Multimorbidity patterns and cognitive trajectories in older adults: functional, behavioral, and environmental pathways—a longitudinal analysis of CHARLS
Year: 2026
Type: article
Abstract: Multimorbidity may affect cognitive aging differently according to disease patterns rather than disease counts alone. This study analyzed 2011-2020 data from the China Health and Retirement Longitudinal Study, including 5979 Chinese adults aged 45 years or older. Fifteen chronic conditions were used to identify multimorbidity patterns through latent class analysis. Latent growth curve models examined associations with baseline cognition and cognitive decline, while mediation and moderation analyses assessed activities of daily living, social and intellectual engagement, living environment quality, and adverse childhood experiences. Five patterns were identified: minimal morbidity, sensory-psychiatric-musculoskeletal multimorbidity, cardiometabolic multimorbidity, extensive multisystem multimorbidity, and respiratory-psychiatric-sensory multimorbidity. In fully adjusted models, sensory-psychiatric-musculoskeletal multimorbidity (β = -0.757; 95% CI, - 0.92 to - 0.59) and extensive multisystem multimorbidity (β = -0.469; 95% CI, - 0.73 to - 0.21) were associated with lower baseline cognition. Both showed slower subsequent decline, suggesting a floor effect. Time-varying models showed faster cognitive decline in the cardiometabolic group (β = -0.028; 95% CI, - 0.052 to - 0.005; P = 0.019). Activities of daily living mediated associations across nonreference patterns, whereas social and intellectual engagement mediated only the sensory-psychiatric-musculoskeletal pattern. Poor living environment quality was associated with lower baseline cognition (β = -0.532; 95% CI, - 0.849 to - 0.214; P = 0.002). These findings support phenotype-aware cognitive risk screening and interventions targeting function, engagement, and living environments.
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Awards: Mega Meta Data Set of the Health and Retirement Surveys Around the World, Archiving & Creating User Friendly Data: the Longitudinal Aging Survey in India, Integrating Information about Aging Surveys: Novel Integration of Contextual Data to Study Late-Life Cognition and Alzheimer’s Disease and Related Dementia and Dementia Care
OpenAlex ID: W7202024939