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Depression

Longitudinal relationships in the psychopathology of depressive symptoms in middle-aged and older adults in China

, ORCID Icon, ORCID Icon, ORCID Icon &
Pages 1692-1701 | Received 13 Sep 2022, Accepted 07 Dec 2022, Published online: 04 Jan 2023
 

Abstract

Objectives

To develop symptom networks and examine the longitudinal relationships of depressive symptoms among middle-aged and older adults in China.

Method

This study used three-wave data from the China Health and Retirement Longitudinal Study (2013 (T1), 2015 (T2), and 2018 (T3)). Depressive symptoms were measured by the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). A multilevel vector autoregression model (VAR) was used to identify ten depressive symptoms dynamically interacting with each other over time.

Results

A total of 3,558 participants were included in the final analysis. The strongest direct effects were ‘D10: felt fearful’ -> ‘D6: felt everything I did was an effort’ (β = 0.14). ‘D10: felt fearful’ reported the largest value of out-predictability (r = 0.064) and out-strength (r = 0.635). ‘D3: felt depressed’ reported the largest value of in-predictability (r = 0.077) and in-strength (r = 0.545). Substantial heterogeneity in the network may stem from an individual’s sex and place of residence.

Conclusions

‘Felt fearful’ was the strongest predictor compared to the other nine depressive symptoms based on node centrality. Our study suggests that, after understanding the causes of fear, strategies to reduce fear should be incorporated into multimodal interventions for middle-aged and older adults with depressive symptoms.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethics approval

CHARLS project were reviewed and approved by Peking University. For more details on consent to participate and consent for publication, please see CHARLS’s official website (https://charls.pku.edu.cn/).

Additional information

Funding

This study is partially supported by the National Institutes of Health (P30AG059304, P50MD017356).

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