Sleep Health最新文献

Objectives: Obstructive sleep apnea (OSA) and cardiovascular disease (CVD) are common among former National Football League (NFL) athletes. The Living Heart Foundation Heart-Obesity-Prevention-Education Group aimed to provide an in-depth health assessment for CVD risk factors among former NFL players to examine the role of OSA on blood pressure (BP) and echocardiographic measurements. We hypothesized that OSA, maladaptive echocardiographic measurements, and elevated BP would be highly prevalent in former NFL athletes, and that OSA presence would detrimentally impact echocardiographic parameters.

Methods: One hundred fifty-three former NFL athletes were enrolled in the present study by the Living Heart Foundation. Participants (n = 86) completed a cardiovascular health assessment consisting of clinical BP readings and transthoracic echocardiography (TTE), which included measurements of ejection fraction, left atrial size, left ventricle diastolic diameter, intraventricular septal thickness, and ascending aortic diameter. Participants (n = 110) were offered an at-home overnight sleep test to estimate sleep apnea presence and severity.

Results: Eighty percent (n = 80) of our sample exhibited at least mild OSA. Further, 34% (n = 29) displayed elevated intraventricular septal thickness and subclinical aortic dilation was present in 47% (n = 40) of retired NFL athletes. In a subanalysis of former players with at-home sleep apnea testing results and TTE measures (n = 43), NFL retirees with OSA demonstrated greater ascending aortic diameter compared to former NFL athletes without OSA (p = .048).

Conclusions: There is a high prevalence of suspected OSA, in addition to maladaptive cardiac remodeling, among retired NFL athletes. Aortic abnormalities may be related to untreated OSA in this population.

Objective: War is a significant factor affecting human health, including sleep and quality of life, however, the characteristics of these differences among university students remain insufficiently studied. This study aimed to comprehensively assess sleep quality, chronotype, and quality of life indicators among students under wartime conditions, to analyze their inter-relationships, and to identify clusters based on their combined patterns.

Methods: A cross-sectional study included 130 students aged 18-25 years. The Pittsburgh Sleep Quality Index (PSQI), the Morningness-Eveningness Questionnaire (MEQ), and the Short Form-36 Health Survey (SF-36) were used to assess sleep quality, chronotype, and quality of life.

Results: Poor sleep quality was identified in 67.7% of participants (PSQI: 5.92 ± 2.96). Students with poor sleep quality were more likely to live separately from family members (p < .05) and to consume alcohol (p < .05). According to chronotype, participants were classified as intermediate (74.6%), morning (9.2%), or evening (16.1%). The evening chronotype was associated with lower vitality scores (p < .05) and more frequent alcohol consumption (p < .05). Poor sleep quality was associated with lower scores in the physical and mental health components; the mental component of quality of life emerged as an independent predictor of poor sleep quality (OR = 0.41; 95% CI: 0.20-0.86). Cluster analysis identified four distinct profiles of sleep quality, chronotype, and quality of life, ranging from optimal to less favorable.

Conclusions: The findings indicate that, under wartime conditions, the interaction between sleep quality, chronotype, and quality of life among students forms four distinct profiles, reflecting the multidimensional nature of the impact of the war context on sleep and related aspects of students' quality of life.

Consumer sleep technologies are increasingly used by the public and have become common tools for their daily living. This trend presents new possibilities for innovative sleep measurement and individualized insights about improvements in sleep health and related outcomes. The National Sleep Foundation (NSF) calls for action across a range of stakeholders, including the public, healthcare providers, education and government organizations, industry, and funding agencies and organizations. Understanding the potential utility and limitations of consumer sleep technologies is an important first step. With appropriate approaches, consumer sleep technologies can present unique promise and powerful possibilities that align well with National Sleep Foundation's goal to rapidly incorporate sleep science and insights into accessible products and services.

Background: While insufficient sleep is associated with poor lifestyle factors, a multidimensional approach assessing multiple sleep health dimensions via subjective and objective measures has emerged as a more comprehensive method of investigating these relationships. We examine the multidimensional association between sleep health, diet, and physical activity (PA).

Methods: We studied 373 adolescents from the Penn State Child Cohort (16.4 ± 2.3 years; 46.6% female; 20.9% racial/ethnic minority), of whom 234 (63.5%) were evaluated while in-school. Sleep dimensions were assessed via self-reports, actigraphy (ACT), and polysomnography (PSG). PA was assessed via ACT and self-reports, metabolic equivalent of task (MET) via ACT, and diet via self-reports. Stepwise multivariable-adjusted regression models tested the association between sleep dimensions and lifestyle factors.

