Progression to Traditional Cigarette Smoking After Electronic Cigarette Use Among US Adolescents and Young Adults.
OBJECTIVE
Electronic cigarettes (e-cigarettes) may help smokers reduce the use of traditional combustible cigarettes. However, adolescents and young adults who have never smoked traditional cigarettes are now using e-cigarettes, and these individuals may be at risk for subsequent progression to traditional cigarette smoking.


OBJECTIVE
To determine whether baseline use of e-cigarettes among nonsmoking and nonsusceptible adolescents and young adults is associated with subsequent progression along an established trajectory to traditional cigarette smoking.


METHODS
In this longitudinal cohort study, a national US sample of 694 participants aged 16 to 26 years who were never cigarette smokers and were attitudinally nonsusceptible to smoking cigarettes completed baseline surveys from October 1, 2012, to May 1, 2014, regarding smoking in 2012-2013. They were reassessed 1 year later. Analysis was conducted from July 1, 2014, to March 1, 2015. Multinomial logistic regression was used to assess the independent association between baseline e-cigarette use and cigarette smoking, controlling for sex, age, race/ethnicity, maternal educational level, sensation-seeking tendency, parental cigarette smoking, and cigarette smoking among friends. Sensitivity analyses were performed, with varying approaches to missing data and recanting.


METHODS
Use of e-cigarettes at baseline.


METHODS
Progression to cigarette smoking, defined using 3 specific states along a trajectory: nonsusceptible nonsmokers, susceptible nonsmokers, and smokers. Individuals who could not rule out smoking in the future were defined as susceptible.


RESULTS
Among the 694 respondents, 374 (53.9%) were female and 531 (76.5%) were non-Hispanic white. At baseline, 16 participants (2.3%) used e-cigarettes. Over the 1-year follow-up, 11 of 16 e-cigarette users and 128 of 678 of those who had not used e-cigarettes (18.9%) progressed toward cigarette smoking. In the primary fully adjusted models, baseline e-cigarette use was independently associated with progression to smoking (adjusted odds ratio [AOR], 8.3; 95% CI, 1.2-58.6) and to susceptibility among nonsmokers (AOR, 8.5; 95% CI, 1.3-57.2). Sensitivity analyses showed consistent results in the level of significance and slightly larger magnitude of AORs.


CONCLUSIONS
In this national sample of US adolescents and young adults, use of e-cigarettes at baseline was associated with progression to traditional cigarette smoking. These findings support regulations to limit sales and decrease the appeal of e-cigarettes to adolescents and young adults.
Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania2Center for Research on Media, Technology, and Health, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvani.
Brian A
BA
Primack
Norris Cotton Cancer Center, Geisel School of Medicine, Dartmouth University, Hanover, New Hampshire5Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Dartmouth University, Hanover, New Hampshire.
Samir
S
Soneji
Oregon Social Learning Center, College of Education, University of Oregon, Eugene.
Michael
M
Stoolmiller
Division of General Internal Medicine, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania7Center for Health Equity and Research Promotion, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania.
Michael J
MJ
Fine
Norris Cotton Cancer Center, Geisel School of Medicine, Dartmouth University, Hanover, New Hampshire5Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine, Dartmouth University, Hanover, New Hampshire8Department of Pediatr.
James D
JD
Sargent
D000293:Adolescent; D000294:Adolescent Behavior; D000328:Adult; D015331:Cohort Studies; D018450:Disease Progression; D066300:Electronic Nicotine Delivery Systems / Q000009:adverse effects*; D005260:Female; D006306:Health Surveys; D006801:Humans; D016015:Logistic Models; D008137:Longitudinal Studies; D008297:Male; D018570:Risk Assessment; D012307:Risk Factors; D012907:Smoking / Q000453:epidemiology*; D016540:Smoking Cessation / Q000706:statistics & numerical data; D014481:United States; D055815:Young Adult