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Examining the heterogeneity of polysubstance use patterns in young adulthood by age and college attendance.

Angela K StevensRachel L GunnAlexander W SokolovskySuzanne M ColbyKristina M Jackson
Published in: Experimental and clinical psychopharmacology (2021)
Substance use in young adulthood and polysubstance users (PSU), in particular, pose unique risks for adverse consequences. Prior research on young adult PSU has identified multiple classes of users, but most work has focused on college students. We examined PSU patterns by age and college attendance during young adulthood in two nationally representative samples. Using National Epidemiological Survey on Alcohol and Related Conditions (NESARC) Wave 1 and NESARC-III data sets, multigroup latent class analysis (MG-LCA) was employed to examine PSU patterns based on age (18-24 vs. 25-34) and determine whether solutions were similar (i.e., statistically invariant) by college attendance/graduation. Classes were estimated by binary past-year use of sedatives, tranquilizers, opioids/painkillers, heroin, amphetamines/stimulants, cocaine, hallucinogens, club drugs, and inhalants, and past-year frequency of alcohol, cigarette, and cannabis use. PSU patterns are largely replicated across waves. Model fit supported 3-class solutions in each MG-LCA: Low frequency-limited-range PSU (alcohol, cigarettes, and cannabis only), medium-to-high frequency limited-range PSU (alcohol, cigarettes, and cannabis only), and extended-range PSU (ER PSU; all substances). Apart from one model, MG-LCA solutions were not invariant by college attendance/graduation, suggesting important differences between these groups. Except for alcohol, cannabis, and cigarette use frequency, results showed that probabilities of illicit and prescription drug use declined in the older age group. Findings also supported examining college and noncollege youth separately when studying PSU. ER PSU may be uniquely vulnerable to coingesting substances, particularly for nongraduates, warranting future research to classify patterns of simultaneous PSU and identify predictors and consequences of high-risk combinations (e.g., alcohol and opioids). (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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