Actigraphy Measured Sleep Indices and Adiposity: The Multi-Ethnic Study of Atherosclerosis (MESA)

Impact of cardiovascular risk factors on associations between state and trait indices of major depression disorder and objectively assessed physical activity, sleep and circadian rhythmicity within a population based cohort

BACKGROUND

Few studies of the association between accelerometry-assessed physical activity with major depressive disorder (MDD) have considered the influence of both the averages and variability of all three domains of the 24 hour activity cycle including sleep, physical activity, and circadian rhythmicity, the physical health correlates of depression, and the extent to which changes in sleep and physical activity reflect current state versus enduring patterns of MDD in people with depression.

METHODS

The sample includes 2307 participants from a population cohort from Lausanne, Switzerland. Average and variability of daily sleep (SL), physical activity (PA), and circadian rhythmicity (CR) were derived from accelerometry.

RESULTS

Cardiovascular risk factors, particularly cigarette smoking and body mass index (BMI), were significantly associated with both the average and variability of sleep, phyiscal activity and circadian rhythmicity, and with MDD. Lower average and less variable physical activity, as well as more variable circadian rhythmicity were associated with remitted MDD, whereas later sleep midpoint and greater variation of sleep duration variability were associated with depressive states.

LIMITATION

The single geographic setting, cross-sectional nature and two-week assessment period may limit the generalizability of these findings.

CONCLUSION

These results demonstrate the importance of considering both the average and variability of accelerometry-derived phenotypes that may distinguish state from trait manifestations of MDD. Further, the confounding influence of smoking, particularly on state manifestations of MDD, should be considered in studies of accelerometer derived phenotypes, particularly sleep characteristics. Interventions for depression should therefore consider modification of health behaviors such as smoking and overweight, as well as stabilizing the 24-hour rest-activity cycle, rather than treatments that focus solely on the average levels of mood, sleep or physical activity alone.

Sleep quality, frailty components and body composition of community-dwelling older adults: An exploratory study

BACKGROUND

Sleep patterns change with the aging process, resulting in an increased risk of sleep disorders. Sleep quality might be associated with body composition and has been associated with frailty. The objective of the present study was to evaluate the association of sleep quality with frailty components and body compositions of community-dwelling elderly individuals.

METHODS

Observational and cross-sectional study conducted with ≥60 years of both sexes. Sleep quality was evaluated by the Pittsburgh Sleep Quality Index (PSQI) and the Epworth Sleepiness Scale (ESS). Self-reports of involuntary weight loss, handgrip strength (HGS), self-reported fatigue by the Geriatric Depression Scale (GDS), gait speed (GS) and levels of physical activity were assessed. Anthropometric measurements of body weight, height, calf circumference (CC) and waist circumference (WC), and body composition was assessed.

RESULTS

A total of 141 participants (82% female; 69.5±6.4 years old) were studied. It was found 60% of poor sleep quality. The prevalence of frailty was 2%, and 38% of the participants were classified as prefrail. Positive moderate correlations between sleep quality and BMI, CC, WC, GS, fat mass, fat mass and depressive symptoms (p<0.05) were found. The logistic regression test revealed that HGS was positively associated with good sleep quality, while fat mass and depressive symptoms were negatively associated.

CONCLUSION

The present study demonstrated a high prevalence of poor sleep quality and a low prevalence of frailty in community-dwelling older adults. Sleep was associated with strength, body composition and depressive symptoms in this population.

Sleep Duration Alters Overfeeding-mediated Reduction in Insulin Sensitivity

CONTEXT

Weight gain and sleep restriction both reduce insulin sensitivity. However, it is not known if sleep duration alters glucose metabolism in response to overfeeding.

OBJECTIVE

To examine the effect of sleep duration on overfeeding-mediated alterations in carbohydrate metabolism and insulin sensitivity.

METHODS

Retrospective exploratory analysis of a longitudinal overfeeding study in healthy participants (n = 28, age: 26.9 ± 5.5 years, body mass index: 25.74 ± 2.45 kg/m2). After providing baseline study measures, participants were overfed 40% above weight maintenance calorie requirements for 8 weeks. Insulin sensitivity was determined by a 2-step hyperinsulinemic-euglycemic clamp. Baseline habitual sleep duration was estimated by accelerometry, and sleep groups were created based on median sleep duration (5.2 hours/night).

RESULTS

Overfeeding led to an average body weight gain of 7.3 ± .4 kg. Habitual sleep duration did not alter overfeeding-mediated body weight gain, fat gain, and fat distribution (all P > .15). Compared to participants with more sleep, fasting insulin (P = .01) and homeostatic model assessment for insulin resistance (P = .02) increased while fasting glucose remained unchanged (P = .68) with overfeeding in participants with shorter sleep duration. Glucose infusion rate during high insulin dose was reduced with overfeeding in participants with short sleep duration but not in participants with more sleep (P < .01).

CONCLUSION

Overfeeding mediated weight gain reduced liver, adipose, and whole-body insulin sensitivity prominently in individuals with short sleep duration but not in individuals with longer sleep duration. This suggests that promoting adequate sleep during short periods of overeating may prevent detrimental effects on glucose metabolism.

Longitudinal assessment of objective sleep and power output in Division I collegiate baseball athletes

OBJECTIVES

Many college athletes experience insufficient sleep due to athletic, academic, and social constraints. While prior studies have observed cross-sectional associations between poor sleep and performance in athletes, few studies have longitudinally assessed performance variations in relation to sleep measures. We investigated whether objectively measured sleep assessments were associated with peak power output improvements during a fall season of Division I collegiate baseball players.

METHODS

Peak power output was assessed weekly for 12weeks in 24 male collegiate baseball players (age: 21±1years). Objective sleep (Oura ring) was assessed over the final 6weeks to determine total sleep time, sleep efficiency, and other assessments of sleep quality, including the proportion of nights in which athletes maintained total sleep time ≥7 hours or sleep efficiency ≥90%. Bivariate correlations between sleep measures and peak power output were performed.

RESULTS

Greater improvements in peak power output throughout the fall season were associated with higher total sleep time (r=0.429, p=.036), higher sleep efficiency (r=0.411, p=.046), and fewer nighttime awakenings (r=-0.495, p=.014). Furthermore, the rate of change in peak power output was associated with the proportion of nights in which athletes maintained total sleep time ≥7 hours (r=0.557, p=.005) or sleep efficiency ≥90% (r=0.509, p=.011).

CONCLUSIONS

These findings support an association between adequate sleep duration, quality, and consistency in training season performance trajectories in college athletes.

DATA AVAILABILITY

Data will be made available upon reasonable request by the corresponding author.

A good night's rest: A contemporary review of sleep and cardiovascular health

Sleep is increasingly recognized as a significant contributor to the development of cardiovascular disease (CVD). Recent American Heart Association guidelines incorporate sleep duration into the "Life's Essential Eight" framework of ideal cardiovascular health. This article will review the evidence relating sleep duration, regularity, and quality with all-cause and cardiovascular mortality, cardiometabolic syndrome, and coronary artery disease in adults. Short sleep duration is strongly associated with cardiovascular mortality, cardiometabolic risk factors, and coronary artery disease. Limited studies also suggest a possible U-shaped association, with long sleep duration also associated with greater cardiovascular risk. Sleep regularity has emerged as a strong and independent risk factor for CVD-related mortality, cardiometabolic syndrome, and subclinical atherosclerosis. Less is known about the impact of sleep quality on CVD, though a number of observational studies suggest a possible association with metabolic syndrome and subclinical atherosclerosis. This review provides an update of the literature on the cardiovascular impact of sleep for the everyday clinician and highlights gaps in knowledge that warrant future research.

Relationship between longer sleep and serum neurofilament light chain in american adults: evidence from the 2013-2014 US national health and nutrition examination survey

BACKGROUND

Sleep disturbance is linked to neurodegenerative diseases and the related brain pathophysiology. Serum neurofilament light chain (NfL) is a reliable biomarker for neurological disorders. This study examined the association between sleep characteristics and serum NfL levels in American adults.

METHODS

In this cross-sectional study, data from the 2013-2014 US National Health and Nutrition Examination Survey were utilized. Participants were categorized into short (≤ 6 h), normal (7-8 h), and long (≥ 9 h) sleep groups based on their self-reported sleep durations. Sleep duration, trouble sleeping, and diagnosed sleep disorders were queried, forming "sleep pattern (healthy, moderate, and poor)." The association between sleep characteristics and serum NfL levels was assessed using multivariate linear regression models. Stratification and sensitivity analyses were conducted to determine the stability of results.

