The mediating role of obesity in the relationship between sleep duration and depressive symptoms: A population-based cross-sectional study.

The moderating role of preterm infants sleep on the relationship between parental sleep and family functioning: An exploratory study.

High noise exposure and temperatures may increase type 2 diabetes (T2D) risk by reducing sleep duration and increasing Body Mass Index (BMI). We studied associations between outdoor noise and nighttime temperature exposure with incident T2D in the Dutch population and assessed mediation by sleep duration and BMI. Six cohorts of the Geoscience and Health Cohort Consortium were linked to environmental exposures based on individuals' postal codes. Noise exposure (road, rail, air traffic) was measured as day-evening-night average decibel levels (dB). High temperature exposure was defined by days with minimum (i.e., nighttime) temperatures above 10°C during summer (June-September). We used logistic regression and sequential causal mediation models. Effect modification by sex, neighborhood socioeconomic status (nSES) and urbanization was tested. Models were adjusted for sex, age, ethnicity, educational level, follow-up time, urbanization level, nSES, and air pollution. Cohort-specific results were meta-analyzed. Among 23,496 participants (mean age range 41.6 (±13.2) to 68.9 (±7.9) years), 724 developed T2D over follow-up periods ranging from 3.0 years [2.0-4.0] to 9.1 years [8.9-9.4]. Noise exposure across cohorts ranged from 53.1 [50.1-57.7] to 57.5 (±4.7) dB, while high nighttime temperature exposure ranged from 88 [87.0-90.0] to 106 [91.0-108.0] days. Meta-analyses showed no associations between noise (OR: 1.00, 95% CI: 0.97-1.02) or temperature exposure and incident T2D (OR: 0.99, 95% CI: 0.97-1.02). No evidence for mediation by sleep duration and BMI was observed. Outdoor noise and elevated nighttime temperatures were not associated with incident T2D, nor mediated by sleep duration and BMI in this study.

Racial and Ethnic Disparities in Obesity and Contributing Behavioral Factors: Diet, Physical Activity, Length of Walk, and Sleep Duration.

Adolescents are among the most frequent smartphone users worldwide. Yet, few studies have examined how smartphone use appears among minority adolescents, including sexual and gender minority (SGM) youth and children of immigrant parents, who often experience unique stressors and heightened mental-health risk. Passive smartphone monitoring provides a promising, low-burden method for continuously and objectively assessing real-world behavior, offering new opportunities to identify dynamic markers of mental health challenges, including suicide risk, in daily life. The present study evaluated the feasibility of a replicable framework for passive smartphone monitoring among adolescents at high risk for suicidal thoughts and behaviors (STB) and explored longitudinal differences in smartphone-derived behavioral features across minority subgroups. Ninety-nine adolescents aged 11-18 with recent STB completed baseline assessments and installed the iFeel app, which collected passive smartphone data for 6 months, including total and social-media screen time and phone-inactivity-based proxy sleep indicators inferred from nighttime phone inactivity. Participants contributed 1500 participant-weeks of data, with an average of 11.9 weeks of valid monitoring, supporting the feasibility and acceptability of this approach. Daily smartphone use time, social-media activity time, and sleep duration were comparable to normative adolescent data. No significant longitudinal differences emerged between SGM and non-SGM adolescents. However, immigrant-origin adolescents displayed shorter but more stable sleep patterns compared to non-immigrant origins, who exhibited longer baseline sleep with steeper declines over time. Findings highlight passive sensing as a feasible, inclusive, and scalable method for examining real-world behavioral processes associated with STB and mental health outcomes among diverse adolescents. This framework offers a scalable approach that future studies can apply to deepen real-time understanding of mental-health challenges and behavioral patterns among diverse adolescents.

Personalized weight loss management through wearable devices and artificial intelligence.

Sleep health of children and adolescents in foster and kinship care: A systematic review.

Objective Sleep Disturbance After Total Hip and Knee Arthroplasty: A Systematic Review of Wearable-Derived Metrics and Targeted Interventions.

Associations of a behavioral and mental health score with all-cause and cause-specific mortality and life expectancy: two nationwide cohort studies from the UK and US.

Poor sleep and emotional wellbeing, which often decline during puberty, are associated with declines in metabolic health and are key determinants of childhood obesity. The aim of the study was to explore bidirectional associations between sleep, emotional wellbeing and obesity from ages 8 to 14 using the Growing Up in Scotland cohort. Secondary analyses were conducted on data from sweeps 7-10 (ages 8-14). Sleep duration was caregiver-reported at age 8 and self-reported at 14. Obesity was assessed using BMI percentiles (BMIp), derived from objective height and weight at ages 8, 10, 12 and 14. Emotional wellbeing was assessed using the Strengths and Difficulties Questionnaire caregiver-report at 10 and 12 years, and self-report at 14 years. Pearson correlations and adjusted regressions examined associations between sleep, BMIp and emotional wellbeing from ages 8 to 14. Analyses included 4157 participants (50.2% male). Shorter sleep at 8 years was associated with higher BMIp at 12 years (β = -0.172, CI (95%) = -0.335, -0.116, p < 0.001) and poorer emotional wellbeing at 10 (β = -0.120, CI (95%) = -0.179, -0.034, p < 0.001) and 12 years (β = -0.101, CI (95%) = -0.164, -0.026, p < 0.001). Poorer emotional wellbeing at 10 (β = -0.116, CI (95%) = -0.232, -0.093, p < 0.001) and 12 years (β = -0.194, CI (95%) = -0.328, -0.174, p < 0.001) predicted shorter sleep at 14 years. Higher BMIp at 8 years was associated with shorter sleep at 14 years (β = -0.182, CI (95%) = -0.359, -0.111, p < 0.001). Poorer emotional wellbeing at 10 years was associated with higher BMIp at 14 years (β = 0.142, CI (95%) = 0.074, 0.629, p = 0.13). Bidirectional associations emerged between short sleep and emotional wellbeing and higher BMIp. Poor emotional wellbeing was associated with subsequent obesity; but not bidirectionally. These interactions should inform the design of health interventions for 8-14-year-olds.

