Bidirectional associations of e-cigarette, conventional cigarette and waterpipe experimentation among adolescents: A cross-lagged model

Pénzes, Melinda; Foley, Kristie L.; Nădășan, Valentin; Paulik, Edit; Ábrám, Zoltán; Urbán, Róbert

doi:10.1016/j.addbeh.2018.01.010

Cited by 28 publications

(32 citation statements)

References 40 publications

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“…It is generally accepted that smoking habits are mainly developed in young people during adolescence and early adulthood. Tobacco prevention programs targeting adolescents should emphasize the risks of using not only CC, but also ATP and general accessibility of ATPs should be better regulated to prevent potential harmful consequences of adolescent poly tobacco use [42].…”

Section: Discussionmentioning

confidence: 99%

E-Cigarette Use Among University Students in Slovakia

Babjaková¹,

Weitzman²,

Vondrová³

et al. 2020

Preprint

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Young adults are more likely to have experimented with electronic cigarettes (EC) and underestimate their risks. The on-line survey adapted from American Survey on Tobacco and Alternative Tobacco Products included questions about the personal use of EC, perceptions about the harms and their role in disease causation, education and cessation training and practices related to classical cigarettes (CC), electronic cigarettes (EC) and alternative tobacco products (ATP). The questionnaire filled in 577 medical students (71.9% women) from Comenius University in Bratislava, the average age was 23±2yrs. The sample comprised of 486 (84.2%) Slovak and 91 (15.8%) foreign students; 385 were (66.7%) non-smokers, 111 (19.3%) ex-smokers and 81 (14 %) current smokers. EC currently use 13.5 % medical students, more males than females (22.2% vs 10.12%; OR 2.53, 95% CI 1.55−4.13), more foreign students than Slovak students (24.2% vs 11.52; OR 2.44, 95% CI 1.41−4.26), more smokers of classical cigarettes than non-smokers (46.9% vs 8.06%; OR 10.07, 95% CI 5.85−17.34). EC seems to be less harmful to 59.97 % students, mostly in the age groups ≤ 24 (61.76% vs 51.49%; OR 1.46, 95% CI 1.03−2.07), 41.25% of students consider EC to be less addictive, 55.6% think they do not get enough education on EC during their medical study. The results show the high consumption of tobacco products and the lack of knowledge and awareness among medical students.

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Section: Discussionmentioning

confidence: 99%

E-Cigarette Use Among University Students in Slovakia

Babjaková¹,

Weitzman²,

Vondrová³

et al. 2020

Preprint

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“…Since the time that we published our earlier analysis [8] and our paper on general considerations relating to vaping as a possible gateway into cigarette smoking [7] a number of other authors have presented evidence from prospective studies [9][10][11][12][13][14][15]. The studies vary in the extent to which potential confounding variables have been adjusted for, with large OR estimates tending to be reported in studies with more limited control.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, a study in the Netherlands [15], which adjusted only for sex, age education and a single indicator of propensity to smoke, reported an OR of 11.90 (95% CI 3.36-42.11) for the relationship between ever use of e-cigarettes with nicotine and initiation of cigarette smoking during follow-up. Also, a study in the US [9], which adjusted only for demographic variables and use of other tobacco products, reported ORs of 7.08 (2.34-21.42) and 3.87 (1.86-2.06) depending on the follow-up period studied, while another US study [13], with limited control for confounding variables, reported an OR of 3.57 (1.96-6.45). Apart from a US study [14] ,which reported an OR of 6.8 (1.7-28.3), following adjustment for ten covariates independently associated with initiation of smoking, most of the other studies which appear to have better control for confounding gave lower estimates.…”

Section: Discussionmentioning

confidence: 99%

“…Some aspects of the analyses described here are the same as those described earlier [8] and are not presented again here. The selection of demographic and other predictor variables is the same as before, except that in some analyses we use exact age (12, 13, 14, 15, 16 and 17) which could now be estimated from the age group (12)(13)(14)(15)(16)(17) at the three Waves and the Wave when youths became adults (18+) for the first time. Use of the person-level weights provided in the PATH study database is as before, as is the process by which a sequence of logistic regression analyses is used to develop the shorter list of demographic variables to be used in forming the propensity scores.…”

Section: Methodsmentioning

confidence: 99%

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Further investigations of gateway effects using the PATH study

