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Public Health Consequences of E-Cigarettes (2018)

Chapter: 19 Modeling of E-Cigarette Use

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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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Suggested Citation:"19 Modeling of E-Cigarette Use." National Academies of Sciences, Engineering, and Medicine. 2018. Public Health Consequences of E-Cigarettes. Washington, DC: The National Academies Press. doi: 10.17226/24952.
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19 Modeling of E-Cigarette Use In Section III, the committee presented a conceptual framework of smoking transitions. The framework captures multiple hypothesized pathways by which e-cigarette use could affect combustible tobacco cigarette use. The hypothesized pathways can be used to understand both individual tobacco use trajectories and population-level effects, and include • Youth and young adults could begin using e-cigarettes and sub- sequently start using combustible tobacco cigarettes, either com- pletely switching or using both products concurrently (increasing combustible tobacco cigarette initiation). • Youth and young adults who otherwise would have begun com- bustible tobacco cigarette smoking could begin using e-cigarettes instead (reducing or delaying combustible tobacco cigarette initiation). • Adults who smoke combustible tobacco cigarettes could switch to using e-cigarettes alone or quit both products (cessation). • Adult combustible tobacco cigarette smokers could start using e-cigarettes in addition to combustible tobacco cigarettes (dual use). Some portion of these adult smokers may subsequently transition to e-cigarette use alone (cessation). • Former smokers could start using e-cigarettes and subsequently transition to combustible tobacco cigarettes (relapse) either alone or concurrently with e-cigarettes (dual use). 631

632 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES Some of these pathways will result in harms while others may confer benefits. In any population, each of these pathways may occur among both individuals and subpopulations. Thus, e-cigarette use could produce harms for some individuals while conferring benefits to others. These benefits and harms can offset each other, making it difficult to draw inferences about the net effect of e-cigarettes at the population level. Thus, to facilitate an assessment of the overall population health effect of e-cigarettes in the U.S. population as a whole, this chapter uses modeling to apply a common metric (years of life lost or gained as a measure of mortality) to these pathways as they occur simultaneously among differ- ent subgroups. Models of population dynamics have been used in tobacco con- trol for more than two decades. The 2014 Surgeon General’s report, The Health Consequences of Tobacco—50 Years of Progress, presents a summary of those models (HHS, 2014). More recently, several modeling studies have addressed the potential future impact of e-cigarettes under various assumptions, reaching different conclusions (Cherng et al., 2016; Hill and Camacho, 2017; Kalkhoran and Glantz, 2015; Levy et al., 2017; Vugrin et al., 2015). To inform their view of the likely effects of e-cigarette use at a population level, the committee employed a dynamic model of combusti- ble tobacco cigarette smoking prevalence and health effects to examine the potential impact of e-cigarettes on mortality in the U.S. population over the next few decades under various assumptions. Specifically, the com- mittee used a well-established dynamic model of tobacco control (Mendez and Warner, 2004; Mendez et al., 1998) to estimate the cumulative number of life-years lost (or gained) due to e-cigarettes during 2015–2050 and 2015–2070 under different assumptions regarding the harm of e-cigarettes compared with combustible tobacco cigarettes, and their potential effects on the initiation and cessation rates of combustible tobacco cigarettes. The results of the model are not precise forecasts, but rather simulation out- puts that inform a qualitative assessment about the potential population health impacts of e-cigarettes. MODEL The Mendez-Warner model (Mendez and Warner, 2004; Mendez et al., 1998) tracks individuals in the population from age 0 to a maximum age of 110, additionally differentiated by gender and smoking status. The number of people of age a in year t is computed by multiplying the number of people of age a – 1 in year t – 1 by the appropriate survival rate (1 − death rate). Birth cohort sizes are supplied exogenously to the model. Death rates are differentiated by year, gender, age, and smoking status. The model tracks the adult population smoking status. At age 18, indi-

