To analyze the significance of various factors affecting depression in middle-aged and elderly individuals, as well as the association between different demographic characteristics and depression based on the theory of social determinants of health, providing a reference for improving the physical and mental health of this population.

Using data from the 2020 China Health and Retirement Longitudinal Study, the research focused on individuals aged 45 and above. A random forest model was employed to rank the importance of factors influencing depression in this demographic, and association rule mining was conducted to analyze population characteristics.

The depression rate among middle-aged and elderly individuals was 34.7%. The random forest model indicated that the top 11 variables influencing depression, ranked by their Mean Decrease Accuracy (MDA) values, were as follows: impaired Activities of Daily Living (ADL) (20.24%), chronic diseases(19.12%), social participation (18.72%), medical insurance (18.10%), age (16.77%), self-rated health status (15.31%), emotional support (11.91%), economic support (10.80%), internet usage (10.67%), education level (9.97%), and sleep duration(9.77%) (P<0.05). The results of association rule mining revealed that the combination of impaired ADL, chronic diseases, age ≥ 66 years, lack of medical insurance, and sleep duration < 7 hours significantly increased the risk of depression in middle-aged and elderly individuals, with a support of 20.740% and a confidence of 77.786%, indicating a risk 3.751 times greater than those without these characteristics.

The factors influencing depression in middle-aged and elderly individuals are multidimensional. Impaired ADL, chronic diseases, age ≥ 66 years, lack of medical insurance, and sleep duration < 7 hours are critical factors affecting depression. Screening for these key factors can identify high-risk populations, thereby reducing the risk of depression and improving the mental health levels of middle-aged and elderly individuals.