Multiple Risks and Adolescent Depressive Symptoms in Ethnic Regions of China: Analyses Using Cumulative Risk Model, Logistic Regression, and Association Rule Mining.

The present study aimed to examine the relationship between multiple risk exposures in family and school settings and the depressive symptoms of Chinese students in early adolescence living in the ethnic regions of Yunnan and Hebei, China, via different multiple risk analytic approaches. A total of 2940 students (47.3% females) in grades 4 to 9 (age = 12.08, = 2.04) from ethnic minority counties in Yunnan and Hebei participated in the survey. The participants completed the questionnaires and reported family risk, school risk, depressive symptoms, and demographic information. The cumulative risk model and the individual multiple risk models with logistic regression/association rule mining were used to examine the effects of cumulative risk, the relative contributions of individual risks, and combinations of multiple risks. We found that (1) when a cumulative risk model was used, the associations between family cumulative risk and school cumulative risk on depressive symptoms were significant, but the cross-domain interaction effect was not significant. (2) The results of logistic regression indicated that high levels of family conflict, low levels of family cohesion, low levels of teacher support, and low levels of peer support were significantly correlated with a high risk for depression. (3) The results of association rule mining revealed meaningful associations between multiple risk factor combinations and depressive symptoms. In conclusion, the use of association rule mining enhanced the analyses and understanding of the effects of multiple risk exposures. Interpersonal stressors in family and school settings need to be addressed in depression prevention and intervention programs for adolescents.