MODELING OF E-CIGARETTE USE 633 viduals are characterized as current, former, or never smokers. The defi- nition of an adult current smoker is consistent with that of the National Health Interview Survey (NHIS)—those who have smoked at least 100 cigarettes in their lifetime and are smoking now every day or some days. In this model, adult initiation is measured by the proportion of the popu- lation who are current smokers at age 18. Youth smoking history before age 18 is subsumed in the adult initiation measure. Subsequently, current smokers in any given year are estimated as the number of current ­ mokers s in the previous year who survived to the current year and did not quit smoking. Former smokers are those who were former smokers the previ- ous year and did not die, plus those who were current smokers the pre- vious year and did not die, but quit. The model differentiates former s ­ mokers up to 30 years abstinent, and years-since-quitting−specific death rates are applied accordingly to those individuals. Smoking prevalence for any specific age group in a specific year is com- puted by taking the ratio of current smokers to the total number of people within the group that year. Baseline cessation rates were estimated within the model using the NHIS and the National Survey on Drug Use and Health data for the period 1990–2014. The model uses permanent quit rates, that is, quitting net of relapse, so that these rates are smaller than those used in models that include quits that eventually result in relapse. The model is calibrated periodically, and is tracking with excellent accuracy the over- all adult smoking prevalence in the United States. At the model baseline (2014), e-cigarette use among working adults was 3.8 percent (Syamlal et al., 2016). However, the model considers that e-cigarette use may increase combustible tobacco cigarette initiation among non-smokers and may also promote cessation among dual users. Thus, the effects of increased e-cigarette prevalence are subsumed in the assumptions of increases in both cessation and initiation of combustible tobacco cigarettes. The model does consider gender differences (e.g., relative risks and death rates), although the committee applied the same values to men and women for some parameters (e.g., background cessation rates). The model uses age, gender, and smoking-status−specific death rates, derived from data from the Cancer Prevention Study II. The model assumes that no smoking- related deaths occur before age 35. MODELING ASSUMPTIONS In the model, the committee assumes that the introduction of e-cigarettes has the potential to increase smoking initiation among young adults, and smoking cessation among adults. The committee also assumes that e-cigarettes are not harmless, and that e-cigarette use increases the risk of mortality over that of a non-vaper, non-smoker individual. At the

634 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES same time, the risk of mortality among e-cigarette users is lower than that among combustible tobacco cigarette smokers. Dual users are treated as current smokers in terms of risk but also as having a different cessation rate than non-vaper smokers. To be conservative, dual users who quit are assumed to continue using e-cigarettes for the rest of their lives and are given a reduction of risk consistent with the direct harm effect assumed for e-cigarettes. For example, if we assume that e-cigarettes are 10 percent as harmful as cigarettes, a dual user who quits smoking will be given 90 percent of the reduction in risk that a non-vaper quitter would attain as a former smoker. The committee’s assumptions about possible effects on smoking initiation among young adults, smoking cessation among adults, and the harm of e-cigarettes in relation to combustible tobacco cigarettes are informed by the committee’s review of the literature presented in the preceding chapters. Some of the parameters were also chosen to provide an extreme upper limit for the harmful effects of e-cigarettes and to illus- trate the level of such negative effects necessary to counterbalance the potential benefits of e-cigarettes at the population level. In particular, the simulations contain scenarios where e-cigarettes are 50 percent as harm- ful as cigarettes and/or increase initiation by 50 percent. The committee considers those scenarios to be extreme and highly unlikely. The committee considered the following specific effect levels: • E-cigarettes increase the smoking initiation rate by 0 percent, 5 percent, 10 percent, 25 percent, or 50 percent; • E-cigarettes increase the net smoking cessation rate by −5 percent, 0 percent, 5 percent, 10 percent, or 15 percent; and • E-cigarettes are 0 percent, 10 percent, 25 percent, or 50 percent as harmful as combustible tobacco cigarettes. The range of parameter values were selected according to the cri- teria described in the following sections: e-cigarette effect on initiation, e-cigarette effect on cessation, and e-cigarette harm. E-Cigarette Effect on Initiation As concluded in Chapter 16, e-cigarette use likely increases the risk of ever using combustible tobacco cigarettes among youth. However, it is unclear whether this increase in ever use results in an increased adult initiation rate. The committee decided to examine a wide range of effect levels, from no impact on initiation to a 50 percent increase in initiation. The upper limit of 50 percent implies that e-cigarettes will not only stop the currently observed downward trend in the adult initiation rate, but

MODELING OF E-CIGARETTE USE 635 that they will increase initiation from its 2015 value of 13 percent (Jamal et al., 2016) to 19.5 percent, a level not observed since 2011 (CDC, 2012). The committee considers this level extreme and very unlikely, as discussed above. E-Cigarette Effect on Cessation Recent meta-analyses including randomized controlled trials and cohort studies report an adjusted odds ratio for cessation around 0.7 (with versus without e-cigarettes); on the other hand, a recent population study (Zhu et al., 2017) reports an adjusted odds ratio of 1.65 (1.40–1.93). Taking the 2014 prevalence of dual users as 16.2 percent (Syamlal et al., 2016), a 0.7 odds ratio translates into 16.2 percent × (0.70 – 1) = −4.86 percent increase (or 4.86 percent decrease) in the overall cessation rate, while 1.65 odds ratio implies a 16.2 percent × (1.65 – 1) = 10.53 percent increase in cessation, with an upper bound of 16.2 percent × (1.93 – 1) = 15 percent. Based on these values, the committee chose to model values between −5 percent and 15 percent for the effect of e-cigarettes on the overall popula- tion cessation rate. An important note is that, as described above, the model uses per- manent quit rates (i.e., quitting net of relapse). Thus, cessation in the modeling refers to net cessation rates. In other words, a positive value indicates that more people in a population have quit smoking than non- smokers who have started/relapsed, and a negative value indicates the opposite. This net cessation statistic is not a common measure in the literature, which generally reports only a cessation rate based on the percentage of smokers who successfully quit smoking, without regard to non-active smokers at baseline who started or relapsed within a specified time period. For clarity, the committee uses the term “net cessation” when discussing the modeling. E-Cigarette Harm As concluded in previous chapters, e-cigarettes are likely to be less harmful than combustible tobacco cigarettes. Estimates of how harmful they are relative to combustible tobacco cigarettes range from 5 percent estimated by the UK Royal College of Physicians (TAG, 2008) to 30–50 percent estimated by Glantz (2016), with most agreement concentrated around the lower figure. The committee examined a wide range of values for the relative harm of e-cigarettes compared with combustible tobacco cigarettes, from 0 to 50 percent as harmful as combustible tobacco ciga- rettes. The upper limit of 50 percent was selected as an extreme and improbable value, used to set an upper limit to the potential harm of

