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/lp/springer_journal/the-us-simsmoke-tobacco-control-policy-model-of-smokeless-tobacco-and-em7dogDOM3
- Publisher
- Springer Journals
- Copyright
- Copyright © 2018 by The Author(s).
- Subject
- Medicine & Public Health; Public Health; Medicine/Public Health, general; Epidemiology; Environmental Health; Biostatistics; Vaccine
- eISSN
- 1471-2458
- DOI
- 10.1186/s12889-018-5597-0
- Publisher site
- See Article on Publisher Site
Abstract
Background: 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. Methods: 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. Results: 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. Conclusions: 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. Keywords: Smokeless tobacco, Tobacco control policies, Simulation model Background Much of that is multi-product use, of which 60% includes Adult smoking prevalence in the US declined from 26% in cigarettes [7]. 1993 to 14% in 2015 [1]. Much of that decrease can be at- Although male SLT use had declined in the US from tributed to the implementation of tobacco control policies, 4.2% in 1993 to 2.8% in 2002 [8, 9], it increased to 3.0% including smoke-free air laws, marketing restrictions, by 2011 [6, 10, 11], with snuff sales increased by 65% media campaigns, treatment and tax increases [2, 3]. [12]. SLT use has been shown to be a direct cause of oral While smoking prevalence has declined, the use of other and esophageal cancer, and may also cause heart disease, tobacco products, such as little cigars or smokeless to- gum disease and oral lesions [13]. With concerns about bacco (SLT), and of e-cigarettes has increased [4–7]. the health effects and increasing use of SLT, some states have directed policies at reducing SLT use, including in- creased SLT taxes, educational campaigns, and cessation * Correspondence: dl777@georgetown.edu treatment [14, 15]. In addition, the 2009 Family Smoking Lombardi Comprehensive Cancer Center, Georgetown University, 3300 Whitehaven St., Suite 4100, Washington DC, USA © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Levy et al. BMC Public Health (2018) 18:696 Page 2 of 17 Prevention and Tobacco Control Act (FSPTCA) autho- been developed and validated for over 25 nations and 8 rized the Food and Drug Administration to regulate the states with a wide range of different policy changes [2, marketing, promotion and sale of cigarettes and SLT. 18–26]. Policies directed at reducing SLT use may also impact The SimSmoke model is extended here to incorporate cigarette use. For example, cigarette use may increase if SLT use, distinguishing between exclusive SLT and dual youth and young adults initiate smoking instead of SLT (both cigarette and SLT) use. We consider the effect of or if smokers are discouraged from using SLT to help tobacco control policies implemented between 1993 and quit cigarette use. However, SLT-oriented policies could 2017 on cigarette and SLT use and on the deaths attrib- reduce cigarette use if the two tend to be used together uted to that use. (i.e. dual use) and the policies encourage cessation, or if SLT acts as a gateway to cigarette smoking. Similarly, Methods policies directed at reducing cigarette use may discour- The model begins with the 1993 population distin- age SLT use if the two are used together or may encour- guished by age and gender and further distinguished as age SLT use if SLT is used as a cigarette substitute. never tobacco users, and both current and former users Policy evaluations have provided limited information on among exclusive cigarette, exclusive SLT, and dual users. their effects [15]. Knowledge of the policy impacts can As shown in Fig. 1, cigarette and SLT use age change help to better design policies towards SLT use, and may over time through modules for population, tobacco use, have implications for other nicotine delivery products, tobacco-attributable deaths and separate modules for such as e-cigarettes [16]. each policy. This paper employs simulation modeling to examine the inter-relationship of tobacco control policies and Population patterns of cigarette and SLT use. We adopt the Population data were obtained by single age (0 through well-established SimSmoke