Abstract
Little is known about cannabis vaping trajectories across adolescence and young adulthood or the co-occurrence with nicotine vaping. To evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to young adulthood (≥18 years of age) and the extent of polysubstance vaping. In this prospective cohort study, 5 surveys (including information on substance vaped) were completed at 10 high schools in the Los Angeles, California, metro area. Students were surveyed at 6-month intervals from fall of 11th grade (October to December 2015; wave 5) through spring of 12th grade (March to June 2017; wave 8) and again approximately 1 to 2 years after high school (October 2018 to October 2019; wave 9). Past 30-day nicotine and cannabis vaping frequency across 5 waves. Self-reported frequency of nicotine vaping and cannabis vaping within the past 30 days across 5 time points from late adolescence to young adulthood. Trajectories were measured with these past 30-day use frequencies at each wave. Parallel growth mixture modeling estimated conditional probabilities of polysubstance vaping. The analytic sample included 3322 participants with at least 1 time point of data (mean [SD] age, 16.50 [0.42] years at baseline; 1777 [53.5%] female; 1573 [47.4%] Hispanic or Latino). Growth mixture modeling identified the 5-trajectory model as optimal for both nicotine vaping and cannabis vaping. Trajectories for nicotine and cannabis vaping were similar (nonusers: 2246 [67.6%] nicotine, 2157 [64.9%] cannabis; infrequent users: 566 [17.0%] nicotine, 608 [18.3%] cannabis; moderate users: 167 [5.0%] nicotine, 233 [7.0%] cannabis; young adult-onset frequent users: 213 [6.4%] nicotine, 190 [5.7%] cannabis; adolescent-onset escalating frequent users: 131 [3.9%] nicotine, 134 [4.0%] cannabis). Males had greater odds of belonging to the adolescent-onset escalating frequent users nicotine (adjusted odds ratio, 2.88; 95% CI, 1.58-5.23; P < .01) and cannabis (adjusted odds ratio, 1.95; 95% CI,1.03-3.66; P < .05) vaping trajectories compared with nonusers. Polysubstance vaping was common, with those in trajectories reflecting more frequent nicotine vaping (adolescent-onset escalating frequent users and young adult-onset frequent users) having a high probability of membership (85% and 93%, respectively) in a cannabis-use trajectory. In this cohort study, the prevalence and type of nicotine vaping and cannabis vaping developmental trajectories from late adolescence to young adulthood were similar. Polysubstance vaping was common from late adolescence to young adulthood, particularly among those reporting more frequent vaping use. The findings suggest that public health policy and clinical interventions should address polysubstance vaping in both adolescence and young adulthood.
Highlights
The prevalence of electronic vaporizer use among US adolescents and young adults has substantially increased
Males had greater odds of belonging to the adolescent-onset escalating frequent users nicotine and cannabis vaping trajectories compared with nonusers
Polysubstance vaping was common from late adolescence to young adulthood, among those reporting more frequent vaping use
Summary
The prevalence of electronic vaporizer use among US adolescents and young adults has substantially increased. Growth mixture modeling (GMM) is a data-driven analytic approach for identifying unobserved subpopulations and describing distinct longitudinal change.[6,7] This approach has been applied to identify youth trajectories of combustible cigarette, alcohol, and cannabis use.[8,9,10] to date, only 2 longitudinal studies have sought to identify trajectories of nicotine vaping. Westling et al[12] reported 2 trajectories of e-cigarette use from 8th to 9th grade: 94.8% infrequent or no use and 5.1% accelerated use. Both studies indicated that membership in e-cigarette-using trajectories was associated with other substance use
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