Relationship between actigraphy-assessed sleep quality and fat mass in college students

Harmonization of three different accelerometers to classify the 24 h activity cycle

Increasing interest in measuring key components of the 24 h activity cycle (24-HAC) [sleep, sedentary behavior (SED), light physical activity (LPA), and moderate to vigorous physical activity (MVPA)] has led to a need for better methods. Single wrist-worn accelerometers and different self-report instruments can assess the 24-HAC but may not accurately classify time spent in the different components or be subject to recall errors.Objective. To overcome these limitations, the current study harmonized output from multiple complimentary research grade accelerometers and assessed the feasibility and logistical challenges of this approach.Approach. Participants (n= 108) wore an: (a) ActiGraph GT9X on the wrist, (b) activPAL3 on the thigh, and (c) ActiGraph GT3X+ on the hip for 7-10 d to capture the 24-HAC. Participant compliance with the measurement protocol was compared across devices and an algorithm was developed to harmonize data from the accelerometers. The resulting 24-HAC estimates were described within and across days.Main results. Usable data for each device was obtained from 94.3% to 96.7% of participants and 89.4% provided usable data from all three devices. Compliance with wear instructions ranged from 70.7% of days for the GT3X+ to 93.2% of days for the activPAL3. Harmonized estimates indicated that, on average, university students spent 34% of the 24 h day sleeping, 41% sedentary, 21% in LPA, and 4% in MVPA. These behaviors varied substantially by time of day and day of the week.Significance. It is feasible to use three accelerometers in combination to derive a harmonized estimate the 24-HAC. The use of multiple accelerometers can minimize gaps in 24-HAC data however, factors such as additional research costs, and higher participant and investigator burden, should also be considered.

Associations of actigraphy-assessed sleep variables with adiposity and serum cardiometabolic outcomes in emerging adults

This study assessed associations of actigraphy-assessed sleep with adiposity and serum cardiometabolic outcomes in emerging adults, and whether sex and race modified these associations. Data on 147 emerging adults (age = 19.4 ± 1.3 years; body mass index = 26.4 ± 7.0 kg m-2 ; 59% female; 65% White) from RIGHT Track Health were used. Actigraphy-based sleep measures included sleep duration, sleep efficiency, sleep timing midpoint, day-to-day sleep duration and sleep timing midpoint variability. Combined sleep duration and sleep timing behaviours were also derived (early-bed/late-rise, early-bed/early-rise, late-bed/late-rise, late-bed/early-rise). Outcomes included body mass index and BodPod-assessed fat mass index, fasting serum leptin, C-reactive protein, and homeostatic model assessment-insulin resistance. Sleep duration was 5.4 h per night. We noted an inverse association between sleep duration and homeostatic model assessment-insulin resistance. The early-bed/early-rise group had greater body mass index, C-reactive protein and homeostatic model assessment-insulin resistance compared with the early-bed/late-rise group (referent). Sex modified associations of sleep efficiency with C-reactive protein; stratified results revealed positive association between sleep efficiency and C-reactive protein in males, but not females. Race modified associations of sleep duration with body mass index and leptin, and of sleep duration variability with C-reactive protein. Stratified analyses revealed inverse associations between sleep duration with body mass index and leptin in Black, multiracial/other race individuals only. Positive association between sleep duration variability and C-reactive protein was noted in White individuals only. Shorter sleep duration, particularly when combined with earlier sleep timing, is associated with greater adiposity and serum cardiometabolic outcomes. Additional studies are needed to assess individual- and contextual-level factors that may contribute to sex and race differences in sleep health and cardiometabolic risk in emerging adults.

Feasibility of a Self-Administered Hypnosis Intervention for Improving Sleep in College Students

Approximately two out of three college students report experiencing suboptimal sleep quality. The aim of this study was to examine the feasibility of a self-administered hypnosis intervention to improve sleep in college students. Twenty-two college students who self-reported poor sleep quality were enrolled in a 4-week study comprising 1 baseline week and a 3-week self-administered hypnosis intervention. Sleep onset latency and sleep efficiency as measured by wrist actigraphy were significantly improved. The mean average nightly sleep duration during the baseline week was 398.88 minutes (SD = 56.44), which increased to a mean of 413.88 minutes (SD = 57.80) during the 3rd week of intervention. However, the results show that there was no statistically significant difference between weeks on objective nightly sleep duration, 95% CI [-11.13, 41.13], t(15) = 1.224, p = .240. Also, results showed that there was no significant difference between weeks on self-reported nightly sleep duration, F(3, 57) = 2.155, p = .103. Twenty participants (91%) completed the study intervention and adherence to daily self-hypnosis practice with an audio recording was high. Zero study-related adverse events were reported, and participants perceived the intervention as easy to use and helpful for improving sleep. These results provide evidence for the feasibility and safety of a self-administered hypnosis intervention to improve sleep in college students. A larger randomized clinical trial is warranted to determine efficacy.

