Sleep Health最新文献

{"title":"Wrist-worn accelerometer measured sleep fragmentation and obesity risk: Socioeconomic gradients and mediation by allostatic load.","authors":"Jie Xing, Xin Lin, Ying Zhang, Ying Tang, Tingsong Yang, Weiwei Zhuang, Fangbiao Tao, Xu Steven Xu, Min Yuan","doi":"10.1016/j.sleh.2026.03.010","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.03.010","url":null,"abstract":"<p><strong>Objectives: </strong>Sleep fragmentation is a recognized risk factor for obesity, yet whether socioeconomic status moderates this association and whether chronic stress responses mediate it remain unclear.</p><p><strong>Methods: </strong>We analyzed 3007 U.S. adults (≥18 years) from NHANES 2013-2014 with valid wrist-worn accelerometer data, representing approximately 132.7 million adults nationwide. Sleep fragmentation was quantified as wake minutes per hour (WASO/h) and awakenings per hour (AWAKE/h) using a Hidden Markov Model. Outcomes were general obesity (Body Mass Index, BMI) and central obesity (Body Roundness Index, BRI). Moderation by a composite socioeconomic status index (poverty income ratio, education, insurance) and mediation by Allostatic Load Index were evaluated using survey-weighted multinomial logistic regression and moderated mediation models.</p><p><strong>Results: </strong>Higher sleep fragmentation was associated with greater odds of obesity (WASO/h: OR, 1.32; 95% confidence interval (CI), 1.15-1.50; AWAKE/h: OR, 1.52; 95% CI, 1.27-1.83; both P < .001), with similar patterns for Body Roundness Index-defined obesity. These associations were stronger among higher-socioeconomic status adults and less pronounced in middle-socioeconomic status groups. Moderated mediation analyses indicated partial mediation by Allostatic Load Index, with significant indirect effects in high-socioeconomic status groups accounting for 13%-16% of the total association. Results were consistent across sensitivity analyses including multiple imputation, alternative Allostatic Load Index definitions, and additional adjustment for sleep duration and physical activity.</p><p><strong>Conclusions: </strong>Sleep fragmentation was significantly associated with increased risk of both general and central obesity, with socioeconomic heterogeneity in effect magnitude. Chronic stress pathways partially explained this relationship, particularly among higher-socioeconomic status adults, suggesting that incorporating sleep quality assessment may benefit obesity prevention across diverse socioeconomic status contexts.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147844751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond sleep duration: Assessment of multidimensional sleep health in a nationally recruited sample of Nigerian adults.","authors":"Jesujoba I Olanrewaju, Leah A Irish","doi":"10.1016/j.sleh.2026.04.005","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.04.005","url":null,"abstract":"<p><strong>Objectives: </strong>Sub-Saharan Africa represents 1.1 billion people, yet sleep health remains critically understudied in this region. This study characterized multidimensional sleep health among Nigerian adults and examined sociodemographic correlates.</p><p><strong>Methods: </strong>A cross-sectional survey recruited 1046 Nigerian adults (M = 33.64 ± 9.29 years; 62.4% male; 51.2% rural) via stratified random sampling. The RU-SATED questionnaire v2.0 assessed six sleep health dimensions. Analyses included Pearson's chi-square statistics, Spearman's rho, and t-test for international comparisons with Norway (n = 1028) and the USA (n = 3401).</p><p><strong>Results: </strong>Mean RU-SATED sleep health was 6.31 ± 2.15, significantly lower than Norway (8.96 ± 2.10, d = 1.25) and USA (7.58 ± 2.35, d = 0.50; both p < .001). Only 16%-22% achieved healthy regularity, efficiency, and duration. Females and urban residents reported better overall sleep health (p = .001). Age was positively correlated with overall sleep health (r = 0.13, p < .001).</p><p><strong>Conclusions: </strong>Nigerian adults reported suboptimal sleep health, particularly in regularity, efficiency, and duration. Findings highlight the need for contextually tailored interventions and provide baseline data for Sub-Saharan Africa.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147844826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inflammation, sleep, and trait mindfulness in pregnancy.","authors":"Lorrie Schmid, Laura Etzel, Sarah J Short, Cathi Propper, W Roger Mills-Koonce, Victoria K Lee, Patricia Garrett-Peters","doi":"10.1016/j.sleh.2026.04.004","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.04.004","url":null,"abstract":"<p><strong>Objectives: </strong>Excessive systemic inflammation during pregnancy is a risk for adverse birth outcomes. Maternal sleep is related to systemic inflammation and may be modifiable through mindful thoughts and behaviors. In this cohort study, we explored the relationships among inflammation, sleep quality, and mindfulness during pregnancy.</p><p><strong>Methods: </strong>Pregnant persons (N = 122) 31.3 ± 5.3 years old, 32% self-identified Black and 57% self-identified White, were recruited during the second and third trimesters. Inflammation was assessed using interleukin-6 (IL-6). The Pittsburgh Sleep Quality Index was used to assess sleep quality, and the Three Facet Mindfulness Questionnaire was used to assess four mindfulness facets (i.e., overall mindfulness, nonjudging to inner experience, nonreactivity to inner experience, and acting with awareness). Relationships between inflammation, sleep quality, mindfulness, and the interaction between sleep and mindfulness were examined using linear regression.