RESULTS

Overall, 1637 participants were included; among them, 48.2% were male and 51.8% were female (mean ± SD, age: 46.9 ± 15.5 years) and 38.8% reported sleeping for ≤ 6 h, 54.4% for 7-8 h, and 6.8% for ≥ 9 h. Participants with longer sleep duration, poor sleep pattern, diagnosed sleep disorders, or trouble sleeping exhibited higher serum NfL levels. A positive correlation was found between extended sleep and elevated serum NfL levels (Adjusted β = 4.82, 95%CI: 2.2, 7.44, P < 0.001), with no significant correlation observed in the short-sleep group or those with poor sleep pattern. Stratified and sensitivity analyses confirmed the robustness of the relationship between longer sleep and elevated serum NfL levels.

CONCLUSIONS

A long sleep duration is associated with higher serum NfL levels than a normal sleep duration in American adults.

An adapted transdiagnostic sleep and circadian intervention for adults with excess weight and suboptimal sleep health: pilot study results

Study Objectives

This single-arm, mixed-methods, pilot study examined the feasibility and preliminary efficacy of an adapted version of the transdiagnostic intervention for sleep and circadian dysfunction (TranS-C) on multidimensional sleep health (MDSH) in a sample of adults with excess weight and suboptimal sleep health.

Methods

Participants received up to eight, weekly, remotely delivered, tailored TranS-C sessions. At pre- and post-intervention, the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and 7 days of Fitbit data were used to evaluate changes in sleep dimensions (regularity, alertness, timing, satisfaction, duration, and efficiency) and the composite MDSH score. Study feasibility examined recruitment, data collection, and intervention engagement (completion of core TranS-C sessions). Acceptability of the intervention was assessed with semi-structured interviews, which were analyzed using thematic analysis.

Results

From 85 referrals, 11 individuals were eligible, and 10 completed the study. All intervention participants completed the measures needed to calculate their composite MDSH score and completed the core intervention sessions. Themes from interviews support the intervention's remote delivery approach, applicability of the information provided, and impact on self-reported health. The intervention resulted in a large improvement in the mean composite MDSH score (Cohen's d = 1.17). Small-to-large effects were also observed for individual sleep health dimensions except for timing.

Conclusions

Adapted TranS-C is acceptable for adults with excess weight and suboptimal sleep health and may be effective at improving short-term MDSH. With changes to recruitment methods, a larger study is feasible. Limitations include the small sample size and the lack of a control condition.

Association of Life's Essential 8 and Simple 7 Scores With Mortality: Comparison With Pooled Cohort Equation

Background

In 2022, the Life's Simple 7 (LS7) score was replaced with the Life's Essential 8 (LE8) score as a tool to measure cardiovascular health. The risk prediction values of LE8 and LS7 scores for mortality have not been compared. Additionally, the risk prediction value of these scores has not been compared with the pooled cohort equations (PCE) in individuals aged 40 to 79 years.

Objectives

This study compared the risk prediction value of the: 1) LE8 and LS7 scores in the overall population; and 2) LE8 score, LS7 score, and PCE in the 40- to 79-year-old age group for all-cause and cardiovascular mortality in a nationally representative US population.

Methods

The LS7 and LE8 scores and the PCE were calculated in the National Health and Nutrition Examination Survey cycles 2007 to 2018. All-cause and cardiovascular mortality were identified by linking the participants to the National Death Index. The C-statistics of the respective weighted Cox models were used to compare the risk prediction value of the standardized scores.

Results

Among 21,721 individuals included, the C-statistics for all-cause mortality were 0.823 (95% CI: 0.803-0.843) and 0.819 (95% CI: 0.799-0.838) in the LE8 and LS7 score-based models, respectively. The C-statistics for cardiovascular mortality were 0.887 (95% CI: 0.857-0.905) for the LE8 score-based model and 0.883 (95% CI: 0.861-0.905) for the LS7 score-based model. Among 12,943 individuals aged 40 to 79 years, the C-statistics for the outcome of all-cause mortality were 0.756 (95% CI: 0.732-0.779), 0.674 (95% CI: 0.646-0.701), and 0.681 (95% CI: 0.656-0.706) for the PCE, LS7 score, and LE8 score-based models, respectively.

Conclusions

The LS7 and LE8 scores had similar risk prediction values for all-cause and cardiovascular mortality. Among 40- to 79-year-old individuals, the PCE had better risk discrimination in the LE8 and LS7 scores in predicting all-cause mortality.

The Emerging Importance of Sleep Regularity on Cardiovascular Health and Cognitive Impairment in Older Adults: A Review of the Literature

The regularity of sleep/wake patterns across multiple days is emerging as an important determinant of health. However, the association between sleep regularity and health outcomes in the aging population is not well understood. The current systematic review identified 22 publications that examined the relationship between sleep regularity and selected health outcomes: cardiovascular risk, cognitive impairment, and mortality. All studies were published after 2010, reflecting a growing research interest in daily sleep regularity. Low sleep regularity was consistently associated with higher cardiovascular risk and elevated risk of all-cause mortality. Results on cognitive impairment are mixed, with inconsistency likely attributed to small sample sizes and differences in sleep regularity assessment. Overall, regularity in sleep carries important information about health and should be included in future studies that collect daily sleep measures. Gaps in literature and methodological shortcomings are discussed.

Study Design and Protocol of the Multisite Pregnancy 24/7 Cohort Study

Hypertensive disorders of pregnancy and other adverse pregnancy outcomes (APOs) are associated with an increased risk of future maternal cardiovascular disease. Physical activity during pregnancy reduces the risk of these APOs, yet few meet physical activity guidelines during pregnancy. Little is known about the role of sedentary behavior or sleep in APOs, a critical gap in knowledge given these behaviors comprise the majority of a 24-hour day. To address this knowledge gap, the Pregnancy 24/7 cohort study (2020-2025) uses 2 devices for 24-hour activity assessment in each trimester of pregnancy to examine associations of sedentary behavior, sleep, and the 24-hour activity cycle (composition of sedentary behavior, physical activity, and sleep) with hypertensive disorders and other APOs. Participants (n = 500) are recruited from the University of Iowa, University of Pittsburgh, and West Virginia University in early pregnancy and followed through delivery. The activPAL3 micro and Actiwatch Spectrum Plus are worn in each trimester for 7 days of 24-hour wear to assess the 24-hour activity cycle. APOs are abstracted from medical charts. This study will provide critical data to fuel future research examining how modifying the 24-hour activity cycle in pregnancy can improve maternal health.

Objectively regular sleep patterns and mortality in a prospective cohort: The Multi-Ethnic Study of Atherosclerosis

Irregular sleep and non-optimal sleep duration separately have been shown to be associated with increased disease and mortality risk. We used data from the prospective cohort Multi-Ethnic Study of Atherosclerosis sleep study (2010-2013) to investigate: do aging adults whose sleep is objectively high in regularity in timing and duration, and of sufficient duration tend to have increased survival compared with those whose sleep is lower in regularity and duration, in a diverse US sample? At baseline, sleep was measured by 7-day wrist actigraphy, concurrent with at-home polysomnography and questionnaires. Objective metrics of sleep regularity and duration from actigraphy were used for statistical clustering using sparse k-means clustering. Two sleep patterns were identified: "regular-optimal" (average duration: 7.0 ± 1.0 hr obtained regularly) and "irregular-insufficient" (duration: 5.8 ± 1.4 hr obtained with twice the irregularity). Using proportional hazard models with multivariate adjustment, we estimated all-cause mortality hazard ratios. Among 1759 participants followed for a median of 7.0 years (Q1-Q3, 6.4-7.4 years), 176 deaths were recorded. The "regular-optimal" group had a 39% lower mortality hazard than did the "irregular-insufficient" sleep group (hazard ratio [95% confidence interval]: 0.61 [0.45, 0.83]) after adjusting for socio-demographics, lifestyle, medical comorbidities and sleep disorders. In conclusion, a "regular-optimal" sleep pattern was significantly associated with a lower hazard of all-cause mortality. The regular-optimal phenotype maps behaviourally to regular bed and wake times, suggesting sleep benefits of adherence to recommended healthy sleep practices, with further potential benefits for longevity.

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.

