The elderly population in our country is large and growing rapidly, and depression is a common emotional disorder and mental health problem among the elderly population. The mental health of the female elderly population is increasingly becoming a focus of social concern.

To explore the influencing factors of depression symptoms in the female elderly population from a multi-level and comprehensive perspective of health ecology, and provide theoretical basis for identifying and intervening in depression symptoms in the elderly female population in China.

In January 2024, we extracted for the 2020 survey data from the China Health and Retirement Longitudinal Survey (CHARLS), and a group of female elderly adults aged 60 years and above were selected for the study (n=4 594). Based on the health ecology model, the influencing factors were divided into five levels: personal characteristics layer, behavioural characteristics layer, interpersonal network layer, living and working conditions layer, and policy environment layer. The χ² test and binary Logistic regression model were used to explore the influencing factors of depression symptoms and to establish a health ecology model of depression symptoms in the Chinese female elderly population.

The detection rate of depression symptoms in the Chinese female elderly population was 48.06% (2 208/4 595). Logistic regression analysis showed that age of ≥80 years (OR=0.601, 95%CI=0.449-0.804), sleep duration of≥6 h (OR=0.561, 95%CI=0.493-0.639), satisfaction with life (OR=0.256, 95%CI=0.199-0.330), better self-rated physical health (OR=0.459, 95%CI=0.395-0.533), urban household registration (OR=0.717, 95%CI=0.603-0.853), satisfaction with children (OR=0.666, 95%CI=0.472-0.940), education level of junior high school and above (OR=0.712, 95%CI=0.582-0.871), family income >50 000 yuan (OR=0.822, 95%CI=0.704-0.959) and the per capita GDP of the city is 50 000 to 100 000 yuan (OR=0.841, 95%CI=0.730-0.970) were the protective factors for the development of depression symptoms in the Chinese female elderly population (P<0.05). Having become disabled (OR=1.786, 95%CI=1.556-2.050), suffering from chronic diseases (OR=1.159, 95%CI=1.014-1.324), central region (OR=1.298, 95%CI=1.107-1.522) and western region (OR=1.407, 95%CI=1.183-1.675) were the risk factors for depression symptoms in the Chinese female elderly population (P<0.05) .

The detection rate of depression symptoms in the Chinese female elderly population is relatively high, and there are many influencing factors, including: age in the personal characteristics layer; sleep time, satisfaction with life, self-related of physical health, disability, and chronic disease in the behavioral characteristics layer; household registration type, satisfaction with children, and geographical distribution in the interpersonal network layer; education and family income in the living and working conditions layer; the per capita GDP of the city in the policy environment layer. Effective intervention measures should be taken at all layers, targeting key populations, in order to reduce the incidence of depression symptoms among the Chinese elderly women.