OBJECTIVES:Sleep and mood are homeostatically regulated systems essential for mental and physical health. Understanding how sleep timing and mood dynamically influence each other, and which individual traits moderate this coupling, can clarify mechanisms of mood regulation. Our objective was to examine bidirectional associations between sleep and daily mood under naturalistic conditions using objective sleep measurements and to identify personality and psychiatric traits that moderate these relationships. METHODS:Data came from the Budapest Sleep, Experiences and Traits Study, a 7-day observational study of 258 healthy adults (1712 nights). Objective sleep was recorded using Dreem2 EEG headbands, and subjective sleep quality was assessed by the Groningen Sleep Quality Scale. Daily mood was measured with the Positive and Negative Affect Schedule. Bidirectional multilevel models tested within-person associations between affect and sleep, while random slopes models examined individual differences. RESULTS:A robust negative feedback loop emerged between sleep timing and positive affect: higher evening positive affect predicted later sleep onset (r= 0.13, P<.001), while later sleep onset predicted lower next-day positive affect (r= -0.17, P<.001). This bidirectional link was absent for negative affect and objective sleep quality. Trait activity (r = -0.21), extraversion (r = -0.29), and conscientiousness (r = -0.19) amplified the effect, whereas neuroticism (r = 0.17) and alexithymia (r = 0.18) attenuated it. CONCLUSIONS:Sleep timing, rather than sleep quality, plays a central role in daily mood regulation through a homeostatic feedback mechanism. Personality and affective traits shape this loop, highlighting sleep timing as a potential target for mood stabilization.
Indigenous communities face disparities in sleep outcomes, which may contribute to broader health inequities. Existing reviews of Indigenous sleep health adopt a regional focus or limit attention to specific sleep disorders. The objective of this scoping review was to describe patterns of sleep problems and sleep health in Indigenous peoples globally. MEDLINE, Embase, and Web of Science were searched from inception to February 25, 2025. Any studies that described the prevalence of a sleep problem in an Indigenous sample were included. A total of 47 studies were included in the review, with sample size ranging from 50 to 810,168. Most studies were conducted in community settings (85%), with self-report questionnaires being the most common method used to assess sleep problems (83%). Prevalence estimates of sleep problems among Indigenous samples ranged widely, with Indigenous communities having generally higher prevalence of sleep problems relative to non-Indigenous comparator groups. Socioeconomic deprivation, housing conditions, mental health comorbidities, behavioral factors, and systemic barriers to health care access were consistently reported as factors associated with sleep health. The findings of this review highlight a disproportionate burden of sleep problems as well as sleep health disparities in Indigenous communities around the world. Prospero CRD420251018819
OBJECTIVES:Multidimensional sleep health captures the 24-hour experience of sleep as regularity, satisfaction, alertness, timing, efficiency, and duration. However, most evidence comes from adults. Adolescents have unique sleep needs that may not be fully represented. This study aimed to empirically identify and validate dimensions of adolescent sleep health and evaluate methods relevant to their assessment. METHODS:We analyzed subjective and objective sleep measures from 347 adolescents in the Penn State Child Cohort (16.3±2.2 years; 45.8% female; 22.2% race and ethnic minority). Exploratory factor analysis was conducted in a random 40% subsample to identify latent dimensions of self-reported, actigraphy, and polysomnography measures, followed by confirmatory factor analysis in the remaining 60% to test model validity. RESULTS:Exploratory factor analysis identified 6 dimensions: Breathing, Efficiency, Duration, Regularity/variability, Satisfaction, and Timing, collectively referred to as the BEDReST framework, explaining 63% of the variance. Confirmatory factor analysis of individual factors within the 6-factor structure demonstrated good to excellent fit (Comparative Fit Index = 0.95-1.00; Tucker-Lewis Index = 0.86-1.00; Root Mean Square Error of Approximation = 0.06-0.15; Standardized Root Mean Square Residual < 0.08). All dimensions, except Satisfaction, included objective measures. CONCLUSIONS:We empirically derived and validated 6 dimensions of adolescent sleep health, the BEDReST framework, using a multimethod approach. This approach highlighted the importance of including objective sleep data to comprehensively capture adolescent sleep health. The BEDReST framework extends existing models by incorporating sleep-disordered breathing and provides a foundation for refining the conceptualization and measurement of sleep health during adolescence.