simulation model [2, 3]. The 85) from the Census Bureau for 1993–2013 [27–29] and model incorporates population and smoking dynamics for 2016–2067 [30] from the Census Bureau’s Population and focuses on the major cigarette-oriented tobacco Projections Program. Starting with the population in control policies, including taxes, smoke-free air laws, 1993, the population evolves through births, deaths and media campaigns, marketing restrictions, cessation treat- net immigration, with births up to age 14 based on the ment policies and youth access enforcement. SimSmoke obtained population data and older age groups subject has been used for advocacy and planning purposes to mortality rates from the CDC [31]. Mortality rates by examine the impact of past and projected future policies age and gender were averaged by age group over the individually and in combination [17]. The model has years 1999 through 2013 and then smoothed using Fig. 1 Components of the SimSmoke Smokeless Model Levy et al. BMC Public Health (2018) 18:696 Page 3 of 17 3-year (ages 0–3), 5-year (ages 4–24), and 10-year (ages estimate quit rates for exclusive SLT and dual users were 25–80) moving averages and extrapolated to age 85. not available from the TUS, we considered previous lit- Population predictions were adjusted by net migration erature. Studies [40–42] generally found that quit rates rates (2014–2020 average) from the Census Bureau [32], were at least as high among SLT as cigarette users. With and calibrated to Census projections. some exceptions [43], studies obtained similar quit rates for dual users and exclusive smokers [42, 44, 45]. Quit Tobacco use rates were set the same for dual and exclusive SLT users Individuals evolve from never tobacco users to current as for all smokers. Age- and gender-specific relapse rates tobacco users through smoking and SLT initiation. To- by years quit were based on the rates for smokers [46– bacco users become former users through quit rates, but 49]. Finally, since studies indicated limited switching be- may return to their prior tobacco use state through re- tween SLT and cigarettes, except at younger ages [40– lapse. A discrete time, first order Markov process was 42], switching only occurred through net initiation. assumed for these transitions. Baseline estimates of exclusive smoking, exclusive SLT Tobacco-attributable deaths and dual use status by age and gender were obtained Relative risk estimates for current and former smokers from the nationally-representative 1992/3 Tobacco Use by age and gender were based on the Cancer Prevention Supplement (TUS) of the Current Population Survey Study II [48, 50, 51], as in previous US SimSmoke [33]. Current smokers were defined as individuals who models [2, 3]. Relative risks for dual users may be less have smoked more than 100 cigarettes in their lifetime than for exclusive smokers due to reduced quantity and currently smoke cigarettes either daily or on some smoked [43], but studies have found similar risks [52, days A question was asked regarding whether the indi- 53] except with large quantity reductions [54]. We vidual “regularly” used SLT. Those regular SLT users assigned the same risks to exclusive cigarette and dual were further distinguished as dual users (with cigarette users, so that risks decline at the same rate with years use) and exclusive SLT users. Former users were defined since quitting [48, 50, 51]. We estimate an exclusive SLT as those who met the respective definitions for use, but relative mortality risk of 1.15 based on a large-scale US reported no current use. Former smokers were split into study [55]. exclusive smokers and former dual users using the To obtain smoking-attributable deaths, the number of age-specific ratio of exclusive smokers and dual users, exclusive smokers at each age is multiplied by the excess and former exclusive SLT users were estimated by the mortality risks (exclusive smokers death rate minus ratio of former to current smokers. Former exclusive never smokers death rate) to obtain attributable deaths smokers and dual users were distinguished by years by age, and then summed over ages. The same proced- since quitting (< 1, 1, 2 …, 15, > 15 years). Since former ure was applied to