Studies have examined the characteristics of individuals who use e-cigarettes, including sociodemographic and smoking characteristics, and the relationship of e-cigarette use to tobacco control policies. While most studies consider a subset of these characteristics with weak measures of regular e-cigarette use, this study uses a large, recent U.S. survey to simultaneously consider the association of each of these factors with different use measures. Data from the May 2014 Tobacco Use Supplement-Current Population Survey is supplemented with information on tobacco control policies. The prevalence of ever, current (at least 1 of the last 30 days), and regular (at least 20 of the last 30 days) e-cigarette use were 7.7%, 2.1% and 0.9%, implying that 27.0% of ever users were current users of which 45.3% were regular users. E-cigarette use varied by socio-demographic characteristics and by smoking status, and depended on the measure of use adopted. However, regardless of measures, e-cigarette use was higher among those smokers who smoked more cigarettes. The association with policies was generally weak, but we found more regular use by smokers in low tax and low tobacco control spending states. The results indicate that the user characteristics differ depending on the e-cigarette use measure. The measure of use should be carefully considered in analyzing how e-cigarette use affects cigarette use.

Introduction: Accurate estimates of e-cigarette use are needed to gauge its impact on public health. We compared the results of online and traditional, large scale surveys and provide additional estimates from the Population Assessment of Tobacco and Health (PATH) survey, with the aim of assessing the extent of variation in prevalence estimates. Materials and Methods: We searched the peer-reviewed literature for nationally representative estimates of U.S. adult e-cigarette prevalence, and developed our own estimates from waves one, two, and three of the PATH survey. We compared estimates by age, gender, cigarette smoking status, and e-cigarette use intensity both between online and traditional surveys and among the traditional surveys. Results: For specific years, online surveys generally yielded higher adult use rates than most traditional surveys, but considerable variation was found among traditional surveys. E-cigarette prevalence was greater for less intensive than for more intensive use. Levels of use were higher among current and recent former cigarette smokers than among former smokers of longer quit duration and never smokers, and by those of younger ages. Conclusions: Considerable variation in e-cigarette use estimates was observed even for a specific year. Further study is needed to uncover the source of variation in e-cigarette prevalence measures, with a view towards developing measures that best explain regular use and transitions between the use of e-cigarettes and other tobacco products.

The public health impact of nicotine vaping products (NVPs) is subject to a complex set of uncertain transitions between NVP and cigarette use. Instead, we apply an indirect method to gauge the impact of NVP use on smoking prevalence and smoking-attributable deaths (SADs) using the well-established SimSmoke tobacco control policy simulation model. Upon validating the model before NVPs were more widely used, we project a No-NVP (i.e., in the absence of NVPs) while controlling for the impact of cigarette-oriented policies. The net impact of NVPs on smoking prevalence is inferred by comparing the projected No-NVP smoking trends to corresponding trends from two US national surveys. Using the TUS-CPS estimates for the period 2012–2018, we estimate that adult smoking prevalence declined in relative terms by 9.7% (95% CI: 7.5–11.7%) for males and 10.7% (95% CI: 9.1–13.0%) for females. Compared to NHIS, smoking prevalence declined by 10.7% (95% CI: 6.8–14.6%) for males and 11.3% (95% CI: 7.4–15.6%) for females. These impacts were confined mainly to ages 18–44. Vaping-related reductions in smoking prevalence were projected to avert nearly 0.4 million SADs between 2012 and 2052. Our analysis indicates that NVP use is associated with substantial reductions in US smoking prevalence among younger adults.

