Nature and Science of Sleep最新文献

Background: Sleep disruptions among prospective university students are increasingly recognized for their potential ramifications on academic achievement and psychological well-being. But, information regarding sleep issues among students preparing for university entrance exams is unknown. Thus, this study aimed to investigate the prevalence and factors associated with sleep duration and insomnia among university entrance test-takers in Bangladesh, utilizing both traditional statistical analyses and advanced geographic information system and machine learning techniques for enhanced predictive capability.

Methods: A cross-sectional study was conducted in June 2023 among 1496 entrance test-takers at Jahangirnagar University, Dhaka. Structured questionnaires collected data on demographics, academic information, and mental health assessments. Statistical analyses, including chi-square tests and logistic regression, were performed using SPSS, while machine learning models were applied using Python and Google Colab.

Results: Approximately 62.9% of participants reported abnormal sleep duration (<7 hours/night or >9 hours/night), with 25.5% experiencing insomnia. Females and those dissatisfied with mock tests were more likely to report abnormal sleep duration, while repeat test-takers, those with unsatisfactory mock test results, or anxiety symptoms had a higher risk of insomnia. Machine learning identified satisfaction with previous mock tests as the most significant predictor of sleep disturbances, while higher secondary school certificate GPA had the least influence. The CatBoost model achieved maximum accuracy rates of 61.27% and 73.46%, respectively, for predicting sleep duration and insomnia, with low log loss values indicating robust predictive performance. Geographic analysis revealed regional variations in sleep disturbances, with higher insomnia prevalence in some southern districts and abnormal sleep duration in northern and eastern districts.

Conclusion: Sleep disturbances are prevalent among prospective university students and are associated with various factors including gender, test-taking status, mock test satisfaction, and anxiety. Targeted interventions, including sleep education and psychological support, hold promise in ameliorating sleep health and overall well-being among students, potentially enhancing entrance test performance.

Objective: This longitudinal study examined the reciprocal relationship between sleep disturbances with non-suicidal self-injury and whether self-compassion mediates these associations.

Methods: A total of 5785 freshmen were sampled from a large-scale health-related cohort among Chinese college students at the baseline. This study spanned six waves with a six-month interval between each wave. Data from the last four waves were used because self-compassion or non-suicidal self-injury was not measured in the first two waves. The cross-lagged panel models were used to examine the longitudinal dynamic relationships between sleep disturbances, self-compassion, and non-suicidal self-injury.

Results: The results showed that all the auto-regressive paths were significant. For the cross-lagged paths, there was a reciprocal relation between sleep disturbances and self-compassion. Importantly, self-compassion played a longitudinal mediating role in the prediction from sleep disturbances to non-suicidal self-injury (indirect effect = 0.007 to 0.009, all p values < 0.001).

Conclusion: Psychological interventions targeting improved sleep quality and self-compassion may hold great promise for reducing the incidence of non-suicidal self-injury.

Narcolepsy type 1 (NT1) is a unique central sleepiness disorder that affects individuals with excessive daytime sleepiness (EDS), cataplexy, sleep paralysis, and hypnagogic hallucinations. The etiology and pathogenesis of NT1 remains unclear, although some viral infections are thought to be related to NT1. This paper reports an unusual case of late-onset NT1 with human immunodeficiency virus (HIV) infection and antiretroviral therapy for five years. The relationship between HIV infection, immune, Immune reconstitution inflammatory syndrome (IRIS) and NT1 should be further investigated, as excessive daytime sleepiness is more common in HIV-infected patients than in the general population.

Purpose: Exposure to artificial light influences human performance, which is essential for maintaining healthy work and sleep. However, existing research has not explored the intrinsic links between sleep performance and human states over time under prebedtime light exposure interventions (LEIs).

Methods: To investigate the time-dependent effects of altered prebedtime light exposure, four LEI groupings (#L1 - #L4) and a Time factor (D8, D9, and D10) were chosen for sleep experiments in enclosed spaces. Forty-eight young adults recruited were available for data analysis. Subjective alertness (SA), negative affect (NA), subjective sleep, and objective sleep were measured via the Karolinska Sleepiness Scale, Positive and Negative Affect Schedule, Next-day Self-assessment Sleep Quality, and joint assessment of wrist actigraphy and sleep diaries, respectively. Statistical analysis was used for the effects of light exposure on the human states (corresponding to the SA and NA) and sleep performance, while the process model helped construct the associations between the two.

Results: The statistical effects revealed that the Time had a significant main effect on subjective sleep and changes in prebedtime alertness; the LEI had a significant main effect only on sleep onset latency (SOL). After undergoing altered prebedtime light exposure, the mean SA increased at prebedtime of D9 (p = 0.022) and D10 (p = 0.044); No significant effect on the NA was observed; Mean subjective sleep had a significant increase from D8 to D10. Moreover, five actigraphy-estimated sleep parameters were interrelated. In light of this, a chained pathway relationship was identified. The SOL played a mediating predictor between prebedtime state and objective sleep, which was linked to the awakening state through subjective sleep.

