Both sleep disorders and chronic kidney disease (CKD) are recognized as significant public health concerns. In the general population, sleep disorders have been shown to be associated with frailty in the elderly. This study aims to evaluate the association between sleep duration and trouble sleeping with frailty in CKD patients, as well as the potential interactive effect between these two factors.

This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005-2018. Sleep duration and trouble sleeping was self-reported. Frailty was assessed using a 49-item frailty index. The associations between sleep duration, trouble sleeping, and frailty were analyzed using weighted multivariate logistic regression and restricted cubic splines. Subgroup analysis was conducted to determine the consistency of the study's conclusions across various subgroups.

A total of 5,211 adult CKD patients were included in this analysis. Regression analysis results indicated that short sleep duration (OR = 1.364, 95% CI: 1.152-1.616), long sleep duration (OR = 1.648, 95% CI: 1.259-2.157), and trouble sleeping (OR = 2.572, 95% CI: 2.102-3.147) were significantly associated with an increased risk of frailty in CKD patients, with an interaction between sleep duration and trouble sleeping. Subgroup analysis revealed that the effects of trouble sleeping and sleep duration on frailty symptoms in CKD patients exhibit significant variation across age groups (p < 0.05 for interaction), with no notable differences observed in other subgroups. RCS results demonstrated a U-shaped relationship between frailty and sleep duration, with the lowest risk of frailty at 7.12 h of sleep.

Our findings indicated that both sleep duration and trouble sleeping were significantly associated with frailty in CKD patients, with a notable interaction between these two factors. Therefore, prevention and intervention strategies for frailty in CKD patients should address multiple aspects of sleep health.

Digital technology offers a convenient way to continuously monitor sleep and assess night-to-night variability, particularly in aging populations where traditional self-reported sleep assessments may be limited.

This study aimed to investigate nightly variability in sleep measures obtained via a ring oximeter sensor in older adults and to explore the influence of demographic and cognitive factors on the stability of these metrics.

The study included 62 participants (mean age 74, 67.7 % women, 90.3 % White) from the Boston University Alzheimer's Disease Research Center (BU ADRC) cohort. Each participant wore a SleepImage Ring for at least three consecutive nights. Thirty-four continuous sleep measures, such as mean SpO2 and apnea-hypopnea index within unstable sleep, were analyzed. Night-to-night variability was assessed using intraclass correlation coefficients (ICC) based on a two-way random-effects model. Subgroup analyses examined variability by sex, age, and cognitive status. Group-level changes were assessed using one-way repeated measures ANOVA.

Seven sleep measures demonstrated high stability across nights (ICC: 0.70-0.88), with average heart rate being the most stable, followed by mean SpO2 and apnea-hypopnea indices. Sleep latency exhibited the highest variability. Stability improved between the second and third nights compared to the first and second nights. Women and participants under 75 years old showed greater stability in several metrics, while cognitively intact individuals exhibited more consistent breathing-related measures.

At least three nights of monitoring are required for reliable estimates of key sleep metrics. Expanding studies with larger samples and extended monitoring periods could further elucidate sleep variability as a potential non-invasive marker for general health.

Affective temperaments predispose to life adaptation and affective disorders. The relationship between temperaments and sleep quality is rarely investigated in community-based studies. We hypothesized that cyclothymic-related temperaments relate to worse sleep quality, whereas the hyperthymic temperament favours sleep quality.

We investigated 3701 18 to 65 years old adults from the population-based CHRIS study in Italy. Participants were 54 % females, mean age 38.5 years. The Pittsburgh Sleep Quality Index (PSQI) was the primary outcome score. Five affective temperaments split into quartiles for direct comparison from the TEMPS-M questionnaire were the exposures of interest. Additional covariates comprised sex, age, trait anxiety, and sleep quality-related lifestyles assessed via interviews, self-administered questionnaires or instrumental measurements.

The hyperthymic temperament showed a negative association (better sleep quality) with the global PSQI, whereas the cyclothymic-related temperaments had all associations in opposite direction. While inclusion of trait anxiety appeared to mediate some results, the anxious and other cyclothymic related temperaments were still directly associated with multiple dimensions of poor sleep quality.

The cross-sectional design, possible selection into the study by temperamental background or sleep disorders, and no clinically validated self-assessed psychiatric constructs represent possible weaknesses.

Our findings support the hypothesis of a biological binary diathesis of affective temperaments, with hyperthymic and cyclothymic-related temperaments predisposing sleep quality in an antithetical way.

Wearable consumer health trackers (CHTs) are increasingly used for sleep monitoring, yet their utility remains debated within the sleep community. To navigate these perspectives, we propose pragmatic, actionable recommendations for users, clinicians, researchers, and manufacturers to support CHT usage and development. We provide an overview of the evolution of multi-sensor CHTs, detailing common sensors and sleep-relevant metrics. We advocate for standardized 'fundamental sleep measures' across manufacturers, distinguishing these from proprietary exploratory metrics with future potential. We outline best practices for using CHT-derived sleep data in healthy individuals while addressing current device limitations. Additionally, we explore their role in evaluating and managing individuals at risk for or diagnosed with insomnia, sleep apnea, or circadian rhythm sleep-wake disorders. Guidance is provided on device selection to align with their intended use and on conducting and interpreting performance evaluation studies. Collaboration with manufacturers is needed to balance feature comprehensiveness with clinical utility and usability. Finally, we examine challenges in integrating heterogeneous sleep data into clinical health records and discuss medical device certification for specific wearable CHT features. By addressing these issues, our recommendations aim to inform the usage of CHTs in the global community and to begin bridging the gap between consumer technology and clinical application, maximizing the potential of CHTs to enhance both personal and community sleep health.

Poor sleep is a long-term sequela of cancer and its treatment. Moderate-to-vigorous physical activity (MVPA) is associated with improved health outcomes among cancer survivors and has been suggested as a nonpharmacological method to improving sleep. We evaluated the efficacy of a MVPA intervention to improve sleep among cancer survivors.

We conducted a randomized controlled trial among 415 cancer survivors embedded within the Cancer Prevention Study-3 cohort. Survivors were randomized to a year-long, web-based MVPA program. MVPA was assessed via hip-worn actigraphy at baseline, 3 months, 6 months, and 1 year. We evaluated sleep through the SATED sleep health questionnaire, PROMIS Sleep Disturbance Scale, and device-measured duration and efficiency. An intent-to-treat (ITT) analysis was performed, and secondary analyses were conducted based on measured MVPA levels with generalized additive mixed-effects models.

