The influence of age and gender on the likelihood of endorsing cannabis abuse/dependence criteria

Monique J. Delforterie, Hanneke E. Creemers, Arpana Agrawal, Michael T. Lynskey, Suzanne Jak, Anja C. Huizink

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


Introduction: Higher prevalence rates of cannabis abuse/dependence and abuse/dependence criteria in 18-24. year old versus older cannabis users and in males versus females might reflect true differences in the prevalence of these disorders across age and gender or, alternatively, they could arise from age- and gender-related measurement bias. To understand differences in endorsement across important subgroups, we examined the influence of age and gender simultaneously on the likelihood of endorsement of the various abuse/dependence criteria. Method: The sample consisted of 1603 adult past year cannabis users participating in the National Epidemiological Survey on Alcohol and Related Conditions (NESARC), a U.S. population study (39.6% aged 18-24; 62.1% male). Past year DSM-IV cannabis abuse/dependence criteria and withdrawal were assessed with the AUDADIS-IV. A restricted factor analysis with latent moderated structures was used to detect measurement bias. Results: Although cannabis abuse and dependence diagnoses and various individual abuse/dependence criteria showed different prevalence rates across younger and older male and female cannabis users, none of the items showed uniform or non-uniform measurement bias with respect to age or gender. Conclusion: The results indicate that, although prevalence rates of cannabis abuse/dependence criteria differ across age and gender, past year abuse/dependence criteria function similarly across these groups. It can thus be concluded that the criteria are applicable to younger and older, as well as male and female, adult cannabis users.

Original languageEnglish
Pages (from-to)172-175
Number of pages4
JournalAddictive Behaviors
StatePublished - Mar 1 2015


  • Age
  • Cannabis abuse/dependence
  • DSM-IV
  • Factor analysis
  • Gender
  • Measurement bias


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