Interrelationships of Sleep Quality, Obesity Severity, and Clinical Headache Features among Women with Comorbid Migraine and Obesity

Obesity and migraine are often comorbid. Poor sleep quality is also common among individuals with migraine and may be influenced by comorbidities such as obesity. However, understanding of migraine's relationship with sleep and the potential exacerbating effect of obesity remains limited. This study evaluated the associations of migraine characteristics and clinical features with sleep quality among women with comorbid migraine and overweight/obesity and assessed the interplay between obesity severity and migraine characteristics/clinical features in relation to sleep quality. Women seeking treatment for migraine and obesity (n = 127; NCT01197196) completed a validated questionnaire assessing sleep quality (Pittsburgh Sleep Quality Index-PSQI). Migraine headache characteristics and clinical features were assessed using smartphone-based daily diaries. Weight was measured in-clinic, and several potential confounders were assessed using rigorous methods. Nearly 70% of participants endorsed poor sleep quality. Greater monthly migraine days and the presence of phonophobia related to poorer sleep quality, and specifically poorer sleep efficiency, controlling for confounders. Obesity severity was neither independently associated nor interacted with migraine characteristics/features to predict sleep quality. Poor sleep quality is common among women with comorbid migraine and overweight/obesity, although obesity severity does not appear to uniquely relate to or exacerbate the association between migraine and sleep in this population. Results can guide research on mechanisms of the migraine-sleep link and inform clinical care.

Association between sleep quality and urolithiasis among general population in Western China: a cross-sectional study

Background

Growing number of studies have evidently shown that sleep disorders are associated with the recently increased risk of various diseases in general human population. However, the relationship between sleep quality and urolithiasis condition in humans is still unclear. The present study explored the relationship between quality of sleep and urolithiasis in Chinese population of population, western China and hence investigated the effects of sleep quality on urolithiasis disease.

Methods

A cross-sectional analysis was performed using data from the West China Natural Population Cohort Study (WCNPCS). The data was collected between May 2019 and June 2021. This study evaluated the association between the sleep quality and urolithiasis. The sleep quality was assessed using the Chinese version of the Pittsburgh Sleep Quality Index (PSQI) whereas urolithiasis, as the outcome was a binary variable. Multivariable logistic regression models that adjust the sociodemographic characteristics and health-related factors were used to assess the association between sleep quality and urolithiasis. Interaction was tested in prespecified subgroup of interest.

Results

After adjusting a series of confounding variables, the Pittsburgh Sleep Quality Index scores were found to have a significant positive correlation with the prevalence of urolithiasis (OR: 1.178; 95% CI = 1.083–1.282; p < 0.001). The risk of urolithiasis was significantly increased with an elevation of the component Pittsburgh Sleep Quality Index score in sleep latency, sleep duration, habitual sleep efficiency, and daytime dysfunction.

Conclusions

It was evident that there is an association between sleep quality and prevalence of renal stones in natural population in western China regions. Poor sleep quality is related to urolithiasis. The findings of the current study hence highlighted the need for future public health guidelines to develop detailed strategies for improving sleep quality.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-14187-5.

Montmorency tart cherry supplementation does not impact sleep, body composition, cellular health, or blood pressure in healthy adults

