Risk factors associated with subsequent initiation of cigarettes and e-cigarettes in adolescence: A structural equation modeling approach.

Autor: Kintz N; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Liu M; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States; Department of Public Health Sciences, University of Miami, Miami, FL, United States., Chou CP; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Urman R; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Berhane K; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Unger JB; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Boley Cruz T; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., McConnell R; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States., Barrington-Trimis JL; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, United States. Electronic address: jtrimis@usc.edu.
Jazyk: angličtina
Zdroj: Drug and alcohol dependence [Drug Alcohol Depend] 2020 Feb 01; Vol. 207, pp. 107676. Date of Electronic Publication: 2019 Oct 29.
DOI: 10.1016/j.drugalcdep.2019.107676
Abstrakt: Background: Previous youth tobacco research has identified multiple correlated risk factors for initiation of cigarette and e-cigarette use; whether these factors are independently associated with initiation is not known, due to challenges with disentangling the independent effects of these correlated risk factors.
Methods: Students in 11 th /12 th grade enrolled in the Southern California Children's Health Study were surveyed in 2014 (baseline) and again in 2015 (N = 1553). Structural equation models (SEM) were developed to investigate associations of susceptibility, marketing, and the social environment (as latent factors), and other tobacco use at baseline with cigarette or e-cigarette initiation between baseline and follow-up. Analyses were restricted to baseline never cigarette users (N = 1293) for models evaluating cigarette initiation, and to never e-cigarette users (N = 1197) for models evaluating e-cigarette initiation.
Results: In fully-adjusted prospective SEM models, latent factors for cigarette susceptibility, marketing, and the social environment, along with ever e-cigarette use and ever hookah use at baseline were independently associated with cigarette initiation between baseline and follow-up (P < 0.05). Similarly, latent factors for e-cigarette susceptibility, marketing, and the social environment, along with ever hookah use at baseline were associated with e-cigarette initiation between baseline and follow-up (P < 0.05); however, cigarette use at baseline was not associated with e-cigarette initiation in SEM models (P = 0.16).
Conclusions: We identified independent effects of multiple risk factors in SEM models on initiation of cigarettes and e-cigarettes. E-cigarette use was associated with cigarette initiation, but cigarette use was not associated with e-cigarette initiation in fully adjusted models. Research to identify underlying causal mechanisms is warranted.
(Copyright © 2019 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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