Modelling changes in sleep timing and duration across the lifespan: Changes in circadian rhythmicity or sleep homeostasis?

Associations between sleep duration trajectories and risk of cardio-metabolic disease among middle-aged and older Chinese adults

BACKGROUND

The association of a single time-point measure of sleep duration with cardio-metabolic disease has been extensively studied, but few studies have focused on the impact of sleep duration trajectory. This study aims to model the sleep duration trajectory as predictors for the subsequent development of cardio-metabolic disease.

METHODS

This study recruited a notably large population (n = 9883) of subjects aged at least 45 years from the China Health and Retirement Longitudinal Study (CHARLS), who participated in sequential surveys conducted in 2011, 2013, 2015, and 2018. Sleep duration trajectories were plotted using data of night sleep duration recorded at intervals from 2011 to 2015 by latent class trajectory model. The onset of cardio-metabolic diseases from 2015 to 2018 were confirmed and then the risk of different sleep duration trajectories on incident cardio-metabolic disease was examined using cox proportional hazards regression model.

RESULTS

We identified four sleep duration trajectories. Compared to the normal-stable trajectory, the short-stable trajectory was significantly associated with higher risk of incident stroke (hazard ratio [HR], 1.32; 95 % confidence interval [CI], 1.02 to 1.70), dyslipidemia (HR, 1.22; 95%CI, 1.01 to 1.49), and diabetes (HR, 1.42; 95%CI, 1.13 to 1.78) within three years of follow-up, and the short-increasing trajectory predicted a higher risk of incident stroke (HR, 2.38; 95%CI, 1.25 to 4.55).

CONCLUSIONS

Short sleep trajectory could increase the risk of incident stroke, dyslipidemia, and diabetes, and an increasing sleep trajectory was associated with increased risk of incident stroke among middle-aged and older Chinese adults.

Data-driven mathematical modeling of sleep consolidation in early childhood

Across early childhood development, sleep behavior transitions from a biphasic pattern (a daytime nap and nighttime sleep) to a monophasic pattern (only nighttime sleep). The transition to consolidated nighttime sleep, which occurs in most children between 2- and 5-years-old, is a major developmental milestone and reflects interactions between the developing homeostatic sleep drive and circadian system. Using a physiologically-based mathematical model of the sleep-wake regulatory network constrained by observational and experimental data from preschool-aged participants, we analyze how developmentally-mediated changes in the homeostatic sleep drive may contribute to the transition from napping to non-napping sleep patterns. We establish baseline behavior by identifying parameter sets that model typical 2-year-old napping behavior and 5-year-old non-napping behavior. Then we vary six model parameters associated with the dynamics of and sensitivity to the homeostatic sleep drive between the 2-year-old and 5-year-old parameter values to induce the transition from biphasic to monophasic sleep. We analyze the individual contributions of these parameters to sleep patterning by independently varying their age-dependent developmental trajectories. Parameters vary according to distinct evolution curves and produce bifurcation sequences representing various ages of transition onset, transition durations, and transitional sleep patterns. Finally, we consider the ability of napping and non-napping light schedules to reinforce napping or promote a transition to consolidated sleep, respectively. These modeling results provide insight into the role of the homeostatic sleep drive in promoting interindividual variability in developmentally-mediated transitions in sleep behavior and lay foundations for the identification of light- or behavior-based interventions that promote healthy sleep consolidation in early childhood.

Circadian rapid eye movement sleep expression is associated with brain microstructural integrity in older adults

Rapid eye movement sleep (REMS) is increasingly suggested as a discriminant sleep state for subtle signs of age-related neurodegeneration. While REMS expression is under strong circadian control and circadian dysregulation increases with age, the association between brain aging and circadian REMS regulation has not yet been assessed. Here, we measure the circadian amplitude of REMS through a 40-h in-lab multiple nap protocol in controlled laboratory conditions, and brain microstructural integrity with quantitative multi-parameter mapping (MPM) imaging in 86 older individuals. We show that reduced circadian REMS amplitude is related to lower magnetization transfer saturation (MTsat), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*) values in several white matter regions mostly located around the lateral ventricles, and with lower R1 values in grey matter clusters encompassing the hippocampus, parahippocampus, thalamus and hypothalamus. Our results further highlight the importance of considering circadian regulation for understanding the association between sleep and brain structure in older individuals.

Napping and circadian sleep-wake regulation during healthy aging

STUDY OBJECTIVES

Daytime napping is frequently reported among the older population and has attracted increasing attention due to its association with multiple health conditions. Here, we tested whether napping in the aged is associated with altered circadian regulation of sleep, sleepiness, and vigilance performance.

METHODS

Sixty healthy older individuals (mean age: 69 years, 39 women) were recruited with respect to their napping habits (30 nappers, 30 non-nappers). All participants underwent an in-lab 40-hour multiple nap protocol (10 cycles of 80 minutes of sleep opportunity alternating with 160 minutes of wakefulness), preceded and followed by a baseline and recovery sleep period. Saliva samples for melatonin assessment, sleepiness, and vigilance performance were collected during wakefulness and electrophysiological data were recorded to derive sleep parameters during scheduled sleep opportunities.

RESULTS

The circadian amplitude of melatonin secretion was reduced in nappers, compared to non-nappers. Furthermore, nappers were characterized by higher sleep efficiencies and REM sleep proportion during day- compared to nighttime naps. The nap group also presented altered modulation in sleepiness and vigilance performance at specific circadian phases.

DISCUSSION

Our data indicate that napping is associated with an altered circadian sleep-wake propensity rhythm. They thereby contribute to the understanding of the biological correlates underlying napping and/or sleep-wake cycle fragmentation during healthy aging. Altered circadian sleep-wake promotion can lead to a less distinct allocation of sleep into nighttime and/or a reduced wakefulness drive during the day, thereby potentially triggering the need to sleep at adverse circadian phase.

Mathematical Analysis of Light-sensitivity Related Challenges in Assessment of the Intrinsic Period of the Human Circadian Pacemaker

Accurate assessment of the intrinsic period of the human circadian pacemaker is essential for a quantitative understanding of how our circadian rhythms are synchronized to exposure to natural and man-made light-dark (LD) cycles. The gold standard method for assessing intrinsic period in humans is forced desynchrony (FD) which assumes that the confounding effect of lights-on assessment of intrinsic period is removed by scheduling sleep-wake and associated dim LD cycles to periods outside the range of entrainment of the circadian pacemaker. However, the observation that the mean period of free-running blind people is longer than the mean period of sighted people assessed by FD (24.50 ± 0.17 h vs 24.15 ± 0.20 h, p < 0.001) appears inconsistent with this assertion. Here, we present a mathematical analysis using a simple parametric model of the circadian pacemaker with a sinusoidal velocity response curve (VRC) describing the effect of light on the speed of the oscillator. The analysis shows that the shorter period in FD may be explained by exquisite sensitivity of the human circadian pacemaker to low light intensities and a VRC with a larger advance region than delay region. The main implication of this analysis, which generates new and testable predictions, is that current quantitative models for predicting how light exposure affects entrainment of the human circadian system may not accurately capture the effect of dim light. The mathematical analysis generates new predictions which can be tested in laboratory experiments. These findings have implications for managing healthy entrainment of human circadian clocks in societies with abundant access to light sources with powerful biological effects.

The sleep-circadian interface: A window into mental disorders

Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.

