Sleep Health最新文献

Objectives: Healthy sleep is vital for firefighter safety, health, wellness, and for public well-being. However, professional firefighters experience disturbed sleep at disproportionately high rates. The current study investigated firefighter sleep in terms of (1) differences in on-duty and off-duty sleep, (2) risk factors for poor sleep, and (3) whether risk factors differed for on-duty and off-duty sleep.

Methods: Professional firefighters from a large, urban fire department in central Virginia (N = 268) reported their sleep using the Pittsburgh Sleep Quality Index both on- and off-duty. Participants also provided information related to demographic characteristics, work (e.g., length of service), general health (self-rated health and pain), and mental health (Patient Health Questionnaire-2 and Generalized Anxiety Disorder-2).

Results: Using a repeated measures MANOVA, on-duty sleep was significantly worse compared to off-duty sleep F(8250) = 40.80, p<.001, η² = .57. On-duty, 84% of firefighters were classified as poor sleepers compared to 53.4% off-duty. Significant associations were observed between work-related factors, health-related factors, and mental health-related factors and on-duty and off-duty sleep; however, the strength of associations was generally greater for on-duty sleep.

Conclusions: Healthy sleep is possible for professional firefighters, as nearly half were classified as "good sleepers" while off-duty. Nonetheless, on-duty sleep was significantly worse overall, and risk factors for poor sleep showed stronger associations with on-duty sleep than off-duty sleep. When working a 24-hour variable shift schedule, it appears that poor sleep may "carryover" from on-duty to off-duty days. Further research is needed to test behavioral and environmental approaches to promote healthy sleep among professional firefighters.

Objectives: This study aims to investigate the associations between past shift work and hyperhomocysteinemia and further explore the modification effects of MTNR1A rs12506228 and MTNR1B rs10830963 (2 single-nucleotide polymorphisms in melatonin receptor genes) on this association.

Methods: Based on the data of 14,043 retirees from the Dongfeng-Tongji cohort, multivariate logistic regression was used to analyze the association between past shift work duration and hyperhomocysteinemia, and gene-environment interaction analysis was performed.

Results: Among 14,043 retirees from the Dongfeng-Tongji cohort, we found that retirees with longer durations of past shift work were significantly associated with higher odds of hyperhomocysteinemia (odds ratio and 95% confidence interval for per 5-year increase: 1.04 [1.02-1.06], P<.001). Furthermore, MTNR1B rs10830963 significantly exacerbated the effect of long-duration past shift work on hyperhomocysteinemia odds (P-trend<.001, P-interaction=.01), and MTNR1A rs12506228 had a joint effect with past shift work on hyperhomocysteinemia odds (P-trend<.001, P-interaction=.89).

Conclusions: The long-term hazard of shift work on hyperhomocysteinemia persisted from past to post retirement, and such association could be modified by MTNR1B rs10830963.

Objectives: Sleep disturbances can impair cognition, and cognitive impairment can dysregulate sleep-wake cycles. Despite biological plausibility, disparities in the sleep-cognition relationship are understudied in nationally representative samples.

Methods: Using National Health Interview Survey data from 2011-2018, we investigated cross-sectional associations between sleep and cognition among adults aged ≥40 years overall and by age, sex, race, and ethnicity. Participants self-reported sleep duration (short [<7-hours], long [>9-hours]); insomnia symptoms (trouble falling asleep or staying asleep ≥3 times/week); and non-restorative sleep (waking feeling unrested ≥4 days/week). Cognitive impairment was defined as "not being able to/having a lot of difficulty remembering or concentrating" based on the Washington Group Short Set on Functioning. Adjusted Poisson regression with robust variance estimated prevalence ratios (PRs) and 95% confidence intervals.

Results: Among 73,477 adults (mean age ± standard error 58.3 ± 0.07 years), 31.8% reported short sleep, 4.1% long sleep, 35.7% insomnia symptoms, and 35.5% non-restorative sleep. Overall, 2.2% reported cognitive impairment. All sleep dimensions were associated with a higher prevalence of cognitive impairment (range: PR_short-sleep = 1.23[95% confidence interval:1.07-1.42] to PR_long-sleep = 4.10[3.48-4.83]). Short sleep, insomnia symptom, and non-restorative sleep were more strongly associated with cognitive impairment among middle-aged adults. Associations with long sleep were stronger among older adults. Differences by sex were not observed. While the prevalence of cognitive impairment was slightly higher among Hispanic/Latine and Black adults, associations with short sleep were strongest among White adults and among Asian adults for long sleep (p-interaction<0.05).

