Dataset Information

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

ABSTRACT: 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?

SUBMITTER: Lanza HI

PROVIDER: S-EPMC7539114 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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

Lanza H Isabella HI Barrington-Trimis Jessica L JL McConnell Rob R Cho Junhan J Braymiller Jessica L JL Krueger Evan A EA Leventhal Adam M AM

JAMA network open 20201001 10

<h4>Importance</h4>Little is known about cannabis vaping trajectories across adolescence and young adulthood or the co-occurrence with nicotine vaping.<h4>Objective</h4>To evaluate nicotine vaping and cannabis vaping trajectories from late adolescence to young adulthood (≥18 years of age) and the extent of polysubstance vaping.<h4>Design, setting, and participants</h4>In this prospective cohort study, 5 surveys (including information on substance vaped) were completed at 10 high schools in the L ...[more]

PMID: 33021651

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Project description:ImportanceRates of e-cigarette use (ie, nicotine vaping) and cannabis vaping continue to increase among youth and young adults. However, the association of nicotine and cannabis vaping with independent respiratory health outcomes has not been well studied.ObjectiveTo investigate associations of nicotine and cannabis vaping with bronchitic symptoms, wheeze, and shortness of breath.Design, setting, and participantsCross-sectional survey data on self-reported lifetime, 6-month, and 30-day vaping from 2553 young adults recruited from high schools in Southern California were collected from June 2018 to October 2019. Of these participants, 94% provided data for shortness of breath and wheeze, and 86% provided data for chronic bronchitis.Main outcomes and measuresSelf-reported nicotine and cannabis vaping were measured on a Likert-type scale using the following responses: (1) never used, (2) lifetime but no past 6-month use, (3) past 6-month use but no use in the past 30 days, (4) use on 1 or 2 of the past 30 days, and (5) use on 3 or more of the past 30 days. Three respiratory health outcomes were assessed separately on the basis of self-reported symptoms: bronchitic symptoms in the previous 12 months (ie, daily cough for 3 months in a row, congestion or phlegm other than with a cold, and/or bronchitis), wheeze in the previous 12 months, and shortness of breath when hurrying on level ground or walking up a slight hill.ResultsOf 2553 participants in the analytic sample (mean [SD] age, 19.3 [0.79] years; 1477 [57.9%] female individuals), 1095 of 2553 young adults (42.9%) reported vaping nicotine and 939 of 2553 (38.4%) reported vaping cannabis. Compared with those who never vaped cannabis, individuals who vaped cannabis in their lifetime but not in the past 60 months (204 of 2553 [8.4%]; adjusted odds ratio [aOR], 1.83 [95% CI, 1.08-3.10]), in the past 6 months but not in the last 30 days (490 of 2443 [20.1%]; aOR, 1.58 [95% CI, 1.02-2.46]), 1-2 days in the past 30 days (90 of 2443 [3.7%]; aOR, 2.83 [95% CI, 1.46-5.50]), and 3 or more days in the past 30 days (155 of 2443 [6.3%]; aOR, 2.14 [95% CI, 1.16-3.92]) had significantly higher odds of chronic bronchitic symptoms after adjusting for nicotine vaping, cigarette smoking, cannabis smoking, and sociodemographic characteristics. Cannabis vaping 3 or more times in the last 30 days was also associated with increased odds of wheeze (aOR, 2.27 [95% CI, 1.17-4.37]). Associations of cannabis vaping with shortness of breath and nicotine vaping with any respiratory health outcome were not statistically significant in fully adjusted models.Conclusions and relevanceFindings of this cross-sectional study suggest that cannabis vaping is associated with increased risk of bronchitic symptoms and wheeze in young adults. Further research is needed to understand the temporality of the association and the mechanisms underlying the difference between nicotine and cannabis vaping in the risk of bronchitic symptoms and wheeze.

Project description:Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant's alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

Project description:ImportanceCharacterizing patterns of handgun carrying among adolescents and young adults can inform programs to reduce firearm-related harm. Longitudinal patterns of handgun carrying among rural adolescents have not been identified.ObjectivesTo assess specific points of intervention by characterizing patterns of handgun carrying by youths in rural communities from early adolescence to young adulthood and to quantify how age at initiation, duration, and frequency of carrying differ across identified patterns.Design, setting, and participantsThis cohort study uses the control group of the community-randomized trial of the Communities That Care prevention system, conducted among public school students in 12 rural communities across 7 states. Participants self-reported their handgun carrying at 10 data collection points from 12 to 26 years of age (2005-2019). Data were analyzed from January to July 2021.Main outcomes and measuresHandgun carrying in the past 12 months. Latent class growth analysis was used to estimate handgun carrying trajectories.ResultsIn this longitudinal rural sample of 2002 students, 1040 (51.9%) were male; 532 (26.6%) were Hispanic, Latino, Latina, or Latinx; 1310 (65.4%) were White; and the highest level of educational attainment of either parent was a high school degree or less for 649 students (32.4%). The prevalence of handgun carrying in the last 12 months ranged from 5.3% (95 of 1795) to 7.4% (146 of 1969) in adolescence and increased during the mid-20s (range, 8.9% [154 of 1722] to 10.9% [185 of 1704] from 23 to 26 years of age). Among the participants who reported handgun carrying at least once between 12 and 26 years of age (n = 601 [30.0%]), 320 (53.2%) reported carrying a handgun in only 1 wave. Latent class growth analysis indicated 6 longitudinal trajectories: never or low probability of carrying (1590 [79.4%]), emerging adulthood carrying (166 [8.3%]), steadily increasing carrying (163 [8.1%]), adolescent carrying (53 [2.6%]), declining carrying (24 [1.2%]), and high probability and persistent carrying (6 [0.3%]). The earliest mean (SD) age at initiation of handgun carrying occurred in both the adolescent and declining carrying groups at the ages of 12.6 (0.9) and 12.5 (0.7) years, respectively. More than 20% of some groups (emerging adulthood [age 26 years: 49 of 154 (31.8%)], steadily increasing [age 26 years: 37 of 131 (28.2%)], declining [age 13 years: 7 of 23 (30.4%)], and high probability and persistent carrying [age 15 years: 3 of 6 (50.0%)]) reported carrying 40 times or more in the past year by the age of 26 years.Conclusions and relevanceThis study found distinct patterns of handgun carrying from adolescence to young adulthood in rural settings. Findings suggest that promoting handgun safety in rural areas should start early. Potential high-risk trajectories, including carrying at high frequencies, should be the focus of future work to explore the antecedents and consequences of handgun carrying in rural areas.

Dataset Information

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

Publications

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

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