</p><p><strong>Results: </strong>Lower inflammation (IL-6) was associated with higher acting with awareness (β = -0.20, 95% CI [-0.53, -0.05], p = .003). Higher inflammation was nonstatistically significant with lower sleep quality (β = 0.19, 95% CI [-0.13, 0.35], p = .05). Controlling for covariates, the interaction between sleep quality and acting with awareness was significant (β = -0.63, 95% CI [-0.85, -0.40], p < .001), indicating that mindfulness may mitigate the relationship between poor sleep quality and higher inflammation.</p><p><strong>Conclusions: </strong>In this sample, poor sleep quality was associated with higher levels of inflammation for women with lower levels of acting with awareness. Mindfulness interventions might be a cost-effective solution to decrease inflammation through improved sleep quality among pregnant women, potentially reducing adverse birth outcomes.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147844816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sleep health in sexual minority youth: An intersectional approach across ethnicity-race and sex-Findings from the Adolescent Brain Cognitive Development (ABCD) Study.","authors":"Youchuan Zhang, Jinjin Yan, Zhenqiang Zhao, Yijie Wang","doi":"10.1016/j.sleh.2026.03.007","DOIUrl":"10.1016/j.sleh.2026.03.007","url":null,"abstract":"<p><strong>Objectives: </strong>Sexual minority (lesbian, gay, and bisexual) youth experience heightened risks for poor sleep health than heterosexual youth. However, they are often treated as a homogeneous group, obscuring critical within-group variations. This study examined sleep disparities by sexual orientation and, within sexual minority youth, how these disparities differ by ethnicity-race and sex-two critical social strata consistently linked to sleep disparities.</p><p><strong>Methods: </strong>Data were drawn from 5359 youth (M_age = 11.52, 51% female) from the Adolescent Brain Cognitive Development Study. Using actigraphy-based, multidimensional sleep data, youth-reported sexual orientation, and caregiver-reported youth ethnicity-race and sex assigned at birth, we examined sleep differences (1) by sexual orientation within the full sample, and (2) within the sexual minority subsample by ethnicity-race, sex, and ethnicity-race × sex.</p><p><strong>Results: </strong>Path analyses revealed poorer sleep among sexual minority youth across multiple dimensions of average sleep and variability than heterosexual youth. Within the sexual minority subsample, ethnically and racially minoritized youth exhibited poorer sleep than White youth; girls showed poorer sleep than boys; ethnically and racially minoritized girls-representing the group with the most marginalized social strata-consistently exhibited poorer sleep compared with groups with fewer marginalized strata. Supplementary analyses within heterosexual youth showed similar pattern, although sex differences were more mixed.</p><p><strong>Conclusions: </strong>Sexual minority youth, especially those with more marginalized social strata (e.g., ethnically and racially minoritized youth, girls, and ethnically and racially minoritized girls), experience multidimensional sleep disparities. These disparities emerge as early as ages 10-13. Early, targeted intervention and policy efforts are needed to address and mitigate sleep health inequities in these vulnerable groups.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use and interest in cannabis as a sleep aid: Results from a National Sleep Foundation population survey.","authors":"Joseph M Dzierzewski, Alysa N Miller, Alexander J Erickson, Spencer A Nielson, Natalie D Dautovich","doi":"10.1016/j.sleh.2026.04.002","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.04.002","url":null,"abstract":"<p><strong>Objectives: </strong>Most adults are dissatisfied with their sleep, and some may see commercially available cannabis-based products as a solution. This study aimed to provide current population-based estimates of behaviors and attitudes related to cannabis use for sleep.</p><p><strong>Methods: </strong>Data from a national survey utilizing a probability-based, random sample of 1367 U.S. adults were analyzed. Cannabis use rates and sleep differences in adults using cannabis were tested.</p><p><strong>Results: </strong>Current and past cannabis use for sleep were reported at 8.6% and 9.9%, respectively. Eleven percent of adults who do not use cannabis endorsed likely future use of cannabis products for sleep. Adults using cannabis (current, past, likely future) tended to report worse sleep quality than those who do not use cannabis (p < .05 for all comparisons).</p><p><strong>Conclusions: </strong>Evident public use and interest in cannabis for sleep was found. Consumer caution is warranted as the short and long-term effects of cannabis products on sleep are poorly characterized in the real world.