BACKGROUND: The association between sleep patterns and young students\' mental health, which is crucial for their development, remains understudied in rural China. Therefore, the relationship between sleep patterns and mental health among primary and junior high school students in rural China was examined.
METHODS: A total of 1592 primary and junior high school students from rural areas of Gansu Province were surveyed, and the Depression Anxiety and Stress Scale (DASS) was utilized to assess mental health, alongside self-reported data on their daily sleep patterns.
RESULTS: Significant sleep inadequacies were identified: 28% of students received less than 8 h of sleep on weekdays, and 19% went to bed later than recommended. On weekends, 38% of students had delayed bedtimes, though only 7.2% received less than 8 h of sleep. Notably, a \"U-shaped\" relationship was uncovered between sleep duration and mental health for students on weekends, with optimal mental health correlated with receiving 10-11 h of sleep, while both shorter and longer sleep durations on weekends worsened outcomes. This pattern is absent on weekdays. Additionally, adequate sleep and an earlier bedtime was linked to a 6-8% decrease in mental health risks.
CONCLUSIONS: These findings provide valuable insights for policymakers seeking to enhance student mental well-being in rural settings, emphasizing the importance of implementing measures that promote balanced sleep habits among young students.

UNASSIGNED: This study investigated associations between the use of electronic media and sleep in children and young adolescents, with a specific focus on the moderation of associations by sex and age.
UNASSIGNED: Between 2021 and 2022, 453 10- to 14-year-old children participating in the LIFE Child cohort study (Germany) reported on their use of electronic media (daily screen time, use at bedtime, device ownership) and on their sleep difficulties (Sleep Self Report). Associations between media use and sleep as well as interactions with age and sex were assessed using linear regression analyses.
UNASSIGNED: The analyses revealed significant associations between the use of media at bedtime and bedtime problems (in girls only), sleep behavior problems (in girls only), and daytime sleepiness (in girls and boys). Daily screen time, in contrast, was associated with none of the sleep difficulties. The number of media devices owned by the child was only associated with bedtime problems in girls, and this association lost statistical significance once media use at bedtime was included as further predictor.
UNASSIGNED: The findings underline the potentially sleep-disturbing role of electronic media at bedtime. Furthermore, they suggest that this effect is more pronounced in girls than in boys.

OBJECTIVE: To determine prospective associations between bedtime screen use behaviors and sleep outcomes one year later in a national study of early adolescents in the United States.
METHODS: We analyzed prospective cohort data from 9,398 early adolescents aged 11-12 years (48.4% female, 45% racial/ethnic minority) in the Adolescent Brain Cognitive Development Study (Years 2-3, 2018-2021). Regression analyses examined the associations between self-reported bedtime screen use (Year 2) and sleep variables (Year 3; self-reported sleep duration; caregiver-reported sleep disturbance), adjusting for sociodemographic covariates and sleep variables (Year 2).
RESULTS: Having a television or Internet-connected electronic device in the bedroom was prospectively associated with shorter sleep duration one year later. Adolescents who left their phone ringer activated overnight had greater odds of experiencing sleep disturbance and experienced shorter sleep duration one year later, compared to those who turned off their phones at bedtime. Talking/texting on the phone, listening to music, and using social media were all prospectively associated with shorter sleep duration, greater overall sleep disturbance, and a higher factor score for disorders of initiating and maintaining sleep one year later.
CONCLUSIONS: In early adolescents, several bedtime screen use behaviors are associated with adverse sleep outcomes one year later, including sleep disturbance and shorter weekly sleep duration. Screening for and providing anticipatory guidance on specific bedtime screen behaviors in early adolescents may be warranted.

UNASSIGNED: To evaluate the association between bedtime and infertility and to identify the optimal bedtime for women of reproductive age.
UNASSIGNED: We conducted a cross-sectional study using data from 3,903 female participants in the National Health and Nutrition Examination Survey (NHANES) from 2015 to 2020. The effect of bedtime on female infertility was assessed using the binary logistic regression in different models, including crude model and adjusted models. To identify the non-linear correlation between bedtime and infertility, generalized additive models (GAM) were utilized. Subgroup analyses were conducted by age, body mass index (BMI), waist circumference, physical activity total time, marital status, smoking status, drinking status and sleep duration.
UNASSIGNED: After adjusting for potential confounders (age, race, sleep duration, waist circumference, marital status, education, BMI, smoking status, drinking status and physical activity total time), a non-linear relationship was observed between bedtime and infertility, with the inflection point at 22:45. To the left side of the inflection point, no significant association was detected. However, to the right of it, bedtime was positively related to the infertility (OR: 1.22; 95% CI: 1.06 to 1.39; P = 0.0049). Subgroup analyses showed that late sleepers with higher BMI were more prone to infertility than those with a lower BMI (BMI: 25-30 kg/m2: OR: 1.26; 95% CI: 1.06 to 1.51; P = 0.0136; BMI ≥ 30 kg/m²: OR: 1.21, 95% CI: 1.09 to 1.34; P = 0.0014).
UNASSIGNED: Bedtime was non-linearly associated with infertility, which may provide guidance for sleep behavior in women of childbearing age.

UNASSIGNED: Glucose metabolism is impacted by circadian disruption. Dinner-bedtime interval (DBI) was an accessible indicator to reflect the alignment between dinner time and circadian clock. We aimed to investigate the association of DBI with type 2 diabetes mellitus (T2DM).
UNASSIGNED: 7676 adult subjects from the Henan Rural Cohort were included. Their demographic information including dinner time and bedtime was collected. Fasting venous blood samples were collected for biochemical determinations. Generalized linear regression model was used to analyze the factors influencing DBI. Furthermore, logistic regression incorporated with restricted cubic spline model was applied to evaluate the association between DBI and T2DM.
UNASSIGNED: The results of multiple linear regression model showed that age (β: -0.018, 95% CI: -0.021, -0.015) was negatively correlated with DBI. Female (β: 0.311, 95% CI: 0.229, 0.393), junior high school education (β: 0.246, 95% CI: 0.187, 0.306), high school education or above (β: 0.346, 95% CI: 0.259, 0.433), average monthly income with 1000-1999 CNY(0.102, 95% CI: 0.032, 0.171), average monthly income ≥ 2000 CNY (β: 0.164, 95% CI: 0.076, 0.251), moderate physical activity (β: 0.134, 95% CI: 0.071, 0.197), current smokers (β: 0.214, 95% CI: 0.118, 0.309), current drinkers (β: 0.099, 95% CI: 0.008, 0.190) were positively correlated with DBI. Furthermore, DBI was significantly associated with T2DM (adjusted OR: 0.910, 95%CI: 0.845-0.979, P = 0.012). DBI longer than 3 h was associated with decreased risk of T2DM (adjusted OR: 0.773, 95%CI: 0.648-0.921, P = 0.004).
UNASSIGNED: DBI larger than 3 h is beneficial to T2DM prevention. Further investigation is required to verify the association.

Introduction  About 65% of adult Americans report playing video games. Despite potential impacts to functioning, there is limited research on the relationship between video game use and sleep, specifically among adults. The present study expands upon the literature by describing demographic, video game, and sleep characteristics of an international adult sample of gamers. Methods  The participants were 3,481 adults aged 18 to 74 who responded to an online questionnaire about video game use (i.e., quantity of play, most common game type), general sleep characteristics (i.e., sleep onset latency [SOL]; duration, sleep timing, and sleep quality), and gaming-specific sleep disruptors (i.e., game-related night awakenings and sleep delays). Most identified as cisgender male (79.8%) and white (77%). Results  Participants reported an average SOL of 24.63 minutes, and most (64.5%) had a sleep duration from 7 to 9 hours with an overall average of 8.42 hours. Most (58.7%) reported that their sleep quality was fair to very poor . Bed and wake times were generally delayed, with 51% reporting a late evening or early morning bedtime and an average wake time of 8:28 am. A majority (81.2%) indicated that their bedtime was delayed due to game-related activities, but game-related night awakenings were less common. Conclusion  Although many report a sufficient amount of sleep, adult gamers tend to report sleep disruptions in other domains, particularly regarding a delayed sleep schedule and poor sleep quality. This may be attributable to game-related bedtime delays or other game-specific factors (e.g., game type) that should be evaluated in the future.

BACKGROUND: The COVID-19 lockdown had a profound effect on everyday life, including sleep health. This systematic review and meta-analysis evaluated changes in quantitative sleep parameters during the first lockdown compared with pre-lockdown in the general population.
METHODS: A search in scientific databases was performed to identify eligible observational studies from inception to 8 February 2023. We performed a random effects meta-analysis of those studies reporting (a) means of sleep duration, time in bed (TIB), and sleep timing (bedtime and wake-up time); (b) the percentages of atypical sleep duration before and during the lockdown; (c) the percentages of change in sleep duration and sleep timing.
RESULTS: A total of 154 studies were included. A small increase in sleep duration (0.25 standardized mean difference, 95% CI 0.180-0.315) was found, with 55.0% of the individuals reporting changes, predominantly an increase (35.2%). The pooled relative risk for sleeping more than 8/9 h per night was 3.31 (95% IC 2.60-4.21). There was a moderately significant delay in sleep timing and a surge in napping.
CONCLUSIONS: An increase in sleep duration and napping, and delayed sleep timing were observed. High-quality studies should evaluate whether these parameters have now become chronic or have returned to pre-lockdown values.