Background: We model the potential impact of relaxing current nicotine vaping product (NVP) restrictions on public health in Australia. Aims and Methods: A Restricted NVP Scenario was first developed to project current smoking and vaping rates, where a U.S. smoking model was calibrated to recent Australian trends. To model less restrictive NVP policies, a Permissive NVP Scenario applied rates of switching from smoking to vaping, initiation into NVP and cigarette use, and cessation from smoking and vaping based on U.S. trends. The model measures vaping risk relative to the excess mortality rate of smoking. The public health impacts are measured as the difference between smoking- and vaping-attributable deaths (SVADs) and life years lost (LYLs) in the Restricted and Permissive NVP Scenarios. Sensitivity analysis is conducted regarding the NVP excess risk and other factors. Results: Assuming an NVP excess risk of 5% that of smoking, 104.2 thousand SVADs (7.7% reduction) and 2.05 million LYLs (17.3% reduction) are averted during 2017–2080 in the Permissive NVP Scenario compared to the Restricted NVP Scenario. Assuming 40% NVP excess risk, 70 thousand SVADs and 1.2 million LYLs are averted. The impact is sensitive to the rate at which smokers switch to NVPs and quit smoking, and relatively insensitive to the smoking initiation and NVP initiation and cessation rates. Conclusions: The model suggests the potential for public health gains to be achieved by relaxing NVP access regulations. However, the model would benefit from better information regarding the impact of NVPs on smoking under a relaxation of current restrictions. Implications: Australia has implemented a strong array of cigarette-oriented policies, but has restricted access to NVPs. The Smoking and Vaping Model offers a framework for modeling hypothetical policy scenarios. The Australian model shows the potential for public health gains by maintaining cigarette-oriented policies while relaxing the current restrictive NVP policy. Modeling results under a permissive NVP policy are particularly sensitive to the estimated rates of smoking cessation and switching to vaping, which are not well established and will likely depend on past and future cigarette-oriented policies and the specific NVP policies implemented in Australia.

Markets for nicotine vaping products (NVPs) and heated tobacco products (HTPs) have grown as these products became positioned as harm-reduction alternatives to combusted tobacco products. Herein, we present a public health decision-theoretic framework incorporating different patterns of HTP, NVP, and cigarette use to examine their impacts on population health. Our framework demonstrates that, for individuals who would have otherwise smoked, HTP use may provide public health benefits by enabling cessation or by discouraging smoking initiation and relapse. However, the benefits are reduced if more harmful HTP use replaces less harmful NVP use. HTP use may also negatively impact public health by encouraging smoking by otherwise non-smokers or by encouraging initiation or relapse into smoking. These patterns are directly influenced by industry behavior as well as public policy towards HTPs, NVPs, and cigarettes. While substantial research has been devoted to NVPs, much less is known about HTPs. Better information is needed to more precisely define the health risks of HTPs compared to cigarettes and NVPs, the relative appeal of HTPs to consumers, and the likelihood of later transitioning to smoking or quitting all products. While our analysis provides a framework for gaining that information, it also illustrates the complexities in distinguishing key factors.

Smokeless tobacco (SLT) prevalence had been declining in the US prior to 2002 but has since increased. Knowledge about the impact of tobacco control policies on SLT and cigarette use is limited. This study examines the interrelationship between policies, cigarette use, and SLT use by applying the SimSmoke tobacco control policy simulation model. Using data from large-scale Tobacco Use Supplement and information on policies implemented, US SimSmoke was updated and extended to incorporate SLT use. The model distinguishes between exclusive SLT and dual use of SLT and cigarettes, and considers the effect of implementing individual and combined tobacco control policies on smoking and SLT use, and on deaths attributable to their use. After validating against Tobacco Use Supplement (TUS) survey data through 2015, the model was used to estimate the impact of policies implemented between 1993 and 2017. SimSmoke reflected trends in exclusive cigarette use from the TUS, but over-estimated the reductions, especially among 18–24 year olds, until 2002 and under-estimated the reductions from 2011 to 2015. By 2015, SimSmoke projections of exclusive SLT and dual use were close to TUS estimates, but under-estimated reductions in both from 1993 to 2002 and failed to estimate the growth in male exclusive SLT use, especially among 18–24 year olds, from 2011 to 2015. SimSmoke projects that policies implemented between 1993 and 2017 reduced exclusive cigarette use by about 35%, dual use by 32.5% and SLT use by 16.5%, yielding a reduction of 7.5 million tobacco-attributable deaths by 2067. The largest reductions were attributed to tax increases. Our results indicate that cigarette-oriented policies may be effective in also reducing the use of other tobacco products. However, further information is needed on the effect of tobacco control policies on exclusive and dual SLT use and the role of industry.