Sleep最新文献

{"title":"Using Polygenic Risk Scores to Evaluate Definitions of Self-Reported Sleep Phenotypes Across Cohorts.","authors":"Annah B Wyss, Michael Brown, Xiang Li, Brian W Spitzer, Zhijie Huang, Heming Wang, Richa Saxena, Linda Gallo, Qibin Qi, Wassim Tarraf, Robert Kaplan, Melissa Lamar, Hector M González, Charles DeCarli, Myriam Fornage, Jerome I Rotter, Stephen S Rich, Kent D Taylor, Xiuqing Guo, Alexis C Wood, Peter Y Liu, Susan R Heckbert, Chloé Sarnowski, Jan Bressler, Alanna C Morrison, Bing Yu, Pamela L Lutsey, Carmen R Isasi, Susan Redline, Tamar Sofer","doi":"10.1093/sleep/zsag200","DOIUrl":"10.1093/sleep/zsag200","url":null,"abstract":"<p><strong>Study objectives: </strong>Since genome-wide association studies (GWAS) of sleep phenotypes have been conducted in differing populations and definitions of sleep phenotypes vary across studies, we investigated associations between several polygenic risk scores (PRSs) and potential sleep definitions among multiethnic cohorts.</p><p><strong>Methods: </strong>Using data from four cohorts (HCHS/SOL, ARIC, MESA, BHS, N = 16 895), we considered multiple definitions of short and long sleep, insomnia, and excessive daytime sleepiness (EDS). PRSs were developed based on summary statistics from GWAS in European ancestry individuals from the UK Biobank (UKB) and from GWAS conducted in a multiethnic population from the Million Veteran Program (MVP). Study-specific analyses estimated associations between sleep PRSs and corresponding sleep measures per 1 standard deviation increase in the PRS. Models were adjusted for age, sex, ancestral principal components, and center and race as appropriate. Results were meta-analyzed across studies.</p><p><strong>Results: </strong>PRSs based on European ancestry UKB GWAS had statistically significant associations with multiple definitions of the corresponding sleep phenotypes. Associations that were most consistent across studies included: short sleep PRS with ≤6 hours (OR = 1.23,p = 1.80x10-7,phet = 0.97); long sleep PRS with ≥9 hours (OR = 1.09,p = 6.76x10-4,phet = 0.77); insomnia PRS with the Women's Health Initiative Insomnia Rating Scale (WHIIRS) ≥10 or a subset of three questions ≥6 in ARIC (OR = 1.17,p = 5.51x10-10,phet = 0.69); and EDS PRS with Epworth Sleepiness Scale (ESS) ≥11 (OR = 1.23,p = 1.83x10-13,phet = 0.83). PRSs based on multi-ancestry MVP GWAS had weaker associations compared to those based on European ancestry only.</p><p><strong>Conclusions: </strong>By evaluating several types of sleep PRSs and sleep phenotypes, we were able to highlight which sleep PRS performed well across diverse populations and which sleep definitions better captured genetic underpinnings.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148550433","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":"Effectiveness of Guided Internet-delivered Cognitive Behavioral Therapy for Insomnia in Autistic Adults (i-Sleep Autism): a Randomized Controlled Trial.","authors":"Kirsten L Spaargaren, Sander Begeer, Smiddy Nieuwenhuis, Jessie Bradley, Heleen Riper, Kirstin Greaves-Lord, Annemieke van Straten","doi":"10.1093/sleep/zsag199","DOIUrl":"https://doi.org/10.1093/sleep/zsag199","url":null,"abstract":"<p><p>An estimated 60% of autistic adults suffer from insomnia symptoms, which significantly impairs daily functioning and wellbeing. This study evaluated the effectiveness of i-Sleep Autism, a 5-week, guided self-help internet-delivered cognitive behavioral therapy-based intervention (ICBT-I) for insomnia in autistic adults. In co-creation with seven autistic adults with sleeping problems, i-Sleep Autism was adapted from i-Sleep, a pre-existing non-autism specific intervention. A total of 163 adults with autism and insomnia (ISI≥10) was randomly allocated to i-Sleep Autism (n=82) or waitlist control (n=81; receiving psychoeducation and sleep hygiene). Participants were assessed at baseline (T0), mid-intervention (T1; 3-weeks), post-test (T2; 6-weeks), and follow-up (T3; 6 months) on insomnia severity (primary outcome), pre-sleep arousal, anxiety, depression, daily functioning, and quality of life. In