Objectively Measured Sleep Patterns in Young Adult Women and the Relationship to Adiposity

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.

Dietary inflammatory index and neuropsychiatric disorders

Neuropsychiatric disorders (NPDs) are considered a potential threat to mental health. Inflammation predominantly plays a role in the pathophysiology of NPDs. Dietary patterns are widely postulated to be involved in the physiological response to inflammation. This review aims to discuss the literature on how dietary inflammatory index (DII) is related to inflammation and, consequently, NPDs. After comprehensive scrutiny in different databases, the articles that investigated the relation of DII score and various NPDs and psychological circumstances were included. The association between dietary patterns and mental disorders comprising depression, anxiety, and stress proved the role of a proinflammatory diet in these conditions' exacerbation. Aging is another condition closely associated with DII. The impact of proinflammatory and anti-inflammatory diet on sleep quality indicated related disorders like sleep latency and day dysfunctions among the different populations are in relation with the high DII score. The potential effects of genetic backgrounds, dietary patterns, and the gut microbiome on DII are discussed as well. To plan preventive or therapeutic interventions considering the DII, these factors, especially genetic variations, should be considered as there is a growing body of literature indicating the role of personalized medicine in different NPDs. To the best of our knowledge, there is a limited number of RCTs on this subject, so future research should evaluate the causality via RCTs and look for therapeutic interventions with an eye on personalized medicine using information about DII in NPDs.

The importance of sleep regularity: a consensus statement of the National Sleep Foundation sleep timing and variability panel

OBJECTIVE

To develop and present consensus findings of the National Sleep Foundation sleep timing and variability panel regarding the impact of sleep timing variability on health and performance.

METHODS

The National Sleep Foundation assembled a panel of sleep and circadian experts to evaluate the scientific evidence and conduct a formal consensus and voting procedure. A systematic literature review was conducted using the NIH National Library of Medicine PubMed database, and panelists voted on the appropriateness of 3 questions using a modified Delphi RAND/UCLA Appropriateness Method with 2 rounds of voting.

RESULTS

The literature search and panel review identified 63 full text publications to inform consensus voting. Panelists achieved consensus on each question: (1) is daily regularity in sleep timing important for (a) health or (b) performance? and (2) when sleep is of insufficient duration during the week (or work days), is catch-up sleep on weekends (or non-work days) important for health? Based on the evidence currently available, panelists agreed to an affirmative response to all 3 questions.

CONCLUSIONS

Consistency of sleep onset and offset timing is important for health, safety, and performance. Nonetheless, when insufficient sleep is obtained during the week/work days, weekend/non-work day catch-up sleep may be beneficial.

The Effects of Exercise on Appetite-Regulating Hormone Concentrations over a 36-h Fast in Healthy Young Adults: A Randomized Crossover Study

Hunger and satiety are controlled by several physiological mechanisms, including pancreatic and gastrointestinal hormones. While the influence of exercise and fasting have been described individually, in relation to these hormones, there is a paucity of work showing the effects of the two modalities (fasting and exercise) combined. Twenty healthy adults (11 males, 9 females) completed both conditions of this study, each consisting of a 36-h water-only fast. One of the fasts began with treadmill exercise, and the differences between the conditions on various appetite hormones were measured every 12 h. The difference in the area under the curve between conditions for ghrelin was 211.8 ± 73.1 pg/mL (F = 8.40, p < 0.0105), and, for GLP-1, it was -1867.9 ± 850.4 pg/mL (F = 4.82, p < 0.0422). No significant differences were noted for areas under the curve between conditions for leptin, PP, PYY, insulin, or GIP. Initiating a fast with exercise lowers ghrelin concentrations and elevates GLP-1 concentrations. Given that ghrelin elicits feelings of hunger and GLP-1 signals feelings of satiety, adding exercise to the beginning of a fast may reduce some of the biological drive of hunger, which could make fasting more tolerable, leading to better adherence and more significant health outcomes.

Associations between Sleep and Body Composition in Older Women and the Potential Role of Physical Function

Purpose

The relationship between sleep and adiposity in older women remains unclear partly due to the reliance of body mass index as a measure of adiposity. The purpose of this study was to investigate associations between objectively measured sleep characteristics and body composition measured by dual energy x-ray absorptiometry (DXA) in older women. A secondary purpose was to examine if physical function mediates this relationship.

Methods

Non-obese older women (ages 60-75 years, n=102) were included in the study. Total sleep time (TST), time in bed (TIB), sleep efficiency (SE), and wake after sleep onset (WASO) were determined by actigraphy. A battery of tests was used to assess physical function.

Results

With adjustment for age, there was a negative association between TST and TIB with lean mass. Both grip strength and dominant leg extension were associated with TST, TIB, and lean mass; the associations between TST and TIB with lean mass were lost after adjusting for grip strength or leg extension strength. Additionally, SE was negatively associated with total, gynoid, and trunk lean mass, and there was a positive association between TST and percent trunk fat, and WASO and gynoid lean mass, with age adjusted.

