The use of accelerometers to improve estimation of the thermic effect of food in whole room calorimetry studies.

We tested whether spontaneous physical activity (SPA) from accelerometers could be used in a whole-room calorimeter to estimate thermic effect of food (TEF). Eleven healthy participants (63% female; age: 27 ± 4 years; body mass index: 22.8 ± 2.6 kg/m2) completed two 23-hour visits in randomized order: one 'fed' with meals provided and one 'fasted' with no food. SPA was measured by ActivPAL and Actigraph accelerometers. Measured TEF was calculated as the difference in total daily energy expenditure (TDEE) between fed and fasted visits and compared to three methods of estimating TEF: 1) SPA-adjusted TEF (adjTEF)-difference in TDEE without SPA between visits, 2) Wakeful TEF-difference in energy expenditure obtained from linear regression and basal metabolic rate during waking hours, 3) 24h TEF-increase in TDEE above SPA and sleeping metabolic rate. Measured TEF was 9.4 ± 4.5% of TDEE. adjTEF (difference in estimated versus measured TEF: activPAL: -0.3 ± 3.3%; Actigraph: -1.8 ± 8.0%) and wakeful TEF (activPAL: -0.9 ± 6.1%; Actigraph: -2.8 ± 7.6%) derived from both accelerometers did not differ from measured TEF (all p>0.05). ActivPAL-derived 24h TEF overestimated TEF (6.8 ± 5.4%, p=0.002), while Actigraph-derived 24h TEF was not significantly different (4.3 ± 9.4%, p=0.156). TEF estimations using activPAL tended to show better individual-level agreement (i.e., smaller coefficients of variation). Both accelerometers can be used to estimate TEF in a whole-room calorimeter; wakeful TEF using activPAL is the most viable option given strong group-level accuracy and reasonable individual agreement.

A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.

Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.

Brown adipose tissue metabolism in women is dependent on ovarian status.

In rodents, loss of estradiol (E2) reduces brown adipose tissue (BAT) metabolic activity. Whether E2 impacts BAT activity in women is not known. BAT oxidative metabolism was measured in premenopausal (n = 27; 35 ± 9 yr; body mass index = 26.0 ± 5.3 kg/m2) and postmenopausal (n = 25; 51 ± 8 yr; body mass index = 28.0 ± 5.0 kg/m2) women at room temperature and during acute cold exposure using [11C]acetate with positron emission tomography coupled with computed tomograph. BAT glucose uptake was also measured during acute cold exposure using 2-deoxy-2-[18F]fluoro-d-glucose. To isolate the effects of ovarian hormones from biological aging, measurements were repeated in a subset of premenopausal women (n = 8; 40 ± 4 yr; BMI = 28.0 ± 7.2 kg/m2) after 6 mo of gonadotropin-releasing hormone agonist therapy to suppress ovarian hormones. At room temperature, there was no difference in BAT oxidative metabolism between premenopausal (0.56 ± 0.31 min-1) and postmenopausal women (0.63 ± 0.28 min-1). During cold exposure, BAT oxidative metabolism (1.28 ± 0.85 vs. 0.91 ± 0.63 min-1, P = 0.03) and net BAT glucose uptake (84.4 ± 82.5 vs. 29.7 ± 31.4 nmol·g-1·min-1, P < 0.01) were higher in premenopausal than postmenopausal women. In premenopausal women who underwent gonadotropin-releasing hormone agonist, cold-stimulated BAT oxidative metabolism was reduced to a similar level (from 1.36 ± 0.66 min-1 to 0.91 ± 0.41 min-1) to that observed in postmenopausal women (0.91 ± 0.63 min-1). These results provide the first evidence in humans that reproductive hormones are associated with BAT oxidative metabolism and suggest that BAT may be a target to attenuate age-related reduction in energy expenditure and maintain metabolic health in postmenopausal women.NEW & NOTEWORTHY In rodents, loss of estrogen reduces brown adipose tissue (BAT) activity. Whether this is true in humans is not known. We found that BAT oxidative metabolism and glucose uptake were lower in postmenopausal compared to premenopausal women. In premenopausal women who underwent ovarian suppression to reduce circulating estrogen, BAT oxidative metabolism was reduced to postmenopausal levels. Thus the loss of ovarian function in women leads to a reduction in BAT metabolic activity independent of age.

Chronotropic Incompetence During Exercise Testing as a Marker of Autonomic Dysfunction in Individuals with Early Parkinson's Disease.

