A Map of Ecodevelopmental Influences on Distinctive Profiles of Substance Use By Urban American Indian Youth

PURPOSE:  The majority of American Indians (AI) now live in urban areas, but rigorous research is lacking on the social determinants of this population’s vulnerability to and resilience against substance use.  This paper describes how distinctive substance use patterns of urban AI youth are related to multi-level ecodevelopmental influences.

METHODS:  Data come from 2,407 urban AI youth in the 2012 Arizona Youth Survey, a state-wide survey of 8^th, 10^th, and 12^th grade students. Eight dichotomized last 30-day substance use measures (alcohol, binge drinking, tobacco, inhalants, marijuana, other illicit drugs, prescription misuse, OTC misuse) were employed in an Mplus latent class analysis (LCA) that also tested for equality of means across 22 scales measuring positive and negative influences of families, peers, schools and neighborhoods.

RESULTS: The LCA supported a 4-class solution: (1) non-users of all substances (69%); (2) users of tobacco and marijuana but not alcohol (4%); (3) “gateway” users (alcohol, cigarettes, marijuana, usually at least two in combination) (17%); and (4) polysubstance users who combined use of four or more “gateway” and other illicit drugs (6%). There were significant mean differences across the classes on 21 ecodevelopmental measures (all except peer approval of prosocial behavior). The general pattern was that the non-user class reported the highest scores on positive influences (e.g. positive family communication, peer prosocial behavior, positive teacher interactions, neighborhood attachment) and lowest scores on negative influences (e.g., adult substance abuse in family, involvement with antisocial peers, neighborhood drug availability), while polysubstance users scored lowest on positive and highest on negative influences.  In pairwise tests the non-user class reported more desirable scores than each of the other classes on both positive and negative influences, while differences among the three substance-using classes were generally limited to negative rather than positive influences. 

CONCLUSION: These findings add to scientific knowledge of the epidemiology of substance use among urban AI adolescents by pinpointing substance use vulnerability and resilience. The latent class using substances other than alcohol is distinctive in this population; compared to other urban AI substance using youth, they reported less exposure to negative ecodevelopmental influences. The polysubstance users were more acutely vulnerable to these negative influences. Knowledge of how to strengthen positive family, peer and school influences on urban AI youth and prevent, counter, or buffer key negative influences can inform family and school interventions and help reduce substance use related health disparities impacting urban AI families.