the intervention group, 56.1% completed four, and 50% all five modules. Intent-To-Treat analyses revealed a significant reduction in insomnia severity at T1 and T2 (d = 1.02, 95%CI = [0.65, 1.40]), and cognitive- and somatic pre-sleep arousal at post-test, when comparing intervention to control. The intervention group showed significantly higher quality of life at post-test. At T2, 37.8% of the intervention group versus 11.1% of the control group showed clinically meaningful improvement of insomnia. Effects on insomnia severity were maintained at 6-month follow up. No significant effects were found for anxiety, depression, or daily functioning. This is the first RCT to investigate autism-adapted ICBT-I for autistic adults suffering from insomnia. i-Sleep Autism effectively and sustainably improves insomnia. Additional strategies are needed to support dropouts and those who did not benefit.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148520931","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":"Automated deep learning-based arousal detection complies with ten expert scorers in unseen data.","authors":"Henna Pitkänen, Riku Huttunen, Masoumeh Tashakori, Marika Rissanen, Matias Rusanen, Heidur Gretarsdottir, Erna Sif Arnardottir, Tiina Paunio, Antti Kulkas, Sami Nikkonen, Timo Leppänen, Henri Korkalainen","doi":"10.1093/sleep/zsag191","DOIUrl":"https://doi.org/10.1093/sleep/zsag191","url":null,"abstract":"<p><strong>Study objectives: </strong>Automatic arousal scoring is essential for the cost-effective analysis of polysomnograms. Many previous automatic methods have been tested in homogeneous, single-center datasets, and all against one scorer, on event-by-event basis, or in 30-second segments. We developed a deep learning-based arousal scoring model and tested it at 1-second resolution in an independent dataset scored by ten expert scorers from seven different sleep centers.</p><p><strong>Methods: </strong>A fully convolutional neural network model was developed using 1,847 openly available polysomnograms from the Multi-Ethnic Study of Atherosclerosis (MESA) and tested in 205 hold-out polysomnograms from the MESA cohort, and in an independent Sleep Revolution (SR) cohort of 50 polysomnograms, each scored by ten scorers. Model performance was evaluated on an event-by-event basis and in 1-second segments. In the SR dataset, the performance was tested against each scorer individually and against their majority agreement.</p><p><strong>Results: </strong>In the MESA test set, the model achieved an event-by-event F1-score of 0.77, a 1-s segment κ-value of 0.67, and an arousal index (ArI) intraclass correlation coefficient (ICC) of 0.83. In the multi-scorer SR dataset, the model reached a median event-by-event F1-score, a 1-second κ-value, and an ArI ICC of 0.61, 0.50, and 0.66, respectively, exceeding the corresponding median values of the scorers among themselves (0.57, 0.46, and 0.59, respectively).</p><p><strong>Conclusions: </strong>The model achieved higher median arousal scoring agreement with ten manual scorers than the scorers did among themselves in an independent dataset. This suggests that the model generalizes well and can reliably be used in different sleep recordings.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148473020","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":"Dose-Response Associations Between Sleep Duration and Health Outcomes in Adults: Comparison Between Self-Reported and Device-Based Measures.","authors":"Jean-Philippe Chaput, Raaj Kishore Biswas, Matthew Ahmadi, Peter A Cistulli, Wenxin Bian, Emmanuel Stamatakis","doi":"10.1093/sleep/zsag193","DOIUrl":"https://doi.org/10.1093/sleep/zsag193","url":null,"abstract":"<p><strong>Study objectives: </strong>This study aimed to: (i) assess whether associations between sleep duration and health outcomes differ by measurement method (self-report vs. actigraphy); and (ii) compare dose-response curves to evaluate whether sleep duration recommendations should vary based on the method of assessment.