Survivors reported similar sleep health and patterns to the general US population. We observed no significant changes to sleep between treatment groups in ITT models. Though not statistically significant, there appeared to be heterogeneity based on baseline sleep disturbance (moderate-to-severe sleep disturbance: βSATED = 0.73 (95% CI - 0.09, 1.60) vs mild-to-normal sleep disturbance: βSATED = - 0.26 (95% CI - 0.57, 0.05)). Participants that engaged in more MVPA at the end of the trial reported better sleep health (p-value = 0.04) and less sleep disturbances (p-value = 0.11).

The MVPA intervention was more effective at improving sleep among survivors with sleep disturbances at baseline. Increasing MVPA improved sleep among cancer survivors IMPLICATIONS FOR CANCER SURVIVORS: Increasing MVPA among cancer survivors with sleep disturbances may be a viable strategy for improving sleep.

Excessive daytime napping has been associated with neurodegeneration in older adults, but prior research has focused on nap duration and frequency. Emerging frameworks emphasize the multidimensionality of sleep, but it remains unknown whether other dimensions of napping (e.g., timing, variability) are linked to neurodegeneration. To address this gap, we investigated the associations of daytime nap timing and intraindividual variability of nap duration with incident Alzheimer's dementia and Alzheimer's disease pathology.

We analyzed data from 936 older adults (age range: 56-99; 77% female) in the Rush Memory and Aging Project to examine incident Alzheimer's dementia and from 320 deceased participants (age range at death: 71-105; 70% female) to examine Alzheimer's pathology. The proportions of morning (9-11am) and early afternoon naps (1-3 pm) and the intraindividual variability of nap duration were assessed using actigraphy. Participants completed neurological assessments at baseline and annually for up to 17 years. In deceased participants, amyloid β and neurofibrillary tangles were examined.

Here we show that more morning naps are linked to a higher risk of Alzheimer's dementia, whereas more early afternoon naps are linked to reduced amyloid β levels. Higher intraindividual variability of nap duration is shown to be associated with increased amyloid β and neurofibrillary tangles.

Our findings suggest that specific timing patterns and irregularities in daytime napping are linked to Alzheimer's disease risk and pathology. Multi-dimensional assessments of nap behaviors may aid in risk stratification for neurocognitive impairment and offer a potential target for interventions aimed at promoting healthy cognitive aging.

Depression is common among pregnant women and identifying modifiable risk factors is critical (e.g., sleep). Individual sleep dimensions, e.g., short sleep duration and poor sleep quality, were associated with a higher risk of depression, while whether the multidimensional construct of sleep health could be a protective or risk factor for prenatal depression remains unknown. This study aimed to examine the relationship between multidimensional sleep health and depression during late pregnancy.

This study was conducted among women during late pregnancy (28-40 weeks). Sleep health was measured by self-report questionnaires. Each dimension (sleep quality, duration, efficiency, timing, regularity and daytime sleepiness) was categorized as "good" or "poor". A composite sleep health score was calculated. Depression was measured using the Edinburgh Postnatal Depression Scale. Logistic regression analyses were used to examine the associations between individual sleep health dimensions and depression. Restricted cubic spline analysis was used to explore the dose-response relationship between overall sleep health and depression.

A total of 329 women were included. Their mean age was 31.6 years and the mean gestational age was 34.7 weeks. Sixty (18.2%) had clinically elevated depression. There was a dose-response relationship between composite sleep health score and depression, with a higher sleep health score associated with a lower risk of depression (OR = 0.572, 95%CI = 0.423-0.774, p for linearity < 0.001). Controlling for covariates, poor sleep quality (OR = 3.485, 95%CI = 1.817-6.683, p < 0.001), short sleep duration (OR = 3.462, 95%CI = 1.513-7.924, p = 0.003), and excessive daytime sleepiness (OR = 3.409, 95%CI = 1.804-6.442, p < 0.001) were associated with a higher risk of depression.

Both overall sleep health and individual dimensions (sleep quality, short sleep duration, and daytime sleepiness) were associated with depression during late pregnancy. These findings highlight the potential benefits of maintaining sleep health to achieve mental wellbeing in pregnant women. Healthcare providers may consider adding the assessment and management of sleep health as part of routine prenatal care.

Not applicable.

Although recognition of the significant reciprocal interplay between sleep and social processes has grown over the past two decades, theoretical frameworks conceptualising this interplay have predominantly focused on psychosocial factors. The current lack of attention to putative neurobiological substrates and physiological mechanisms that may facilitate the dynamics of sleep-social relationships limits interdisciplinary research into sleep and clinical treatment of sleep problems and disorders. Thus, this narrative review hypothesises that the neuropeptide oxytocin represents a promising candidate physiological substrate underpinning sleep-social interplay, and integrates the endogenous oxytocin system into a novel tripartite biopsychosocial framework-the sleep-social-oxytocin nexus. The current narrative review outlines the theoretical rationale for the existence of reciprocal sleep-social-oxytocin interactions, and examines the clinical and preclinical evidence for interactions between sleep processes, social processes, and the oxytocin system, highlighting the paucity of experimental research that addresses all three nexus factors. Subsequently, we explore important clinical implications of the sleep-social-oxytocin nexus: comorbidities between sleep, social, and oxytocinergic dysfunction in sleep and other psychiatric disorders, the emerging therapeutic potential of oxytocin-based therapeutics, and potential adjunctive interventions to achieve optimal treatment outcomes. We conclude by proposing future avenues for research and clinical implementation warranted within this space.

Childhood trauma has been found to have serious negative consequences for mental and physical health. However, the precise mechanisms through which trauma influences health outcomes are unclear. Childhood trauma-related disruptions to sleep in adulthood represent an important potential mechanism. Two 7-day multilevel studies investigated the effects of childhood trauma on daily sleep outcomes and stress-related variables and whether the effects of trauma on sleep outcomes were mediated through these stress-related variables (or vice versa). Participants completed the Childhood Trauma Questionnaire before a 7-day online daily diary study. Measures of daily stress, perseverative cognition, and sleep were completed daily. Multi-level modelling found that higher levels of childhood neglect were associated with poorer daily sleep quality, shorter sleep duration, longer sleep onset latency, and higher daily stress and rumination levels. Higher childhood abuse was associated with shorter sleep duration, greater morning tiredness, and higher levels of daily stress, rumination, and worry. Childhood trauma was found also to have bidirectional, indirect effects on sleep quality and morning tiredness through daily stress-related variables. The current findings suggest that interventions aimed at mitigating the negative effects of childhood trauma should also incorporate components that target modifiable risk factors, such as sleep, stress, worry, and rumination.

Sleep is a biological necessity and fundamental to health. However, the associations of sleep patterns (integrating sleep determinants) with DNA methylation age acceleration (DNAm AA) remain unknown. We aimed to investigate the associations of sleep patterns with DNAm AA.

