Sleep Health最新文献

{"title":"Sleep health characteristics and positive mental health in Canadian youth: A cross-sectional analysis of the Health Behaviour in School-aged Children study.","authors":"Joses Robinson, Jean-Philippe Chaput, Karen C Roberts, Gary S Goldfield, Suzy L Wong, Ian Janssen, Geneviève Garépy, Stephanie A Prince, Colin A Capaldi, Justin J Lang","doi":"10.1016/j.sleh.2024.09.008","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.09.008","url":null,"abstract":"<p><strong>Objectives: </strong>This study investigated the associations between specific sleep health characteristics and indicators of positive mental health among Canadian youth in grades 6-10.</p><p><strong>Methods: </strong>We used cross-sectional data from the Canadian 2017/2018 Health Behaviour in School-aged Children study, a nationally representative sample of Canadian students. Our analyses included 14,868 participants (53.1% girls). We assessed the following self-reported characteristics of sleep health: nighttime insomnia symptoms, sleep duration, problems with daytime wakefulness, and weekend catch-up sleep. Positive mental health measures included self-reported life satisfaction, positive affect, self-efficacy, and self-confidence. Logistic regression models were used to assess associations while controlling for confounders.</p><p><strong>Results: </strong>Participants who had no or little nighttime insomnia symptoms, who met sleep duration recommendations, who had no or rare daytime wakefulness problems, and who had no or little weekend catch-up sleep were more likely to report high life satisfaction (range of adjusted odds ratios=1.29-2.50), high positive affect (range of adjusted odds ratios=1.35-3.60), high self-efficacy (range of adjusted odds ratios=1.22-2.54), and high self-confidence (range of adjusted odds ratios=1.28-2.31). Almost all of the associations remained significant in the gender- and age-stratified analyses.</p><p><strong>Conclusion: </strong>The findings suggest that good sleep health is associated with higher odds of positive mental health among Canadian youth in grades 6-10. Further research is needed to understand the temporality of the associations and the underlying mechanisms.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142592204","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":"Bidirectional relationships between chronotype and sleep hygiene in children with and without parental history of alcohol use disorder.","authors":"Emma J Tussey, Madisen Hillebrant-Openshaw, Maria M Wong","doi":"10.1016/j.sleh.2024.09.007","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.09.007","url":null,"abstract":"<p><strong>Study objectives: </strong>Children with evening chronotype may be at risk for insufficient sleep because their chronotype makes it difficult to sustain healthy sleep habits. We evaluated bidirectional relationships between chronotype and sleep hygiene.</p><p><strong>Methods: </strong>Two hundred forty-six children (n = 246 at T1, n = 200 at T2, n = 147 at T3), with a mean age of 9.9 (SD=1.4) at T1, participated in a longitudinal study on sleep and substance use. Participants either had a parental history of alcohol use disorder or were matched controls. The Adolescent Sleep Hygiene Scale measured sleep hygiene. Chronotype was measured using the Morningness/Eveningness Questionnaire. We used random intercept cross-lagged panel models to examine longitudinal relations between chronotype and sleep hygiene across three time points, each approximately 1 year apart.</p><p><strong>Results: </strong>Chronotype at T1 predicted sleep hygiene at T2 (b=0.38, p < .05). Chronotype at T2 predicted sleep hygiene at T3 (b=0.38, p < .05). T1 Sleep Hygiene predicted chronotype at T2 (b=0.27, p < .05). T2 Sleep Hygiene predicted chronotype at T3 (b=0.24, p < .05). Chronotype also predicted itself over time (T1-T2: b=0.31, p < .05; T2-T3: b=0.31, p < .05). Sleep hygiene did not predict itself at future time points. Parental history of alcohol use disorder did not predict sleep hygiene or chronotype.</p><p><strong>Conclusions: </strong>There is a bidirectional relationship between chronotype and sleep hygiene; more eveningness predicts poorer sleep hygiene at a later time point, and poorer sleep hygiene predicts more eveningness later. Sleep hygiene is not stable over time and may be a more modifiable target for public health interventions than chronotype.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564669","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":"Phenotypes of sleep health among adults with chronic heart failure in a randomized controlled trial of cognitive behavioral therapy for insomnia.","authors":"Sangchoon Jeon, Samantha Conley, Meghan O'Connell, Zequan Wang, Nancy S Redeker","doi":"10.1016/j.sleh.2024.09.006","DOIUrl":"10.1016/j.sleh.2024.09.006","url":null,"abstract":"<p><strong>Background: </strong>Poor sleep contributes to adverse health in heart failure. However, studies are limited to isolated sleep characteristics.