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The interplay between genetic and lifestyle factors in the development of bipolar disorder (BD) remains unclear. A cohort study was carried out on 365,517 participants from the UK Biobank. Lifestyle scores, based on smoking, physical activity, diet, alcohol consumption, sedentary behavior, sleep duration, and social contact, were grouped as favorable (scores 6–7), intermediate (scores 4–5), or unfavorable (scores 0–3). The BD polygenic risk score (PRS) was also categorized into high, intermediate, and low-risk groups using PRS tertiles. Cox regression models determined hazard ratios (HRs) and 95 % confidence intervals (CIs) for BD. During the 12.9-year follow-up, 529 individuals developed BD. Comparing those with favorable lifestyles to those with unfavorable participants, the HR of developing BD was 3.28 (95 % CI, 2.76–3.89). Similarly, individuals with a high PRS had a risk of 3.20 (95 % CI, 2.83–3.63) compared to those with a low PRS. Notably, individuals with both a high PRS and an unfavorable lifestyle had a significantly higher risk of BD (HR = 6.31, 95 % CI, 4.14–9.63) compared to those with a low PRS and a favorable lifestyle. Additionally, the interaction between PRS and lifestyle contributed an additional risk, with a relative excess risk of 1.74 (95 % CI, 0.40–3.07) and an attributable proportion due to the interaction of 0.37 (95 % CI, 0.16–0.58). Our findings suggest that genetic liability for BD, measured as PRS, and lifestyle have an additive effect on the risk of developing BD. A favorable lifestyle was associated with a reduced risk of developing BD. • High polygenic risk score (PRS) and unfavorable lifestyles both increase risk of bipolar disorder (BD). • The coexistence of high PRS and unfavorable lifestyle has an additive interaction on the risk of developing BD. • Irrespective of PRS, adopting a favorable lifestyle was consistently linked to a decreased risk of BD. [ABSTRACT FROM AUTHOR]

Summary We explored the effects of daylight saving time clock changes on sleep duration in a large accelerometer dataset. Our sample included UK Biobank participants (n = 11,780; aged 43–78 years) with accelerometer data for one or more days during the 2 weeks surrounding the Spring and Autumn daylight saving time transitions from October 2013 and November 2015. Between‐individual t‐tests compared sleep duration on the Sunday (midnight to midnight) of the clock changes with the Sunday before and the Sunday after. We also compared sleep duration on all other days (Monday–Saturday) before and after the clock changes. In Spring, mean sleep duration was 65 min lower on the Sunday of the clock changes than the Sunday before (95% confidence interval −72 to −58 min), and 61 min lower than the Sunday after (95% confidence interval −69 to −53). In Autumn, the mean sleep duration on the Sunday of the clock changes was 33 min higher than the Sunday before (95% confidence interval 27–39 min), and 38 min higher than the Sunday after (95% confidence interval 32–43 min). There was some evidence of catch‐up sleep after both transitions, with sleep duration a little higher on the Monday–Friday than before, although this was less pronounced in Autumn. Future research should use large datasets with longer periods of accelerometer wear to capture sleep duration before and after the transition in the same individuals, and examine other aspects of sleep such as circadian misalignment, sleep fragmentation or daytime napping. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the independent and joint associations of accelerometer-derived sleep duration and physical activity (PA) in different intensities with the risk of incident heart failure (HF). The study included 89,572 participants (mean age 62.2 ± 7.8 years, 42.8% male) from the UK Biobank. Sleep duration (short: <6 h/day; normal: 6–8 h/day; long: >8 h/day) and PA [total PA, light PA (LPA), moderate-to-vigorous PA (MVPA), vigorous PA (VPA)] were measured using accelerometers over 7 days. MVPA and VPA were categorized according to the World Health Organization's recommended levels, while LPA and total PA were categorized based on the median. HF cases were identified through hospital records or death registries. Over a 7-year follow-up period, 1324 participants (2.1%; incidence rate, 2.1 per 1000 person-years) developed HF. Short, but not long, sleep duration was linked to a 33% increased risk of HF [hazard ratio (HR) 1.33, 95% confidence interval (CI): 1.11–1.59]. This increased risk associated with short sleep could be mitigated by increasing PA, especially to the levels of recommended MVPA or VPA. In joint analyses, compared to participants meeting the recommended MVPA and with normal sleep duration, those not meeting the MVPA recommendation and with short sleep had the highest HF risk (HR 1.78, 95% CI: 1.42–2.25). Accelerometer-derived short, but not long, sleep duration was associated with a higher risk of incident HF. Engaging in sufficient PA, especially recommended MVPA or VPA, can partially mitigate this risk. [Display omitted] • Accelerometer-measured short sleep duration is independently associated with a higher risk of heart failure. • Higher physical activity levels, regardless of intensity, reduce the heart failure risk linked to short sleep duration. • Our study suggests for promoting recommended levels of PA, especially in situations where sleep duration may be compromised. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the relationship between training load and subjective wellness in English Premier League goalkeepers (GKs) and examine potential positional differences in subjective wellness. Methods: A total of 34 players (GK = 7, outfield = 27) completed a daily subjective wellness questionnaire assessing sleep quality, sleep hours, fatigue, mood, soreness, and total wellness over two and a half seasons. Ten-Hertz GPS devices were worn during training to calculate previous-day and 7-day total distance, player load, total dives, total dive load, average time to feet, and high, medium, and low jumps. Results: All previous 7-day training loads were associated with all wellness markers (r =.073 to.278, P <.05). However, associations between previous 7-day dive load and mood, average time to feet, and both sleep quality and quantity, and between low jumps and sleep quality, were not significant. For previous-day metrics, total distance was associated with all wellness markers (r =.097 to.165, P <.05). In addition, player load and high jump were associated with fatigue, soreness, and wellness (r =.096 to.189, P <.05). Total dives and soreness were also related (r =.098, P <.05), and relationships were evident between average time to feet, medium jumps, and all wellness markers excluding sleep quality (r =.114 to.185, P <.05). No positional differences in subjective wellness occurred (P >.05). Conclusion: Some GK GPS variables are associated with subjective wellness, which could inform training-load prescription to maximize recovery and performance. In addition, GKs are no more vulnerable to poorer subjective wellness when compared with outfield players. [ABSTRACT FROM AUTHOR]

Purpose: The association between type 2 diabetes mellitus (T2DM), lifestyle factors, and the risk of osteoporosis (OP) is well-established. However, the impact of a healthy lifestyle on diabetes-related osteoporosis needs further investigation. Our objective was to explore if a combination of healthy lifestyle factors could mitigate the risk of OP in individuals with type 2 diabetes. Methods: This longitudinal analysis included 237,725 middle-aged and older participants. An overall lifestyle score, ranging from 0 to 7, was calculated by assigning a point for each of the seven healthy lifestyle factors, including no current smoking, non-excessive alcohol consumption, regular physical activity, healthy diet, adequate sleep duration, less sedentary behavior, and adequate sunshine exposure. Results: During a median follow-up 12.21 years, 5760 OP cases were documented. Participants with T2DM showed a higher risk of OP than those without diabetes. Compared with participants without diabetes who had a lifestyle score of 6–7, the hazard ratios (HRs) for OP were 1.58 (95% CI 1.23–2.03), 1.62 (95% CI 1.16–2.25), and 2.58 (95% CI 1.64–4.05) for participants with T2DM who had a lifestyle score of 4, 3, and 0–2, respectively. There was a graded association between higher lifestyle scores and lower risks of incident OP among participants without diabetes as well as among those with T2DM. We estimated that the population attributable fraction for not adhering to 6–7 lifestyle behaviors was 15.7%. Conclusions: Participants with T2DM who adhered to a variety of healthy lifestyle factors demonstrated a substantially reduced risk of developing OP. [ABSTRACT FROM AUTHOR]

Healthier lifestyle decreased the risk of mental disorders (MDs) such as depression and anxiety. However, research on the effects of a comprehensive healthy lifestyle on their progression is lacking. 385,704 individuals without baseline MDs from the UK Biobank cohort were included. A composite healthy lifestyle score was computed by assessing alcohol intake, smoking status, television viewing time, physical activity, sleep duration, fruit and vegetable intake, oily fish intake, red meat intake, and processed meat intake. Follow-up utilized hospital and death register records. Multistate model was used to examine the role of healthy lifestyle on the progression of specific MDs, while a piecewise Cox regression model was utilized to assess the influence of healthy lifestyle across various phases of disease progression. Higher lifestyle score reduced risks of transitions from baseline to anxiety and depression, as well as from anxiety and depression to comorbidity, with corresponding hazard ratios (HR) and 95 % confidence intervals (CI) of 0.94 (0.93, 0.95), 0.90 (0.89, 0.91), 0.94 (0.91, 0.98), and 0.95 (0.92, 0.98), respectively. Healthier lifestyle decreased the risk of transitioning from anxiety to comorbidity within 2 years post-diagnosis, with HR 0.93 (0.88, 0.98). Higher lifestyle scores at 2–4 years and 4–6 years post-depression onset were associated with reduced risk of comorbidity, with HR 0.93 (0.87, 0.99) and 0.92 (0.86, 0.99), respectively. The generalizability to other ethnic groups is limited. This study observed a protective role of holistic healthy lifestyle in the trajectory of MDs and contributed to identifying critical progression windows. • Evidence is scarce on association between a holistic healthy lifestyle and depression and anxiety comorbidity. • Trajectory and time courses of mental disorders need consideration. • Healthy lifestyle adherence inversely linked to mental disorder progression and prognosis. • Each lifestyle score increase reduces depression to comorbid anxiety by 6% and anxiety to comorbid depression by 5%. • Important progression windows were detected in the protective role of a holistic healthy lifestyle. [ABSTRACT FROM AUTHOR]

