Stephen Aichele1, Patrick Rabbitt2, Paolo Ghisletta1,3,4. 1. a Swiss National Center of Competence in Research LIVES - Overcoming Vulnerability: Life Course Perspectives , Universities of Lausanne and of Geneva , Switzerland. 2. b Department of Experimental Psychology , University of Oxford , Oxford , UK. 3. c Faculty of Psychology and Educational Sciences , University of Geneva , Geneva , Switzerland. 4. d Swiss Distance Learning University , Brig , Switzerland.
Abstract
OBJECTIVE: We compared the importance of socio-demographic, lifestyle, health, and multiple cognitive measures for predicting individual differences in depressive symptoms in later adulthood. METHOD: Data came from 6203 community-dwelling older adults (age 41-93 years at study entry) from the United Kingdom. Predictors (36 in total) were assessed up to four times across a period of approximately 12 years. Depressive symptoms were measured with the Geriatric Depression Scale. Statistical methods included multiple imputation (for missing data), random forest analysis (a machine learning approach), and multivariate regression. RESULTS: On average, depressive symptoms increased gradually following middle age and appeared to accelerate in later life. Individual differences in depressive symptoms were most strongly associated with differences in combined symptoms of physical illness (positive relation) and fluid intelligence (negative relation). The strength of association between depressive symptoms and fluid intelligence was unaffected by differences in health status within a subsample of chronically depressed individuals. CONCLUSION: Joint consideration of general health status and fluid intelligence may facilitate prediction of depressive symptoms severity during later life and may also serve to identify sub-populations of community-dwelling elders at risk for chronic depression.
OBJECTIVE: We compared the importance of socio-demographic, lifestyle, health, and multiple cognitive measures for predicting individual differences in depressive symptoms in later adulthood. METHOD: Data came from 6203 community-dwelling older adults (age 41-93 years at study entry) from the United Kingdom. Predictors (36 in total) were assessed up to four times across a period of approximately 12 years. Depressive symptoms were measured with the Geriatric Depression Scale. Statistical methods included multiple imputation (for missing data), random forest analysis (a machine learning approach), and multivariate regression. RESULTS: On average, depressive symptoms increased gradually following middle age and appeared to accelerate in later life. Individual differences in depressive symptoms were most strongly associated with differences in combined symptoms of physical illness (positive relation) and fluid intelligence (negative relation). The strength of association between depressive symptoms and fluid intelligence was unaffected by differences in health status within a subsample of chronically depressed individuals. CONCLUSION: Joint consideration of general health status and fluid intelligence may facilitate prediction of depressive symptoms severity during later life and may also serve to identify sub-populations of community-dwelling elders at risk for chronic depression.
Authors: Stephen Aichele; Paolo Ghisletta; Janie Corley; Alison Pattie; Adele M Taylor; John M Starr; Ian J Deary Journal: Psychol Sci Date: 2018-10-25