former exclusive smokers and SLT users were not asked about years since quitting, the summed over current and former smokers. Separate esti- initial percentages were assumed the same as for former mates were derived in the same way for exclusive SLT smokers. and for dual users. Because evidence on initiation and early transitions to SLT use from the literature was mixed [34–38] and be- Policies cause the TUS did not provide such information, we The model was initialized with 1993 policy levels, and employed a measure of net initiation, whereby initiation incorporates US and state policy changes occurring be- was measured for each of the three user groups as the tween 1993 and 2017. Policy descriptions and effect sizes difference between the base year prevalence at a given are shown in Table 1. Policies are generally modelled as age and base year prevalence at the previous age. having immediate effects on prevalence rates and on- Thereby, this measure incorporates initiation, cessation going effects through initiation and cessation rates. and switching between tobacco products, similar to pre- When more than one policy is in effect, the effects are vious SimSmoke models without the ability to switch multiplicatively applied as percent changes, subject to products [2, 3]. This method ensures stability and in- synergies (e.g., through publicity from media campaigns, ternal consistency of the model. We allowed for initi- see Table 1). ation through age 30 for males and age 27 for females, In the tax module [56], prices were modeled as having the respective ages when net initiation for all three user constant proportional effects (i.e., constant price elastici- groups began to decline. Cessation occurs after the last ties) with respect to price, as derived from demand stud- age of net initiation. ies. Based on previous reviews [56, 57], the model Data on smoker quit rates were obtained from the assigns a prevalence elasticity for exclusive cigarette and TUS, measured as those who quit in the last year, but dual use of − 0.4 through age 17; − 0.3 for ages 18 to 24; not the last 3 months [39]. Since sufficient data to − 0.2 for ages 25 to 34; − 0.1 for ages 35 to 64; and − 0.2 Levy et al. BMC Public Health (2018) 18:696 Page 4 of 17 Table 1 Policy Inputs for Cigarette and Smokeless Tobacco in SimSmoke Simulation Model Policy Description Cigarette Effect Size Smokeless Tobacco Effect Size Tax Policies [56, 67, 98, 99] Cigarette price/tax Elasticities The effect of taxed is directly incorporated −0.4 ages 10–17 Same through average US price (including generics), with separate prices for cigarette and SLT. − 0.3 ages 18–24 Same The price elasticity is used to convert the % − 0.2 ages 25–34 Same price changes into effect sizes. The dual price is computed as 4/5 of the cigarette − 0.1 ages 35–64 Double price + 1/5 SLT price − 0.2 ages 65 Same Smoke-Free Air Policies [62] Worksite smoking ban Ban in all indoor worksites, with strong −6% One-fourth public acceptance and enforcement of laws (reduced by 1/3 if allowed in ventilated areas and by 2/3 if allowed in common areas) Restaurant smoking ban Ban in all indoor restaurants (reduced by −2% One-fourth half if partial) Bars smoking ban Ban in all indoor (reduced by half if partial) −1% One-fourth Other place bans Ban in 3 out of 4 government buildings, retail −1% One-fourth stores, public transportation, and elevators Enforcement Government agency enforces the laws Effects reduced 50% absent Same enforcement Mass Media Campaigns [65] High publicity media campaign Campaign publicized heavily on TV and at −6.5% Half least some other media, with a social marketing approach Moderate publicity media campaign Campaign publicized sporadically on TV and −3.25% Half at least some other media Low publicity media campaign Campaign publicized only sporadically −1.625% Half in newspaper, billboard, or some other media Marketing Restrictions [67, 68] Comprehensive marketing ban Ban is applied to television, radio, print, −5% prevalence,-8% initiation, Same billboard, in-store displays, sponsorships + 4% cessation and free samples (all indirect marketing) Moderate advertising ban Ban is applied to all media (television, −3% prevalence,-4% initiation, Same