Background: Sleep disturbances are linked with cardiovascular and metabolic disease as well as poor body composition. Aim: To investigate the use of tart cherry supplements, which are high in antioxidants and may contain melatonin, on parameters of health such as sleep, body composition, cellular health, and blood pressure (BP). Methods: Forty-four participants had completed sleep record data and were included in this analysis. Participants consumed either two 240 ml bottles per day of Montmorency tart cherry (MTC) juice or placebo or two capsules per day of powdered MTC or placebo for 30 days. Participants tracked their sleep daily via questionnaire and completed body composition and BP assessments at baseline, 14 days, and 30 days after supplementation. Results: There were no significant differences in sleep time or quality between groups, though both increased over 30 days. The capsule groups had significantly lower body mass (BM) 14 days versus baseline for placebo group (p = 0.01, mean difference: 0.70 kg) and at 30 days versus 14 days in MTC group (p = 0.02, mean difference: 0.75 kg). No other differences in body composition or cellular health were found. BP was unaffected by MTC supplementation over 30 days. Despite the potential benefits of antioxidants and melatonin, we did not find improvements in sleep time or quality, cellular health or BP in participants consuming MTC for 30 days, though BM decreased in capsule groups. Conclusion: These results conflict with previous data on MTC and sleep and BP, therefore further investigation is warranted.

The Potential Role of Sleep in Promoting a Healthy Body Composition: Underlying Mechanisms Determining Muscle, Fat, and Bone Mass and Their Association with Sleep

Sleep plays an essential role in human life. While sleep is a state elicited by the brain, its vital role reaches beyond maintaining brain health. Unhealthy sleeping habits have been associated with increased risk for inflammation, obesity, or diabetes. Evidence is emerging that sleep guides processes playing an important role in promoting the regulation of endocrine function involved in tissue regeneration and tissue remodelling. Thereby, sleep presumably is a critical factor contributing to the balance of core body tissues: bone, fat, and muscle mass. Given the increasing prevalence of various chronic diseases and comorbidities due to unhealthy lifestyle choices, sleep could be a key target to promote a healthy body composition up until old age. Here, we review the potential role of sleep and its underlying brain oscillations in body core tissues turnover. Specifically, we discuss potential underlying mechanisms linking sleep to body composition, both during rest and under challenging conditions. Among other described pathways, we highlight the possible role of the growth hormone that was found to be involved in the homeostasis of all core body tissues and has been strongly linked to brain activity dominating deep sleep, the so-called slow waves. Finally, we formulate important questions to be addressed in future research on the effect of sleep on body composition and specifically emphasize the importance of intervention studies to move from correlative to causal evidence.

Syndrome Metabolic Markers, Fitness and Body Fat Is Associated with Sleep Quality in Women with Severe/Morbid Obesity

Background: Sleep is an important modulator of neuroendocrine function and glucose metabolism. Poor sleep quality is related to metabolic and endocrine alterations, including decreased glucose tolerance, decreased insulin sensitivity, and increased hunger and appetite. Objective: The aim of the present study was to determine the association between sleep quality with metabolic syndrome (MetS) markers, fitness and body fat of women with severe/morbid obesity. Methods: This cross-sectional study included 26 women with severe/morbid obesity. Fasting plasma glucose (FPG), high-density lipids (HDL-c), triglycerides (TGs), and the metabolic outcomes total cholesterol (Tc) and low-density lipids (LDL-c), systolic (SBP) and diastolic blood pressure (DBP), body composition and fitness were measured. Results: Poor sleep quality showed a positive association with body fat (%) ≥ 48.2 (OR; 8.39, 95% CI; 1.13–62.14, p = 0.037), morbid obesity (OR; 8.44, 95% CI; 1.15–66.0, p = 0.036), glucose ≥ 100 mg/dL (OR; 8.44, 95% CI; 1.15–66.0, p = 0.036) and relative handgrip strength ≤ 0.66 (OR; 12.2, 95% CI; 1.79–83.09, p = 0.011). Conclusion: sleep quality is associated with health markers in women with severe/morbid obesity.

Sleep duration and anthropometric indices in an Iranian population: the Fasa PERSIAN cohort study