Conclusions

Sleep characteristics, TST, TIB, SE, and WASO, were associated body composition measures in this sample of older women. The relationship between TST and TIB with body composition was mediated, in part, by grip strength and leg extension strength.

A developmental perspective on sleep consistency: Preschool age through emerging adulthood

OBJECTIVE/BACKGROUND

Beyond sleep duration, the regularity of sleep patterns (e.g., sleep consistency), including variability in sleep timing (e.g., bedtime, wake time) and duration, is a critical marker of sleep health. Sleep consistency is captured using a variety of methods within the literature (e.g., sleep intraindividual variability, social jetlag), but most of the research focuses on adolescents.

METHODS

Drawing on a developmental perspective, this narrative review highlights how normative changes at the individual (e.g., biological, cognitive, and social) and contextual (e.g., home, school, sociocultural) levels may contribute to inconsistent sleep patterns across development.

RESULTS AND CONCLUSIONS

This review emphasizes how inconsistent sleep may increase across pivotal transitions throughout development (e.g., elimination of naps, puberty, summertime, entering college). Finally, recommendations for measuring sleep consistency and areas to address in future research are discussed.

The Updating and Individualizing of Sleep Hygiene Rules for Non-clinical Adult Populations

Sleep hygiene is essential for the prevention of somatic and mental disorders, including the prevention of sleep disorders. However, it does not typically address individual differences. The aim of this review is threefold: first, to outline the empirical evidence for particular components of sleep hygiene rules; second, to indicate the importance of individualized sleep hygiene application with regard to the varying degree of validity of sleep hygiene rules in the population; third, to highlight a new field of sleep hygiene, namely light hygiene. PubMed and Google Scholar were used to identify studies that were published between 2007 and 2022. A search was conducted for studies related to sleeping rules topics: sleep regularity, regular exercise, alcohol, caffeine, napping, relaxation and meditation, food intake and light exposure. In applying these sleep hygiene principles, it is essential to pay attention to individual variables such as age, genetic predisposition, health status, and substance (caffeine, alcohol) possible dependence.

Changes in dietary inflammatory potential predict changes in sleep quality metrics, but not sleep duration

STUDY OBJECTIVES

Non-pharmacological sleep interventions may improve sleep profiles without the side-effects observed with many pharmacological sleep aids. The objective of this research was to examine the association between sleep and inflammation and to examine how changes in dietary inflammatory potential influence changes in sleep.

METHODS

The Inflammation Management Intervention Study (IMAGINE), which was a dietary intervention designed to lower inflammation, provided access to 24-h dietary recalls (24HR), objectively measured sleep using SensewearTM armbands, and a range of self-reported demographics, health histories, lifestyle behaviors, psychosocial metrics, anthropometric measurements, and inflammatory biomarkers. Dietary Inflammatory Index® (DII®) scores were calculated from three unannounced 24HR-derived estimated intakes of whole foods and micro and macronutrients over a 2-week period at baseline and post-intervention (i.e. month 3). Statistical analyses primarily utilized linear regression.

RESULTS

At baseline, for every 1-min increase in sleep onset latency, tumor necrosis factor-α increased by 0.015 pg/mL (±0.008, p = 0.05). Every one-percentage increase in sleep efficiency was associated with decreased C-reactive protein (CRP) of -0.088 mg/L (±0.032, p = 0.01). Every 1-min increase in wake-after-sleep-onset (WASO) increased both CRP and interleukin-6. Compared to participants with pro-inflammatory DII changes over 3 months, those with anti-inflammatory changes decreased WASO (0 vs. -25 min, respectively, p < 0.01) and improved sleep efficiency (-2.1% vs. +2.6%, respectively, p = 0.04).

CONCLUSIONS

Non-pharmacological treatments, such as anti-inflammatory diets, may improve sleep in some adults. Future research involving dietary treatments to improve sleep should not only focus on the general population, but also in those commonly experiencing co-morbid sleep complaints.

CLINICAL TRIAL INFORMATION

NCT02382458.

Variability of Sleep and Relations to Body Weight Among First-Year College Students

BACKGROUND

Existing research suggests that greater sleep variability may increase risk for weight gain. College often marks a transition to a less consistent daily schedule, which may adversely impact sleep routines and further increase risk for weight gain. The current study is among the first to explore relations between nighttime sleep variability and daytime sleep (napping) and body weight among first-year college students.

METHODS

Using daily diary methods, first-year college students (N = 307; 84.7% female) self-reported their sleep for seven days. Several indices were created to capture sleep variability for reported bedtime, wake time, and sleep duration, including weekday versus weekend differences (WvW), day to day differences (D2D), and overall standard deviation (SD). Napping was also assessed. Based on body mass index (BMI), individuals were categorized as underweight, healthy weight, overweight, and obese.

