Abstract: Using Latent Variable Interaction Modeling to Understand Ecodevelopmental Influences on Substance Use for Urban American Indian Adolescents (Society for Prevention Research 24th Annual Meeting)

111 Using Latent Variable Interaction Modeling to Understand Ecodevelopmental Influences on Substance Use for Urban American Indian Adolescents

Schedule:
Wednesday, June 1, 2016
Bayview A (Hyatt Regency San Francisco)
* noted as presenting author
Stephanie Ayers, PhD, Associate Director of Research and Research Faculty, Arizona State University, Phoenix, AZ
Justin Jager, PhD, Assistant Professor, Arizona State University, Tempe, AZ
Stephen S. Kulis, PhD, Cowden Distinguished Professor of Sociology, Arizona State University, Phoenix, AZ
Most American Indian (AI) families now live in urban areas, but rigorous research is lacking on the social determinants of their health. Urban AI youth report higher rates, earlier initiation, and more severe consequences of substance use than their non-AI counterparts. Family disruptions, stresses related to moving, and difficulties in establishing and sustaining social and cultural connections are frequently mentioned as contributing to adverse health outcomes for urban AI youth. Ecodevelopmental theory is useful for understanding how peer, family, school, and neighborhood levels interact to influence substance use among urban AI youth.  This presentation examines, through latent variable interaction modeling, the complex ways that peers and families influence substance use (alcohol, cigarette, and marijuana) among urban AI youth. Data come from the 2012 Arizona Youth Survey, a state-wide self-report survey of 8th, 10th, and 12th grade students, which includes 2,407 urban AI youth. Using Mplus, confirmatory factor analysis (CFA) and structural equation modeling (SEM) tested the direct and interaction effects of last 30-day alcohol, cigarette and marijuana use.  The CFA results comprised four latent variables: two negative influences- substance users in the family and associations with anti-social peers; and, two positive influences- supportive family environment and involvement with pro-social peers (X2= 235.8 (34), p<.001; RMSEA=.05; CFI=.95). For each substance, three SEM models were examined: (1) direct effects only; (2) a model including latent variable interactions for substance users in the family X supportive family environment and substance users in the family X involvement with pro-social peers; and (3) a model including latent variable interactions for associations with anti-social peers X supportive family environment and associations with anti-social peers X involvement with pro-social peers.  The SEM results showed significant direct effects for only the negative latent constructs of family and peers, which significantly increased substance use. When latent variable interactions were included, the positive influences - supportive family environment and involvement with pro-social peers - significantly buffered the negative latent effects on substance use.  The emerging patterns and relationships between ecodevelopmental factors on substance use help to identify issues that urban AI youth face when navigating within larger socio-environmental contexts that influence the youth’s vulnerability to health disparities. Understanding possible moderators can be useful in designing and delivering strengths-based prevention programs that enhance health and wellbeing of urban AI youth.