Differentiating heavy cannabis users through latent class analysis

Abstract Background: Daily or near-daily cannabis users vary considerably in their daily dosage and use frequency, impacting both experienced effects and adverse consequences. This study identified heavy cannabis user groups according to consumption patterns and factors associated with class membership. Methods: We conducted a cross-sectional survey of 400 Spanish residents (62.2% male; average age=29.6 years) who had used cannabis ≥3 days/week throughout the past year. Participants were recruited through chain referral and cannabis social clubs. We applied latent class analysis (LCA) to cluster participants according to use intensity. Associations between class membership and socio-demographics, use patterns, motives, supply sources, adverse outcomes, and use of other substances were measured using ANOVA and chi-squared tests. Multinomial regression identified the factors associated with latent class membership. Results: Three latent classes (moderately heavy: 23%, heavy: 67.5%, very heavy: 9.5%) had average weekly cannabis intakes of 2.3, 5.6, and 18.3 grams, respectively. Age, education, years of use, buying cannabis in a club, Cannabis Abuse Screening Test (CAST) scores, and cocaine use were associated with cannabis use intensity. Very heavy users were older ( X 2 =20.44, p <0.01), less educated X 2 =28.92, p <0.001), and had used cannabis for longer ( F =6.80, p =0.001). The prevalence of past-month cocaine use ( X 2 =13.90, p <0.05) and CAST scores ( F =25.73, p <0.001) increased across the classes. Cannabis was usually obtained from a club by very heavy users ( X 2 =24.40, p <0.001). Conclusions : Heavy cannabis users are heterogenous and present several groups according to frequency and quantity of cannabis consumption. Use intensity is associated with increased cannabis use disorders and dependence.