Prospective multidimensional predictors of poor sleep quality in older adults: A cross-national study.

Abstract

Poor sleep quality is highly prevalent among older adults and is associated with a wide range of adverse psychological, cognitive, and physical health outcomes. However, existing evidence has largely been derived from single-country studies, limiting the understanding of whether predictors of poor sleep quality are consistent across different sociocultural contexts. Guided by the biopsychosocial framework, this study aimed to identify shared and context-specific predictors of subsequent poor sleep quality among older adults using data from four nationally representative longitudinal cohorts (Health and Retirement Study [HRS], English Longitudinal Study of Ageing [ELSA], China Health and Retirement Longitudinal Study [CHARLS], and Mexican Health and Aging Study [MHAS]). Participants aged ≥60 years with good baseline sleep quality were included, and harmonized predictors across demographic, biological, psychological, and social-behavioral domains were examined using cross-validated least absolute shrinkage and selection operator (LASSO) regression within each cohort. Depressive symptoms consistently emerged as the strongest predictor of subsequent poor sleep quality across all cohorts, whereas gender, cognitive function, educational attainment, self-rated health, and comorbidity burden showed varying predictive contributions across populations. These findings highlight the multidimensional nature of sleep quality in later life and suggest that psychological health, particularly depressive symptoms, represents a potential target for early identification and intervention across diverse cultural settings.