636 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES e-cigarettes. The likelihood that e-cigarettes have none of the harm of combustible tobacco cigarettes is equally extreme and improbable. SIMULATION SCENARIOS The model runs were designed as follows: First, to establish a base case, the model was used to estimate the number of life-years lost due to smoking over the periods 2015–2050 and 2015–2070, under the assump- tion that the annual initiation and net cessation rates observed in 2015 (13 percent among young adults age 18–24 and 4.35 percent among adult s ­mokers, respectively [Jamal et al., 2016; Mendez et al., 2017]) would remain constant in the future. Then, starting in 2015, the committee increased the base initiation and net cessation rates by different per- centages that reflect the impact of e-cigarettes on those rates and again calculated the cumulative life-years lost or gained over the same periods as in the base-case scenario. As described in the model assumptions, the committee also assumed that individuals who quit smoking because of e-cigarettes will continue to use e-cigarettes for the remainder of their lives, and so they only achieve a fraction of the health benefits due to quitting combustible tobacco smoking. Finally, the committee compared the different scenarios with the base case to calculate the extra number of life-years gained or lost due to the effects of e-cigarettes. Overall, the committee considered 85 different simulation scenarios. They reflect a range of likely real-world scenarios as well as scenarios that the committee views as extreme and unlikely, for heuristic purposes. The committee only considered five cases in which e-cigarette use reduces net cessation because it chose not to increase the relative risk of death for anyone beyond that of a current smoker. That is, the differential effect of reducing the net cessation rate would be to increase the number of s ­ mokers, who would then be subject to the mortality risk of a current smoker, regardless of the harm associated with e-cigarettes. The entirety of the simulation runs is summarized in Table 19-1. RESULTS All scenarios show a decrease in combustible tobacco cigarette smok- ing prevalence, which reflect effects from past tobacco policies. Table 19-2 presents the model-estimated life-years lost during 2015–2050 due to e-cigarettes, under the assumption that e-cigarettes cause no harm directly, but their health consequences stem from their effects on initia- tion and net cessation of combustible tobacco cigarettes. The first section of the table (upper part) shows the life-years lost due to combustible tobacco cigarettes and e-cigarettes combined; the second section shows

MODELING OF E-CIGARETTE USE 637 TABLE 19-1  Summary of Simulation Runs Considered by the Committee Percent Initiation Percent Net Cessation Percent Case Increases Increases E-Cigarette Harm  1 0 0 0  2 5 0 0  3 10 0 0  4 25 0 0  5 50 0 0  6 0 5 0  7 5 5 0  8 10 5 0  9 25 5 0 10 50 5 0 11 0 10 0 12 5 10 0 13 10 10 0 14 25 10 0 15 50 10 0 16 0 15 0 17 5 15 0 18 10 15 0 19 25 15 0 20 50 15 0 21 0 0 10 22 5 0 10 23 10 0 10 24 25 0 10 25 50 0 10 26 0 5 10 27 5 5 10 28 10 5 10 29 25 5 10 30 50 5 10 31 0 10 10 32 5 10 10 continued

638 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES TABLE 19-1  Continued Percent Initiation Percent Net Cessation Percent Case Increases Increases E-Cigarette Harm 33 10 10 10 34 25 10 10 35 50 10 10 36 0 15 10 37 5 15 10 38 10 15 10 39 25 15 10 40 50 15 10 41 0 0 25 42 5 0 25 43 10 0 25 44 25 0 25 45 50 0 25 46 0 5 25 47 5 5 25 48 10 5 25 49 25 5 25 50 50 5 25 51 0 10 25 52 5 10 25 53 10 10 25 54 25 10 25 55 50 10 25 56 0 15 25 57 5 15 25 58 10 15 25 59 25 15 25 60 50 15 25 61 0 0 50 62 5 0 50 63 10 0 50 64 25 0 50