This cross-sectional and prospective cohort study used data from the Dongfeng-Tongji cohort collected from 2013 to December 31, 2018. Sleep patterns were reflected by sleep scores (range 0-4, with higher scores indicating healthier sleep patterns) characterized by bedtime, sleep duration, sleep quality, and midday napping. DNAm AA was estimated by PhenoAge acceleration (PhenoAgeAccel), GrimAge acceleration (GrimAgeAccel), DunedinPACE, and DNAm mortality risk score (DNAm MS). Linear regression models were used to estimate β and 95% confidence intervals (CIs) for the cross-sectional associations between sleep patterns and DNAm AA. Mediation models were applied to assess the mediating role of DNAm AA in the associations between sleep patterns and all-cause mortality in a prospective cohort.

Among 3566 participants (mean age 65.5 years), 426 participants died during a mean 5.4-year follow-up. A higher sleep score was associated with lower DNAm AA in a dose-response manner. Each 1-point increase in sleep score was associated with significantly lower PhenoAgeAccel (β = - 0.208; 95% CI - 0.369 to - 0.047), GrimAgeAccel (β = - 0.107; 95% CI - 0.207 to - 0.007), DunedinPACE (β = - 0.008; 95% CI - 0.012 to - 0.004), and DNAm MS (β = - 0.019; 95% CI - 0.030 to - 0.008). Chronological age modified the associations between higher sleep scores and lower PhenoAgeAccel (p for interaction = 0.031) and DunedinPACE (p for interaction = 0.027), with stronger associations observed in older adults. Moreover, a slower DunedinPACE mediated 6.2% (95% CI 0.8% to 11.5%) of the association between a higher sleep score and a lower all-cause mortality risk.

In this cohort study, individuals with a higher sleep score had a slower DNAm AA, particularly in older adults. A slower DunedinPACE partially explained the association between higher sleep scores and lower all-cause mortality risk. These findings suggest that adopting healthy sleep patterns may promote healthy aging and further benefit premature mortality prevention, highlighting the value of sleep patterns as a potential tool for clinical management in aging.

Improving maternal and child health has been a global priority since the early 2000s, with a focus on reducing perinatal complications and improving overall maternal well-being. Sleep characteristics influence various health outcomes, yet their role in perinatal complications and adverse outcomes remains poorly understood.

A Mendelian randomization analysis was conducted, using seven common sleep characteristics (sleeplessness, sleep duration, getting up in the morning, daytime napping, morning/evening person, narcolepsy, snoring) as exposure factors and twelve common perinatal complications and adverse outcomes (preterm birth, polyhydramnios, slow fetal growth and fetal malnutrition, dystocia, umbilical cord-related complications, postpartum hemorrhage, fetal distress, gestational diabetes, pregnancy hypertension, eclampsia, abruptio placentae, placenta previa) as outcomes. A two-sample Mendelian randomization analysis was performed to infer causal effects.

The inverse variance weighted (IVW) analysis showed that sleeplessness was associated with preterm birth, sleep duration with gestational diabetes, and narcolepsy with pregnancy hypertension and eclampsia. These results were consistently supported by other methods, suggesting that sleep characteristics are causal risk factors for perinatal complications and adverse outcomes.

This study found that sleeplessness is associated with preterm birth, sleep duration with gestational diabetes, and narcolepsy with pregnancy hypertension and eclampsia. These findings contribute to a better understanding of the impact of sleep characteristics on common perinatal complications and adverse outcomes. Targeting sleep interventions, such as improving sleep duration and addressing sleep disorders like sleeplessness and narcolepsy, may reduce the incidence of preterm birth, gestational diabetes, and pregnancy hypertension, offering effective strategies to improve maternal and infant health outcomes.

The increasing prevalence of reduced habitual sleep duration presents a significant public health challenge, impacting cardiovascular health, metabolic function and mental well-being. This umbrella review analyses findings from systematic reviews and meta-analyses to comprehensively evaluate the consequences of sleep deprivation (SD) on health. The databases searched included PubMed, Scopus, and Web of Science. Inclusion criteria focused on adult populations with SD and systematic reviews/meta-analyses. Twenty-nine articles were included in the final synthesis, encompassing a variety of health outcomes. Key findings highlight a U-shaped relationship between sleep duration and all-cause mortality, with both short (<7 h) sleep durations associated with increased risks. SD was a significant risk factor for cardiovascular diseases such as hypertension, stroke and coronary heart disease. Alongside heightened risks of metabolic disorders, like obesity and type 2 diabetes. Moreover, SD contributed to elevated anxiety levels, impaired emotional regulation. As well as increased susceptibility to stress and depressive symptoms. This synthesis underscores the critical importance of maintaining recommended sleep duration (typically 7-9 h for adults) to mitigate these health risks effectively. The findings support the need for robust public health interventions aimed at promoting healthy sleep habits to reduce the burden of associated health conditions and enhance overall well-being.

We examined the associations between sleep characteristics and cardiovascular biomarkers among middle-aged and older adults from the general population and explored interactions by age and sex. Cross-sectional data from wave 6 (2013-2017) of the Doetinchem Cohort Study were used, including 3,437 adults aged 46-85 years. Sleep characteristics were measured with the Medical Outcomes Study Sleep Scale (MOS-SS). Sleep duration was categorized into short/moderate/long; sleep quality was expressed on a scale between 0 and 100 with higher scores reflecting poorer sleep quality (sleep disturbance, shortness of breath or headache, sleep adequacy, somnolence, snoring). Multivariable linear regression analyses were performed to assess the association between sleep characteristics with cardiovascular biomarkers (Body Mass Index (BMI), mean arterial pressure, cholesterol ratio). Effect-modification by sex and age was examined. Associations were adjusted for age, sex, educational level, cigarette smoking, alcohol consumption, physical activity and the other biomarkers. Almost all unhealthy sleep characteristics were associated with higher BMI, e.g. somnolence (β = 0.023, 95%CI: 0.014-0.031) and short sleep duration (β = 0.723, 95%CI: 0.154-1.291). The association of snoring with BMI was stronger for women (β = 0.044, 95%CI: 0.035-0.053). A higher cholesterol ratio was associated with somnolence and snoring (in particular age group 65-85 years). For hypertension no associations were found with one exception: somnolence was associated with lower mean arterial pressure. Unhealthy sleep characteristics seem predominantly associated with a higher BMI. More research is needed into the mechanisms underlying the associations between sleep characteristics and cardiovascular biomarkers.

Negative affect may trigger a variety of psychological and behavioral problems, while physical activity has been shown to reduce negative affect. However, the underlying mechanisms remain unclear. The aim of this study was to investigate the relationship between physical activity and negative affect, specially examining the role of sleep quality in the relationship.

