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Determinants of verbal fluency trajectories among older adults from the English Longitudinal Study of Aging

Authors :
Gkotzamanis V
Koliopanos G
Sánchez-Niubó A
Olaya B
Caballero FF
Ayuso-Mateos JL
Chatterji S
Haro JM
Panagiotakos DB
Source :
APPL NEUROPSYCH-ADUL, r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu, instname, r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu, Fundació Sant Joan de Déu
Publication Year :
2021
Publisher :
Taylor and Francis, 2021.

Abstract

BACKGROUND: Prevalence of dementia and cognitive impairment increase creating the need for identifying modifiable risk factors to reduce their burden. The aim of this study was to identify latent groups following similar trajectories in cognitive performance assessed with the verbal fluency test, as well as their determinants. METHODS: Data from English Longitudinal Study of Aging (ELSA) were studied. Latent groups of similar course through a 6-year period in the outcome variable (verbal fluency) were investigated, along with their determinants, using Group Based Trajectory Modeling (GBTM). RESULTS: Four latent groups of verbal fluency trajectories were revealed. Education was the strongest predictor for a favorable trajectory, while cardiovascular disease and depression symptoms were associated with lower within each trajectory. CONCLUSION: Cardiovascular diseases and depressive symptoms are associated with a worse course of verbal fluency through aging, implying that they might serve as targets for interventions to prevent cognitive decline in the aging population. Contrarily, higher level of education is associated with a more favorable course through aging.

Details

ISSN :
23279095
Database :
OpenAIRE
Journal :
APPL NEUROPSYCH-ADUL, r-FSJD. Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu, instname, r-FSJD: Repositorio Institucional de Producción Científica de la Fundació Sant Joan de Déu, Fundació Sant Joan de Déu
Accession number :
edsair.dedup.wf.001..873e9ec5b243440a2993d58a75ad52f3