Sleep Apnea Physiological Burdens and Cardiovascular Morbidity and Mortality

Rationale: Obstructive sleep apnea is characterized by frequent reductions in ventilation, leading to oxygen desaturations and/or arousals. Objectives: In this study, association of hypoxic burden with incident cardiovascular disease (CVD) was examined and compared with that of "ventilatory burden" and "arousal burden." Finally, we assessed the extent to which the ventilatory burden, visceral obesity, and lung function explain variations in hypoxic burden. Methods: Hypoxic, ventilatory, and arousal burdens were measured from baseline polysomnograms in the Multi-Ethnic Study of Atherosclerosis (MESA) and the Osteoporotic Fractures in Men (MrOS) studies. Ventilatory burden was defined as event-specific area under ventilation signal (mean normalized, area under the mean), and arousal burden was defined as the normalized cumulative duration of all arousals. The adjusted hazard ratios for incident CVD and mortality were calculated. Exploratory analyses quantified contributions to hypoxic burden of ventilatory burden, baseline oxygen saturation as measured by pulse oximetry, visceral obesity, and spirometry parameters. Measurements and Main Results: Hypoxic and ventilatory burdens were significantly associated with incident CVD (adjusted hazard ratio [95% confidence interval] per 1 SD increase in hypoxic burden: MESA, 1.45 [1.14, 1.84]; MrOS, 1.13 [1.02, 1.26]; ventilatory burden: MESA, 1.38 [1.11, 1.72]; MrOS, 1.12 [1.01, 1.25]), whereas arousal burden was not. Similar associations with mortality were also observed. Finally, 78% of variation in hypoxic burden was explained by ventilatory burden, whereas other factors explained only <2% of variation. Conclusions: Hypoxic and ventilatory burden predicted CVD morbidity and mortality in two population-based studies. Hypoxic burden is minimally affected by measures of adiposity and captures the risk attributable to ventilatory burden of obstructive sleep apnea rather than a tendency to desaturate.

The interplay between macronutrients and sleep: focus on circadian and homeostatic processes

Sleep disturbances are an emerging risk factor for metabolic diseases, for which the burden is particularly worrying worldwide. The importance of sleep for metabolic health is being increasingly recognized, and not only the amount of sleep plays an important role, but also its quality. In this review, we studied the evidence in the literature on macronutrients and their influence on sleep, focusing on the mechanisms that may lay behind this interaction. In particular, we focused on the effects of macronutrients on circadian and homeostatic processes of sleep in preclinical models, and reviewed the evidence of clinical studies in humans. Given the importance of sleep for health, and the role of circadian biology in healthy sleep, it is important to understand how macronutrients regulate circadian clocks and sleep homeostasis.

Short-term and intermediate-term fine particulate air pollution are synergistically associated with habitual sleep variability in adolescents - A cross-sectional study

BACKGROUND

Both air pollution and poor sleep have been associated with increased risk of cardiovascular diseases. However, the association between air pollution and sleep health, especially among adolescents, is rarely investigated.

METHODS

To investigate the association between fine particulate (PM2.5) air pollution and habitual sleep patterns, we analyzed data obtained from 246 adolescents who participated in the Penn State Child Cohort follow-up examination. We collected their individual-level 24-h (short-term) PM2.5 concentration by using a portable monitor. We estimated their residential-level PM2.5 concentration during the 60-day period prior to the examination (intermediate-term) using a kriging approach. Actigraphy was used to measure participants' sleep durations for seven consecutive nights. Habitual sleep duration (HSD) and sleep variability (HSV) were calculated as the mean and SD of the seven-night sleep duration. Multivariable-adjusted linear regression models were used to assess the association between PM2.5 exposures and HSD/HSV. An interaction between short-term and intermediate-term PM2.5 was created to explore their synergistic associations with HSD/HSV.

RESULTS

Elevated short-term and intermediate-term PM2.5 exposure were significantly (p < 0.05) associated with higher HSV, but not HSD. Specifically, the mean (95% CI) increase in HSV associated with 1 SD higher 24-h (26.3 μg/m3) and 60-day average (2.2 μg/m3) PM2.5 were 14.6 (9.4, 14.8) and 4.9 (0.5, 9.2) minutes, respectively. In addition, there was a synergistic interaction (p = 0.08) between short-term and intermediate-term PM2.5 exposure on HSV, indicative that the association between intermediate-term PM2.5 and HSV became stronger as short-term PM2.5 increases, and vice versa.

CONCLUSION

Short-term individual-level and intermediate-term residential-level PM2.5 exposures are adversely and synergistically associated with increased sleep variability, an indicator of instability of sleep quantity, in adolescents. Through such an association with sleep pattern, PM2.5 air pollution may increase long-term cardiometabolic risks.

The association between sleep duration and detailed measures of obesity: A cross sectional analysis in the ADDITION-PRO study

Background

Sleep duration is associated with BMI and waist circumference. However, less is known about whether sleep duration affects different measurements of obesity differently.

Objective

To investigate the association between sleep duration and different measures of obesity.

Methods

In this cross-sectional analysis 1309, Danish, older adults (55% men) completed at least 3 days of wearing a combined accelerometer and heart rate-monitor for assessing sleep duration (hours/night) within self-reported usual bedtime. Participants underwent anthropometry and ultrasonography to assess BMI, waist circumference, visceral fat, subcutaneous fat, and fat percentage. Linear regression analyses examined the associations between sleep duration and obesity-related outcomes.

Results

Sleep duration was inversely associated with all obesity-related outcomes, except visceral-/subcutaneous-fat-ratio. After multivariate adjustment the magnitude of associations became stronger and statistically significant for all outcomes except visceral-/subcutaneous-fat-ratio, and subcutaneous fat in women. The associations with BMI and waist circumference demonstrated the strongest associations, when comparing standardized regression coefficients.

Conclusions

Shorter sleep duration were associated with higher obesity across all outcomes except visceral-/subcutaneous-fat-ratio. No specifically salient associations with local or central obesity were observed. Results suggest that poor sleep duration and obesity correlate, however, further research is needed to conclude on beneficial effects of sleep duration regarding health and weight loss.

Association between insomnia phenotypes and subclinical myocardial injury: the Multi-Ethnic Study of Atherosclerosis

STUDY OBJECTIVES

To assess whether the association between insomnia and subclinical myocardial injury, as measured by cardiac troponin T (cTnT), differs across insomnia phenotypes.

METHODS

We measured cTnT in 2188 participants in the Multi-Ethnic Study of Atherosclerosis study who had completed sleep questionnaires and undergone unattended polysomnography (PSG) and 7-day actigraphy. Insomnia symptoms were defined as reporting at least one of the following ≥5 nights/week over the past 4 weeks: trouble falling asleep, waking up several times a night, having trouble getting back to sleep after waking up too early, or taking sleeping pills to help falling asleep. Obstructive sleep apnea (OSA) was defined as an apnea-hypopnea index (AHI >15 events/h). Participants were classified into insomnia phenotypes, including comorbid insomnia and OSA (COMISA) and insomnia associated with actigraphy-estimated short sleep (<6 h) or sleep fragmentation.

RESULTS

The mean age was 68.8 (SD 9.2) years, 53.6% were male. In total, 47.8% met threshold levels for insomnia symptoms, and 43.1% had an AHI >15. In adjusted linear regression models COMISA (β 0.08 [standard error (SE) 0.03], p < .01) and insomnia with short sleep duration (β 0.07 [SE 0.03], p < .05) were each associated with higher cTnT compared to a reference group with no insomnia. Insomnia with fragmented sleep (β 0.03 [SE 0.02]) was not associated with higher cTnT (p > .05) in adjusted analyses. OSA was associated with higher cTnT (β 0.09 [SE 0.03], p < .01) in adjusted models.

CONCLUSIONS

COMISA and insomnia with short sleep duration, but not insomnia symptoms alone or fragmented sleep, were associated with increased circulating cTnT in older adults.

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.

Irregular sleep and cardiometabolic risk: Clinical evidence and mechanisms

Sleep regularity is an essential part of the multidimensional sleep health framework. The phenomenon of irregular sleep patterns is widespread in contemporary lifestyles. This review synthesizes clinical evidence to summarize the measures of sleep regularity and discusses the role of different sleep regularity indicators in developing cardiometabolic diseases (coronary heart disease, hypertension, obesity, and diabetes). Existing literature has proposed several measurements to assess sleep regularity, mainly including the standard deviation (SD) of sleep duration and timing, sleep regularity index (SRI), interdaily stability (IS), and social jetlag (SJL). Evidence on associations between sleep variability and cardiometabolic diseases varies depending on the measure used to characterize variability in sleep. Current studies have identified a robust association between SRI and cardiometabolic diseases. In comparison, the association between other metrics of sleep regularity and cardiometabolic diseases was mixed. Meanwhile, the associations of sleep variability with cardiometabolic diseases differ across the population. SD of sleep characteristics or IS may be more consistently associated with HbA1c in patients with diabetes compared with the general population. The association between SJL and hypertension for patients with diabetes was more accordant than in the general population. Interestingly, the age-stratified association between SJL and metabolic factors was observed in the present studies. Furthermore, the relevant literature was reviewed to generalize the potential mechanisms through which irregular sleep increases cardiometabolic risk, including circadian dysfunction, inflammation, autonomic dysfunction, hypothalamic-pituitary-adrenal (HPA) axis disorder, and gut dysbiosis. Health-related practitioners should give more attention to the role of sleep regularity on human cardiometabolic in the future.