Conclusions: Sleep disturbances were associated with cognitive impairment. Most associations were stronger among middle-aged adults, although future studies with objective measures are warranted.

Objectives: This study investigates the association between sleep and precarious working conditions in the digital platform economy. Specifically, we examine how six dimensions of employment precariousness are associated with the likelihood of experiencing sleep problems among online platform workers (OPW).

Methods: We analyze survey data from German-speaking OPW (N = 1969). Sleep outcomes are measured using the Jenkins Sleep Scale (JSS-4), and precariousness is captured by six factor scores derived from an exploratory factor analysis, based on adapted questionnaire items from the Employment Precariousness Scale (EPRES). Logistic regression models with average marginal effects are used to estimate associations, controlling for sociodemographic and work-related characteristics.

Results: Among the six dimensions of precariousness, two are robustly associated with higher likelihood of reporting sleep problems: Time poverty (the inability to take breaks and leave when needed) and vulnerability (reflecting opaque rating and payment systems). A typical variation across each of these scales corresponds to a 7.7%-8.1% increase in the probability of reporting elevated sleep problems.

Conclusions: Our findings highlight that platform-related working conditions, particularly opaque management systems and limited ability to take time off, are important correlates of sleep problems among OPW. Addressing these factors may contribute to improving sleep health in this growing segment of the workforce.

Introduction: Sleep disorders are a major public health issue, and urban noise may contribute to their prevalence. However, no large-scale geospatial studies have specifically examined the relationship between sleep quality and noise in urban settings.

Methodology: This cross-sectional study, conducted in Geneva, Switzerland, between June and September 2023, involved 3691 participants (mean age 54.84 years, 59.7% women). Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while nighttime traffic noise exposure was measured using the sonBASE georeferenced database from the Swiss Federal Office for the Environment. Spatial statistics (Getis-Ord Gi*) were employed to identify spatial clusters of sleep disturbances and noise exposure.

Results: Analysis revealed that sleep quality issues and associated indicators were not randomly distributed. Spatial patterns were observed in both subjective noise perception and objective noise measures.

Conclusion: Poor sleep quality in urban environments is spatially correlated with noise exposure, suggesting the need for targeted interventions to mitigate these effects.

Objectives: Attention-deficit/hyperactivity disorder (ADHD) has been linked to sleep disturbances. There is little evidence of this association among a nationally representative sample of school-aged children. This study explored the association between current ADHD diagnosis and short sleep duration among U.S. school-aged children. Parent-reported severity of ADHD and short sleep duration among those with a current ADHD diagnosis was also assessed.

Methods: A secondary analysis of 2020-2021 National Survey of Children's Health (NSCH) data including 26,148 U.S. children ages 6-11 years was performed. Sleep duration was categorized using the National Sleep Foundation's age-specific recommendations defining <9 hours as short sleep duration. Weighted unadjusted and adjusted logistic regression models were performed. The adjusted models included child age, sex, race/ethnicity, health status, overweight status, screen time, physical activity, parent education, family structure, and federal poverty level.

Results: Nearly 10% of children currently had an ADHD diagnosis, with 62% having moderate or severe ADHD. Over one-third (35%) had reports of short sleep duration. Unadjusted (odds ratio [OR] = 1.58, 95% confidence interval [CI] = 1.35-1.84) and adjusted (adjusted OR [AOR] = 1.25, 95%CI = 1.06-1.47) results indicated that children with ADHD were at increased odds of having short sleep duration compared to children without ADHD. Among children with ADHD only, unadjusted (OR = 1.70, 95%CI = 1.26-2.31) and adjusted (AOR = 1.61, 95%CI = 1.19-2.19) results indicated that children with a moderate or severe diagnosis were at increased odds of having short sleep duration than children with a mild diagnosis.

Conclusion: ADHD may influence short sleep duration among U.S. school-aged children. Behavioral sleep treatments should aim toward improving sleep duration among this population.

Objectives: The potential reasons why long sleepers are at increased risk, including cardiovascular events and mortality, are intriguing. This study aimed to explore independent variables related to long (primary aim) and short sleep duration (SDUR) (secondary aim) using objective measurements in a large sample of adults.