MODELING OF E-CIGARETTE USE 639 TABLE 19-1  Continued Percent Initiation Percent Net Cessation Percent Case Increases Increases E-Cigarette Harm 65 50 0 50 66 0 5 50 67 5 5 50 68 10 5 50 69 25 5 50 70 50 5 50 71 0 10 50 72 5 10 50 73 10 10 50 74 25 10 50 75 50 10 50 76 0 15 50 77 5 15 50 78 10 15 50 79 25 15 50 80 50 15 50 81 0 −5 0 82 5 −5 0 83 10 −5 0 84 25 −5 0 85 50 −5 0 the life-years lost attributable to e-cigarettes; and the third section shows the same figure as in the second section, as a fraction of the total toll of combustible cigarettes over 2015–2050. In this table, as in all subsequent tables, results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustibles. For example, under the scenario that e-cigarette use causes a decrease of 5 percent (from 4.35 percent to 4.13 percent) on the net cessation rate, and an increase of 5 percent on the initiation rate (from 13 percent to 13.65 percent), the estimated total life-years lost due to smoking (counting the extra smokers because of e-cigarettes) would be 296,067,599. Given

TABLE 19-2  Model-Estimated Life-Years Lost During 2015–2050 Due to E-Cigarettesa 640 Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 296,001,655 294,605,788 293,312,834 292,068,581 290,870,879 5% 296,067,599 294,670,840 293,377,037 292,131,976 290,933,506 10% 296,133,543 294,735,891 293,441,240 292,195,371 290,996,133 25% 296,331,375 294,931,046 293,633,848 292,385,557 291,184,015 50% 296,661,095 295,256,304 293,954,861 292,702,533 291,497,151 Life-Years Lost Due to E-Cigarettes 0% 1,395,867 0 (1,292,954) (2,537,207) (3,734,909) 5% 1,461,811 65,052 (1,228,751) (2,473,812) (3,672,282) 10% 1,527,755 130,103 (1,164,549) (2,410,417) (3,609,655) 25% 1,725,587 325,258 (971,940) (2,220,231) (3,421,773) 50% 2,055,307 650,516 (650,927) (1,903,255) (3,108,638) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.4% −0.9% −1.3% 5% 0.5% 0.0% −0.4% −0.8% −1.3% 10% 0.5% 0.0% −0.4% −0.8% −1.2% 25% 0.6% 0.1% −0.3% −0.8% −1.2% 50% 0.7% 0.2% −0.2% −0.7% −1.1% a Under the assumptions that e-cigarettes cause no harm directly and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 0% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustible tobacco cigarettes.

MODELING OF E-CIGARETTE USE 641 that approximately 50 percent of life-long smokers die prematurely of smoking-related causes, losing an average of 20 years of life, this figure translates into 14,803,380 total premature deaths over a span of 35 years, or an average of 422,954 premature deaths per year. Out of this figure, the extra toll imposed by e-cigarettes is 1,461,811 life-years lost (or 2,088 premature deaths per year), representing 0.5 percent of the total toll of smoking over the 35-year span. If, on the other hand, e-cigarettes increased net smoking cessation rates by 5 percent (4.57 percent) while still increasing initiation by 5 percent, 1,228,751 life-years would be saved in 2015–2050, representing approximately 1,755 premature deaths averted per year. Under the sce- nario of a 5 percent increase in the net smoking cessation rate due to e-cigarettes, even assuming that e-cigarettes increase the initiation rate by 50 percent (to 19.5 percent), there would still be 650,927 life-years saved by 2050. Scenarios extending outcomes through 2070 under the same assump- tions indicate worse outcomes in all scenarios compared with those through 2050. This is because, under any scenario that increases adult initiation, the benefits of increased net cessation are felt much sooner than the negative effects of increased initiation. Of note, the committee chose to keep the background rates on smoking initiation and cessation constant, to avoid forecasting future values of those parameters. In reality, current trends indicate that the adult smoking initiation rate is decreasing while the cessation rate is increasing. If those trends continue into the future, the negative effects of e-cigarettes on smoking initiation will be smaller while the positive effects on cessation will be larger. Table 19-3 illustrates this fact. It shows cumulative life-years lost (or saved) over 2015–2070. For example, assuming that e-cigarettes increase the initiation rate by one-quarter (to 16.3 percent), and the net cessation rate by 5 percent (to 4.57 percent) in 2015, around 577,000 life-years would be lost by 2070 due to e-cigarettes. However, under the same conditions, there would be 971,940 extra life-years by 2050; by 2070, this gain would be offset by the excess mortality brought by the increased initiation. The rest of the scenarios show the same results as Tables 19-2 and 19-3, considering different levels of harm associated with e-cigarettes. Tables 19-4 and 19-5 show the life-years lost by 2050 and 2070, respec- tively, under the assumption that e-cigarettes cause 10 percent of the harm of (i.e., are 90 percent less harmful than) combustible tobacco cigarettes. These tables show that, if net smoking cessation increases by 5 percent, by 2050, there would be life-years gained. The gains would range from 467,228 life-years if smoking initiation increases by 50 percent to 1,110,728 life-years if there is no increase in smoking initiation. By 2070, if net smok- ing cessation increases by 5 percent, there would be life-years gained