</p><p><strong>Methods: </strong>We conducted a prospective cohort study using data from UK Biobank participants aged 40-69 years who wore wrist-worn accelerometers for 7 days and self-reported their daily sleep duration. Outcome measures included all-cause mortality, incident cardiovascular disease (CVD), type 2 diabetes, dementia, and depression. Dose-response associations between sleep duration-measured using device-based metrics (total sleep time and sleep period time) as well as self-report-and these outcomes were examined, adjusting for multiple covariates.</p><p><strong>Results: </strong>We analyzed data from 69,153 adults for cardiovascular disease (CVD) and up to 76,811 adults for mortality, with an average follow-up of 8.0 (SD: 0.9) years. Across all sleep measurement methods, adjusted dose-response curves showed a similar inverse J-shaped pattern (particularly for device-based measures), and a U-shaped association for incident depression. Associations were stronger for sleep period time than for the other sleep metrics. For example, a sleep period time of 7 hours was associated with a 30% lower risk of mortality relative to the 5-hour reference value (HR: 0.70; 95% CI: 0.61-0.79). In comparison, a total sleep time and a self-reported sleep duration of 7 hours were associated with 17% (HR: 0.83; 95% CI: 0.78-0.89) and 14% (HR: 0.86; 95% CI: 0.74-1.00) lower mortality risk relative to the 5-hour reference value, respectively. The lowest estimated risk across outcomes occurred at approximately 7.2 hours for self-reported sleep, 7.7 hours for sleep period time, and between 6.8 and 9.3 hours for total sleep time.</p><p><strong>Conclusions: </strong>Both self-reported and device-measured sleep durations demonstrated broadly similar dose-response relationships with health outcomes, although associations were substantially stronger for device-measured sleep period time. These findings support existing evidence that 7-9 hours of sleep per night is optimal for adults, regardless of how sleep is measured, and suggest that sleep period time may be more relevant than total sleep time for future device-based recommendations.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148449614","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 Aging, Sex and Insomnia Disorder Shape NREM Brain Oscillations.","authors":"Nyissa A Walsh, Aurore A Perrault, Nathan E Cross, Antonia Maltezos, Emma-Maria Phillips, Loïc Barbaux, Oren Weiner, Claire Dyment, Florence Borgetto, Jean-Phillipe Gouin, Thien Thanh Dang-Vu","doi":"10.1093/sleep/zsag192","DOIUrl":"https://doi.org/10.1093/sleep/zsag192","url":null,"abstract":"<p><strong>Study objectives: </strong>Chronic insomnia disorder (INS) is particularly prevalent in older adults and females. Sex- and age-related differences in neurophysiological markers of sleep quality (sleep spindles and slow-wave activity [SWA]) may underlie differential vulnerability to INS. This study investigated the effects of sex and chronic insomnia disorder on spindle and SWA beyond aging, to better understand the mechanistic differences contributing to the higher prevalence of INS in females.</p><p><strong>Methods: </strong>After a habituation night, one night of sleep assessed with polysomnography was analyzed in 222 adults (aged 18-82) including 119 INS (71% female) and 103 healthy sleepers (HS; 61% female). Spindle density, slow oscillation (SO) density, relative sigma power and SWA were derived during NREM sleep. Age, group, sex, and group-by-sex interactions were examined, with age as a covariate.</p><p><strong>Results: </strong>Age, INS, and sex each contributed uniquely to NREM oscillatory activity. INS primarily reduced spindle and SO density, while sex accounted for differences in SWA. While SWA was higher in females overall, sex differences were not significant within the INS or HS groups. Female INS reported highest rates of insomnia severity as well as lower sigma power than males in the INS group. Spindle and SO density deficits were also present in female INS relative to female HS, as well as male INS relative to male HS.