Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.
Circadian rhythm disturbance is a common feature of psychiatric disorders. Light is the primary input to the circadian clock, with daytime light exposure strengthening rhythms and nighttime light exposure weakening rhythms. However, the independent effects of day and night light exposure on psychiatric outcomes have not been well characterized. In this study, we performed the largest to-date cross-sectional analysis of objectively measured day and night light exposure and examined their relationship with psychiatric disorders. UK Biobank cohort participants aged 37-73 years were recruited into the UK Biobank general cohort population. In a subset of participants (n=86,772; 43% male), light and physical activity patterns were monitored for ~7 days. Using regression models adjusted for age, sex, ethnicity, photoperiod (day length), employment, and physical activity, we examined the independent associations of day and night-time light with psychiatric disorders and measures of symptom severity. We found that greater night light exposure was associated with greater odds of major depressive disorder (MDD), generalized anxiety disorder (GAD), bipolar disorder, post-traumatic stress disorder (PTSD), self-harm behavior and psychotic experiences. Conversely, greater daytime light exposure was associated with lower odds of MDD, PTSD, self-harm behavior and psychotic experiences. There was no significant association of day light exposure with GAD or bipolar disorder. Our findings demonstrate that low day light and bright night light exposure are associated with a wide range of psychiatric outcomes. Avoiding light at night and seeking light during the day may be a simple and effective, non-pharmacological means of broadly improving mental health.
Sleep duration and sleep efficiency are observed risk factors for all-cause mortality, but the role of sleep regularity is unknown. Irregular sleep patterns are associated with ageing, cancer, depressed mood, and cardio-metabolic diseases, and may therefore increase risk of mortality. We extracted Sleep Regularity Index (SRI) scores, sleep duration, and sleep efficiency from one week of actigraphy in 60,997 UK Biobank participants (62.8±7.8 years, 55.6% female). Using Cox Proportional Hazards models, we assessed whether SRI, sleep duration, and sleep efficiency predicted all-cause mortality up to 7.6 years post-actigraphy. A one standard deviation increase in SRI score (+10.7), indicating more regular sleep patterns, predicted a 20.4±2.0% reduced hazard of all-cause mortality (p < .0001). This relationship remained robust after controlling for age, sex, ethnicity, education, income, and employment status (+1SD in SRI predicted an 18.7±2.4% hazard reduction, p < .0001). SRI was a relatively stronger predictor of mortality hazard than sleep duration (explaining 19.0±2.1% vs. 12.4±2.6% of hazard reduction) or sleep efficiency (19.0±2.1% vs. 13.1±2.6%) in two additional Cox models. Sleep regularity may play a causal role in mortality, via contribution to poor health outcomes, or it may be a marker of poor health leading to mortality. These findings suggest that sleep regularity should be monitored and/or adjusted alongside traditional sleep metrics for optimal health and longevity.
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