Trajectories of depressive symptoms and subsequent cognitive decline in older adults: a pooled analysis of two longitudinal cohorts.

Journal Article (Journal Article)

BACKGROUND: the course of depression is variable, but it is unknown how this variability over time affects long-term cognitive decline. OBJECTIVE: to examine the relationship of different trajectories of depressive symptoms on rates of subsequent cognitive decline in older adults. DESIGN: population-based cohort study. SETTING: communities in the USA and England. SUBJECTS: 17,556 older adults from the Health and Retirement Study and the English Longitudinal Study of Ageing. METHODS: depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale, and trajectories were calculated using group-based trajectory modelling. Global cognitive function and three cognitive domains of memory, executive function and temporal orientation were assessed for up to 18 years. RESULTS: five trajectories of depressive symptoms were identified. Compared with the 'non-depressed' trajectory, the 'worsening depressive symptoms' trajectory (pooled β = -0.016 standard deviation (SD)/year, 95% confidence interval (CI): -0.021 to -0.010), 'persistent depressive symptoms' trajectory (pooled β = -0.016 SD/year, 95% CI: -0.024 to -0.008), and 'mild depressive symptoms' trajectory (pooled β = -0.008 SD/year, 95% CI: -0.014 to -0.003) were associated with faster rates of cognitive decline, while no such association was found for the 'improving depressive symptoms' trajectory (pooled β = 0.001 SD/year, 95% CI: -0.010 to 0.012). CONCLUSIONS: subthreshold depressive symptoms are associated with an increased rate of cognitive decline, while individuals who show improving depressive symptoms do not exhibit accelerated cognitive decline. These findings raise the possibility that maintaining depressive symptoms as low as possible and ignoring the clinical threshold, might mitigate cognitive decline in older adults.

Full Text

Duke Authors

Cited Authors

  • Zhu, Y; Li, C; Xie, W; Zhong, B; Wu, Y; Blumenthal, JA

Published Date

  • January 6, 2022

Published In

Volume / Issue

  • 51 / 1

PubMed ID

  • 34657957

Electronic International Standard Serial Number (EISSN)

  • 1468-2834

Digital Object Identifier (DOI)

  • 10.1093/ageing/afab191

Language

  • eng

Conference Location

  • England