited. CONCLUSIONS: Some adults with overweight or obesity may be more active than they perceived themselves to be, and accumulation of ≥150 min/wk of MVPA may have favorable effects on weight and adiposity status. Findings may influence physical activity recommendations, and confirmation with prospective and randomized studies is needed.

The impact of the covid-19 pandemic on lifestyle behaviors in U.S. college students.

OBJECTIVE: To investigate COVID-19's impact on college student health behaviors. PARTICIPANTS: 189 college students. METHODS: Participants completed an online survey on behaviors relating to sleep, sedentary activities, and physical activity before and during the COVID-19 pandemic. Comparisons utilized Students' dependent t-test or Wilcoxon signed-rank tests. RESULTS: There was an increase in time to fall asleep (before: 23.4 ± 18.0 vs. during: 42.8 ± 44.3 min·day-1, p < 0.001), time spent in bed (before: 7.8 ± 1.5 vs. during: 8.5 ± 1.5 hr·day-1, p < 0.001), as well as shifts in later bed and awake time (p < 0.001). Total sedentary time increased during the pandemic (before: 9.0 ± 3.8 vs. during: 9.9 ± 4.1 hr·day-1, p = 0.016); and time spent using a TV, computer, or phone (before: 3.1 ± 1.9 vs. during: 4.2 ± 2.3 hr·day-1, p < 0.001). There was a significant decrease in moderate-vigorous activity (before: 123.8 ± 96.0 vs. during: 108.9 ± 75.5 min·week-1, p = 0.028) and resistance training days (before: 2.4 ± 2.1 vs. during: 1.7 ± 2.1 days·week-1, p < 0.001). CONCLUSIONS: COVID-19 negatively influenced health behaviors in college students.

Convergent validity of time in bed estimates from activPAL and Actiwatch in free-living youth and adults.

Actiwatch devices are often used to estimate time in bed (TIB), but recently became commercially unavailable. Thigh-worn activPAL devices could be a viable alternative. We tested convergent validity between activPAL (CREA algorithm) and Actiwatch devices. Data were from free-living samples comprising 47 youth (3-16 valid nights/participant) and 42 adults (6-26 valid nights/participant) who wore both devices concurrently. On average, activPAL predicted earlier bedtimes and later risetimes compared to Actiwatch, resulting in longer overnight intervals (by 1.49 hours/night for youth and 0.67 hours/night for adults; both p < 0.001). TIB interruptions were predicted less commonly by activPAL (mean < 2 interruptions/night for both youth and adults) than Actiwatch (mean of 24-26 interruptions/night in both groups; both p < 0.001). Overnight intervals for both devices tended to overlap for lengthy periods (mean of 7.38 hours/night for youth and 7.69 hours/night for adults). Within these overlapping periods, the devices gave matching epoch-level TIB predictions an average of 87.9% of the time for youth and 84.3% of the time for adults. Most remaining epochs (11.8% and 15.1%, respectively) were classified as TIB by activPAL but not Actiwatch. Overall, the devices had fair agreement during the overlapping periods, but limited agreement when predicting interruptions, bedtime, or risetime. Future work should assess the criterion validity of activPAL devices to understand implications for health research. The present findings demonstrate that activPAL is not interchangeable with Actiwatch, which is consistent with their differing foundations (thigh inclination for activPAL versus wrist movement for Actiwatch).

Altered motivation states for physical activity and 'appetite' for movement as compensatory mechanisms limiting the efficacy of exercise training for weight loss.

