Research associates short (and to a lesser extent long) sleep duration with obesity, diabetes, and cardiovascular disease; and although 7–8 h of sleep seems to confer the least health risk, these ...findings are often based on non-representative data. We hypothesize that short sleep (<7 h) and long sleep (>8 h) are positively associated with the risk of obesity, diabetes, hypertension, and cardiovascular disease; and analyze 2004–2005 US National Health Interview Survey data (n = 56,507 observations, adults 18–85) to test this. We employ multilevel logistic regression, simultaneously controlling for individual characteristics (e.g., ethnoracial group, gender, age, education), other health behaviors (e.g., exercise, smoking), family environment (e.g., income, size, education) and geographic context (e.g., census region). Our model correctly classified at least 76% of adults on each of the outcomes studied, and sleep duration was frequently more strongly associated with these health risks than other covariates. These findings suggest a 7–8 h sleep duration directly and indirectly reduces chronic disease risk.
The glymphatic system plays an important role in clearing the amyloid-β (Aβ) and tau proteins that are closely linked to Alzheimer disease (AD) pathology. Glymphatic clearance, as well as Aβ ...accumulation, is highly dependent on sleep, but the sleep-dependent driving forces behind cerebrospinal fluid (CSF) movements essential to the glymphatic flux remain largely unclear. Recent studies have reported that widespread, high-amplitude spontaneous brain activations in the drowsy state and during sleep, which are shown as large global signal peaks in resting-state functional magnetic resonance imaging (rsfMRI), are coupled with CSF movements, suggesting their potential link to glymphatic flux and metabolite clearance. By analyzing multimodal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) project, here we showed that the coupling between the global fMRI signal and CSF influx is correlated with AD-related pathology, including various risk factors for AD, the severity of AD-related diseases, the cortical Aβ level, and cognitive decline over a 2-year follow-up. These results provide critical initial evidence for involvement of sleep-dependent global brain activity, as well as the associated physiological modulations, in the clearance of AD-related brain waste.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract
Study Objectives
Multisensor wearable consumer devices allowing the collection of multiple data sources, such as heart rate and motion, for the evaluation of sleep in the home environment, ...are increasingly ubiquitous. However, the validity of such devices for sleep assessment has not been directly compared to alternatives such as wrist actigraphy or polysomnography (PSG).
Methods
Eight participants each completed four nights in a sleep laboratory, equipped with PSG and several wearable devices. Registered polysomnographic technologist-scored PSG served as ground truth for sleep–wake state. Wearable devices providing sleep–wake classification data were compared to PSG at both an epoch-by-epoch and night level. Data from multisensor wearables (Apple Watch and Oura Ring) were compared to data available from electrocardiography and a triaxial wrist actigraph to evaluate the quality and utility of heart rate and motion data. Machine learning methods were used to train and test sleep–wake classifiers, using data from consumer wearables. The quality of classifications derived from devices was compared.
Results
For epoch-by-epoch sleep–wake performance, research devices ranged in d′ between 1.771 and 1.874, with sensitivity between 0.912 and 0.982, and specificity between 0.366 and 0.647. Data from multisensor wearables were strongly correlated at an epoch-by-epoch level with reference data sources. Classifiers developed from the multisensor wearable data ranged in d′ between 1.827 and 2.347, with sensitivity between 0.883 and 0.977, and specificity between 0.407 and 0.821.
Conclusions
Data from multisensor consumer wearables are strongly correlated with reference devices at the epoch level and can be used to develop epoch-by-epoch models of sleep–wake rivaling existing research devices.
We validated actigraphy for detecting sleep and wakefulness versus polysomnography (PSG).
Actigraphy and polysomnography were simultaneously collected during sleep laboratory admissions. All studies ...involved 8.5 h time in bed, except for sleep restriction studies. Epochs (30-sec; n = 232,849) were characterized for sensitivity (actigraphy = sleep when PSG = sleep), specificity (actigraphy = wake when PSG = wake), and accuracy (total proportion correct); the amount of wakefulness after sleep onset (WASO) was also assessed. A generalized estimating equation (GEE) model included age, gender, insomnia diagnosis, and daytime/nighttime sleep timing factors.
Controlled sleep laboratory conditions.
Young and older adults, healthy or chronic primary insomniac (PI) patients, and daytime sleep of 23 night-workers (n = 77, age 35.0 ± 12.5, 30F, mean nights = 3.2).
N/A.
Overall, sensitivity (0.965) and accuracy (0.863) were high, whereas specificity (0.329) was low; each was only slightly modified by gender, insomnia, day/night sleep timing (magnitude of change < 0.04). Increasing age slightly reduced specificity. Mean WASO/night was 49.1 min by PSG compared to 36.8 min/night by actigraphy (β = 0.81; CI = 0.42, 1.21), unbiased when WASO < 30 min/night, and overestimated when WASO > 30 min/night.
This validation quantifies strengths and weaknesses of actigraphy as a tool measuring sleep in clinical and population studies. Overall, the participant-specific accuracy is relatively high, and for most participants, above 80%. We validate this finding across multiple nights and a variety of adults across much of the young to midlife years, in both men and women, in those with and without insomnia, and in 77 participants. We conclude that actigraphy is overall a useful and valid means for estimating total sleep time and wakefulness after sleep onset in field and workplace studies, with some limitations in specificity.
