Longitudinal association between depressive symptoms and cognitive decline among middle-aged and elderly population

Abstract

Background: Depression is considered a risk factor for cognitive decline. The long-term impact of depressive symptoms on cognitive performance has not been established thus far.

Objectives: This study aimed to determine the longitudinal associations between depressive symptoms and cognitive performance among middle-aged and elderly population.

Methods: We included 10,387 adults aged ≥45 years from the Health and Retirement Study (2004 to 2014) in this study. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CESD) scale. Participant's cognitive function was assessed via the telephone interview for cognitive status (TICS); the total cognitive score ranged from 0 to 35. We classified the participants into four clusters according to the quartile of the total cognitive score (TCS). We examined the change of depressive symptoms and cognitive performance by using the unconditional latent growth curve modeling (LGCM) method, and a parallel LGCM method was used to examine the longitudinal associations between depressive symptoms and cognitive performance among middle-aged and elderly adults in each cluster.

Results: Participants with lower levels of cognitive performance were associated with a greater risk of high depressive symptoms. Results from unconditional LGCM showed a sustained decline in cognitive performance and an increasing trend in depressive symptoms per 2 years for each cluster of participants. The parallel LGCM indicated that baseline levels of depression showed a significant negative correlation with the cognitive performance at baseline (β [95% CI] of intercept_(Dep) predicting intercept_(TCS) were -0.33 [-0.41, -0.26], -0.03[-0.06, -0.00], -0.05 [-0.07, -0.02] and -0.64 [-0.70,-0.58], for clusters of Q1 to Q3 and the entire population, respectively). Further, a significant positive prospective association was observed between baseline levels of depression and changes in cognitive performance (intercept_(Dep) predicting slope_(TCS) were -0.05 [-0.08, -0.02], -0.09[-0.13, -0.05], -0.12 [-0.15, -0.08], -0.11 [-0.15, -0.06] and -0.04 [-0.06,-0.02] for clusters of Q1 to Q4 and the entire population, respectively). Moreover, for participants with the highest quartile of TCS, the rising trend of depressive symptoms accelerated the decline of cognitive performance during the follow-up period (Slope_(Dep) predicting Slope_(TCS): -0.44 [-0.86, -0.01]).

Conclusion: Our results suggest that depressive symptoms were associated with lower cognitive performance and larger subsequent decline during follow-up period. Adults with depression may require more medical attention, and early intervention is required to delay the development of cognitive impairment and dementia.

Keywords: Cognitive decline; Depressive symptoms; Latent growth curve modeling; Longitudinal association.