Melatonin suppression by light involves different retinal photoreceptors in young and older adults

Age-related sleep and circadian rhythm disturbances may be due to altered nonvisual photoreception. Here, we investigated the temporal dynamics of light-induced melatonin suppression in young and older individuals. In a within-subject design study, young and older participants were exposed for 60 min (0030-0130 at night) to nine narrow-band lights (range: 420-620 nm). Plasma melatonin suppression was calculated at 15, 30, 45, and 60 min time intervals. Individual spectral sensitivity of melatonin suppression and photoreceptor contribution were predicted for each interval and age group. In young participants, melanopsin solely drove melatonin suppression at all time intervals, with a peak sensitivity at 485.3 nm established only after 15 min of light exposure. Conversely, in older participants, spectral light-driven melatonin suppression was best explained by a more complex model combining melanopsin, S-cone, and M-cone functions, with a stable peak (~500 nm) at 30, 45, and 60 min of light exposure. Aging is associated with a distinct photoreceptor contribution to melatonin suppression by light. While in young adults melanopsin-only photoreception is a reliable predictor of melatonin suppression, in older individuals this process is jointly driven by melanopsin, S-cone, and M-cone functions. These findings offer new prospects for customizing light therapy for older individuals.

Sleep, Nutrition, and Injury Risk in Adolescent Athletes: A Narrative Review

This narrative review explores the impact of sleep and nutrition on injury risk in adolescent athletes. Sleep is viewed as essential to the recuperation process and is distinguished as an active participant in recovery through its involvement in growth, repair, regeneration, and immunity. Furthermore, the literature has shown that the sleep of athletes impacts elements of athletic performance including both physical and cognitive performance, recovery, injury risk, and mental well-being. For sleep to have a restorative effect on the body, it must meet an individual's sleep needs whilst also lasting for an adequate duration and being of adequate quality, which is age-dependent. The literature has suggested that athletes have increased sleep needs compared to those of the general population and thus the standard recommendations may not be sufficient for athletic populations. Therefore, a more individualised approach accounting for overall sleep health may be more appropriate for addressing sleep needs in individuals including athletes. The literature has demonstrated that adolescent athletes achieve, on average, ~6.3 h of sleep, demonstrating a discrepancy between sleep recommendations (8-10 h) and actual sleep achieved. Sleep-wake cycles undergo development during adolescence whereby adaptation occurs in sleep regulation during this phase. These adaptations increase sleep pressure tolerance and are driven by the maturation of physiological, psychological, and cognitive functioning along with delays in circadian rhythmicity, thus creating an environment for inadequate sleep during adolescence. As such, the adolescent period is a phase of rapid growth and maturation that presents multiple challenges to both sleep and nutrition; consequently, this places a significant burden on an adolescent athletes' ability to recover, thus increasing the likelihood of injury. Therefore, this article aims to provide a comprehensive review of the available literature on the importance of sleep and nutrition interactions in injury risk in adolescent athletes. Furthermore, it provides foundations for informing further investigations exploring the relation of sleep and nutrition interactions to recovery during adolescence.

Method to determine whether sleep phenotypes are driven by endogenous circadian rhythms or environmental light by combining longitudinal data and personalised mathematical models

Sleep timing varies between individuals and can be altered in mental and physical health conditions. Sleep and circadian sleep phenotypes, including circadian rhythm sleep-wake disorders, may be driven by endogenous physiological processes, exogeneous environmental light exposure along with social constraints and behavioural factors. Identifying the relative contributions of these driving factors to different phenotypes is essential for the design of personalised interventions. The timing of the human sleep-wake cycle has been modelled as an interaction of a relaxation oscillator (the sleep homeostat), a stable limit cycle oscillator with a near 24-hour period (the circadian process), man-made light exposure and the natural light-dark cycle generated by the Earth's rotation. However, these models have rarely been used to quantitatively describe sleep at the individual level. Here, we present a new Homeostatic-Circadian-Light model (HCL) which is simpler, more transparent and more computationally efficient than other available models and is designed to run using longitudinal sleep and light exposure data from wearable sensors. We carry out a systematic sensitivity analysis for all model parameters and discuss parameter identifiability. We demonstrate that individual sleep phenotypes in each of 34 older participants (65-83y) can be described by feeding individual participant light exposure patterns into the model and fitting two parameters that capture individual average sleep duration and timing. The fitted parameters describe endogenous drivers of sleep phenotypes. We then quantify exogenous drivers using a novel metric which encodes the circadian phase dependence of the response to light. Combining endogenous and exogeneous drivers better explains individual mean mid-sleep (adjusted R-squared 0.64) than either driver on its own (adjusted R-squared 0.08 and 0.17 respectively). Critically, our model and analysis highlights that different people exhibiting the same sleep phenotype may have different driving factors and opens the door to personalised interventions to regularize sleep-wake timing that are readily implementable with current digital health technology.

Modeling the Effects of Napping and Non-napping Patterns of Light Exposure on the Human Circadian Oscillator

In early childhood, consolidation of sleep from a biphasic to a monophasic sleep-wake pattern, that is, the transition from sleeping during an afternoon nap and at night to sleeping only during the night, represents a major developmental milestone. Reduced napping behavior is associated with an advance in the timing of the circadian system; however, it is unknown if this advance represents a standard response of the circadian clock to altered patterns of light exposure or if it additionally reflects features of the developing circadian system. Using a mathematical model of the human circadian pacemaker, we investigated the impact of napping and non-napping patterns of light exposure on entrained circadian phases. Simulated light schedules were based on published data from 20 children (34.2 ± 2.0 months) with habitual napping or non-napping sleep patterns (15 nappers). We found the model predicted different circadian phases for napping and non-napping light patterns: both the decrease in afternoon light during the nap and the increase in evening light associated with napping toddlers' later bedtimes contributed to the observed circadian phase difference produced between napping and non-napping light schedules. We systematically quantified the effects on phase shifting of nap duration, timing, and light intensity, finding larger phase delays occurred for longer and earlier naps. In addition, we simulated phase response curves to a 1-h light pulse and 1-h dark pulse to predict phase and intensity dependence of these changes in light exposure. We found the light pulse produced larger shifts compared with the dark pulse, and we analyzed the model dynamics to identify the features contributing to this asymmetry. These findings suggest that napping status affects circadian timing due to altered patterns of light exposure, with the dynamics of the circadian clock and light processing mediating the effects of the dark pulse associated with a daytime nap.

Sleep Health, Individual Characteristics, Lifestyle Factors, and Marathon Completion Time in Marathon Runners: A Retrospective Investigation of the 2016 London Marathon

Despite sleep health being critically important for athlete performance and well-being, sleep health in marathoners is understudied. This foundational study explored relations between sleep health, individual characteristics, lifestyle factors, and marathon completion time. Data were obtained from the 2016 London Marathon participants. Participants completed the Athlete Sleep Screening Questionnaire (ASSQ) along with a brief survey capturing individual characteristics and lifestyle factors. Sleep health focused on the ASSQ sleep difficulty score (SDS) and its components. Linear regression computed relations among sleep, individual, lifestyle, and marathon variables. The analytic sample (N = 943) was mostly male (64.5%) and young adults (66.5%). A total of 23.5% of the sample reported sleep difficulties (SDS ≥ 8) at a severity warranting follow-up with a trained sleep provider. Middle-aged adults generally reported significantly worse sleep health characteristics, relative to young adults, except young adults reported significantly longer sleep onset latency (SOL). Sleep tracker users reported worse sleep satisfaction. Pre-bedtime electronic device use was associated with longer SOL and longer marathon completion time, while increasing SOL was also associated with longer marathon completion. Our results suggest a deleterious influence of pre-bedtime electronic device use and sleep tracker use on sleep health in marathoners. Orthosomnia may be a relevant factor in the relationship between sleep tracking and sleep health for marathoners.