RESULTS

Across indices, students' sleep varied over an hour on average across the week. Hierarchical regressions revealed that greater differences in wake time D2D, wake time SD, and sleep duration WvW were all associated with higher BMI, after accounting for gender, depressive symptoms, and sleep duration. Longer napping was also associated with higher BMI, using the same covariates. Finally, greater sleep variability was reported by overweight and obese than healthy weight individuals.

CONCLUSION

These findings suggest that sleep variability, particularly wake times and napping may be important modifiable sleep behaviors to investigate in future studies. More longitudinal research is needed to explore relations between multiple facets of sleep variability and weight gain, including possible mechanisms.

The association between sleep health and weight change during a 12-month behavioral weight loss intervention

BACKGROUND

Prior research on the relationship between sleep and attempted weight loss failed to recognize the multidimensional nature of sleep. We examined the relationship between a composite measure of sleep health and change in weight and body composition among adults in a weight loss intervention.

METHODS

Adults (N = 125) with overweight or obesity (50.3 ± 10.6 years, 91% female, 81% white) participated in a 12-month behavioral weight loss intervention, with assessments of sleep, weight, fat mass, and fat-free mass at baseline, 6 months, and 12 months. Six sleep dimensions (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as "good" or "poor" using questionnaires and actigraphy. A composite score was calculated by summing the number of "good" dimensions. Obstructive sleep apnea (OSA) was assessed in a subsample (n = 117), using the apnea-hypopnea index (AHI) to determine OSA severity. Linear mixed modeling was used to examine the relationships between sleep health and outcomes of percent weight, fat mass, or fat-free mass change during the subsequent 6-month interval, adjusting for age, sex, bed partner, and race; an additional model adjusted for AHI.

RESULTS

Mean baseline and 6-month sleep health was 4.5 ± 1.1 and 4.5 ± 1.2, respectively. Mean weight, fat mass, and fat-free mass changes from 0 to 6 months were -9.3 ± 6.1%, -16.9 ± 13.5%, and -3.4 ± 3.4%, respectively, and 0.4 ± 4.8%, -0.3 ± 10.3%, and 0.7 ± 4.1% from 6 to 12 months. Better sleep health was associated with greater subsequent weight loss (P = 0.016) and fat loss (P = 0.006), but not fat-free mass loss (P = 0.232). Following AHI adjustment, the association between sleep health and weight loss was attenuated (P = 0.102) but remained significant with fat loss (P = 0.040). Regularity, satisfaction, timing, and efficiency were each associated with weight and/or fat loss (P ≤ 0.041).

CONCLUSIONS

Better sleep health was associated with greater weight and fat loss, with associations attenuated after accounting for OSA severity. Future studies should explore whether improving sleep health, OSA, or the combination improves weight loss.

Association between objectively measured body composition, sleep parameters and physical activity in preschool children: a cross-sectional study

OBJECTIVE

Associations between self-reported sleep duration and obesity indices in children are well recognised; however, there are no studies on associations between objectively measured other sleep parameters and physical activity with body composition in preschoolers. Therefore, the aim of this study was to determine the associations between sleep parameters and moderate-to-vigorous physical activity (MVPA) with body composition indices in preschoolers using objective measures.

DESIGN

A cross-sectional study.

PARTICIPANTS

The study group consisted of 676 children aged 5-6 years, who were enrolled in kindergartens in the 2017/2018 school year.

OUTCOME MEASURES

Sleep parameters and MVPA were measured using accelerometers for 7 days. Bioelectrical impedance analysis was used to estimate body composition.

RESULTS

Sleep duration and sleep efficiency were inversely associated with body fat percentage (BFP) (β=-0.013 and β from -0.311 to -0.359, respectively) and body mass index (BMI) (β from -0.005 to -0.006 and from -0.105 to -0.121, respectively), and directly associated with fat-free mass (FFM) (β from 0.010 to 0.011 and from 0.245 to 0.271, respectively) and muscle mass (β from 0.012 to 0.012 and from 0.277 to 0.307, respectively) in unadjusted and adjusted models. BFP was inversely associated with MVPA and positively associated with number of awakenings and sleep periods. Number of sleep periods was inversely associated with FFM, and positively with BMI and muscle mass. Correlation matrix indicated significant correlation between BFP, FFM and muscle mass with sleep duration, sleep efficiency, number of sleep periods and MVPA.

CONCLUSIONS

Periodic assessment of sleep parameters and MVPA in relation to body composition in preschool children may be considered, especially in those who are at risk for obesity.