This study tests a central theoretical assumption of stress process and job strain models, namely that increases in employees' control and support at work should promote well-being. To do so, we use ...a group-randomized field trial with longitudinal data from 867 information technology (IT) workers to investigate the well-being effects of STAR, an organizational intervention designed to promote greater employee control over work time and greater supervisor support for workers' personal lives. We also offer a unique analysis of an unexpected field effect— a company merger—among workers surveyed earlier versus later in the study period, before or after the merger announcement. We find few STAR effects for the latter group, but over 12 months, STAR reduced burnout, perceived stress, and psychological distress, and increased job satisfaction, for the early survey group. STAR effects are partially mediated by increases in schedule control and declines in family-to-work conflict and burnout (an outcome and mediator) by six months. Moderating effects show that STAR benefits women in reducing psychological distress and perceived stress, and increases non-supervisory employees' job satisfaction. This study demonstrates, with a rigorous design, that organizational-level initiatives can promote employee well-being.
Given the pervasive use of screen-based media and the high prevalence of insufficient sleep among American youth and teenagers, this brief report summarizes the literature on electronic media and ...sleep and provides research recommendations. Recent systematic reviews of the literature reveal that the vast majority of studies find an adverse association between screen-based media consumption and sleep health, primarily via delayed bedtimes and reduced total sleep duration. The underlying mechanisms of these associations likely include the following: (1) time displacement (ie, time spent on screens replaces time spent sleeping and other activities); (2) psychological stimulation based on media content; and (3) the effects of light emitted from devices on circadian timing, sleep physiology, and alertness. Much of our current understanding of these processes, however, is limited by cross-sectional, observational, and self-reported data. Further experimental and observational research is needed to elucidate how the digital revolution is altering sleep and circadian rhythms across development (infancy to adulthood) as pathways to poor health, learning, and safety outcomes (eg, obesity, depression, risk-taking).
Sleep is essential for optimal health. The American Academy of Sleep Medicine (AASM) and Sleep Research Society (SRS) developed a consensus recommendation for the amount of sleep needed to promote ...optimal health in adults, using a modified RAND Appropriateness Method process. The recommendation is summarized here. A manuscript detailing the conference proceedings and evidence supporting the final recommendation statement will be published in SLEEP and the Journal of Clinical Sleep Medicine.
Significance It is established that glucose tolerance decreases from the morning to the evening, and that shift work is a risk factor for diabetes. However, the relative importance of the endogenous ...circadian system, the behavioral cycle (including the sleep/wake and fasting/feeding cycles), and circadian misalignment on glucose tolerance is unclear. We show that the magnitude of the effect of the endogenous circadian system on glucose tolerance and on pancreatic β-cell function was much larger than that of the behavioral cycle in causing the decrease in glucose tolerance from morning to evening. Also, independent from circadian phase and the behavioral cycle, circadian misalignment resulting from simulated night work lowered glucose tolerance—without diminishing effects upon repeated exposure—with direct relevance for shift workers.
Glucose tolerance is lower in the evening and at night than in the morning. However, the relative contribution of the circadian system vs. the behavioral cycle (including the sleep/wake and fasting/feeding cycles) is unclear. Furthermore, although shift work is a diabetes risk factor, the separate impact on glucose tolerance of the behavioral cycle, circadian phase, and circadian disruption (i.e., misalignment between the central circadian pacemaker and the behavioral cycle) has not been systematically studied. Here we show—by using two 8-d laboratory protocols—in healthy adults that the circadian system and circadian misalignment have distinct influences on glucose tolerance, both separate from the behavioral cycle. First, postprandial glucose was 17% higher (i.e., lower glucose tolerance) in the biological evening (8:00 PM) than morning (8:00 AM; i.e., a circadian phase effect), independent of the behavioral cycle effect. Second, circadian misalignment itself (12-h behavioral cycle inversion) increased postprandial glucose by 6%. Third, these variations in glucose tolerance appeared to be explained, at least in part, by different mechanisms: during the biological evening by decreased pancreatic β-cell function (27% lower early-phase insulin) and during circadian misalignment presumably by decreased insulin sensitivity (elevated postprandial glucose despite 14% higher late-phase insulin) without change in early-phase insulin. We explored possible contributing factors, including changes in polysomnographic sleep and 24-h hormonal profiles. We demonstrate that the circadian system importantly contributes to the reduced glucose tolerance observed in the evening compared with the morning. Separately, circadian misalignment reduces glucose tolerance, providing a mechanism to help explain the increased diabetes risk in shift workers.
Resting-state functional magnetic resonance imaging (rsfMRI) allows the study of functional brain connectivity based on spatially structured variations in neuronal activity. Proper evaluation of ...connectivity requires removal of non-neural contributions to the fMRI signal, in particular hemodynamic changes associated with autonomic variability. Regression analysis based on autonomic indicator signals has been used for this purpose, but may be inadequate if neuronal and autonomic activities covary. To investigate this potential co-variation, we performed rsfMRI experiments while concurrently acquiring electroencephalography (EEG) and autonomic indicator signals, including heart rate, respiratory depth, and peripheral vascular tone. We identified a recurrent and systematic spatiotemporal pattern of fMRI (named as fMRI cascade), which features brief signal reductions in salience and default-mode networks and the thalamus, followed by a biphasic global change with a sensory-motor dominance. This fMRI cascade, which was mostly observed during eyes-closed condition, was accompanied by large EEG and autonomic changes indicative of arousal modulations. Importantly, the removal of the fMRI cascade dynamics from rsfMRI diminished its correlations with various signals. These results suggest that the rsfMRI correlations with various physiological and neural signals are not independent but arise, at least partly, from the fMRI cascades and associated neural and physiological changes at arousal modulations.
The American Academy of Sleep Medicine and Sleep Research Society recently released a Consensus Statement regarding the recommended amount of sleep to promote optimal health in adults. This paper ...describes the methodology, background literature, voting process, and voting results for the consensus statement. In addition, we address important assumptions and challenges encountered during the consensus process. Finally, we outline future directions that will advance our understanding of sleep need and place sleep duration in the broader context of sleep health.
PDF