Sleep is essential for human functioning, but little attention has been paid to the interplay between sleep and maladaptive personality traits. We examined genetic and environmental associations between sleep and four maladaptive domains (MDs)-Negative Affectivity, Detachment, Disinhibition, and Psychoticism-within the framework of the DSM-5 Alternative Model of Personality Disorders (AMPD). We estimated phenotypic, genetic, and environmental variance and covariance using a twin study approach. Phenotypically, the four MDs showed small associations with sleep duration, medium associations with sleep efficiency, and large associations with sleep quality. A similar pattern was observed in genetic correlations, with Negative Affectivity and Detachment consistently showing the strongest associations. Multilevel Regression results based on the co-twin control design indicated that genetic factors only partially account for these relations. Whilst previous research has extensively focused on adaptive personality traits predicting sleep, our study highlights the importance of maladaptive traits as meaningful predictors of sleep health.

This repeated cross-sectional study examined trends and behavioral correlates of excessive screen time among Swedish adolescents across 2017, 2020 and 2023. Specifically, this study examined 1) temporal trends of variables used, 2) correlates of pooled screen time, and 3) correlates of specific screen modalities (gaming, social media, and film/TV viewing). Data were collected from n=8,300 upper secondary school students in Jönköping County (n=2,319 in 2017; n=3,056 in 2020; n=2,925 in 2023). Measures used included risk behaviors (e.g., alcohol, smoking), physical activity, psychosocial trust, exposure to violence and victimization, sleep duration, psychosomatic symptoms, absenteeism and living arrangement. General linear models (GLM; UNIANOVA) were conducted, adjusting for relevant covariates. Alcohol use, smoking, shorter sleep duration, higher psychosomatic symptoms, and school absenteeism were associated with higher pooled screen time, whereas physical activity, female gender, and living with both parents were associated with lower pooled screen time. Across modality-specific analyses, shorter sleep duration, lower physical activity, living without both parents, and school absenteeism were consistently associated with higher screen use across gaming, social media, and film/TV viewing, while substance-use and gender associations varied by modality. Sleep, physical activity, family structure, and school absenteeism appear to be robust correlates across screen modalities, supporting the importance of targeting these factors in adolescent health promotion and digital media guidance. These findings highlight the need for parents, researchers, and health professionals to pay closer attention to adolescents' digital media use.

Associations of adverse childhood experiences and sleep in adulthood and older age: A nationwide cohort study.

Does poor sleep affect cognition differently across ages? Insights from a national cohort.

Short and disrupted sleep is related to perceptions of neighborhood in pregnant African American women of low socioeconomic status.

Counting pollen instead of sheep? Investigating the relationship between pollen exposure and sleep.

Association of daytime circadian-aligned activity with glycemic control in type 2 diabetes: Insights from continuous glucose monitoring and wearable data.

Impacts of Alagille syndrome on sleep of patients and their caregivers.

Cognitive performance is significantly affected by sleep, but mild chronic sleep deprivation in daily life remains difficult to measure. Laboratory-enforced sleep restriction may not fully replicate real-life conditions. This study investigates whether Social Jet Lag (SJL), an indicator of misalignment between biological and social time, can used as a proxy for mild chronic sleep deprivation and its impact on cognitive function. Participants leading typical social lives were selected based on their SJL scores, and cognitive performance was assessed using an online experiment incorporating a Psychomotor Vigilance Task (PVT) and a Sustained Attention to Response Task (SART) at different times (post-wake and pre-sleep) and across multiple days (Sunday, Monday, and Friday). Generalised linear modelling (GLM) revealed that SJL was consistently the most explanatory factor for cognitive performance, while test timing also had a significant impact. Cognitive performance impairments due to SJL remained stable across days, suggesting a stable influence of sleep timing irregularity. Additionally, SJL was associated with increased false-positive rates in the SART, indicating reduced response inhibition ability. While SJL proved to be a useful measure compared to average sleep duration and the Sleep Regularity Index (SRI), its effectiveness may be specific to populations following structured work schedules.

A Rhodiola-derived acidic glycopeptide maintains sleep homeostasis by regulating brain lipid metabolism in Drosophila.