Introduction US tobacco control policies to reduce cigarette use have been effective, but their impact has been relatively slow. This study considers a strategy of switching cigarette smokers to e-cigarette use (‘vaping’) in the USA to accelerate tobacco control progress.
Methods A Status Quo Scenario, developed to project smoking rates and health outcomes in the absence of vaping, is compared with Substitution models, whereby cigarette use is largely replaced by vaping over a 10-year period. We test an Optimistic and a Pessimistic Scenario, differing in terms of the relative harms of e-cigarettes compared with cigarettes and the impact on overall initiation, cessation and switching. Projected mortality outcomes by age and sex under the Status Quo and E-Cigarette Substitution Scenarios are compared from 2016 to 2100 to determine public health impacts.
Findings Compared with the Status Quo, replacement of cigarette by e-cigarette use over a 10-year period yields 6.6 million fewer premature deaths with 86.7 million fewer life years lost in the Optimistic Scenario. Under the Pessimistic Scenario, 1.6 million premature deaths are averted with 20.8 million fewer life years lost. The largest gains are among younger cohorts, with a 0.5 gain in average life expectancy projected for the age 15 years cohort in 2016.
Conclusions The tobacco control community has been divided regarding the role of e-cigarettes in tobacco control. Our projections show that a strategy of replacing cigarette smoking with vaping would yield substantial life year gains, even under pessimistic assumptions regarding cessation, initiation and relative harm.
- electronic nicotine delivery devices
- end game
- harm reduction
- public policy
This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Statistics from Altmetric.com
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.
Contributors DTL wrote most of the original paper. DBA and DTL conceived the original idea. ZY and YL conducted the analysis and helped write up the methods and results section. RB, RM, TRH, RJO’C, MLG and RN helped with the writing and revisions and contributed to the discussion of methodology.
Funding Funding was received by DTL, DBA, RM and RN from the National Institute on Drug Abuse, under grant R01DA036497. TRH and RM received funding from the Cancer Intervention and Surveillance Modeling Network (CISNET) of the Division of Cancer Control and Population Sciences, NCI under grant UO1-CA97450. RB, MLG, RJO’C and DTL received funding from the National Cancer Institute under grant P01-CA200512.
Competing interests MLG received a research grant from Pfizer and served as an advisory board member to Johnson & Johnson, manufacturers of smoking cessation medications. No other conflicts of interest are declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The model used in this article and a manual will be made available by Dr. Levy upon request.