Below: Effect of gender on the relationship between the presence of depressive symptoms and physical aggressive behaviors. *p < 0.05 Results from logistic regression models with the presence of depressive symptoms as the dependant variable and physical aggressive behaviors as the independent variable. Models were adjusted on age, alcohol use, cannabis use, repeat school years, sexual abuse, mother’s educational level, family situation and the presence of other antisocial behaviors
After adjusting for confounding variables, the odds-ratio between depressive symptoms and physical aggressive behaviors was around 1.4. This relationship was stronger for girls than for boys in presence of clinically significant levels of depressive symptoms, but did not differ between the genders in the case of subthreshold levels of depressive symptoms.
Girls with severe depressive symptoms were more likely to present physical aggressive behaviors than boys. Future studies will be needed to explore the role of irritability in these differences.
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Below: Conceptual model of relationships among race/ethnic marginalization, socioemotional distress, and substance use with student gender, race/ethnicity, and schoolwide race/ethnic diversity as moderators.
We investigated the links between race/ethnic marginalization (i.e., having few same-race/ethnic peers at school) and adolescents’ socioemotional distress and subsequent substance use (alcohol and marijuana) initiation and use. Data from 7,731 adolescents (52% females; 55% White, 21% African American, 16% Latino, 8% Asian American) were drawn from the National Longitudinal Study of Adolescent to Adult Health (Add Health). In our path analysis model, we found that adolescents who were racial/ethnically marginalized at school (i.e., who had less than 15% same-ethnic peers) reported poorer school attachment, which was linked to greater depressive symptoms. More depressive symptoms were associated with higher levels of subsequent marijuana and alcohol use. These relationships showed some variation by students’ gender, race/ethnicity, and age. Findings suggest that the influence of school demographics extends beyond the academic domain into the health and well-being of young people.
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