[Sleep in patients of a memory clinic : Clinical characteristics of the discrepancy between subjective and objective assessment]

BACKGROUND

Dementia is often accompanied by sleep disturbances, whereby the diagnostics with subjective procedures and objective methods can produce discrepant results. The frequency and clinical characteristics of patients, whose subjective sleep efficiency was unimpaired and was in contrast to an objectively conspicuous sleep efficiency in the sense of an overestimation, were investigated in a memory consultation.

METHODS

On 2 consecutive days, patients underwent guideline-oriented diagnostics for dementia (including mini-mental status examination, MMSE and clinical dementia rating, CDR), supplemented by a subjective (Pittsburgh sleep quality index, PSQI) and objective (overnight actigraphy) sleep assessment. Overestimation of sleep efficiency was defined as a subjective sleep efficiency (SSE) of ≥85% with an actigraphic sleep efficiency (ASE) of <85%.

RESULTS

Of 45 patients (74.4 ± 7.8 years; 26 f/19 m; CDR < 1: n = 16, CDR = 1: n = 28; diagnostic groups according to ICD-10: F0: n = 39, F3: n = 5, Z03.x: n = 1) 10 showed an overestimation of sleep efficiency, who showed a lower MMSE score and a higher proportion of patients with a dementia syndrome (CDR = 1) when compared with the other three groups of SSE and ASE ≥85% (n = 17), SSE and ASE <85% (n = 9) and SSE <85% with ASE ≥85% (n = 9). Binary regression showed that MMSE remained an important predictor for overestimation of sleep efficiency.

CONCLUSION

Cognitive deficits in memory clinic patients appear to contribute to a poorer perception and/or an underreporting of objectively disturbed sleep. This could promote false negative subjective screening results in a diagnostic process in which a comprehensive sleep assessment is not routinely considered.

Associations between sleep variability and cardiometabolic health: A systematic review

This review explored the associations between sleep variability and cardiometabolic health. It was performed following PRISMA guidelines. We identified 63 studies. Forty-one studies examined the association between sleep variability and body composition, with 29 examined body mass index (BMI). Thirteen studies used social jet lag (SJL), n = 30,519, with nine reporting a null association. Eight studies used variability in sleep duration (n = 33,029), with five reporting a correlation with BMI. Fourteen studies (n = 133,403) focused on overweight/obesity; significant associations with sleep variability were found in 11 (n = 120,168). Sleep variability was associated with weight gain (seven studies; n = 79,522). Twenty-three studies examined glucose outcomes. The association with hemoglobin A1c (16 studies, n = 11,755) differed depending on populations, while associations with diabetes or glucose were mixed, and none were seen with insulin resistance (five studies; n = 6416). Sixteen studies examined cardiovascular-related outcomes, with inconsistent results. Overall significant associations were found in five studies focusing on metabolic syndrome (n = 7413). In summary, sleep variability was likely associated with obesity, weight gain, and metabolic syndrome. It might be associated with hemoglobin A1c in people with type 1 diabetes. The associations with other outcomes were mixed. This review highlighted the possible association between sleep variability and cardiometabolic health.

How much does sleep vary from night-to-night? A quantitative summary of intraindividual variability in sleep by age, gender, and racial/ethnic identity across eight-pooled datasets

Habitual sleep duration and efficiency vary widely by age, gender, and racial/ethnic identity. Despite growing research on the importance of night-to-night, intraindividual variability (IIV) in sleep, few studies have examined demographic differences in sleep IIV. The present study describes typical sleep IIV overall and by demographics among healthy sleepers. Eight datasets of healthy sleepers (N = 2,404; 26,121 total days of sleep data) were synthesised to examine age, gender, and racial/ethnic identity differences in sleep IIV measured via diaries, actigraphy, and electroencephalography (EEG). Sleep IIV estimates included the intraindividual standard deviation (iSD), root mean square of successive differences (RMSSD), coefficient of variation (CV), and a validated Bayesian Variability Model (BVM). There was substantial IIV in sleep across measurement types (diary, actigraphy, EEG) for both sleep duration (iSD: 85.80 [diary], 77.41 [actigraphy], 67.04 [EEG] minutes; RMSSD: 118.91, 108.89, 91.93 minutes; CV: 19.19%, 19.11%, 18.57%; BVM: 60.60, 58.20, 48.60 minutes) and sleep efficiency (iSD: 5.18% [diary], 5.22% [actigraphy], 6.46% [EEG]; RMSSD: 7.01%, 7.08%, 8.44%; CV: 5.80%, 6.27%, 8.14%; BVM: 3.40%, 3.58%, 4.16%). Younger adults had more diary and actigraphy sleep duration IIV. Gender differences were inconsistent. White and non-Hispanic/Latinx adults had less IIV in sleep duration and efficiency compared to racial/ethnic minority groups. Even among healthy sleepers, sleep varies widely from night-to-night. Like mean sleep, there also may be disparities in IIV in sleep by demographic characteristics. Study results help characterise normative values of sleep IIV in healthy sleepers.

Sleep and Circadian Disturbance in Cardiovascular Risk

PURPOSE OF REVIEW

We discuss the relationship between sleep and circadian factors with cardiovascular disease (CVD) risk, including physiologic, behavioral, and psychological mechanisms along this pathway.

RECENT FINDINGS

The relationship between short and long sleep duration, as well as insomnia, with CVD risk is well-established. Recent work has highlighted how other sleep factors, such as sleep regularity (i.e., consistency of sleep timing), multidimensional sleep health, and circadian factors like chronotype and social jetlag, relate to CVD risk. Sleep-focused interventions (e.g., cognitive behavioral therapy for insomnia and sleep extension) may be effective to reduce CVD risk and disease burden. Sleep is increasingly recognized as an integral component of cardiovascular health. This was underscored by the recent inclusion of sleep duration as a health behavior in the American Heart Association's Life's Essential 8 for defining optimal cardiovascular health.

Effect of sleep disturbance on biomarkers related to the development of adverse health outcomes: A systematic review of the human literature

Literature suggests that unrestricted and undisturbed sleep is vital for basic human function and performance; however, it is unclear as to what amount of sleep disturbance leads to dysregulation in biomarkers, which may underscore the development of adverse health effects. This systematic review aims to identify the amount of sleep disturbance that contributes to biomarker changes as a potential precursor to the development of adverse health effects. English-language comparative studies available in PubMed, Cochrane Central, EMBASE, and CINAHL databases from 1 January 1980 to 31 July 2021 were searched. Where possible, random-effects meta-analyses were used to examine the effect of sleep disturbances on adverse health effects. The risk of bias of individual studies was assessed using the Cochrane Risk of Bias Tool and the Risk of Bias of Nonrandomised Studies - of Exposures instruments and the certainty of the body of evidence for each outcome was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach. The search identified 92 primary studies reporting on blood pressure, hypertension, heart rate, cardiac arrhythmia, cardiac output, waist circumference, cortisol, adrenaline, noradrenaline, immune system markers, glucose, insulin, cholesterol, and triglyceride levels. Although some meta-analyses suggested there may be an association between sleep disturbances and certain outcomes, the certainty in the evidence was very low due to concerns with risk of bias, inconsistency across exposures, populations, and imprecision in the estimates of effects. Further research is needed to explore the point at which types, levels and duration of sleep disturbances may begin to increase the risk of developing adverse health outcomes to inform and tailor health interventions.

Redefining Cardiovascular Health to Include Sleep: Prospective Associations With Cardiovascular Disease in the MESA Sleep Study

Background Although sufficient and healthy sleep is inversely associated with cardiovascular disease (CVD) and its risk factors, the American Heart Association's Life's Simple 7 (LS7), as a measure of cardiovascular health (CVH), did not include sleep. We evaluated an expanded measure of CVH that includes sleep as an eighth metric in relation to CVD risk. Methods and Results The analytic sample consisted of MESA (Multi-Ethnic Study of Atherosclerosis) Sleep Study participants who had complete data on sleep characteristics from overnight polysomnography, 7-day wrist actigraphy, validated questionnaires, and the outcome. We computed the LS7 score and 4 iterations of a new CVH score: score 1 included sleep duration, score 2 included sleep characteristics linked to CVD in the literature (sleep duration, insomnia, daytime sleepiness, and obstructive sleep apnea), scores 3 and 4 included sleep characteristics associated with CVD in MESA (score 3: sleep duration and efficiency, daytime sleepiness, and obstructive sleep apnea; score 4: score 3+sleep regularity). Multivariable-adjusted logistic and Cox proportional hazards models evaluated associations of the LS7 and CVH scores 1 to 4 with CVD prevalence and incidence. Among 1920 participants (mean age: 69±9 years; 54% female), there were 95 prevalent CVD events and 93 incident cases (mean follow-up, 4.4 years). Those in the highest versus lowest tertile of the LS7 score and CVH scores 1 to 4 had up to 80% lower odds of prevalent CVD. The LS7 score was not significantly associated with CVD incidence (hazard ratio, 0.62 [95% CI, 0.37-1.04]). Those in the highest versus lowest tertile of CVH score 1, which included sleep duration, and CVH score 4, which included multidimensional sleep health, had 43% and 47% lower incident CVD risk (hazard ratio, 0.57 [95% CI, 0.33-0.97]; and hazard ratio, 0.53 [95% CI, 0.32-0.89]), respectively. Conclusions CVH scores that include sleep health predicted CVD risk in older US adults. The incorporation of sleep as a CVH metric, akin to other health behaviors, may enhance CVD primordial and primary prevention efforts. Findings warrant confirmation in larger cohorts over longer follow-up.