The prevalence and associated factors of sleep deprivation among healthy college students in China: a cross-sectional survey

Background

The prevalence of sleep deprivation among college students is increasing and has a few associated factors.

Methods

The present study analyzed 2,142 college students from 28 provinces in China. The Chinese version of the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep duration. Binary logistic regression was conducted to explore the sleep deprivation related factors. Age and gender were controlled as covariates.

Results

Among the 2,142 college students (27.7% male, 72.3% female), 1,620 (75.6%) reported the average sleep duration was below 7 h per day for one month, 49.3% (1,055/2,142) slept 6∼7 h (contains 6 h), 21.0% (449/2,142) slept 5∼6 h (contains 5 h), and 5.4% (116/2,142) slept <5 h. Age increased the risk of sleep deprivation, the adjusted odds ratio = 1.05 (95% CI [1.01∼1.10]). The adjusted odds ratio (A-OR) for sleep deprivation was higher for students of more than 60 min nap duration per day (A-OR = 2.35, 95% CI [1.45∼3.80]), and age growth (A-OR = 1.05, 95% CI [1.01∼1.10]). In contrast, A-ORs were lower among sleeping inconsistency between work and rest days (A-OR = 0.61, 95% CI [0.49∼0.75]), accustomed to staying up late (A-OR = 0.45, 95% CI [0.36∼0.57]), staying up late to work or study (A-OR = 0.62, 95% CI [0.49∼0.78]), stress (A-OR = 0.75, 95% CI [0.58∼0.98]), and repeated thoughts in bed had (A-OR = 0.79, 95% CI [0.62∼0.99]).

Conclusions

Sleep deprivation is extremely common among healthy college students in China. It is necessary to perform methods maintaining enough sleep due to the current high incidence of sleep deprivation. Controlling the nap duration and getting enough sleep on rest days to replace missing hours of sleep on workdays might improve college students' sleep.

Association between circadian sleep regulation and cortical gyrification in young and older adults

The circadian system orchestrates sleep timing and structure and is altered with increasing age. Sleep propensity, and particularly REM sleep is under strong circadian control and has been suggested to play an important role in brain plasticity. In this exploratory study, we assessed whether surface-based brain morphometry indices are associated with circadian sleep regulation and whether this link changes with age. Twenty-nine healthy older (55-82 years; 16 men) and 28 young participants (20-32 years; 13 men) underwent both structural magnetic resonance imaging and a 40-h multiple nap protocol to extract sleep parameters over day and night time. Cortical thickness and gyrification indices were estimated from T1-weighted images acquired during a classical waking day. We observed that REM sleep was significantly modulated over the 24-h cycle in both age groups, with older adults exhibiting an overall reduction in REM sleep modulation compared to young individuals. Interestingly, when taking into account the observed overall age-related reduction in REM sleep throughout the circadian cycle, higher day-night differences in REM sleep were associated with increased cortical gyrification in the right inferior frontal and paracentral regions in older adults. Our results suggest that a more distinctive allocation of REM sleep over the 24-h cycle is associated with regional cortical gyrification in aging, and thereby point towards a protective role of circadian REM sleep regulation for age-related changes in brain organization.

A real-time, personalized sleep intervention using mathematical modeling and wearable devices

The prevalence of artificial light exposure has enabled us to be active any time of the day or night, leading to the need for high alertness outside of traditional daytime hours. To address this need, we developed a personalized sleep intervention framework that analyzes real-world sleep-wake patterns obtained from wearable devices to maximize alertness during specific target periods. Our framework utilizes a mathematical model that tracks the dynamic sleep pressure and circadian rhythm based on the user's sleep history. In this way, the model accurately predicts real-time alertness, even for shift workers with complex sleep and work schedules (N = 71, t = 13~21 days). This allowed us to discover a new sleep-wake pattern called the adaptive circadian split sleep, which incorporates a main sleep period and a late nap to enable high alertness during both work and non-work periods of shift workers. We further developed a mobile application that integrates this framework to recommend practical, personalized sleep schedules for individual users to maximize their alertness during a targeted activity time based on their desired sleep onset and available sleep duration. This can reduce the risk of errors for those who require high alertness during nontraditional activity times and improve the health and quality of life for those leading shift work-like lifestyles.

COVID-19 effects on diet, sleep, and physical activity among mid- to late-adolescents residing in the deep south in the United States

PURPOSE

This study investigated the differential impact of COVID-19 on United States (US) adolescents' physical health as a function of sociodemographic factors over 18 months. It was hypothesized that the impact of COVID-19 and its mitigation efforts on physical health factors would vary by sociodemographic factors.

DESIGN AND METHODS

Data were drawn from a longitudinal study in which participants (ages 16 or 18) self-reported sleep, diet, and physical activity over 18months. Participants were enrolled between 2018 and 2022. Participants (n = 190, 73% Black/African American, 53% female) provided 1330 reports over 194 weeks (93 weeks before and 101 weeks after COVID-19 restrictions implementation).

RESULTS

Physical health outcomes moderated by demographic factors were measured and assessed over 18 months. Multilevel models and general estimated equations estimated the impact of COVID-19 restrictions on participants' health outcomes. Sleep and physical activity worsened after COVID-19 regardless of moderating factors, but some specific outcomes varied across subgroups.

CONCLUSIONS

This study diversifies the literature on the impact of COVID-19 and its mitigation measures on adolescents' social health. Further, it is based in the US's Deep South, largely populated by those identifying as Black/African American or of low socioeconomic status. Both subgroups are underrepresented in US-based health outcomes research. COVID-19 directly and indirectly impacted adolescents' physical health.

PRACTICE IMPLICATIONS

Understanding if and how COVID-19 impacted adolescents' health will inform nursing practice to adapt to and overcome adverse sequelae to promote positive patient health outcomes.

Pilot feasibility testing of biomathematical model recommendations for personalising sleep timing in shift workers

Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation is undertested. This study tested the feasibility of implementing two biomathematical models-the Phillips-Robinson Model and the Model for Arousal Dynamics-in 28 shift-working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips-Robinson Model. For the Phillips-Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre-study, significant improvements were observed post-study for sleep disturbance (Phillips-Robinson Model), and insomnia severity and sleep-related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof-of-concept for using biomathematical models to recommend sleep in operational contexts.

The Associations between the Homeostatic and Circadian Sleep Processes and the Neurobehavioral Functioning (NBF) of Individuals with ADHD-A Systematic Review

The objective of the present review was to systematically examine associations between perturbations of the homeostatic or circadian sleep processes and the neurobehavioral functioning (NBF) of individuals with ADHD. Electronic databases were searched for articles published between December 2013 and March 2023. Studies were included if they used objective measures of NBF, used objective or subjective measures of sleep, and focused on individuals with ADHD. Ten studies met these inclusion criteria. Of these, eight studies found perturbations in the interplay between NBF and Process S or Process C, and three studies did not. The quality of the studies was degraded because they failed to address key factors that affect the sleep processes and by the presence of methodological weaknesses. Our review suggests that homeostatic and circadian sleep processes are associated with NBF in individuals with ADHD. However, to confirm the validity of this conclusion, future studies should examine or control for confounders and utilize experimental designs that allow causality to be inferred.