Sleep Inconsistency and Markers of Inflammation

Objective: Poor sleep is associated with higher levels of inflammatory biomarkers. Conventionally, higher average time awake, lower average time asleep, and lower sleep efficiency define poor sleep. Recent research suggests that, in addition to average sleep, sleep inconsistency is an important indicator of sleep dysfunction. The current study sought to extend our knowledge of the relationship between sleep and inflammation through an examination of sleep inconsistency and inflammatory biomarkers. Methods: Secondary analyses of the Survey of Midlife in the United States (MIDUS) sleep study were conducted. Five hundred thirty-three individuals completed nightly sleep diaries, actigraphy, and underwent a blood draw for the inflammatory biomarkers C-reactive protein, interleukin-6, and fibrinogen. Sleep inconsistency was derived from 7 consecutive nights of assessment and was operationalized as nightly fluctuations in the following variables: terminal wakefulness, number of awakenings, time in bed, sleep onset latency, and wake after sleep onset. Structural equation modeling was used to examine the influence of a latent average sleep and a latent sleep inconsistency variable on a latent inflammation variable. Models were subsequently adjusted for age, sex, BMI, health, and medication. Stratified models by sex were also analyzed. Results: The average sleep model would not converge. The sleep inconsistency model fit the data well. A significant positive association between the latent factors sleep inconsistency and inflammation was observed (β = 10.18, SE = 4.40, p = 0.021), suggesting inconsistent sleep is associated with higher levels of inflammatory biomarkers. When stratified by sex, the association between the latent sleep inconsistency factor and inflammation was significant for women (β = 1.93, SE = 0.82, p = 0.018), but not men (β = 0.20, SE = 0.35, p = 0.566). The association between sleep inconsistency and inflammation weakened following multivariate adjustment (β = 6.23, SE = 3.71, p = 0.093). Conclusions: Inconsistent sleep may be an associated feature of inflammatory dysfunction, especially in women. Future studies should build upon this preliminary work and examine these associations longitudinally and through treatment trials.

Evaluating Relationships Between Sleep and Next-Day Physical Activity in Young Women

BACKGROUND

To evaluate the relationship between sleep and next-day physical activity (PA) under free-living conditions in women.

METHODS

Sleep and PA were measured objectively for 7 consecutive days by accelerometry in 330 young adult women (aged 17-25 y). A structural equation model was used to evaluate the relationship between the driving factor of sleep (total sleep or morning wake time) and the amount of nonsleep sedentary (SED) and moderate to vigorous physical activity (MVPA) each day.

RESULTS

With sleep duration as the driving factor, the estimates of βSED and βMVPA were -0.415 and -0.093, respectively (P ≤ .05). For every hour slept, a 24.9-minute reduction in SED time and a 5.58-minute reduction in MVPA were observed. With wake time as the driving factor, the estimates of βSED and βMVPA were -0.636 and -0.149, respectively. For every wake time that was 1 hour later, a 38.2-minute decrease in SED and a 8.9-minute decrease in MVPA (P ≤ .05) were observed.

CONCLUSIONS

Women who wake later or who sleep longer tend to get less MVPA throughout the day. Getting up earlier and going to bed earlier may support behaviors that improve PA and lifestyle.

Does bedtime matter among patients with chronic pain? A longitudinal comparison study

Introduction

Chronic pain patients frequently report having sleep disturbances and many tend to stay up during the night and then sleep into the day.

Objectives

This study was designed to compare a heterogeneous group of persons with chronic pain who reported typically going to bed between the hours of 9 pm and midnight with those who go to bed at other hours of the day and night.

Methods

Two hundred seventy-nine participants were divided between those who reported going to bed between the hours of 9 pm and midnight (N = 205) and those who reported having atypical bedtimes (N = 74) based on pre-post questionnaire data and average pain assessments from a smartphone pain application (app).

Results

Those individuals in the atypical bedtime group reported waking up more frequently and getting fewer hours sleep (P < 0.05). These individuals also reported significantly higher pain scores, activity interference, and taking more prescription opioid medication compared with those who had typical bedtimes (P < 0.05). Based on average 3-month daily assessments, those subjects with an atypical bedtime consistently reported more sleep disturbances, pain, activity interference, negative mood, and general worsening conditions over time, and elevated pain catastrophizing, pain-related disability, emotional distress scores, and more prescription medication for pain at 3-month follow-up (P < 0.01).

Conclusion

These results support the importance of providers asking patients with pain about what time they typically go to bed at night to gain a greater understanding of their lifestyle habits. Future studies are needed to further determine the importance of maintaining a typical bedtime among patients with chronic pain.

The Effect of Structured Exercise on Sleep During the Corresponding Night Among Older Women in an Exercise Program

This study investigated the acute effect of exercise on sleep outcomes among healthy older women by comparing days with structured exercise versus days without structured exercise during 4 months of exercise training. Participants (n = 51) in this study had wrist-worn actigraphic sleep data available following at least 3 days with structured exercise and 3 days without structured exercise at mid-intervention and at the end of intervention. The exercise intervention was treadmill walking. Multilevel models were used to examine whether structured exercise impacted sleep outcomes during the corresponding night. Overall, 1,362 nights of data were included in the analyses. In unadjusted and adjusted models, bedtimes were significantly earlier on evenings following an acute bout of structured exercise than on evenings without structured exercise. No other sleep parameters differed between exercise and nonexercise days. Understanding the effects of exercise on sleep in this understudied population may help to improve their overall sleep quality.