OBJECTIVES:While insufficient sleep is known to contribute to motor vehicle accident (MVA) mortality, limited research has focused on the impact of self-reported sleep duration and quality. This study aims to investigate the relationship between sleep duration, sleep quality, and MVA mortality. METHODS:In a cohort of 482,507 participants aged 20 years or older, medical screenings were conducted from 1996 to 2017. Sleep characteristics, including self-reported duration, quality, and sleeping pill use, were assessed via self-reported questionnaires. MVA mortality was identified using International Classification of Diseases-9 and ICD-10 codes. Cox proportional hazards models were applied to calculate hazard ratios (HRs) for MVA mortality. RESULTS:There were 37,541 deaths, including 791 due to accidents. Approximately 70% of participants reported sleeping 6-8 hours per night, while 20.2% reported 4-6 hours, 1.2% less than 4 hours, and 8.7% more than 8 hours. After adjusting for covariates, participants with a shorter sleep duration (4-6 hours) had a 30% increased risk of MVA mortality compared with those with 6-8 hours (HR: 1.30; 95% CI: 1.09-1.55). Those with sleep durations exceeding 8 hours had a similar 31% increase in risk (HR: 1.31; 95% CI: 1.05-1.64). This risk was further elevated among smokers, frequent alcohol drinkers, and sleeping pill users. CONCLUSIONS:Both self-reported shorter sleep durations (less than 6 hours) and longer sleep durations (more than 8 hours) are associated with elevated MVA mortality risk, forming a U-shaped relationship. This risk is amplified among smokers, frequent alcohol consumers, and sleeping pill users.
Objectives Insomnia is highly prevalent in the general population. We aimed to identify long-term insomnia trajectories, examine baseline predictors of trajectory membership, and assess how lifestyle factors and health outcomes evolve across these trajectories. Methods Data were obtained from the Swedish Longitudinal Occupational Survey of Health, including 15,807 participants with repeated sleep assessments collected biennially between 2010 and 2018. Latent class trajectory modeling identified 4 distinct insomnia trajectories. Multinomial logistic regression examined baseline predictors of trajectory membership, and repeated-measures regression models assessed longitudinal associations with lifestyle factors and somatic and psychiatric morbidity. Results Four trajectories were identified as follows: low and stable, increasing, decreasing, and persistently high insomnia probability. Compared with the low and stable trajectory, all higher-risk trajectory groups at baseline consisted of a higher proportion with female sex, younger age, lower physical activity, higher body mass index, and a higher prevalence of sleep apnea and neurological and psychiatric disorders. During follow-up, body mass index increased more steeply for those in the increasing and persistently high trajectories, whereas physical activity increased in the decreasing trajectory. Individuals with persistently high insomnia trajectory also showed a more rapid increase in psychiatric disorders and sleep duration compared to those who remained free of disease. Conclusions Higher-risk insomnia trajectories are associated with adverse lifestyle profiles and increasing morbidity over time, whereas decreasing insomnia probability is accompanied by increasing physical activity. These findings highlight the dynamic and heterogeneous nature of insomnia and the relevance of lifestyle factors and evolving morbidity in long-term insomnia patterns.
Rotating shift work, including night shifts, disrupts circadian rhythms and the sleep-wake cycle, contributing to sleep disturbances, cognitive impairment, and increased medical errors among healthcare workers. We evaluated associations between sleep quality and quantity, rotating shift work characteristics, cognitive function, and work performance among healthcare workers, and to identify moderating factors influencing these relationships in a systematic review. Six databases (PubMed, EMBASE, Scopus, Web of Science, Cochrane Library, and PsycINFO) and Google Scholar were searched from inception to April 30, 2026. Eligible experimental or observational studies were published in English and assessed sleep, cognitive functions, or work performance in rotating shift healthcare workers. Risk of bias was assessed using the Newcastle-Ottawa Scale, RoB 2, and ROBINS-I V2 tools. Findings were synthesized narratively. We included 59 studies involving 17,660 participants. Poor sleep quality affected 52% to 90% of rotating night shift healthcare workers and was associated with impaired attention (50% higher at night vs. day), memory (OR = 1.86), medical errors (OR = 1.78-2.1), and slowed reaction time after 6 to 7 consecutive nights (comparable to BAC 0.05%). Counterclockwise and rapidly rotating schedules were associated with 1.3-hour less sleep, 44% greater attentional problems, and 36% to 50% greater work-life interference than clockwise rotation. Limiting shifts to ≤16 hours reduced attentional failures by 50%, while scheduled 30-minute naps reduced sleepiness (d = 0.43) and improved cognition (d = 0.23-0.33). Overall, rotating shift and night work substantially impair sleep, cognition, and occupational functioning among healthcare workers. Clockwise rotation, slower rotation, scheduled naps, and limiting extended shifts may mitigate these impairments. PROSPERO registration CRD420251128550.