Association Between Nocturnal Sleep Duration and Obesity Indicators Among People with Type 2 Diabetes: A Cross-Sectional Study in Ningbo, China

AIM

The study aimed to investigate the association between the nocturnal sleep duration and five obesity indicators, namely, visceral fat area (VFA), subcutaneous fat area (SFA), bodyweight, body mass index (BMI) and waist circumference (WC), among people with type 2 diabetes mellitus (T2DM) in Ningbo, China.

METHODS

A cross-sectional study was conducted using the National Metabolic Management Centre (MMC) - Ningbo First Hospital data from 1st March 2018 to 28th February 2021. Adults with T2DM were included in the study. Simple and multiple (adjusted for sociodemographic and lifestyle factors and health conditions) linear regression analyses were performed to identify the associations.

RESULTS

In terms of VFA, SFA, bodyweight, BMI and WC, the eligibility criteria were satisfied by 2771, 2771, 2863, 2863 and 2862 patients, respectively. In the unadjusted model, the shorter nocturnal sleep duration was associated with higher VFA, SFA, bodyweight, BMI and WC. In other words, an hour increase in the nocturnal sleep duration was associated with a decrease of 2.07 cm2 in VFA (regression coefficient = -2.07; 95% CI = -3.25 to -0.88), 2.67 cm2 in SFA (-2.67; -4.55 to -0.78); 0.82 kg in bodyweight (-0.82; -1.2 to -0.43), 0.2 kg/m2 in BMI (-0.2; -0.31 to -0.09) and 0.46 cm in WC (-0.46; -0.76 to -0.16). In the adjusted models, the shorter nocturnal sleep duration was still found to be associated with higher VFA, SFA, bodyweight, BMI and WC (except SFA and WC in models where we further adjusted for health conditions).

CONCLUSION

The nocturnal sleep duration among people with T2DM in Ningbo, China is negatively associated with visceral and general obesity indicators (VFA, bodyweight and BMI). Thus, there is a need for appropriate interventions to address the issue of sleep deprivation.

Effects of Experimental Sleep Restriction on Energy Intake, Energy Expenditure, and Visceral Obesity

BACKGROUND

Although the consequences of sleep deficiency for obesity risk are increasingly apparent, experimental evidence is limited and there are no studies on body fat distribution.

OBJECTIVES

The purpose of this study was to investigate the effects of experimentally-induced sleep curtailment in the setting of free access to food on energy intake, energy expenditure, and regional body composition.

METHODS

Twelve healthy, nonobese individuals (9 males, age range 19 to 39 years) completed a randomized, controlled, crossover, 21-day inpatient study comprising 4 days of acclimation, 14 days of experimental sleep restriction (4 hour sleep opportunity) or control sleep (9 hour sleep opportunity), and a 3-day recovery segment. Repeated measures of energy intake, energy expenditure, body weight, body composition, fat distribution and circulating biomarkers were acquired.

RESULTS

With sleep restriction vs control, participants consumed more calories (P = 0.015), increasing protein (P = 0.050) and fat intake (P = 0.046). Energy expenditure was unchanged (all P > 0.16). Participants gained significantly more weight when exposed to experimental sleep restriction than during control sleep (P = 0.008). While changes in total body fat did not differ between conditions (P = 0.710), total abdominal fat increased only during sleep restriction (P = 0.011), with significant increases evident in both subcutaneous and visceral abdominal fat depots (P = 0.047 and P = 0.042, respectively).

CONCLUSIONS

Sleep restriction combined with ad libitum food promotes excess energy intake without varying energy expenditure. Weight gain and particularly central accumulation of fat indicate that sleep loss predisposes to abdominal visceral obesity. (Sleep Restriction and Obesity; NCT01580761).

Handling missing data in rest-activity time series measured by actimetry

A handling procedure of off-wrist episodes in actimetry time series of motor activity is presented using two records (regular vs. irregular sleep-wake cycle and daytime activity) of 14 consecutive days sampled in 1-minute epochs. We generated single missing value (NA) intervals of 1 h, 2 h, 4 h, 6 h, 12 h, and 24 h as well as random NA episodes following probabilistic rules to simulate real-life off-wrist episodes. Then, we replaced these episodes with "zeroes" (i.e., the default of immobility records), mean or median of the remaining 13 days corresponding to the missing bins. Single missing episodes of up to 12 h resulted in less than 5% variation from the original values. The irregular series showed higher variability in acrophase, MESOR, L5, M10 and RA compared to the regular series. Random missing allocation simulating real-life off-wrist episodes resulted in significant changes in most parameters, and the imputation of zeroes significantly increased the variance; however, replacing NA with mean or median resulted in patterns similar to those of NA. We recommend replacing 'zeroes' with NA whenever possible, given the risk of inflating invariance using zeroes. If the parameters cannot be computed in the presence of NA, we recommend using the weekly mean of corresponding timepoints.

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.

Consistency where it counts: Sleep regularity is associated with circulating white blood cell count in young adults

Background

Sleep irregularity is predictive of poor health outcomes, and particularly those of cardiometabolic origins. The immune system is implicated in the pathogenesis of cardiometabolic diseases, however the relation between sleep regularity and immune cell profile is unclear.

Methods and results

Forty-two healthy young adults (20 ​± ​2 years) completed 14 days of 24-h wrist actigraphy followed by a morning blood sample to evaluate circulating white blood cells (WBC) and subtypes (neutrophils, lymphocytes, monocytes). Sleep regularity was operationalized as the standard deviation (SD) of nightly sleep duration and SD of sleep onset time. Every 60-min increase in sleep duration SD was associated with an estimated 2.7 ​± ​0.60 x10³ ​cells/μL (p<0.001) increase in total WBC count, while every 60-min increase in sleep onset SD was associated with an estimated 2.4 ​± ​0.60 x10³ ​cells/μL (p<0.001) increase in WBCs. Sleep duration SD was also associated with lymphocyte count (11.5 ​± ​3.8 ​cells/μL per 1-min increase, p<0.01), while sleep onset SD was associated with neutrophil (34.7 ​± ​9.8 ​cells/μL per 1-min increase, p<0.01) and monocyte counts (3.0 ​± ​0.9 ​cells/μL per 1-min increase, p<0.01). Sleep regularity metrics remained significantly associated with WBCs in a series of regressions which adjusted for sex, body mass index, resting blood pressure, mean sleep duration, physical activity, dietary sodium, and alcohol consumption.

Conclusions

Unfavorable associations between irregular sleep patterns and circulating immune cells are apparent in young adulthood. These findings contribute to the growing body of evidence suggesting that consistent sleep schedules are an important dimension of sleep and circadian health and may reduce excess chronic disease risk.

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Young adults with irregular sleep patterns have higher total white blood cell count.

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Sleep irregularity is also associated with neutrophils, lymphocytes, and monocytes.

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Associations remain significant after adjusting for several key confounders.

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Consistent sleep patterns may assist in preventing inflammatory-mediated diseases.

Sleep Duration and Waking Activities in Relation to the National Sleep Foundation's Recommendations: An Analysis of US Population Sleep Patterns from 2015 to 2017

The objective was to investigate the association between time spent on waking activities and nonaligned sleep duration in a representative sample of the US population. We analysed time use data from the American Time Use Survey (ATUS), 2015-2017 (N = 31,621). National Sleep Foundation (NSF) age-specific sleep recommendations were used to define recommended (aligned) sleep duration. The balanced, repeated, replicate variance estimation method was applied to the ATUS data to calculate weighted estimates. Less than half of the US population had a sleep duration that mapped onto the NSF recommendations, and alignment was higher on weekdays (45%) than at weekends (33%). The proportion sleeping longer than the recommended duration was higher than those sleeping shorter on both weekdays and weekends (p < 0.001). Time spent on work, personal care, socialising, travel, TV watching, education, and total screen time was associated with nonalignment to the sleep recommendations. In comparison to the appropriate recommended sleep group, those with a too-short sleep duration spent more time on work, travel, socialising, relaxing, and leisure. By contrast, those who slept too long spent relatively less time on each of these activities. The findings indicate that sleep duration among the US population does not map onto the NSF sleep recommendations, mostly because of a higher proportion of long sleepers compared to short sleepers. More time spent on work, travel, and socialising and relaxing activities is strongly associated with an increased risk of nonalignment to NSF sleep duration recommendations.