TABLE 19-3  Model-Estimated Life-Years Lost During 2015–2070 Due to E-Cigarettesa 642 Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 451,006,794 448,561,255 445,791,244 443,165,422 440,674,738 5% 451,693,674 449,239,108 446,460,647 443,826,916 441,328,825 10% 452,380,554 449,916,960 447,130,050 444,488,409 441,982,911 25% 454,441,193 451,950,517 449,138,260 446,472,889 443,945,172 50% 457,875,591 455,339,779 452,485,276 449,780,357 447,215,606 Life-Years Lost Due to E-Cigarettes 0% 2,445,539 0 (2,770,011) (5,395,833) (7,886,518) 5% 3,132,418 677,852 (2,100,608) (4,734,340) (7,232,431) 10% 3,819,298 1,355,705 (1,431,205) (4,072,846) (6,578,344) 25% 5,879,937 3,389,262 577,005 (2,088,366) (4,616,083) 50% 9,314,336 6,778,523 3,924,021 1,219,101 (1,345,649) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.6% −1.2% −1.8% 5% 0.7% 0.2% −0.5% −1.1% −1.6% 10% 0.8% 0.3% −0.3% −0.9% −1.5% 25% 1.3% 0.7% 0.1% −0.5% −1.0% 50% 2.0% 1.5% 0.9% 0.3% −0.3% a Under the assumptions that e-cigarettes cause no harm directly and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 0% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustible tobacco cigarettes.

TABLE 19-4  Model-Estimated Life-Years Lost During 2015–2050 Due to E-Cigarettesa Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 296,001,655 294,605,788 293,495,061 292,426,926 291,399,483 5% 296,067,599 294,670,840 293,559,410 292,490,610 291,462,534 10% 296,133,543 294,735,891 293,623,760 292,554,294 291,525,585 25% 296,331,375 294,931,046 293,816,810 292,745,345 291,714,738 50% 296,661,095 295,256,304 294,138,560 293,063,763 292,029,994 Life-Years Lost Due to E-Cigarettes 0% 1,395,867 0 (1,110,728) (2,178,862) (3,206,305) 5% 1,461,811 65,052 (1,046,378) (2,115,178) (3,143,254) 10% 1,527,755 130,103 (982,028) (2,051,494) (3,080,203) 25% 1,725,587 325,258 (788,978) (1,860,443) (2,891,050) 50% 2,055,307 650,516 (467,228) (1,542,025) (2,575,794) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.4% −0.7% −1.1% 5% 0.5% 0.0% −0.4% −0.7% −1.1% 10% 0.5% 0.0% −0.3% −0.7% −1.1% 25% 0.6% 0.1% −0.3% −0.6% −1.0% 50% 0.7% 0.2% −0.2% −0.5% −0.9% a Under the assumptions that e-cigarettes are 90 percent less harmful than combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 10% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation 643 or net cessation of combustible tobacco cigarettes.

TABLE 19-5  Model-Estimated Life-Years Lost During 2015–2070 Due to E-Cigarettesa 644 Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 451,006,794 448,561,255 446,234,477 444,031,875 441,945,525 5% 451,693,674 449,239,108 446,905,736 444,696,985 442,604,900 10% 452,380,554 449,916,960 447,576,995 445,362,095 443,264,275 25% 454,441,193 451,950,517 449,590,773 447,357,426 445,242,400 50% 457,875,591 455,339,779 452,947,068 450,682,976 448,539,275 Life-Years Lost Due to E-Cigarettes 0% 2,445,539 0 (2,326,778) (4,529,380) (6,615,731) 5% 3,132,418 677,852 (1,655,519) (3,864,270) (5,956,356) 10% 3,819,298 1,355,705 (984,260) (3,199,160) (5,296,981) 25% 5,879,937 3,389,262 1,029,517 (1,203,830) (3,318,856) 50% 9,314,336 6,778,523 4,385,812 2,121,721 (21,981) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.5% −1.0% −1.5% 5% 0.7% 0.2% −0.4% −0.9% −1.3% 10% 0.8% 0.3% −0.2% −0.7% −1.2% 25% 1.3% 0.7% 0.2% −0.3% −0.7% 50% 2.0% 1.5% 1.0% 0.5% 0.0% a Under the assumptions that e-cigarettes are 90 percent less harmful than combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 10% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustible tobacco cigarettes.