Summary: Experimental studies suggest that short or disrupted sleep impairs memory consolidation, mood, and perception of emotional stimuli. However, studies have chiefly relied on laboratory‐based study designs and small sample sizes. The aim of this fully online and pre‐registered study was to investigate the association between sleep and overnight memory consolidation, emotion perception, and affect in a large, self‐selected UK sample. A total of 1646 participants (473 completed) took part in an online study, where they completed a declarative (word‐pairs) memory task, emotion perception task (valence ratings of images), and rated their affect within 2 h of bed‐time. The following morning, participants reported on their state affect, sleep for the previous night, completed a cued recall task for the previously presented word‐pairs, rated the valence of previously viewed images, and completed a surprise recognition task. Demographic data and habitual sleep quality and duration (sleep traits) were also recorded. Habitual sleep traits were associated with immediate recall for the word‐pairs task, while self‐reported sleep parameters for the specific night were not associated with overnight memory consolidation. Neither habitual sleep traits, nor nightly sleep parameters were associated with unpleasantness ratings to negative stimuli or overnight habituation. Habitual poor sleep was associated with less positive and more negative affect, and morning affect was predicted by the specific night's sleep. This study suggests that overnight emotional processing and declarative memory may not be associated with self‐reported sleep across individuals. More work is needed to understand how findings from laboratory‐based studies extrapolate to real‐world samples and contexts. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the genetic correlation and causal links between sleep traits (including sleep duration, chronotype, and insomnia) and myopia. Methods: Summary data on three sleep traits (sleep duration, chronotype and insomnia) and myopia from FinnGen (n = 214,211) and UK Biobank (n = 460,536) were analyzed using linkage disequilibrium score regression (LD Score), univariable and multivariable mendelian randomization (MR) experiments and Causal Analysis Using Summary Effect (CAUSE) estimation. Results: LD Score regression detected candidate genetic correlation between sleep traits and myopia, such as sleep duration, chronotype (Genetic Correlation Z-score >10.00, h2_observed_p < 0.005, Lambda GC > 1.05, p > 0.05). Univariable MR analyses indicated that increased sleep duration has a promotional effect on the occurrence of myopia (p = 0.046 < 0.05, P_FDR = 0.138 < 0.2, OR = 2.872, 95% CI: 1.018-8.101). However, after accounting for potential confounding factors, multivariable MR and CAUSE analysis did not provide evidence for a causal effect of the three sleep traits on myopia. Conclusion: There may be a potential genetic correlation between sleep duration, chronotype and myopia. However, neither of sleep duration, chronotype or insomnia had causal effect on myopia. [ABSTRACT FROM AUTHOR]

Aims: The association of sleep traits (insomnia, sleep duration, chronotype, daytime sleepiness, and snoring) with benign prostatic hyperplasia (BPH) is unclear. This research aimed to examine the effects of sleep traits on BPH risk. Methods: A total of 170 241 men aged 38 to 73 years from UK Biobank were included. An overall healthy sleep score was created based on five sleep traits. A Cox regression model was utilized to compute adjusted hazard ratios (HRs) and population attributable fractions (PAFs) with 95% confidence intervals (CIs) for BPH risk in relation to sleep traits. Results: During a median of 12.0 years follow‐up, 13 026 incident BPH cases occurred. We observed that sleep duration (7–8 h/d; HR 0.95; 95% CI 0.92–0.99), no frequent insomnia (HR 0.71; 95% CI 0.69–0.74), and no frequent daytime sleepiness (HR 0.86; 95% CI 0.79–0.93) were significantly related to reduced BPH risk. Each one‐point increment of the healthy sleep score was related to a decreased BPH risk, with an adjusted HR of 0.90 (95% CI 0.89–0.92). The multivariable‐adjusted HR in men adopting five versus zero to one low‐risk sleep traits was 0.68 (95% CI 0.61–0.75) for BPH risk. Estimates of the PAF indicated that 9.1% (95% CI 5.8–12.5%) of BPH cases would be prevented if all individuals had adopted all five low‐risk sleep traits, assuming causality. Conclusions: Our study indicates an association between a healthy sleep pattern and a lower risk of BPH, emphasizing the importance of adhering to such patterns for potentially reducing BPH risk. Geriatr Gerontol Int 2024; 24: 675–682. [ABSTRACT FROM AUTHOR]

Previous research on sleep and aging largely has failed to illustrate the optimal dose–response curve of this relationship. We aimed to analyze the associations between sleep duration and measures of predicted age. In total, 241,713 participants from the UK Biobank were included. Habitual sleep duration was collected from the baseline questionnaire. Four indicators, homeostatic dysregulation (HD), phenoAge (PA), Klemera–Doubal method (KDM), and allostatic load (AL), were chosen to assess predicted age. Multivariate linear regression models were utilized. The association of sleep duration and predicted age followed a U‐shape (All p for nonlinear <0.05). Compared with individuals who sleep for 7 h/day, the multivariable‐adjusted beta of ≤5 and ≥9 h/day were 0.05 (95% CI 0.03, 0.07) and 0.03 (95% CI 0.02, 0.05) for HD, 0.08 (95% CI 0.01, 0.14) and 0.36 (95% CI 0.31, 0.41) for PA, and 0.21 (95% CI 0.12, 0.30) and 0.30 (95% CI 0.23, 0.37) for KDM. Significant independent and joint effects of sleep and cystatin C (CysC) and gamma glutamyltransferase (GGT) on predicted age metrics were future found. Similar results were observed when conducting stratification analyses. Short and long sleep duration were associated with accelerated predicted age metrics mediated by CysC and GGT. [ABSTRACT FROM AUTHOR]

Aim: To investigate the association between cardiovascular health metrics defined by Life's Essential 8 (LE8) scores and vascular complications among individuals with type 2 diabetes (T2D). Materials and Methods: This prospective study included 11 033 participants with T2D, all devoid of macrovascular diseases (including cardiovascular and peripheral artery disease) and microvascular complications (e.g. diabetic retinopathy, neuropathy and nephropathy) at baseline from the UK Biobank. The LE8 score comprised eight metrics: smoking, body mass index, physical activity, non‐high‐density lipoprotein cholesterol, blood pressure, glycated haemoglobin, diet and sleep duration. Cox proportional hazards models were established to assess the associations of LE8 scores with incident macrovascular and microvascular complications. Results: During a median follow‐up of 12.1 years, we identified 1975 cases of incident macrovascular diseases and 1797 cases of incident microvascular complications. After adjusting for potential confounders, each 10‐point increase in the LE8 score was associated with an 18% lower risk of macrovascular diseases and a 15% lower risk of microvascular complications. Comparing individuals in the highest and lowest quartiles of LE8 scores revealed hazard ratios of 0.55 (95% confidence interval 0.47‐0.62) for incident macrovascular diseases, and 0.61 (95% confidence interval 0.53‐0.70) for incident microvascular complications. This association remained robust across a series of sensitivity analyses and nearly all subgroups. Conclusion: Higher LE8 scores were associated with a lower risk of incident macrovascular and microvascular complications among individuals with T2D. These findings underscore the significance of adopting fundamental strategies to maintain optimal cardiovascular health and curtail the risk of developing diabetic vascular complications. [ABSTRACT FROM AUTHOR]

The recently discovered glymphatic system may support the removal of neurotoxic proteins, mainly during sleep, that are associated with neurodegenerative diseases such as Alzheimer's and Parkinson's Disease. Diffusion tensor image analysis along the perivascular space (DTI-ALPS) has been suggested as a method to index the health of glymphatic system (with higher values indicating a more intact glymphatic system). Indeed, in small-scale studies the DTI-ALPS index has been shown to correlate with age, cognitive health, and sleep, and is higher in females than males. To determine whether these relationships are stable we replicated previous findings associating the DTI-ALPS index with demographic, sleep-related, and cognitive markers in a large sample of participants from the UK Biobank. We calculated the DTI-ALPS index in UK Biobank participants (n = 17723). Using Bayesian and Frequentist analysis approaches, we replicate previously reported relationships between the DTI-ALPS index. We found the predicted associations between the DTI-ALPS index and age, longest uninterrupted sleep window (LUSWT) on a typical night, cognitive performance, and sex. However, these effects were substantially smaller than those found in previous studies. Parameter estimates from this study may be used as priors in subsequent studies using a Bayesian approach. These results suggest that the DTI-ALPS index is consistently, and therefore predictably, associated with demographics, LUWST, and cognition. We propose that the metric, calculated for the first time in a large-scale, population-based cohort, is a stable measure, but one for which stronger links to glymphatic system function are needed before it can be used to understand the relationships between glymphatic system function and health outcomes reported in the UK Biobank. • We calculated an index of diffusion along the perivascular space (DTI-ALPS index) in 44073 participants from the UK Biobank. • We replicated analyses from previous studies showing a relationship between the DTI-ALPS index, sex, age, sleep, & cognition. • Although these replications were broadly successful, the effect sizes were substantially smaller than previously reported. [ABSTRACT FROM AUTHOR]

