Inter-relationship between cognitive performance and depressive symptoms and their association with quality of life in older adults: A network analysis based on the 2017-2018 wave of Chinese Longitudinal Healthy Longevity Survey (CLHLS)

Abstract

Background: Depressive symptoms and cognitive impairment are common psychiatric conditions and often co-occur in older adults. Network analysis has been widely used in exploring the inter-connections between psychiatric symptoms. The aim of this study was to explore the network model of depressive symptoms and cognitive performance, and their association with quality of life in people aged 65 years or above based on the 2017-2018 wave of Chinese Longitudinal Healthy Longevity Survey (CLHLS).

Method: Global cognitive performance, depressive symptoms, and global quality of life (QoL) were measured using the validated Chinese version of the Mini Mental State Examination (MMSE), the 10-item Center for Epidemiologic Studies Short Depression Scale (CES-D), and the World Health Organization Quality of Life-brief version (WHOQOL-BREF), respectively. Central symptoms and bridge symptoms were identified via strength and bridge strength, respectively. The flow network was used to identify symptoms directly related to QoL. Network stability was examined using the case dropping bootstrap method.

Results: A total of 9023 participants were included in the network analysis. CESD3 "Feeling blue/depressed", CESD4 "Everything was an effort", and At_C "Attention and Calculation" were the central (influential) symptoms that had the highest strength value. Three bridge symptoms (i.e., Nam "Naming", CESD2 "Difficulty with concentrating", and Lan "Language") were also identified. CESD10 "Sleep disturbances" had the strongest direct connection to QoL.

Conclusions: This exploratory study highlights the inter-relationships between cognitive performance and depressive symptoms in older adults in the general population. Interventions targeting bridge symptoms have the potential to alleviate depressive and cognitive symptoms in this population. Furthermore, improving sleep quality in older adults may reduce the negative impact of depression and cognition decline on QoL.

Keywords: Cognition; Depression; Network analysis; Older adults; Quality of life.