</p><p><strong>Purposes: </strong>To evaluate changes in sleep health phenotypes after cognitive behavioral therapy for insomnia or attention control and associations between sleep health phenotypes, symptoms, stress, functional performance, and emergency department visits and hospitalizations.</p><p><strong>Methods: </strong>Secondary analysis of a randomized controlled trial of cognitive behavioral therapy for insomnia among adults with heart failure. We measured sleep (rest-activity rhythms, sleep duration, quality, and efficiency, insomnia severity, daytime sleepiness), symptoms, cognitive ability, vigilance, and 6-minute walk distance at baseline and 3-, 6-, and 12-month postintervention and collected hospitalizations and emergency department visits. We used K-means cluster analysis and generalized linear mixed models, generalized estimating equations, and Cox proportional hazard models.</p><p><strong>Results: </strong>Among 166 participants (M age=63.2 (SD=12.6) years; 57% male; 23% New York Heart Association Class III/IV), there were four sleep health phenotypes (\"Unstable Sleep\" (15%); \"Short Sleep\" (39%); \"Low Sleep Efficiency\" (25%); and \"Good Sleep\" (21%)) at baseline. The healthiest phenotype was associated with the lowest fatigue. The proportions of participants in the healthiest sleep group increased from pre- to post-treatment. Low sleepiness (p = .0188) and a robust circadian quotient (p = .007) predicted transition to the healthiest phenotype. The poorest sleep phenotype at baseline predicted time to hospitalizations and emergency department visits (hazard ratios 0.35-0.60) after adjusting for covariates.</p><p><strong>Conclusion: </strong>Sleep phenotypes predict heart failure outcomes. Tailored interventions targeting phenotypes may be more effective than approaches that focus on single sleep characteristics.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142559161","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":"Neighborhood social vulnerability as a mediator of racial disparities in insomnia severity.","authors":"Philip Cheng, Matthew B Jennings, David Kalmbach, Dayna A Johnson, Salma Habash, Melynda D Casement, Christopher Drake","doi":"10.1016/j.sleh.2024.09.005","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.09.005","url":null,"abstract":"<p><strong>Study objectives: </strong>Recent data has indicated that Black Americans experience more severe insomnia compared to their White counterparts. Although previous studies have identified psychosocial mechanisms driving this disparity, little is known about the structural determinants of insomnia disparities. This study tested neighborhood social vulnerability as a mechanism driving Black-White disparities in insomnia severity in the United States.</p><p><strong>Methods: </strong>Participants with a previous diagnosis of insomnia (N = 196) reported their race and insomnia severity (Insomnia Severity Index). As a measure of the neighborhood environment Social Vulnerability Index was calculated by geocoding home address at the time of participation to the respective census tract from the 2020 US Census. A mediation analysis tested the indirect effect of the Social Vulnerability Index between race and insomnia severity.</p><p><strong>Results: </strong>Black participants reported worse insomnia severity compared to White participants. Black participants also had 3.3 times the odds of living in neighborhoods with higher social vulnerability compared to White participants, with a group median difference of 0.26 percentile points (scale 0 to 1). As hypothesized, results revealed a significant indirect effect of the Social Vulnerability Index, which accounted for 31.1% of the variance between race and insomnia severity.</p><p><strong>Conclusion: </strong>Living in a socially vulnerable neighborhood environment may be a mechanism driving racial disparities in insomnia severity. Interventions that consider structural determinants of health, including community-based and policy-level interventions could have an enhanced impact on addressing insomnia and its public health consequences.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142548436","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 patterns in adolescents and associations with substance use.","authors":"Clara Sancho-Domingo, José Luis Carballo","doi":"10.1016/j.sleh.2024.09.002","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.09.002","url":null,"abstract":"<p><strong>Objectives: </strong>Good sleep during adolescence is crucial for maintaining physical and psychological health; however, sleep disturbance during this period may contribute to health risks, such as substance use. This study aimed to identify the latent sleep patterns across male and female adolescents, and their association with drug use.