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Journal Article

Citation

Green KM, Musci RJ, Johnson RM, Matson PA, Reboussin BA, Ialongo NS. Addict. Behav. 2016; 53: 155-160.

Copyright

(Copyright © 2016, Elsevier Publishing)

DOI

10.1016/j.addbeh.2015.10.014

PMID

unavailable

Abstract

OBJECTIVE
This study identifies and compares outcomes in young adulthood associated with longitudinal patterns of alcohol and marijuana use during adolescence among urban youth.
Method
Data come from a cohort of 678 urban, predominantly Black children followed from ages 6-25 (1993-2012). Analyses are based on the 608 children who participated over time (53.6% male). Longitudinal patterning of alcohol and marijuana use were based on annual frequency reports from grades 8-12 and estimated through latent profile analysis.
Results
We identified four classes of alcohol and marijuana use including Non-Use (47%), Moderate Alcohol Use (28%), Moderate Alcohol/Increasing Marijuana Use (12%) and High Dual Use (13%). A marijuana only class was not identified. Analyses show negative outcomes in adulthood associated with all three adolescent substance use classes. Compared to the non-use class, all use classes had statistically significantly higher rates of substance dependence. Those in the 'High Dual Use' class had the lowest rate of high school graduation. Comparing classes with similar alcohol but different marijuana patterns, the 'Moderate Alcohol/Increasing Marijuana Use' class had a statistically significant increased risk of having a criminal justice record and developing substance use dependence in adulthood.
Conclusion
Among urban youth, heterogeneous patterns of alcohol and marijuana use across adolescence are evident, and these patterns are associated with distinct outcomes in adulthood. These findings suggest a need for targeted education and intervention efforts to address the needs of youth using both marijuana and alcohol, as well as the importance of universal early preventive intervention efforts.


Language: en

Keywords

African Americans; Blacks; Cannabis; Longitudinal latent profile analysis; Longitudinal patterns; Substance use effects

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