radio, print, billboard) plus one indirect + 2% cessation marketing medium Weak advertising ban Ban is applied to some television, radio, −1% prevalence and initiation Same print, and billboard only Enforcement Government agency enforces the laws Effects reduced 50% absent Same enforcement Health Warnings [69] Strong Labels are large, bold and graphic, and −4% prevalence, −2% initiation, Same cover at least 30% of pack + 10% cessation Moderate Laws cover 1/3 of package, not bold −2% prevalence & initiation, Same or graphic + 2% cessation Weak Laws cover less than 1/3 of package, not − 1% prevalence & initiation, Same bold or graphic + 2% cessation Cessation Treatment Policies [70] Availability of pharmacotherapies Legality of nicotine replacement therapy, −1% prevalence, + 6% cessation Half Wellbutrin and varenecline Proactive quitline A proactive quitline with publicity −1% prevalence, + 8% cessation Half throughout the media campaign with no cost nicotine replacement therapy Levy et al. BMC Public Health (2018) 18:696 Page 5 of 17 Table 1 Policy Inputs for Cigarette and Smokeless Tobacco in SimSmoke Simulation Model (Continued) Policy Description Cigarette Effect Size Smokeless Tobacco Effect Size Subsidization pharmacotherapy Payments to cover pharmacotherapy −2.25% prevalence, + 12% cessation Half and behavioral cessation treatment Brief health care provider Advice by health care provider to quit −1% prevalence, + 8% cessation Half interventions and methods provided All of the above Complete availability and reimbursement −5.2% prevalence, + 43% cessation Half of pharmaco- and behavioral treatments, quitlines, and brief interventions Youth Access Restrictions [75] Strongly enforced Compliance checks are conducted 4 −16% initiation and prevalence for Half times per year per outlet, penalties are ages 16–17 and − 24% ages < 16 potent and enforced with heavy publicity Well enforced Compliance checks are conducted − 8% initiation and prevalence for Half regularly, penalties are potent, and ages 16–17 and − 12% ages < 16 publicity and merchant training are included Low enforcement Compliance checks are conducted −2% initiation and prevalence for Half sporadically, penalties are weak ages 16–17 and − 3% ages < 16 Vending machine restrictions Total ban Enforcement effects increase by 8% Half Self-service restrictions Total ban Enforcement effects increase by 4% Half Publicity Media campaigns directed at youth use Enforcement effects increase by 10% Half Unless otherwise indicated, the effects are in terms of the reduction in prevalence during the first year, the reduction in initiation, and increase in first year quit rates during the years that the policy is in effect Effect sizes are relative to cigarette effect sizes and applied to exclusive cigarette use only unless otherwise indicated Elasticities translate into effect sizes through percentage change in price Effect size differs for exclusive SLT and for dual use for age 65 and older. Price elasticities for adult SLT use sizes were set at 25% those of cigarettes. Data on state have generally ranged from − 0.2 to − 0.8 [15]. The price level smoke-free air laws [63] were weighted by state prevalence elasticities for exclusive SLT use were esti- smoker populations. The enforcement level was set at mated at − 0.4 for those through age 17, − 0.3 for ages 80% for all years, as previously developed for US 18–24, and − 0.2 for ages 25 and above. Cigarette prices SimSmoke [2, 3]. were measured by national average cigarette retail prices SimSmoke evaluates media campaigns in terms of over- (including generics) [58] for 1993–2014 with the 2014 all tobacco control expenditures, much of which are for price adjusted upward for 2015–2017 to reflect state media campaigns [64]. They are categorized as high, level tax increases as weighted by the state population. medium, or low levels [65]. Studies have generally found The national average retail prices and manufacturer tax SLT-oriented educational campaigns effective in redu- for SLT products through 2014 were measured by the cing youth and adults and adult use [15], but due to re- state retail prices and manufacturer taxes weighted by duced emphasis on SLT as compared to the SLT smoker population [59], using manufacturer cigarette-oriented campaigns, exclusive SLT and dual ef- sales and quantity shipped in pounds [60], tax data [61], fect sizes were set at 50% that of cigarettes. State per estimated weights per unit [60], and estimated capita expenditures [66] were categorized by levels and mark-ups. We adjusted the 2014 price upward for 2015– weighted by the state smoker population, and were ini- 2017 by the state population-weighted tax increase. For tially categorized as low level in 1993 increasing to SLT users, we used a weighted price, with weights of medium level by 2004. 