Skip to main content

Advertisement

Log in

Does Marijuana Use at Ages 16–18 Predict Initiation of Daily Cigarette Smoking in Late Adolescence and Early Adulthood? A Propensity Score Analysis of Add Health Data

  • Published:
Prevention Science Aims and scope Submit manuscript

Abstract

Given the declining trend in adolescent cigarette smoking and increase in general access to marijuana, it is important to examine whether marijuana use in adolescence is a risk factor for subsequent cigarette smoking in late adolescence and early adulthood. Preliminary evidence from a very small number of studies suggests that marijuana use during adolescence is associated with later smoking; however, to control confounding, previously published studies used regression adjustment, which is susceptible to extrapolation when the confounder distributions differ between adolescent marijuana users and non-users. The current study uses propensity score weighting, a causal inference method not previously used in this area of research, to weight participants based on their estimated probability of exposure given confounders (the propensity score) to balance observed confounders between marijuana users and non-users. The sample consists of participants of Add Health (a nationally representative dataset of youth followed into adulthood) who were 16–18, with no history of daily cigarette smoking at baseline (n = 2928 for female and 2731 for male sub-samples). We assessed the effect of adolescent marijuana use (exposure, ascertained at wave 1) on any daily cigarette smoking during the subsequent 13 years (outcome, ascertained at wave 4). Analyses suggest that for females (but not males) who used marijuana in adolescence, marijuana use increased the risk for subsequent daily smoking: OR = 1.71, 95% CI = (1.13, 2.59). We recommend that adolescent marijuana use be viewed as a possible risk factor for subsequent initiation of daily cigarette smoking in women.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  • Agrawal, A., Budney, A. J., & Lynskey, M. T. (2012). The co-occurring use and misuse of cannabis and tobacco: A review. Addiction, 107(7), 1221–1233.

    Article  PubMed  PubMed Central  Google Scholar 

  • Agrawal, A., & Lynskey, M. T. (2009). Tobacco and cannabis co-occurrence: Does route of administration matter? Drug and Alcohol Dependence, 99(1–3), 240–247.

    Article  CAS  PubMed  Google Scholar 

  • Agrawal, A., Scherrer, J. F., Lynskey, M. T., Sartor, C. E., Grant, J. D., Haber, J. R., et al. (2011). Patterns of use, sequence of onsets and correlates of tobacco and cannabis. Addictive Behaviors, 36(12), 1141–1147.

    Article  PubMed  PubMed Central  Google Scholar 

  • Azofeifa, A., Mattson, M. E., Schauer, G., McAfee, T., Grant, A., & Lyerla, R. (2016). National estimates of marijuana use and related indicators — National Survey on drug use and health, United States, 2002-2014. Morbidity and Mortality Weekly Report, 65(11).

  • Badiani, A., Boden, J. M., De Pirro, S., Fergusson, D. M., Horwood, L. J., & Harold, G. T. (2015). Tobacco smoking and cannabis use in a longitudinal birth cohort: Evidence of reciprocal causal relationships. Drug and Alcohol Dependence, 150, 69–76.

    Article  PubMed  Google Scholar 

  • Brook, J. S., Lee, J. Y., & Brook, D. W. (2015). Trajectories of marijuana use beginning in adolescence predict tobacco dependence in adulthood. Substance Abuse, 36(4), 470–477.

    Article  PubMed  Google Scholar 

  • Dunn, L. M., & Dunn, L. M. (1981). Manual for the peabody picture vocabulary test-revised. Circle Pines, MN: American Guidance Service.

    Google Scholar 

  • Fairman, B. J., Johnson, R. M., & Furr-Holden, C. D. M. (2018). When cannabis is used before tobacco or alcohol: Demographic predictors and associations with heavy use, cannabis use disorder, and other drug outcomes. Prevention Science. Manuscript under review.

  • Farrelly, M. C., Loomis, B. R., Han, B., Gfroerer, J., Kuiper, N., Couzens, G. L., … Caraballo, R. S.. (2013). A comprehensive examination of the influence of state tobacco control programs and policies on youth smoking. American Journal of Public Health, 103(3), 549–555.

