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Addict Behav. 2019 Apr;91:51-60. doi: 10.1016/j.addbeh.2018.11.027. Epub 2018 Nov 17.

Associations of risk factors of e-cigarette and cigarette use and susceptibility to use among baseline PATH study youth participants (2013-2014).

Author information

1
Office of Science, Center for Tobacco Products, Food and Drug Administration, Silver Spring, MD, USA. Electronic address: Michael.Sawdey@fda.hhs.gov.
2
Office of Science, Center for Tobacco Products, Food and Drug Administration, Silver Spring, MD, USA.
3
Department of Health Behavior, Division of Cancer Prevention & Population Sciences, Roswell Park Cancer Institute, Buffalo, NY, USA.
4
Department of Social and Behavioral Sciences, NYU College of Global Public Health, New York University, New York, NY, USA.
5
Westat, Rockville, MD, USA; Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC, USA.
6
Division of Social and Behavioral Sciences/Health Administration and Policy, University of Nevada, Reno, Reno, NV, USA.
7
Tobacco Control Research Branch, Behavioral Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, National Institutes of Health, Rockville, MD, USA.
8
National Institute on Drug Abuse, National Institutes of Health, U.S. Department of Health and Human Services, Bethesda, MD, USA.
9
Department of Health Education and Behavioral Science, Center for Tobacco Studies, Rutgers School of Public Health, Piscataway, NJ, USA.

Abstract

INTRODUCTION:

Improved understanding of the distribution of traditional risk factors of cigarette smoking among youth who have ever used or are susceptible to e-cigarettes and cigarettes will inform future longitudinal studies examining transitions in use.

METHODS:

Multiple logistic regression analysis was conducted using data from youth (ages 12-17 years) who had ever heard of e-cigarettes at baseline of the PATH Study (n = 12,460) to compare the distribution of risk factors for cigarette smoking among seven mutually exclusive groups based on ever cigarette/e-cigarette use and susceptibility status.

RESULTS:

Compared to committed never users, youth susceptible to e-cigarettes, cigarettes, or both had increasing odds of risk factors for cigarette smoking, with those susceptible to both products at highest risk, followed by cigarettes and e-cigarettes. Compared to e-cigarette only users, dual users had higher odds of nearly all risk factors (aOR range = 1.6-6.8) and cigarette only smokers had higher odds of other (non-e-cigarette) tobacco use (aOR range = 1.5-2.3), marijuana use (aOR = 1.9, 95%CI = 1.4-2.5), a high GAIN substance use score (aOR = 1.9, 95%CI = 1.1-3.4), low academic achievement (aOR range = 1.6-3.4), and exposure to smoking (aOR range = 1.8-2.1). No differences were observed for externalizing factors (depression, anxiety, etc.), sensation seeking, or household use of non-cigarette tobacco.

CONCLUSIONS:

Among ever cigarette and e-cigarette users, dual users had higher odds of reporting traditional risk factors for smoking, followed by single product cigarette smokers and e-cigarette users. Understanding how e-cigarette and cigarette users differ may inform youth tobacco use prevention efforts and advise future studies assessing probability of progression of cigarette and e-cigarette use.

KEYWORDS:

Cigarettes; E-cigarettes; Risk factors of tobacco use; Susceptibility

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