Multidimensional factors of depressive symptoms among Chinese undergraduate students: a cross-sectional study using binary logistic regression

Introduction This cross-sectional study investigates the interplay of lifestyle, behavioral, and psychosocial factors in predicting depressive symptoms among Chinese college students (N=508) using binary logistic regression. Methods Participants were recruited from four geographically diverse provinces (Eastern: Shandong; Western: Shaanxi, Sichuan; Southern: Hainan) across 8 universities (5 comprehensive universities, 3 specialized institutions), with balanced urban (n=245, 48.22%) and rural (n=263, 51.78%) representation. Standardized scales assessed depressive symptoms (PHQ-9), perceived stress (PSS), academic procrastination (PASS), physical activity (PARS-3), cyberbullying victimization (CVQ), and alcohol use (AUDIT). Results Results revealed significant negative associations of sleep duration and physical activity with depressive symptoms (p<0.05), while academic procrastination, cyberbullying, perceived stress, and alcohol consumption showed significant positive predictive effects (p<0.01). Discussion Despite limitations of convenience sampling and cross-sectional design, findings suggest a complex interplay of multidimensional factors in college students’ mental health. Early screening and comprehensive interventions targeting lifestyle, behavioral, and psychosocial domains are recommended. Further longitudinal and experimental studies are warranted to elucidate causal pathways and inform targeted prevention strategies in university settings.