This study aimed to examine the association between past/current sleep duration and macro-/micro-structural brain outcomes and explore whether hypertension or social activity plays a role in such association. Within the UK Biobank, 40 436 dementia-free participants (age 40–70 years) underwent a baseline assessment followed by a brain magnetic resonance imaging (MRI) scan 9 years later. Past (baseline) and current (MRI scans) sleep duration (hours/day) were recorded and classified as short (≤5), intermediate (6–8), and long (≥9). Brain structural volumes and diffusion markers were assessed by MRI scans. Compared with past intermediate sleep, past short sleep was related to smaller cortex volumes (standardized β [95 % CI]: −0.04 [-0.07, −0.02]) and lower regional fractional anisotropy (FA) (−0.08 [-0.13, −0.03]), while past long sleep was related to smaller regional subcortical volumes (standardized β: −0.04 to −0.07 for thalamus, accumbens, and hippocampus). Compared to current intermediate sleep, current short sleep was associated with smaller cortex volumes (−0.03 [-0.05, −0.01]), greater white matter hyperintensities (WMH) volumes (0.04 [0.01, 0.08]), and lower regional FA (−0.07 [-0.11, −0.02]). However, current long sleep was related to smaller total brain (−0.03 [-0.05, −0.02]), grey matter (−0.05 [-0.07, −0.03]), cortex (−0.05 [-0.07, −0.03]), regional subcortical volumes [standardized β: −0.05 to −0.09 for putamen, thalamus, hippocampus, and accumbens]), greater WMH volumes (0.06 [0.03, 0.09]), as well as lower regional FA (−0.05 [-0.09, −0.02]). The association between current long sleep duration and poor brain health was stronger among people with hypertension or low frequency of social activity (all P interaction <0.05). Both past and current short/long sleep are associated with smaller brain volume and poorer white matter health in the brain, especially in individuals with hypertension and low frequency of social activity. Our findings highlight the need to maintain 6–8 h' sleep duration for healthy brain aging. [Display omitted] • Long or short sleep is associated with poorer brain health. • People with hypertension or lack of social activity particularly need healthy sleep to delay brain aging. [ABSTRACT FROM AUTHOR]

Introduction: Sleep is associated with psychiatric disorders. However, their causality remains unknown. Methods: The study explored the causal relationship between seven sleep parameters (sleep duration, insomnia, sleep apnea, chronotype, daytime dozing, napping during the day, and snoring) and three psychiatric disorders including major depressive disorder (MDD), schizophrenia, and attention-deficit/ hyperactivity disorder (ADHD) using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS) summary data for sleep parameters were obtained from the United Kingdom biobank, FinnGen biobank, and EBI databases. MR-Egger, weighted median, inverse-variance weighted (IVW), simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW(fixed effects) were used to perform the MR analysis. The heterogeneity was detected by Cochran’s Q statistic. The horizontal pleiotropy was detected by MR Egger. The sensitivity was investigated by the leave-one-out analysis. Results: Insomnia (OR = 2.02, 95%CI = 1.34–3.03, p = 0.001, False-discovery rate (FDR) corrected p-value = 0.011) and napping during the day (OR = 1.81, 95%CI = 1.34–2.44, FDR corrected p-value<0.001) were associated with an increased risk of MDD. Longer sleep duration (OR = 2.20, 95%CI = 1.24–3.90, FDR corrected p-value = 0.049) had an association with the increased risk of schizophrenia, while daytime dozing (OR = 4.44, 95%CI = 1.20–16.41, corrected p-value = 0.088)and napping during the day (OR = 2.11, 95%CI = 1.11–4.02, FDR corrected p-value = 0.088) had a suggestive association with an increased risk of schizophrenia. Longer sleep duration had a suggestive association with a decreased risk of ADHD (OR = 0.66, 95%CI = 0.42–0.93, FDR corrected p-value = 0.088). Conclusion: This study provides further evidence for a complex relationship between sleep and psychiatric disorders. Our findings highlight the potential benefits of addressing sleep problems in the prevention of psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors. Methods: This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes. Results: Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men. Conclusions: A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation. [ABSTRACT FROM AUTHOR]

Background: Disturbances in habitual sleep have been associated with multiple age‐associated diseases. However, the biological mechanisms underpinning these associations remain largely unclear. We assessed the possible involvement of the circulating immune system by determining the associations between sleep traits and white blood cell counts using multivariable‐adjusted linear regression and Mendelian randomization. Methods: Cross‐sectional multivariable‐adjusted linear regression analyses were done using participants within the normal range of total white blood cell counts (>4.5 × 109 and <11.0 × 109/μL) from UK Biobank. For the sleep traits, we examined (short and long) sleep duration, chronotype, insomnia symptoms and daytime dozing. Two‐sample Mendelian randomization analyses were done using instruments for sleep traits derived from European‐ancestry participants from UK Biobank (over 410,000 participants) and using SNP‐outcome data derived from European‐ancestry participants from the Blood Cell Consortium (N = 563,946) to which no data from UK Biobank contributed. Results: Using data from 357,656 participants (mean [standard deviation] age: 56.5 [8.1] years, and 44.4% men), we did not find evidence that disturbances in any of the studied sleep traits were associated with differences in blood cell counts (total, lymphocytes, neutrophiles, eosinophiles and basophiles). Also, we did not find associations between disturbances in any of the studied sleep traits and white blood cell counts using Mendelian Randomization. Conclusion: Based on the results from two different methodologies, disturbances in habitual sleep are unlikely to cause changes in blood cell counts and thereby differences in blood cell counts are unlikely to be underlying the observed sleep‐disease associations. [ABSTRACT FROM AUTHOR]

Background: This study was to explore the causal associations of sleep traits including sleep duration, snoring, chronotype, sleep disorders, getting up in the morning, sleeplessness/insomnia and nap during day with the risk of thyroid cancer based on Mendelian randomization (MR) analysis. Method: Summary single nucleotide polymorphism (SNP)-phenotype association data were obtained from published genome-wide association studies (GWASs) using the FinnGen and UK Biobank databases. A series of screening processes were performed to select qualified SNPs strongly related to exposure. We applied the inverse variance weighted (IVW), the Mendelian Randomization robust adjusted profile score (MR-RAPS), the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO), and the Weighted Median to estimate the causal links between sleep traits and the risk of thyroid cancer. Odds ratio (OR) and 95% confidence interval (CI) were calculated. Results: The IVW results showed that getting up in the morning (OR = 0.055, 95%CI: 0.004–0.741) and napping during day (OR = 0.031, 95%CI: 0.002–0.462) were associated with decreased risk of thyroid cancer in the Italian population. A 1.30-h decrease of sleep duration was associated with 7.307-fold of thyroid cancer risk in the Finnish population (OR = 7.307, 95%CI: 1.642–32.519). Cronotype could decrease the risk of thyroid cancer in the Finnish population (OR = 0.282, 95%CI: 0.085–0.939). Sleep disorders increased the risk of thyroid cancer in the Finnish population (OR = 2.298, 95%CI: 1.194–4.422). The combined results revealed that sleep duration was correlated with increased risk of thyroid cancer (OR = 5.600, 95%CI: 1.458–21.486). Conclusion: Decreased sleep duration was associated with increased risk of thyroid cancer, which indicated the importance of adequate sleep for the prevention of thyroid cancer. [ABSTRACT FROM AUTHOR]

Obesity, along with its associated health issues, is closely tied to lifestyle habits. While certain elements affecting childhood health, such as genetics and ethnicity, are beyond individuals' control, there exists modifiable lifestyle behaviours that can facilitate healthier living. This study employed multiple regression analysis to investigate the relationship between specific modifiable lifestyle behaviours and self-reported health. The independent variables considered included days of moderate to vigorous physical activity (MVPA), fruit and vegetable consumption, breakfast frequency, school night sleep duration, and non-school night sleep duration. These variables were chosen for their practical modifiability within participants' daily lives. The analysis revealed a highly significant overall model (F(13,11363) = 191.117, p <.001), explaining 17.9% of the variance in self-reported health. Notably, higher MVPA levels were associated with improved self-reported health (B = 0.136 to 0.730, p <.001). Additionally, regular breakfast consumption and increased fruit and vegetable intake exhibited positive associations with self-reported health (B = 0.113 to 0.377, p <.001), while girls reported lower self-reported health (B = -0.079, p <.001). School night sleep duration was positively linked to self-reported health (B = 0.071, p <.001). Furthermore, a dose-response relationship between MVPA, dietary habits, and health was identified. These findings hold substantial potential for public health campaigns to promote healthy behaviours and prevent chronic diseases in young individuals. It is imperative to emphasise that all the variables considered in this study are readily modifiable aspects of individuals' lives, offering a promising avenue for personal health and well-being enhancement. [ABSTRACT FROM AUTHOR]

Low testosterone levels in men have been linked to decreased physical and mental function, as well as a reduced quality of life. Previous prospective observational studies have suggested an association between testosterone and sleep traits, but the causality of this relationship remains unclear. We aimed to explore the potential causal link between genetically determined sleep traits and testosterone levels in men using Mendelian randomization (MR) analysis from the UK Biobank dataset. Our exposures were genetic variants associated with sleep traits (chronotype and sleep duration), whereas our outcomes were traits of sex steroid hormones (total testosterone, TT; bioavailable testosterone, BAT; and sex hormone-binding globulin, SHBG). We employed inverse variance weighted (IVW) and weighted median (WM) methods to assess the causal associations. The IVW method offers a robust estimate of causality, whereas the WM method provides reliable results even when some genetic variants are invalid instruments. Our main analysis involving sex steroid hormones and chronotype identified 155 chronotype-related variants. The primary findings from the analysis, which used chronotype as the exposure and sex steroid hormones as the outcomes, showed that a genetically predicted chronotype score was significantly associated with an increased levels of TT (association coefficient β, 0.08; 95% confidence interval [CI], 0.02-0.14; P = 0.008) and BAT (β, 0.08; 95% CI, 0.02-0.14; P = 0.007), whereas there was no significant association with SHBG (b, 0.01; 95% CI, -0.02-0.03; P = 0.64). Meanwhile, MR analysis of sex steroid hormones and sleep duration was performed, and 69 variants associated with sleep duration were extracted. There were no significant association between sleep duration and sex steroid hormones (TT, P = 0.91; BAT, P = 0.82; and SHBG, P = 0.95). Our data support a causal association between chronotype and circulating testosterone levels in men. These findings underscore a potential causal relationship between chronotype and testosterone levels in men, suggesting that lifestyle adjustments are crucial for men's health. Recognizing factors that influence testosterone is essential. One limitation of this study is the use of one-sample MR, which can introduce potential bias due to non-independence of genetic associations for exposure and outcome. In conclusion, our findings indicate that a morning preference is correlated with circulating testosterone levels, emphasizing the potential impact of lifestyle habits on testosterone levels in men. [ABSTRACT FROM AUTHOR]

Little is known about the role that combined sleep behaviors play in the association with chronic liver disease (CLD) risk. We included 408,560 participants initially free of CLD from the UK Biobank. A healthy sleep pattern was defined by early chronotype, sleep duration of 7–8 h/day, no insomnia, no snoring, and no excessive daytime sleepiness. Cox regression models were used to examine the association of healthy sleep pattern with incident CLD and their interaction with PNPLA3 genetic risk. During a median 12.5 years of follow-up, we documented 10,915 incident all-cause CLD cases, including 388 viral hepatitis, 4782 non-alcoholic fatty liver disease (NAFLD), 1356 cirrhosis, 973 alcoholic liver disease, and 725 liver cancer cases. Compared to participants with a healthy sleep score of 0–1, the hazard ratio (HR) (95 % confidence interval [CI]) for those with a sleep score of 5 was 0.54 (0.49, 0.60) for CLD, 0.52 (0.30, 0.90) for viral hepatitis, 0.47 (0.41, 0.55) for NAFLD, 0.57 (0.43, 0.75) for cirrhosis, 0.32 (0.23, 0.44) for alcoholic liver disease, and 0.53 (0.37, 0.77) for liver cancer. Healthy sleep pattern and PNPLA3 genetic risk exerted significant additive effects on CLD risk (relative excess risk due to the interaction: 0.05; attributable proportion due to the interaction: 13 %). Measurement error was unavoidable for self-reported data on sleep behaviors. Our analyses provide evidence that healthy sleep pattern was inversely associated with the development of CLD, and participants with higher genetic risk were more likely to develop CLD when exposed to the unhealthy sleep pattern. • Adherence to a healthy sleep pattern was associated with a reduced risk of chronic liver diseases. • Healthy sleep pattern and genetic predisposition may synergistically influence the risks of chronic liver diseases. • Our findings underscore the importance of extensive intervention targeting sleep behaviors should be undertaken to reduce the risk of chronic liver diseases. [ABSTRACT FROM AUTHOR]

The relationships between sleep duration and aging-associated diseases are intricate. Leukocyte telomere length (LTL) is a biomarker of aging, while the association of sleep duration and LTL is unclear. The 310,091 study participants from UK Biobank were enrolled in this cross-sectional study. Restricted cubic splines (RCS) analysis was firstly performed to assess the nonlinear relationship between sleep duration and LTL. Sleep duration was then categorized into three groups: <7 h (short sleep duration), 7–8 h (reference group), and >8 h (long sleep duration) and multiple linear regression was applied to analyze the association of short sleep and long sleep duration with LTL. We further performed subgroup analyses stratified by sex, age, chronotype and snoring. RCS showed an inverted J-shaped relationship between sleep duration and LTL. Compared with the reference group, the inverse association of long sleep duration and LTL was statistically significant in fully-adjusted model (P = 0.001). Subgroup analyses showed that this association was more apparent in people over 50 years (51–60 y: P = 0.002; >60 y: P = 0.005), in men (P = 0.022), and in people preferred evening chronotype (P = 0.001). Compared with participants sleeping 7–8 h, those sleep longer than 8 h had shorter LTL in middle-aged and young-old adults. The negative association between long sleep duration and LTL was more apparent in older people, in men, and in people preferred evening chronotype. • The research was based on the large sample size and in-depth health information of UK Biobank. • Compared with participants sleeping 7–8 h, those sleep longer than 8 h have shorter LTL in middle-aged and young-old adults. • The association between sleep duration and LTL is modified by age, sex and chronotype preference. [ABSTRACT FROM AUTHOR]

Objective: Prediabetes and lifestyle factors have been associated with the risks of multiple adverse outcomes, but the effect of a healthy lifestyle on prediabetes‐related complications remains unknown. We aimed to investigate whether the risks of multiple adverse outcomes including incident type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), and chronic kidney disease (CKD) among individuals with prediabetes can be offset by a broad combination of healthy lifestyle factors. Methods: This prospective study used data from the UK Biobank cohort. An overall lifestyle score ranging from 0 to 6 was created with 1 point for each of the 6 healthy lifestyle factors: no current smoking, moderate alcohol consumption, regular physical activity, healthy diet, no overweight or obese, and adequate sleep duration. T2DM, CVD, and CKD were ascertained during a median follow‐up of 14 years. Cox proportional hazard regression models were used to estimate the associations. Sensitivity analyses were performed to test the robustness of the results. Results: We included 202,993 participants without T2DM, CVD, and CKD at baseline (mean age 55.5 years [SD 8.1]; 54.7% were women). Among these participants, 6,745, 16,961, and 6,260 participants eventually developed T2DM, CVD, and CKD, respectively. Compared with the participants with normoglycaemia, those with prediabetes showed a higher risk of these adverse outcomes. In addition, those prediabetic participants with a lifestyle score of 0‐1 had a significantly higher risk of T2DM (hazard ratio [HR] 16.73, 95% CI 14.24, 19.65), CVD (HR 1.96, 95% CI 1.74, 2.21), and CKD (HR 1.92, 95% CI 1.58, 2.34) compared with those with no prediabetes and a score of 5–6. Moreover, among the participants with prediabetes, the HRs for T2DM, CVD, and CKD comparing a lifestyle score of 5–6 versus 0‐1 decreased to 0.43 (95% CI 0.36, 0.51), 0.52 (95% CI 0.44, 0.62), and 0.60 (95% CI 0.46, 0.79), respectively. Conclusions: Combined healthy lifestyle factors were associated with a significantly lower risk of multiple adverse outcomes, including T2DM, CVD, and CKD. This indicates that prioritising multifactorial approaches to behavioural lifestyle modification is crucial for preventing and postponing the development of complications related to prediabetes. [ABSTRACT FROM AUTHOR]

This study aimed to establish if a significant relationship exists between sleep and aggression in a large representative adolescent cohort and explores the impact of potential confounders. This cross-sectional secondary data analysis included 10,866 males and females aged 13–15 years, from the UK-based 2015 Millenium Cohort Study (sixth sweep). Independent variables included self-report measures of sleep duration and quality. The parent reported 'Strengths and Difficulties Questionnaire' conduct score measured aggression. Binary logistic regression examined independent associations between each sleep variable and aggression. Multiple regression models then adjusted for potential confounders: age, sex, socioeconomic status, arousal, and affect. Under 8 hours of sleep on average was significantly associated with aggression when age, sex and income were controlled (p =.008). This became insignificant following adjustment for both affect and arousal. Sleep quality remained significantly associated with aggression when all confounders were controlled: 'sleep onset latency >30 minutes' and 'wakening at least a good bit of the time' increased the odds of aggression by around 27.9% (p <.001) and 43.5% respectively (p <.001). A significant association exists between poor subjective sleep quality and heightened aggression in this cohort, when all our confounders are controlled, identifying sleep quality as a potential target in treating adolescent aggression. [ABSTRACT FROM AUTHOR]

Although the association between sleep behavior and morbidity and mortality risk has been reported before, there is still uncertainty whether the observed associations are causal or confounding. Therefore, we investigated the causal relationships between sleep-behavioral traits and terminated healthspan risk using Mendelian randomization (MR). We conducted a one-sample MR analysis to evaluate causality between six sleep-behavioral traits (sleep duration, chronotype/morningness, napping, sleeplessness/insomnia, and getting up from bed) and risk of healthspan termination among 388, 909 UK Biobank (UKB) participants. Instrumental variables for sleep behaviors (N = 590) were obtained from recent genome-wide association studies (GWAS). We defined healthspan based on eight predominant health-terminating events associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death). We further constructed a sleep score and a weighted genetic risk score to increase the predictive ability of the sleep-behavioral traits. Cox regression models and Inverse Probability Treatment Weighting (IPTW) were implemented, followed by MR to assess causation. We used inverse-variance-weighted MR to estimate causal effects, and weighted-median and MR-egger for sensitivity analysis to test the pleiotropic effects. In IPTW, we observed a decreased risk of terminated healthspan for healthy sleep behaviors such as 'sleep duration 7-8h/d' (Hazard ratio, HR = 0.93; 95 % confidence interval, CI: 0.92–0.96; P < 0.001); 'morningness' (HR = 0.95; 95%CI: 0.93–0.98; P < 0.01); 'napping' (HR = 0.93; 95%CI: 0.91–0.94; P < 0.001); 'easy getting up from bed' (HR = 0.91; 95%CI: 0.88–0.93; P < 0.001); and, 'never/rarely experience sleeplessness/insomnia' (HR = 0.94; 95%CI: 0.92–0.96; P < 0.001). MR results further indicated causal associations between healthy sleep duration (OR = 0.98; 95%CI: 0.97–1.00; P = 0.036) and insomnia (OR = 1.02; 95%CI: 1.01–1.03; P < 0.001) with terminated healthspan. MR-egger did not suggest any potential pleiotropy. This study supports abnormal sleep duration and insomnia as potential causal risk factors for terminated healthspan. Thus, healthy sleep behavior is valuable for the extension of healthspan, and well-designed and tailored sleep health interventions are warranted. [ABSTRACT FROM AUTHOR]