Methods: Participants from the ELSA-Brasil study performed a standard clinical evaluation, sleep questionnaires, a home sleep monitoring to determine obstructive sleep apnea (OSA; apnea-hypopnea index ≥15 events/hour), and a 7-day actigraphy to measure SDUR. A multinomial regression analysis was used to identify the predictors of long (≥8 hours) and short (<6 hours) SDUR relative to the reference group (6 to <8 hours).

Results: A total of 2062 participants were included in the analysis (age: 49 ± 8 years; 57.3% women). A third of them had OSA. The mean SDUR was 6.55 ± 0.49 hours. Long and short SDUR were observed in 6.5% and 26.9%, respectively. In the multinomial logistic regression analysis, older individuals (OR = 1.36; 95% CI 1.07-1.75) and depression disorder (OR = 2.59; 95% CI 1.26-5.3) were independently associated with long SDUR. In contrast, the independent variables associated with short SDUR were male sex (OR = 1.9; 95% CI 1.51-2.4), Black participants (OR = 1.75; 95% CI 1.29-2.36), excessive daytime sleepiness (OR = 1.49; 95% CI 1.20-1.86), and OSA (OR = 1.48; 95% CI 1.16-1.88).

Conclusions: In a large multiethnic cohort, we observed significant heterogeneity in the long and short SDUR predictors. Important characteristics such as age and depressive disorder might provide tips for the curious higher cardiovascular risk associated with long SDUR.

Objective: We investigated whether kindergarten bedtime and later sleep duration predicted executive function (EF), behavior, and academic achievement in middle childhood, and whether associations varied by socioeconomic status (SES), race or ethnicity, and disability. By accounting for the independent effects of these factors, findings reflect the unique associations between early sleep patterns and later developmental outcomes.

Methods: Data were drawn from the nationally representative Early Childhood Longitudinal Study, Kindergarten Cohort of 2010-11 (N = 6945). Structural equation modeling (SEM) tested whether kindergarten bedtime (age 5, 2010-2011) predicted third-grade sleep duration (age 9), which in turn influenced fourth-grade EF and behavior (age 10), and fifth-grade academic test scores (age 11, 2015-2016). We examined whether sleep duration mediated bedtime's association with EF, behavior, and achievement; whether EF and behavior mediated sleep duration's association with achievement; and whether these associations were also moderated by SES, disability, and race or ethnicity.

Results: Bedtime predicted duration, which predicted higher achievement through effects on cold EF (i.e., emotionally neutral cognitive processes like working memory and cognitive flexibility). These indirect effects were observed across racial or ethnic and SES groups but became nonsignificant after adjusting for covariates. Although cold EF was the strongest predictor of achievement, duration remained a small but significant contributor.

Conclusions: Disparities in achievement by SES and race or ethnicity may be driven by structural factors beyond sleep duration or bedtime. Promoting early bedtime routines is important, but broader systemic interventions are needed to close achievement gaps.

Objective: To examine how load shedding (scheduled power outages) affects multiple dimensions of sleep health, associated behaviors, and lived experiences among South African adults.

Methods: This study used a convergent mixed-method cross-sectional design. Data were collected through an online survey, that included demographic questions, the RU SATED questionnaire, structured items evaluating sleep-related behavioral changes, and an open-ended question for qualitative insights. A total of 173 participants experiencing load shedding in South Africa completed the survey between May and August of 2023. Quantitative analyses comprised nonparametric tests and multiple linear regression, whereas qualitative responses were subjected to thematic analysis. Data integration was achieved through joint display and thematic triangulation.

Results: Overall sleep health scores significantly declined with increasing load shedding severity (p = .023), particularly affecting sleep satisfaction (p < .001) and duration (p = .002). Participants exposed to stage six load shedding demonstrated significantly poorer sleep health scores compared to those exposed to lower stages (p < .001). Two themes were developed through qualitative analysis: (1) disruption of sleep quality due to environmental disturbances (noise, light, and temperature), and (2) emotional and psychological stress (anxiety, and safety concerns). Structured survey items further indicated disruptions to sleep continuity, regularity and duration.

Conclusion: In this study, load shedding affected multiple dimensions of sleep health through environmental disruption, psychological strain, and adaptive behavioral responses. These preliminary findings highlight the need for replication in diverse populations using objective measures and suggest that integrating sleep health considerations into energy policy may be warranted.