Recent decades have seen a dramatic rise in the prevalence of obesity. While genetic factors can influence obesity, environmental factors and lifestyle may play important roles as well. Sleep can be regarded as one of these factors. This study aimed to examine sleep duration, as a potential risk factor for obesity in an Iranian population. In this cross-sectional study, the Fasa PERSIAN cohort study data was used and 10,136 subjects aged 35-70 were entered. Anthropometrics indices have been measured and the total body fat percentage (BFP) was obtained by Bio-Impedance Analysis. Also, physical activity and dietary intake have been recorded. Sleep duration was obtained and individuals categorized into two groups of "< 8" and "≥ 8" h of sleep. The mean age and sleep duration of the participants were 48.63 ± 9.57 years and 6.92 ± 1.62 h in the total population, respectively. All of the anthropometric indices were significantly higher in the "< 8 h of sleep" group than in the "≥ 8 h of sleep" group. Regarding BFP and fat mass index (FMI) the same results was seen (p-value < 0.05). Body mass index (BMI), Waist and hip circumferences (WC, HC), and waist-to-height ratio (WHtR) were in a significant negative association with night time sleep (p-value < 0.001), while these associations with daytime napping were positive (p-value < 0.001). After multi-variable adjusting, BMI, WC, HC, WHtR, and wrist circumference showed significant negative associations with 24-h sleep duration (p-value < 0.05). This study established the association between nocturnal, daytime napping, 24-h sleep duration and obesity parameters. Daytime napping was positively associated with obesity parameters and short 24-h sleep duration was associated with higher risk of overweight/obesity. These results indicate that insufficient sleep can be a screening indicator for an unhealthy lifestyle and poor health outcomes.

Association between sleep quality and central obesity among southern Chinese reproductive-aged women

BACKGROUND

The connections between sleep quality and central obesity among reproductive-aged women are not clear. The study aimed to explore the association between sleep quality and central obesity among Chinese reproductive-aged women and identify the independent contributions of sociodemographic characteristics, health-related factors, and sleep quality to central obesity.

METHODS

In this cross-sectional survey, the minimal sample sizes were 2404 subjects; 2449 Chinese women aged 18-49 participated in this study. Sleep quality was assessed by the Chinese version of the Pittsburgh Sleep Quality Index (PSQI). Central obesity as the outcome of interest was a binary variable; women were categorized as with versus without central obesity measured by waist circumference (WC). The independent contribution of sociodemographic characteristics (Cluster 1), health-related variables (Cluster 2), and sleep quality (Cluster 3) to central obesity was derived from the corresponding R² change (individual R² change/total R² × 100%), using clustered multiple logistic regression analyses.

RESULTS

The risk of central obesity increased significantly with poor sleep quality (assessed by global PSQI score) [adjusted odds ratio (OR) = 2.20 per SD increase; 95% confidence interval (CI) = 1.28-3.78; P = 0.004], increased sleep disturbance score (adjusted OR = 1.11 per SD increase; 95% CI = 1.01-1.22; P = 0.042) and decreased subjective sleep quality score (adjusted OR = 0.81 per SD increase; 95% CI = 0.73-0.90; P < 0.001). The independent contribution of sleep quality was 9.9%, less than those of sociodemographic (73.3%) and health-related (16.8%) variables. Among complaints related to sleep disturbance, the inability to breathe comfortably, and having bad dreams showed significant associations with central obesity.

CONCLUSIONS

There exists some degree of correlation between sleep quality and central obesity among Chinese reproductive-aged women. These findings underscore the need for future public health guidelines to formulate some detailed strategies to improve sleep quality, such as preventing and intervening risk factors that influence sleep quality and suggesting optimal sleep duration, which might effectively reduce the incidence of central obesity in this population group.

Relationships between College Students' Sedentary Behavior, Sleep Quality, and Body Mass Index

PURPOSE

Sedentary behavior (SB), sleep efficiency (SE), sleep duration (SD), and body mass index (BMI) are crucial determinants of an individual's health. However, empirical evidence regarding associations between these factors in young adults living in China remains unknown. Therefore, the purpose of this study was to examine the relationships between accelerometer-measured SB, SE, SD, and BMI in Chinese college students.

METHODS

Two-hundred and twenty college students (115 females, Meanage = 20.29 years, SD = 2.37) were recruited from a south-central Chinese university. Participants' SB (daily % time spent in SB), SE (number of minutes of sleep duration/number of minutes in bed), and SD were assessed via wrist-worn ActiGraph GT9X Link accelerometers for one week. Body weight was measured using a digital weight scale, height was measured using a stadiometer, and BMI was calculated as weight (kg)/height (m2).

RESULTS

Participants' average time spent in SB was 76.52% (SD = 10.03), SE was 84.12% (SD = 4.79), and BMI was 20.67 kg/m2 (SD = 3.12), respectively. Regression analyses indicated that SB (β = -0.17, p = 0.01) and BMI (β = -0.20, p < 0.01) negatively predicted SE. In addition, BMI negatively predicted SD (β = -0.22, p < 0.01).

