Evaluating the mutual pathways among electronic cigarette use, conventional smoking and nicotine dependence

Abstract

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 (β = 0.021, P = 0.081) or through nicotine dependence (β = 0.005, P = 0.693). Conventional smoking was associated positively with later e-cigarette use, both directly (β = 0.118, P < 0.001) and through nicotine dependence (β = 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 (β = 0.604, P < 0.001) but weak for e-cigarettes (β = 0.120, P < 0.001). Nicotine dependence moderately strongly predicted later conventional smoking (β = 0.169, P < 0.001), but was a weak predictor of later e-cigarette use (β = 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.

Keywords: Cigarettes; dual product use; e-cigarettes; mediation; nicotine dependence; structural equation modeling.

Figure 1. Full path analysis model

Observed variables are shown in rectangles and unobserved variables (error terms) are shown in circles. Similar variables are presented in rows, and variables from the same assessment wave are shown in columns. Gray, curved lines represent covariances. Straight lines represent regression relationships, and are organized into categories based on line type.

Figure 2. Path analysis results

Regression coefficients are presented in proportion to line thickness (font size = 10 × β coefficient). Solid lines represent significant regression coefficients (p<.05) and dot-dash lines represent nonsignificant coefficients. For clarity, covariances and error terms are not presented here.