1. Urban-rural differences in key factors of depressive symptoms among Chinese older adults based on random forest model.
- Author
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Wang, Jun, Wang, Yiwen, Chen, Shufeng, Fu, Tiantian, and Sun, Guoxiao
- Subjects
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OLDER people , *MENTAL depression , *RANDOM forest algorithms , *RURAL-urban differences , *CROSS-cultural studies , *PRESBYCUSIS - Abstract
Depression is a major challenge in the global healthy aging process, and exploring the key factors of depression in urban and rural older adults is essential for differentiated and precise interventions. To explore the urban-rural differences and key influencing factors of depressive symptoms among Chinese older adults. The data of 5267 older adults were obtained from the China Health and Retirement Longitudinal Survey (CHARLS2018). Random forest model and logistic regression were used to analyze the key factors influencing depressive symptoms 19 variables. The detection rate of depressive symptoms in older adults was 31.0 %, with 22.3 % and 34.8 % in urban and rural areas, respectively. Education, self-rated health, self-rated pain, and self-rated vision were common factors. Physical activity (OR = 0.716 for Moderate PA), social activity (OR = 0.671 for social activity), and self-rated hearing (OR = 0.602 for good) were key factors specific to urban older adults, and alcohol consumption (OR = 0.716 for drinking more than once a month) and marital status (OR = 0.689 for cohabitation) were key factors specific to depressive symptoms in rural older adults (all P < 0.05). Cross-sectional data cannot reflect dynamic processes among variables; The cultural background might affect the cross-cultural validity of the study. The key factors of depressive symptoms among older adults in urban and rural areas differed, which provides priority and references for differential prevention and precise intervention of depressive symptoms to promote the process of healthy aging. • Education, self-rated health, pain, and vision are common factors that influence depressive symptoms in older adults. • Physical activity, social activity, and self-rated hearing were key factors specific to urban older adults. • Alcohol consumption and marital status were key factors specific to rural older adults. • The combination of random forest and logistic regression achieves the importance measurement and analysis of factors. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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