BACKGROUND: An attenuated heart rate response to exercise, termed chronotropic incompetence, has been reported in Parkinson's disease (PD). Chronotropic incompetence may be a marker of autonomic dysfunction and a cause of exercise intolerance in early stages of PD. OBJECTIVE: To investigate the relationship between chronotropic incompetence, orthostatic blood pressure change (supine - standing), and exercise performance (maximal oxygen consumption, VO2peak) in individuals with early PD within 5 years of diagnosis not on dopaminergic medications. METHODS: We performed secondary analyses of heart rate and blood pressure data from the Study in Parkinson's Disease of Exercise (SPARX). RESULTS: 128 individuals were enrolled into SPARX (63.7±9.3 years; 57.0% male, 0.4 years since diagnosis [median]). 103 individuals were not taking chronotropic medications, of which 90 had a normal maximal heart rate response to exercise testing (155.3±14.0 bpm; PDnon-chrono) and 13 showed evidence of chronotropic incompetence (121.3±11.3 bpm; PDchrono, p < 0.05). PDchrono had decreased VO2peak compared to PDnon-chrono (19.7±4.5 mL/kg/min and 24.3±5.8 mL/kg/min, respectively, p = 0.027). There was a positive correlation between peak heart rate during exercise and the change in systolic blood pressure from supine to standing (r = 0.365, p < 0.001). CONCLUSIONS: A subgroup of individuals with early PD not on dopaminergic medication had chronotropic incompetence and decreased VO2peak, which may be related to autonomic dysfunction. Evaluation of both heart rate responses to incremental exercise and orthostatic vital signs may serve as biomarkers of early autonomic impairment and guide treatment. Further studies should investigate whether cardiovascular autonomic dysfunction affects the ability to exercise and whether exercise training improves autonomic dysfunction.

Distribution of dim light melatonin offset (DLMOff) and phase relationship to waketime in healthy adults and associations with chronotype.

OBJECTIVES: Dim light melatonin onset, or the rise in melatonin levels representing the beginning of the biological night, is the gold standard indicator of circadian phase. Considerably less is known about dim light melatonin offset, or the decrease in melatonin to low daytime levels representing the end of the biological night. In the context of insufficient sleep, morning circadian misalignment, or energy intake after waketime but before dim light melatonin offset, is linked to impaired insulin sensitivity, suggesting the need to characterize dim light melatonin offset and identify risk for morning circadian misalignment. METHODS: We examined the distributions of dim light melatonin offset clock hour and the phase relationship between dim light melatonin offset and waketime, and associations between dim light melatonin offset, phase relationship, and chronotype in healthy adults (N = 62) who completed baseline protocols measuring components of the circadian melatonin rhythm and chronotype. RESULTS: 74.4% demonstrated dim light melatonin offset after waketime, indicating most healthy adults wake up before the end of biological night. Later chronotype (morningness-eveningness, mid-sleep on free days corrected, and average mid-sleep) was associated with later dim light melatonin offset clock hour. Later chronotype was also associated with a larger, positive phase relationship between dim light melatonin offset and waketime, except for morningness-eveningness. CONCLUSIONS: These findings suggest morning circadian misalignment risk among healthy adults, which would not be detected if only dim light melatonin onset were assessed. Chronotype measured by sleep timing may better predict this risk in healthy adults keeping a consistent sleep schedule than morningness-eveningness preferences. Additional research is needed to develop circadian biomarkers to predict dim light melatonin offset and evaluate appropriate dim light melatonin offset timing to promote health.

Energy balance and body composition after switch between integrase strand transfer inhibitors and doravirine among people with HIV.

BACKGROUND: Integrase strand transfer inhibitors (INSTIs) are associated with excessive weight gain among a subset of persons with HIV (PWH), due to unclear mechanisms. We assessed energy intake (EI) and expenditure (EE) following switch off and onto INSTIs. METHODS: PWH with >10% weight gain on an INSTI-based regimen switched INSTI to doravirine for 12 weeks, then back to INSTI for 12 weeks while keeping their remaining regimen stable. Twenty-four-hour EE, EI and weight were measured on INSTI, following switch to doravirine, and upon INSTI restart. Mixed models analysed changes over time. RESULTS: Among 18 participants, unadjusted 24 h EE decreased by 83 (95% CI -181 to 14) kcal following switch to doravirine, and by 2 (-105 to 100) kcal after INSTI restart; energy balance (EE-EI) increased by 266 (-126 to 658) kcal from Week 0 to Week 12, and decreased by 3 (-429 to 423) kcal from Week 12 to Week 24. Trends toward weight loss occurred following switch to doravirine [mean -1.25 (-3.18 to 0.69) kg] and when back on INSTI [-0.47 (-2.45 to 1.52) kg]. Trunk fat decreased on doravirine [-474 (-1398 to 449) g], with some regain following INSTI restart [199 (-747 to 1145) g]. Fat-free mass decreased on doravirine [-491 (-1399 to 417) g] and increased slightly after INSTI restart [178 (-753 to 1108) g]. CONCLUSIONS: Among PWH with >10% weight gain on an INSTI, switch to doravirine was associated with a trend towards decreases in 24 h EE, weight, trunk fat mass and fat-free mass. Observed changes were not significant, but suggest a mild weight-suppressive effect of doravirine among PWH.