Conclusion: Our study suggests that time-dependent effects of altered prebedtime light exposure on sleep performance are associated with human states at prebedtime and awakening, with implications for its prediction of sleep health.

Purpose: Although experimental psychopathology using PET, EEG, and fMRI is at the forefront of understanding the underlying mechanisms of sleep inertia, many questions concerning causality remain unanswerable due to ethical constraints and the use of small and heterogeneous samples in experimental methods. There is a pressing need for a novel perspective in a large and relatively homogeneous population to fully capture and elucidate longitudinal processes and dynamic causality that culminate in episodes of sleep inertia over time. Therefore, this study aimed to reveal the causal relationships between symptoms of sleep inertia across its distinct patterns.

Patients and methods: A total of 1636 intern nurses participated in the first survey (94.1% validity rate), then 1277 intern nurses were followed up (82.9% tracing rate). Symptoms of sleep inertia were self-reported using the Sleep Inertia Questionnaire. The cross-lagged panel network models were used to examine unique longitudinal relationships between symptoms of sleep inertia across distinct trajectories.

Results: Four distinct trajectories of sleep inertia were established. Additionally, we found differences in those symptoms with the highest influence on other symptoms at the subsequent point across the networks of four trajectories, particularly, "Difficulty in concentrating" in the persistent-high group and "Feeling tense" in the deteriorating groups.

Conclusion: The current study highlights changes in sleep inertia based on the long-term course over time. Notably, symptoms of "Difficulty in concentrating" and "Feeling tense" are imperative to address these specific symptoms within subpopulations.

Purpose: There are currently no ideal indicators for predicting the cardiovascular risk of obstructive sleep apnea (OSA). This study aimed to employ urinary metabolomics to detect early cardiovascular risk in patients with moderate-to-severe OSA.

Patients and methods: Male participants who underwent polysomnography from November 2020 to May 2021 were screened. Clinical data, polysomnography data and urine samples were collected. Untargeted metabolomics analyses of urine were performed. Multivariate analyses and receiver operating characteristic (ROC) curve analyses were subsequently performed to identify potential biomarkers. Associations between metabolites and clinical indicators and cardiovascular risk were examined through linear regression analyses with interaction and mediation analyses.

Results: Thirty-six male participants were included in the study, comprising 22 males with moderate-to-severe OSA and 14 age-matched controls, with an average age of 39.6 ± 9.2 years. We identified 65 metabolites in the study, involving pathways including pyrimidine, androgen, estrogen, vitamin B6 and sulfate/sulfite metabolism. Among them, epinephrine sulfate was the most significantly altered metabolite. ROC analyses highlighted that epinephrine sulfate had the highest area under the curve (AUC=0.883) for detecting moderate-to-severe OSA. Epinephrine sulfate was statistically correlated with OSA severity, hypoxia-related indicators (apnea-hypopnea index: r=0.685; oxygen desaturation index: r=0.743, p<0.0001), arterial stiffness (arterial augmentation index: r=0.361, p=0.031) and long-term cardiovascular risk (Framingham cardiovascular risk: r=0.375, p=0.024). Linear regression analysis revealed that epinephrine sulfate was significantly associated with an increased in the Framingham risk (β = 0.004, 95% CI = 0.000-0.009, p = 0.049), with the effect partly mediated by systolic blood pressure (27.6%) and not moderated by other factors. Additionally, it also significantly associated with the increased in the arterial augmentation index (β = 0.019, 95% CI = 0.000-0.037, p = 0.046), with the effect fully mediated by blood pressure and not moderated by other indices statistically.

Conclusion: There are significant metabolic pathway alterations in moderate-to-severe OSA patients. Urinary epinephrine sulfate markedly predicts early cardiovascular risk in OSA patients.

Background: Sleep complaints were reported to be associated with stroke, however, the evidence on the association between healthy sleep pattern and stroke risk in Chinese is limited.

Objective: The aim of this study was to investigate the association between healthy sleep pattern and stroke in Chinese, and the influence of metabolic diseases on the association.

Methods: A total of 11,851 participants from the Kailuan study in China without stroke at baseline were included. We calculated a healthy sleep score according to four sleep factors, and defined the low-risk groups as follows: no insomnia, no excessive daytime sleepiness, no frequent snoring, and sleep 7-8h/d. Each low-risk sleep factor was assigned a score of 1. Cox proportional hazard models were used to assess the association between healthy sleep score and stroke. Mediation analysis was used to estimate the role of metabolic diseases (obesity, diabetes, and hypertension) in the healthy sleep score-stroke association.

Results: During a mean follow-up period of 7.7 years, 504 cases of stroke were identified. A higher healthy sleep score was associated with a lower risk of stroke in a dose-response manner (P-trend=0.03). The adjusted hazard ratio (HR) for participants with a healthy sleep score of 4 versus ≤2 was 0.75 (95% confidence interval [CI]: 0.56, 0.96). In addition, obesity, diabetes, and hypertension collectively explained 21.9% (95% CI: 17.2, 26.5) of the association between healthy sleep score and stroke.

Conclusion: Adherence to healthy sleep pattern was associated with a lower risk of stroke, and the favorable association was partially mediated by metabolic diseases.