Sleep duration regularity, but not sleep duration, is associated with microvascular function in college students

STUDY OBJECTIVES

Vascular dysfunction is a hypothesized mechanism linking poor sleep habits to an increased incidence of cardiovascular diseases (CVDs). However, the vascular profile associated with free-living sleep duration and sleep regularity has not been well elucidated, particularly in young adults. Thus, this study aimed to evaluate the associations between mean sleep duration, regularity in sleep duration, and peripheral vascular function in young adult college students.

METHODS

Fifty-one healthy undergraduate students (20 ± 1 years) completed 14 days of 24-hour wrist actigraphy and subsequent vascular assessments. Macrovascular function was measured using brachial artery flow-mediated dilation (FMD) while microvascular function was measured via passive leg movement (PLM).

RESULTS

Mean sleep duration was unrelated to FMD and PLM. Conversely, more irregular sleep duration (14-day sleep duration standard deviation [SD]) was unfavorably associated with all three measures of PLM-induced hyperemia (peak leg blood flow [LBF], p = 0.01; change in LBF from baseline to peak, p < 0.01; LBF area under the curve, p < 0.01), and remained significant in regression models which adjusted for sex, body mass index, blood pressure, physical activity, alcohol and caffeine consumption, and sleep duration (all p < 0.05). When using a median split to dichotomize "low" and "high" sleep duration SD groups, those demonstrating high variability in sleep duration exhibited ~45% lower PLM responses compared with those demonstrating low variability.

CONCLUSIONS

Irregular sleep duration is associated with poorer microvascular function as early as young adulthood. These findings support the growing body of evidence that irregular sleep patterns may be an independent and modifiable risk factor for CVD.

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.

Obstructive sleep apnea is associated with lower adiponectin and higher cholesterol levels independently of traditional factors and other sleep disorders in middle-aged adults: the ELSA-Brasil cohort

PURPOSE

Obstructive sleep apnea (OSA) may contribute to metabolic and inflammatory deregulation but previous studies failed to consider sleep duration, sleep fragmentation, insomnia, and daytime sleepiness as potential confounders.

METHODS

Consecutive non-diabetic middle-aged participants from the ELSA-Brasil cohort were invited to perform a clinical evaluation, home sleep study for 1 night, and wrist actigraphy for 7 days. OSA was defined by an apnea-hypopnea index ≥ 15 events/h. Participants were stratified according to the presence of OSA measuring the following markers: fasting glucose, glucose tolerance test, homeostatic model assessment of insulin resistance (HOMA-IR) index, fasting insulin, insulin after 2 h of glucose load, glycated hemoglobin, total cholesterol and their fractions, triglycerides, C-reactive protein, TNF-alpha, interleukin-6, interleukin-10, leptin, adiponectin, E-selectin, ADMA, MCP-1, TGF, apolipoprotein B, fibrinogen, and lipoprotein(a). Differences between groups were identified by chi-square test and ANOVA.

RESULTS

We studied 708 participants (mean age: 46 ± 5 years, men: 44%, BMI 26.1 ± 4.1 kg/m²). Compared to no OSA, participants with OSA presented higher levels while fasting and after 2 h glucose load of insulin, HOMA-IR, cholesterol, triglycerides, and C-reactive protein (all p < 0.001). After linear regression analysis adjusting for traditional risk factors plus sleep duration, fragmentation, insomnia, and daytime sleepiness, OSA was negatively associated with adiponectin (β = - 0.271 CI 95% - 0.456 - 0.085) and positively associated with cholesterol (β = 9.707 CI 95% 2.737 16.678). Sex-stratification revealed that these associations were significant for men but not women.

CONCLUSIONS

In non-diabetic middle-age adults, men with OSA presented with lower adiponectin and higher cholesterol levels independently of sleep duration, sleep fragmentation, insomnia, and daytime sleepiness.

Sleep Regularity and Cardiometabolic Heath: Is Variability in Sleep Patterns a Risk Factor for Excess Adiposity and Glycemic Dysregulation?

PURPOSE OF REVIEW

Night-to-night variability in sleep patterns leads to circadian disruption and, consequently, could increase cardiometabolic risk. The purpose of this review is to summarize findings from studies published between 2015 and 2020 examining various measures of night-to-night variability in sleep in relation to metabolic syndrome (MetS), type 2 diabetes (T2D), and their risk factors. We illustrate a potential causal pathway between irregular sleep patterns and T2D, highlighting knowledge gaps along the way.

RECENT FINDINGS

Across different measures of sleep variability, irregular sleep patterns were associated with poorer cardiometabolic outcomes. Higher standard deviations (SD) across nights of sleep duration and onset or midpoint of sleep were associated with increased odds of having MetS and clusters of metabolic abnormalities as well as greater adiposity and poorer glycemic control. Conversely, greater regularity of rest-activity patterns related to lower risk for T2D. Social jetlag was associated with glycemic dysregulation, adiposity, T2D, and MetS. These associations are often observed in both metabolically healthy and unhealthy individuals; both higher SD of sleep duration and social jetlag relate to poorer glucose regulation in individuals with diabetes. There is consistent evidence of associations of sleep variability with increased risk for adiposity, glucose dysregulation, T2D, and MetS. Although experimental evidence is needed to determine causation, there is support to recommend stabilizing sleep patterns for cardiometabolic risk prevention.

Multidimensional sleep health is not cross-sectionally or longitudinally associated with adiposity in the Study of Women's Health Across the Nation (SWAN)

OBJECTIVES

The association between sleep and adiposity (indexed by body mass index or waist-to-hip ratio) has typically been evaluated using a single dimension of self-reported sleep. However, other dimensions and behavioral measures of sleep may also be associated with adiposity. This study evaluated whether multidimensional sleep health calculated from actigraphy and self-report was longitudinally associated with adiposity in a sample of midlife women who have a high prevalence of sleep disturbances and adiposity.

DESIGN

Longitudinal study with 11-14 years of follow-up time between the sleep health assessment and body mass index / waist-to-hip ratio measurements.

PARTICIPANTS

Two hundred and twenty-one midlife women enrolled in the Study of Women's Health Across the Nation Sleep Study.

MEASUREMENTS

Multidimensional sleep health was quantified using actigraphy (M[SD] = 29.1[7.2] nights) measures of sleep efficiency, midpoint, duration, regularity, and self-report measures of alertness and satisfaction. Each component was dichotomized and summed; higher values indicated better sleep health. Height, body weight, and waist and hip circumference were measured at the sleep study and at follow-up. Linear regression models were used to assess associations between sleep health and adiposity, adjusting for demographic and menopausal covariates.

RESULTS

There was no substantial within-person change in adiposity over time. Better sleep health was cross-sectionally and longitudinally associated with lower adiposity in unadjusted, but not in adjusted, models. Individual sleep health components were not associated with adiposity after adjustment.

CONCLUSION

We did not observe cross-sectional or longitudinal associations between multidimensional sleep health and adiposity. The sleep-adiposity link may be weaker in midlife adults than in other age groups.

High sleep variability predicts a blunted weight loss response and short sleep duration a reduced decrease in waist circumference in the PREDIMED-Plus Trial

BACKGROUND

Whether short sleep duration or high sleep variability may predict less weight loss and reduction in measures of adiposity in response to lifestyle interventions is unknown. The aim of this study was to compare the 12-month changes in weight and adiposity measures between those participants with short or adequate sleep duration and those with low or high sleep variability (intra-subject standard deviation of the sleep duration) in PREvención con DIeta MEDiterránea (PREDIMED)-Plus, a primary prevention trial based on lifestyle intervention programs.

METHODS

Prospective analysis of 1986 community-dwelling subjects (mean age 65 years, 47% females) with overweight/obesity and metabolic syndrome from the PREDIMED-Plus trial was conducted. Accelerometry-derived sleep duration and sleep variability and changes in average weight, body mass index (BMI), and waist circumference (WC) attained after 12-month interventions were analyzed.