Maximal daily stepping cadence partially explains functional capacity of individuals with end-stage knee osteoarthritis.

BACKGROUND: Individuals with end-stage knee osteoarthritis (OA) walk at a lower intensity (ie, slower step cadence) contributing to worse physical function. Previous literature reports daily step counts and sedentary time, with little information regarding stepping bouts or cadence. Determining relationships between daily higher stepping cadence duration and clinical outcomes can move the field toward optimal daily stepping prescription. OBJECTIVE: To quantify daily physical activity patterns of individuals with end-stage knee OA and determine the contribution of high stepping cadence to explain functional capacity variability. DESIGN: Cross-sectional analysis. SETTING: Veterans Administration medical center. PARTICIPANTS: U.S. military veterans (n = 104; age: 67.1 years [7.2]; mean [SD]; male [89.3%]) with end-stage knee OA were enrolled. INTERVENTION: Not applicable. MAIN OUTCOME MEASURE: Functional capacity (6-Minute Walk Test [6MWT]). Physical activity (activPAL wearable sensor; cadence and time sitting, standing, and stepping), pain (Western Ontario and McMaster Universities Osteoarthritis Index-pain subscale) sociodemographic variables, and comorbidities (body mass index and Functional Comorbidity Index) are the main explanatory variables. RESULTS: Participants' wake time was mainly sitting (11.0 h/day) in ≥60-minute bouts (29.7% ± 12.7 of sitting time). Standing (3.4 hours/day) and stepping (1.4 h/day) primarily occurred in 0-5 minute bouts (standing: 87.7% ± 14.4 of standing time, stepping: 98.7% ± 12.7 of stepping time) and stepping cadence was predominantly incidental (1-19 spm; 52.9% ± 9.6 of total stepping time). Backward elimination model results indicated shorter medium-to-brisk cadence bout duration, older age, and higher pain significantly explained shorter 6MWT distance (Adj R2 =0.24, p < .01). CONCLUSIONS: Individuals with knee OA spend most of their waking hours sitting, while standing and stepping occurs in short bouts at very low stepping cadence. Decreased time in high stepping cadence is associated with lower functional capacity. Future studies should explore if increasing the daily time spent in higher step cadence can improve functional capacity in this population.

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 Effects of an Acute Bout of Aerobic or Resistance Exercise on Nonexercise Physical Activity.

Introduction/Purpose: A reduction in nonexercise physical activity (NEPA) after exercise may reduce the effectiveness of exercise interventions on weight loss in adults with overweight or obesity. Aerobic exercise (AEx) and resistance exercise (REx) may have different effects on NEPA. The purpose of this secondary analysis was to examine the effect of a single bout of AEx or REx on NEPA and sedentary behavior in inactive adults with overweight or obesity. Methods: Adults with overweight or obesity (n = 24; 50% male; age, 34.5 ± 1.5 yr; body mass index, 28.5 ± 0.9 kg·m-2) not meeting current physical activity guidelines completed a single 45-min bout of AEx, REx, or a sedentary control on different days in random order. After each condition, participants' NEPA was recorded for 84 h by accelerometer. Time spent sedentary and in light, moderate, and vigorous physical activity; steps; metabolic equivalent of task (MET)-hours; and sit-to-stand transitions were calculated using activity count data. Results: No differences were observed in the percent of waking time spent sedentary and in light, moderate, and vigorous activity between conditions (P > 0.05). No differences were observed in steps, MET-hours, or sit-to-stand transitions between conditions (P > 0.05). NEPA responses were variable among individuals, with approximately half of participants reducing and half increasing NEPA over the 84 h after each exercise condition. Conclusion: NEPA was not reduced after an acute bout of AEx or REx in a sample of inactive adults with overweight or obesity.

Comparison of postoperative mobilization measurements by activPAL versus Johns Hopkins Highest Level of Mobility scale after major abdominal surgery.