CONCLUSION

Prolonged SB (e.g., screen viewing, smartphone use, and computer playing) and higher BMI may link to shorter sleep duration and lower sleep efficiency in Chinese young adults. Future randomized controlled trials are needed to further confirm these findings. Given that increased BMI status and SB may relate to adverse health outcomes, more population-based intervention strategies seeking to lower BMI and reduce SB (e.g., nutrition education and physical activity promotion) are needed in this population.

Markers of poor sleep quality increase sedentary behavior in college students as derived from accelerometry

PURPOSE

Sleep is essential for overall health and can impact academic performance. Prior research reports reduced sleep time in college students. Poor sleep may impact physical activity (PA) and sedentary behavior, or vice versa, but has not been examined extensively in this population. Therefore, the purpose of this study was to examine markers of sleep quality, PA, and sedentary behavior in college students using objective means.

METHODS

A convenience sample of college students underwent body composition analysis and 7-day objective PA and sleep assessment via accelerometry.

RESULTS

Among 81 college students (53 women), there was no association between total sleep time (TST) and weekly average PA. TST was negatively associated with sedentary minutes per day, sedentary bouts per day, and total time in sedentary bouts per day. Greater sedentary bouts per day and average sedentary minutes per day were seen in those with a TST < 6 h, with no difference in body composition. Further, TST was negatively associated with sedentary minutes accumulated on the subsequent day, for all 7 days.

CONCLUSION

In a primarily residential college student cohort, poor sleep is associated with sedentary behavior more than PA. These students, who require a high amount of transport PA to and from campus during the week, are compensating by sleeping more and moving less on the weekend.

Multiple measures derived from 3D photonic body scans improve predictions of fat and muscle mass in young Swiss men

INTRODUCTION

Digital tools like 3D laser-based photonic scanners, which can assess external anthropometric measurements for population based studies, and predict body composition, are gaining in importance. Here we focus on a) systematic deviation between manually determined and scanned standard measurements, b) differences regarding the strength of association between these standard measurements and body composition, and c) improving these predictions of body composition by considering additional scan measurements.

METHODS

We analysed 104 men aged 19-23. Bioelectrical Impedance Analysis was used to estimate whole body fat mass, visceral fat mass and skeletal muscle mass (SMM). For the 3D body scans, an Anthroscan VITUSbodyscan was used to automatically obtain 90 body shape measurements. Manual anthropometric measurements (height, weight, waist circumference) were also taken.

RESULTS

Scanned and manually measured height, waist circumference, waist-to-height-ratio, and BMI were strongly correlated (Spearman Rho>0.96), however we also found systematic differences. When these variables were used to predict body fat or muscle mass, explained variation and prediction standard errors were similar between scanned and manual measurements. The univariable predictions performed well for both visceral fat (r2 up to 0.92) and absolute fat mass (AFM, r2 up to 0.87) but not for SMM (r2 up to 0.54). Of the 90 body scanner measures used in the multivariable prediction models, belly circumference and middle hip circumference were the most important predictors of body fat content. Stepwise forward model selection using the AIC criterion showed that the best predictive power (r2 up to 0.99) was achieved with models including 49 scanner measurements.

CONCLUSION

The use of a 3D full body scanner produced results that strongly correlate to manually measured anthropometric measures. Predictions were improved substantially by including multiple measurements, which can only be obtained with a 3D body scanner, in the models.

Sedentary Behavior: A Key Component in the Interaction between an Integrated Lifestyle Approach and Cardiac Autonomic Function in Active Young Men

This study aimed to verify the association between autonomic cardiac function (CAF) and the integration of caloric expenditure by physical activity (PA) intensity, sedentary behavior (SB), and sleep quality (PSQI) in active young men. Thirty-five subjects were included, and caloric expenditure in moderate-to-vigorous and light-intensity PA, SB, and PSQI were assessed using questionnaires. Heart rate variability (HRV) was recorded for short periods of time in the supine and orthostatic positions. Multiple linear regression was realized unadjusted and adjusted for covariables, such as age, body mass index, and fat mass. No adjusted analysis indicated that, in the supine position, there were negative associations between the SB and the TP, HF, and NorHF indices, and positive associations between SB and NorLF and LF/HF. In the orthostatic position, an interaction between SB and NorLF was found. Significance of proportion with the TP, HF, and LF/HF indices was confirmed. When adjusted, for the supine position, negative interactions were documented between SB and the TP as well as the HF indices, and between PSQI and the LF/HF index, with interference under the HF and LF/HF indices. Finally, our findings indicate that the proposed approach interacts with CAF, and SB is significantly related to CAF in young active men.

