Citation

Dash GF, Gizer IR, Slutske WS. Drug Alcohol Depend. Rep. 2022; 5: e100123.

Copyright

(Copyright © 2022, Elsevier Publishing)

DOI

10.1016/j.dadr.2022.100123

PMID

36591566

PMCID

PMC9802645

Abstract

BACKGROUND: Prescription opioid misuse (POM) is often implicated in heroin initiation, despite evidence that POM does not predict heroin initiation any better than other drug use. Additionally, prescription misuse and illicit use behaviors tend to respectively "cluster" together. This study aimed to test a series of theory-driven factor models to explore how POM and heroin use are situated within the broader constellation of drug use that typically occurs alongside opioid (mis)use.

METHODS: 36,309 individuals from NESARC-III (56.31% female; mean age=45.63 [SD=17.53]) reported their lifetime (mis)use of prescription opioids, prescription stimulants, prescription sedatives, heroin, cannabis, cocaine/crack, illicit stimulants (e.g., methamphetamine), club drugs, hallucinogens, and inhalants, and were administered a DSM-5 substance use disorder (SUD) assessment. Bifactor, correlated factors, and one-factor confirmatory factor models were fit using all drug use/SUD variables and subsequently compared.

RESULTS: POM was most strongly correlated with prescription sedative misuse; heroin use was most strongly correlated with cocaine/crack use. All factor models fit the data well. Highly correlated factors and patterns of factor loadings suggested that POM and heroin use were most parsimoniously captured within a general factor alongside all other forms of drug use. This was also the case for SUD. Additional analyses testing an alternate factor structure provided further support for unidimensionality.

CONCLUSIONS: POM and heroin use, as well as prescription- and heroin-based SUDs, were neither separable nor distinctly associated. Future research should account for other drug use more comprehensively rather than isolating POM as a primary risk factor in heroin use and use disorder.

Language: en

Keywords

Structural equation modeling; Drug use; Substance use disorder; Heroin; NESARC; Prescription opioids