Development of the Self-Efficacy for Sleep Hygiene Inventory

BACKGROUND AND PURPOSE

Few studies have examined how self-efficacy is related to sleep behaviors in young adults. The purpose of this study was to develop and test an instrument specifically designed to measure self-efficacy for sleep hygiene in young adults.

METHODS

The Self-Efficacy for Sleep Hygiene Inventory (SESHI) was developed in three phases using principal components analysis. The 30-item scale was pilot tested with a sample of 305 young adults. A second study with a sample of 96 young adults confirmed reliability.

RESULTS

A 24-item three-factor solution: time management, disruptive influences, and sleep influences. Cronbach's alphas were 0.83 (total SESHI), 0.87 (time management), 0.69 (disruptive influences), and 0.73 (sleep influences).

CONCLUSIONS

Initial psychometric testing indicated the SESHI may be a reliable measure of self-efficacy for sleep hygiene in this population.

Validation of the Sleep Regularity Index in Older Adults and Associations with Cardiometabolic Risk

Sleep disturbances, including insufficient sleep duration and circadian misalignment, confer risk for cardiometabolic disease. Less is known about the association between the regularity of sleep/wake schedules and cardiometabolic risk. This study evaluated the external validity of a new metric, the Sleep Regularity Index (SRI), among older adults (n = 1978; mean age 68.7 ± 9.2), as well as relationships between the SRI and cardiometabolic risk using data from the Multi-Ethnic Study of Atherosclerosis (MESA). Results indicated that sleep irregularity was associated with delayed sleep timing, increased daytime sleep and sleepiness, and reduced light exposure, but was independent of sleep duration. Greater sleep irregularity was also correlated with 10-year risk of cardiovascular disease and greater obesity, hypertension, fasting glucose, hemoglobin A1C, and diabetes status. Finally, greater sleep irregularity was associated with increased perceived stress and depression, psychiatric factors integrally tied to cardiometabolic disease. These results suggest that the SRI is a useful measure of sleep regularity in older adults. Additionally, sleep irregularity may represent a target for early identification and prevention of cardiometabolic disease. Future studies may clarify the causal direction of these effects, mechanisms underlying links between sleep irregularity and cardiometabolic risk, and the utility of sleep interventions in reducing cardiometabolic risk.

Association between sleep and overweight/obesity among women of childbearing age in Canada

OBJECTIVES

Tests of the relationship between sleep and overweight/obesity (OW/OB) among women have been inconsistent. Few studies reporting such associations have focused on women of childbearing age. This paper investigates this association among Canadian women of childbearing age.

METHODS

Data were from the Canadian Community Health Survey 2011-2014. The sample consisted of women aged 18-44 years. All variables were self-reported. Sleep duration was dichotomized as insufficient (< 7 h/night) or adequate (≥ 7 h/night). A composite score of sleep quality was used and dichotomized as poor none/little of the time or some/most/all of the time. Height and weight were used to calculate body mass index. Associations between sleep and OW/OB were assessed using logistic regression analyses with survey weights. Three models were computed for sleep duration/quality: model without covariates, model adjusted for demographics (age, ethnicity, level of education, household income, marital status, employment, parity, region, and season), and model adjusted for demographics and variables associated with OW/OB (mood disorder, fruit and vegetable intake, physical activity, smoking, and alcohol).

RESULTS

Total sample consisted of 9749 women of childbearing age. Thirty-eight percent had insufficient sleep duration. Sleep duration was significantly associated with OW/OB in the model with no covariates and discriminated 52.8% of women of childbearing age, but this association was no longer significant in the models adjusted for covariates. Sleep quality was not significantly linked to OW/OB in any of the models.

CONCLUSION

Targeting sleep alone would likely not contribute to lower risk of OW/OB among Canadian women of childbearing age. Additional studies, especially longitudinal ones, are needed to confirm these findings.

Associations Among Sleep, Body Mass Index, Waist Circumference, and Risk of Type 2 Diabetes Among U.S. Childbearing-Age Women: National Health and Nutrition Examination Survey

BACKGROUND

Women of childbearing age (18-44 years) present an important group for understanding sleep, but few studies have focused on this population. No study has investigated the associations among sleep, overweight/obesity, and risk of type 2 diabetes among childbearing-age women in the National Health and Nutrition Examination Survey (NHANES).

METHODS

Data were from NHANES, 2005-2008. The study population consisted of 18-44 year old women. Pregnant women and those diagnosed with sleep disorders were excluded. Sleep duration and quality were self-reported. Body mass index (BMI), waist circumference (WC) measurements, and a 2-hour 75 g oral glucose tolerance test (OGTT) were performed by trained NHANES staff. An unadjusted linear regression analysis; a second adjusted for demographics only (partially adjusted model); and a third adjusted for demographics and variables associated with overweight/obesity and diabetes (fully adjusted model) were computed to assess associations among sleep duration/quality and BMI, WC, and 2-hour OGTT.

RESULTS

Total sample consisted of 2388 childbearing-age women. Only sleep duration was significantly associated with BMI and WC in the unadjusted and partially adjusted models, but was no longer significant in the fully adjusted model. Neither sleep duration nor quality was significantly associated with 2-hour OGTT in any of the models.