Association between Sleep Quality and Body Composition in Sedentary Middle-Aged Adults

Background: Ageing is associated with sleep pattern changes and body composition changes, which are related to several diseases. Purpose: This study aimed to analyse the association between sleep quality and an extensive set of body composition parameters (waist-hip ratio, body mass index, bone mineral content, bone mineral density, lean mass, lean mass index, fat mass, fat mass percentage, fat mass index, visceral adipose tissue) and sleep quality in sedentary middle-aged adults. We also aimed to evaluate whether the possible associations accord between subjective and objective measurements of sleep quality. Methods: 74 (39 women) middle-aged sedentary adults (40–65 years old) participated in the present study. The sleep quality was assessed using the Pittsburgh sleep quality index (PSQI) scale and accelerometers. A PSQI global score more than 5 indicates poor sleep quality. Weight, height, waist and hip circumferences were measured, and body mass index and waist-hip ratio were also calculated. Body composition was assessed with a dual-energy X-ray absorptiometry scanner. Results: The PSQI global score was negatively associated with bone mineral content, bone mineral density, lean mass, lean mass index and positively associated with fat mass percentage. No association was found between accelerometer parameters and body composition variables. Conclusion: We showed that a subjective poor sleep quality was negatively associated with bone mineral content (BMC), bone mineral density (BMD), lean mass and lean mass index (LMI) whereas was positively associated with fat mass percentage in middle-aged adults. We also observed that these associations did not accord with objective sleep quality measurements.

Weight gain in first-semester university students: Positive sleep and diet practices associated with protective effects

For university students, alterations in sleep and diet quality are common, and the propensity for weight gain is well established. The role of sleep duration during periods of rapid weight gain is understudied. This study explored the relationships between sleep duration, diet patterns, and body composition in first-year university students. Data collection occurred during the beginning of the fall (August) and spring semesters (January). Anthropometric measures included weight, height, and percent body fat (%BF). Survey questions assessed sleep and diet quality. As a group, participants (N = 60) gained weight (1.8 ± 2.1 kg) over the 4.5-month period of study. Hierarchical cluster analysis (HCA) identified three groups based on weight change between baseline and follow-up visits. Group 1 ("maintainers") (N = 21) gained 0.1 ± 1.3 kg, group 2 ("modest gainers") (N = 24) gained 2.0 ± 1.7 kg, and group 3 ("major gainers") (N = 15) gained 3.8 ± 1.8 kg. No differences in weight, body mass index (BMI), %BF, or average sleep duration existed between clusters at baseline. Minimal differences in baseline dietary behaviors between groups were noted other than maintainers used more fat, e.g., butter, to season vegetables, bread, and potatoes compared to modest gainers (p = .010). At follow-up, sleep duration significantly decreased from baseline among major gainers (7.1 ± 0.7 vs. 6.8 ± 0.7 h, p = .017) while sleep duration increased from baseline among maintainers (7.3 ± 0.9 vs. 7.6 ± 1.0 h, p = .048). Sleep duration at follow-up was significantly shorter among major gainers compared to maintainers (p = .016). Total diet scores for maintainers and modest gainers improved between visits (p = .038 and 0.002, respectively) but did not change among major gainers. Combining sleep and diet education may increase the effectiveness of interventions designed to mitigate weight gain in this high-risk population.

Objective Measurements of Energy Balance Are Associated With Sleep Architecture in Healthy Adults

Study Objectives

We objectively measured body composition, energy expenditure, caloric intake, and sleep in a large, diverse sample of healthy men and women and determined how energy balance and diet associated with sleep physiology.

Methods

Healthy adults (n = 50; 21-50 years) participated in an in-laboratory study involving two baseline sleep nights (BL1-2, 10 hours time-in-bed/night, 2200-0800 hours). Polysomnography was recorded on BL2. Demographic information, body composition, and energy expenditure measurements were collected at study admittance and on BL1. Daily food/drink intake was recorded both before (on BL1) and after (on BL2) the sleep measurement. Partial Pearson's correlations assessed the relationship between energy balance and sleep physiology variables.

