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Abstract

Aim
The present study examined patterns and correlates of polysubstance use among individuals with severe alcohol use disorder (AUD).


Methods
Participants were 2785 individuals (63% female; mean age = 43 years, range = 18–78 years) from the Genes, Addiction and Personality Study. All participants met lifetime criteria for severe AUD (6+ symptoms). We used latent class analysis to identify patterns of frequency of lifetime use for cigarettes, marijuana, cocaine, stimulants, sedatives, opioids and hallucinogens. A variety of demographic and behavioral correlates of latent class membership were tested in univariable and multivariable models.


Results
A five-class solution was selected: extended range polysubstance use (24.5%); cigarette and marijuana use (18.8%); 'testers,' characterized by high probabilities of smoking 100 or more cigarettes, using marijuana 6+ times, and trying the remaining substances 1–5 times (12.3%); moderate range polysubstance use (17.1%) and minimal use (reference class; 27.3%). In univariable analyses, all potential correlates were related to latent class membership. In the multivariable model, associations with gender, race/ethnicity, age of onset for alcohol problems, dimensions of impulsivity, depressive symptoms, antisocial behavior and family history density of alcohol problems remained significant, though the pattern and strength of associations differed across classes. For instance, sensation-seeking, lack of premeditation and family history were uniquely associated with membership in the extended range polysubstance use class.


Conclusion
Patterns of polysubstance use are differentially related to demographic and behavioral factors among individuals with severe AUD. Assessing use across multiple substances may inform the selection of targets for treatment and prevention.

The relationship between the genetic and environmental risk factors for alcohol use disorders (AUD) detected in Swedish medical, pharmacy, and criminal registries has not been hitherto examined. Prior twin studies have varied with regard to the detection of shared environmental effects and sex differences in the etiology of AUD. In this report, structural equation modeling in OpenMx was applied to (1) the three types of alcohol registration in a population-based sample of male–male twins and reared-together full and half siblings (total 208,810 pairs), and (2) AUD, as a single diagnosis, in male–male, female–female, and opposite-sex (OS) twins and reared-together full and half siblings (total 787,916 pairs). An independent pathway model fit best to the three forms of registration and indicated that between 70% and 92% of the genetic and 63% and 98% of the shared environmental effects were shared in common with the remainder unique to each form of AUD registration. Criminal registration had the largest proportion of unique genetic and environmental factors. The best fit model for AUD estimated the heritability to be 22% and 57%, respectively, in females and males. Both shared (12% vs. 6%) and special twin environment (29% vs. 2%) were substantially more important in females versus males. In conclusion, AUD ascertained from medical, pharmacy, and criminal Swedish registries largely share the same genetic and environmental risk factors. Large sex differences in the etiology of AUD were seen in this sample, with substantially stronger familial environmental and weaker genetic effects in females versus males.

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use.