Literature DB >> 32405646

Cognitive Functions Predict Trajectories of Sleepiness Over 10 Years: A Population-Based Study.

Ann D Cohen1, Yichen Jia2, Stephen Smagula1,3, Chung-Chou H Chang2,4, Beth Snitz5, Sarah B Berman5,6, Erin Jacobsen1, Mary Ganguli1,3.   

Abstract

BACKGROUND: Excessive daytime sleepiness is associated with chronic disorders of aging and mortality. Because longitudinal data are limited on the development of sleep disturbances and cognitive changes in older adults, we investigated the demographic, clinical, and cognitive predictors of self-reported daytime sleepiness over a period of 10 years.
METHODS: We jointly modeled latent trajectories over time of sleepiness, cognitive domains, and informative attrition and then fit models to identify cognitive trajectories and baseline characteristics that predicted the trajectories of sleepiness.
RESULTS: Three latent trajectory groups were identified: emerging sleepiness, persistent sleepiness, and consistently low daytime sleepiness accounting for attrition in all groups. Compared with low sleepiness, emerging sleepiness was significantly associated with declining attention and subjective memory complaints; persistent sleepiness was associated with lower baseline scores in all cognitive domains, declining language trajectory, and more subjective memory complaints.
CONCLUSIONS: These findings suggest that persistent sleepiness and emerging daytime sleepiness are associated with cognitive decline and multiple morbidities, albeit more subtly in emerging daytime sleepiness. Furthermore, these data suggest that change in the cognitive domain of attention and subjective memory complaints may be early indicators of future sleep disturbance.
© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Cognition; Cognitive aging; Sleep

Year:  2021        PMID: 32405646      PMCID: PMC7907493          DOI: 10.1093/gerona/glaa120

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.053


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