Urban-rural disparities in the prevalence and trends of depressive symptoms among Chinese elderly and their associated factors

Abstract

Background: This study aimed to examine urban-rural disparities in the prevalence and trends of depressive symptoms (DS) among Chinese elderly and associated factors.

Methods: A total of 8025, 7808, and 4887 respondents aged 60 years and above were selected from the China Family Panel Studies (CFPS) in 2016, 2018, and 2020, respectively. DS was assessed using a short version of Center for Epidemiologic Studies Depression Scale (CES-D). Twenty-two associated factors from six categories were included in random forest (RF) models. All urban-rural comparisons were conducted based on good model performance.

Results: The DS prevalence among all rural elderly was significantly higher than corresponding urban elderly. This disparity continued to widen among younger elderly, while it continued to narrow among older elderly. The top 10 common leading factors were sleep quality, self-rated health, life satisfaction, memory ability, child relationship, IADL disability, marital status, educational level, and gender. Urban-rural disparities in sleep quality, interpersonal trust, and child relationship continued to widen, while disparities in multimorbidity, hospitalization status, and frequency of family dinner continued to narrow.

Limitation: This study may exist recall bias and lacks causal explanation.

Conclusions: Significant and continuing disparities in the DS prevalence were observed between urban and rural elderly in China, showing opposite trends in younger and older elderly. The top 10 leading associated factors for DS were nearly consistent across urban and rural elderly, with sleep quality having strongest contribution. Urban-rural disparities in associated factors also showed different trends. This study provides a reference for mental health promotion among Chinese elderly.

Keywords: Depressive symptoms; Elderly; Machine learning; Random forest; Urban-rural disparity.