Cardiovascular risks and sociodemographic correlates of multidimensional sleep phenotypes in two samples of US adults

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index with disease outcomes and their interaction in a clinical biobank

OBJECTIVES

Sleep is a complex behavior regulated by genetic and environmental factors impacting disease outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on common diseases, specifically mental health disorders, has yet to be fully elucidated. Using the Mass General Brigham Biobank, we examined the association of multidimensional sleep with disease outcomes and investigated whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health diseases.

METHODS

We generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms and constructed a Sleep Lifestyle Index based on self-reported questions and electronic health records; tested their association; performed phenome-wide association analyses between these indexes and clinical phenotypes; and analyzed their interaction on prevalent mental health diseases. A total of 15,884 participants were included in the analysis (mean age 54.4; 58.6% female).

RESULTS

The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95% CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). A total of 108 disease outcomes were associated with both indexes, spanning 12 disease groups. No interactions were found between the indexes on mental health diseases.

CONCLUSIONS

Favorable sleep behaviors and genetic predisposition to healthy sleep may independently protect against disease, underscoring the impact of multidimensional sleep on population health and the need for prevention strategies focused on healthy sleep habits.

Sleep health profiles across six population-based cohorts and recommendations for validating clustering models

OBJECTIVES

Model-based clustering is increasingly used to identify multidimensional sleep health profiles. However, generalizability is rarely assessed because of complexities of data sharing and harmonization. Our goal was to evaluate the generalizability of multidimensional sleep health profiles across older adult populations in Western countries and assess whether they predict depressive symptoms over time.

METHODS

We harmonized five self-reported sleep health indicators (satisfaction, alertness, timing, efficiency, and duration) across six population-based cohorts from the United States and Netherlands (N=614 - 3209 each) and performed identical latent class analysis in each cohort. Novel multivariable similarity metrics, patterns of sleep health and cluster sizes were used to match clusters and assess generalizability across cohorts. We compared cluster characteristics cross-sectionally and used linear mixed-effects modeling to relate sleep health clusters to depressive symptoms over time.

RESULTS

"Average sleep health" (moderate duration; high quality/efficiency; 42.7%-76.7% of sample) and "poor sleep health" (short duration; low quality/efficiency; high daytime sleepiness; 9.4%-20.4% of sample) clusters were generalizable across cohorts. In four cohorts "inefficient sleep" clusters were identified and in two cohorts "long, efficient sleep" clusters were identified. At 3years, those in the poor sleep cluster had depression symptoms that were 1.40-2.79 times greater than in the average sleep cluster, across all cohorts.

CONCLUSIONS

We identified two profiles - average sleep health and poor sleep health - that were generalizable across six samples of older adults and predicted depressive symptoms, underscoring the importance of the sleep health paradigm.

S, Vinay S. Sleep patterns and their correlation with cardiovascular health in the general population: A cross-sectional study

Sleep patterns, including duration and quality, are closely linked to cardiovascular health. This cross-sectional study of 100 participants aged 30-65 years assessed sleep patterns using validated questionnaires and measured cardiovascular health using the Framingham Risk Score. Short sleep duration (<6 hours) and poor sleep quality were significantly associated with higher cardiovascular risk (p < 0.001), while optimal sleep duration (7-8 hours) correlated with the lowest risk scores (p = 0.002). Long sleep duration also increased cardiovascular risk, particularly in individuals with conditions such as obesity and hypertension. These findings underscore the importance of promoting healthy sleep habits as a key strategy in preventing cardiovascular disease in the general population.

Influence of sleep on physiological systems in atherosclerosis

Sleep is a fundamental requirement of life and is integral to health. Deviation from optimal sleep associates with numerous diseases including those of the cardiovascular system. Studies, spanning animal models to humans, show that insufficient, disrupted or inconsistent sleep contribute to poor cardiovascular health by disrupting body systems. Fundamental experiments have begun to uncover the molecular and cellular links between sleep and heart health while large-scale human studies have associated sleep with cardiovascular outcomes in diverse populations. Here, we review preclinical and clinical findings that demonstrate how sleep influences the autonomic nervous, metabolic and immune systems to affect atherosclerotic cardiovascular disease.

The multidimensional sleep health of individuals with multiple sclerosis and Huntington's disease and healthy controls

STUDY OBJECTIVES

Sleep issues are common for people with neurodegenerative conditions, yet research has focused on specific aspects of sleep. While important, a more holistic approach to investigating sleep, termed "sleep health," considers sleep's positive and negative aspects. Current studies exploring sleep health have lacked a control group for reference. For the first time, this study investigated the sleep health of people living with multiple sclerosis and Huntington's disease (HD) and compared it with a community sample.

METHODS

111 people, including 43 with multiple sclerosis, 19 with HD, and 49 from a community sample, participated in this study. The data, including actigraphy, Pittsburgh Sleep Quality Index, and Epworth Sleepiness Scale, were collected as part of ongoing research studies. Seven sleep health domains were determined from the collected data, and a composite sleep health score was developed. Analysis of variance and independent t tests were performed to identify population and sex differences.

RESULTS

The HD group had higher sleep regularity and lower sleep rhythmicity than the multiple sclerosis and community sample groups. The HD group had significantly less sleep duration than the multiple sclerosis group. No significant differences between the groups were observed in the sleep health composite score. Males had significantly higher sleep regularity within the HD group but significantly lower sleepiness scores in the community sample.

