Adolescent Sexual Initiation: A Cross-Classified Multilevel Analysis of Peer Group-, School-, and Neighborhood-Level Influences

Abstract

Purpose: This study examines the simultaneous roles of neighborhood, school, and peer group contexts on variation in age of U.S. adolescent sexual initiation (coitarche). All three contexts have been shown to be important determinants of adolescent sexual and reproductive health outcomes but are typically examined separately, leaving a large gap in our understanding of their relative and joint importance. Furthermore, little is known about whether these contexts matter differently for boys and girls.

Methods: Using sociocentric network data from the National Longitudinal Study of Adolescent to Adult Health, we combine gender-stratified analyses, social network community detection (to identify teens' social cliques), and cross-classified multilevel modeling to simultaneously analyze gender, neighborhood, school, and peer group effects. These results are compared against results from traditional multilevel models (MLMs), which analyze the contexts individually.

Results: Evaluated separately in MLM, peer groups accounted for 6.79% of the total variation in coitarche, schools for 3.56%, and neighborhoods for 4.11%. Under simultaneous cross-classified multilevel modeling analysis, a different story emerges: peer groups and schools accounted for 3.66% and 3.19% of the total variation in coitarche, respectively, whereas neighborhood explained only 1.16% of the total variation. Stratified analyses indicate that gender modifies these associations.

Conclusions: Results demonstrate that omitting any one of these contexts may lead to an overestimation of the importance of contexts included in models. When modeled simultaneously with neighborhoods, our findings suggest that peer groups and schools are meaningful contributing contexts to the variance in sexual initiation, and that these contexts matter differently for boys and girls.

Keywords: Contextual effects; Cross-classified multilevel modeling; Gender; Neighborhood effects; Peer measurements; School effects; Sexual and reproductive health; Social networks.