Weight loss is a major motive for engaging in exercise, despite substantial evidence that exercise training results in compensatory responses that inhibit significant weight loss. According to the Laws of Thermodynamics and the CICO (Calories in, Calories out) model, increased exercise-induced energy expenditure (EE), in the absence of any compensatory increase in energy intake, should result in an energy deficit leading to reductions of body mass. However, the expected negative energy balance is met with both volitional and non-volitional (metabolic and behavioral) compensatory responses. A commonly reported compensatory response to exercise is increased food intake (i.e., Calories in) due to increased hunger, increased desire for certain foods, and/or changes in health beliefs. On the other side of the CICO model, exercise training can instigate compensatory reductions in EE that resist the maintenance of an energy deficit. This may be due to decreases in non-exercise activity thermogenesis (NEAT), increases in sedentary behavior, or alterations in sleep. Related to this EE compensation, the motivational states associated with the desire to be active tend to be overlooked when considering compensatory changes in non-exercise activity. For example, exercise-induced alterations in the wanting of physical activity could be a mechanism promoting compensatory reductions in EE. Thus, one's desires, urges or cravings for movement-also known as "motivation states" or "appetence for activity"-are thought to be proximal instigators of movement. Motivation states for activity may be influenced by genetic, metabolic, and psychological drives for activity (and inactivity), and such states are susceptible to fatigue-or reward-induced responses, which may account for reductions in NEAT in response to exercise training. Further, although the current data are limited, recent investigations have demonstrated that motivation states for physical activity are dampened by exercise and increase after periods of sedentarism. Collectively, this evidence points to additional compensatory mechanisms, associated with motivational states, by which impositions in exercise-induced changes in energy balance may be met with resistance, thus resulting in attenuated weight loss.

Long-term function, body composition and cardiometabolic health in midlife former athletes: a scoping review.

While sports medicine has traditionally focused on recovering from injury and returning athletes to sport safely after injury, there is a growing interest in the long-term health of athletes. The purpose of this scoping review was to (1) summarise the literature (methodologies and findings) on physical function, body composition and cardiometabolic health in midlife (age 40-65 years) former competitive athletes compared with non-athlete controls, (2) identify areas for future study in long-term health in athletes and (3) determine outcomes that could be evaluated in a future systematic review(s). We searched PubMed, CINAHL, Web of Science and SPORTDiscus for studies published between 2000 and 2022 evaluating former athletes and controls on physical function, body composition and/or cardiometabolic measures using MeSH terms. We identified 20 articles that met our criteria. Outcomes varied considerably across studies, most of which were cross-sectional and evaluated only males. Limited data suggest that former endurance athletes have leaner body compositions, higher aerobic capacity and better cardiometabolic indicators than controls; former athletes who maintain higher physical activity (ie, self-reported exercise) are healthier than those who do not; and former team sport athletes, who have higher injury prevalence, may have poorer functional performance than controls who were recreationally active in college. Studies rarely evaluated functional performance, did not control for prior injury or diet and seldom assessed current physical activity levels. Future research should include females and evaluate sex differences, control for prior sports-related injury(ies), quantify physical activity, use standardised outcome measures including performance-based functional assessments and incorporate longitudinal designs.

Physical Activity and Total Daily Energy Expenditure in Older US Adults: Constrained versus Additive Models.

PURPOSE: This study aimed to examine the shape of the relationship between physical activity (PA) and total energy expenditure (TEE) and to explore the role of energy balance status (negative, stable, positive) in influencing this association. METHODS: Cross-sectional. Participants were 584 older adults (50-74 yr) participating in the Interactive Diet and Activity Tracking in AARP study. TEE was assessed by doubly labeled water and PA by accelerometer. The relationship between PA and TEE was assessed visually and using nonlinear methods (restricted cubic splines). Percent weight change (>3%) over a 6-month period was used as a proxy measurement of energy balance status. RESULTS: TEE generally increased with increasing deciles of PA averaging 2354 (SD, 351) kcal·d-1 in the bottom decile to 2693 (SD, 480) kcal·d-1 in the top decile. Cubic spline models showed an approximate linear association between PA and TEE (linear relation, P < 0.0001; curvature, P = 0.920). Results were similar in subgroup analyses for individuals classified as stable or positive energy balance. For those in negative energy balance, TEE was generally flat with increasing deciles of PA averaging 2428 (SD, 285) kcal·d-1 in the bottom decile to 2372 (SD, 560) kcal·d-1 in the top decile. CONCLUSIONS: Energy balance status seems to play an important role in the relationship between PA and TEE. When in a positive energy balance, the relationship between TEE and PA was consistent with an additive model; however, when energy balance was negative, TEE seems to be consistent with a constrained model. These findings support PA for weight gain prevention by increasing TEE; however, the effect of PA on TEE during periods of weight loss may be limited. An adequately powered, prospective study is warranted to confirm these exploratory findings.

Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults.

Objective: To develop an algorithm to quantify indices of sleep quantity and quality using the SenseWear armband (SWA) and to compare indices of sleep from this novel algorithm to standard wrist actigraphy (Actiwatch 2; AW2) under free-living conditions. Material and Methods: Thirty participants (47±10 years; 33.0±4.8kg/m2) wore the SWA and AW2 for seven consecutive days. Participants self-reported bedtime and waketime across these 7 days. Bedtime, sleep onset, sleep offset, waketime, total sleep time (TST), time in bed (TIB), sleep effciency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), sleep fragmentations (SF), sleep regularity (calculated as SD of waketime), and mid-point of sleep were calculated using each device. Results: There was significant evidence for equivalence of means (or mean ranks) for bedtime, sleep onset, sleep offset, waketime, TST, TIB, SOL, WASO, and midpoint of sleep measured by the SWA and AW2 (p<0.05). There was insuffcient evidence for equivalence of means in SF (SW: 25±6 vs. AW2: 10±3 events; p=1.0), mean ranks in sleep regularity (SW: 58±33 vs. AW2: 68±40 min; p=0.11), and mean ranks in SE (SW: 84.7±5.1% vs. AW2: 86.3±5.5%; p=0.05). When comparing minute-by-minute sleep/wake status, the sensitivity and specificity of the SWA were 0.94 (95%CI: 0.93, 0.95) and 0.88 (95%CI: 0.85, 0.90), respectively, using AW2 as the criterion measure. Conclusion: The algorithm developed for the SWA produced relatively accurate and consistent measurements of sleep quantity, timing, and quality compared to the AW2 under free-living conditions. Thus, the SWA is a viable alternative to standard wrist actigraphy.

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.

Appetitive and Metabolic Responses to an Exercise versus Dietary Intervention in Adults with Obesity.

Introduction/Purpose: 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. Methods: 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, ad libitum energy intake (EI) at a single meal, and over three days of free-living conditions and eating behavior traits. Resting metabolic rate (RMR) was measured with indirect calorimetry and adjusted for body composition measured by dual X-ray absorptiometry. Non-exercise activity was measured using accelerometers. Results: Forty-four individuals were included (age: 37 ± 9 years, body mass index: 30.6 ± 3.1 kg/m2). Both interventions resulted in weight and fat mass loss. The DIET group lost fat-free mass, although differences between groups were not significant (DIET: -1.2 ± 1.7 kg, p<0.001; AEX: 0.4 ± 1.5 kg, p=0.186; p=0.095 interaction). There were no differences in RMR after body composition adjustment. Both interventions were associated with an increase in dietary restraint (DIET: 4.9 ± 1.2, AEX: 2.8 ± 0.7; p<0.001 in both groups). Hunger decreased with DIET (-1.4 ± 0.5, p=0.003), and disinhibition decreased with AEX (-1.5 ± 0.5, p<0.001), although these changes were not different between groups (i.e., no group × time interaction). No other differences in appetite, EI, or non-exercise physical activity were observed within or between groups. Conclusions: AEX did not result in compensatory alterations in appetite, ad libitum EI, or physical activity, despite assumed increased energy expenditure. Modest evidence also suggested that disinhibition and hunger may be differentially impacted by weight loss modality.

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.

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.

A standard calculation methodology for human doubly labeled water studies.

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 (<10 kg). Using data for 1,021 babies and infants, we show that the DSR varies non-linearly with body mass between 0 and 10 kg. Using this relationship to predict DSR from weight provides an equation for rCO2 over this size range that agrees well with indirect calorimetry (average difference 0.64%; SD = 12.2%). We propose adoption of these equations in future studies.

Maximizing precision and accuracy of the doubly labeled water method via optimal sampling protocol, calculation choices, and incorporation of 17O measurements.

BACKGROUND/OBJECTIVES: 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. SUBJECTS/METHODS: 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). RESULTS: 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%). CONCLUSIONS: This work shows that optimizing sampling and calculation protocols can improve the accuracy and precision of DLW measurements.

Physical Activity Energy Expenditure and Total Daily Energy Expenditure in Successful Weight Loss Maintainers.

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.

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.