Cross-sectional design was adopted in this study. A total of 557 adolescents participated in the study, completing self-reported questionnaires on physical activity, sleep quality, and negative affect.

Sleep quality mediated the relationship between physical activity and negative affect. There was a positive correlation between "exercise" and "sleep quality" and a negative correlation between "sleep restfulness" and "feeling bored".

This study uncovered the underlying mechanism of physical activity associated with negative affect, offering significance for the prevention and intervention of depression and anxiety disorders.

To explore the relation of self-reported sleep quality with the International Classification of Functioning domains of activity (e.g., physical functioning) and participation (e.g., disability).

Descriptive, secondary, cross-sectional data-analysis SETTING: General community PARTICIPANTS: Community-dwelling older adult, volunteers, n=249 INTERVENTIONS: not applicable MAIN OUTCOME MEASURES: . The Pittsburgh Sleep Quality Index (PSQI), self-reported measures of activity and participation by the Late-Life Function and Disability Instrument (LLFDI), the modified Gait Efficacy Scale for confidence in walking, and performance-based measures of physical functioning (gait speed, Six Minute Walk, Figure of 8 Walk and Short Physical Performance Battery, SPPB). Measures of function were regressed on sleep quality adjusted for age, sex, and comorbidities.

Older adults with good (PSQI≤5) compared to poor (>5) sleep quality reported better function and disability across almost all considered domains (p< 0.05). Effect sizes for self-reported and performance-based measures were comparable and in the small to moderate range.

Among older adults with mild to moderate functional limitations and disability, self-reported sleep quality related broadly to activity and participation. Experimental studies are needed to assess the effects of sleep interventions on activity and participation and understand if sleep quality may represent a novel treatment target in future intervention trials to improve function in older adults.

Differences in sleep duration, quality, and timing are associated with variation in cognition, health outcomes, and quality of life. Genetic studies may help explain the underlying mechanisms of sleep and its relationships to other conditions. Our previous work highlighted risk loci associated with short (<6hrs) and long sleep (>9hrs), using data from the UK Biobank and the Million Veteran Program. We build on this work by conducting a genome wide association study (GWAS) and multi-ancestry meta-analysis of sleep duration as a quantitative trait. We used LD score regression (LDSC) to evaluate the correlation between sleep duration and other traits, and genomic structural equation modelling (genomicSEM) to consider the relationships between traits of interest. We identify 234 independent genome-wide significant loci for sleep duration, of which 143 are novel. The average impact of each risk variant amounts to approximately ±0.86minutes (sd=0.19), with a sum total of ± 220.5 minutes across all genome-wide significant loci. We support previous findings showing the most strongly associated gene is PAX8. Linkage disequilibrium score regression shows that the genetic architecture of sleep duration is largely distinct from other measures of sleep quality and sleep disorders. We see several examples of negative correlation between deleterious traits and the quantitative measure of sleep duration reported here, contrasting with positive associations with long and short sleep (e.g., depression, ADHD, cannabis use disorder, smoking). We derive genomic-SEM models that show short and long sleep load on separate factors, as does overall sleep duration loading alone. This is the largest available GWAS of sleep duration, and the first to extend analyses outside of European ancestry populations. We identify novel loci for sleep duration and provide insight to the shared and unique genetic architecture across multiple sleep and neuropsychiatric traits.

There has been sharp increase in the incidence of hip fractures (HFs) with the increasing aging globally. However, it remains ambiguous regarding the association between HF risk and sleep duration. This study intended to explore the association between sleep duration and HF risk among the older adults.

The study assessed a cohort of 7,540 participants aged at least 60 years old using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2010, as well as from 2013 to 2014. Two distinct groups of HF and non-HF were constructed on the basis of their history of HFs. Based on the self-reported sleep duration through a structured questionnaire, multivariate logistic regression analyses were conducted to examine the relationship between sleep duration and HF risk. In addition, restricted cubic splines (RCS) were used to assess linearity. The receiver operating characteristic (ROC) curve was used to explore the threshold of sleep duration for HF risk.

HFs were found in 129 patients among the 7,540 participants over 60 years of age with mean age of 70.17 ± 7.1 years. Significant differences in sleep duration were observed between the HF and non-HF groups (7.73 ± 1.68 h vs. 7.11 ± 1.42 h; p = 0.006). The multivariate analysis was adjusted for sociodemographic, behavioral lifestyle, and comorbidities. A 1-h increase in sleep duration was associated with higher odds of having prior hip fractures in unadjusted models [odds ratio (OR) = 1.36; 1.11, 1.67; p = 0.004], minimally adjusted models (OR = 1.23; 1.03, 1.48; p = 0.025), second adjusted models (OR = 1.22; 1.02,1.45; p = 0.026) and fully adjusted models (OR = 1.22; 1.03,1.45; p = 0.026). The relationship remained consistent across all four models, indicating the correlation of a longer sleep duration with an elevated HF risk. RCS analysis revealed a statistically linear relationship between sleep duration and HF risk (p-nonlinear = 0.244, p-overall < 0.01). In addition, the identified threshold of sleep duration linked to HF risk was determined to be 7.5 h among the older adults (AUC = 0.611).

This study suggests an linear association between sleep duration and the risk of HFs. Further research is needed to validate these findings and more clearly identify the clinical relevance of this potential relationship.

Both sleep and cognition are multidimensional constructs. Using univariate methods to examine associations between sleep and cognition may inadequately characterize the association between these arrays of variables. The current study used a multivariate approach to identify key sleep metrics and cognitive domains contributing to the maximum sleep-cognition covariance in healthy older adults. In 773 community-dwelling older adults of ages 65-80 years, sleep was assessed using the Oura Ring worn for 15-28 days. Cognition performance in seven domains was assessed using standardized tests. The overall covariance between sleep and cognition was examined by a partial least square correlation (PLSC) analysis. Sleep metrics and cognitive domains contributing to significant PLSC components were identified by bootstrapping. PLSC analysis identified a component that explained 82 % of covariance between sleep and cognition matrices (r = 0.2, p < 0.001). Bootstrapping tests further identified 11 sleep continuity and regularity metrics and 3 corresponding cognitive domains that contributed significantly to the observed covariance. Post-hoc univariate analyses showed that sleep continuity metrics correlated with speed of processing, while sleep regularity metrics correlated with verbal memory, executive functions, and speed of processing. Our results suggest that sleep continuity and regularity may be more sensitive markers of impairments across multiple cognitive domains in healthy aging compared to sleep duration and timing.