OBJECTIVES:Sleep inequities are marked and persistent in the U.S., yet there remains limited research examining the patterning of adverse sleep outcomes across intersecting dimensions of social identity. This study's objective was to estimate the prevalence of short and long sleep duration across population subgroups jointly defined by racialized identity, sex, and sexual identity, and quantify inequities. METHODS:Data came from the 2022 Behavioral Risk Factor Surveillance System (N = 235,326). We implemented Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) by grouping participants into 20 intersectional social strata and fitting Bayesian multilevel logistic models to obtain intersectional social stratum-specific prevalence estimates for each outcome. Intersectional social strata were jointly defined by racialized identity (Black, Latine, White, multiracial/other) and sex/sexual identity (heterosexual-cisgender males, heterosexual-cisgender females, LGBQ-cisgender males, LGBQ-cisgender females, trans and gender nonconforming people). RESULTS:Multiply marginalized groups (e.g., people of color who are also LGBQ+) had the highest prevalence of both short and long sleep duration. CONCLUSIONS:Equity-focused policies and interventions targeting sleep health should center the needs and priorities of multiply marginalized groups who are at particularly elevated risk of both short and long sleep duration.
OBJECTIVES:Healthy sleep is associated with lower stroke risk, but the underlying metabolic mechanisms remain poorly understood. We investigated whether a nuclear magnetic resonance-derived metabolic signature mediates this association. METHODS:This prospective cohort study included 200,729 UK Biobank participants (mean age 56.48±8.10 years, 53.80% female) free of stroke at baseline. A healthy sleep score (0-6) was derived from 6 behaviors as follows: chronotype, sleep duration, insomnia, snoring, daytime dozing, and ease of getting up. Sleep-related metabolites among 249 plasma nuclear magnetic resonance biomarkers were selected using elastic net regression and combined into a metabolic signature score. Associations with incident stroke were estimated using Cox models, and mediation was assessed using counterfactual analyses over a median 12.6 -year follow-up. RESULTS:During 2,530,392 person-years, 5140 incident strokes occurred. Elastic net identified 35 sleep-related metabolites, mainly reflecting lower glycoprotein acetyls and VLDL particles and higher polyunsaturated fatty acids, including DHA and linoleic acid. Each 1-point higher healthy sleep score was associated with lower risk of stroke (HR 0.97; 95% CI, 0.95-0.99). Each 1-SD higher metabolic signature score was associated with a reduced risk of stroke (HR 0.93; 95% CI, 0.90-0.96), and the highest versus lowest tertile had lower risk (HR 0.86; 95% CI, 0.79-0.93). The signature mediated 8.63% (95% CI, 3.65%-18.25%) of the sleep-stroke association, with omega-3 fatty acids, HDL subfractions, amino acids, and GlycA as major contributors. CONCLUSIONS:A nuclear magnetic resonance-derived metabolic signature partially mediates the protective effect of healthy sleep on stroke risk through lipid metabolism, amino acid homeostasis, and systemic inflammation pathways, highlighting potential metabolic targets for stroke prevention in individuals with sleep disturbances.