80% of the cigarette price and 20% of SLT price [59]. All SimSmoke considers restrictions on both direct and in- prices were deflated by the consumer price index to ad- direct marketing [67, 68]. While no studies have directly just for price inflation. examined the relationship of marketing restrictions to SimSmoke considers worksites, restaurants, pub and SLT use, awareness of and exposure to SLT advertise- bars, and other public places laws, and the role of en- ments has been associated with increased use [15]. SLT forcement [62]. Studies of SLT use have found a negative and dual use were assigned the same policy effect sizes relationship to smoke-free air laws [15]. Based on these as for cigarettes. Restrictions on advertising for both findings and since smoke-free air laws are not explicitly SLT and cigarette use were set at a minimal level from directed at SLT use, exclusive SLT and dual use effect 1993 to 2009, reflecting an earlier media advertising ban, Levy et al. BMC Public Health (2018) 18:696 Page 6 of 17 with enforcement set at 90% [2]. In 2010, they were in- mid-level since 2003 [6]. Levels for vending machine creased to 25% moderate and 75% minimal, reflecting bans were set at 50% beginning in 1993 [80]increas- added 2009 FSPTCA restrictions on sponsorships and ing to 75% by 2000, and for self-service bans were set coupons, and in publications. at 50% beginning in 1995. Both vending machine and The effectiveness of health warnings depends primarily self-service bans were increased to 100% in 2010, on their size and whether they include graphics [69]. reflecting requirements under the 2009 FSPTCA. Limited effectiveness has been found for text-only warn- ings on SLT packages, but pictorial warnings were asso- Validation ciated with less susceptibility to SLT use among youth To validate the model, we compared predicted cigarette and greater interest in cessation among adults [15]. We and SLT prevalence rates (that incorporate policy assume the same effect of SLT warnings on exclusive changes) to the comparable use rates estimated from the SLT and dual use as for cigarette warnings on cigarette 2002, 2010/11 and 2014/15 TUS surveys. Because use. Health warnings for cigarettes have been minimal screening questions on SLT use in the TUS changed since 1966. However, since 2010, SLT packaging is re- from “regular use” to days use, current users from 2002 quired to display large text warnings covering at least onward were defined as individuals currently using SLT 30% of two principal sides of the package, larger than at least 10 days in the last month [81]. For the years cigarette warnings. SLT warnings were assigned a min- 2002, 2010/11 and 2014/15, we considered whether imal level until 2009 and a moderate level since 2010. SimSmoke predictions were within the 95% confidence Cessation treatment policy includes brief interven- intervals (CI) from the TUS, assuming a binomial distri- tions, pharmacotherapy availability, financial coverage of bution for each use category. We also compared the treatments, and quitlines. [70] Reviews of randomized relative change in prevalence rates from SimSmoke to trials of pharmacological SLT interventions found mixed those from the TUS by sub-periods (1993–2002, 2002– effects [13, 71, 72] and have also found behavioral inter- 2011, and 2011–2015) and overall (1993–2015). ventions to promote quitting among SLT users [15]. However, SLT users currently use these resources at low The effect of past tobacco control policies rates [73]. Compared to exclusive smokers, cessation Upon validating the model, we estimated the effect of treatment policies were assigned 50% the effect