CONCLUSIONS

Targeting sleep duration and sleep quality alone would not likely contribute to significantly lower BMI, WC, or risk of type 2 diabetes in US childbearing-age women. Additional studies, especially longitudinal ones using objective measures of sleep, are needed to confirm these findings.

Persistence of social jetlag and sleep disruption in healthy young adults

Sleep disruption has been associated with increased risks for several major chronic diseases that develop over decades. Differences in sleep/wake timing between work and free days can result in the development of social jetlag (SJL), a chronic misalignment between a person's preferred sleep/wake schedule and sleep/wake timing imposed by his/her work schedule. Only a few studies have examined the persistence of SJL or sleep disruption over time. This prospective investigation examined SJL and sleep characteristics over a 2-year period to evaluate whether SJL or poor sleep were chronic conditions during the study period. SJL and sleep measures (total sleep time [TST], sleep onset latency [SOL], wake after sleep onset [WASO]), and sleep efficiency [SE]), were derived from armband monitoring among 390 healthy men and women 21-35 years old. Participants wore the armband for periods of 4-10 days at 6-month intervals during the follow-up period (N = 1431 repeated observations). The consistency of SJL or sleep disruption over time was analyzed using generalized linear mixed models (GLMMs) for repeated measures. Repeated measures latent class analysis (RMLCA) was then used to identify subgroups among the study participants with different sleep trajectories over time. Individuals in each latent group were compared using GLMMs to identify personal characteristics that differed among the latent groups. Minor changes in mean SJL, chronotype, or TST were observed over time, whereas no statistically significant changes in SOL, WASO, or SE were observed during the study period. The RMLCA identified two groups of SJL that remained consistent throughout the study (low SJL, mean ± SE: 0.4 ± 0.04 h, 42% of the study population; and high SJL, 1.4 ± 0.03 h, 58%). Those in the SJL group with higher values tended to be employed and have an evening chronotype. Similarly, two distinct subgroups were observed for SOL, WASO, and SE; one group with a pattern suggesting disrupted sleep over time, and another with a consistently normal sleep pattern. Analyses of TST identified three latent groups with relatively short (5.6 ± 1.0 h, 21%), intermediate (6.5 ± 1.0 h, 44%), and long (7.3 ± 1.0 h, 36%) sleep durations, all with temporally stable, linear trajectories. The results from this study suggest that sleep disturbances among young adults can persist over a 2 year period. Latent groups with poor sleep tended to be male, African American, lower income, and have an evening chronotype relative to those with more normal sleep characteristics. Characterizing the persistence of sleep disruption over time and its contributing factors could be important for understanding the role of poor sleep as a chronic disease risk factor.

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.

Changes in Behaviors and Outcomes Among School-Based Employees in a Wellness Program

OBJECTIVE

To examine the health behavior changes and mental-health and job-related outcomes of school-based employees over 2 years while participating in a worksite wellness program.

METHOD

All participants in this analysis (n = 1,873) were employees of a large public school district in the western United States and voluntarily enrolled in a comprehensive wellness program. Exercise level, fruit and vegetable consumption, restful sleep, smoking, alcohol consumption, self-rated health, mental health-related outcomes (stress, depression, life-satisfaction, and loneliness), and job-related outcomes (job performance, absenteeism, job-related satisfaction) are reported.

RESULTS

There was an increase in days and minutes/week exercised, fruit/vegetable consumption, days per week of restful sleep, and a decrease in alcohol consumption (ps < .037) over 2 years. Among those who reported smoking, the number of days smoked increased after 1 year but then dropped below baseline levels at year 2 (p < .0001). Several mental health-related outcomes improved (ps < .033); however, job performance was slightly lower (↓ 2%), and the other job-related outcomes were unchanged.

CONCLUSION

School employees may benefit from a comprehensive worksite wellness program, particularly to improve health behaviors. However, mental health and job-related outcome results were mixed over 2 years.

Behavioral interventions to promote adequate sleep among women: protocol for a systematic review and meta-analysis

BACKGROUND

Short and poor sleep have been associated with adverse health outcomes in adults, such as overweight/obesity and type 2 diabetes, especially among women. Women therefore represent an important target for interventions aimed at improving sleep and such interventions have been advocated to enhance maternal, fetal, and infant health. This systematic review will assess the efficacy or effectiveness of behavioral interventions aimed at promoting adequate sleep among women. The primary outcomes will be changes in sleep duration and/or sleep quality from baseline to post-intervention and to the last available follow-up measured either through self-reports or objectively. Secondary outcomes will be assessing the behavior change techniques that are responsible for the changes in sleep duration and quality among women.