PURPOSE:We aimed to demonstrate a method for identifying subgroups that may have experienced heterogeneous effects of a delayed high school start time policy. This approach could suggest how the implementation of a policy might be prioritized. METHODS:In the START study, students (n = 2230) from 5 schools in the Twin Cities, Minnesota metropolitan area were followed over 3 waves of annual data collection. All schools started early (7:30 or 7:45 am) at baseline. Two "policy change schools" had set start times later by roughly 1 hour by follow-up 1; 3 "comparison schools" maintained their early start time throughout the study. We employed generalized linear mixed model trees, a data-driven method that detects potential treatment-subgroup interactions while accounting for the clustered nature of the data. The stability of variable selection was assessed using a subsampling approach. RESULTS:Among Asian and Black students whose parents did not complete college (a subgroup identified by the generalized linear mixed model trees), those who attended policy change schools gained over 1 hour and 15 minutes of sleep per night, relative to comparison school students. The other subgroups had lesser treatment effects. With body mass index, minimal differences were observed between subgroups identified by generalized linear mixed model trees. CONCLUSION:We showed how the generalized linear mixed model trees method can enable identification of groups that may experience differing impacts from a population-based policy. However, this analysis was meant primarily as a demonstration and the results should be seen as preliminary and hypothesis generating, due to the small number of participants in some subgroups.
OBJECTIVES:We examined the association between sleep duration and quality with cardiometabolic risk factors, assessed whether these associations varied by socioeconomic status, and identified prevalent risk factor combinations in those with poor sleep health. METHODS:We conducted a cross-sectional analysis of 25,433 adults using the 2022 National Health Interview Survey data. Sleep health exposures included self-reported sleep duration (<7, 7-9, >9 h), sleep quality measures (frequency of feeling well rested, difficulty falling asleep, difficulty staying asleep), and a composite sleep health indicator. Cardiometabolic risk factors included overweight/obesity, diabetes, hypertension, and hyperlipidemia. We examined the mean count of cardiometabolic risk factors (individual range: 0-4) and patterns of cardiometabolic risk factor combinations across sleep measures using Poisson regression with marginal standardization for covariates, accounting for the complex survey design. RESULTS:Population-average cardiometabolic risk factor count was 9% higher among short sleepers, 15% to 20% higher across poor sleep quality measures, and 18% higher among those without healthy composite sleep compared with healthy reference groups. Associations between difficulty staying asleep and mean cardiometabolic risk factor count were stronger among those with lower SES (p-interaction ≤0.001) on the ratio scale. Poor sleep quality was associated with more severe CMRF combinations and patterns, while sleep duration showed heterogeneous associations across cardiometabolic outcomes. CONCLUSION:Poor sleep quality and short sleep duration were associated with higher population-level cardiometabolic risk factor burden. Associations for difficulty staying asleep were stronger among individuals with lower socioeconomic status. Poor sleep quality was also associated with more severe cardiometabolic risk factor combinations, suggesting sleep quality may be a potential target for multimorbidity prevention.
STUDY OBJECTIVES:As sleep-disordered breathing has become more prevalent, so has cannabis use due to legalization across many regions of the United States of America (USA). This study sought to determine if there is an association between cannabis use and signs of sleep-disordered breathing. METHODS:This was a cross-sectional study of a sample of 14,485 US adults from the 2017 to 2018 Behavioral Risk Factor Surveillance System (BRFSS). Data from state-administered telephone surveys were used. We utilized survey-weighted multivariable logistic regression to investigate the association between self-reported frequency of cannabis use with witnessed apnea during sleep and reported loud snoring. RESULTS:Cannabis use and signs of sleep-disordered breathing were present in 5.5% and 44.7%, respectively, of the cohort. Compared to no cannabis use, non-regular use (1-15 days of use in last 30) was associated with witnessed apnea during sleep (OR 1.41; 95%CI 1.05, 1.86), loud snoring (1.26; 1.01, 1.57), and either sign (1.33; 1.07, 1.65). Regular use of cannabis (16-30 days of use) was associated with witnessed apnea during sleep (1.73; 1.27, 2.33), loud snoring (1.68; 1.32, 2.14), and either sign (1.82; 1.43, 2.33). Additionally, each additional day per month of cannabis use was associated with increased odds of reported witnessed apnea during sleep, reported loud snoring, and either sleep-disordered breathing sign. CONCLUSIONS:Cannabis use was associated with a greater odds of signs of sleep-disordered breathing. More research is required to examine the causality of this relationship and to determine if the potential effect is mediated by the method of cannabis use.