on SLT policies on tobacco prevalence and tobacco-attributable users, but 100% of the effect on dual users. The levels of deaths. First, we programmed SimSmoke with all policies cessation treatment use were based on previous versions remaining at their 1993 levels to estimate the counter- of US SimSmoke [2, 3, 70]. Treatment coverage was initi- factual without any policies implemented. We then sub- ated in stages beginning with minimal in 1997 increasing tracted estimates incorporating all implemented policies to moderate by 2007 [74]. A national (active) quitline from those for the counterfactual in order to estimate was implemented at 25% capacity beginning in 2003 in- the net reductions due to the policies implemented since creasing in stages to 100% by 2007 [74]. Brief interven- 1993. The contribution of individual policies were esti- tions were set at a level of 50% for all years. Most states mated by reprogramming SimSmoke to only allow for currently have provisions for SLT advice and treatment, the change in that policy while holding other policies and consequently the policy levels were set the same as constant, which was compared to the counterfactual for cigarettes. with no policies implemented. The relative reductions Youth access enforcement include enforcement, and for each policy were measured relative to the summed restrictions on vending machines and self-service. effects of all policies, since the effects with multiple pol- Strongly enforced and publicized youth access laws icies depend on assumed synergies and do not sum to yield a larger reduction in youth smoking initiation one. for 10–15 year-olds than for 16–17 year-olds, further enhanced by vending machine and self-service bans Results [75]. Two studies of youth SLT use [76, 77]found Predictions of smoking and SLT prevalence from 1993 to youth access policies affected SLT use, although the 2014/15 effect was weak, and two studies [78, 79]found lower SimSmoke predictions for 1993 to 2015 incorporating compliance rates for SLT than cigarette purchases. policy changes and estimated smoking prevalence from Youth access policy effect sizes for exclusive SLT use TUS are shown for exclusive cigarette, dual and exclu- were assigned 50% of the effect sizes for cigarettes, sive SLT users in Table 2. while the effects on dual use were assigned the same For the adult population (ages 18 and above), SimS- effect sizes as for exclusive cigarette use. Enforcement moke predicted that exclusive male (female) cigarette levels for both SLT and cigarettes were set at none prevalence fell from 25.6% (22.1%) in 1993 to 14.2% before 1997, at low-level from 1998 to 2002 and at (12.4%) in 2015, while the TUS showed a decline from Levy et al. BMC Public Health (2018) 18:696 Page 7 of 17 Table 2 Validation: Exclusive Cigarette, Dual and Exclusive SLT Use, SimSmoke Projections vs.Tobacco Use Supplement, by Age and Gender, 1993–2015 EXCLUSIVE CIGARETTE USE a a a a Ages Source 1993 2002 Relative change 2011 Relative change 2015 Relative change Relative change 1993–2002 2002–2011 2011–2015 1993–2015 Male 18+ SimSmoke 25.6% 20.2% −21.3% 15.4% −23.5% 14.2% −8.2% −44.7% CPS-TUS 25.7% 22.0% −14.1% 17.1% −22.5% 14.9% −12.6% −41.8% 95% CI (21.7, 22.4%) (16.8, 17.4%) (14.7, 15.2%) 18–24 SimSmoke 25.1% 20.4% −18.7% 17.0% −16.4% 16.9% −1.0% −32.8% CPS-TUS 25.5% 26.8% 5.4% 18.7% −30.2% 15.6% −16.7% −38.7% 95% CI (25.7, 28.0%) (17.8, 19.7%) (14.6, 16.6%) 25–34 SimSmoke 29.0% 23.9% −17.6% 20.2% −15.4% 19.3% −4.4% −33.3% CPS-TUS 29.0% 24.2% −16.6% 21.2% −12.5% 18.0% −15.2% −38.1% 95% CI (23.4, 25.0%) (20.5, 21.9%) (17.3, 18.7%) 35–54 SimSmoke 29.5% 22.0% −25.2% 15.7% −28.8% 14.1% −10.1% −52.1% CPS-TUS 29.6% 25.5% −13.8% 19.2% −24.9% 16.7% −12.9% −43.6% 95% CI (24.9, 26.1%) (18.7, 19.6%) (16.2, 17.2%) 55+ SimSmoke 17.4% 14.9% −14.4% 11.7% −21.0% 10.4% −11.5% −40.1% CPS-TUS 17.5% 14.5% −17.0% 12.7% −12.4% 12.2% −4.2% −30.3% 95% CI (14.0, 15.0%) (12.3, 13.1%) (11.8, 12.6%) Female 18+ SimSmoke 22.1% 17.3% −21.4% 13.4% −22.5% 12.4% −7.7% − 43.8% CPS-TUS 22.3% 18.1% −18.6% 14.3% −21.1% 12.8% −10.9% −42.7% 95% CI (17.9, 18.4%) (14.1, 14.5%) (12.5, 13.0%) 18–24 SimSmoke 23.6% 19.5% −17.5% 16.3% −16.3% 16.1% −1.1% −31.7% CPS-TUS 23.8% 23.3% −2.2% 15.5% −33.5% 