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Updated: May 17, 2025

Comparing the Effects of Electronic Cigarette Vapor and Cigarette Smoke in a Novel In Vivo Exposure System
Published on: May 24, 2017
Comparing smoking-related disease rates from e-cigarette use with those from tobacco cigarette use: a reanalysis of a
Peter N Lee1, Konstantinos Farsalinos2,3
1P.N.Lee Statistics and Computing Ltd, 17 Cedar Road, Sutton, SM2 5DA, UK.
Background:
A recent meta-analysis by Glantz et al. combined odds ratios (ORs) relating e-cigarette use (vaping) to cardiovascular disease, stroke, chronic obstructive pulmonary disease (COPD) and other endpoints. They assessed all included studies as having a low risk of bias, and concluded that vaping and smoking have a "comparable" disease odds, with dual use associated with more risk than smoking.
Aim:
To examine the accuracy of these conclusions, giving particular attention to myocardial infarction (MI), stroke and COPD.
Methods:
We determined (1) whether the pooled random-effect estimates were correctly calculated from the ORs included, (2) whether the detailed outcomes were correctly described and appropriate and whether additional OR estimates could have been included from the studies considered, (3) whether the data were correctly extracted from the source papers, (4) whether some studies should definitely or possibly have been excluded, (5) what the pooled OR estimates were for MI, stroke and COPD after excluding definitely invalid results and restricting attention to data based on appropriate disease definitions, (6) how estimates of the excess risk (ER = OR - 1) for vaping compare to those we estimate for quitting, (7) whether various sources of bias were adequately accounted for, and (8) whether conclusions were confirmed in studies where reverse causation was not an issue, i.e. where disease onset could not have preceded uptake of vaping.
Results:
We found no major issues regarding pooled estimation, description of diagnoses and extraction of data from the source papers, but some studies should have been excluded, and one further result was available for MI. Using data appropriately extracted for valid diagnoses, we derived pooled OR estimates for vaping vs. smoking of 0.48 (95%CI: 0.35-0.67) for MI, 0.65 (0.49-0.86) for stroke and 0.46 (0.35-0.60) for COPD. These showed a significantly reduced risk for vaping, similar to or lower than expected for quitting smoking for 5 to 10 years, highly relevant given the short period of vaping following earlier smoking for most study participants. For dual use vs. smoking, pooled OR estimates were 1.41 (1.18-1.68) for MI, 1.39 (1.06-1.82) for stroke and 1.32 (1.17-1.50) for COPD. The studies considered were predominantly cross-sectional so could not account for reverse causation, or for those who smoked and became dual users possibly having smoked more cigarettes or smoked for a longer period than those not doing so. Only three publications accounted for reverse causation, each using the same data source, and each found a significant effect of smoking, but not vaping, on the diseases considered.
Conclusion:
The claim in the original meta-analysis that the studies had a low risk of bias is demonstrably incorrect, and even the biased data suggests that switching to e-cigarettes may reduce disease risk similarly to quitting. Biases may also explain the somewhat higher risk observed in those who smoked and vaped than in those smoking exclusively. Very limited unbiased data found no significant effect of vaping on the diseases considered. Though more good studies are urgently needed, the conclusions of Glantz et al. are not supported by the currently available evidence.
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