Multidimensional Sleep Health: Concepts, Advances, and Implications for Research and Intervention

Abstract The new paradigm of multidimensional sleep health (‘sleep health’) offers both challenges and opportunities for sleep science. Buysse (2014) has described sleep health to be multidimensional, framed as positive attributes, operationalizable into composite measures of global sleep health, sensitive to upstream exposures, and consequential for downstream health. We highlight two paradigm-shifting effects of a multidimensional sleep health perspective. The first is the use of composite sleep metrics which i) enable quantification of population shifts in sleep health, ii) with possibly reduced measurement error, iii) greater statistical stability, and iv) reduced multiple-testing burdens. The second is that sleep dimensions do not occur in isolation, that is, they are commonly biologically or statistically dependent. These dependencies complicate hypothesis tests yet can be leveraged to inform scale construction, model interpretation, and inform targeted interventions. To illustrate these points, we i) extended Buysse’s Ru SATED model; ii) constructed a conceptual model of sleep health; and iii) showed exemplar analyses from the Multi-Ethnic Study of Atherosclerosis (n=735). Our findings support that sleep health is a distinctively useful paradigm to facilitate interpretation of a multitude of sleep dimensions. Nonetheless, the field of sleep health is still undergoing rapid development and is currently limited by: i) a lack of evidence-based cut-offs for defining optimal sleep health; ii) longitudinal data to define utility for predicting health outcomes; and iii) methodological research to inform how to best combine multiple dimensions for robust and reproducible composites.