Background and aims: Few studies have examined the relationship between daytime napping and risk of kidney diseases. We aimed to investigate the association of daytime napping with the incidence of chronic kidney disease (CKD) and end-stage kidney disease (ESKD). We also examined whether sleep duration modified the association of nap with CKD or ESKD. Methods: We recruited 460,571 European middle- to older-aged adults without prior CKD or ESKD between March 13, 2006, and October 1, 2010, in the UK Biobank. Sleep behavior data were obtained through questionnaires administered during recruitment. The analysis of the relationship between napping and the occurrence of CKD and ESKD utilized Cox proportional hazards regression models. The modification role of sleep duration on the effect of nap on CKD and ESKD was also examined. Results: After a mean follow-up of 11.1 (standard deviation 2.2) years, we observed 28,330 incident CKD cases and 927 ESKD cases. The daytime napping was associated with incident CKD (P for trend =.004). After fully adjusted, when compared with participants who did not take nap, those in sometimes and usually nap groups had higher risk of CKD. Nevertheless, the available evidence did not support a link between daytime napping and ESKD (P for trend =.06). Simultaneously, there was insufficient evidence suggesting that sleeping duration modified the association of daytime napping with incident CKD or ESKD. Conclusion: Daytime napping was associated with an increased risk of CKD. However, the absence of conclusive evidence did not indicate a connection between daytime napping and ESKD. [ABSTRACT FROM AUTHOR]

Background Studies of sleep and prostate cancer are almost entirely based on self-report, with limited research using actigraphy. Our goal was to evaluate actigraphy-measured sleep and prostate cancer and to expand on findings from prior studies of self-reported sleep. Methods We prospectively examined 34 260 men without a history of prostate cancer in the UK Biobank. Sleep characteristics were measured over 7 days using actigraphy. We calculated sleep duration, onset, midpoint, wake-up time, social jetlag (difference in weekend-weekday sleep midpoints), sleep efficiency (percentage of time spent asleep between onset and wake-up time), and wakefulness after sleep onset. Cox proportional hazards models were used to estimate covariate-adjusted hazards ratios (HRs) and 95% confidence intervals (CIs). Results Over 7.6 years, 1152 men were diagnosed with prostate cancer. Sleep duration was not associated with prostate cancer risk. Sleep midpoint earlier than 4:00 am was not associated with prostate cancer risk, though sleep midpoint of 5:00 am or later was suggestively associated with lower prostate cancer risk but had limited precision (earlier than 4:00 am vs 4:00-4:59 am HR = 1.00, 95% CI = 0.87 to 1.16; 5:00 am or later vs 4:00-4:59 am HR = 0.79, 95% CI = 0.57 to 1.10). Social jetlag was not associated with greater prostate cancer risk (1 to <2 hours vs <1 hour HR = 1.06, 95% CI = 0.89 to 1.25; ≥2 hours vs <1 hour HR = 0.90, 95% CI = 0.65 to 1.26). Compared with men who averaged less than 30 minutes of wakefulness after sleep onset per day, men with 60 minutes or more had a higher risk of prostate cancer (HR = 1.20, 95% CI = 1.00 to 1.43). Conclusions Of the sleep characteristics studied, higher wakefulness after sleep onset—a measure of poor sleep quality—was associated with greater prostate cancer risk. Replication of our findings between wakefulness after sleep onset and prostate cancer are warranted. [ABSTRACT FROM AUTHOR]

This study presents the sleep characteristics of British student‐athletes and examines the relationships between sport scheduling and time demands on sleep outcomes. Student‐athletes (n = 157, 51% male) completed the Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), and the Sleep Hygiene Index (SHI). Self‐reported sleep characteristics on weekdays and weekends, weekly frequencies of early morning and late evening sport sessions, and academic‐related and sport‐related time demands were also collected. Questionnaires revealed a high prevalence of undesired sleep characteristics including poor sleep quality (global PSQI >5 in 49.0%) and low sleep durations on weekdays (25% reporting <7 h). Paired t‐tests revealed significant differences in bedtime, waketime, sleep duration, and sleep onset latency between weekdays and weekends (all p < 0.01). Hierarchical regression analyses indicated that early morning sport frequency was a significant predictor of PSQI (β = 0.30) and SHI (β = 0.24) global scores, weekday waketimes (β = −0.17), and weekday sleep durations (β = −0.25; all p < 0.05) in models adjusted for participant characteristics. Late evening sport frequency, and academic‐related and sport‐related time demands, were not significant predictors of any sleep outcome. Adjusting sport scheduling to avoid early start times could provide a means to improve sleep outcomes and may improve sporting performance and academic attainment. [ABSTRACT FROM AUTHOR]

OBJECTIVE: To prospectively evaluate the association between modifiable lifestyle factors and peripheral artery disease (PAD) among individuals with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We included 14,543 individuals with T2D from the UK Biobank. We defined a weighted healthy lifestyle score using nonsmoking, regular physical activity, high-quality diet, moderate alcohol consumption, optimal waist-to-hip ratio, and adequate sleep duration, and categorized into unfavorable, intermediate, and favorable lifestyles. We created a genetic risk score (GRS) using 19 single nucleotide polymorphisms previously found to be associated with PAD. We modeled the association between lifestyle score and PAD, overall and stratified by PAD genetic susceptibility. RESULTS: After a median 13.5 years of follow-up, 628 incident cases of PAD were documented. A linear inverse association between the weighted lifestyle score and PAD was observed, with a hazard ratio (HR) (95% CI) of 0.27 (0.19, 0.38) for favorable compared with unfavorable lifestyle (Ptrend < 0.0001). An estimated 58.3% (45.0%, 69.1%) of PAD in this population could be potentially avoidable if all participants attained a favorable lifestyle. Moreover, the PAD GRS was associated with increased PAD risk (HR [95% CI] per SD increment: 1.13 [1.03, 1.23]). A favorable lifestyle was able to partially mitigate the excess risk of PAD associated with higher GRS, albeit as a nonsignificant interaction. Several biomarkers in the lipid metabolism, hepatic/renal function, and systemic inflammation pathways collectively explained 13.3% (8.5%, 20.1%) of the association between weighted lifestyle score and PAD. CONCLUSIONS: A favorable lifestyle was associated with lower risk of PAD among individuals with T2D, independent of genetic predisposition to PAD. [ABSTRACT FROM AUTHOR]

Background: Diabetic individuals often encounter various sleep-related challenges. Although the association between sleep duration and atrial fibrillation (AF) have been explored, the association of other sleep traits with the incidence of AF remains unclear. A comprehensive understanding of these traits is essential for a more accurate assessment of sleep conditions in patients with diabetes and the development of novel AF prevention strategies. Methods: This study involved 23,785 patients with diabetes without any pre-existing cardiovascular disease, drawn from the UK Biobank. Sleep behaviour traits examined encompassed sleep duration, chronotype, insomnia, snoring and daytime sleepiness. Sleep duration was categorised into three groups: low (≤ 5 h), proper (6–8 h) and long (≥ 9 h). We assessed associations using multivariate Cox proportional risk regression models. Furthermore, four poor sleep behaviours were constructed to evaluate their impact on the risk of new-onset AF. Results: Over a mean follow-up period of 166 months, 2221 (9.3%) new cases of AF were identified. Short (hazard ratio (HR), 1.28; 95% confidence interval (CI) 1.10–1.50) and long sleep durations (HR 1.16; 95% CI 1.03–1.32) consistently exhibited an elevated risk of AF compared to optimal sleep duration. Early chronotype, infrequent insomnia and daytime sleepiness were associated with 11% (HR 0.89; 95% CI 0.82–0.97), 15% (HR 0.85; 95% CI 0.77–0.95) and 12% (HR 0.88; 95% CI 0.81–0.96) reduced risk of new-onset AF, respectively. However, no significant association was found between snoring and the incidence of AF (HR 0.99; 95% CI 0.91–1.07). Conclusions: In diabetic populations, sleep duration, chronotype, insomnia and daytime sleepiness are strongly associated with AF incidence. An optimal sleep duration of 6–8 h presents the lowest AF risk compared to short or long sleep duration. Additionally, poor sleep patterns present a greater risk of new-onset AF in women than in men. [ABSTRACT FROM AUTHOR]

Background: How physical activity (PA) and different sleep traits and overall sleep pattern interact in the development of Parkinson's disease (PD) remain unknown. Objective: To prospectively investigate the joint associations of PA and sleep pattern with risk of PD. Methods: Included were 339,666 PD-free participants from the UK Biobank. Baseline PA levels were grouped into low (< 600 MET-mins/week), medium (600 to < 3000 MET-mins/week) and high (≥ 3000 MET-mins/week) according to the instructions of the UK Biobank. Healthy sleep traits (chronotype, sleep duration, insomnia, snoring, and daytime sleepiness) were scored from 0 to 5 and were categorized into "ideal sleep pattern" (≥ 3 sleep scores) and "poor sleep pattern" (0–2 sleep scores). Hazard ratios (HRs) and 95% confidence intervals (CIs) of PD were estimated by Cox proportional hazards models. Results: During a median of 11.8 years of follow-up, 1,966 PD events were identified. The PD risk was lower in participants with high PA (HR = 0.73; 95% CI: 0.64, 0.84), compared to those with low PA; and participants with ideal sleep pattern also had a lower risk of PD (HR = 0.78; 95% CI: 0.69, 0.87), compared to those with poor sleep pattern. When jointly investigating the combined effect, participants with both high PA and ideal sleep pattern had the lowest risk of incident PD (HR = 0.55; 95% CI: 0.44, 0.69), compared to those with low PA and poor sleep pattern; notably, participants with high PA but poor sleep pattern also gained benefit on PD risk reduction (HR = 0.74; 95% CI: 0.55, 0.99). Conclusions: Both high PA and ideal sleep pattern were independently associated with lower risk of developing PD, and those with both high PA level and ideal sleep pattern had the lowest risk. Our results suggest that improving PA levels and sleep quality may be promising intervention targets for the prevention of PD. [ABSTRACT FROM AUTHOR]