</p><p><strong>Conclusions: </strong>The combination of reduced sigma power in females with chronic insomnia disorder relative to their male counterparts, as well as less spindle and SO density compared to female healthy sleepers may contribute to greater insomnia severity in females.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148449582","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":"Interpreting the effects of digital cognitive behavioral therapy for insomnia for sleep problems among university students.","authors":"Wenjun Li, JiaLi Wang","doi":"10.1093/sleep/zsaf417","DOIUrl":"10.1093/sleep/zsaf417","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145865505","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":"Automatic alveolar ventilation-targeted NIV mode vs polysomnographic titration of fixed pressure in naive patients with chronic respiratory failure.","authors":"Mónica Matute-Villacís, Marta Puig Dupre, Dunia Gascueña, Anabel Moraleda, Gemma Guerrero Romero, Lidia López-Escuredo, Mireia Dalmases, Àlvar Agustí, Cristina Embid","doi":"10.1093/sleep/zsag085","DOIUrl":"10.1093/sleep/zsag085","url":null,"abstract":"<p><strong>Study objectives: </strong>Polysomnographic titration of fixed pressures of non-invasive ventilatory support (NIV) is recommended for patients with chronic hypercapnic respiratory failure (CHRF). Here we compared the effects of NIV titrated manually by PSG vs. fully automatic mode (iVAPS AE) in sleep quality, respiratory events manually scored and estimated by built-in software, nocturnal hypoventilation, daytime arterial blood gases and patient comfort.</p><p><strong>Methods: </strong>We studied 26 adult patients (13 female) with CHRF due to COPD (n = 13), neuromuscular disease (n = 8), obesity hypoventilation syndrome (n = 3) and chest wall disorders (n = 2), all naïve to NIV. They were randomized to standard PSG titration of fixed NIV pressures or PSG using \"learn target\" iVAPS AE mode in two separate nights, both under PSG monitoring.</p><p><strong>Results: </strong>Main results showed that:(1) there were no significant differences in the reduction of diurnal PaCO2, nocturnal hypoventilation, sleep quality, upper airway obstruction events with both ventilatory modes; (2) the apnea-hypopnea index from built-in software underestimated that manually scored in both ventilatory modes; (3) ventilatory pressures were lower in fixed mode than iVAPS AE mode; (4) patient comfort was higher in fixed mode than iVAPS AE.</p><p><strong>Conclusions: </strong>This study shows that iVAPS AE initiated with the \"learned target\" procedure achieved similar short and long-term ventilatory efficacy to PSG manual bilevel titration. However, its higher pressure levels and lower comfort indicate that the modes are not fully equivalent. Moreover, underestimation of the AHI by the built-in software demands careful interpretation before changing ventilatory settings. Further studies are required to determine the long-term clinical relevance of these differences.</p><p><strong>Clinical trial information: </strong>This study was registered at ClinicalTrials.gov under the title \"Evaluation of Conventional Non-invasive Mechanical Ventilation (NIV) Versus an Automatic Ventilation Mode\". URL: https://clinicaltrials.gov/study/NCT03872167. Registration number: NCT03872167.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147514614","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":"Effect of electronic nicotine delivery systems for smoking cessation on sleep quality: secondary analysis of a randomized controlled trial.","authors":"Tamara Scharf, Anna Rihs, Anna Schoeni, Micheline Maire, Kali Tal, Julian Jakob, Isabelle Jacot-Sadowski, Jean-Paul Humair, Aurélie Berthet, Martin Brutsche, Anja Frei, Lucy Bolt, Ramin Khatami, Reto Auer, Stéphanie Baggio","doi":"10.1093/sleep/zsag028","DOIUrl":"10.1093/sleep/zsag028","url":null,"abstract":"<p><strong>Study objectives: </strong>E-cigarettes can help smokers quit, but how e-cigarettes used for tobacco smoking cessation impact sleep is still unclear. The primary objective was to evaluate the effect of e-cigarettes for smoking abstinence on sleep quality. Secondary objectives included subscales of sleep quality.