Results: Later self-reported and ACT-measured bedtime and rising time were associated with more snacking, higher caloric intake, and sedentarism. A later ACT-measured sleep midpoint was associated with higher carbohydrate intake and more snacking. Higher ACT-measured sleep variability was associated with higher sedentarism. Longer self-reported or ACT-measured sleep latency was associated with more snacking and higher PA and METs. Longer ACT-measured time in bed was associated with lower PA. Sleep dimensions were more strongly associated with diet, PA, and sedentarism among adolescents evaluated while in-school, whereas they were more strongly associated with snacking among those on-break. PSG-measured sleep dimensions were not strongly associated with lifestyle factors; although a greater apnea/hypopnea index was associated with lower METs and greater sedentarism, it was not significant after adjusting for BMI.

Conclusions: Evaluating sleep with a multidimensional approach better captures its association with lifestyle factors. Future research should assess downstream effects on cardiovascular outcomes.

Objectives: We investigated cross-sectional associations between perceived discrimination and actigraphic sleep health among young adults.

Methods: Data from the age 22 wave (mean ± SD age = 22.1 ± 0.4 years) of the Future of Families and Child Wellbeing Young Adult Sleep Study, a national birth cohort originally drawn from 20 U.S. cities, included young adults (n = 334; 68.9% Black, 14.7% Hispanic/Latino) who self-reported experiences of discrimination. Wrist-worn actigraphy was collected across ∼2 weeks from 2020-2024 and measures included sleep duration, onset, midpoint, maintenance efficiency (SMeff), and wake after sleep onset (WASO). Multiple linear regression models examined the association between experiencing a specific type of discrimination and dimensions of sleep health, adjusting for sociodemographic characteristics.

Results: Job-based discrimination was associated with shorter sleep duration. Age-based discrimination was associated with worse sleep quality (more WASO and lower SMeff).

Conclusions: We found that the association between perceived discrimination and sleep health varied by type of experience and the sleep dimension examined. Future research using longitudinal designs, nuanced measures of discrimination, or interventions targeting coping and stress regulation may help clarify discrimination-sleep pathways and reduce sleep disparities.

Objectives: Obstructive sleep apnea (OSA) is a common sleep disorder associated with poor cardiometabolic and neurocognitive outcomes; however, the role of ambient air pollution in OSA remains unclear. We investigated the association between ambient air pollution exposure and OSA risk in Korean adults using individual-level exposure estimates.

Methods: We analyzed data from 4235 adults aged ≥40 years in the 2019 Korea National Health and Nutrition Examination Survey. The OSA risk was assessed using the STOP-Bang questionnaire. Individual exposure to air pollutants-particulate matter (PM) ≤2.5 µm (PM_2.5) and ≤10 µm (PM₁₀), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and ozone (O₃)-was estimated using geocoded residential data. Regression models and threshold-based analyses were used to assess associations across various exposure windows, adjusting for major sociodemographic, lifestyle, and clinical covariates.

Results: An increase in the interquartile range of PM_2.5 (8.9 µg/m³) at a 30-day average was associated with a higher risk of OSA (adjusted odds ratio [OR]: 1.140, 95% confidence interval [CI]: 1.00-1.29). PM₁₀ exposure showed consistent associations with intermediate OSA risk (STOP-Bang 3-4), with the strongest effects observed at 90 days (OR: 1.340, 95% CI: 1.05-1.69). CO exposure above the 480 ppb threshold was associated with a higher risk of OSA at 90 days (OR: 1.337, 95% CI: 1.00-1.77) and 180 days (OR: 1.495, 95% CI: 1.12-2.00). NO₂, SO₂, and O₃ showed no associations with OSA risk after adjustment.

Conclusions: Mid-term (1-6 months) exposure to PM and CO was associated with a modestly increased screening-defined OSA risk.

Background: Heart failure is a major public health burden, and insomnia has emerged as a potential risk factor for heart failure development. Although a small amount of clinical evidence supports this association, the underlying molecular mechanisms remain poorly understood.

Methods: Based on 52,273 participants from the UK Biobank, plasma samples were analyzed for 2911 proteins by using Olink technology. Insomnia was assessed through self-reported questionnaires. Linear regression and LASSO regression revealed that plasma proteins were associated with insomnia. LASSO regression was used to construct proteomic signatures associated with insomnia. Cox regression models were used to assess the relationship between insomnia and insomnia-related proteomic signatures and heart failure; additionally, mediation analyses identified key proteins that potentially mediate the association between insomnia and heart failure.

Results: Insomnia (reported "usually") was independently associated with an increased heart failure risk (HR: 1.39; 95% CI: 1.17-1.65). The study identified 118 proteins associated with insomnia that are primarily associated with immune inflammation and metabolism, as well as complement and coagulation cascades. Proteomic signatures constructed by using these 118 proteins were also independently associated with the risk of new heart failure. Mediation analysis revealed 68 proteins potentially mediating the insomnia-heart failure relationship through similar pathways. TNF, CD4, AMBP, SPP1, and ITGAM were identified as central hub proteins in the protein-protein interaction network.

Conclusion: This study demonstrates that insomnia significantly increases heart failure risk through multiple molecular pathways, which primarily involve inflammatory responses and complement cascade activation. Sleep quality optimization may provide additional benefits in the prevention of heart failure.