Fluctuations in cerebral blood volume (CBV) are a dominant mechanism aiding cerebrospinal fluid (CSF) movement in the brain during wakefulness and non-rapid eye movement (NREM) sleep. However, it is unclear if the amplitudes of CBV oscillations also change in proportion to the changes in amplitude of CSF movement across specific NREM sleep states. It is also not known if the coupling strength between them varies between NREM sleep states. To investigate these relationships, we measured cerebral hemodynamics and craniad CSF movement at the fourth ventricle simultaneously during wakefulness and NREM sleep states using concurrent Electroencephalography and functional Magnetic Resonance Imaging. We found that the amplitude fluctuations of cerebral hemodynamics and CSF oscillations desynchronize from one another only during deep NREM3 state, despite the strong mechanical coupling between CBV changes and CSF movement, which was consistent across all states. This suggests the existence of a different mechanism, linked to the cortical interstitial volume/resistance change, that regulates the NREM3 CSF inflow into the brain.

Short sleep duration (<7 h/day) affects one-third of the population, is implicated in morbidity and mortality from coronary heart disease (CHD), and is driven by an interplay of individual, social, and societal factors.

To review observational and experimental studies that have tested interventions to address short sleep in various clinical presentations (sleep disorders, behaviorally induced short sleep, lack of sleep opportunity) and describe considerations needed for CHD populations.

Few existing interventions have a primary aim to increase sleep duration in individuals with insufficient sleep, and none specifically target individuals with established CHD. Short sleep duration may be modifiable via treatment of insomnia, behavioral sleep extension, and system-level changes to healthcare settings, workplace policies, and communities. With further research on interventions that address diverse phenotypes of short sleep-while assessing long-term cardiometabolic outcomes, patient preferences, and mechanisms-of-action-sleep health could become an important component of CHD secondary prevention.

Mothers with young children tend to have shorter sleep durations than childfree women, but previous research has not considered heterogeneity in sleep duration among midlife mothers who have varying coresidential patterns with their adult, minor, and grandchildren. We examine the distribution of sleep duration across mothers' different intergenerational coresidential contexts (living without any children, living with any minor children, living with only adult children, and living with any grandchildren) and test how these patterns differ across racial/ethnic groups.

Regression analyses estimate sleep duration among a sample of midlife mothers with minor and adult children and grandchildren from the National Longitudinal Survey of Youth 1979 (NLSY79) data (N = 3,300). Moderation analyses consider differences across racial/ethnic groups (non-Hispanic White, non-Hispanic Black, Hispanic).

Relative to the mothers with no coresiding children or grandchildren, mothers with coresiding minor or adult children reported less sleep. However, this gap varies across racial/ethnic groups; specifically, the lower sleep duration for mothers with coresidential children is only significant for White and Black mothers, not Hispanic mothers.

Sleep is a critical health indicator across the life course and a contributor to other health outcomes later in life. Thus, it is important to identify whose sleep is most vulnerable-especially in midlife when sleep trajectories are the groundwork for later-life well-being. We demonstrate the importance of coresidential status with adult and minor children and grandchildren on the sleep of mothers in midlife, drawing specific attention to the differences across racial/ethnic groups.

We performed a systematic review evaluating evidence regarding whether/which 24-h sleep-wake characteristics (e.g. sleep, activity levels, and 24-h rhythms) related to worse BPSDs. We searched PubMed for cross-sectional observational studies of people with dementia examining relationships between actigraphy-measured sleep/wake factors and BPSDs (search completed June 2024). We used the JBI checklists to assess the risk of bias and summarize results within subcategories of sleep/wake (sleep, activity level, and rhythm) and BPSD (composite, agitation, apathy, and mood/affect) dimensions. Thirteen articles met inclusion criteria. Measures of inactivity were most frequently examined and correlated with: (a) greater apathy (6/6 studies); (b) worse depression (only in bivariate analyses in 1 study); (c) more agitation (2/3 studies); and (d) higher composite BPSD scores (1/2 studies). All six studies measuring sleep duration failed to identify associations with BPSDs. Studies examining sleep continuity measures generally found associations, i.e. with a BPSD composite (1 study), agitation (1 study), apathy (1/2 studies), and mood (only in bivariate analyses in 1 study). Studies examining rhythm variables found associations with mood (1 study), mixed evidence for associations with apathy (1 study), and no evidence for association with a BPSD composite (1 study). Actigraphy measures of inactivity are associated with apathy in people with dementia. Due to relatively low numbers of articles, future studies are needed to confirm if inactivity, sleep continuity issues, rhythm disruption, and timing independently relate to BPSDs, and if changes in objective sleep/wake measures, e.g. increase in activity following intervention, signal/mediate improvements in BPSDs.

Sleep is regarded as one of the most crucial factors in keeping a healthy lifestyle. To function normally, a person needs at least 6-8 h of sleep per day. Sleep influences not only our mood but also the efficiency with which we complete tasks. Sleep disorders exhibit diverse etiologies across different conditions and populations, with genetic and environmental factors playing a significant role in their development. Many issues emerge as a result of inadequate sleep. Unhealthy food and lifestyle choices have increased our susceptibility to sleep disorders. A well-balanced diet rich in essential vitamins and minerals can have a profound impact on sleep patterns, enhancing both the duration and quality of rest. The primary categories of sleep disorders include insomnia, sleep apnea (SA), narcolepsy, parasomnias, circadian rhythm disorders, and restless legs syndrome (RLS). The drugs used to treat sleep disorders are primarily habit-forming and have a history of withdrawal effects. This insufficiency in medication has prompted the hunt for newer, better options. Nutraceuticals are well-suited to the treatment of such illnesses. Its non-toxic, non-habit-forming properties, and practical efficiency have made it an outstanding choice. This review provides nutraceuticals used in sleep disorders. A comprehensive literature search was conducted utilizing several databases, including Google Scholar, Elsevier, Springer Nature, Wiley, PubMed, and EKB. Nutraceuticals are products that employ food or dietary components to treat or prevent disease. In the therapy of sleep disorders, nutraceuticals such as Artemisia annua, valerian, rosemary, jujube, Passionflower, lemon balm, ashwagandha, kava-kava, lavender, and chamomile have been shown to have remarkable benefits. These remedies exert their effects through multiple mechanisms, both directly by modulating neurotransmitter and hormonal pathways within sleep circuits, and indirectly by enhancing sleep quality through the alleviation of stress, inflammation, and oxidative stress. Clinical studies were piloted to validate the efficacy of natural sleep aids. Future research should focus on elucidating the precise mechanisms through which natural products influence sleep.

Pregnant women often report poor sleep quality and increased sleep disturbances, especially in the second and third trimesters. Studies showed inconsistent prevalence of poor sleep quality among pregnant women, with unclear predictive factors. Furthermore, physical, psychological, and socioeconomic factors may negatively affect sleep in pregnant women.

