Trajectories of Nicotine and Cannabis Vaping and Polyuse. From Adolescence to Young Adulthood, H. Isabella Lanza, 2020

Trajectories of Nicotine and Cannabis Vaping and Polyuse. From Adolescence to Young Adulthood

H. Isabella Lanza, PhD; Jessica L. Barrington-Trimis, PhD; RobMcConnell, MD; Junhan Cho, PhD; Jessica L. Braymiller, PhD; Evan A. Krueger, PhD, MPH, MSW; Adam M. Leventhal, PhD

JAMA Network Open, 2020, 3, (10), :e2019181.

doi : 10.1001/jamanetworkopen.2020.19181



IMPORTANCE : Little is known about cannabis vaping trajectories across adolescence and young
adulthood or the co-occurrence with nicotine vaping.

OBJECTIVE : To evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to
young adulthood (18 years of age) and the extent of polysubstance vaping.

DESIGN, SETTING, AND PARTICIPANTS : 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).

EXPOSURES : Past 30-day nicotine and cannabis vaping frequency across 5 waves.

MAIN OUTCOMES AND MEASURES : 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.

RESULTS : 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.

CONCLUSIONS AND RELEVANCE : 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.



The prevalence of electronic vaporizer use among US adolescents and young adults has substantially increased. Recent past 30-day estimates indicate marked increases for both nicotine vaping (20.9% to 25.4%among 12th graders from 2018 to 2019; 6.5%to 10.6%among young adults from 2017 to 2018) and cannabis vaping (7.5%to 14.0%% among 12th graders from 2018 to 2019; 6.6%to 9.3% among young adults from 2017 to 2018).1-3 There is a wide distribution in the frequency of past 30-day use among youths, ranging from vaping 1-2 days to daily use4,5; however, the extent to which this wide distribution represents individuals on escalating, deescalating, or stable use trajectories is unclear.

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.8-10 However, to date, only 2 longitudinal studies have sought to identify trajectories of nicotine vaping. Park et al11 identified 3 e-cigarette trajectories from 13 to 17 years of age: never (66.6%), low and increasing (20.1%), and high and increasing (13.3%).Westling et al12 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.

Although Park et al11 andWestling et al12 showed that adolescents can be classified into distinct trajectories of vaping, neither study examined the transition from adolescence to young adulthood. This is a population at high risk because transitions to college and/or the workforce and increased familial and financial responsibility are associated with increased risk of polysubstance use, enduring substance use problems, and substance use disorder.13-16 Furthermore, to our knowledge, developmental trajectories of cannabis vaping have not been identified in adolescence or young adulthood; thus, it is unknown how cannabis vaping develops over time. Examining gender and racial/ethnic differences of nicotine and cannabis vaping trajectories is also warranted because there is some evidence that males are more likely to vape than females17,18; racial/ethnic differences are less clear.19,20 In addition, although cross-sectional studies have reported high rates of nicotine and cannabis vaping polyuse among adolescents and young adults,21-24 to our knowledge, no longitudinal study has examined co-occurring development of nicotine and cannabis vaping trajectories.

Identifying common polysubstance vaping patterns may inform both nicotine and cannabis policy and prevention. Using a prospective longitudinal design following a cohort of adolescents through young adulthood (18 years of age), the current study evaluated nicotine and cannabis vaping trajectories, demographic covariates of trajectories, and co-occurrence of nicotine and cannabis vaping trajectories.