Modeling homeostatic and circadian modulation of human pain sensitivity

Introduction

Mathematical modeling has played a significant role in understanding how homeostatic sleep pressure and the circadian rhythm interact to influence sleep-wake behavior. Pain sensitivity is also affected by these processes, and recent experimental results have measured the circadian and homeostatic components of the 24 h rhythm of thermal pain sensitivity in humans. To analyze how rhythms in pain sensitivity are affected by disruptions in sleep behavior and shifts in circadian rhythms, we introduce a dynamic mathematical model for circadian and homeostatic regulation of sleep-wake states and pain intensity.

Methods

The model consists of a biophysically based, sleep-wake regulation network model coupled to data-driven functions for the circadian and homeostatic modulation of pain sensitivity. This coupled sleep-wake-pain sensitivity model is validated by comparison to thermal pain intensities in adult humans measured across a 34 h sleep deprivation protocol.

Results

We use the model to predict dysregulation of pain sensitivity rhythms across different scenarios of sleep deprivation and circadian rhythm shifts, including entrainment to new environmental light and activity timing as occurs with jet lag and chronic sleep restriction. Model results show that increases in pain sensitivity occur under conditions of increased homeostatic sleep drive with nonlinear modulation by the circadian rhythm, leading to unexpected decreased pain sensitivity in some scenarios.

Discussion

This model provides a useful tool for pain management by predicting alterations in pain sensitivity due to varying or disrupted sleep schedules.

Perspectives on interpersonal touch are related to subjective sleep quality

Affective touch has been reported for its calming effects; however, it is less clear whether touch is associated with sleep. Here, the relationship between different touch variables and self-reported sleep indicators was investigated. Data were extracted from the Touch Test, a cross-sectional survey conducted in 2020. Data from a sample of 15,049 healthy adults from the UK (mean age = 56.13, SD = 13.8; 75.4% female) were analysed. Participants were asked to attribute positive, negative, or no effects on sleep to hugs, strokes, massages, intimate touch, and sleep onset with and without touch. The time since last intentional touch, touch amount satisfaction, and childhood bed routine with hugs and kisses were assessed. Sleep quality, duration, latency, wake after sleep onset and diurnal preference were measured. Data were analysed using chi-square tests and logistic regressions. Affective touch before sleep was perceived to have positive effects on sleep. Touch recency emerged as a significant predictor for some sleep variables, with a longer timespan since the last intentional touch relating to improved sleep quality, longer sleep duration, and shorter and fewer instances of waking up after sleep onset in some participants. Experiencing too much touch was related to lower sleep quality and higher instances of waking up after sleep onset. These findings highlight the importance of interpersonal touch for subjective sleep quality.

Childhood sleep health and epigenetic age acceleration in late adolescence: Cross-sectional and longitudinal analyses

AIM

Investigate if childhood measures of sleep health are associated with epigenetic age acceleration in late adolescence.

METHODS

Parent-reported sleep trajectories from age 5 to 17, self-reported sleep problems at age 17, and six measures of epigenetic age acceleration at age 17 were studied in 1192 young Australians from the Raine Study Gen2.

RESULTS

There was no evidence for a relationship between the parent-reported sleep trajectories and epigenetic age acceleration (p ≥ 0.17). There was a positive cross-sectional relationship between self-reported sleep problem score and intrinsic epigenetic age acceleration at age 17 (b = 0.14, p = 0.04), which was attenuated after controlling for depressive symptom score at the same age (b = 0.08, p = 0.34). Follow-up analyses suggested this finding may represent greater overtiredness and intrinsic epigenetic age acceleration in adolescents with higher depressive symptoms.

CONCLUSION

There was no evidence for a relationship between self- or parent-reported sleep health and epigenetic age acceleration in late adolescence after adjusting for depressive symptoms. Mental health should be considered as a potential confounding variable in future research on sleep and epigenetic age acceleration, particularly if subjective measures of sleep are used.

Many faces of sleep regulation: beyond the time of day and prior wake time

The two-process model of sleep regulation posits two main processes regulating sleep: the circadian process controlled by the circadian clock and the homeostatic process that depends on the history of sleep and wakefulness. The model has provided a dominant conceptual framework for sleep research since its publication ~ 40 years ago. The time of day and prior wake time are the primary factors affecting the circadian and homeostatic processes, respectively. However, it is critical to consider other factors influencing sleep. Since sleep is incompatible with other behaviors, it is affected by the need for essential behaviors such as eating, foraging, mating, caring for offspring, and avoiding predators. Sleep is also affected by sensory inputs, sickness, increased need for memory consolidation after learning, and other factors. Here, we review multiple factors influencing sleep and discuss recent insights into the mechanisms balancing competing needs.

Changes in daily sleep duration and subsequent risk of mortality among older people

BACKGROUND

Single self-reported measures of daily sleep duration are associated with adverse health outcomes; however, the association between changes in daily sleep duration and all-cause mortality has not been thoroughly evaluated among a large group of older people.

METHODS

Using data from the Chinese Longitudinal Healthy Longevity Surveys, a total of 8588 older participants were included in the present study. Changes in daily sleep duration were assessed using annual changes, and Cox regression analysis examined the association of the annual changes with mortality.

RESULTS

The median age of the study population was 82.00 (IQR: 72.00, 90.00) years, and 3974 (46.27%) participants were men. During a median follow-up period of 3.81 (IQR: 2.03, 6.74) years, 5100 (59.39%) deaths were recorded. After adjusting for initial daily sleep duration and other confounders, there was a non-linear relationship between annual changes in daily sleep duration and all-cause mortality. Annual changes were not associated with mortality before 0.0 h/year, and mortality risk increased after 0.0 h/year, specially after 1 h/year (adjusted HR: 1.32 per 1-hour/year increment, 95% CI: 1.18-1.47). Compared to the stable group (annual changes between -1 and 1 h), adjusted HRs for mortality were 0.98 (95% CI: 0.89-1.08) for the shorter group (annual decline more than 1 h) and 1.29 (95% CI: 1.19-1.41) for the longer group (annual increase greater than 1 h), respectively. Stratified and sensitivity analyses suggested robustness of the results.

CONCLUSIONS

The present study suggested there was a non-linear relationship between annual changes in daily sleep duration and all-cause mortality among older people: longer changes were associated with higher mortality; while, shorter changes were not associated with mortality. Specially, mortality risk increased significantly with longer than 1 h of annual changes. The findings highlight the importance of closely monitoring the changes in daily sleep duration among older people.

Daytime rest: Association with 24-h rest-activity cycles, circadian timing and cognition in older adults

Growing epidemiological evidence points toward an association between fragmented 24-h rest-activity cycles and cognition in the aged. Alterations in the circadian timing system might at least partially account for these observations. Here, we tested whether daytime rest (DTR) is associated with changes in concomitant 24-h rest probability profiles, circadian timing and neurobehavioural outcomes in healthy older adults. Sixty-three individuals (59-82 years) underwent field actigraphy monitoring, in-lab dim light melatonin onset assessment and an extensive cognitive test battery. Actimetry recordings were used to measure DTR frequency, duration and timing and to extract 24-h rest probability profiles. As expected, increasing DTR frequency was associated not only with higher rest probabilities during the day, but also with lower rest probabilities during the night, suggesting more fragmented night-time rest. Higher DTR frequency was also associated with lower episodic memory performance. Moreover, later DTR timing went along with an advanced circadian phase as well as with an altered phase angle of entrainment between the rest-activity cycle and circadian phase. Our results suggest that different DTR characteristics, as reflective indices of wake fragmentation, are not only underlined by functional consequences on cognition, but also by circadian alteration in the aged.