</p><p><strong>Method: </strong>A cross-sectional study was conducted involving 1391 high school students (aged 15-17; 56.4% female). Participants completed the brief Pittsburgh Sleep Quality Index alongside other sleep measures, and the Timeline Follow-Back and Drug Use History Questionnaire to measure substance use. A multiple-group latent class analysis was used to identify sleep patterns across sexes, and pairwise Logistic Regression models to compare their association with substance use.</p><p><strong>Results: </strong>Four sleep patterns were identified with varying degrees of sleep difficulties: \"Good Sleep\" (43.3%), \"Night Awakenings\" (31.8%), \"Poor Efficiency and Sleep Onset\" (9.4%), and \"Poor Sleep\" (15.5%). Female adolescents were more likely to belong to Poor Sleep and Poor Efficiency and Sleep Onset patterns, and male adolescents to Good Sleep. Likewise, binge drinking and using alcohol for a longer period were associated with experiencing Poor Efficiency and Sleep Onset (OR=1.03 and 2.3, respectively); smoking tobacco within the past month was linked to Night Awakenings (OR=2.2); and using cannabis or illegal drugs to the Poor Sleep pattern (OR=2.4 and 2.6, respectively).</p><p><strong>Conclusions: </strong>Varied sleep difficulties exist among adolescents that significantly correlate with different aspects of drug use. Targeted interventions that address both sleep and drug prevention are recommended.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510642","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":"Insomnia and sleep apnea in the entire population of US Army soldiers: Associations with deployment and combat exposure 2010-2019, a retrospective cohort investigation.","authors":"John A Caldwell, Joseph J Knapik, Soothesuk Kusumpa, Tanja C Roy, Kathryn M Taylor, Harris R Lieberman","doi":"10.1016/j.sleh.2024.09.004","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.09.004","url":null,"abstract":"<p><strong>Objectives: </strong>This retrospective cohort study examined clinically diagnosed insomnia and sleep apnea and analyzed associations with deployment and combat exposure in active-duty soldiers (n=1,228,346) from 2010 to 2019.</p><p><strong>Methods: </strong>Retrospective data were obtained from the Soldier Performance, Health, and Readiness database.</p><p><strong>Results: </strong>Overseas soldier deployments peaked in 2010, decreasing thereafter as soldiers were withdrawn from Iraq and Afghanistan. From 2010 to 2012 insomnia incidence increased at a rate of 6.7 cases/1000 soldier-years, then decreased after 2012 at 5.3 cases/1000 soldier-years. Sleep apnea increased 2010-2016 at 1.9 cases/1000 soldier-years and generally declined thereafter. Risk of insomnia increased with deployment (hazard ratio=1.51; 95% confidence interval=1.49-1.52) and combat exposure (hazard ratio=1.15; 95% confidence interval=1.13-1.17). Risk of sleep apnea was increased by deployment (hazard ratio=1.89; 95% confidence interval, 1.86-1.92) and combat exposure (hazard ratio=1.09; 95% confidence interval, 1.07-1.11). Most relationships remained after accounting for other factors in multivariable analyses, except that the association between sleep apnea and combat exposure was reduced (hazard ratio=0.94; 95% confidence interval=0.92-0.97).</p><p><strong>Conclusions: </strong>Insomnia risk decreased in the period nearly in parallel with a reduction in the number of deployments; nonetheless deployment and combat exposure increased insomnia risk in the period examined. Risk of sleep apnea increased in the period and was related to deployment but not combat exposure after accounting for demographics and comorbid conditions. Despite reductions in insomnia incidence and a slowing in sleep apnea incidence, sleep disorders remain highly prevalent, warranting continued emphasis on sleep-disorder screening and improving the soldier sleep habits.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142510641","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":"Associations between neighborhood factors and insomnia and their spatial clustering in Philadelphia, Pennsylvania.","authors":"Foster Osei Baah, Augustine Cassis Obeng Boateng, Janeese A Brownlow, Christine J So, Katherine E Miller, Philip Gehrman, Barbara Riegel","doi":"10.1016/j.sleh.2024.09.003","DOIUrl":"10.1016/j.sleh.2024.09.003","url":null,"abstract":"<p><strong>Background: </strong>Neighborhood-level adverse social determinants may be a risk factor for sleep health disparities. We examined the associations between neighborhood factors and insomnia and explored their spatial clustering in the city of Philadelphia, Pennsylvania.