UNASSIGNED: Dementia is marked by a steady decline or worsening in cognitive abilities, affecting memory, logic, and social competencies. While many studies suggest a potential link between the amount of sleep and dementia risk, the outcomes are not yet consistent. This research delved into the relationship between sleep length and bedtime on cognitive abilities using an extensive dataset from the China Family Panel Studies (CFPS) from 2014 to 2020.
UNASSIGNED: Data from 175,702 observations were collected, including cognitive function test data from 22,848 participants. Various cognitive tests were used to assess cognitive function. Restricted cubic spline (RCS) models were used for data analysis.
UNASSIGNED: The optimal sleep duration for cognitive function was found to be 6-7 h, and the optimal bedtime was generally between 22:00-23:00. Longitudinal analysis revealed that sleep duration four years prior had a significant impact on current cognitive function. After accounting for various factors, those who slept for 7-8 h and over 8 h displayed lower cognitive function scores. Conversely, individuals sleeping less than 6 h had higher scores on the Vocabulary Test. Bedtime before 22:00 was associated with lower scores on the Vocabulary Test and Mathematical Test. Subgroup analyses based on age, gender, and urban residence showed variations in optimal sleep duration for different populations. Propensity Score Matching (PSM) analysis supported the findings.
UNASSIGNED: Maintaining a sleep duration of 6-7 h and a regular bedtime between 22:00-23:00 is important for optimizing cognitive performance.

OBJECTIVE: Sleep duration and bedtime may play a role in children\'s cardiometabolic health, but research is lacking. This study examined associations between sleep patterns and cardiometabolic risk factors in Swedish nine-year-olds.
METHODS: This cross-sectional study used data from three studies, where identical outcome measures were conducted in 411 nine-year-olds, 51% boys, between 2016 and 2020. Sleep was assessed with wrist-worn accelerometers and sleep journals. Children were grouped based on meeting the sleep guidelines of 9-11 h and going to bed early or late based on the median bedtime. Analysis of covariance was used to examine associations between sleep patterns and cardiometabolic risk factors.
RESULTS: Meeting sleep guidelines and going to bed early were associated with lower metabolic syndrome score (-0.15 vs. 0.42, p = 0.029), insulin resistance (0.30 vs. 0.60, p = 0.025) and insulin levels (6.80 vs. 8.87 mIU/L, p = 0.034), compared with their peers who did not meet the guidelines and went to bed later. When adjusting for total sleep time, analyses still showed associations with the metabolic syndrome score (-0.19 vs. 0.50, p = 0.011).
CONCLUSIONS: The findings indicate that good sleep patterns could help mediate positive overall cardiometabolic health in children.

UNASSIGNED: Sleep is a potentially modifiable factor associated with dementia, including Alzheimer\'s disease, but current evidence supporting this is insufficient.
UNASSIGNED: This study aimed to determine whether sleep duration and bedtime patterns are associated with the risk of dementia among middle-aged and older people.
UNASSIGNED: This cohort study had an eight-year follow-up period. Participants were 13,601 community-dwelling people aged 40-74 years living in Murakami (Niigata, Japan). Data were collected using a self-administered questionnaire. Predictors were self-reported sleep duration and bedtime, and the outcome was newly-diagnosed dementia determined using the long-term care insurance database. Covariates were demographic characteristics, body mass index, smoking, alcohol consumption, total physical activity, insomnia symptoms, disease history, and either bedtime or sleep duration. Cox proportional hazard models were used to calculate hazard ratios (HRs).
UNASSIGNED: The mean age of participants at baseline was 59.2 years. Over a mean follow-up period of 8.0 years, 319 cases of dementia were observed. A long self-reported sleep duration relative to the reference sleep duration (7 hours) was associated with increased dementia risk, with the \"8 hours\" group (adjusted HR = 1.30, 95% CI:0.99-1.73) and \"≥9 hours\" group (adjusted HR = 1.46, 95% CI:1.00-2.15) having an increased risk (marginally significant) relative to the reference group. Early bedtime was associated with increased dementia risk (adjusted p for trend = 0.0010), with the \"21 : 00 or earlier\" group (adjusted HR = 1.61, 95% CI:1.14-2.28) having an increased risk relative to the reference (\"23 : 00\").
UNASSIGNED: A long self-reported sleep duration and early bedtime are both associated with increased dementia risk in middle-aged and older people.