To explore the current situation and influencing factors of depression among middle-aged and elderly people in China through the analysis of the 2020 survey data of CHARLS, and to provide a theoretical basis for the prevention of depression among middle-aged and elderly people.

First, 13 124 middle-aged and elderly people aged 45 to 74 with complete information were included according to the inclusion and exclusion criteria. Second, the research subjects were divided according to the scores of the Center for Epidemiologic Studies Depression Scale (CES-D10). Then, the Lasso model was used to screen the influencing factors. Finally, a logistic prediction model for depressive symptoms in the elderly was constructed and the prediction effect was evaluated.

Among the 13 124 research subjects, 4 877 had depressive symptoms, with a detection rate of 37.16% (95%CI: 36.33%-37.99%). The LASSO results showed that when the lambda (λ) value was 0.008 595 583, the error was the smallest, and 15 influencing factors were screened out: gender, marital status, type of residence, educational level (junior high school, high school and above), region (central region, western region), drinking status, nighttime sleep duration (h) (>6-7, >7), whether there were social activities in the past month, Internet use, whether often uncomfortable due to pain, number of chronic diseases: ≥ 2, physical activity (Met*min/week): 600-3 000. The logistic regression prediction model showed that female gender, other marital statuses, region (central region, western region), often being uncomfortable due to pain, and number of chronic diseases: ≥ 2 were independent risk factors for depressive symptoms in middle-aged and elderly people (P < 0.05); educational level (junior high school, high school and above), drinking, nighttime sleep duration (h) (>6-7, >7), having social activities in the past month, and Internet use were protective factors for depressive symptoms in middle-aged and elderly people (P < 0.05). The area under the receiver operating characteristic curve was 0.743(95%CI: 0.735-0.752).

The detection rate of depressive symptoms among middle-aged and elderly people is relatively high and is affected by multiple factors. It is recommended to consider preventive measures from multiple aspects and perspectives.