CONCLUSIONS

These findings indicate that people with HD may experience greater variance in their wake times, therefore decreasing the consistency of being awake or asleep 24 hours apart. Understanding the mechanisms for this should be explored in people with HD.

CITATION

Turner M, Griffiths M, Laws M, Vial S, Bartlett D, Cruickshank T. The multidimensional sleep health of individuals with multiple sclerosis and Huntington's disease and healthy controls. J Clin Sleep Med. 2024;20(6):967-972.

Multidimensional Sleep Health Problems Across Middle and Older Adulthood Predict Early Mortality

BACKGROUND

Having multiple sleep problems is common in adulthood. Yet, most studies have assessed single sleep variables at one timepoint, potentially misinterpreting health consequences of co-occurring sleep problems that may change over time. We investigated the relationship between multidimensional sleep health across adulthood and mortality.

METHODS

Participants from the Midlife in the United States Study reported sleep characteristics in 2004-2006 (MIDUS-2; M2) and in 2013-2014 (MIDUS-3; M3). We calculated a composite score of sleep health problems across 5 dimensions: Regularity, Satisfaction, Alertness, Efficiency, and Duration (higher = more problems). Two separate models for baseline sleep health (n = 5 140; median follow-up time = 15.3 years) and change in sleep health (n = 2 991; median follow-up time = 6.4 years) to mortality were conducted. Cox regression models controlled for sociodemographics and key health risk factors (body mass index, smoking, depressive symptoms, diabetes, and hypertension).

RESULTS

On average, 88% of the sample reported having one or more sleep health problems at M2. Each additional sleep health problem at M2 was associated with 12% greater risk of all-cause mortality (hazard ratio [HR] = 1.12, 95% confidence interval [CI] = 1.04-1.21), but not heart disease-related mortality (HR = 1.14, 95% CI = 0.99-1.31). An increase in sleep health problems from M2 to M3 was associated with 27% greater risk of all-cause mortality (HR = 1.27, 95% CI = 1.005-1.59), and 153% greater risk of heart disease mortality (HR = 2.53, 95% CI = 1.37-4.68).

CONCLUSIONS

More sleep health problems may increase the risk of early mortality. Sleep health in middle and older adulthood is a vital sign that can be assessed at medical checkups to identify those at greater risk.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (β=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

Poor sleep health predicts the onset of a fear of falling among community-dwelling older adults

INTRODUCTION

A greater fear of falling predicts disability, falls, and mortality among older adults. Although poor sleep has been identified as a relevant risk factor for fear of falling among older adults, evidence is primarily shown in cross-sectional studies using isolated sleep characteristics. Less is known about whether prior fall experiences change the sleep health-fear of falling link among older adults. We investigated the longitudinal relationship between sleep health and the incidence of fear of falling among community-dwelling older adults and how the association differed between those with or without prior fall experiences.

METHODS

Data were from individuals who completed the sleep module in the National Health and Aging Trends Study (2013-2014; n = 686). Fear of falling was assessed with a single item. Multidimensional sleep health was measured with self-reported sleep items based on the SATED model (ie, sleep satisfaction, daytime alertness, timing, efficiency, and duration). Covariates included sociodemographics, assistive device usage, health, risky behavior, and sleep medications. Multiple logistic regression was used to analyze the data.

RESULTS

Poor sleep health was associated with the onset of fear of falling at 1-year follow-up (odds ratios=1.20, 95% confidence interval=1.02-1.41). Moreover, poor sleep health increased the odds of having fear of falling among individuals without prior falls experiences and elevated the already heightened risks of developing fear of falling among those who fell at baseline.

CONCLUSIONS

Given that fear of falling and experiencing a fall each increase the risk of the other occurring in the future, improving sleep health may prevent older adults from stepping into the vicious cycle of fear of falling and falls.

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.

Goldilocks at work: Just the right amount of job demands may be needed for your sleep health

OBJECTIVES

It has been reported that job demands affect sleep, but how different levels of job demands affect sleep remains unclear. We examined whether curvilinear relationships exist between job demands and multiple sleep health outcomes.

DESIGN

Cross-sectional analyses with linear and quadratic effects, using self-administered survey data.

SETTING

A national sample of US adults.

PARTICIPANTS

Workers from Midlife in the United States Study (MIDUS2; n = 2927).

MEASUREMENTS

The Job Content Questionnaire assessed overall and 5 specific aspects of job demands (intensity, role conflict, work overload, time pressure, and interruptions). Habitual sleep health patterns across 5 dimensions (regularity, satisfaction/quality, daytime alertness, efficiency, and duration) were assessed. Age, sex, race/ethnicity, marital/partnered status, education, job tenure, work hours, body mass index, smoking status, and study sample were covariates.

RESULTS

There were significant linear and quadratic relationships between job demands and sleep outcomes. Specifically, the linear effects indicated that participants with higher job demands had worse sleep health, such as shorter duration, greater irregularity, greater inefficiency, and more sleep dissatisfaction. The quadratic effects, however, indicated that sleep regularity and efficiency outcomes were the best when participants' job demands were moderate rather than too low or too high. These effects were found for overall job demands as well as for specific aspects of job demands. Stratified analyses further revealed that these curvilinear associations were mainly driven by participants with low job control.

CONCLUSIONS

Moderate levels of job demands, especially if combined with adequate job control, are related to optimal sleep health.