</p><p><strong>Methods: </strong>We conducted a cross-sectional analysis of data from Philadelphia residents who participated in online screening for insomnia-related research. Participants self-reported sex, age, body mass index, anxiety, post-traumatic stress disorder, depression, and insomnia symptoms. The sample was stratified as \"No Insomnia\" (≤7) and \"Insomnia\" (>7) based on the Insomnia Severity Index (range: 0-28). Neighborhood and participant data were merged using geospatial techniques. Multiple regression models and geospatial analysis were used to identify neighborhood variables that are associated with insomnia and their spatial distribution.</p><p><strong>Results: </strong>The sample (N = 350) was predominantly female (53%), middle-aged (40.8 ± 13.8), overweight (body mass index=26.1 ± 5.54), and 53.7% had insomnia. The insomnia group had significantly higher depression scores (14.6 ± 5.5), a large percentage had anxiety (64.4%) and post-traumatic stress disorder symptoms (31.9%), and largely resided in high crime (p < .001) and highly deprived neighborhoods (p = .034). Within the insomnia group, a 1-point increase in the number of spiritual centers in the neighborhood was associated with lower insomnia symptoms (b=-1.02, p = .002), while a 1-point increase in depression scores (b=0.44, p < .001) and residence in a highly deprived neighborhood (b=1.49, p = .021) was associated with greater insomnia.</p><p><strong>Conclusion: </strong>Disparities exist in the neighborhood determinants of insomnia and their spatial distribution in Philadelphia. Interventions targeting the spatial distribution of adverse social determinants may improve insomnia disparities.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478083","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":"Mediating role of obstructive sleep apnea in altering slow-wave activity and elevating Alzheimer's disease risk: Pilot study from a northern Taiwan cohort.","authors":"Cheng-Yu Tsai, Chien-Ling Su, Huei-Tyng Huang, Hsin-Wei Lin, Jia-Wei Lin, Ng Cheuk Hei, Wun-Hao Cheng, Yen-Ling Chen, Arnab Majumdar, Jiunn-Horng Kang, Kang-Yun Lee, Zhihe Chen, Yi-Chih Lin, Cheng-Jung Wu, Yi-Chun Kuan, Yin-Tzu Lin, Chia-Rung Hsu, Hsin-Chien Lee, Wen-Te Liu","doi":"10.1016/j.sleh.2024.08.012","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.08.012","url":null,"abstract":"<p><strong>Objectives: </strong>Obstructive sleep apnea is associated with alterations in slow-wave activity during sleep, potentially increasing the risk of Alzheimer's disease. This study investigated the associations between obstructive sleep apnea manifestations such as respiratory events, hypoxia, arousal, slow-wave patterns, and neurochemical biomarker levels.</p><p><strong>Methods: </strong>Individuals with suspected obstructive sleep apnea underwent polysomnography. Sleep disorder indices, oxygen metrics, and slow-wave activity data were obtained from the polysomnography, and blood samples were taken the following morning to determine the plasma levels of total tau (T-Tau) and amyloid beta-peptide 42 (Aβ₄₂) by using an ultrasensitive immunomagnetic reduction assay. Subsequently, the participants were categorized into groups with low and high Alzheimer's disease risk on the basis of their computed product Aβ₄₂ × T-Tau. Intergroup differences and the associations and mediation effects between sleep-related parameters and neurochemical biomarkers were analyzed.</p><p><strong>Results: </strong>Forty-two participants were enrolled, with 21 assigned to each of the low- and high-risk groups. High-risk individuals had a higher apnea-hypopnea index, oxygen desaturation index (≥3%, ODI-3%), fraction of total sleep time with oxygen desaturation (SpO_2-90% _TST), and arousal index and greater peak-to-peak amplitude and slope in slow-wave activity, with a correspondingly shorter duration, than did low-risk individuals. Furthermore, indices such as the apnea-hypopnea index, ODI-3% and SpO_2-90% _TST were found to indirectly affect slow-wave activity, thereby raising the Aβ₄₂ × T-Tau level.</p><p><strong>Conclusions: </strong>Obstructive sleep apnea manifestations, such as respiratory events and hypoxia, may influence slow-wave sleep activity (functioning as intermediaries) and may be linked to elevated neurochemical biomarker levels. However, a longitudinal study is necessary to determine causal relationships among these factors.</p><p><strong>Statement of significance: </strong>This research aims to bridge gaps in understanding how obstructive sleep apnea is associated with an elevated risk of Alzheimer's disease, providing valuable knowledge for sleep and cognitive health.