BACKGROUND: The Johns Hopkins Highest Level of Mobility scale is a validated tool for assessing patient mobility in the hospital. It has excellent inter-rater and test-retest reliabilities, but it is unknown how accurately Johns Hopkins Highest Level of Mobility documentation reflects the patients' mobility performance in the immediate postoperative period compared to objective measures such as accelerometers. METHODS: In this single-center observational study, consented adults undergoing open abdominal surgery wore a research-grade accelerometer, activPAL, starting immediately postoperatively until hospital discharge or up to 7 days. We collected the Johns Hopkins Highest Level of Mobility scores documented by hospital staff via retrospective chart review and evaluated their accuracy in describing the type, frequency, and volume of postoperative out-of-bed mobilization using the activPAL as the criterion. RESULTS: We analyzed data from 56 participants. The activPAL showed that participants spent 97.7% of their time lying in bed or sitting in a chair. Meanwhile, the Johns Hopkins Highest Level of Mobility documentation of preambulatory activities (scores 1-5) was rare. The activPAL detected 4 times more out-of-bed mobilization than routine Johns Hopkins Highest Level of Mobility documentation. Whereas the frequency of activPAL-measured out-of-bed mobilization increased steadily to a median of 9 sessions by postoperative day 6, the number of Johns Hopkins Highest Level of Mobility documentation remained around twice daily. ActivPAL measurements demonstrated that Johns Hopkins Highest Level of Mobility documentation of ambulatory sessions (scores 6-8) was accurate. CONCLUSIONS: We found that routine Johns Hopkins Highest Level of Mobility documentation did not accurately detect preambulatory activities or the overall frequency of out-of-bed mobility sessions, poorly reflecting the highly sedentary behaviors of the acute postoperative inpatients and highlighting the need to improve clinical documentation or use alternative methods to track postoperative mobilization.

Accelerometer-Measured Inpatient Physical Activity and Associated Outcomes After Major Abdominal Surgery: Systematic Review.

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 <18 years. Risk of bias was assessed using the risk-of-bias assessment tool for nonrandomized studies (RoBANS) for observational studies and the revised Cochrane risk-of-bias tool for randomized trials (RoB 2) for randomized controlled trials (RCTs). Findings were summarized by qualitative synthesis. 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 <100. Of the 15 studies, 13 (87%) included the general surgery population, 1 (7%) was a study of patients who had undergone gynecologic surgery, and 1 (7%) included a mixed (abdominal, thoracic, gynecologic, and orthopedic) surgical population. Of the 15 studies, 12 (80%) used consumer-grade accelerometers to measure physical behaviors. Step count was the most commonly reported physical activity outcome (12/15, 80%). In the observational studies (9/15, 60%), increased physical activity during the immediate postoperative period was associated with earlier return of gastrointestinal function, fewer surgical and pulmonary complications, shorter hospital length of stay, and fewer readmissions. In the RCTs (6/15, 40%), only 1 (17%) of the 6 studies demonstrated improved outcomes (shorter time to flatus and hospital length of stay) when a mobility-enhancing intervention was compared with usual care. Notably, mobility-enhancing interventions used in 4 (67%) of the 6 RCTs did not result in increased postoperative physical activity. 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.

The effects of resistance exercise on appetite sensations, appetite related hormones and energy intake in hormone receptor-positive breast cancer survivors.

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 minutes after a standardized breakfast meal. Appetite visual analog scales and hormones (total ghrelin and peptide-YY [PYY]) were measured before and 30, 90, 120, 150, and 180 minutes post-meal and expressed as area under the curve (AUC). Participants were offered a buffet-type meal 180 minutes after breakfast to assess ad libitum EI. Body composition (dual X-ray absorptiometry) and RMR (indirect calorimetry) were measured during a separate visit. Sixteen BCS were included (age: 46 ± 2 y, BMI: 24.9 ± 1.0 kg/m2). There were no differences in appetite ratings or EI between conditions. There were no differences in appetite hormone AUC, but REx resulted in lower ghrelin 120 (-85 ± 39 pg/mL, p = 0.031) and 180 (-114 ± 43 pg/mL, p = 0.018) minutes post-breakfast and higher PYY 90 (21 ± 10 pg/mL, p = 0.028) and 120 (14 ± 7 pg/mL, p = 0.041) minutes post-breakfast. Fat-free mass and RMR negatively correlated with hunger and prospective food consumption AUC after SED, but not REx. In sum, a single REx bout temporarily reduces orexigenic and increases anorexic appetite hormones, but not acute subjective appetite sensations or EI.

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.

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.

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.

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.

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.

Body composition and cardiometabolic health across the menopause transition.

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.