The study aims to explore sleep quality and to identify possible physical, psychological, and socioeconomic predictors of poor sleep quality among pregnant women.

The cross-sectional study was conducted from July 2021 to January 2022. Pregnant women in their second and third trimesters were recruited during their regular visits to the gynecology and obstetrics clinics and hospitals in northern Jordan. Using convenience sampling, two hundred six participants completed questions about sociodemographics, pregnancy, and women's health history using the interviewer-administered method. Additionally, participants completed the Pittsburgh Sleep Quality Index (PSQI), Pregnant Physical Activity Questionnaire (PPAQ), and Hospital Anxiety and Depression Scale (HADS). Descriptive statistics were used to analyze sleep quality, and a multivariable linear regression model was used to identify significant predictors of the PSQI total score.

206 pregnant women participated: 23.3% in the second trimester and 73.3% in the third, with a mean age of 30.6 years. 76.6% of pregnant women reported poor sleep quality (PSQI total score >5). The results showed that increased age (B= 0.125, 95% CI [0.042 - 0.208], p< 0.003), Low educational level (high school or lower vs higher education) (B= 1.097, 95% CI= [0.033-2.161], p= 0.043), having leg cramps (B= 1.578, 95% CI [0.627-2.529], p< 0.001), anemia during pregnancy (B= 1.311, 95% CI [0.131-2.492], p= 0.030), and increased anxiety (B= 0.355, 95% CI [0.258 - 0.452], p< 0.001) are significant predictors poor sleep quality.

Poor sleep is highly prevalent among pregnant women due to factors such as age, education, anxiety, and medical conditions. Clinicians should consider this high prevalence and the possible associated factors in assessing and managing sleep quality to improve pregnant women's health and quality of life.

Poor sleep health has wide-ranging consequences for general health. The year 2020 marked the first year of the COVID-19 pandemic throughout the world, an event that introduced dramatic disruptions to daily life. Studies conducted during the first wave of the pandemic reported a decrease in sleep quality but also an increase in sleep duration, which contradicts the simultaneous decrease in sleep duration reported in Canada. However, prior studies were not representative of the Canadian population. To assess pandemic-induced health disruptions, we investigated sleep health trajectories and health correlates during the first wave of COVID-19 in a longitudinal nationally representative sample of Canadians. We aimed (1) to determine the trajectories of sleep duration and sleep quality, (2) to identify health factors associated with unstable sleep trajectories, and (3) to explore associations between sleep trajectory groups.

A nationally representative sample of 2,246 individuals residing in Canada was surveyed 6 times between April and July 2020. Participants reported on their sleep and health-related factors (e.g., sociological and demographic factors). We first used latent class growth analysis to identify sleep trajectories. We then used multinomial logistic regression models to determine the relationships between health-related predictors and trajectory groups. Finally, we used joint trajectory analysis to explore the relationships between sleep duration trajectories and sleep quality trajectories.

We identified four constant sleep quality trajectories (6.7%, 37.1%, 45.5%, and 10.7% of the sample). We identified two sleep duration trajectories, one of stable shortshort and stable sleep (33.9% of the sample), and one of long and decreasing (-2.32 min/2 weeks) sleep (66.1% of the sample). Living with someone predicted longer and decreasing sleep duration. Being 25 or older was associated with a lower likelihood of belonging to the long and decreasing sleep duration trajectory. There was a 98.9% likelihood of belonging to the long and decreasing sleep duration trajectory for those belonging to the higher sleep quality trajectory.

In our study, we found no convincing evidence that sleep health indicators deteriorated during the first wave of COVID-19 in Canada. The overall stability of sleep suggests that sleep is likely governed by factors that remained stable.

The Regularity, Satisfaction, Alertness, Timing, Efficiency, and Duration (RU-SATED) version 4.0 is a 6-item tool designed to evaluate sleep health. This study examined the psychometric properties of the traditional Chinese version of RU-SATED (RU-SATED-TC) scale.

A cross-sectional survey was conducted on December 9, 2023 for 4weeks. Participants were recruited via a Facebook page to complete an online questionnaire assessing sleep, mental, and physical health. The RU-SATED-TC uses a 5-point Likert scale, with a total score range from 0-24. The psychometric properties of the RU-SATED-TC, including internal consistency, concurrent validity, 1-week test-retest reliability, and factor analysis, were evaluated.

A total of 1043 participants (67.3% female, 55.9% aged 18-39) completed the survey. The average RU-SATED-TC scale score was 12.24 (SD = 3.53). Confirmatory factor analyses showed an acceptable model fit (CFI = 0.94, TLI = 0.89, RMSEA = 0.09, and SRMR = 0.04), supporting a two-factor structure of "consistency and effectiveness" and "timing." "Efficiency" did not load on any factors. The Cronbach's alpha was 0.608, with corrected item-total correlations ranged from 0.099-0.530. The "timing" item showed the weakest item-total and concurrent correlations with other sleep outcome measures. The 1-week test-retest reliability was good to excellent (ICCs ranging from 0.605-0.843), except for item 4 (efficiency), which had fair reliability (ICC = 0.464).

The RU-SATED-TC scale appears to be a reliable valid tool for measuring sleep health in Chinese Hong Kong residents. Nevertheless, future research may be needed to refine the "timing" item.

The circadian system maintains optimal biological functions at the appropriate time of day, and the disruption of this organization can contribute to the pathogenesis of cardiometabolic disorders. The timing of eating is a prominent external time cue that influences the circadian system. "Chrononutrition" is an emerging dimension of nutrition and active area of research that examines how timing-related aspects of eating and nutrition impact circadian rhythms, biological processes, and disease pathogenesis. There is evidence to support chrononutrition as a form of chronotherapy, such that optimizing the timing of eating may serve as an actionable strategy to improve cardiometabolic health. This report summarizes key information from the National Heart, Lung, and Blood Institute's virtual workshop entitled "Chrononutrition: Elucidating the Role of Circadian Biology and Meal Timing in Cardiometabolic Health," which convened on May 2 to 3, 2023, to review current literature and identify critical knowledge gaps and research opportunities. The speakers presented evidence highlighting the impact on cardiometabolic health of earlier and shorter eating windows and more consistent day-to-day eating patterns. The multidimensionality of chrononutrition was a common theme, as it encompasses multiple facets of eating along with the timing of other behaviors including sleep and physical activity. Advancing the emerging field of chrononutrition will require: (1) standardization of terminology and metrics; (2) scalable and precise tools for real-world settings; (3) consideration of individual differences that may act as effect modifiers; and (4) deeper understanding of social, behavioral, and cultural influences. Ultimately, there is great potential for circadian-based dietary interventions to improve cardiometabolic health.