Circadian rhythms and disorders of the timing of sleep

The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep-wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.

Adaptive Solutions to the Problem of Vulnerability During Sleep

Sleep is a behavioral state whose quantity and quality represent a trade-off between the costs and benefits this state provides versus the costs and benefits of wakefulness. Like many species, we humans are particularly vulnerable during sleep because of our reduced ability to monitor the external environment for nighttime predators and other environmental dangers. A number of variations in sleep characteristics may have evolved over the course of human history to reduce this vulnerability, at both the individual and group level. The goals of this interdisciplinary review paper are (1) to explore a number of biological/instinctual features of sleep that may have adaptive utility in terms of enhancing the detection of external threats, and (2) to consider relatively recent cultural developments that improve vigilance and reduce vulnerability during sleep and the nighttime. This paper will also discuss possible benefits of the proposed adaptations beyond vigilance, as well as the potential costs associated with each of these proposed adaptations. Finally, testable hypotheses will be presented to evaluate the validity of these proposed adaptations.

Weekend sleep after early and later school start times confirmed a model-predicted failure to catch up sleep missed on weekdays

Background

Many people believe they sleep for longer time on weekend nights to make up for sleep lost on weekdays. However, results of simulations of risetimes and bedtimes on weekdays and weekends with a sleep–wake regulating model revealed their inability to prolong weekend sleep. In particular, they predicted identical durations of weekend sleep after weeks with relatively earlier and relatively later risetime on weekdays. In the present study, this paradoxical prediction was empirically confirmed.

Methods

Times in bed were calculated from weekday and weekend risetimes and bedtimes in pairs of samples of students with early and later school start time and in subsets of samples from 7 age groups with weekday risetime earlier and later than 7:00 a.m.

Results

Among 35 pairs of students, mean age ± standard deviation was 14.5 ± 2.9 years and among the age group samples, 21.6 ± 14.6 years. As predicted by the simulations, times in bed on weekends were practically identical in the samples with early and later school start time and in two subsets with earlier and later weekday risetime.

Conclusions

The model-based simulations of sleep times can inform an individual about an amount of irrecoverable loss of sleep caused by an advance shift of wakeups on weekdays.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11325-022-02648-5.

Epidemiology of accelerometer-based sleep parameters in US school-aged children and adults: NHANES 2011-2014

We aimed to provide objectively measured sleep parameters across lifespan by sex and race in a national representative sample of US population. The study included 11,279 participants 6 years and older from the National Health and Nutrition Examination Survey (NHANES) 2011–2014, who had at least 3 days of valid sleep parameters calculated from 7-day 24-h accelerometer recording. Sleep duration showed a U-shaped association with age and reached the minimum at age 40 and started to increase again around age 50. The clock time for sleep onset (CTSO) delayed with age and reached the maximum at about age 20. CTSO then advanced until age 50, leveled off until age 70, then advanced again after age 70. Sleep efficiency showed an overall decreasing trend across the lifespan but stabilized from age 30 to about age 60. US young adults in age 20 s are the ones who slept at the latest around midnight, while the middle aged US residents between 40 and 50 years old slept the least. Females generally present longer sleep duration than males, while more likely to have later sleep onset, particularly at older ages. Non-Hispanic Blacks showed worse sleep characteristics, i.e. sleep later, sleep shorter, and sleep less efficiently, compared to other racial groups. In conclusion, this study provides valuable insights on the characteristics of sleep habits of residents of the United States by using objectively measurements of sleep parameters and will help guide personalized advice on sleep hygiene.

What Can Make the Difference Between Chronotypes in Sleep Duration? Testing the Similarity of Their Homeostatic Processes

The two-process conceptualization of sleep-wake regulation suggests that the biological underpinnings of the differences between morning and evening types in sleep timing and duration might be related to either the circadian process or the homeostatic process or both. The purpose of this report was to test whether morning and evening types might have similar homeostatic processes to achieve such ultimate goal of homeostatic sleep regulation as taking an adequate amount of sleep on free days. Weekend and weekday rise- and bedtimes reported for 50 paired samples of morning and evening types were averaged and simulated with a model of sleep-wake regulation. In morning and evening types of the same age, the homeostatic components of the sleep-wake regulation were found to be identical. Therefore, the difference in the circadian process between chronotypes of similar age can account for the observed differences between them in sleep timing and duration on weekdays and weekends. It was also demonstrated that the model-based simulations might have practical implications for informing an individual about the extent of unrecoverable reduction of his/her sleep on weekdays.

Circadian timing of eating and BMI among adults in the American Time Use Survey

BACKGROUND/OBJECTIVES

Experimental studies of time-restricted eating suggest that limiting the daily eating window, shifting intake to the biological morning, and avoiding eating close to the biological night may promote metabolic health and prevent weight gain.

SUBJECTS/METHODS

We used the Eating & Health Module of the 2006-2008 and 2014-2016 American Time Use Survey to examine cross-sectional associations of timing of eating in relation to sleep/wake times as a proxy for circadian timing with body mass index (BMI). The analytical sample included 38 302 respondents (18-64 years; BMI 18.5-50.0 kg/m²). A single 24-hour time use diary was used to calculate circadian timing of eating variables: eating window (time between first and last eating activity); morning fast (time between end of sleep and start of eating window); and evening fast (time between end of eating window and start of sleep). Multinomial logistic regression and predictive margins were used to estimate adjusted population prevalences (AP) by BMI categories and changes in prevalences associated with a one-hour change in circadian timing of eating, controlling for sociodemographic and temporal characteristics.

RESULTS

A one-hour increase in eating window was associated with lower adjusted prevalence of obesity (AP = 27.1%, SE = 0.1%). Conversely, a one-hour increase in morning fast (AP = 28.7%, SE = 0.1%) and evening fast (AP = 28.5%, SE = 0.1%) were each associated with higher prevalence of obesity; interactions revealed differing patterns of association by combination of eating window with morning/evening fast (p < 0.0001).

CONCLUSIONS

Contrary to hypotheses, longer eating windows were associated with a lower adjusted prevalence of obesity and longer evening fasts were associated with a higher prevalence of obesity. However, as expected, longer morning fast was associated with a higher adjusted prevalence of obesity. Studies are needed to disentangle the contributions of diet quality/quantity and social desirability bias in the relationship between circadian timing of eating and BMI.

Melatonin's Benefits and Risks as a Therapy for Sleep Disturbances in the Elderly: Current Insights

Aging is accompanied by circadian changes, including disruptive alterations in the sleep/wake cycle, as well as the beginning of low-degree inflammation ("inflammaging"), a scenario that leads to several chronic illnesses, including cancer, and metabolic, cardiovascular, and neurological dysfunctions. As a result, any effective approach to healthy aging must consider both the correction of circadian disturbance and the control of low-grade inflammation. One of the most important prerequisites for healthy aging is the preservation of robust circadian rhythmicity (particularly of the sleep/wake cycle). Sleep disturbance disrupts various activities in the central nervous system, including waste molecule elimination. Melatonin is a chemical with extraordinary phylogenetic conservation found in all known aerobic creatures whose alteration plays an important role in sleep changes with aging. Every day, the late afternoon/nocturnal surge in pineal melatonin helps to synchronize both the central circadian pacemaker found in the hypothalamic suprachiasmatic nuclei (SCN) and a plethora of peripheral cellular circadian clocks. Melatonin is an example of an endogenous chronobiotic substance that can influence the timing and amplitude of circadian rhythms. Moreover, melatonin is also an excellent anti-inflammatory agent, buffering free radicals, down-regulating proinflammatory cytokines, and reducing insulin resistance, among other things. We present both scientific and clinical evidence that melatonin is a safe drug for treating sleep disturbances in the elderly.

