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. 2018 Oct 1;191:25-36.
doi: 10.1016/j.drugalcdep.2018.06.018. Epub 2018 Jul 25.

Longitudinal Associations Between Youth Tobacco and Substance Use in Waves 1 and 2 of the Population Assessment of Tobacco and Health (PATH) Study

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Longitudinal Associations Between Youth Tobacco and Substance Use in Waves 1 and 2 of the Population Assessment of Tobacco and Health (PATH) Study

Marushka L Silveira et al. Drug Alcohol Depend. .
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Abstract

Background: While evidence suggests bidirectional associations between cigarette use and substance (alcohol or drug) use, how these associations are reflected across the range of currently available tobacco products is unknown. This study examined whether ever tobacco use predicted subsequent substance use, and ever substance use predicted subsequent tobacco use among 11,996 U.S. youth (12-17 years) from Waves 1 (2013-2014) and 2 (2014-2015) of the Population Assessment of Tobacco and Health (PATH) Study.

Methods: Ever use of cigarettes, e-cigarettes, traditional cigars, cigarillos, filtered cigars, pipe, hookah, snus pouches, smokeless tobacco excluding snus pouches, dissolvable tobacco, bidis, kreteks, alcohol, marijuana, prescription drugs, and other drugs (cocaine and other stimulants, heroin, inhalants, solvents, and hallucinogens) was assessed at Wave 1 followed by past 12-month use assessments at Wave 2. The analyses included covariates (demographics, mental health, sensation seeking, prior use) to mitigate confounding.

Results: Ever tobacco use predicted subsequent substance use. The magnitude of the associations was lowest for alcohol, higher for marijuana, and highest for other drugs. Ever substance use also predicted subsequent tobacco use. Specifically, ever alcohol, marijuana, and non-prescribed Ritalin/Adderall use predicted tobacco-product use. Ever e-cigarette and cigarette use exclusively and concurrently predicted subsequent any drug (including and excluding alcohol) use. E-cigarette and cigarette use associations in the opposite direction were also significant; the strongest associations were observed for exclusive cigarette use.

Conclusion: Tobacco and substance use prevention efforts may benefit from comprehensive screening and interventions across tobacco products, alcohol, and drugs, and targeting risk factors shared across substances.

Keywords: Bidirectional; Drugs; Epidemiologic studies; Marijuana; Tobacco products; Youth.

Conflict of interest statement

Conflict of Interest

Dr. Compton reports holding stock in General Electric, the 3M Companies, and Pfizer; Dr. Cummings reports receiving grant support from Pfizer and receiving fees as a paid expert witness in litigation filed against the tobacco industry; Dr. Niaura reports having been a witness for plaintiffs vs. tobacco companies, receiving speaker fees, receiving honoraria, sitting on advisory boards, being a site PI, and consulting for pharmaceutical companies testing and marketing smoking cessation aids, but not in the last 6 years. No other potential conflict of interest relevant to this manuscript was reported.

Figures

Figure 1.
Figure 1.
Prevalence of Wave 2 (W2) Past 12-month Substance Use by Wave 1 (W1) Ever Any Tobacco Use Among 11,996 Wave 1 Youth (12–17 years) in the PATH Study. Note: Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) from multivariable logistic regression models adjusting for age, gender, race/ethnicity, sensation seeking, past-year mental health problems at Wave 1, and ever substance use at Wave 1. ᶲIncludes past 12-month use of cigars as blunts. ᶱRefers to prescription drugs that were not prescribed for the participant or taken only for the experience or feeling they caused. ⱡRefers to cigarettes, e-cigarettes, traditional cigars, cigarillos, filtered cigars, pipe, hookah, snus pouches, smokeless tobacco excluding snus pouches, kreteks, bidis, or dissolvable tobacco. Models were restricted to observations with non-missing data; unweighted sample sizes ranged from 10493 (for the any tobacco and alcohol or any drug model) to 10538 (for the any tobacco and non-prescribed painkiller/sedative model). Statistically significant associations at p<.05 indicated in bold text.
Figure 2.
Figure 2.
Prevalence of Wave 2 (W2) Past 12-month Tobacco Use by Wave 1 (W1) Ever Any Substance Use Among 11,996 Wave 1 Youth (12–17 years) in the PATH Study. Note: Adjusted odds ratios (AORs) and 95% confidence intervals (CIs) from multivariable logistic regression models adjusting for age, gender, race/ethnicity, sensation seeking, past-year mental health problems at Wave 1, and ever tobacco use at Wave 1. ᵠRefers to snus pouches, smokeless tobacco excluding snus pouches, or dissolvable tobacco. ⱡRefers to cigarettes, e-cigarettes, traditional cigars, cigarillos, filtered cigars, pipe, hookah, snus pouches, smokeless tobacco excluding snus pouches, or dissolvable tobacco. Unreliable estimates (for dissolvable tobacco) were suppressed based on relative standard error greater than 0.30 or denominator sample size less than 50. Models were restricted to observations with non-missing data; unweighted sample sizes ranged from 10397 (for the alcohol or any drug and any tobacco model) to 10568 (for the alcohol or any drug and cigarette model). Statistically significant associations at p<.05 indicated in bold text.

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