METHODS

Behavioral interventions that are non-pharmacological and target either sleep directly or sleep hygiene behaviors will be included. Randomized controlled trials, quasi-experimental, and one-group pre-post studies will be included, but treated separately in the analyses, given that a limited number of studies on the topic of sleep is expected. MEDLINE/PubMed, PsycINFO, CINAHL, EMBASE, and Proquest Dissertations and Theses will be investigated. There will be no restriction on the year of publication of the articles, but we will include only the ones written in English or French. Two authors will independently assess articles for eligibility and will extract data using a standardized data extraction form that will have been previously pilot-tested. The quality of the studies will be assessed using the Effective Public Health Practice Project tool for quantitative study designs. The intervention procedures will be classified according to the latest validated taxonomy of behavior change techniques. If there is a sufficient number of studies (k > 5), a meta-analysis of the results will be performed with a random-effect model. If the heterogeneity is high (I ² ≥ 75%), it will be investigated through sensitivity analyses and meta-regression.

DISCUSSION

This review will provide valuable information to those interested in promoting adequate sleep among women and, hopefully, encourage additional research in this important field to promote maternal, fetal, and infant health.

SYSTEMATIC REVIEW REGISTRATION

The study protocol was registered in PROSPERO in October 2016 (CRD42016049538).

Sleep quality and obesity in young subjects: a meta-analysis

OBJECTIVES

To assess the effect of poor sleep quality on Overweight/Obesity (Ow/Ob) in young subjects, and explore if this association is independent of sleep duration.

METHODS

Pubmed, EMBASE, and MEDLINE databases were searched for papers on sleep quality and overweight/obesity, focusing on children, adolescents, and young adults. Studies based on subjects with medical/psychological problems or published in languages other than English were excluded. Quality effects model was used to pool studies for meta-analysis.

RESULTS

Findings from the systematic review suggest a link between poor sleep quality and Ow/Ob in young subjects. Pooled estimate (from 26,553 subjects) suggest a role of inadequate sleep (including both short duration and poor quality) in Ow/Ob (OR: 1.27 95% CI: 1.05-1.53). Sub-group-analyses suggest considerably higher odds of Ow/Ob (OR = 1.46, 95% CI: 1.24-1.72) in young subjects with poor sleep quality (independent of duration).

CONCLUSIONS

Poor sleep quality seems to be associated with Ow/Ob, and some studies indicate this association to be independent of duration. Therefore, considering only sleep duration might not help in disentangling sleep-obesity association. However, this review is mostly composed of cross-sectional studies. Therefore, a causal link or the stability of the sleep quality and Ow/Ob association could not be established.

Reduced Sleep Acutely Influences Sedentary Behavior and Mood But Not Total Energy Intake in Normal-Weight and Obese Women

Using a crossover design, 22 normal-weight and 22 obese women completed two free-living sleep conditions: (a) Normal Sleep: night of ~8 hr time in bed; and (b) Reduced Sleep: night of < 5 hr time in bed). Outcome measures were energy intake, physical activity and sedentary time, and mood. Sleep time was 7.7 ± 0.3 and 4.8 ± 0.2 hrs during the Normal Sleep and Reduced Sleep conditions, respectively (F = 1791.94; p < 0.0001). Energy intake did not differ between groups or as a function of sleep condition (F = 2.46; p = 0.1244). Sedentary time was ~ 30 min higher after the Reduced Sleep condition (F = 4.98; p = 0.0318); other physical activity outcomes were not different by condition (p > 0.05). Total mood score, depression, anger, vigor, fatigue, and confusion were worse after Reduced Sleep (p < 0.05). Reducing sleep acutely and negatively influenced sedentary time and mood in normal-weight and obese women.

Associations of common chronic non-communicable diseases and medical conditions with sleep-related problems in a population-based health examination study

A cross-sectional population-based survey, the National FINRISK 2012 Study, designed to monitor chronic diseases and their risk factors in Finland. A random sample of 10,000 adults aged 25-74 years, and of them, 64% (n=6424) participated the study. Participants subjectively reported the total durations for sleep and naps (n=6238), sleep quality (n=5878), bedtimes and wake-up times separately for working days and weekends yielding the amount of sleep debt (n=5878), and the seasonal variation in sleep duration (n=4852). The participants were asked whether they were diagnosed or treated for common chronic diseases in the past 12 months. Logistic regression models were adopted to analysis and adjusted for a range of covariates as potential confounding factors. Total sleep duration and nap duration prolonged in depression and other mental disorder (p<.001 for all). Seasonal variation in sleep duration was associated with depression (p=.014), hypertension (p=.018) and angina pectoris (p=.024). Participants with gallstones, cardiac insufficiency, depression, or degenerative arthritis had poor sleep quality (odds ratios of 1.6-6.3, p=.001 or less for each). Those with degenerative arthritis had sleep debt less (p<.05) and those with angina pectoris more (p<.05) than individuals without these medical conditions. Depression is significantly associated with sleep problems, albeit no sleep debt. Cardiovascular diseases, degenerative arthritis, and gallstones had significant associations with one or more sleep problems. There is therefore a need for more successful management of sleep problems in chronic diseases to improve the quality of life, to reduce treatment relapses, and to increase health and longevity in a population.