  • Goodman, E., & Whitaker, R. C. (2002). A prospective study of the role of depression in the development and persistence of adolescent obesity. Pediatrics, 109(3), 497–504.

    Article  Google Scholar 

  • Harris, K. M. (2009). The National Longitudinal Study of adolescent to adult health (add health), waves I & II, 1994-1996; wave III, 2001-2002; wave IV, 2007-2009 [machine-readable data file and documentation]. Chapel Hill, NC: Carolina Population Center, Univeristy of Carolina at Chapel Hill. https://doi.org/10.3886/ICPSR27021.v9

  • Harris, K. M. (2013). The Add Health Study: Design and Accomplishments. Retrieved from www.cpc.unc.edu/projects/addhealth/documentation/guides/DesignPaperWIIV.pdf

  • Ho, D. E., Imai, K., King, G., & Stuart, E. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15(3), 199–236.

    Article  Google Scholar 

  • Hu, M. C., Davies, M., & Kandel, D. B. (2006). Epidemiology and correlates of daily smoking and nicotine dependence among young adults in the United States. American Journal of Public Health, 96(2), 299–308.

    Article  PubMed  PubMed Central  Google Scholar 

  • Humfleet, G. L., & Haas, A. L. (2004). Is marijuana use becoming a “gateway” to nicotine dependence? Addiction, 99, 5–6.

    Article  PubMed  Google Scholar 

  • Jamal, A., King, B. A., Neff, L. J., Whitmill, J., Babb, S. D., & Graffunder, C. M. (2016). Current cigarette smoking among adults -- United States, 2005-2015. MMWR. Morbidity and Mortality Weekly Report, 65(44), 1205–1211.

    Article  PubMed  Google Scholar 

  • Johnson, R. M., Brooks-Russell, A., Ma, M., Fairman, B. J., Tolliver, R. L., & Levinson, A. H. (2016). Usual modes of marijuana consumption among high school students in Colorado. Journal of Studies on Alcohol and Drugs, 77(4), 580–588.

    Article  PubMed  PubMed Central  Google Scholar 

  • Johnson, R. M., Fairman, B., Gilreath, T., Xuan, Z., Rothman, E. F., Parnham, T., & Furr-Holden, C. D. M. (2015). Past 15-year trends in adolescent marijuana use: Differences by race/ethnicity and sex. Drug and Alcohol Dependence, 155, 8–15.

    Article  PubMed  PubMed Central  Google Scholar 

  • Johnson, R. M., Fleming, C. B., Cambron, C., Brighthaupt, S.-C., Dean, L. T., & Guttmannova, K. (2018). Race/ethnicity differences in trends of alcohol, cigarette, and marijuana use among adolescents in Washington state, 2004–2014. Manuscript submitted for publication.

  • Johnston, L. D., Malley, P. M. O., Miech, R. A., Bachman, J. G., & Schulenberg, J. E. (2016). Monitoring the future national survey results on drug use, 1975-2015: Overview, key findings on adolescent drug use. Ann Arbor: Institute for Social Research, The University of Michigan. https://doi.org/10.1017/CBO9781107415324.004.

  • Kostova, D., Ross, H., Blecher, E., & Markowitz, S. (2010). Prices and cigarette demand: Evidence from youth tobacco use in developing countries (NBER working paper series no. 15781). Retrieved from http://www.nber.org/papers/w15781.pdf

  • Kristman-Valente, A., Hill, K. G., Epstein, M., Kosterman, R., Bailey, J. A., Steeger, C. M., … Hawkins, J. D. (2017). The relationship between marijuana and conventional cigarette smoking behavior from early adolescence to adulthood. Prevention Science. https://doi.org/10.1007/s11121-017-0774-4.

  • Lantz, P. M. (2000). Investing in youth tobacco control: A review of smoking prevention and control strategies. Tobacco Control, 9(1), 47–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lumley, T. (2004). Analysis of complex survey samples. Journal of Statistical Software, 9(8), 1–19.

    Article  Google Scholar 

  • Mendel, J. R., Berg, C. J., Windle, R. C., & Windle, M. (2012). Predicting young adulthood smoking among adolescent smokers and nonsmokers. American Journal of Health Behavior, 36(4), 542–554.