RESULTS

The adjusted difference in 12-month changes in weight and BMI in participants in the third tertile of sleep variability was 0.5 kg (95% CI 0.1 to 0.9; p = 0.021) and 0.2 kg/m2 (0.04 to 0.4; p = 0.015), respectively, as compared with participants in the first tertile. The adjusted difference in 12-month changes from baseline in WC was -0.8 cm (-1.5 to -0.01; p = 0.048) in participants sleeping <6 h, compared with those sleeping between 7 and 9 h.

CONCLUSIONS

Our findings suggest that the less variability in sleep duration or an adequate sleep duration the greater the success of the lifestyle interventions in adiposity.

Circulating metabolites associated with objectively measured sleep duration and sleep variability in overweight/obese participants: a metabolomics approach within the SATIN study

STUDY OBJECTIVES

To investigate the associations of circulating metabolites with sleep duration and sleep variability. We also assessed the ability of metabolites to discriminate between sleep duration and sleep variability categories.

METHODS

Cross-sectional analyses were performed on baseline data from 205 participants with overweight/obesity in the "Satiety Innovation" (SATIN) study. A targeted metabolite profiling (n = 159 metabolites) approach was applied using three different platforms (nuclear magnetic resonance, liquid chromatography coupled to mass spectrometry, and gas chromatography coupled to mass spectrometry). Associations between circulating metabolite concentrations and accelerometer-derived sleep duration and variability in sleep duration were assessed using elastic-net regression analysis. Ten-fold cross-validation was used to estimate the discriminative accuracy of metabolites for sleep duration and sleep variability categories.

RESULTS

A metabolite profile, including acyl-carnitines (C11:0/C5:1-DC/iso-C11:0, 2-M-C4:1/3-M-C4:1, C4:0), sphingomyelins (42:1, 33:1), glycerol, stearic acid, 2- and 3- hydroxyl-butyric acid, docosahexaenoic acid, serotonin, and phosphatidylcholine (34:2), was significantly associated with high sleep duration (4th plus 5th quintile). Ten metabolites, including acyl-carnitines (C18:1, C7:0, C6-OH), phosphatidylcholine (40:6, 37:4, 42:5), lyso-phosphatidylcholine (20:1), sucrose, glutamic acid, and triacylglycerol (52:4), were significantly associated with high sleep variability (4th plus 5th quintile). The area under the curve was 0.69 (95% CI: 0.62-0.75) and 0.63 (95% CI: 0.53-0.72) in the multimetabolite score for high sleep duration and sleep variability, respectively. The variance in sleep duration explained by metabolites was 7%. No metabolites were selected for prediction of sleep variability (continuous).

CONCLUSIONS

A small set of metabolites within distinct biochemical pathways were associated with high sleep duration and sleep variability. These metabolites appeared to moderately discriminate sleep duration and sleep variability categories.

Sleep Patterns and Obesity: Hispanic Community Health Study/Study of Latinos Sueño Ancillar Study

BACKGROUND

The relationship of poor sleep patterns to the increased risk of obesity has been reported, but the results are variable. This study evaluated the association between objectively measured sleep patterns and obesity in a representative adult population of Hispanic/Latino subjects living in the United States.

METHODS

This cross-sectional study was an analysis of a multicenter, community-based cohort of 2,156 participants aged 18 to 64 years from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Recruitment was conducted in San Diego, California; Chicago, Illinois; Bronx, New York; and Miami, Florida. Models were controlled for age, sex, ethnic background, site, income, education, and apnea-hypopnea index. Seven days of wrist actigraphy data were collected. Obesity was defined as BMI ≥ 30 kg/m², and abdominal obesity was defined as waist circumference ≥ 88 cm in women and ≥ 102 cm in men. Napping was defined as more than one 15-min nap per week.

RESULTS

An inverse linear relationship was found between sleep duration and prevalence of obesity (P linear trend ≤ 0.01). A reduction of 1 h sleep increased obesity prevalence by 4.1% (95% CI, 1.6-6.6; P = .002) and abdominal obesity prevalence by 3.6% (95% CI, 1.1-6.1; P = .007). Daytime napping increased obesity prevalence by 10.4% (95% CI, 3.5-17.3; P = .004) and abdominal obesity prevalence by 7.1% (95% CI, 1.0-13.2; P = .02).

CONCLUSIONS

In a population of young to older adult Hispanic/Latino subjects, we found an inverse linear association between sleep duration and the prevalence of obesity. Daytime napping was strongly associated with greater adiposity. Interventional and longitudinal studies are needed to better understand how abnormal sleep patterns contribute to the obesity epidemic.

Obesity

The role of internists in evaluating obesity is to assess the burden of weight-related disease, mitigate secondary causes of weight gain (medications, sleep deprivation), and solicit patient motivation for weight loss. Internists should assess these factors and emphasize the importance of weight loss for the individual patient. All patients wishing to lose weight should be encouraged to monitor their diet and physical activity and should be referred to high-intensity behavioral programs. Some patients with obesity may also benefit from pharmacotherapy or bariatric surgery.

Prevalence of sleep disturbances: Sleep disordered breathing, short sleep duration, and non-restorative sleep

Recently, interest in sleep disturbances, such as sleep disordered breathing (SDB), short sleep duration, and non-restorative sleep (NRS), has been increasing. The potentially large public health implications of sleep disturbances indicate a need to determine their prevalence in a general population. This review describes the characteristics of population-based sleep cohorts from past to present. Unavoidable methodological and baseline characteristic heterogeneity was found between studies. The prevalence of SDB (apnea hypopnea index (AHI), respiratory disturbance index (RDI), or oxygen desaturation index (ODI) ≥5/h) was 24.0-83.8% in men and 9.0-76.6% in women, and that of moderate-to-severe SDB (AHI, RDI, or ODI ≥15/h) was 7.2-67.2% in men and 4.0-50.9% in women. Additionally, the prevalence of SDB in post-menopausal women was 3-6 times higher than in pre-menopausal women. The prevalence of subjective short sleep duration (<6 h) was 7.5-9.6%, while that of objective short sleep duration (<6 h) was 22.1-53.3%. The prevalence of NRS was 19.2-31.0% in men and 26.3-42.1% in women, as determined from studies using a yes-no questionnaire, while a multi-national survey using a telephone-based expert system showed a wide range of prevalence between countries, from 2.4% to 16.1%. An association between SDB, short sleep duration, and NRS has recently been suggested. To gain a better understanding of the burden of sleep disturbances, a consensus on the definition of several sleep disturbances is needed, as methodological heterogeneity exists, including SDB scoring rules, subjective versus objective data collection for short sleep duration, and the definition of NRS itself.

Assessing potential shared genetic aetiology between body mass index and sleep duration in 142,209 individuals

Observational studies find an association between increased body mass index (BMI) and short self-reported sleep duration in adults. However, the underlying biological mechanisms that underpin these associations are unclear. Recent findings from the UK Biobank suggest a weak genetic correlation between BMI and self-reported sleep duration. However, the potential shared genetic aetiology between these traits has not been examined using a comprehensive approach. To investigate this, we created a polygenic risk score (PRS) of BMI and examined its association with self-reported sleep duration in a combination of individual participant data and summary-level data, with a total sample size of 142,209 individuals. Although we observed a nonsignificant genetic correlation between BMI and sleep duration, using LD score regression (rg  = -0.067 [SE = 0.039], P = 0.092) we found that a PRS of BMI is associated with a decrease in sleep duration (unstandardized coefficient = -1.75 min [SE = 0.67], P = 6.13 × 10-7 ), but explained only 0.02% of the variance in sleep duration. Our findings suggest that BMI and self-reported sleep duration possess a small amount of shared genetic aetiology and other mechanisms must underpin these associations.

Association between actigraphy-based sleep duration variability and cardiovascular risk factors - Results of a population-based study

BACKGROUND

Although a few studies suggest an adverse effect of sleep duration variability on cardiovascular risk factor, others did not and this association remains controversial. Moreover, most studies were non-representative of the general population, used different sleep duration variability measures, and relied on self-reported sleep duration. We aimed to assess the association between different, actigraphy-based sleep duration variability measures and cardiovascular risk factors in a population-based sample.

METHODS

In a middle-aged population-based cohort, 2598 subjects had data on sleep duration variability measured by actigraph over 14 days. Multivariable logistic regressions were performed to assess the relationship between different sleep duration variability measures [ie, night-to-night variability (NNV), range between shortest and longest sleep duration (RSL), range between average weekday and weekend sleep duration (RWW)] and cardiovascular risk factors including obesity, diabetes and hypertension.

RESULTS

Subjects with highest sleep duration variability - measured as NNV, RSL and RWW, were more likely to be obese. These associations robust in most but not all sensitivity analyses, and no associations between sleep duration variability measures and diabetes or hypertension were found.

CONCLUSION

There is a possible association between high sleep duration variability and obesity, although results were not robust in all sensitivity analyses. Further, no associations between sleep duration variability and other cardiovascular risk factor such as diabetes or hypertension were found.

