Exploring the diversity and determinants of various depression symptoms in youth: analysis based on the living environments of university students.
This study aimed to investigate the prevalence and determinants of depression and subthreshold depression among Chinese university students, with a focus on the influence of demographic, behavioral, and academic factors.
A cross-sectional survey was conducted among 3,600 undergraduates from five universities in central China using the CES-D scale and a self-designed lifestyle questionnaire. Multivariate logistic regression and ANOVA were employed to identify risk and protective factors.
The overall depression detection rate was 25.60%, with 9.97% classified as subthreshold depression. Male gender, senior year, low family income, and major dissatisfaction were significant risk factors. Regular exercise served as a protective factor, while excessive smartphone use, smoking, alcohol use, and family history of mental illness were associated with increased risk. A dose-response relationship was observed between major satisfaction and depression severity.
The findings support a spectrum-based view of depression and highlight the need for multidimensional, personalized mental health interventions targeting high-risk student subgroups.
A cross-sectional survey was conducted among 3,600 undergraduates from five universities in central China using the CES-D scale and a self-designed lifestyle questionnaire. Multivariate logistic regression and ANOVA were employed to identify risk and protective factors.
The overall depression detection rate was 25.60%, with 9.97% classified as subthreshold depression. Male gender, senior year, low family income, and major dissatisfaction were significant risk factors. Regular exercise served as a protective factor, while excessive smartphone use, smoking, alcohol use, and family history of mental illness were associated with increased risk. A dose-response relationship was observed between major satisfaction and depression severity.
The findings support a spectrum-based view of depression and highlight the need for multidimensional, personalized mental health interventions targeting high-risk student subgroups.