12.1% −22.0% −49.2% 95% CI (22.3, 24.3%) (14.7, 16.4%) (11.3, 13.0%) 25–34 SimSmoke 27.3% 20.9% −23.5% 17.6% −15.8% 16.8% −4.6% −38.6% CPS-TUS 27.6% 20.1% −27.1% 17.2% −14.7% 15.0% −12.9% −45.9% 95% CI (19.5, 20.8%) (16.6, 17.8%) (14.4, 15.6%) 35–54 SimSmoke 25.1% 19.5% −22.2% 14.2% − 27.1% 12.7% −10.7% −49.4% CPS-TUS 25.1% 21.8% −13.1% 17.2% −20.9% 15.6% −9.6% −37.9% 95% CI (21.3, 22.2%) (16.8, 17.6%) (15.2, 16.0%) 55+ SimSmoke 14.4% 12.1% −15.6% 9.8% −18.9% 9.1% −7.8% − 36.9% CPS-TUS 14.8% 11.4% −22.5% 10.1% −12.2% 9.8% −2.2% −33.4% 95% CI (11.0, 11.8%) (9.7, 10.4%) (9.5, 10.1%) Dual use Male 18+ SimSmoke 1.0% 0.9% −14.6% 0.7% −16.4% 0.7% −5.7% −32.6% CPS-TUS 1.0% 0.5% −47.0% 0.5% −11.4% 0.5% 0.0% −53.0% 95% CI (0.5, 0.6%) (0.4, 0.5%) (0.4, 0.5%) 18–24 SimSmoke 2.2% 1.5% −33.5% 1.3% −8.8% 1.3% −0.3% −39.5% CPS-TUS 2.3% 1.1% −52.0% 1.1% 0.5% 1.1% 0.0% −51.7% 95% CI (0.8, 1.4%) (0.9, 1.4%) (0.8, 1.4%) 25–34 SimSmoke 1.4% 1.4% 0.7% 1.0% −31.9% 0.9% −1.7% −32.6% Levy et al. BMC Public Health (2018) 18:696 Page 8 of 17 Table 2 Validation: Exclusive Cigarette, Dual and Exclusive SLT Use, SimSmoke Projections vs.Tobacco Use Supplement, by Age and Gender, 1993–2015 (Continued) EXCLUSIVE CIGARETTE USE a a a a Ages Source 1993 2002 Relative change 2011 Relative change 2015 Relative change Relative change 1993–2002 2002–2011 2011–2015 1993–2015 CPS-TUS 1.4% 1.0% −31.0% 0.8% −17.8% 0.9% 7.6% −39.0% 95% CI (0.8, 1.1%) (0.7, 1.0%) (0.7, 1.0%) 35–54 SimSmoke 0.8% 0.8% 5.8% 0.8% −1.9% 0.7% −8.8% −5.4% CPS-TUS 0.8% 0.5% −40.5% 0.5% 6.7% 0.5% 10.4% −30.0% 95% CI (0.4, 0.5%) (0.4, 0.6%) (0.4, 0.6%) 55+ SimSmoke 0.5% 0.4% −23.9% 0.3% −14.8% 0.3% −0.2% −35.3% CPS-TUS 0.5% 0.2% −64.3% 0.2% −11.1% 0.1% −6.7% −70.4% 95% CI (0.1, 0.2%) (0.1, 0.2%) (0.1, 0.2%) Female 18+ SimSmoke 0.05% 0.03% −33.3% 0.02% −32.4% 0.02% −13.2% −60.9% CPS-TUS 0.05% 0.02% −62.5% 0.01% −44.3% 0.02% 100.0% −58.2% 95% CI (0.01, 0.03%) (0.01, 0.02%) (0.01, 0.03%) 18–24 SimSmoke 0.05% 0.03% −32.2% 0.03% −9.1% 0.03% −0.48% −38.7% CPS-TUS 0.05% 0.01% −77.1% 0.08% 555.7% 0.02% −75.0% −62.5% 95% CI (0.00, 0.03%) (0.04, 0.18%) (0.00, 0.10%) 25–34 SimSmoke 0.03% 0.03% −2.6% 0.02% −33.4% 0.02% −2.8% − 36.9% CPS-TUS 0.02% 0.02% −6.3% 0.02% −9.9% 0.01% −50.0% −57.8% 95% CI (0.00, 0.04%) (0.01, 0.06%) (0.00, 0.05%) 35–54 SimSmoke 0.06% 0.03% −49.1% 0.02% −42.7% 0.01% −18.6% −76.3% CPS-TUS 0.06% 0.02% −69.0% 0.01% −43.2% 0.03% 200.0% −47.2% 95% CI (0.00, 0.03%) (0.00, 0.03%) (0.01, 0.05%) 55+ SimSmoke 0.05% 0.04% −26.3% 0.02% −34.0% 0.02% −19.5% −60.8% CPS-TUS 0.05% 0.02% −66.6% 0.00% −100.0% 0.01% … −81.0% 95% CI (0.00, 0.03%) (0.00, 0.02%) (0.00, 0.03%) Exclusive smokeless tobacco use Male 18+ SimSmoke 3.2% 2.8% −13.6% 2.5% −9.3% 2.4% −3.3% −24.2% CPS-TUS 3.1% 2.3% −27.1% 2.5% 8.0% 2.6% 6.5% −16.1% 95% CI (2.1, 2.4%) (2.3, 2.6%) (2.5, 2.7%) 18–24 SimSmoke 4.9% 3.6% −26.9% 3.8% 5.9% 3.8% 0.5% −22.2% CPS-TUS 5.0% 1.8% −63.5% 2.3% 28.2% 2.9% 24.0% −42.0% 95% CI (1.5, 2.2%) (2.0, 2.8%) (2.5, 3.4%) 25–34 SimSmoke 4.1% 3.9% −4.5% 3.2% −16.9% 3.3% 3.2% −18.1% CPS-TUS 4.2% 3.6% −14.2% 3.0% −17.4% 3.0% 3.1% −27.0% 95% CI (3.2, 3.9%) (2.7, 3.3%) (2.8, 3.4%) 35–54 SimSmoke 2.3% 2.5% 4.8% 2.6% 4.2% 2.4% −5.0% 3.7% CPS-TUS 2.3% 2.2% −4.1% 3.1% 42.1% 3.4% 9.4% 49.0% 95% CI (2.0, 2.4%) (2.9, 3.3%) (3.2, 3.6%) 55+ SimSmoke 2.7% 2.0% −25.6% 1.4% −27.2% 1.4% −6.0% −49.0% CPS-TUS 2.7% 1.8% −36.0% 1.6% −9.9% 1.7% 9.5% −36.8% 95% CI (1.6, 1.9%) (1.4, 1.7%) (1.6, 1.9%) Levy et al. BMC Public Health (2018) 18:696 Page 9 of 17 Table 2 Validation: Exclusive Cigarette, Dual and Exclusive SLT Use, SimSmoke Projections vs.Tobacco Use Supplement, by Age and Gender, 1993–2015 (Continued) EXCLUSIVE CIGARETTE USE a a a a Ages Source 1993 2002 Relative change 2011 Relative change 2015 Relative change Relative change 1993–2002 2002–2011 2011–2015 1993–2015 Female 18+ SimSmoke 0.4% 0.2% −42.7% 0.1% −39.3% 0.1% −16.4% −70.9% CPS-TUS 0.4% 0.2% −60.4% 0.1% −42.4% 0.1% 0.0% −77.2% 95% CI (0.1, 0.2%) (0.1, 0.1%) (0.1, 0.1%) 18–24 SimSmoke 0.1% 0.1% −24.5% 0.1% 5.5% 0.1% 0.6% −19.8% CPS-TUS 0.1% 0.0% −62.4% 0.1% 86.9% 0.1% −12.5% −38.5% 95% CI (0.0, 0.1%) (0.0, 0.2%) (0.0, 0.2%) 25–34 SimSmoke 0.1% 0.1% −24.1% 0.1% −10.4% 0.1% 2.9% −30.0% CPS-TUS 0.1% 0.1% −20.0% 0.1% −48.8% 0.1% 