Sex and race differences in the association between sleep duration and adiposity: the Bogalusa Heart Study

BACKGROUND

Short sleep duration has been consistently associated with obesity. However, few studies in adults have assessed whether this association varies by sex and race.

METHODS

In the 2013-2016 examination of 1116 participants from the biracial Bogalusa Heart Study, habitual sleep duration was measured in categories (<6 hours, 6-7 hours, 7-8 hours, > 8 hours) using self-report. Anthropometry was performed and adiposity was assessed using body mass index (BMI) and waist circumference. Linear regression models estimated the relationship between sleep duration and adiposity adjusting for age, education, employment, bed partner status, depressive symptoms, smoking status, physical activity, and the use of alcohol and sleeping pills. Effect modification by sex and race was examined using cross-product terms in the models and marginal means were reported.

RESULTS

Of 1116 participants (mean age 48.2 years), 58.3% were female, and 31.7% were Black. In adjusted analyses, women sleeping <6 hours had a 3.2 (95% CI 1.4, 5.0) kg/m² greater BMI and 6.1 (1.8, 10.4) cm greater waist circumference compared to women sleeping 7-8 hours. In contrast, men had similar BMIs and waist circumferences regardless of sleep duration (p's for interaction = 0.04 & 0.11). There was no effect modification by race.

CONCLUSIONS

In this sample, lower habitual sleep duration was associated with greater adiposity among women compared to men. Further research is needed to understand the potential mechanisms of the adverse metabolic effects of short sleep in women.

Actigraphy-based sleep characteristics and aortic stiffness: the Multi-Ethnic Study of Atherosclerosis

The study aimed to examine the association between objective estimates of sleep duration and quality and aortic stiffness while accounting for the potential confounding effect of sleep-disordered breathing. Participants were part of the Multi-Ethnic Study of Atherosclerosis Sleep study. Sleep duration and quality were assessed by 7-day wrist actigraphy, sleep-disordered breathing by home polysomnography, and aortic stiffness by magnetic resonance imaging-based aortic pulse wave velocity (aPWV), ascending and descending aorta distensibility. Aortic stiffness of participants with "normal" sleep duration (6-8 hours) were compared with those of "short" (<6 hours) and "long" sleep duration (>8 hours) adjusting for common cardiovascular risk factors and apnea-hypopnea index. The sample consisted of 908 participants (mean age 68.4 ± 9.1 years, 55.3% female). There was a significant linear trend of increased aPWV across short (n = 252), normal (n = 552), and long sleep durations (n = 104) (P for trend = .008). Multivariable analysis showed that people with short sleep duration had 0.94 m/s lower aPWV (95% CI: -1.54, -0.35), compared with those with normal sleep duration. In this ethnically diverse community cohort, habitual short sleep duration as estimated by actigraphy was associated with lower aortic stiffness.

Cross-sectional associations of objectively-measured sleep characteristics with obesity and type 2 diabetes in the PREDIMED-Plus trial

STUDY OBJECTIVES

To examine independent and combined associations of sleep duration and sleep variability with body composition, obesity and type 2 diabetes (T2D) in elders at high cardiovascular risk.

METHODS

Cross-sectional analysis of 1986 community-dwelling elders with overweight/obesity and metabolic syndrome from PREDIMED-Plus trial. Associations of accelerometry-derived sleep duration and sleep variability with body mass index (BMI), waist circumference (WC) and body composition were assessed fitting multivariable-adjusted linear regression models. Prevalence ratios (PR) and 95% confidence intervals (CI) for obesity and T2D were obtained using multivariable-adjusted Cox regression with constant time. "Bad sleepers" (age-specific non-recommended sleep duration plus sleep variability above the median) and "good sleepers" (age-specific recommended sleep duration plus sleep variability below the median) were characterized by combining sleep duration and sleep variability, and their associations with these outcomes were examined.

RESULTS

One hour/night increment in sleep duration was inversely associated with BMI (β -0.38 kg/m2 [95% CI -0.54, -0.23]), WC (β -0.86 cm [95% CI -1.25, -0.47]), obesity (PR 0.96 [95% CI 0.93, 0.98]), T2D (PR 0.93 [95% CI 0.88, 0.98]) and other DXA-derived adiposity-related measurements (android fat and trunk fat, all p < .05). Each 1-hour increment in sleep variability was positively associated with T2D (PR 1.14 [95% CI 1.01, 1.28]). Compared with "good sleepers," "bad sleepers" were positively associated with obesity (PR 1.12 [95% CI 1.01, 1.24]) and T2D (PR 1.62 [95% CI 1.28, 2.06]).

CONCLUSIONS

This study revealed cross-sectional associations of sleep duration with adiposity parameters and obesity. Sleep duration and sleep variability were associated with T2D. Considering simultaneously sleep duration and sleep variability could have additional value, particularly for T2D, as they may act synergistically.

Associations between polysomnography and actigraphy-based sleep indices and glycemic control among those with and without type 2 diabetes: the Multi-Ethnic Study of Atherosclerosis

Study Objectives

To examine the associations of sleep measures with hemoglobin A1c (HbA1c) among individuals with and without type 2 diabetes.

Methods

Data were from 2049 Multi-Ethnic Study of Atherosclerosis participants taking part in a sleep ancillary study. Cross-sectional linear regression models examined associations of actigraphy estimates of sleep (sleep duration, variability, and maintenance efficiency) and polysomnography measures (obstructive sleep apnea [OSA] and hypoxemia) with HbA1c, stratified by diabetes status. Primary models were adjusted for demographics, lifestyle behaviors, and obesity.

Results

Among individuals with diabetes (20 per cent population), those who slept <5 hr/night had greater HbA1c than those who slept 7-8 hr/night (7.44 vs. 6.98 per cent, ptrend = 0.04), with no attenuation of associations after adjusting for OSA/hypoxemia. In women with diabetes, but not men, those in the lowest quartile of sleep maintenance efficiency had greater HbA1c than those in the highest quartile of sleep maintenance efficiency (7.60 vs. 6.97 per cent, ptrend < 0.01). Among those without diabetes, individuals with severe OSA or in the highest quartile of hypoxemia had significantly greater HbA1c than those without OSA or who were in the lowest quartile of hypoxemia (5.76 vs. 5.66 per cent, ptrend = 0.01; 5.75 vs. 5.66 per cent, ptrend < 0.01, respectively). Associations did not meaningfully differ by race/ethnicity.

Conclusions

Among individuals with diabetes, HbA1c was significantly higher in men and women with short sleep duration and in women with poor sleep maintenance efficiency, suggesting a role for behavioral sleep interventions in the management of diabetes. Among individuals without diabetes, untreated severe OSA/hypoxemia may adversely influence HbA1c.

Habitual Sleep Measures are Associated with Overall Body Fat, and not Specifically with Visceral Fat, in Men and Women

OBJECTIVE

This study aimed to investigate the associations of sleep duration and sleep quality with visceral adipose tissue (VAT) in middle-aged individuals.

METHODS

In this cross-sectional analysis of baseline measurements of the Netherlands Epidemiology of Obesity (NEO) study, participants underwent anthropometry and completed the Pittsburgh Sleep Quality Index (PSQI) for assessing short sleep duration (as sex-specific age-adjusted percentiles) and poor quality (PSQI > 5). VAT was assessed by magnetic resonance imaging in a random subgroup. We performed linear regression analyses to examine associations of short sleep and poor sleep with measures of body fat, adjusted for confounding, including total body fat in models with VAT.

RESULTS

A total of 5,094 participants (52% women; mean age of 56 [SD 6] years), 1,947 of whom had VAT measurements, were analyzed. The difference in VAT between poor sleep (PSQI > 5) and good sleep (PSQI ≤ 5) was 7.2cm² (95% CI: 1.2-13.8) in women and 16.1cm² (95% CI: 6.2-26.0) in men. These differences attenuated toward the null after the adjustment for total body fat. Similar patterns of associations were observed for short sleep (lowest 10% compared with median 60%).

CONCLUSIONS

Our results suggest that measures of sleep are not specifically associated with a higher amount of VAT.

Impact of Poor Sleep on Physical and Mental Health in Older Women

Many aspects of sleep and circadian rhythms change as people age. Older adults usually experience decrease in sleep duration and efficiency, increase in sleep latency and fragmentation, high prevalence of sleep disorders, and weakened rest-activity rhythms. Research evidence suggests that women are more likely to report aging-related sleep problems. This review presents epidemiologic and clinical evidence on the relationships between sleep deficiency and physical and mental outcomes in older women, explores potential mechanisms underlying such relationships, points out gaps in the literature that warrant future investigations, and considers implications in clinical and public health settings.