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J Natl Cancer Inst. 2019 Jan 25. doi: 10.1093/jnci/djz006. [Epub ahead of print]

Longitudinal e-cigarette and cigarette use among US youth in the PATH Study (2013-2015).

Author information

1
Westat, Rockville, MD, USA.
2
Department of Oncology, Georgetown University Medical Center, Washington, DC, USA.
3
Department of Health Behavior, Division of Cancer Prevention & Population Sciences, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA.
4
The Schroeder Institute for Tobacco Research and Policy Studies at Truth Initiative, Washington, DC, USA.
5
Office of Science, Center for Tobacco Products, Food and Drug Administration, Silver Spring, MD, USA.
6
National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA.
7
Kelly Government Solutions, Rockville, MD, USA.
8
Norris Cotton Cancer Center and Dartmouth Institute for Health Policy & Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
9
Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
10
Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
11
Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC, USA.
12
School of Community Health Sciences, University of Nevada, Reno, Reno, NV, USA.

Abstract

Background:

Evidence is accumulating that youth who try ENDS (e-cigarettes) may go on to try cigarettes. This analysis examines the bidirectional patterns of ENDS and cigarette use among US youth over one year and uses propensity score matching (PSM) to examine frequency of ENDS use on changes in cigarette smoking.

Methods:

Our analysis included 11,996 partcipants who had two waves of available data (W1 2013-2014; W2 2014-2015) drawn from the longitudinal Population Assessment of Tobacco and Health (PATH) Study. Cross-sectional weighted prevalence estimates are reported for cigarettes and ENDS. We used PSM to estimate the likelihood of ENDS use at W1 and to draw matched analytic samples, then used regression (logistic or linear) models to examine the effect of W1 ENDS use on W2 cigarette smoking. All statistical tests were two-sided.

Results:

In weighted analyses, 69.3% of W1 past-30-day cigarette smokers exhibited past-30-day smoking at W2; 42.2% of W1 past-30-day ENDS users were using ENDS at W2. W1 ever use of either product was similarly associated with W2 new use of the other product. Unweighted PSM models indicated: W1 cigarette-naïve ENDS use was associated with W2 ever cigarette smoking (n = 676 ; aOR 3.21, 95%CI = 1.95, 5.45, p < 0.001); W1 ever ENDS use did not affect change in cigarette frequency at W2 (n = 1020, beta=0.31, 95%CI = -0.76, 1.39, p = 0.57); 1-5 days ENDS use compared to ever, no past-30-day ENDS use was associated with a statistically significant decrease of W2 smoking days (n = 256, beta = -2.64, 95%CI = -4.96, -0.32; p = 0.03); and W1 6+ day ENDS users did not show a decrease in frequency of cigarette smoking.

Conclusions:

Ever ENDS use predicts future cigarette smoking and frequency of ENDS use has a differential impact on subsequent cigarette smoking uptake or reduction. These results suggest that both cigarettes and ENDS should be targeted in early tobacco prevention efforts with youth.

PMID:
30689915
DOI:
10.1093/jnci/djz006

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