Purpose: Servicewomen are at increased risk of common mental disorders compared with servicemen and their female civilian counterparts. The prevalence of eating disorder risk and common mental disorders, and associated risk factors in British servicewomen are poorly understood. Methods: All women younger than 45 yr in the UK Armed Forces were invited to complete a survey about demographics, exercise behaviors, eating behaviors, and common mental disorders. Results: A total of 3022 women participated; 13% of participants were at high risk of an eating disorder based on Brief Eating Disorder in Athletes Questionnaire and Female Athlete Screening Tool scores. Twenty-five percent of participants had symptoms of anxiety (seven-item Generalized Anxiety Disorder Assessment score ≥10), and 26% had symptoms of depression (nine-item Patient Health Questionnaire score ≥10). Older age was associated with a lower risk, and heavier body mass was associated with a higher risk, of eating disorders (P ≤ 0.043). Older age and higher rank were associated with a lower risk of symptoms of anxiety and depression (P ≤ 0.031), and a heavier body mass was associated with a higher risk of symptoms of depression (P ≤ 0.012). Longer habitual sleep duration was associated with a lower risk of eating disorders and symptoms of anxiety and depression (P ≤ 0.028). A higher volume of field exercise was associated with a lower risk, and a higher volume of military physical training and personal physical training was associated with a higher risk, of eating disorders (P ≤ 0.024). Job role and deployment history were not associated with any outcome. Conclusions: Sleeping and training habits provide potential novel targets for exploring how common mental disorders can be managed in British servicewomen. [ABSTRACT FROM AUTHOR]

Physical activity presents an important cornerstone in the management and care of individuals with hypertrophic cardiomyopathy (HCM). Twenty-one individuals with HCM (age: 52±15 years old, body mass index (BMI): 30±7 kg/m2) completed 7-day monitoring using wrist-worn triaxial accelerometers (GENEActiv, ActivInsights Ltd, UK) and were compared to age and sex-matched healthy controls (age: 51±14 years old, BMI: 25±4 kg/m2). For individuals with HCM, clinical parameters (left atrial diameter and volume, peak oxygen consumption, NTproBNP and Minnesota Living with Heart Failure (MLHF)) were correlated with accelerometry. After adjusting for BMI, individuals with HCM spent less time in moderate-vigorous physical activity (MVPA) (86 (55–138) vs. 140 (121–149) minutes/day, p <0.05) compared to healthy controls. Individuals with HCM engaged in fewer MVPA-5 min (6 (2–15) vs. 27 (23–37) minutes/day, p <0.01) and MVPA-10 min bouts (9 (0–19) vs. 35 (17–54) minutes/day, p <0.01) versus healthy controls. For HCM only, peak oxygen consumption was correlated with MVPA (r =0.60, p <0.01) and MVPA-5 min bouts (r =0.47, p <0.05). MLHF score was correlated with slee p duration (r =0.45, p <0.05). Individuals with HCM should be encouraged to engage in moderate-intensity physical activity bouts and reduce prolonged periods of inactivity in order to potentially improve exercise tolerance and reduce disease burden. [ABSTRACT FROM AUTHOR]

Background: Atypical temporal work patterns such as working longer than the standard 35–40 h/ week, weekend working, and nonstandard work schedules (i.e. outside of the typical 9–5, including but not restricted to shiftwork) are increasingly prevalent in the UK. Aside from occupation-specific studies, little is known about the effects of these atypical temporal work patterns on sleep among workers in the UK, even though poor sleep has been linked to adverse health problems, lower workplace productivity, and economic costs. Method: We used regression models to investigate associations between three types of atypical temporal work patterns (long and short weekly work hours, weekend working, and nonstandard schedules) and sleep duration and disturbance using data from over 25,000 employed men and women from 2012–2014 and/or 2015–2017 in the UK Household Longitudinal Study, adjusting for potential confounders and psychosocial work factors. Results: We found that relative to a standard 35–40 h/week, working 55 h/week or more was related to short sleep (less than 7 h/night) and sleep disturbance. Working most/all weekends compared to non-weekends was associated with short sleep, long sleep (more than 8 h/night), and sleep disturbance, as was working nonstandard schedules relative to standard schedules (fixed day-time schedules). Further analyses suggested some gender differences. Conclusions: These results should prompt employers and policymakers to recognise the need for rest and recovery, consider how the timing and scheduling of work might be improved to better support workers' health and productivity, and consider appropriate compensation for anyone required to work atypical temporal work patterns. [ABSTRACT FROM AUTHOR]

Background: To explore the relationship between sleep patterns and cardiovascular disease (CVD) incidence and mortality risk in a population with type 2 diabetes through a UK Biobank sample. Methods: A total of 6860 patients with type 2 diabetes were included in this study. Five sleep factors (including Chronotype, sleep duration, insomnia, daytime sleepiness, and snoring) were collected as a questionnaire. The calculation generates a sleep score of 0–5, and then three sleep patterns were defined based on the sleep scores: poor sleep pattern (0–2), Intermediate sleep pattern (3–4), and healthy sleep pattern (5). HRs and 95% confidence intervals were calculated by multivariate COX proportional risk model adjustment. Restricted cubic splines were used to validate linear associations between sleep scores CVD events. Results: Our results found a reduced risk of CVD events in individuals with healthy sleep patterns compared to participants with poor sleep patterns. CVD Mortality (HR, 0.690; 95% CI 0.519–0.916), ASCVD (Atherosclerosis CVD) (HR, 0.784; 95% CI 0.671–0.915), CAD (Coronary Artery Disease) (HR, 0.737; 95% CI 0.618–0.879), PAD (Peripheral Arterial Disease) (HR, 0.612; 95% CI 0.418–0.896), Heart Failure (HR, 0.653; 95% CI 0.488–0.875). Restricted cubic spline responded to a negative linear correlation between sleep scores and CVD Mortality, ASCVD, CAD, PAD, and Heart Failure. Conclusions: Healthy sleep patterns are significantly associated with a reduced risk of CVD Mortality, ASCVD, CAD, PAD, and Heart Failure in the diabetes population. [ABSTRACT FROM AUTHOR]

Social isolation has been found associated with multiple sleep traits in conventional observational studies. However, whether this association is causal and if so, its direction is uncertain. We analyzed the association between social isolation and multiple sleep traits in 30 430 participants from the Guangzhou Biobank Cohort Study. In bidirectional Mendelian randomization, we used 6, 17, and 11 single nucleotide polymorphisms associated with attendance at sports club/gym, religious group, and pub/social club from the UK Biobank (n = 452 302), respectively, and 152 single nucleotide polymorphisms associated with insomnia from the combination of UK Biobank and 23andme (n = 1 331 010). Observationally in the Guangzhou Biobank Cohort Study, insomnia (yes/no) (beta = 0.12, 95% confidence interval (CI) 0.10–0.16) and poor sleep quality (yes/no) (beta = 0.12, CI: 0.08–0.15), but not sleep duration and chronotype, were associated with a higher social isolation score (severe social isolation). In bidirectional MR, genetically predicted insomnia decreases the odds of attendance at sports club/gym (beta = 0.98, CI: 0.98–0.99) and religious groups (beta = 0.99, CI: 0.98–0.99), but not pub/social club. However, these 3 types of social activity were not associated with insomnia. Our results support the causal effects of insomnia on social activity. Further clinical investigations into the utility of insomnia treatment in alleviating social isolation are needed. [ABSTRACT FROM AUTHOR]

We investigated the effects of long-term greenspace deprivation on sleep during adolescence. Using data from a UK birth cohort, we studied deviations from age-recommended sleep duration through Time Use Diaries. Our sample (N = 1370; 53% female) of urban adolescents had been exposed to the same levels of neighbourhood greenspace from birth up to age 14 years when their time use was tracked. We factored in sex and ethnicity, family income, long-term illness, sharing of a bedroom, access to a garden, as well as air pollution and perceived area safety. Even after full adjustment, there was a significant interaction between greenspace availability and income when predicting sleep duration, such that low-income adolescents living in the greyest urban areas were found to sleep more than the 8–10 h recommended for their age group, while the inverse was true for their counterparts living in areas with more greenspace. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the joint association of asthma and sleep duration with cardiovascular disease (CVD) and mortality risk. This prospective cohort study included 366,387 participants from the UK Biobank. The participants were divided into three groups based on their sleep duration (short: <7 h/d; referent: 65+ years: 7–8 h/d; ages 39–64 years: 7–9 h/d; and long: 65+ years: >8 h/d; ages 39–64 years: >9 h/d). Cox proportional hazards models were used to examine the association between asthma and sleep duration on CVD and all-cause mortality. Participants with asthma and short sleep duration showed increased risk of CVD (hazard ratio [HR] 1.42; 95% confidence interval [CI] 1.34–1.51) and all-cause mortality (HR, 1.26; 95% CI, 1.17–1.36), compared with participants with no asthma in the referent sleep duration group. We documented significant additive interactions between asthma and short sleep duration in relation to CVD (relative excess risk due to interaction [RERI], 0.13; 95% CI, 0.04–0.23) and all-cause mortality (RERI, 0.12; 95% CI, 0.01–0.23). Asthma and short sleep duration may have additive interactions on CVD and all-cause mortality risk, highlighting the importance of controlling asthma in combination with improving sleep duration. [Display omitted] • Asthma and a short sleep duration were associated with an increased risk of CVD and all-cause mortality. • Asthma and short sleep duration have a additive interaction on CVD and all-cause mortality. • Combining improving sleep duration and controlling asthma is beneficial for health. [ABSTRACT FROM AUTHOR]