BackgroundOur understanding of sleep during early stroke care and its impact on rehabilitation outcomes remains limited. The objectives of this work were to (1) evaluate multidimensional sleep health and disruptions during acute inpatient rehabilitation for individuals with stroke, and (2) explore the relationship between sleep health/disruptions and functional recovery.MethodsData from 103 individuals with stroke were analyzed during acute inpatient rehabilitation. Sleep health/disruptions were assessed via patient reports, actigraphy, and biometric sensors. Functional outcomes were measured at admission and discharge. Generalized Linear Models (GLMs) were used to describe changes in sleep health over time, and multivariate regressions analyzed sleep disruptions and sleep-related predictors of functional recovery.ResultsOver inpatient stays, sleep improved with a 23% reduction in wake after sleep onset and 15% fewer multiple overnight disruptions. GLMs revealed that improved sleep quality was associated with reduced overnight activity and increased heart rate over time. Poor initial sleep quality and cognitive status were associated with more overnight disruptions. Lastly, minimal associations were found between sleep health and functional recovery.ConclusionsSleep health during inpatient stroke rehabilitation is generally poor, though improves over time. Sleep is affected by neurological recovery and hospital environment. Overnight activity and autonomic biomarkers were associated with perceived sleep health, and both physiological and environmental factors triggered disruptions. The association between functional recovery and indirect indicators of sleep health requires further investigation. These findings reveal new insights about inpatient sleep which can inform early, targeted sleep interventions to optimize post-stroke outcomes.SIESTA, ClinicalTrials.gov (NCT04254484).

Pregnant women often experience subjective sleep disturbances shown to be associated with maternal and fetal outcomes. However, subjectively experienced sleep often deviates from objective measurements. Therefore, the aim of this study was to explore the relationship between objectively measured sleep in early to mid-pregnancy and maternal and fetal outcomes and inflammatory biomarkers.

A total of 1,610 pregnant women aged 18 or older from the Safe Physical Activity in Pregnancy (SPAP) study were recruited during early (week 10-14) to mid-pregnancy (week 16-19). Blood samples were taken and sleep was monitored using an Actiwatch, tracking total sleep time, sleep efficiency, wake after sleep onset, and sleep onset latency for 7 days in early to mid-pregnancy. A combined sleep categorisation was created using total sleep time and sleep efficiency to categorise participants into three sleep quality groups: Good, Intermediate, and Poor. Maternal and fetal outcomes were collected via questionnaires, medical records, and plasma samples were analysed using the Olink cardiovascular paneI Il (n = 407).

A total of 1,444 participants were included. The women were categorized as good sleepers (50.4%), intermediate (32.6%), or poor sleepers (17.0%) based on the distribution of the participant's sleep parameters. Poor sleep was more common in women born outside Europe, those with higher pre-gestational BMI, and those with pre-pregnancy diabetes. Sleep groups did not differ in metabolic factors. Poor sleep was associated with an increased likelihood of requiring an emergency caesarean section (AOR = 1.86, 95% CI 1.13-3.05). No significant associations were found for other outcomes such as pre-eclampsia, premature birth, small for gestational age etc. Nine inflammatory biomarkers were significantly lower in poor sleepers, while one marker was higher.

Poor sleep in early to mid-pregnancy was more common in pregnant women with pre-pregnancy diabetes, obesity, and those born outside of Europe. Poor sleep was associated with a higher likelihood of emergency caesarean section, but no other maternal or fetal outcomes. An overall trend was observed towards lower levels of inflammatory markers in women that slept poorly; however, additional studies are needed to better understand the immune system's role in the relationship between sleep, maternal health, and maternal and fetal outcomes. Possible mechanisms underlying these associations warrant further research.

Negative reinforcement is proposed to mediate associations between sleep and alcohol use, especially among people with depression and/or anxiety symptoms. Worse sleep (e.g., shorter duration, less efficiency, more irregular timing) exacerbates negative emotions, which alcohol may temporarily relieve. Not yet examined, we propose sleep indirectly impacts early stages of alcohol use via differences in negative reinforcement learning (NRL), since sleep impacts emotion, reward response, and learning. The current study aimed to replicate associations between sleep and alcohol use, test associations with NRL, and examine indirect associations between sleep health and alcohol use via NRL among 60 underage college students (ages 18-20 years, 77% female) varying in depression and anxiety symptoms. Participants wore Fitbit smartwatches and completed daily diaries measuring sleep and substance use for ∼14 days before completing two computer tasks assessing social (SNRL) and monetary (MNRL) negative reinforcement learning. Robust generalized linear models tested direct associations within the proposed model. SNRL performance was positively associated with alcohol use, but no other associations were observed. Statistical mediation models failed to indicate indirect effects of sleep on alcohol use via SNRL or MNRL performance. Post-hoc exploratory models examining depression and anxiety symptoms as moderators of direct associations indicated several interactions. Positive associations between sleep timing variability and alcohol use were weakened at higher anxiety symptom severity and stronger at higher depression symptom severity. The positive association between SNRL performance and alcohol use was also stronger at higher depression symptom severity. Among students with elevated depression symptoms, variable sleep timing and stronger SNRL performance were independently associated with more alcohol use, but indirect effects were not supported. Future research should replicate findings, confirm causality of interactions, and examine sleep timing and behavioral responses to negative social stimuli as targets for improving alcohol-related outcomes among underage college students with elevated depressive symptoms.

This study assessed the feasibility of Sleepfit, an app-based sleep intervention for shiftworkers, to evaluate participant reach, engagement, and interaction.

The RE-AIM framework guided the feasibility assessment. Participants from various shiftwork industries (e.g. healthcare, mining) completed a 14-day trial of the Sleepfit app, alongside baseline and post-intervention surveys. Descriptive statistics were used to evaluate participant enjoyment and engagement, including daily app usage and the number of activities completed.

Among the 110 enrolled shiftworkers, 53 (48%) completed post-intervention assessments, and 34 (30.9%) adhered to the full study protocol. Of those who completed baseline surveys, 85.4% downloaded and used Sleepfit, engaging with an average of 17.3% of available activities, with shiftwork-specific modules like "Coping with Shiftwork" showing the highest engagement. Participants cited lack of time, inconvenience, and losing interest as reasons for discontinuing app use.

This study indicates the potential feasibility of app-based interventions like Sleepfit to improve shiftworkers' sleep health through tailored, relevant content. Future studies should consider longer durations and larger samples, incorporating wearable technology to enhance data accuracy and assess sustained effects across varied shift schedules.

