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Journal Article

Citation

Guttmannova K, Calhoun BH, Duckworth JC, Martinez G, Fleming CB, Patrick ME, Lee CM. Addict. Behav. 2023; 150: e107909.

Copyright

(Copyright © 2023, Elsevier Publishing)

DOI

10.1016/j.addbeh.2023.107909

PMID

37992453

Abstract

OBJECTIVE: We examined age-varying associations between young adult simultaneous alcohol and marijuana/cannabis use (SAM) and heavy episodic drinking (HED) and positive and negative affect to inform harm reduction efforts.

METHODS: Young adults reporting past-year alcohol use (n = 556; ages 19-25) were recruited in a state where alcohol and nonmedical cannabis use was legal for those 21 +. Participants provided 24 repeated monthly assessments. Among those reporting past-month cannabis use on at least one survey, logistic time-varying effect models estimated (1) the age-varying prevalence of and associations between past-month SAM and HED and (2) age-varying unique associations of affect with SAM and HED.

RESULTS: There was a positive age-varying association between HED and SAM over time that was highest at age 19 (OR = 7.56), decreased until age 20.7 (OR = 3.39), increased until age 23.0 (OR = 4.85), and decreased until the association became non-significant by age 25. Negative affect was positively associated with SAM from ages 20.7 to 23.0, peaking at age 21.8 (OR = 1.36). Positive affect was positively associated with HED from ages 19.4 to 20.4 (peak OR = 1.25) and ages 22.5 to 24.5 (peak OR = 1.38). In contrast, positive affect was not uniquely associated with SAM nor negative affect with HED across ages 19-25.

CONCLUSIONS: While HED and SAM were positively associated throughout young adulthood and interventions could target them in tandem, their associations with affect suggest differential etiologic processes. Preventive intervention and harm reduction efforts should attend to psychological context in which these behaviors occur.


Language: en

Keywords

Young adults; Heavy episodic drinking; Negative affect; Positive affect; Simultaneous alcohol and cannabis use; Time-varying effects modeling

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