AbstractObjectivesTo examine age related differences in self-reported sleep quality and their associations with health outcomes across four domains: Physical Health, Cognitive Health, Mental Health and Neural Health.SettingCam-CAN is a cohort study in East Anglia/England, which collected self-reported health and lifestyle questions as well as a range of objective measures from healthy adults.Participants2406 healthy adults (age 18-98) answered questions about their sleep quality (Pittsburgh Sleep Quality Index) and measures of Physical, Cognitive, Mental, and Neural Health. A subset of 641 individuals provided measures of brain structure.Main outcome measuresPittsburgh Sleep Quality Index scores (PSQI) of sleep, and scores across tests within the four domains of health. Latent Class Analysis (LCA) is used to identify sleep types across the lifespan. Bayesian regressions quantify the presence, and absence, of relationships between sleep quality and health measures.ResultsBetter sleep is generally associated with better health outcomes, strongly so for mental health, moderately for cognitive and physical health, but not for sleep quality and neural health. Latent Class Analysis identified four sleep types: ‘Good sleepers’ (68.6%, most frequent in middle age), ‘inefficient sleepers’ (13.05%, most frequent in old age), ‘Delayed sleepers’ (9.76%, most frequent in young adults) and ‘poor sleepers’ (8.6%, most frequent in old age). There is little evidence for interactions between sleep quality and age on health outcomes. Finally, we observe u-shaped associations between sleep duration and mental health (depression and anxiety) as well as self-reported general health, such that both short and long sleep were associated with poorer outcomes.ConclusionsLifespan changes in sleep quality are multifaceted and not captured well by summary measures, but instead as partially independent symptoms that vary in prevalence across the lifespan. Better self-reported sleep is associated with better health outcomes, and the strength of these associations differs across health domains. Notably, we do observed associations between self-reported sleep quality and white matter.FundingBiotechnology and Biological Sciences Research Council (grant number BB/H008217/1). RAK is supported by the Wellcome Trust (grant number 107392/Z/15/Z and the UK Medical Research Council (MC-A060-5PR61).Strengths and limitations of this studyBroad phenotypic assessment of healthy ageing across multiple health domainsAdvanced analytic techniques (i.e. Latent Class Analysis regression) allows new insightsA uniquely large neuroimaging sample combined with Bayesian inference allows for quantification of evidence for the null hypothesisSubjective sleep measures may have drawbacks in older samplesCross-sectional data precludes modelling of within subject changes
Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis
