Multidimensional Sleep Health Methods: Findings From US and Netherlands Cohorts of Older Adults
Meredith Wallace

TL;DR
This paper explores how different aspects of sleep health relate to health outcomes in older adults using data from US and Netherlands studies.
Contribution
The study introduces and compares methods to quantify multidimensional sleep health and its impact on health outcomes.
Findings
Multidimensional sleep health is associated with longitudinal trajectories of depression and cognitive outcomes.
Different sleep health dimensions are linked to different health outcomes in older adults.
Methods range from simple questionnaires to complex machine learning models for analyzing sleep health.
Abstract
Sleep health is a multidimensional construct, with dimensions including Regularity, Satisfaction, Alertness/Sleepiness, Timing, Efficiency, and Duration. Global estimates from large cohort studies suggest that approximately 30-40% of adults report ≥2 suboptimal sleep health dimensions. Moreover, poor sleep health dimensions are established risk factors for disease and disability, regardless of the presence or absence of a sleep disorder. Although current literature indicates that different sleep health dimensions are associated with different health outcomes, several methodological challenges have created hurdles to understanding which combinations of sleep dimensions are most relevant for each health outcome. In this presentation, Dr. Wallace will outline and demonstrate approaches for quantifying multidimensional sleep health and relating it to health outcomes. These methods range…
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Taxonomy
TopicsSleep and related disorders · Cardiovascular Health and Risk Factors · Mental Health Research Topics