Sleep in an At Risk Adolescent Group: A Qualitative Exploration of the Perspectives, Experiences and Needs of Youth Who Have Been Excluded From Mainstream Education

The sleep needs, experiences and viewpoints were explored for UK adolescents who have been excluded from mainstream education. Qualitative data was gathered through interviews with 9 participants, aged 11–15 years, who also completed questionnaires. The participants had symptoms of inadequate sleep, poor sleep hygiene behaviours and were not getting the recommended amount of sleep on school nights. Participants described sleep patterns involving often staying up late and having different sleep timing on weekends than weekdays and having difficulties with their sleep. Use of technology and the relevance of family were identified as important and associated with facilitating and hindering factors for sleep. Participants communicated that they lack control over aspects of their sleep and their lives. The experiences and views of the participants can inform professionals’ understanding of how to collaborate with adolescents to improve their sleep and highlight that continued development of sleep education programmes is timely.

Heritability of Sleep and Its Disorders in Childhood and Adolescence

Purpose of Review

This review summarizes recent literature on the heritability of sleep and sleep disorders in childhood and adolescence. We also identify gaps in the literature and priorities for future research.

Recent Findings

Findings indicate that age, measurement method, reporter, and timing of sleep measurements can influence heritability estimates. Recent genome-wide association studies (GWAS) have identified differences in the heritability of sleep problems when ancestral differences are considered, but sample sizes are small compared to adult GWAS. Most studies focus on sleep variables in the full range rather than on disorder. Studies using objective measures of sleep typically comprised small samples.

Summary

Current evidence demonstrates a wide range of heritability estimates across sleep phenotypes in childhood and adolescence, but research in larger samples, particularly using objective sleep measures and GWAS, is needed. Further understanding of environmental mechanisms and the interaction between genes and environment is key for future research.

Extracting Circadian and Sleep Parameters from Longitudinal Data in Schizophrenia for the Design of Pragmatic Light Interventions

Sleep and circadian rhythm dysfunction is prevalent in schizophrenia, is associated with distress and poorer clinical status, yet remains an under-recognized therapeutic target. The development of new therapies requires the identification of the primary drivers of these abnormalities. Understanding of the regulation of sleep-wake timing is now sufficiently advanced for mathematical model-based analyses to identify the relative contribution of endogenous circadian processes, behavioral or environmental influences on sleep-wake disturbance and guide the development of personalized treatments. Here, we have elucidated factors underlying disturbed sleep-wake timing by applying a predictive mathematical model for the interaction of light and the circadian and homeostatic regulation of sleep to actigraphy, light, and melatonin profiles from 20 schizophrenia patients and 21 age-matched healthy unemployed controls, and designed interventions which restored sleep-circadian function. Compared to controls, those with schizophrenia slept longer, had more variable sleep timing, and received significantly fewer hours of bright light (light > 500 lux), which was associated with greater variance in sleep timing. Combining the model with the objective data revealed that non 24-h sleep could be best explained by reduced light exposure rather than differences in intrinsic circadian period. Modeling implied that late sleep offset and non 24-h sleep timing in schizophrenia can be normalized by changes in environmental light-dark profiles, without imposing major lifestyle changes. Aberrant timing and intensity of light exposure patterns are likely causal factors in sleep timing disturbances in schizophrenia. Implementing our new model-data framework in clinical practice could deliver personalized and acceptable light-dark interventions that normalize sleep-wake timing.

Probing different aspects of short and ill-timed sleep in adolescents using the Morningness-Eveningness Scale for Children

Sleep problems among adolescents are believed to be related to the circadian changes that occur at this age. Therefore, most self-report instruments that measure sleep patterns in adolescence focus solely on measuring circadian rhythms. However, sleep-wake cycles reflect both circadian and homeostatic processes. Recently, it was shown that answers to the Morningness-Eveningness Questionnaire for adults, which is used to assess circadian typology, were able to identify three interrelated latent factors: two that can be conceptualized as homeostatic (sensitivity to the build-up of sleep pressure and efficiency of dissipation of sleep pressure) and a less well-defined factor related to activity preference time (APT). To better understand self-reported changes in sleep patterns in adolescents we applied confirmatory factor analysis to explore whether responses to the Morningness-Eveningness Scale for Children (MESC) could also identify these three factors. The sample comprised 397, 9- to 17-year-olds. A three-correlated and a bifactor-(S-1) model (with sleep onset characteristics as a reference factor) had acceptable/good fit indices. This indicates that the MESC captures dissociable, but interrelated, homeostatic and circadian processes in addition to APT. These factors correlated with corresponding reported sleep habits, showing individual differences that may be more associated with sleep difficulties than the effects of age, which only correlated very modestly with some sleep habits. Our results indicate that the MESC can show distinct individual differences in three sleep factors that can help identify adolescents at higher risk of sleep-related problems that may require factor-specific interventions.

Modeling the change trajectory of sleep duration and its associated factors: based on an 11-year longitudinal survey in China

BACKGROUND

Sleep duration is a vital public health topic, yet most existing studies have been limited to cross-sectional surveys or inconsistent classifications of sleep duration categories, and few characterized its continuous development process. The current study aimed to depict its change trajectory in the general population and identify associated factors from a dynamic perspective.

METHODS

A total of 3788 subjects (45.4% male, mean age 46.72 ± 14.89 years) from the China Health and Nutrition Survey were recruited, and their daily sleep duration for five consecutive measurements from 2004 to 2015 was recorded. We adopted latent growth modelling to establish systematic relations between sleep duration and time. Participants' sociodemographic characteristics, lifestyle, and health factors were taken as covariates.

RESULTS

The change in sleep duration could be depicted by a linear decreasing trajectory with the mean yearly decrease at 2.5 min/day. The trajectory did not differ by residence, BMI category, chronic disease situation, smoking status, or drinking status. Moreover, there were sex and age differences in the trajectory, and females and those under 30 were prone to larger decrease rates.

CONCLUSION

The quantified yearly change in sleep duration provided insights for the prediction and early warning of insufficient sleep. Public health interventions focusing on slowing down the decrease rates among females and young individuals are warranted.

Gender moderates the relationship between media use and sleep quality

With high screen time and poor sleep commonly reported in adolescents, it is important to more fully understand how screen time impacts sleep. Despite similar overall screen times, male and female media preferences and usages differ, making it critical to determine if different domains of screen time differentially affect sleep quality. The present study examined whether differing amounts and domains of screen-based media vary in impact on sleep quality of 16-year-old male and female adolescents over a 3-month period. A total of 98 adolescents (mean [SD] age 16.27 [0.29] years; 51% female) completed two online surveys spaced 3 months apart and comprised of well-validated self-reported measures of sleep quality, media usage, and depressive symptoms. The various domains of media were categorised into screen-based media with little-to-no peer-to-peer interaction involved (video-only) and screen-based media with interaction a predominant component to the usage (peer-to-peer interaction-involved). Self-reported sleep quality decreased across the 3-month study period. Gender moderated the effect of interactive screen time on sleep quality 3 months later, with interactive screen time associated with better sleep quality in males, but remaining poorer in females. Screen time competes with sleep time and may do so differentially depending on the media domain. Compared to females, interactive components of screen time may lessen worsening sleep quality over time in males. Understanding the relationships among screen time, its content, age, and gender may inform guidelines for educators, parents, and adolescents to help improve sleep quality of adolescents.

Sleep in Normal Aging, Homeostatic and Circadian Regulation and Vulnerability to Sleep Deprivation

In the context of geriatric research, a growing body of evidence links normal age-related changes in sleep with many adverse health outcomes, especially a decline in cognition in older adults. The most important sleep alterations that continue to worsen after 60 years involve sleep timing, (especially early wake time, phase advance), sleep maintenance (continuity of sleep interrupted by numerous awakenings) and reduced amount of sigma activity (during non-rapid eye movement (NREM) sleep) associated with modifications of sleep spindle characteristics (density, amplitude, frequency) and spindle-Slow Wave coupling. After 60 years, there is a very clear gender-dependent deterioration in sleep. Even if there are degradations of sleep after 60 years, daytime wake level and especially daytime sleepiness is not modified with age. On the other hand, under sleep deprivation condition, older adults show smaller cognitive impairments than younger adults, suggesting an age-related lower vulnerability to extended wakefulness. These sleep and cognitive age-related modifications would be due to a reduced homeostatic drive and consequently a reduced sleep need, an attenuation of circadian drive (reduction of sleep forbidden zone in late afternoon and wake forbidden zone in early morning), a modification of the interaction of the circadian and homeostatic processes and/or an alteration of subcortical structures involved in generation of circadian and homeostatic drive, or connections to the cerebral cortex with age. The modifications and interactions of these two processes with age are still uncertain, and still require further investigation. The understanding of the respective contribution of circadian and homeostatic processes in the regulation of neurobehavioral function with aging present a challenge for improving health, management of cognitive decline and potential early chronobiological or sleep-wake interventions.

Mindful larks and lonely owls: The relationship between chronotype, mental health, sleep quality, and social support in young adults

Chronotype is related to mental health, with evening chronotypes being more susceptible to psychological disorders than intermediate and morning types. The present study investigated the relationship between chronotype, mental health, sleep quality, and social support in Canadian young adults. We surveyed 3160 university students aged 18-35 years. Participants completed the Morningness-Eveningness Questionnaire, the Hospital Anxiety and Depression Scale, the Mindful Attention Awareness Scale, the Pittsburgh Sleep Quality Index, and the Medical Outcomes Study - Social Support Survey. We conducted Bonferroni-corrected one-way analyses of covariance with post hoc paired comparisons to determine the relationship between the aforementioned variables, with age and sex as covariates. We further looked at the moderation of social support on the relationship between chronotype and sleep quality. Overall, 55%, 36% and 9% of participants were classified as intermediate, evening and morning types, respectively. There was a significant difference between chronotype on levels of depression, anxiety, and sleep quality, with evening types reporting more severe symptomology than morning-types and intermediate types. Morning types reported greater levels of overall social support and mindfulness. Evening types reported the lowest levels of all types of social support. Social support did not moderate the relationship between chronotype and sleep quality. This study further demonstrates the association between worse psychological well-being and eveningness and between more social support, and mindfulness in morning chronotype young adults. Education and intervention are warranted to help evening chronotypes manage the potential negative features of their circadian rhythm, as well as to cultivate a greater sense of social support and mindfulness.

The interindividual variability of sleep timing and circadian phase in humans is influenced by daytime and evening light conditions

Human cognitive functioning shows circadian variations throughout the day. However, individuals largely differ in their timing during the day of when they are more capable of performing specific tasks and when they prefer to sleep. These interindividual differences in preferred temporal organization of sleep and daytime activities define the chronotype. Since a late chronotype is associated with adverse mental and physical consequences, it is of vital importance to study how lighting environments affect chronotype. Here, we use a mathematical model of the human circadian pacemaker to understand how light in the built environment changes the chronotype distribution in the population. In line with experimental findings, we show that when individuals spend their days in relatively dim light conditions, this not only results in a later phase of their biological clock but also increases interindividual differences in circadian phase angle of entrainment and preferred sleep timing. Increasing daytime illuminance results in a more narrow distribution of sleep timing and circadian phase, and this effect is more pronounced for longer photoperiods. The model results demonstrate that modern lifestyle changes the chronotype distribution towards more eveningness and more extreme differences in eveningness. Such model-based predictions can be used to design guidelines for workplace lighting that help limiting circadian phase differences, and craft new lighting strategies that support human performance, health and wellbeing.

Sex differences in deterioration of sleep properties associated with aging: a 12-year longitudinal cohort study

STUDY OBJECTIVES

The sleep patterns of humans are greatly influenced by age and sex and have various effects on overall health as they change continuously during the lifespan. We investigated age-dependent changes in sleep properties and their relation to sex in middle-aged individuals.

METHODS

We analyzed data from 2,640 participants (mean age of 49.8 ± 6.8 years at baseline, 50.6% women) in the Korean Genome and Epidemiology Study, which assessed sleep habits using the Pittsburgh Sleep Quality Index and other clinical characteristics. We analyzed the sleep habit changes that occurred between baseline and a follow-up point (mean interval: 12.00 ± 0.16 years). Associations of age and sex with 9 sleep characteristics were evaluated.

RESULTS

Age was associated with most of the sleep characteristics cross-sectionally and longitudinally (P < .05), except for the time in bed at baseline (P = .455) and change in sleep duration (P = .561). Compared with men, women had higher Pittsburgh Sleep Quality Index scores, shorter time in bed, shorter sleep duration, and longer latency at baseline (P ≤ .001). Longitudinal deterioration in Pittsburgh Sleep Quality Index score, habitual sleep efficiency, duration, and latency was more prominent in women (P < .001). The sex differences in these longitudinal sleep changes were mainly noticeable before age 60 years (P < .05). Worsening of Pittsburgh Sleep Quality Index scores, habitual sleep efficiency, and latency was most evident in perimenopausal women. Men presented with greater advancement of chronotype (P = .006), with the peak sex-related difference occurring when they were in their late 40s (P = .048).

CONCLUSIONS

Aging is associated with substantial deterioration in sleep quantity and quality as well as chronotype advancement, with the degree and timing of these changes differing by sex.

Associations Between Sleep Quality and Health Span: A Prospective Cohort Study Based on 328,850 UK Biobank Participants

OBJECTIVE

To examine the associations between sleep quality and health span using a prospective cohort design based on the UK Biobank (UKB).

MATERIALS AND METHODS

This longitudinal cohort study enrolled 328,850 participants aged between 37 and 73 years from UKB to examine the associations between sleep quality and risk of terminated health span. End of health span was defined by eight events strongly associated with longevity (cancer, death, congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, and diabetes), and a sleep score was generated according to five sleep behavioral factors (sleep duration, chronotype, sleeplessness, daytime sleepiness, and snoring) to characterize sleep quality. The hazard ratio (HR) and 95% confidence intervals (CIs) were calculated by multivariate-adjusted Cox proportional hazards model. Moreover, we calculated population attributable risk percentage (PAR%) to reflect the public health significance of healthy sleep quality.

RESULTS

Compared with poor sleep quality, participants with healthy sleep quality had a 15% (HR: 0.85, 95% CI: 0.81-0.88) reduced risk of terminated health span, and those of less-healthy sleep quality had a 12% (HR: 0.88, 95% CI: 0.85-0.92) reduced risk. Linear trend results indicated that the risk of terminated health span decreased by 4% for every additional sleep score. Nearly 15% health span termination events in this cohort would have been prevented if a healthy sleep behavior pattern was adhered to (PAR%: 15.30, 95% CI: 12.58-17.93).

