Unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents

Background: It is well known that some lifestyle-related behaviors are related to depressive symptoms, but the unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents are still controversial. Aims: The aims of this study were to examine the unique and cumulative effects of lifestyle-related behaviors on depressive symptoms among Chinese adolescents, and explored the potential influences of gender difference on these associations. Methods: We conducted a cross-sectional study among 3967 Chinese adolescents aged 11 to 19 from Jilin, China during September and October of 2018. Students reported their lifestyle factors including sleep duration, time spent on computer, time spent on television, time spent on homework, eating breakfast, smoking, drinking, physical activity, and outdoor activity. Depressive symptoms were measured using the Center for Epidemiologic Studies Depression Scale (CES-D). Results: The prevalence of depressive symptoms was 28.2% among Chinese adolescents. Multivariate logistic regression analysis revealed that sleep duration <8 hour/day, time spent on homework > 3 hour/day, skipping breakfast, alcohol use, physical activity <3 days/week, and outdoor activity <2 hour/day were positively associated with depressive symptoms in both girls and boys. Time spent on computer > 2 hour/day was an independent risk predictor for depressive symptoms in males, while smoking only showed higher risk of depressive symptoms in females. There was an additive relationship between the lifestyle risk index scores and the risk of depressive symptoms for both genders, the relationship being strongest among females. Conclusion: The important role of lifestyle factors should be taking into consideration when create intervention programs to prevent and reduce depressive symptoms among adolescents. In addition, preventive interventions may need to focus on gender-informed approaches when targeting multiple lifestyle factors.