TABLE 19-6  Model-Estimated Life-Years Lost During 2015–2050 Due to E-Cigarettesa Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 296,001,655 294,605,788 293,762,024 292,951,883 292,173,826 5% 296,067,599 294,670,840 293,826,594 293,015,998 292,237,512 10% 296,133,543 294,735,891 293,891,164 293,080,114 292,301,197 25% 296,331,375 294,931,046 294,084,875 293,272,460 292,492,255 50% 296,661,095 295,256,304 294,407,727 293,593,038 292,810,683 Life-Years Lost Due to E-Cigarettes 0% 1,395,867 0 (843,764) (1,653,905) (2,431,962) 5% 1,461,811 65,052 (779,194) (1,589,790) (2,368,277) 10% 1,527,755 130,103 (714,624) (1,525,674) (2,304,591) 25% 1,725,587 325,258 (520,913) (1,333,328) (2,113,534) 50% 2,055,307 650,516 (198,061) (1,012,750) (1,795,105) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.3% −0.6% −0.8% 5% 0.5% 0.0% −0.3% −0.5% −0.8% 10% 0.5% 0.0% −0.2% −0.5% −0.8% 25% 0.6% 0.1% −0.2% −0.5% −0.7% 50% 0.7% 0.2% −0.1% −0.3% −0.6% a Under the assumptions that e-cigarettes are 75 percent less harmful than combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 25% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation 645 or net cessation of combustible tobacco cigarettes.

TABLE 19-7  Model-Estimated Life-Years Lost During 2015–2070 Due to E-Cigarettesa 646 Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 451,006,794 448,561,255 446,878,122 445,290,048 443,790,754 5% 451,693,674 449,239,108 447,552,145 445,960,546 444,458,007 10% 452,380,554 449,916,960 448,226,169 446,631,044 445,125,260 25% 454,441,193 451,950,517 450,248,241 448,642,538 447,127,019 50% 457,875,591 455,339,779 453,618,360 451,995,029 450,463,284 Life-Years Lost Due to E-Cigarettes 0% 2,445,539 0 (1,683,134) (3,271,207) (4,770,501) 5% 3,132,418 677,852 (1,009,110) (2,600,709) (4,103,248) 10% 3,819,298 1,355,705 (335,086) (1,930,211) (3,435,995) 25% 5,879,937 3,389,262 1,686,985 81,283 (1,434,236) 50% 9,314,336 6,778,523 5,057,105 3,433,774 1,902,029 Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.4% −0.7% −1.1% 5% 0.7% 0.2% −0.2% −0.6% −0.9% 10% 0.8% 0.3% −0.1% −0.4% −0.8% 25% 1.3% 0.7% 0.4% 0.0% −0.3% 50% 2.0% 1.5% 1.1% 0.8% 0.4% a Under the assumptions that e-cigarettes are 75 percent less harmful than combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 25% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustible tobacco cigarettes.

TABLE 19-8  Model-Estimated Life-Years Lost During 2015–2050 Due to E-Cigarettesa Percent Net Cessation Increases Initiation Increases Percent −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 296,001,655 294,605,788 294,190,793 293,794,957 293,417,330 5% 296,067,599 294,670,840 294,255,730 293,859,791 293,482,070 10% 296,133,543 294,735,891 294,320,666 293,924,624 293,546,811 25% 296,331,375 294,931,046 294,515,476 294,119,124 293,741,033 50% 296,661,095 295,256,304 294,840,160 294,443,290 294,064,736 Life-Years Lost Due to E-Cigarettes 0% 1,395,867 0 (414,995) (810,831) (1,188,458) 5% 1,461,811 65,052 (350,059) (745,998) (1,123,718) 10% 1,527,755 130,103 (285,122) (681,164) (1,058,977) 25% 1,725,587 325,258 (90,312) (486,664) (864,755) 50% 2,055,307 650,516 234,371 (162,498) (541,052) Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.1% −0.3% −0.4% 5% 0.5% 0.0% −0.1% −0.3% −0.4% 10% 0.5% 0.0% −0.1% −0.2% −0.4% 25% 0.6% 0.1% 0.0% −0.2% −0.3% 50% 0.7% 0.2% 0.1% −0.1% −0.2% a Under the assumptions that e-cigarettes are half as harmful as combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 50% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation 647 or net cessation of combustible tobacco cigarettes.