Lee¹,

Fry²

2020

Preprint

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Background: Considerable interest exists in whether e-cigarette use (“vaping”) by youths increases the risk of initiating cigarette smoking. Based on Waves 1 and 2 of the Population Assessment of Tobacco and Health study we reported that adjustment for propensity for vaping using Wave 1 variables explained about 80% of the unadjusted relationship. This analysis may be over-adjusted had vaping at Wave 1 affected some variables recorded then. Here we present analyses using Waves 1 to 3 to avoid this possibility. Methods: Our main analysis M1 concerned those who had never smoked by Wave 2 and never vaped by Wave 1. Wave 2 vaping was linked to smoking initiation by Wave 3, adjusting for Wave 1 predictors. Sensitivity analyses excluded other tobacco product users at Wave 1, included other tobacco product use as an additional predictor, or were based on propensity for ever smoking or ever any tobacco use, rather than ever vaping. Other analyses adjusted for propensity as derived originally, or ignored Wave 1 data. Other analyses used grouped age (only available originally) or exact age (available now) as a confounder variable, attempted residual confounding adjustment by modifying values of predictor variables using data later recorded, or considered interactions with age. Results: In M1, propensity adjustment removed about 50% of the excess odds ratio (i.e. OR–1), the unadjusted OR, 5.60 (95% CI 4.52-6.93) becoming 3.37 (2.65-4.28), 3.11 (2.47-3.92) or 3.27 (2.57-4.16) depending whether adjustment was for propensity as a continuous variable, as quintiles, or for the 16 variables making up the propensity score. Many factors studied hardly affected the results, including using grouped or exact age, consideration of other tobacco products, including interactions, or using predictors of smoking or tobacco use rather than vaping. The clearest conclusion was that analyses avoiding over-adjustment only explained about 50% of the excess OR whereas analyses subject to over-adjustment explained about 80%. Conclusions: Although much of the unadjusted gateway effect results from uncontrolled confounding, our current analysis provides stronger evidence of a causal effect of vaping than did our earlier analysis. However, some doubts remain about the completeness of confounder adjustment.

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“…Eric und Denise Kandel formulierten im New England Journal of Medicine als Erste die Hypothese, E-Zigaretten könnten aufgrund der schnellen Entwicklung einer Nikotinabhängigkeit den Einstieg in den Konsum konventioneller Zigaretten fördern (Gateway-Theorie) [4]. Diese Hypothese wurde inzwischen theoretisch weiterentwickelt [5] und mit Kohortenstudien aus den USA und Kanada [6 -19], Großbritannien [20 -22], Finnland [23], Mexiko [24], den Niederlanden [25], Rumänien [26], Taiwan [27] sowie Deutschland [28] empirisch geprüft. Die Ergebnisse dieser Studien weisen übereinstimmend darauf hin, dass das Probieren von E-Zigaretten im Jugendalter ein bedeutsamer Risikofaktor für das spätere Experimentieren mit klassischen Zigaretten ist.…”

Section: Hintergrundunclassified

E-Zigarettenkonsum und späterer Konsum konventioneller Zigaretten

et al. 2019

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Zusammenfassung Ziel Es sollte untersucht werden, ob der vorherige E-Zigarettenkonsum das spätere Probieren konventioneller Zigaretten vorhersagt. Methode Im Schuljahr 2016/2017 nahmen in den Bundesländern Baden-Württemberg, Mecklenburg-Vorpommern, Nordrhein-Westfalen, Rheinland-Pfalz, Schleswig-Holstein und Sachsen 2388 Kinder und Jugendliche, die nie zuvor konventionelle Zigaretten geraucht haben, über 2 Jahre an einer Fragebogenstudie teil (mittleres Alter = 11,8 Jahre, SD = 1,21; 49,6 % weiblich). Ergebnisse Zur Eingangserhebung gaben 85 Schülerinnen und Schüler (3,6 %) an, schon einmal E-Zigaretten probiert zu haben. Im Beobachtungszeitraum begannen 430 der ehemals nie rauchenden Jugendlichen (18,0 %) mit konventionellen Zigaretten zu experimentieren. Auch nach statistischer Kontrolle von Alter, Geschlecht, Migrationshintergrund, „Sensation Seeking“, subjektiver Schulleistung, Alkoholkonsum, sozioökonomischem Status und Schulart war das relative Risiko für das Experimentieren bei Nutzern von E-Zigaretten um 85 % erhöht (adjustiertes relatives Risiko = 1,85, 95 % KI [1, 34 – 2,56]). Weiterführende Analysen zeigten, dass das Risiko insbesondere für Jugendliche mit niedrigem „Sensation Seeking“ erhöht war. Schlussfolgerungen Jugendliche experimentierten häufiger mit konventionellen Zigaretten, wenn sie zuvor E-Zigaretten konsumiert hatten. Diese Assoziation scheint stärker für Jugendliche zu sein, die ein generell niedrigeres Risiko haben, mit dem Rauchen zu beginnen.

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Bidirectional associations of e-cigarette, conventional cigarette and waterpipe experimentation among adolescents: A cross-lagged model

Abstract: The high rates of poly-tobacco use and the bidirectionality of tobacco product experimentation demands comprehensive tobacco control and prevention programs that address the increasingly diverse tobacco product market targeting adolescents.

Cited by 28 publications

References 40 publications

E-Cigarette Use Among University Students in Slovakia

E-Cigarette Use Among University Students in Slovakia

Further investigations of gateway effects using the PATH study

E-Zigarettenkonsum und späterer Konsum konventioneller Zigaretten

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