Two-part models identifying predictors of cigarette, e-cigarette, and cannabis use and change in use over time among young adults in the US

Authors

Yan Wang, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Katelyn F. Romm, TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
Mark C. Edberg, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Jeffrey B. Bingenheimer, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Cassidy R. LoParco, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Yuxian Cui, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.
Carla J. Berg, Department of Prevention and Community Health, Milken Institute School of Public Health, George Washington University, Washington, District of Columbia, USA.

Document Type

Journal Article

Publication Date

4-29-2024

Journal

The American journal on addictions

DOI

10.1111/ajad.13569

Abstract

BACKGROUND AND OBJECTIVES: Limited longitudinal research has examined differential interpersonal and intrapersonal correlates of young adult use and use frequency of cigarettes, e-cigarettes, and cannabis. This study aimed to address these limitations. METHODS: We analyzed five waves of longitudinal data (2018-2020) among 3006 US young adults (M = 24.55, 44% male, 32% sexual minority, ~30% racial/ethnic minority). Two-part latent growth models examined likelihood of past-month cigarette, e-cigarette, and cannabis use (binary part) and days used (continuous part) and identified predictors (depressive symptoms, personality traits, adverse childhood experiences [ACEs], parental use) of baseline use and changes over time. RESULTS: Regarding baseline past-month use (27% cigarettes, 38% e-cigarettes, 39% cannabis), depressive symptoms, ACEs, and parental substance use predicted use outcomes (i.e., likelihood, frequency) for each product; extraversion predicted cigarette and e-cigarette use outcomes; openness predicted e-cigarette and cannabis use outcomes; conscientiousness negatively predicted cigarette and cannabis use outcomes; and agreeableness negatively predicted cannabis use frequency. Regarding longitudinal changes, conscientiousness predicted accelerated increase of cigarette use frequency at later timepoints; depressive symptoms predicted increases in likelihood of e-cigarette use but the association weakened over time; and parental cannabis use predicted decreased cannabis use frequency but the association weakened over time. DISCUSSION AND CONCLUSIONS: Young adult substance use interventions should target high-risk subgroups and focus on distinct factors impacting use, including chronic, escalating, and decreasing use. SCIENTIFIC SIGNIFICANCE: This study advances the literature regarding distinct predictors of different substance use outcomes and provides unique data to inform interventions targeting young adult cigarette, e-cigarette, and cannabis use.

APA Citation

Wang, Yan; Romm, Katelyn F.; Edberg, Mark C.; Bingenheimer, Jeffrey B.; LoParco, Cassidy R.; Cui, Yuxian; and Berg, Carla J., "Two-part models identifying predictors of cigarette, e-cigarette, and cannabis use and change in use over time among young adults in the US" (2024). GW Authored Works. Paper 4663.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/4663

Department

Prevention and Community Health