Sleep Health最新文献

Study objectives: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Background: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Background: Many individuals use the Internet, including generative artificial intelligence like ChatGPT, for sleep-related information before consulting medical professionals. This study compared responses from sleep disorder specialists and ChatGPT to common sleep queries, with experts and laypersons evaluating the responses' accuracy and clarity.

Methods: We assessed responses from sleep medicine specialists and ChatGPT-4 to 140 sleep-related questions from the Korean Sleep Research Society's website. In a blinded study design, sleep disorder experts and laypersons rated the medical helpfulness, emotional supportiveness, and sentence comprehensibility of the responses on a 1-5 scale.

Results: Laypersons rated ChatGPT higher for medical helpfulness (3.79 ± 0.90 vs. 3.44 ± 0.99, p < .001), emotional supportiveness (3.48 ± 0.79 vs. 3.12 ± 0.98, p < .001), and sentence comprehensibility (4.24 ± 0.79 vs. 4.14 ± 0.96, p = .028). Experts also rated ChatGPT higher for emotional supportiveness (3.33 ± 0.62 vs. 3.01 ± 0.67, p < .001) but preferred specialists' responses for sentence comprehensibility (4.15 ± 0.74 vs. 3.94 ± 0.90, p < .001). When it comes to medical helpfulness, the experts rated the specialists' answers slightly higher than the laypersons did (3.70 ± 0.84 vs. 3.63 ± 0.87, p = .109). Experts slightly preferred specialist responses overall (56.0%), while laypersons favored ChatGPT (54.3%; p < .001). ChatGPT's responses were significantly longer (186.76 ± 39.04 vs. 113.16 ± 95.77 words, p < .001).

Discussion: Generative artificial intelligence like ChatGPT may help disseminate sleep-related medical information online. Laypersons appear to prefer ChatGPT's detailed, emotionally supportive responses over those from sleep disorder specialists.

Objective: This study gathered adolescent and caregiver perspectives on sleep hygiene practices and beliefs for Black families living in low-resourced urban communities.

Methods: Semistructured interviews were conducted with adolescents (n = 9) and caregivers (n = 9) from January-March 2021, during the COVID-19 pandemic. Interview questions included adolescent's current sleep habits, barriers, and home and neighborhood influences. Trained researchers coded data using inductive analysis and a constant comparative method to derive themes.

Results: Two themes focused on sleep hygiene practices, including items used to facilitate sleep (e.g., melatonin, electronics) and COVID-19 consequences on sleep schedules. Two themes focused on sleep hygiene beliefs, including a common value on the importance of sleep and influences on caregiver's bedtime rules.

Conclusions: Findings provide important insights on sleep hygiene practices and beliefs in a historically marginalized population of Black adolescents and caregivers in urban communities to inform targeted sleep interventions, policies, and programs for optimal sleep and well-being.

Objective: We analyze the relationship between employment status, income, and sleep in South Africa to address two research questions: (1) How does employment status influence the sleep quantity of the individual and their partner? (2) How does income impact the sleep quantity of the individual and their partner?

Method: Using data from 1600 Black African couples in the South African Time Use Study, we employ the Actor-Partner Interdependence Model to investigate the relationship between employment status, income, and sleep in couples. We categorize nighttime sleep into three categories: recommended sleep (7-9 hours), short sleep (<7 hours), and long sleep (>9 hours).

Results: Employed individuals were more likely to get the recommended amount of sleep and less likely to experience long sleep. However, men whose wives are employed are almost twice as likely as men whose wives are unemployed to experience short sleep, and they experience 47% lower risk of long sleep. Men with a medium level of income have a higher risk of short sleep than those with low income, while those in the highest income category are more likely to get the recommended amount of sleep.

Conclusion: These results highlight the intricate dynamics between managing employment demands and securing economic stability for both men and women in the context of high unemployment and shifting gender norms.

Background: Inadequate sleep is associated with all-cause mortality in the general population. Substance use has adverse effects on sleep, and insomnia symptoms are common among people with HIV. Therefore, persons who inject drugs may face a heightened risk of adverse outcomes from inadequate sleep. We evaluated the association of inadequate sleep with mortality among persons who inject drugs in a long-standing community cohort.

Methods: Participants were from the AIDS Linked to the IntraVenous Experience (ALIVE) study, a cohort of persons who inject drugs in Baltimore, Maryland, USA. From 2005-2020, perceived sleep adequacy and duration were assessed semiannually using survey. Mortality data were obtained through linkage to the National Death Index-Plus. Cause of death was independently characterized and validated by three physicians. Hazards of all-cause and cause-specific mortality were evaluated using Cox regression accounting for repeated measurements.

Results: A total of 2633 participants were included, with a median age at entry of 45.8years; 32.5% were female, and 75% were Black. After adjustment for demographics, mental health, and comorbidities, inadequate sleep was associated with a 32% greater hazard of all-cause mortality (hazard ratio: 1.32, 95% confidence interval: 1.12-1.55) and a 67% greater hazard of HIV/infectious disease-related deaths (hazard ratio: 1.67, 95% confidence interval: 1.15-2.42). Short (<6 hours) and long (≥8 hours) duration of sleep were both associated with higher hazard of all-cause and chronic disease-related mortality (all p < .05).

Conclusions: Sleep plays a critical role in longevity in persons who inject drugs. Research is needed to determine whether interventions targeting sleep improve health and longevity in persons who inject drugs.