    Article  PubMed  PubMed Central  Google Scholar 

  • Patton, G. C., Coffey, C., Carlin, J. B., Sawyer, S. M., & Lynskey, M. (2005). Reverse gateways? Frequent cannabis use as a predictor of tobacco initiation and nicotine dependence. Addiction, 100(10), 1518–1525.

    Article  PubMed  Google Scholar 

  • Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401.

    Article  Google Scholar 

  • Resnick, M. D., Bearman, P. S., Wm Blum, R., Bauman, K. E., Harris, K. M., Jones, J., et al. (1997). Protecting adolescents from harm findings from the National Longitudinal Study on adolescent health. JAMA, 278(10), 823–832.

    Article  CAS  PubMed  Google Scholar 

  • Ridgeway, G., McCaffrey, D. F., Morral, A., Griffin, B. A., & Burgette, L. (2015). Twang: Toolkit for weighting and analysis of nonequivalent groups. Retrieved from https://cran.r-project.org/web/packages/twang/vignettes/twang.pdf

  • Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55.

    Article  Google Scholar 

  • Rubin, D. B. (1987). Multiple imputation for nonresponse in surveys. New York: John Wiley & Sons Inc..

    Book  Google Scholar 

  • Stuart, E. A. (2010). Matching methods for causal inference: A review and a look forward. Statistical Science, 25(1), 1–21.

    Article  PubMed  PubMed Central  Google Scholar 

  • Swift, W., Coffey, C., Degenhardt, L., Carlin, J. B., Romaniuk, H., & Patton, G. C. (2012). Cannabis and progression to other substance use in young adults: Findings from a 13-year prospective population-based study. Journal of Epidemiology and Community Health, 66(7), e26.

    Article  PubMed  Google Scholar 

  • Timberlake, D. S., Haberstick, B. C., Hopfer, C. J., Bricker, J., Sakai, J. T., Lessem, J. M., & Hewitt, J. K. (2007). Progression from marijuana use to daily smoking and nicotine dependence in a national sample of U.S. adolescents. Drug and Alcohol Dependence, 88(2–3), 272–281.

    Article  PubMed  Google Scholar 

  • U.S. Department of Health and Human Services. (2012). Preventing tobacco use among youth and young adults a report of the surgeon general executive summary. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.

    Google Scholar 

  • U.S. Department of Health and Human Services. (2014). The health consequences of smoking—50 years of progress: A report of the surgeon general. Atlanta, GA: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health http://doi.org/NBK179276

    Google Scholar 

  • U.S. Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, & Center for Behavioral Health Statistics and Quality. (2014). National Survey on drug use and health. Retrieved from https://doi.org/10.3886/ICPSR36361.v1.

  • US Department of Health and Human Services. (2002). Women and smoking: A report of the Surgeon General.

  • van Buuren, S., & Groothuis-Oudshoorn, K. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3). https://doi.org/10.18637/jss.v045.i03

  • VanderWeele, T. J., & Arah, O. a. (2011). Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders. Epidemiology, 22(1), 42–52.

    Article  PubMed  PubMed Central  Google Scholar 

  • White, I. R., Royston, P., & Wood, A. M. (2011). Multiple imputation using chained equations: Issues and guidance for practice. Statistics in Medicine, 30(4), 377–399.

    Article  PubMed  Google Scholar 

Download references

Funding

The current study is supported by the National Institute on Drug Abuse (K01DA031738, Johnson).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Trang Quynh Nguyen.

Ethics declarations

Conflicts of Interest

The authors declare that they have no conflict of interest.

Research Involving Human Participants and/or Animals

The current project did not involve data collection. We used de-identified data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill.

Informed Consent

Non-applicable, because the current project did not involve data collection.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nguyen, T.Q., Ebnesajjad, C., Stuart, E.A. et al. Does Marijuana Use at Ages 16–18 Predict Initiation of Daily Cigarette Smoking in Late Adolescence and Early Adulthood? A Propensity Score Analysis of Add Health Data. Prev Sci 20, 246–256 (2019). https://doi.org/10.1007/s11121-018-0874-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11121-018-0874-9

Keywords

Navigation