Objective: Observational studies had demonstrated a link between sleep disturbances and cognitive decline. Here, we aimed to investigate the causal association between genetically predicted sleep traits and cognitive impairment using Mendelian randomization (MR). Methods: Using strict criteria, we selected genetic variants from European ancestry Genome‐wide association studies (GWAS) from the Sleep Disorders Knowledge Portal and UK Biobank as instrumental variables for several sleep traits, including insomnia, sleep duration, daytime sleepiness, daytime napping, and chronotype. Summary statistics related to cognitive impairment were derived from five different GWAS, including the Social Science Genetic Association Consortium. The role of self‐reported sleep trait phenotypes in the etiology of cognitive impairment was explored using inverse‐variance weighted (IVW) tests, MR‐Egger tests, and weighted medians, and sensitivity analyses were conducted to ensure robustness. Results: In the main IVW analysis, sleep duration (reaction time: β = –0.05, 95% CI –0.07 to –0.04, p = 1.93×10−12), daytime sleepiness (average cortical thickness: β = –0.12, 95% CI –0.22 to –0.02, p = 0.023), and daytime napping (fluid intelligence: β = –0.47, 95% CI –0.87 to –0.07, p = 0.021; hippocampal volume in Alzheimer's disease: β = –0.99, 95% CI –1.64 to –0.35, p = 0.002) were significantly negatively correlated with cognitive performance. However, any effects of insomnia and chronotype on cognitive impairment were not determined. Conclusions: Our findings highlighted that focusing on sleep behaviors or distinct sleep patterns‐particularly sleep duration, daytime sleepiness, and daytime napping, was a promising approach for preventing cognitive impairment. This study also shed light on risk factors for and potential early markers of cognitive impairment risk factors. [ABSTRACT FROM AUTHOR]

Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature. The associations between sleep, depression and brain activity are not well understood. Here, the authors show patterns of brain activity associated with insomnia and depression resemble those found in people who sleep less, but only under cognitive load. At rest, these activation patterns are hyperconnected and resemble those found in longer sleepers. [ABSTRACT FROM AUTHOR]

Disrupted circadian rhythms have been linked to an increased risk of hypertension and cardiovascular disease. However, many studies show inconsistent findings and are not sufficiently powered for targeted subgroup analyses. Using the UK Biobank cohort, we evaluate the association between circadian rhythm-disrupting behaviours, blood pressure (SBP, DBP) and inflammatory markers in >350,000 adults with European white British ancestry. The independent U-shaped relationship between sleep length and SBP/DBP is most prominent with a low inflammatory status. Poor sleep quality and permanent night shift work are also positively associated with SBP/DBP. Although fully adjusting for BMI in the linear regression model attenuated effect sizes, these associations remain significant. Two-sample Mendelian Randomisation (MR) analyses support a potential causal effect of long sleep, short sleep, chronotype, daytime napping and sleep duration on SBP/DBP. Thus, in the current study, we present a positive association between circadian rhythm-disrupting behaviours and SBP/DBP regulation in males and females that is largely independent of age. Circadian disruption is linked to increased blood pressure and heart disease risk. Here, the authors show a positive association between circadian disruption and blood pressure (SBP/DBP) regulation in males and females irrespective of age, weight and inflammatory status. [ABSTRACT FROM AUTHOR]

Background: The co-occurrence of cardiometabolic diseases (CMDs) is increasingly prevalent and has been associated with an additive risk of dementia in older adults, but the extent to which this risk can be offset by a healthy lifestyle is unknown. We aimed to examine the associations of cardiometabolic multimorbidity and lifestyle with incident dementia and related brain structural changes. Methods: This prospective study extracted health and lifestyle data from 171 538 UK Biobank participants aged 60 years or older without dementia at baseline between 2006 and 2010 and followed up until July 2021, as well as brain structural data in a nested imaging subsample of 11 972 participants. Cardiometabolic multimorbidity was defined as the presence of two or more CMDs among type 2 diabetes, coronary heart disease, stroke, and hypertension. Lifestyle patterns were determined based on 7 modifiable lifestyle factors including smoking, alcohol consumption, physical activity, diet, sleep duration, sedentary behavior, and social contact. Results: Over a median follow-up of 12.3 years, 4479 (2.6%) participants developed dementia. The presence of CMDs was dose-dependently associated with an increased risk of dementia. Compared with participants with no CMDs and a favourable lifestyle, those with ≥ 3 CMDs and an unfavourable lifestyle had a five times greater risk of developing dementia (HR 5.33, 95% CI 4.26–6.66). A significant interaction was found between CMD status and lifestyle (Pinteraction=0.001). The absolute difference in incidence rates of dementia per 1000 person years comparing favourable versus unfavourable lifestyle was − 0.65 (95% CI − 1.02 to − 0.27) among participants with no CMDs and − 5.64 (− 8.11 to − 3.17) among participants with ≥ 3 CMDs, corresponding to a HR of 0.71 (0.58–0.88) and 0.42 (0.28–0.63), respectively. In the imaging subsample, a favourable lifestyle was associated with larger total brain, grey matter, and hippocampus volumes across CMD status. Conclusion: Our findings suggest that adherence to a healthy lifestyle might substantially attenuate dementia risk and adverse brain structural changes associated with cardiometabolic multimorbidity. [ABSTRACT FROM AUTHOR]

Background: Few studies have investigated the joint effects of sleep traits on the risk of acute myocardial infarction (AMI). No previous study has used factorial Mendelian randomization (MR) which may reduce confounding, reverse causation, and measurement error. Thus, it is prudent to study joint effects using robust methods to propose sleep-targeted interventions which lower the risk of AMI. Methods: The causal interplay between combinations of two sleep traits (including insomnia symptoms, sleep duration, or chronotype) on the risk of AMI was investigated using factorial MR. Genetic risk scores for each sleep trait were dichotomized at their median in UK Biobank (UKBB) and the second survey of the Trøndelag Health Study (HUNT2). A combination of two sleep traits constituting 4 groups were analyzed to estimate the risk of AMI in each group using a 2×2 factorial MR design. Results: In UKBB, participants with high genetic risk for both insomnia symptoms and short sleep had the highest risk of AMI (hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.03, 1.18), although there was no evidence of interaction (relative excess risk due to interaction (RERI) 0.03; 95% CI −0.07, 0.12). These estimates were less precise in HUNT2 (HR 1.02; 95% CI 0.93, 1.13), possibly due to weak instruments and/or small sample size. Participants with high genetic risk for both a morning chronotype and insomnia symptoms (HR 1.09; 95% CI 1.03, 1.17) and a morning chronotype and short sleep (HR 1.11; 95% CI 1.04, 1.19) had the highest risk of AMI in UKBB, although there was no evidence of interaction (RERI 0.03; 95% CI −0.06, 0.12; and RERI 0.05; 95% CI –0.05, 0.14, respectively). Chronotype was not available in HUNT2. Conclusions: This study reveals no interaction effects between sleep traits on the risk of AMI, but all combinations of sleep traits increased the risk of AMI except those with long sleep. This indicates that the main effects of sleep traits on AMI are likely to be independent of each other. [ABSTRACT FROM AUTHOR]

Modern society is structured around early routines which cause evening types to suffer from health and performance detriments associated with sleep times being misaligned with biological needs (circadian preference). Given that COVID-19 lockdowns were less constrained by social schedules, the current study explores whether temporal behaviours became better aligned with biological needs, and whether these changes benefited work engagement. 406 UK participants reported circadian preference and pre-lockdown and lockdown sleep times, work times, and work engagement. Results found that sleep health improved under lockdown measures in terms of increased sleep duration and reduced social jetlag, and sleep and work times became better aligned with circadian preferences. The most circadian-misaligned participants – students and young adults – exhibited the largest changes to sleep and work habits. However, work engagement decreased more in participants with improved social jetlag and delayed work habits, which is surprising given that these temporal changes reflect improved circadian alignment. We discuss potential moderators including poor sleep quality, non-engaging work-from-home environments, and mental health. These findings have implications for encouraging flexible educational and employment schedules post-COVID-19 to satisfy the common drive to improve circadian alignment, but future work must determine the moderating factors that impair work engagement during remote work. [ABSTRACT FROM AUTHOR]

Aims: To investigate the association between socioeconomic deprivation and indicators of sleep health among patients with type 2 diabetes mellitus (T2DM), and additionally, to examine whether socioeconomic deprivation is associated with higher glycated haemoglobin (HbA1c) levels in these patients. Materials and Methods: We analysed data from the UK Biobank, consisting of 17 206 participants with T2DM, to explore the relationship between socioeconomic deprivation, self‐reported indicators of sleep health, and HbA1c levels. Socioeconomic deprivation was assessed using the Townsend deprivation index. Participants were divided into two groups: low socioeconomic deprivation (n = 8604; reference group) and high socioeconomic deprivation (n = 8602). Logistic regression models were employed, adjusting for covariates such as body mass index (BMI), age, and biological sex. Results: Patients with high socioeconomic deprivation had higher odds of reporting usual difficulties falling asleep or sleeping through the night (adjusted odds ratio 1.20, 95% confidence interval [CI] 1.12, 1.28), and they were more likely to use at least one hypnotic medication (adjusted odds ratio 1.41, 95% CI 1.09, 1.84). They also had higher odds of reporting snoring and difficulties staying awake during the daytime (adjusted odds ratio 1.09, 95% CI 1.01, 1.18), as well as experiencing short sleep duration (defined as <6 hours of sleep per day; adjusted odds ratio 1.69, 95% CI 1.50, 1.91). Moreover, patients with high socioeconomic deprivation had increased odds of experiencing comorbid sleep problems (P ≤ 0.001). Finally, high socioeconomic deprivation was associated with a 0.1% higher HbA1c level (P < 0.001). Controlling for indicators of poor sleep health did not alter the strength of this association. Conclusions: Socioeconomic deprivation may represent a risk factor for poor sleep health in patients with T2DM. [ABSTRACT FROM AUTHOR]

