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Updated: May 5, 2026

Comparing the Effects of Electronic Cigarette Vapor and Cigarette Smoke in a Novel In Vivo Exposure System
Published on: May 24, 2017
Evidence update on e-cigarette dependence: A systematic review and meta-analysis
Anasua Kundu1, Sherald Sanchez1, Siddharth Seth1
1University of Toronto Temerty Faculty of Medicine, Canada.
Introduction:
We conducted this review to examine the risk of e-cigarette dependence in different populations by updating the review on this topic by the National Academies of Science, Engineering, and Medicine.
Methods:
Six academic databases were searched for studies published between September 2017 and December 2023. We included peer-reviewed human, animal, cell/in vitro original studies examining associations of e-cigarette use and dependence but excluded qualitative studies. Three types of e-cigarette exposure were examined: acute, short-to-medium term, and long-term. Meta-analysis were conducted when possible. Different risk of bias tools were used for assessing quality of the included human studies.
Results:
We included 107 studies, of which 34 studies were included in the subgroup analysis. Meta-analyses showed that non-smoker current vapers had no statistically significant difference in level or prevalence of dependence compared to non-vaper current smokers and dual users. However, never smoker current vapers had a lower level of dependence (SMD -0.723, p < 0.01) compared to dual users, which was also supported by ANOVA test. Narrative review findings suggest that nicotine vapers had higher level of dependence than non-nicotine vapers and e-cigarette dependence is positively associated with nicotine concentration, frequency, and duration of use. No strong relationship was found between dependence and product types or features. Socio-demographic factor-based subgroup findings were inconclusive.
Conclusions:
The level and prevalence of e-cigarette dependence is similar to cigarette dependence. There was high variability in the definitions and methods used for defining populations and assessing dependence. Further research and monitoring are crucial.
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