CONCLUSION

Healthy sleep quality was associated with a reduced risk of premature end of health span, suggesting healthy sleep behavior may extend health span. However, further studies are suggested for confirmation of causality and potential mechanism.

Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning

BACKGROUND

Despite recent significant progress in the development of automatic sleep staging methods, building a good model still remains a big challenge for sleep studies with a small cohort due to the data-variability and data-inefficiency issues. This work presents a deep transfer learning approach to overcome these issues and enable transferring knowledge from a large dataset to a small cohort for automatic sleep staging.

METHODS

We start from a generic end-to-end deep learning framework for sequence-to-sequence sleep staging and derive two networks as the means for transfer learning. The networks are first trained in the source domain (i.e. the large database). The pretrained networks are then finetuned in the target domain (i.e. the small cohort) to complete knowledge transfer. We employ the Montreal Archive of Sleep Studies (MASS) database consisting of 200 subjects as the source domain and study deep transfer learning on three different target domains: the Sleep Cassette subset and the Sleep Telemetry subset of the Sleep-EDF Expanded database, and the Surrey-cEEGrid database. The target domains are purposely adopted to cover different degrees of data mismatch to the source domains.

RESULTS

Our experimental results show significant performance improvement on automatic sleep staging on the target domains achieved with the proposed deep transfer learning approach.

CONCLUSIONS

These results suggest the efficacy of the proposed approach in addressing the above-mentioned data-variability and data-inefficiency issues.

SIGNIFICANCE

As a consequence, it would enable one to improve the quality of automatic sleep staging models when the amount of data is relatively small.¹¹The source code and the pretrained models are published at https://github.com/pquochuy/sleep_transfer_learning.

Sleepiness is a signal to go to bed: data and model simulations

Study Objectives

Assess the validity of a subjective measure of sleepiness as an indicator of sleep drive by quantifying associations between intraindividual variation in evening sleepiness and bedtime, sleep duration, and next morning and subsequent evening sleepiness, in young adults.

Methods

Sleep timing and sleepiness were assessed in 19 students in late autumn and late spring on a total of 771 days. Karolinska Sleepiness Scales (KSS) were completed at half-hourly intervals at fixed clock times starting 4 h prior to participants’ habitual bedtime, and in the morning. Associations between sleepiness and sleep timing were evaluated by mixed model and nonparametric approaches and simulated with a mathematical model for the homeostatic and circadian regulation of sleepiness.

Results

Intraindividual variation in evening sleepiness was very large, covering four or five points on the 9-point KSS scale, and was significantly associated with subsequent sleep timing. On average, a one point higher KSS value was followed by 20 min earlier bedtime, which led to 11 min longer sleep, which correlated with lower sleepiness next morning and the following evening. Associations between sleepiness and sleep timing were stronger in early compared to late sleepers. Model simulations indicated that the directions of associations between sleepiness and sleep timing are in accordance with their homeostatic and circadian regulation, even though much of the variance in evening sleepiness and details of its time course remain unexplained by the model.

Conclusion

Subjective sleepiness is a valid indicator of the drive for sleep which, if acted upon, can reduce insufficient sleep.

Investigation of the relationships between sleep behaviors and risk of healthspan termination: a prospective cohort study based on 323,373 UK-Biobank participants

OBJECTIVES

To examine the associations between four sleep behaviors and the risk of healthspan termination.

METHODS

This study included 323,373 participants, free of terminated healthspan at baseline, from the UK-Biobank (UKB). We applied multivariable-adjusted Cox regression models to estimate the risk of terminated healthspan based on four sleep behaviors (insomnia/sleeplessness, napping, daytime sleepiness, and difficulty getting up from bed), which were self-reported and measured on Likert scales from "usually" to "never/rarely" experiences. In this study, healthspan was defined based on eight events that are strongly associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death).

RESULTS

Participants who reported the following unhealthy sleep behaviors had a significantly higher risk of terminated healthspan: "usually experience sleeplessness/insomnia" (HR = 1.05, 95% CI: 1.03-1.07; P < 0.001); "usually nap" (HR = 1.22, 95% CI: 1.18-1.26; P < 0.01); "excessive daytime sleepiness" (HR = 1.25, 95% CI: 1.19-1.32; P < 0.001); and "difficult getting up from bed" (HR = 1.08, 95% CI: 1.05-1.10; P < 0.001). The corresponding population attributable risk percentage (PAR%) indicated that about 7% of healthspan termination in this cohort would have been eliminated if all participants had healthy sleep behaviors.

CONCLUSION

Participants who reported "usually experience sleeplessness/insomnia," "usually nap," "excessive daytime sleepiness," and "difficult getting up from bed" had increased risk of shortened healthspan. Therefore, adherence to healthy sleep behavior is significant for the extension of healthspan.

Individual differences in light sensitivity affect sleep and circadian rhythms

Artificial lighting is omnipresent in contemporary society with disruptive consequences for human sleep and circadian rhythms because of overexposure to light, particularly in the evening/night hours. Recent evidence shows large individual variations in circadian photosensitivity, such as melatonin suppression, due to artificial light exposure. Despite the emerging body of research indicating that the effects of light on sleep and circadian rhythms vary dramatically across individuals, recommendations for appropriate light exposure in real-life settings rarely consider such individual effects. This review addresses recently identified links among individual traits, for example, age, sex, chronotype, genetic haplotypes, and the effects of evening/night light on sleep and circadian hallmarks, based on human laboratory and field studies. Target biological mechanisms for individual differences in light sensitivity include differences occurring within the retina and downstream, such as the central circadian clock. This review also highlights that there are wide gaps of uncertainty, despite the growing awareness that individual differences shape the effects of evening/night light on sleep and circadian physiology. These include (1) why do certain individual traits differentially affect the influence of light on sleep and circadian rhythms; (2) what is the translational value of individual differences in light sensitivity in populations typically exposed to light at night, such as night shift workers; and (3) what is the magnitude of individual differences in light sensitivity in population-based studies? Collectively, the current findings provide strong support for considering individual differences when defining optimal lighting specifications, thus allowing for personalized lighting solutions that promote quality of life and health.

The relationship between chronotype and sleep behavior during rotating shift work: a field study

Shift work, an essential part of our 24/7 society, inevitably leads to displacement of the habitual sleep period and thereby to misalignment of the internal circadian timing system with the rest-activity cycle and the environment. How interindividual differences in circadian organization affect sleep duration and timing during rotating shift work is not fully understood. The objective of this study was to assess the effect of chronotype, shift type, and their interaction on actigraphy-based sleep behavior in 74 police officers (20 women and 54 men; age [mean ± SD]: 32.1 ± 5.4 years) involved in rotating shift work throughout a 28- to 35-day work cycle consisting of morning, evening, and night shifts. Using linear mixed modeling, we found that chronotype was associated with sleep duration depending on the shift type: increasing morningness was correlated with longer sleep duration during series of consecutive morning shifts, while increasing eveningness was correlated with longer sleep duration during series of evening shifts. During series of night shifts, increasing eveningness was associated with a longer duration of the main sleep episode, but this relationship was attenuated and no longer significant when naps were taken into account due to increased napping in morning chronotypes during series of night shifts. Providing a detailed within-subject characterization of sleep behavior across a complete work cycle consisting of morning, evening, and night shifts, this study advances the understanding of the relationship between chronotype and sleep in rotating shift workers and supports the implementation of work schedules that take into account chronobiological principles.