Sleep behaviors are potentially modifiable risk factors for common mental disorders and cardiovascular disease (CVD). However, the associations between combined sleep behaviors and common mental disorders among individuals with CVD remain unclear. A total of 18,776 participants with a history of CVD from UK Biobank, who were free of depression or anxiety from 2006 to 2010 were included. A composite healthy sleep score was constructed based on five sleep behaviors (chronotype, sleep duration, insomnia, snoring, and excessive daytime sleepiness). Cox proportional hazard regression models were performed to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs) for incident depression and anxiety. During a median follow-up of 11.8 years, 965 depression and 812 anxiety cases were recorded. The adjusted HRs for participants with a healthy sleep pattern compared with a poor sleep pattern were 0.45 (95 % CI: 0.35–0.57) for depression and 0.77 (95 % CI: 0.58–1.03) for anxiety. There was a linear dose-response association of healthy sleep score with incident depression and anxiety (HR = 0.82, 95 % CI: 0.77–0.87; HR = 0.92, 95 % CI: 0.86–0.99 per 1-score increase, respectively). Likewise, these associations were observed among individuals with coronary heart disease, stroke, heart failure and atrial fibrillation. A healthy sleep pattern is significantly associated with a lower risk of depression among individuals with CVD, highlighting the importance of monitoring and improving sleep health in the prevention of common mental disorders among individuals with CVD. • The adjusted HRs for healthy sleepers versus poor sleepers were 0.45 (95% CI: 0.35-0.57) for depression. • A higher sleep score is associated with a lower risk of depression and anxiety, with a linear dose-response relationship. • Monitoring and improving sleep health is crucial in preventing common mental disorders among CVD patients. [ABSTRACT FROM AUTHOR]

The circadian clock regulates multiple aspects of human physiology including immunity. People have a circadian preference termed chronotype. Those with an evening preference may be better suited to shift work, but also carry higher risk of adverse health. Shift work leads to misalignment of circadian rhythms and is associated with increased risk of inflammatory disease such as asthma and cancer. Here, we investigate the association between chronotype, shift work, and rheumatoid arthritis (RA). The associations between exposures of shift work and chronotype on risk of RA were studied in up to 444,210 U.K. Biobank participants. Multivariable logistic regression models were adjusted for covariates: age, sex, ethnicity, alcohol intake, smoking history, Townsend Deprivation Index (TDI), sleep duration, length of working week, and body mass index (BMI). After adjusting for covariates, individuals with a morning chronotype had lower odds of having rheumatoid arthritis (RA; odds ratio [OR]: 0.93, 95% confidence interval [CI]: 0.88-0.99) when compared to intermediate chronotypes. The association between morning chronotype and RA persisted with a more stringent RA case definition (covariate-adjusted OR: 0.89, 95% CI: 0.81-0.97). When adjusted for age, sex, ethnicity, and TDI, shift workers had higher odds of RA (OR: 1.22, 95% CI: 1.1-1.36) compared to day workers that attenuated to the null after further covariate adjustment (OR: 1.1, 95% CI: 0.98-1.22). Morning chronotypes working permanent night shifts had significantly higher odds of RA compared to day workers (OR: 1.89, 95% CI: 1.19-2.99). These data point to a role for circadian rhythms in RA pathogenesis. Further studies are required to determine the mechanisms underlying this association and understand the potential impact of shift work on chronic inflammatory disease and its mediating factors. [ABSTRACT FROM AUTHOR]

Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short (≤ 5 h) and long (≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression. Here, the authors investigate the genetic basis of short (≤ 5 h) and long (≥ 10 h) sleep duration, identifying 84 independent significant risk loci for short sleep and 1 locus for long sleep, and causal associations between sleep and psychiatric traits. [ABSTRACT FROM AUTHOR]

Increasing evidence suggests a correlation between changes in the composition of gut microbiota and sleep-related phenotypes. However, it remains uncertain whether these associations indicate a causal relationship. The genome-wide association study summary statistics data of gut microbiota (n = 18,340) was downloaded from the MiBioGen consortium and the data of sleep-related phenotypes were derived from the UK Biobank, the Medical Research Council-Integrative Epidemiology Unit, Jones SE, the FinnGen consortium. To test and estimate the causal effect of gut microbiota on sleep traits, a two-sample Mendelian randomization (MR) approach using multiple methods was conducted. A series of sensitive analyses, such as horizontal pleiotropy analysis, heterogeneity test, MR Steiger directionality test and "leave-one-out" analysis as well as reverse MR analysis, were conducted to assess the robustness of MR results. The genus Anaerofilum has a negative causal effect on getting up in the morning (odd ratio = 0.977, 95% confidence interval: 0.965–0.988, p = 7.28 × 10−5). A higher abundance of order Enterobacteriales and family Enterobacteriaceae contributed to becoming an "evening person". Six and two taxa were causally associated with longer and shorter sleep duration, respectively. Specifically, two SCFA-produced genera including Lachnospiraceae UCG004 (odd ratio = 1.029, 95% confidence interval = 1.012–1.046, p = 6.11 × 10−4) and Odoribacter contribute to extending sleep duration. Two obesity-related genera such as Ruminococcus torques (odd ratio = 1.024, 95% confidence interval: 1.011–1.036, p = 1.74 × 10−4) and Senegalimassilia were found to be increased and decreased risk of snoring, respectively. In addition, we found two risk taxa of insomnia such as the order Selenomonadales and one of its classes called Negativicutes. All of the sensitive analysis and reverse MR analysis results indicated that our MR results were robust. Our study revealed the causal effect of gut microbiota on sleep and identified causal risk and protective taxa for chronotype, sleep duration, snoring and insomnia, which has the potential to provide new perspectives for future mechanistic and clinical investigations of microbiota-mediated sleep abnormal patterns and provide clues for developing potential microbiota-based intervention strategies for sleep-related conditions. [ABSTRACT FROM AUTHOR]

Objectives: We test the hypothesis that the incidence of sleep problems is influenced by socio-demographic variables, particularly social deprivation and ethnicity. Methods: Self-reports of sleep duration and sleep difficulties (waking in the night, sleeping in the day, difficulty waking and snoring), personal wealth (household income, property-owning, etc.), ethnic group, employment, education, as well as post-code-based Townsend Social Deprivation, were extracted from UK Biobank's cohort of c500,000 British-domiciled adults (40–70 years). Analyses contrasted the incidence of different sleep problems and a composite measure of these (the Problematic Sleep Index) across groups. Results: Almost one-third of participants reported sleeping shorter (24.7%), or longer (7.7%) than age-corrected recommended sleep durations. The incidence of shorter or longer sleep increased with social deprivation and varied with ethnicity. Snoring, waking during the night, finding it difficult to get up in the morning and sleeping in the daytime were subject to similar effects. The Problematic Sleep Index showed being younger, male, employed, home-owning, having a higher household income, having a higher level of educational achievement, and time in education were all associated with better sleep, as was living in a more affluent area and being White. Conclusions: Sleep problems in Britain show a social gradient, independently of a range of other demographic and social influences, suggesting that sleep quality differs with and between ethnic groups. These sleep inequalities suggest that the protective and recuperative effects of sleep are disproportionately distributed across society and should encourage us to consider the potential benefits of community-specific sleep interventions. [ABSTRACT FROM AUTHOR]

Aims: To investigate whether the association between sleep patterns and cardiovascular disease (CVD) risk differs according to glucose tolerance status. Materials and Methods: This prospective study included 358,805 participants initially free of CVD from the UK Biobank. We created a sleep score based on five sleep factors (sleep duration, chronotype, insomnia, snoring, and daytime sleepiness) with one point for each unhealthy factor. Cox proportional hazards models were used to examine the association between sleep and incident CVD, including coronary heart disease (CHD) and stroke, according to normal glucose tolerance (NGT), prediabetes, and diabetes. Results: During a median follow‐up of 12.4 years, 29,663 incident CVD events were documented. There was a significant interaction between sleep score and glucose tolerance status on CVD (P for interaction = 0.002). Each 1 point increment in sleep score was associated with a 7% (95% confidence interval 6%–9%), 11% (8%–14%), and 13% (9%–17%) higher risk of CVD among participants with NGT, prediabetes, and diabetes, respectively. Similar interaction patterns were observed for CHD and stroke. Among the individual sleep factors, sleep duration and insomnia significantly interacted with glucose tolerance status on CVD outcomes (all P for interaction <0.05). All five unhealthy sleep factors accounted for 14.2% (8.7%–19.8%), 19.5% (7.4%–31.0%), and 25.1% (9.7%–39.3%) of incident CVD cases among participants with NGT, prediabetes, and diabetes, respectively. Conclusions: The CVD risk associated with a poor sleep pattern was exacerbated across glucose intolerance status. Our findings emphasise the importance of integrating sleep management into a lifestyle modification programme, particularly in people with prediabetes or diabetes. [ABSTRACT FROM AUTHOR]