Bedtime Variability and Metabolic Health in Midlife Women: The SWAN Sleep Study

STUDY OBJECTIVES

Circadian misalignment, as seen in shift workers, can disrupt metabolic processes. Associations between sleep timing in nonshift workers and metabolic health are unknown. We examined sleep timing and indices of metabolic health in a community sample of midlife women.

METHODS

Caucasian (n = 161), African American (n = 121) and Chinese (n = 56) non-shift-working women aged 48-58 y who were not taking insulin-related medications, participated in the Study of Women's Health Across the Nation (SWAN) Sleep Study and were subsequently examined approximately 5.39 (standard deviation = 0.71) y later. Daily diary-reported bedtimes were used to calculate four measures of sleep timing: mean bedtime, bedtime variability, bedtime delay and bedtime advance. Body mass index (BMI) and insulin resistance (homeostatic model assessment-insulin resistance, HOMA-IR) were measured at two time points. Linear regressions evaluated whether sleep timing was associated with BMI and HOMA-IR cross-sectionally and prospectively.

RESULTS

In cross-sectional models, greater variability in bedtime and greater bedtime delay were associated with higher HOMA-IR (β = 0.128; P = 0.007, and β = 0.110; P = 0.013, respectively) and greater bedtime advance was associated with higher BMI (β = 0.095; P = 0.047). Prospectively, greater bedtime delay predicted increased HOMA-IR at Time 2 (β = 0.152; P = 0.003). Results were partially explained by shifted sleep timing on weekends.

CONCLUSION

Frequent shifts in sleep timing may be related to metabolic health among non-shift working midlife women.

COMMENTARY

A commentary on this article appears in this issue on page 269.

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

OBJECTIVE

Only a few studies have used objective measurements to investigate the relationship between sleep quality and obesity. These studies showed controversial results.

METHODS

Sleep efficiency was measured by Actiwatch 2 in 132 healthy students (age 23.3 ± 3.7 years, BMI 23.1 ± 4.1 kg/m(2) ) for 12 ± 3 nights, differentiating between work and free days. Physical activity, dietary habits, and autonomic function (heart rate variability, HRV) were analyzed as potential determinants of sleep quality and its relationship with body composition.

RESULTS

Sleep efficiency was 87.0% in women and 84.9% in men (P < 0.05) and was higher at free days when compared to work days in women (P < 0.05). Lower sleep efficiency was associated with a higher fat mass. This was true for sleep efficiency on work days in women [fat mass index (FMI): r = -0.35, P < 0.01] and for free days in men (FMI: r = -0.37, P < 0.05). Poor sleep efficiency was associated with less physical activity (r = 0.29, P < 0.05) and impaired HRV in women (r = 0.60, P < 0.05) and with a higher fat intake in men (r = -0.39, P < 0.05).

CONCLUSIONS

Poor sleep efficiency was associated with higher fat mass. The relationship between sleep quality and fat mass differs between work and free days and may be explained by physical activity and autonomic function in women and dietary habits in men.

The role of sleep in the regulation of body weight

Sleep participates in the regulation of body weight. The amount of sleep and synchronization of the biological clock are both necessary to achieve the energy balance and the secretion of hormones that contribute to weight regulation. In this review, we first reconsider what normal physiological sleep is and what the normative values of sleep are in the general population. Second, we explain how the biological clock regulates the hormones that may be involved in weight control. Third, we provide some recent data on how sleep may be disturbed by sleep disorders or reduced by sleep debt with consequences on weight. Finally, we explore the relationships between sleep debt and obesity.

Association between actigraphic sleep metrics and body composition

PURPOSE

Determine if individuals with poor sleep characteristics (i.e., late sleep onset or wake times, short sleep duration, long sleep latency, low sleep efficiency, high wake after sleep onset) have greater body mass index (BMI = kg/m(2)) or body fat.

METHODS

Data for these cross-sectional analyses were from the Energy Balance Study (University of South Carolina). Participants were between 21 and 35 years of age and had a BMI of 20 to 35 kg/m(2). Body fat percent was measured by dual X-ray absorptiometry. Sleep and physical activity were measured by actigraphy (BodyMedia's SenseWear physical activity armband). General linear models were used to estimate mean BMI and body fat percent by sleep metric categories.

RESULTS

Greater BMI and body fat percent were associated with low sleep efficiency (BMI = 25.5 vs. 24.8 kg/m(2), P < .01; body fat = 27.7% vs. 26.5%, P = .04) and high wake after sleep onset (BMI = 25.6 vs. 25.0 kg/m(2), P = .02; body fat = 28.0% vs. 26.7%, P = .03). Elevated BMI or body fat percent also were observed for later wake times, shorter sleep duration, and longer sleep latency. Sex modified the association between wake times and body composition.

CONCLUSIONS

Understanding the complex relationships between sleep and health outcomes could help reduce chronic disease burden by incorporating sleep components, measured through novel noninvasive techniques (SenseWear armband), into weight loss interventions.