Objective: To analyze the longitudinal association between mobile phone dependence and depressive symptoms in college students, so as to provide a theoretical basis for psychological health education among college students. Methods: From November 2021 to June 2023, 2 515 first year students from 2 universities in Yunnan Province were surveyed with a questionnaire by a cluster random sampling method, including baseline survey (November 2021, T1) and three follow up visits (June 2022, T2; November 2022, T3; June 2023, T4). The Self rating Questionnaire for Adolescent Problematic Mobile Phone Use and the Depression Anxiety Stress Scales-21 (DASS-21) were used to evaluate mobile phone dependence and depressive symptoms of college students. The χ 2 test was used to analyze the difference in depressive symptoms among different demographic groups, and a generalized estimation equation model was established to analyze the association between mobile phone dependence symptoms and depressive symptoms. Results: The detection rates of depressive symptoms among university students in Yunnan Province at time points T1, T2, T3, and T4 were 23.02%, 33.36%, 34.79% and 35.51%, respectively. There were statistically significant differences in the detection rates of depressive symptoms among college students with different sacademic burden (T1, T2, T3, T4), different number of close friends (T1, T2, T3), as well as their father s educational level (T1), mothers educational level (T2, T4), gender (T4), major (T3, T4), education (T2, T3, T4), family residency (T1, T2), and family economic conditions (T1, T2, T4) ( χ 2= 59.68 , 49.38, 16.70, 39.31; 55.35, 26.01, 16.69; 10.22; 14.87, 11.51; 14.90; 27.81, 50.28; 9.75, 7.42, 24.76; 6.06, 4.47 ; 15.88, 14.58, 15.85, P < 0.05 ). After controlling for demographic variables and confounding factors in the generalized estimation equation model, mobile phone dependence ( β =0.11), withdrawal symptoms of mobile phone dependence ( β =0.14), and the physical and mental effects of mobile phone dependence ( β =0.14) were all positively correlated with depressive symptoms ( P <0.01). Further gender analysis showed that depressive symptoms in both boys ( β =0.13, 0.13, 0.18) and girls ( β =0.10, 0.13, 0.13 ) were associated with mobile phone dependence, withdrawal symptoms of mobile phone dependence and the physical and mental effects of mobile phone dependence ( P <0.01). Conclusions Depressive symptoms of college students are positively correlated with mobile phone dependence, and family economic conditions, academic burden and number of close friends are factors that continued to affect depressive symptoms. College students should be guided to pay attention to the impact of excessive use of mobile phones on their physical and mental health, use mobile phones reasonably to reduce the incidence of depressive symptoms among college students.