Objective To model the trend of depressive symptoms in the elderly population in China and explore the multidimensional influencing factors, including variables related to the COVID-19 pandemic, to provide insights for the prevention and treatment of depression in the elderly. Methods Based on The China Health and Retirement Longitudinal Study database (2013-2020), group-based trajectory modeling was used to fit the development trajectory of depressive symptoms in the elderly. The trajectory classification determined by the model was used as the dependent variable, and unordered multinomial logistic regression was conducted to analyze the influencing factors. Results Four trajectories of depressive symptom development were identified: the low-risk group, the moderate-risk group, the high-risk group, and the depressive group, accounting for 11.77%, 38.43%, 37.92%, and 11.88% of the sample, respectively. Unordered multinomial logistic regression analysis showed that (1) compared to males, those having a spouse, or with an educational background of college degree or below, living in urban areas, without physical pain, without impaired activities of daily living (ADL), and without impaired instrumental activities of daily living (IADL), individuals living in rural areas (OR=1.64, 95%CI: 1.22~2.21), experiencing physical pain (OR=1.84, 95%CI: 1.42~2.39), having IADL (OR=2.01, 95%CI: 1.44~2.79), and being affected by the pandemic (OR=1.19, 95%CI: 1.09~1.31) were associated with a moderate risk of depression in the elderly; (2) having an education background of college degree or above (OR=0.55, 95%CI: 0.35~0.86), living in urban or semi-urban areas (OR=1.79, 95%CI: 1.07~3.00), living in rural areas (OR=2.15, 95%CI: 1.55~2.98), experiencing physical pain (OR=3.97, 95%CI: 2.97~5.31), having impaired ADL (OR=2.62, 95%CI: 1.78~3.84), having impaired IADL (OR=3.07, 95%CI: 2.19~4.29), and being affected by the pandemic (OR=1.36, 95%CI: 1.24~1.49) were factors associated with a high risk of depression in the elderly; (3) being female (OR=2.07, 95%CI: 1.43~3.01), having a spouse (OR=1.80, 95%CI: 1.19~2.72), living in urban or semi-urban areas (OR=2.26, 95%CI: 1.11~4.57), living in rural areas (OR=2.96, 95%CI: 1.85~4.75), experiencing physical pain(OR=9.67, 95%CI: 5.37~17.43), having impaired ADL (OR=4.63, 95%CI: 2.96~7.23), having impaired IADL (OR=8.03, 95%CI: 5.20~12.40), and being affected by the pandemic (OR=1.46, 95%CI:1.32~1.62) were factors associated with depression in the elderly. Conclusion The COVID-19 pandemic has impacted the proportion of different trajectories of depressive symptoms in the elderly, with an increase in the proportion of high-risk and depressive trajectories. Sex, marital status, education background, living arrangement, recent history (last 2 years) of physical pain, ADL, IADL, and the pandemic's impact on the mental health of the elderly are identified as influencing factors for the trajectory of depressive symptoms.
Key words
elderly individual /
depression /
development trajectory /
COVID-19 pandemic /
geriatric care
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