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Day-by-day changes in the indoor environment and sleep health among African American adults.","authors":"Yinxian Chen, Laura Ward, Donald Bliwise, Dayna A Johnson","doi":"10.1016/j.sleh.2026.03.008","DOIUrl":"10.1016/j.sleh.2026.03.008","url":null,"abstract":"<p><strong>Objectives: </strong>The study aimed to examine the association between day-by-day changes in the indoor physical environment and dimensions of sleep health among African American adults.</p><p><strong>Methods: </strong>A total of 36 African American participants with at least five consecutive days of objective sleep measured by actigraphy (417 person-days) were included in the analysis. Indoor environmental factors, including temperature, carbon dioxide, noise, humidity, and barometric pressure, were objectively measured by an indoor environmental monitor. Linear mixed models were utilized to assess the within-person association between day-by-day changes in indoor environmental factors and sleep efficiency, wakefulness after sleep onset, sleep duration, and linear models for the association with sleep regularity, adjusting for sex, age, educational attainment, and the number of household members. The joint associations of all factors with sleep measures were assessed using quantile g-computation.</p><p><strong>Results: </strong>The participants' mean (standard deviation) age was 55.3 (8.1), and most were female and had a bachelor's degree or higher. In complete case analysis (N = 29, 288 person-days), higher noise levels were associated with lower sleep efficiency (β = -1.81%, 95% CI: -2.00, -0.45), especially among those in the highest quartile vs. the lowest (β = -2.73%, 95% CI: -4.91, -0.54). Higher pressure levels were associated with longer sleep duration (β = 15.22 minutes, 95% CI: 1.11, 28.02) and more irregular sleep (β = 16.07 minutes, 95% CI: 1.40, 30.73). Having higher levels of all environmental factors was associated with lower sleep efficiency (β = -1.38%, 95% CI: -3.01, 0.26). Multiple-imputation analysis yielded consistent results.</p><p><strong>Conclusions: </strong>Day-by-day changes in indoor physical environment were associated with sleep efficiency, duration, and irregularity among African American adults in the Atlanta Metro area.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Citizenship status and report of trouble sleeping to a healthcare provider among U.S. adults with high-risk sleep symptoms: NHANES 2015-2018.","authors":"Gretchen K Weaver, Emmanuella A Asiedu, Shiwei Liang, Laël N Ngangmeni, Shao-Hsien Liu, Apurv Soni","doi":"10.1016/j.sleh.2026.04.001","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.04.001","url":null,"abstract":"<p><strong>Objectives: </strong>Immigrants experience barriers to healthcare and may be less likely to engage in patient-provider conversations about their sleep health. This study examined the association between citizenship status and report of trouble sleeping among adults with poor sleep health, which has not been readily studied.</p><p><strong>Methods: </strong>We conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (2015-2018) among 5052 adults (≥18 years) that had at least one high-risk sleep symptom (short sleep duration, snoring, snorting, and daytime sleepiness). We employed a two-step analysis by assessing the association between citizenship status and self-report of trouble sleeping to a healthcare provider and the interaction between citizenship status and the number of high-risk sleep (1, 2, 3-4) health symptoms.</p><p><strong>Results: </strong>In the sample, 38.7% of native-born citizens, 26.7% of naturalized citizens, and 14.0% of noncitizens had reported trouble sleeping to an healthcare provider. Covariate-adjusted, survey-weighted logistic regression and sensitivity analysis results showed noncitizens had significantly lower odds of reporting trouble sleeping to an healthcare provider compared with native-born citizens (OR: 0.52, 95% CI: 0.33-0.84). Predicted probability estimates of the interaction of citizenship status and the number of high-risk sleep symptoms showed noncitizens consistently under-reported trouble sleeping to an healthcare provider despite an increasing number of symptoms.</p><p><strong>Conclusions: </strong>Noncitizens may be disenfranchised to engage in conversations with an healthcare provider about sleep. Further inquiry into how citizenship status may be associated with patient-provider communication with specific attention to immigrant subpopulations is warranted.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Domains included in multidimensional sleep health composite scores: A scoping review.","authors":"Catherine Siengsukon, Jade Robichaud, Lauren Hand, Ashley Barry, Prasanna Vaduvathiriyan, Karen Bock","doi":"10.1016/j.sleh.2026.03.004","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.03.004","url":null,"abstract":"<p><p>While the SATED/Ru-SATED sleep health framework is well-recognized, there is no consensus for how many or which domains should be included in the construct of a multidimensional sleep health composite score. Therefore, the purpose of this scoping review is to determine what domains are included in multidimensional sleep health composite scores and how those domains are assessed. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) and the Joanna Briggs Institute's (JBI) updated methodology for scoping reviews were used. Two authors independently reviewed titles/abstracts, full texts, and performed data extraction, and one author resolved discrepancies with discussion as needed. The search strategy generated 1879 references, 130 underwent a full-text screening, and 45 were eligible for inclusion. Five and six domains were the most common number of domains included in the multidimensional sleep health composite scores (n = 20 each). Articles mainly included only self-report measures (n = 21) or a mix of self-report and objective measures (n = 21). Twelve unique domains were identified with Duration being the most common (n = 45), followed by Alertness/Sleepiness (n = 42), Satisfaction/Quality (n = 39), and Timing (n = 37). In conclusion, while the domains most often included in the multidimensional sleep health composite scores followed the SATED/Ru-SATED framework, there was variability in the domains included as well as variability in how the domains were assessed. Consensus is needed on the definition of sleep health domains or, at a minimum, clear reporting on the definitions used. Further research is needed to determine which multidimensional sleep health domains are most associated with health outcomes.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147718446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Technology use and sleep: An examination of population data from the National Sleep Foundation.","authors":"Steven E Carlson, Christopher D Sparks, Joseph M Dzierzewski, Kelly G Baron","doi":"10.1016/j.sleh.2026.03.006","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.03.006","url":null,"abstract":"<p><strong>Objectives: </strong>Evening technology use is common and may be associated with poorer sleep health. We sought to understand pre-sleep technology use in a national sample of adults and its cross-sectional association with sleep health characteristics.</p><p><strong>Methods: </strong>Participants reported their pre-sleep technology use in the hour before bedtime, as well as location of use. Self-reported sleep duration, sleep quality, sleep deficiency, and social jetlag were assessed from the Sleep Health Index. We used weighted analyses to evaluate the prevalence of technology use in the hour prior to bedtime, location of technology use, and sociodemographic differences in pre-bedtime technology use. Further, we examined associations between technology use and self-reported sleep characteristics.</p><p><strong>Results: </strong>The sample included 1000 participants (M_age = 51.92, 51.1% women). The majority (89.9%) reported using electronic devices within 1 hour of bedtime, with 76.5% using technology in the bedroom. Hispanic participants and younger participants reported greater device use before bed and in the bedroom. Use of any device near bedtime was associated with poorer sleep quality and greater sleep deficits. Smartphone use, specifically, was associated with greater social jetlag.</p><p><strong>Conclusions: </strong>Technology use before bed was reported in 9 out of 10 participants and was commonly used in the bedroom. Smartphone use in the hour before bed was associated with less consistent sleep patterns. Presence of racial and ethnic differences in pre-sleep technology use may signify a potential target for promoting health equity.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147700480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of stress on sleep architecture: A seven-day study leveraging a psychophysiological stress detection algorithm and wearable EEG.","authors":"Andrea Montanari, Alex Limin Wang, Martin Karl Moser, Bernd Resch, Amit Birenboim, Basile Chaix","doi":"10.1016/j.sleh.2026.02.008","DOIUrl":"https://doi.org/10.1016/j.sleh.2026.02.008","url":null,"abstract":"<p><strong>Objectives: </strong>Stress is known to be a modifiable key determinant of sleep quality. This study aims to investigate the impact of daytime physiological stress and nighttime environmental stressors on sleep architecture using a rule-based algorithm and wearable sensors in a real-world setting.</p><p><strong>Methods: </strong>Twenty-one participants in Jerusalem were monitored over a 7-day period using the Dreem Headband, a wearable device that measures sleep via electroencephalography. Daytime stress was quantified through the Moment of Stress algorithm, utilizing electrodermal activity from the Empatica Embrace Plus bracelet. To assess potential sources of nighttime stress, we used indoor sensors to measure noise and temperature levels in the bedroom. We applied linear mixed-effects models with a random intercept at the individual level to assess the effects of these factors on sleep outcomes.</p><p><strong>Results: </strong>An increase in the number of Moments of Stress per day from the 10th to the 90th percentile was related to a 6.57-point increase in the rapid eye movement (REM) sleep percentage and a 5.74-point decrease in the deep (N3) sleep percentage, indicating a shift in sleep architecture under heightened stress. Each additional minute of noise exposure above 65 dB(A) was linked to 1.20 more minutes of wake after sleep onset (WASO) (95% CI: 0.54-1.86) and to a 0.10-point increase in light (N1) sleep percentage (95% CI: 0.03-0.16). No association was detected between temperature and sleep.</p><p><strong>Conclusions: </strong>Overall, these preliminary findings suggest that daytime physiological stress and nighttime noise may be associated with alterations in sleep architecture in naturalistic settings.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147677848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}