</p><p><strong>Methods: </strong>We conducted a secondary analysis of the Efficacy, Safety, and Toxicology of electronic nicotine delivery systems for smoking cessation (ESTxENDS) randomized controlled trial, which included adult smokers in Switzerland (five sites, 7.2018-6.2021). The intervention group received free e-cigarettes and e-liquids over 6 months plus standard-of-care smoking-cessation counseling (SOC); the control group received SOC alone. The primary outcome was overall self-reported sleep quality at 6 months, measured by the Pittsburgh Sleep Quality Index (PSQI). We considered a minimal clinically important difference (MCID) of 2.5-5. Secondary outcomes included PSQI subscales. We used adjusted linear regressions with inverse probability of attrition weights (IPAW).</p><p><strong>Results: </strong>ESTxENDS included 1246 participants. Of these, 831 participants completed the PSQI at follow-up. For the primary outcome, there was no significant difference in PSQI score between groups (b = -0.20, p = .256, adjusted analyses with IPAW). For PSQI subscales, only sleep efficiency was significantly better in the intervention group (b = 1.87, p = .018), below MCID.</p><p><strong>Conclusion: </strong>E-cigarettes added to SOC for tobacco smoking abstinence did not significantly alter participant's self-reported sleep quality compared to SOC alone. Clinicians can inform patients willing to quit smoking with e-cigarettes that their use is not likely to disrupt their perceived sleep quality on average.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13357506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146126480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of glutamatergic inputs to the sublaterodorsal tegmental nucleus and their role in rapid eye movement sleep control.","authors":"Steven Ngo, Gerard Kim, HanHee Lee, Anita Taksokhan, Jimmy J Fraigne, John Peever","doi":"10.1093/sleep/zsag014","DOIUrl":"10.1093/sleep/zsag014","url":null,"abstract":"<p><p>Rapid eye movement (REM) sleep is characterized by rapid eye movements, cortical activation, and paralysis of skeletal muscles. Sublaterodorsal tegmental nucleus (SLD) glutamate neurons play a critical role in generating rapid eye movement sleep, and glutamate release in the sublaterodorsal tegmental nucleus is needed to generate rapid eye movement sleep. However, the source of glutamate inputs to sublaterodorsal tegmental nucleus neurons remains poorly understood. Here, we characterized brain-wide glutamatergic inputs to the sublaterodorsal tegmental nucleus using genetically-assisted tract tracing in mice and find input from the cortex and the brainstem (including in region surrounding the injection area, in the pons, and the medulla). Because the ventrolateral peri-aqueductal gray (vlPAG) is a region known to regulate rapid eye movement sleep, we wanted to characterize the activity of ventrolateral peri-aqueductal gray→sublaterodorsal tegmental nucleus glutamate neurons and did so using in vivo fiber photometry. We found that population activity of ventrolateral peri-aqueductal gray glutamate neurons varied across the sleep-wake cycle. We also found that ventrolateral peri-aqueductal gray glutamate neurons tended to increase their activity seconds before rapid eye movement sleep onset and decreased their activity at rapid eye movement sleep offset. However, more precise tools are needed to determine that ventrolateral peri-aqueductal gray glutamate neurons function to gate the initiation and termination of rapid eye movement sleep by controlling the activity of glutamate sublaterodorsal tegmental nucleus neurons.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13357502/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146041697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpreting explained variance in racial disparities in sleep health: conceptual and methodological considerations.","authors":"Lina Ding, Na Zhan","doi":"10.1093/sleep/zsag019","DOIUrl":"10.1093/sleep/zsag019","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146107265","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}