Chenshu Zhang1, Judith S Brook1, Carl G Leukefeld2, David W Brook1. 1. Department of Psychiatry, New York University School of Medicine, New York City, New York. 2. Department of Behavioral Sciences, University of Kentucky, Lexington, Kentucky.
Abstract
OBJECTIVES: To study the degree to which individuals in different trajectories of marijuana use are similar or different in terms of unemployment status at mean age 43. METHODS: We gathered longitudinal data on a prospective cohort taken from a community sample (N = 548). Forty-nine percent of the original participants were females. Over 90% of the participants were white. The participants were followed from adolescence to early midlife. The mean ages of participants at the follow-up interviews were 14.1, 16.3, 22.3, 27.0, 31.9, 36.6, and 43.0, respectively. We used the growth mixture modeling (GMM) approach to identify the trajectories of marijuana use over a 29-year period. RESULTS: Five trajectories of marijuana use were identified: chronic users/decreasers (8.3%), quitters (18.6%), increasing users (7.3%), chronic occasional users (25.6%), and nonusers/experimenters (40.2%). Compared with nonusers/experimenters, chronic users/decreasers had a significantly higher likelihood of unemployment at mean age 43 (adjusted odds ratio = 3.51, 95% confidence interval = 1.13-10.91), even after controlling for the covariates. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: The results of the associations between the distinct trajectories of marijuana use and unemployment in early midlife indicate that it is important to develop intervention programs targeting chronic marijuana use as well as unemployment in individuals at this stage of development. Results from this study should encourage clinicians, teachers, and parents to assess and treat chronic marijuana use in adolescents.
OBJECTIVES: To study the degree to which individuals in different trajectories of marijuana use are similar or different in terms of unemployment status at mean age 43. METHODS: We gathered longitudinal data on a prospective cohort taken from a community sample (N = 548). Forty-nine percent of the original participants were females. Over 90% of the participants were white. The participants were followed from adolescence to early midlife. The mean ages of participants at the follow-up interviews were 14.1, 16.3, 22.3, 27.0, 31.9, 36.6, and 43.0, respectively. We used the growth mixture modeling (GMM) approach to identify the trajectories of marijuana use over a 29-year period. RESULTS: Five trajectories of marijuana use were identified: chronic users/decreasers (8.3%), quitters (18.6%), increasing users (7.3%), chronic occasional users (25.6%), and nonusers/experimenters (40.2%). Compared with nonusers/experimenters, chronic users/decreasers had a significantly higher likelihood of unemployment at mean age 43 (adjusted odds ratio = 3.51, 95% confidence interval = 1.13-10.91), even after controlling for the covariates. CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: The results of the associations between the distinct trajectories of marijuana use and unemployment in early midlife indicate that it is important to develop intervention programs targeting chronic marijuana use as well as unemployment in individuals at this stage of development. Results from this study should encourage clinicians, teachers, and parents to assess and treat chronic marijuana use in adolescents.
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