Latent profile analysis of depression among medical graduate students: evidence from Anhui Province, China

Background To examine the relationship between social capital and depression among medical graduate students in Anhui Province, China. Methods A cross-sectional study was undertaken involving medical graduate students from Anhui Province, China, utilizing a multi-stage stratified cluster random sampling technique. Data collection was executed through questionnaire-based interviews, gathering information on demographic characteristics, social capital, and depression. To evaluate the association between social capital and depression, a generalized linear model was employed alongside classification and multinomial logistic regression analyses of depression profiles. Results A total of 2587 medical graduate students were included in the analysis. Latent profile analysis divided the subjects' depression levels into three categories: high, medium, and low. Compared to moderate depression, low depression was associated with social connection (OR = 0.518, 95% CI = 0.408–0.658), trust (OR = 0.339, 95% CI = 0.273–0.420), and sense of belonging (OR = 0.650, 95% CI = 0.515–0.820); compared to high depression, low depression was associated with social support (OR = 0.326, 95% CI = 0.214–0.499), social connection (OR = 0.351, 95% CI = 0.222–0.553), trust (OR = 0.245, 95% CI = 0.157–0.382), and sense of belonging (OR = 0.316, 95% CI = 0.194–0.515); using moderate depression as reference, high depression was associated with social support (OR = 0.396, 95% CI = 0.282–0.555), trust (OR = 0.647, 95% CI = 0.438–0.955), and sense of belonging (OR = 0.453, 95% CI = 0.291–0.705). Conclusions Our research indicates that enhancing social capital may contribute to the prevention of depression among medical graduate students.