TABLE 19-9  Model-Estimated Life-Years Lost During 2015–2070 Due to E-Cigarettesa 648 Percent Net Cessation Increases Percent Initiation Increases −5% 0% 5% 10% 15% Life-Years Lost Due to Smoking and E-Cigarettes 0% 451,006,794 448,561,255 447,897,792 447,283,134 446,713,620 5% 451,693,674 449,239,108 448,576,373 447,962,514 447,393,860 10% 452,380,554 449,916,960 449,254,955 448,641,895 448,074,101 25% 454,441,193 451,950,517 451,290,700 450,680,036 450,114,822 50% 457,875,591 455,339,779 454,683,609 454,076,939 453,516,024 Life-Years Lost Due to E-Cigarettes 0% 2,445,539 0 (663,464) (1,278,122) (1,847,636) 5% 3,132,418 677,852 15,118 (598,741) (1,167,395) 10% 3,819,298 1,355,705 693,700 80,639 (487,155) 25% 5,879,937 3,389,262 2,729,445 2,118,781 1,553,567 50% 9,314,336 6,778,523 6,122,353 5,515,683 4,954,769 Percentage of Life-Years Lost Due to E-Cigarettes 0% 0.5% 0.0% −0.1% −0.3% −0.4% 5% 0.7% 0.2% 0.0% −0.1% −0.3% 10% 0.8% 0.3% 0.2% 0.0% −0.1% 25% 1.3% 0.7% 0.6% 0.5% 0.3% 50% 2.0% 1.5% 1.3% 1.2% 1.1% a Under the assumptions that e-cigarettes are half as harmful as combustible tobacco cigarettes and a range of assumptions about smoking initiation and net cessation. E-cigarettes = 50% × risk of combustibles. NOTE: Results shown in red text in parentheses indicate life-years saved compared with a baseline scenario of no effect of e-cigarettes on initiation or net cessation of combustible tobacco cigarettes.

MODELING OF E-CIGARETTE USE 649 under scenarios with 0 percent, 5 percent, and 10 percent increases in smoking initiation, and life-years lost if smoking increased by 25 or 50 percent. Tables 19-6 and 19-7 show the life-years lost by 2050 and 2070, respec- tively, under the assumption that e-cigarettes cause 25 percent of the mortality harm of combustible tobacco cigarettes. If e-cigarettes increase the net cessation rate by 5 percent, by 2050 there would be life-year gains, ranging from 198,061 if e-cigarettes increase the initiation rate by 50 per- cent to 843,764 if e-cigarettes have no impact on the initiation rate. Extend- ing the same scenarios to 2070, the results show that, with an increase of 5 percent in net cessation, there would be cumulative life-year gains under the 0, 5, and 10 percent increase in initiation scenarios, but life-year losses below 25 percent and 50 percent increase in initiation assumptions. Tables 19-8 and 19-9 show the life-years lost by 2050 and 2070, respec- tively, under the assumption that e-cigarettes are half as harmful as com- bustible tobacco cigarettes. If e-cigarettes increase the net cessation rate by 5 percent, by 2050 there would be life-year gains if net smoking initia- tion increases by 0, 5, 10, or 25 percent, but life-year losses if initiation increases by 50 percent. By 2070, if e-cigarettes increase the net cessation rate by 5 percent, there are life-year gains only if there are no increases in smoking initiation. SUMMARY The specific time frame and magnitude of population health effects of e-cigarettes will depend on their impact on the rates of initiation and net cessation of combustible tobacco cigarettes and their intrinsic harm. Any population health effect includes the possibility of some groups incurring harm (e.g., youth who initiate combustible tobacco cigarettes), while others benefit (e.g., adult combustible tobacco cigarette users who completely quit or reduce smoking). As with other models of population health effects of tobacco use, the effects of changing net cessation rates are seen earlier than effects of changing initiation rates, due to the lag in time for serious chronic health effects of combustible tobacco cigarettes to manifest. Under the assumption that the use of e-cigarettes increases the net cessation rate of combustible tobacco cigarette smoking among adults (i.e., the increase in permanent quitting offsets the potential relapsing of former smokers because of e-cigarettes), the modeling projects that use of these products will generate a net public health benefit, at least in the short run. The harms from increased initiation by youth will take time to manifest, occurring decades after the benefits of increased cessation are seen. However, for long-range projections (e.g., 50 years out), the net