Results

At baseline, greater fat-free mass associated with lower total sleep time (r = -0.52, p = .030), lower sleep efficiency (r = -0.53, p = .004), and greater wake after sleep onset (r = 0.55, p = .002). Higher body fat percentage (r = 0.39, p = .038) and being overweight (Body Mass Index [BMI] 25-30; p = .026) associated with more rapid eye movement (REM) sleep. Higher protein intake (r's = 0.46-0.52; p's < .001-.002) and lower carbohydrate intake (r's = -0.31 to -0.34; p's = .027-.046) on BL1 and BL2 associated with more REM sleep. Greater fiber consumption on BL1 and BL2 associated with more slow-wave sleep (SWS; r's = 0.33-0.35; p's = .02-.03). More SWS related to increased carbohydrate intake the following day (BL2, r = 0.32, p = .037).

Conclusions

Body composition and diet were related to baseline sleep characteristics, including SWS and REM sleep duration and sleep maintenance. Future studies should further evaluate the influence of energy balance measures on sleep physiology, since dietary interventions may be useful in treating insufficient sleep, poor sleep quality, excessive sleepiness or other sleep disorders.

Multilevel analysis exploring the links between stress, depression, and sleep problems among two-year college students

OBJECTIVE

This study explored the association of stress and depression with a multidimensional sleep problems construct in a sample of 2-year college students.

PARTICIPANTS

The sample consisted of 440 students enrolled in 2-year study from Fall 2011 to Fall 2013.

METHODS

Participants in an obesity prevention study completed surveys assessing sleep, stress, and depression at baseline, 4, 12, and 24 months. Multilevel models predicting sleep problems were conducted to distinguish episodic from chronic reports of stress and depression.

RESULTS

Participants were primarily women (68%), white (73%), young adults (M age = 22.8), with an average of 8.4 hours of sleep per night. Neither stress nor depression was predictive of sleep quantity; however, they were predictive of sleep quality.

CONCLUSIONS

Results show that sleep quality rather than sleep quantity may be the greater health concern for young adults, suggesting that intervention programs targeting depression, stress management, and healthy sleep patterns are warranted.

Sleep Quality and Body Composition Variations in Obese Male Adults after 14 Weeks of Yoga Intervention: A Randomized Controlled Trial

Background:

Obesity is a big challenge all over the world. It is associated with many noncommunicable diseases. Yoga known to be add-on treatment may be effective for obesity control.

Aim:

To assess the effect of integrated approach of yoga therapy (IAYT) for body composition and quality of sleep in adult obese male.

Subjects and Methods:

A randomized controlled trial was conducted for 14 weeks on obese male of urban setting. Eighty individuals were randomly divided into two groups, i.e., yoga group (n = 40; age; 40.03 ± 8.74 years, body mass index [BMI] 28.7 ± 2.35 kg/m²) and control group (age; 42.20 ± 12.06 years, BMI 27.70 ± 2.05 kg/m²). The IAYT was imparted to yoga group for 1½ hour for 5 days in a week for 14 weeks. The control group continued their regular activities. The body composition by InBody R20 and sleep quality by Pittsburgh Sleep Quality Index (PSQI) were assessed. Statistical analysis was done for within and between groups using SPSS version 21. The correlation analysis was done on the difference in pre-post values.

Results:

The results showed that weight (P = 0.004), BMI (P = 0.008), bone mass (P = 0.017), obesity degree (P = 0.005), and mineral mass (P = 0.046) were improved in yoga group and no change in control group (P > 0.05). The global score of PSQI improved (P = 0.017) in yoga group alone.

Conclusion:

The results indicate the beneficial effects of IAYT on body composition and sleep quality in obese males. The yoga practice may reduce obesity with the improvement in quality of life.

Daily family stress and HPA axis functioning during adolescence: The moderating role of sleep

The present study examined the moderating role of sleep in the association between family demands and conflict and hypothalamic-pituitary-adrenal (HPA) axis functioning in a sample of ethnically diverse adolescents (n=316). Adolescents completed daily diary reports of family demands and conflict for 15 days, and wore actigraph watches during the first 8 nights to assess sleep. Participants also provided five saliva samples for 3 consecutive days to assess diurnal cortisol rhythms. Regression analyses indicated that sleep latency and efficiency moderated the link between family demands and the cortisol awakening response. Specifically, family demands were related to a smaller cortisol awakening response only among adolescents with longer sleep latency and lower sleep efficiency. These results suggest that certain aspects of HPA axis functioning may be sensitive to family demands primarily in the context of longer sleep latency and lower sleep efficiency.