Study objectives: We investigated profiles of community support and challenges in relation to insomnia symptoms among the Bhutanese living in the United States.

Methods: Using data from the pilot Bhutanese Community of Central Ohio Health Study (N = 495; 51.5% men, 69.8% aged 18-44years), we used latent class analysis to identify distinct profiles of neighborhood social cohesion, social support, and community challenges (e.g., limited access to healthcare services and transportation, crime and safety issues, substance use, intimate partner violence) and their associations with insomnia symptoms. Insomnia symptoms were self-reported as difficulty falling and staying asleep and dichotomized as "not at all" vs. "some to always." Identified classes/profiles were further differentiated by self-reported sociodemographic, socioeconomic, health, acculturative, and discrimination factors.

Results: Latent class analysis revealed four distinct classes/profiles. The High Cohesion (class 1) profile (30.1% of sample) had the lowest likelihood of insomnia symptoms at 6.5%, followed by class 2 or High Support (23.6%) with a 15.3% likelihood. Class 3 or High Challenges profile (11.5%) had a moderate likelihood of insomnia symptoms at 49%. Class 4 or the Low Cohesion/Support profile (34.7%) had a 100% likelihood of reporting insomnia symptoms. Class 4 when compared to class 1 was more likely to report cardiometabolic conditions, experiences of everyday discrimination, limited English linguistic proficiency, and not using telehealth.

Conclusion: Community social cohesion and support may play an important role in mitigating insomnia symptoms among Bhutanese refugees. Further investigations are warranted.

Objectives: We investigated intrafamilial sleep evolution by identifying children's sleep multitrajectory groups between 3- and 60-month of age and their association with parental sleep multitrajectory groups.

Methods: We included 180 children from the SEPAGES cohort (Grenoble, France) whose parents belonged to previously identified sleep multitrajectory groups, through group-based multitrajectory modeling, between 3 and 36months postpartum, using nighttime (NSD) and weekend daytime (DSD) sleep durations and subjective sleep loss, comprising "No," "Subjective," and "Global" sleep problems groups. Child sleep information (NSD, DSD, subjective sleep loss, night waking, and sleep onset difficulties) was collected by parental questionnaires at 3-, 12-, 36-, and 60-month. We identified sleep multitrajectory groups using group-based multitrajectory modeling in children and examined their associations with parental sleep multitrajectory groups using multinomial logistic regressions.

Results: We identified three sleep multitrajectory groups in children: the "No/few" group (29.4%) had moderate NSD, long DSD, low subjective sleep loss/night waking/sleep onset difficulties prevalence, the "Moderate" group (60.0%) had long NSD and moderate DSD, and medium subjective sleep loss/night waking/sleep onset difficulties prevalence, and the "Global" group (10.6%) had the shortest NSD and DSD, and the highest subjective sleep loss/night waking/sleep onset difficulties prevalence. After adjusting for covariates, mothers in the "Global" group were more likely to have children in the same group, and mothers in "Subjective" and "Global" groups were less likely to have children in the "Moderate" group than in the "No/few" group. No association was identified with paternal or couple sleep multitrajectory groups.

Conclusions: The observed associations between parent-child sleep multitrajectory groups suggest greater maternal sensitivity to or involvement in the child's sleep than the fathers. Early preventive sleep actions could improve sleep in children and mothers.

Goal and aims: Performance evaluation of automatic sleep staging on two-channel subcutaneous electroencephalography.

Focus technology: UNEEG medical's 24/7 electroencephalography SubQ (the SubQ device) with deep learning model U-SleepSQ.

Reference method/technology: Manually scored hypnograms from polysomnographic recordings.

Sample: Twenty-two healthy adults with 1-6 recordings per participant. The clinical study was registered at ClinicalTrials.gov with the identifier NCT04513743.

Design: Fine-tuning of U-Sleep in 11-fold cross-participant validation on 22 healthy adults. The resultant model was called U-SleepSQ.

Core analytics: 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.

Additional analytics and exploratory analyses: 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.

Core outcomes: There was a strong agreement between the focus and reference method/technology.

Important supplemental outcomes: The confidence score was a promising metric for estimating the reliability of each hypnogram classified by the system.

Core conclusion: 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.

Objectives: Black and older adults have higher risk for sleep problems than their White and younger counterparts. Yet, our understanding of the determinants of sleep problems specifically among older Black adults is severely limited. The aim of this study was to determine whether everyday and major discrimination are longitudinally associated with sleep disturbance in a nationally representative sample of older Black adults.

Methods: Non-Latinx Black respondents aged 51+ were selected from waves 8 (2006) through 15 (2020) of the Health and Retirement Study (baseline N = 1397). Sleep disturbance was measured with the 4-item Jenkins Sleep Questionnaire. The 6-item Everyday Discrimination Scale was used to measure everyday discrimination, and the Major Experiences of Discrimination Scale was used to measure major discrimination. Analyses controlled for sociodemographics, health behaviors, and health conditions. Lagged mixed-effects linear regression models were performed to test the longitudinal associations between baseline discrimination and sleep disturbance over 12years.

Results: Higher baseline everyday discrimination was longitudinally associated with more severe sleep disturbance. Compared to respondents who reported no major discrimination at baseline, those who reported two or more major discrimination experiences had more severe sleep disturbance over time.

Conclusions: This study provides critical information on the possible longitudinal drivers of sleep disparities at the population level. This information has implications for better understanding the mechanisms of health disparities and for attaining health equity.