650 PUBLIC HEALTH CONSEQUENCES OF E-CIGARETTES public health benefit is substantially less, and is negative under some sce- narios. With the range of assumptions used, the model projects that there would be net public health harm in the short and long term if the products do not increase net combustible tobacco cessation in adults. Factors that would maximize potential health benefits associated with these products include determining with more precision whether and under which conditions e-cigarettes could serve as an effective smok- ing cessation aid; discouraging their use among youth through standard tobacco control strategies, such as education and access restrictions; and increasing their safety through data-driven engineering and design. REFERENCES CDC (Centers for Disease Control and Prevention). 2012. Current cigarette smoking among adults—United States, 2011. Morbidity and Mortality Weekly Report 61(44):889–894. Cherng, S. T., J. Tam, P. J. Christine, and R. Meza. 2016. Modeling the effects of e-cigarettes on smoking behavior: Implications for future adult smoking prevalence. Epidemiology 27(6):819–826. Glantz, S. 2016. Accumulating evidence suggests e-cigs 1/3 to 1/2 as bad as cigs (maybe higher). https://tobacco.ucsf.edu/accumulating-evidence-suggests-e-cigs-13-12-bad-cigs- maybe-higher (accessed November 30, 2017). HHS (U.S. Department of Health and Human Services). 2014. The health consequences of ­ moking—50 years of progress: A report of the Surgeon General. Atlanta, GA: U.S. Depart- s ment of Health and Human Services, Centers for Disease Control and Prevention, National Center for Disease Prevention and Health Promotion, Office on Smoking and Health. Hill, A., and O. M. Camacho. 2017. A system dynamics modelling approach to assess the impact of launching a new nicotine product on population health outcomes. Regulatory Toxicology and Pharmacology 86:265–278. Jamal, A., B. A. King, L. J. Neff, J. Whitmill, S. D. Babb, and C. M. Graffunder. 2016. Current cigarette smoking among adults—United States, 2005–2015. Morbidity and Mortality Weekly Report 65(44):1205–1211. Kalkhoran, S., and S. A. Glantz. 2015. Modeling the health effects of expanding e-cigarette sales in the United States and United Kingdom: A Monte Carlo analysis. JAMA Internal Medicine 175(10):1671–1680. Levy, D. T., Z. Yuan, Y. Luo, and D. B. Abrams. 2017. The relationship of e-cigarette use to cigarette quit attempts and cessation: Insights from a large, nationally representative U.S. survey. Nicotine & Tobacco Research. https://doi.org/10.1093/ntr/ntx166 (accessed February 8, 2018). Mendez, D., and K. E. Warner. 2004. Adult cigarette smoking prevalence: Declining as ex- pected (not as desired). American Journal of Public Health 94(2):251–252. Mendez, D., K. E. Warner, and P. N. Courant. 1998. Has smoking cessation ceased? Expected trends in the prevalence of smoking in the United States. American Journal of Epidemiol- ogy 148(3):249–258. Mendez, D., J. Tam, G. A. Giovino, A. Tsodikov, and K. E. Warner. 2017. Has smoking ces- sation increased? An examination of the U.S. adult smoking cessation rate 1990–2014. Nicotine & Tobacco Research 19(12):1418–1424.

MODELING OF E-CIGARETTE USE 651 Syamlal, G., A. Jamal, B. A. King, and J. M. Mazurek. 2016. Electronic cigarette use among working adults—United States, 2014. Morbidity and Mortality Weekly Report 65(22): 557–561. TAG (Tobacco Advisory Group of the Royal College of Physicians). 2008. Ending tobacco smoking in Britain: Radical strategies for prevention and harm reduction in nicotine addic- tion. https://cdn.shopify.com/s/files/1/0924/4392/files/ending-tobacco-smoking. pdf?2801907981964551469 (accessed October 11, 2017). Vugrin, E. D., B. L. Rostron, S. J. Verzi, N. S. Brodsky, T. J. Brown, C. J. Choiniere, B. N. Coleman, A. Paredes, and B. J. Apelberg. 2015. Modeling the potential effects of new tobacco products and policies: A dynamic population model for multiple product use and harm. PLoS ONE 10(3):e0121008. https://doi.org/10.1371/journal.pone.0121008 (accessed February 8, 2018). Zhu, S. H., Y. L. Zhuang, S. Wong, S. E. Cummins, and G. J. Tedeschi. 2017. E-cigarette use and associated changes in population smoking cessation: Evidence from U.S. current population surveys. BMJ 358:j3262. https://doi.org/10.1136/bmj.j3262 (accessed Feb- ruary 8, 2018).

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Millions of Americans use e-cigarettes. Despite their popularity, little is known about their health effects. Some suggest that e-cigarettes likely confer lower risk compared to combustible tobacco cigarettes, because they do not expose users to toxicants produced through combustion. Proponents of e-cigarette use also tout the potential benefits of e-cigarettes as devices that could help combustible tobacco cigarette smokers to quit and thereby reduce tobacco-related health risks. Others are concerned about the exposure to potentially toxic substances contained in e-cigarette emissions, especially in individuals who have never used tobacco products such as youth and young adults. Given their relatively recent introduction, there has been little time for a scientific body of evidence to develop on the health effects of e-cigarettes.

Public Health Consequences of E-Cigarettes reviews and critically assesses the state of the emerging evidence about e-cigarettes and health. This report makes recommendations for the improvement of this research and highlights gaps that are a priority for future research.

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