Decomposition and comparative analysis of differences in depressive symptoms between urban and rural older adults: Evidence from a national survey

Abstract

ABSTRACT Objectives: The aim of this study was to investigate the factors influencing urban–rural differences in depressive symptoms among old people in China and to measure the contribution of relevant influencing factors. Design: A cross-sectional research. The 2018 data from The Chinese Longitudinal Health Longevity Survey (CLHLS). Setting: Twenty-three provinces in China. Participants: From the 8th CLHLS, 11,245 elderly participants were selected who met the requirements of the study. Measurements: We established binary logistic regression models to explore the main influencing factors of their depressive symptoms and used Fairlie models to analyze the influencing factors of the differences in depressive symptoms between the urban and rural elderly and their contribution. Results: The percentage of depressive symptoms among Chinese older adults was 11.72%, and the results showed that rural older adults (12.41%) had higher rates of depressive symptoms than urban (10.13%). The Fairlie decomposition analysis revealed that 73.96% of the difference in depressive symptoms could be explained, which was primarily associated with differences in annual income (31.51%), education level (28.05%), sleep time ( − 25.67%), self-reported health (24.18%), instrumental activities of daily living dysfunction (20.73%), exercise (17.72%), living status ( − 8.31%), age ( − 3.84%), activities of daily living dysfunction ( − 3.29%), and social activity (2.44%). Conclusions: The prevalence of depressive symptoms was higher in rural than in urban older adults, which was primarily associated with differences in socioeconomic status, personal lifestyle, and health status factors between the urban and rural residents. If these factors were addressed, we could make targeted and precise intervention strategies to improve the mental health of high-risk elderly.