OBJECTIVES:Public use and perceptions of sleep-focused technologies continue to be largely unknown in the United States and other countries. This study sought to provide population-based estimates of sleep tracker use and privacy concerns, as well as confidence in sleep-focused technologies, broadly, to improve sleep. METHODS:A random, probability-based sample of 1009 U.S. adults and 1000 South Korean adults were collected through national surveys. Surveys collected demographic characteristics, sleep health characteristics, use and privacy concerns around sleep tracking technologies, and perceptions of sleep-focused technologies broadly. Descriptive and inferential statistics were calculated to test demographic differences within countries. RESULTS:Majorities in both the U.S. (86.1%) and South Korea (91.2%) did not use sleep tracking technologies, with some demographic differences in use. A majority of Americans expressed concerns about misuse of collected data from sleep tracking devices (61.7%), while also having skepticism regarding the potential benefits of technology to support sleep health (65%). A majority of South Koreans had little to no concern about sleep tracking device data misuse (59.2%) and perceived potential benefits from sleep-focused technologies (59.7%). CONCLUSIONS:More efforts to build public trust in sleep-focused technology are needed across populations. As sleep tracking and related technologies grow more prominent, U.S. and South Korean adults may benefit from greater education on the strengths and limitations of various forms of sleep technology to support empirically guided perspectives and behaviors towards good sleep health.
PURPOSE:Healthy sleep habits are important when children transition from variable preschool environments to a more structured elementary school setting. However, few studies have harnessed the unique partnership between teachers and parents in preventing suboptimal child sleep. This study aimed to engage key community partners (i.e., 4K & 5K teachers and parents) in developing a combined school- and home-based sleep promotion program for young children (4-6 years old). METHODS:Teachers (n=34, 100% female, 12.4±9.0 years' experience) from 2 school districts participated in semistructured focus groups or phone interviews (n=26 teachers in 3 focus groups; n=8 interviews), while parents (n=61, 97% female, age=33.1 ± 5.1 years) completed an online semistructured survey to inform the development of a sleep promotion program. Transcripts were independently coded using an inductive approach and consensus coding. Themes were generated using constant-comparison methods. Survey results were summarized using descriptive statistics. RESULTS:Four key themes emerged from teachers' perspectives: 1) suboptimal sleep impacts children during the school day across multiple domains, (2) several barriers to adequate sleep exist, 3) parent-teacher interactions about sleep are complex and require unique approaches, and 4) a sleep program must fit within parent and teacher needs. Teachers noted leveraging the parent-teacher relationship may increase parent buy-in. Parents reported challenges with their child's sleep and conveyed interest in a tailored sleep promotion program during 4K. CONCLUSIONS:Teachers are concerned about suboptimal child sleep and are invested in working with parents to support healthy sleep habits. A sleep promotion program that encompasses collaboration between the school and home environment would be well-received by families of young children. Findings will inform future content, engagement strategies, and delivery mode.
OBJECTIVES:Over the past 2 decades, armed conflicts have intensified globally, disrupting everyday life for those in affected areas. While some studies have suggested that civilians' sleep is negatively impacted, little is known about how civilians themselves experience and explain these sleep disruptions. This exploratory study uses the armed conflict in Israel as a case study to advance understanding of the lived dynamics through which conflict affects sleep. METHODS:This article draws on a reflexive thematic analysis of focus groups with Muslim and Jewish men and women from Israel's northern and southern regions. RESULTS:Most participants reported a decline in both sleep quality and quantity, attributing this decline to 5 interrelated factors: fear for their own safety and that of family members; sensory and spatiotemporal disruptions, including acoustic triggers and repeated shelter seeking; relational dynamics, particularly children's sleep, which affected parents; spatial dislocation through relocation and displacement; and economic insecurity marked by worry, uncertainty, and material hardship. CONCLUSIONS:By showing that sleep is a deeply sociopolitical experience, the study contributes to scholarly understandings of sleep during conflict and, more broadly, to research on the social determinants of sleep. The study underscores the need for further research and for policies and interventions to mitigate the profound impacts of armed conflict on sleep, while recognizing the limits of such efforts under conditions of ongoing armed conflict.
