Article de Périodique
Evaluating the mutual pathways among electronic cigarette use, conventional smoking and nicotine dependence (2018)
Auteur(s) :
SELYA, A. S. ;
ROSE, J. S. ;
DIERKER, L. ;
HEDEKER, D. ;
MERMELSTEIN, R. J.
Année
2018
Page(s) :
325-333
Langue(s) :
Anglais
Refs biblio. :
37
Domaine :
Tabac / Tobacco / e-cigarette
Discipline :
EPI (Epidémiologie / Epidemiology)
Thésaurus géographique
ETATS-UNIS
Thésaurus mots-clés
TABAC
;
E-CIGARETTE
;
CIGARETTE
;
NICOTINE
;
DEPENDANCE
;
POLYCONSOMMATION
;
MODELE STATISTIQUE
;
THEORIE DE L'ESCALADE
Note générale :
Commentary: Advantages in the consideration of causal mechanisms for studies of gateway e-cigarette use. Cahn Z., Berg C.J., p. 334-335.
Résumé :
Background and Aims: The implications of the rapid rise in electronic cigarette (e-cigarette) use remain unknown. We examined mutual associations between e-cigarette use, conventional cigarette use and nicotine dependence over time to (1) test the association between e-cigarette use and later conventional smoking (both direct and via nicotine dependence), (2) test the converse associations and (3) determine the strongest pathways predicting each product's use.
Design: Data from four annual waves of a prospective cohort study were analyzed. Path analysis modeled the bidirectional, longitudinal relationships between past-month smoking frequency, past-month e-cigarette frequency and nicotine dependence.
Setting: Chicago area, Illinois, USA.
Participants: A total of 1007 young adult smokers and non-smokers (ages 19-23 years).
Measurements: Frequency of (1) cigarettes and (2) e-cigarettes was the number of days in the past 30 on which the product was used. The Nicotine Dependence Syndrome Scale measured nicotine dependence to cigarettes.
Findings: E-cigarette use was not associated significantly with later conventional smoking, either directly (beta = 0.021, P = 0.081) or through nicotine dependence (beta = 0.005, P = 0.693). Conventional smoking was associated positively with later e-cigarette use, both directly (beta = 0.118, P < 0.001) and through nicotine dependence (beta = 0.139, P < 0.001). The strongest predictors of each product's use was prior use of the same product; this pathway was strong for conventional cigarettes (beta = 0.604, P < 0.001) but weak for e-cigarettes (beta = 0.120, P < 0.001). Nicotine dependence moderately strongly predicted later conventional smoking (beta = 0.169, P < 0.001), but was a weak predictor of later e-cigarette use (beta = 0.069, P = 0.039).
Conclusions: Nicotine dependence is not a significant mechanism for e-cigarettes' purported effect on heavier future conventional smoking among young adults. Nicotine dependence may be a mechanism for increases in e-cigarette use among heavier conventional smokers, consistent with e-cigarettes as a smoking reduction tool. Overall, conventional smoking and, to a lesser extent, its resulting nicotine dependence, are the strongest drivers or signals of later cigarette and e-cigarette use.
Design: Data from four annual waves of a prospective cohort study were analyzed. Path analysis modeled the bidirectional, longitudinal relationships between past-month smoking frequency, past-month e-cigarette frequency and nicotine dependence.
Setting: Chicago area, Illinois, USA.
Participants: A total of 1007 young adult smokers and non-smokers (ages 19-23 years).
Measurements: Frequency of (1) cigarettes and (2) e-cigarettes was the number of days in the past 30 on which the product was used. The Nicotine Dependence Syndrome Scale measured nicotine dependence to cigarettes.
Findings: E-cigarette use was not associated significantly with later conventional smoking, either directly (beta = 0.021, P = 0.081) or through nicotine dependence (beta = 0.005, P = 0.693). Conventional smoking was associated positively with later e-cigarette use, both directly (beta = 0.118, P < 0.001) and through nicotine dependence (beta = 0.139, P < 0.001). The strongest predictors of each product's use was prior use of the same product; this pathway was strong for conventional cigarettes (beta = 0.604, P < 0.001) but weak for e-cigarettes (beta = 0.120, P < 0.001). Nicotine dependence moderately strongly predicted later conventional smoking (beta = 0.169, P < 0.001), but was a weak predictor of later e-cigarette use (beta = 0.069, P = 0.039).
Conclusions: Nicotine dependence is not a significant mechanism for e-cigarettes' purported effect on heavier future conventional smoking among young adults. Nicotine dependence may be a mechanism for increases in e-cigarette use among heavier conventional smokers, consistent with e-cigarettes as a smoking reduction tool. Overall, conventional smoking and, to a lesser extent, its resulting nicotine dependence, are the strongest drivers or signals of later cigarette and e-cigarette use.
Affiliation :
Department of Population Health, University of North Dakota, Grand Forks, ND, USA
Cote :
Abonnement
Historique