Neighborhood Influences on Adolescent Behavioral Problems: The Moderating Role of Gender

Background:

A growing body of empirical and theoretical studies has suggested that neighborhood factors are substantially associated with adolescent problematic behaviors (Arcaya, Tucker-Seeley, Kim, Schnake-Mahl, So, & Subramanian, 2016). Meanwhile, neighborhood influences may affect individual behavioral problems differently for boys and girls because of the difference in exposures to neighborhoods between genders. To better understand the mechanisms of neighborhood influences and adolescent internalizing and externalizing symptoms, this study examined gender as a moderator of such relationships.

Methods:

The present study used data from the age 9 and age 15 restricted files of the Fragile Family Child Wellbeing Study (FFCWS; N=3,411). Neighborhood structural factors were measured at children’s age 9 by three indexes: economic disadvantage, residential instability, and ethnic heterogeneity. Two latent neighborhood process factors, social cohesion and social control, were measured at age 9 using two subscales in the FFCWS: The Informal Social Control Scale and the Social Cohesion and Trust Scale. Internalizing and externalizing symptoms were measured by the Child’s Behavioral Checklist (CBCL) at age 15. The focal children’s gender was measured at birth (0 = male, 1 = female). Multigroup structural equation modeling was conducted using Mplus 8.0 (Muthen & Muthen, 2015). Missing data were handled using full maximum likelihood.

Results:

The model fit indexes suggested a good model fit: RMSEA = .03, CFI = .95, and SRMR = .06. Results indicate that gender differences existed in terms of the influences of neighborhood factors on adolescent behavioral problems. Higher neighborhood social cohesion significantly predicted lower levels of both internalizing and externalizing symptoms for boys but not for girls (boys’ internalizing symptoms: b= -.10, p = .02; boys’ externalizing symptoms: b = -.10, p = .02; girls’ internalizing symptoms: b = -.02, p = .60; girls’ externalizing symptoms: b = -.04, p = .43). Living in neighborhoods with high levels of residential instability predicted higher levels of internalizing symptoms only for girls but not boys (girls’ internalizing symptoms: b = .08, p = .005; boys’ internalizing symptoms: b = .04, p = .10).

Conclusion:

This study examined whether different types of neighborhood factors were associated with adolescent internalizing and externalizing symptoms and gender differences in this process. Using data from adolescents in at-risk families, different types of neighborhood factors predicted different adolescent internalizing and externalizing symptoms and gender moderated the influences of residential instability and social cohesion, which contributed to neighborhood research by addressing gender differences. Findings of this study contribute to the current literature by capturing the influences of gender and different types of neighborhood factors and the moderating effects of these two factors on adolescent behavioral problems, which provides critical insights for practitioners at both micro and macro levels. Prevention programs that build a supportive and closely connected neighborhood environment can significantly improve the social cohesion of communities, which can directly decrease internalizing and externalizing symptoms among boys living in these communities.