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478097","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":"Association between joint physical activity and sleep duration and hypertension in US adults: Cross-sectional NHANES study.","authors":"Zhendong Cheng, Qingfeng Zeng, Changdong Zhu, Guiying Yang, Linling Zhong","doi":"10.1016/j.sleh.2024.08.005","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.08.005","url":null,"abstract":"<p><strong>Background: </strong>Previous studies have adequately demonstrated that physical activity or healthy sleep duration can reduce the risk of hypertension. However, the combined effects of physical activity and healthy sleep on hypertension have not been well explored in studies using nationally representative samples.</p><p><strong>Methods: </strong>The data were obtained from the National Health and Nutrition Examination Survey (2007-2018). Sleep duration and physical activity were obtained from self-reported questionnaires. Survey logistic regression and restricted cubic spline curves were used to evaluate the joint effects of physical activity and healthy sleep duration on hypertension.</p><p><strong>Results: </strong>A total of 18,007 participants were enrolled in the main study. Physical activity was categorized into insufficient physical activity (600 < Met-min/week) and sufficient physical activity (≥600 Met-min/week). Sleep duration of ≤6 or ≥9 hours was defined as unhealthy sleep duration, and 7-8 hours was defined as healthy sleep duration. Compared to the individuals with unhealthy sleep duration and insufficient physical activity, only the participants with healthy sleep duration and sufficient physical activity (adjusted odds ratio: 0.76, 95% CI 0.66-0.88) were negatively associated with hypertension, while the participants with healthy sleep duration but insufficient physical activity or sufficient physical activity but unhealthy sleep duration were not associated with hypertension. Physical activity was nonlinearly associated with hypertension in the healthy sleep duration group, whereas in the unhealthy sleep duration group, physical activity was not associated with hypertension.</p><p><strong>Conclusion: </strong>Our findings indicate that sufficient physical activity and healthy sleep duration were negatively associated with hypertension. This underscores the importance of integrating both sufficient physical activity and healthy sleep duration in strategies aimed at reducing hypertension risk.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478082","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 sleep staging based on 24/7 EEG SubQ (UNEEG medical) data displays strong agreement with polysomnography in healthy adults.","authors":"Esben Ahrens, Poul Jennum, Jonas Duun-Henriksen, Bjarki Djurhuus, Preben Homøe, Troels W Kjær, Martin Christian Hemmsen","doi":"10.1016/j.sleh.2024.08.007","DOIUrl":"https://doi.org/10.1016/j.sleh.2024.08.007","url":null,"abstract":"<p><strong>Goal and aims: </strong>Performance evaluation of automatic sleep staging on two-channel subcutaneous electroencephalography.</p><p><strong>Focus technology: </strong>UNEEG medical's 24/7 electroencephalography SubQ (the SubQ device) with deep learning model U-SleepSQ.</p><p><strong>Reference method/technology: </strong>Manually scored hypnograms from polysomnographic recordings.</p><p><strong>Sample: </strong>Twenty-two healthy adults with 1-6 recordings per participant. The clinical study was registered at ClinicalTrials.gov with the identifier NCT04513743.</p><p><strong>Design: </strong>Fine-tuning of U-Sleep in 11-fold cross-participant validation on 22 healthy adults. The resultant model was called U-SleepSQ.</p><p><strong>Core analytics: </strong>Bland-Altman analysis of sleep parameters. Advanced multiclass model performance metrics: stage-specific accuracy, specificity, sensitivity, kappa (κ), and F1 score. Additionally, Cohen's κ coefficient and macro F1 score. Longitudinal and participant-level performance evaluation.</p><p><strong>Additional analytics and exploratory analyses: </strong>Exploration of model confidence quantification. Performance vs. age, sex, body mass index, SubQ implantation hemisphere, normalized entropy, transition index, and scores from the following three questionnaires: Morningness-Eveningness Questionnaire, World Health Organization's 5-item Well-being Index, and Major Depression Inventory.</p><p><strong>Core outcomes: </strong>There was a strong agreement between the focus and reference method/technology.</p><p><strong>Important supplemental outcomes: </strong>The confidence score was a promising metric for estimating the reliability of each hypnogram classified by the system.</p><p><strong>Core conclusion: </strong>The U-SleepSQ model classified hypnograms for healthy participants soon after implantation and longitudinally with a strong agreement with the gold standard of manually scored polysomnographics, exhibiting negligible temporal variation.</p>","PeriodicalId":48545,"journal":{"name":"Sleep Health","volume":" ","pages":""},"PeriodicalIF":3.4,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142478095","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}