Our objectives were to compare sleep health composite dimensions and chronotype in children and adolescents with and without type 1 diabetes (T1D) and to explore the relationship between sleep and glycemic variability in T1D.

The study comprised 84 participants with T1D aged between 6 to 18 years and age- and sex-matched controls. The sleep health composite was measured using actigraphy, sleep diaries, and self or parental reports. Sleep disturbance was evaluated using the DSM-5 Level 2 Sleep Disorders Scale Short Form. Chronotype was determined using the Children's Chronotype Questionnaire.

The median total sleep health composite score for both the T1D and control groups was 3.0 (3.0-4.0) (P = .485). Sleep quality was reported as good by 89.3% of participants with T1D and 96.4% of controls (P = .072). Objective data from actigraphy indicated poor sleep quality in 56% of participants with T1D and 59.5% of controls (P = .639). Additionally, 88% of participants with T1D and 84.5% of controls had inadequate total age-appropriate sleep duration (P = .501). Among participants with T1D, those with a stable glycemic variability (coefficient of variation < 36%) had an earlier midpoint sleep (P = .008).

Our study indicates that there are no significant differences in the sleep health composite and chronotype between children and adolescents with and without T1D. Although most participants reported good sleep quality, objective assessments indicated poor sleep quality. These findings suggest that children and adolescents may overestimate their sleep quality.

Registry: ClinicalTrials.gov; Name: Sleep Patterns and Chronotype in Children With and Without Type 1 Diabetes; URL: https://clinicaltrials.gov/study/NCT06318611; Identifier: NCT06318611.

İpar N, Boran P, Barış HE, et al. The sleep health composite and chronotype among children and adolescents with type 1 diabetes compared to case-control peers without diabetes. J Clin Sleep Med. 2025;21(5):825-834.

Poor sleep health is associated with cardiometabolic disease and related risk factors, including heart disease, stroke, elevated blood pressure and lipid levels, inflammation, glucose intolerance, obesity, physical inactivity, poor diet, unhealthy substance use, poor mental health, and increased all-cause and cardiovascular mortality, and is associated with social determinants of cardiovascular health and health disparities. Therefore, sleep duration has been recognized by the American Heart Association as one of Life's Essential 8. Although chronic sleep duration is the sole metric used in Life's Essential 8, sleep health represents a multidimensional construct. This scientific statement outlines the concept of multidimensional sleep health (sleep duration, continuity, timing, regularity, sleep-related daytime functioning, architecture, and absence of sleep disorders) as it applies to cardiometabolic health. Considerations of how these dimensions are related to cardiometabolic health and patterned by sociodemographic status are explained, and knowledge gaps are highlighted. Additional data are needed to understand better how these various dimensions of sleep should be assessed and how interventions targeting sleep health in clinical and community settings can be leveraged to improve health.

Comparing sleep and rest-activity rhythms across different cognitive aging pathways can identify novel risk factors and potential mechanisms. However, our current understanding is restricted by differences in sleep measurement, limited longitudinal data, and heterogeneous cognitive aging processes.

We applied cubic splines to longitudinal self-reported sleep and actigraphy data from 1449 participants in the Rush Memory and Aging Project and quantified differences in the levels and trajectories of sleep amount, regularity, and timing within and between three cognitive aging pathways: normal, stable mild cognitive impairment, dementia.

Sleep amount was lowest in the dementia pathway prior to cognitive impairment but increased with age, most rapidly after dementia. Regularity declined across all pathways, most rapidly after cognitive diagnoses. Timing advanced across all pathways.

Shorter sleep amount in cognitively healthy older adults may be a risk factor or prodromal indicator of dementia, while longer sleep amounts and decreasing regularity may reflect neurodegeneration.

We quantified longitudinal changes in sleep across three cognitive-aging pathways. We incorporated both subjective and objective measures of sleep health. Self-report duration increased noticeably from before to after cognitive diagnosis. Sleep irregularity increased most prominently after cognitive diagnosis. Advances in sleep timing occurred in both normal and pathological aging.

To map the extent, range and nature of studies that examine sleep of nurses and identify how sleep has been examined in relation to the different aspects of nurses' health and nursing work and practice.

A scoping review.

A search of five electronic databases including MEDLINE, Embase, EMcare, PsycINFO (using the Ovid platform) and Scopus was undertaken in May 2023 to identify primary studies that examined nurses' sleep.

This review was undertaken in accordance with the Joanna Briggs Institute methodology for scoping reviews and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist.

This review included 1040 studies from a wide range of countries. Most studies were observational in design and examined nurses working in the acute care sector. Studies were mostly descriptive (32%) or discussed sleep as a workforce issue (21%) or lifestyle behaviour that is important for the health of nurses working clinically (27%). A range of different sleep parameters were examined, with sleep quality the focus of most studies, especially in relation to well-being.

There has been an exponential increase in the number of studies that examine nurses' sleep. Efforts to examine the sleep of nurses are beginning to align with contemporary understandings and methodological approaches to examining sleep. However, this field of research could benefit from better consistency in the definition and reporting of sleep, prioritising objective measures of sleep and improving understanding of the relative and combined importance of different dimensions of sleep.

This review provides a comprehensive overview of studies that examine nurses' sleep. Findings highlight areas of growing interest, areas in need of further research and methodological considerations to strengthen research in this field.

No patient or public contribution. REGISTRATION DOI: https://doi.org/10.17605/OSF.IO/RZC4M.

Adequate sleep is crucial for healthy development, contributing significantly to physical and mental well-being. While research on paediatric sleep is expanding, there remain several open questions. This narrative review provides an overview of our current knowledge on paediatric sleep health and identifies literature gaps, considering factors such as age, gender, cultural differences, and the interplay between sleep, physical activity, nutrition, and mental health. It also considers sleep health in the more specific group of children with neurodevelopmental disorders. By viewing paediatric sleep health as a multidimensional construct, this review discusses age-specific issues, including the different factors affecting satisfaction, daytime alertness, sleep timing, efficiency and duration, and sleep-related behaviours. While gender differences in sleep health become apparent after puberty, few studies have addressed sex differences in children or different parental attitudes toward sleep in boys and girls. Cultural differences in sleep duration, timing, and setting are reported from infancy through adolescence; however, the cultural influence on sleep health, particularly during adolescence, remains unclear. This is crucial when considering the effects of screen time, smartphone use, and social media exposure on sleep. Further research is required to understand how sleep, nutrition, and physical health interact throughout the developmental span. Additionally, this review underscores the protective nature of sleep for adolescent mental health and for the management of emotional and behavioural problems in children with neurodevelopmental disorders. The review identifies critical areas for future research to enhance our understanding of paediatric sleep health and develop more effective and tailored interventions and preventive programmes.