66.7% −31.7% 95% CI (0.1, 0.2%) (0.0, 0.1%) (0.1, 0.2%) 35–54 SimSmoke 0.2% 0.1% −44.9% 0.1% −23.1% 0.1% −9.7% −61.8% CPS-TUS 0.2% 0.1% −54.0% 0.1% −8.0% 0.1% 0.0% −57.7% 95% CI (0.1, 0.1%) (0.1, 0.1%) (0.1, 0.1%) 55+ SimSmoke 0.9% 0.4% −47.4% 0.2% −54.1% 0.1% −28.0% −82.6% CPS-TUS 0.9% 0.3% −67.9% 0.1% −58.4% 0.1% −16.7% −88.8% 95% CI (0.2, 0.4%) (0.1, 0.2%) (0.1, 0.1%) Relative change measured as the absolute difference in prevalence between the end and the initial year of the specified period divided by the prevalence of the initial year 25.7% (22.3%) to 14.9% (12.8%). The 2015 SimSmoke Male (female) exclusive SLT use estimated by Sims- male (female) projected prevalence were outside the moke fell from 3.2% (0.4%) in 1993 to 2.4% (0.1%) in TUS 95% CI, but the relative reductions between 1993 2015, yielding a 24% (71%) relative reduction between and 2015 were 44.7% for males and 43.8% for females 1993 and 2015 compared to a 16% (77%) relative reduc- and were within 3% of the TUS estimates for both males tion in TUS. Female projections for 2015 were margin- (41.9%) and females (42.7%). By sub-periods, SimSmoke ally within the 95% CI of the TUS, while the male SLT over-estimated the relative reduction in exclusive smok- projection was just outside the 95% CI. SimSmoke ing from 1993 to 2002 less for females (− 21.4% vs. − underestimated male relative reduction for 1993–2002 18.6%) than for males (− 21.3 vs. -14.1%), did better for and overestimated relative reductions for 2002–2011 males (− 23.5% vs − 22.5%) than females (− 22.5 vs. and 2011–2015, while female relative reductions were -21.1%) for 2002–2011, and underestimated the 2011– underestimated in first two sub-periods and then re- 2013 reduction similarly for males (− 8.2% vs. -12.6%) versed in 2011–2015. Discrepancies were particularly and females (− 7.7% vs. -10.9%). In examining trends by large in the 18–24 age group. age group, the biggest discrepancies were for 18–24 year olds, where SimSmoke over-predicted male and female The effect of policies implemented through 2017 reductions during the period 1993–2002, which was Results comparing exclusive smoking, dual use and exclu- then reversed in 2002–2011 and 2011–2015. sive SLT prevalence projections with policies implemented Adult male (female) estimates from SimSmoke for dual between 1993 and 2017 to a counterfactual with policies use fell from 1.0% (0.05%) in 1993 to 0.7% (0.02%) in 2015, set to their 1993 levels (i.e., the absence of policy change) compared to TUS estimates of 0.05 (0.02). Compared to are shown in Table 3. Results for tobacco-attributable the TUS, the 2015 projections were within the 95% CI for deaths and lives saved are shown in Table 4, with the last females (falling from 0.5 to 0.2%), but outside the 95% column showing the summation over the years 1993– CI for males. SimSmoke under-predicted male reduc- 2067 to obtain the lives saved over that period. tions in 1993–2002 and over-predicted the reductions In 1993, total tobacco-attributable deaths for males in 2002–2011 and 2011–2015, but underestimated (females) were estimated as 226,979 (128,191), including female reductions for 1993–2002 and 2002–2011 and 214,536 (125,607) exclusive smokers, 7072 (506) dual over-predicted for 2011–2015. Similar results were users and 5371 (2078) exclusive SLT users. For 2017, obtained for most age groups. SimSmoke projected 251,180 (148,076) total attributable Levy et al. BMC Public Health (2018) 18:696 Page 10 of 17 Table 3 Prevalence by Smoking Status (Exclusive Cigarette, Dual and Smokeless Tobacco Use) Projected by SimSmoke under Multiple Scenarios for Males and Females, 1993–2067 Prevalence Type 1993 2003 2017 2037 2067 Relative Difference 2017 2067 Male No policy change Cigarette 25.6% 22.9% 20.9% 19.1% 18.6% –– Dual 1.05% 1.02% 1.02% 0.96% 0.93% –– SLT 3.19% 3.00% 2.86% 2.68% 2.60% –– Actual/ status quo Cigarette 25.6% 19.6% 13.6% 10.5% 9.6% −34.8% −48.3% Dual 1.05% 0.88% 0.68% 0.57% 0.52% −32.5% −43.6% SLT 3.19% 2.71% 2.38% 2.14% 2.03% −16.5% −21.9% Price alone Cigarette 25.6% 20.3% 15.8% 12.7% 11.7% −24.5% −37.1% Dual 1.05% 0.91% 0.78% 0.67% 0.62% −23.1% −33.3% SLT 3.19% 2.74% 2.49% 2.26% 2.15% −12.8% −17.4% Smoke-free air law alone Cigarette 25.6% 22.8% 20.0% 17.9% 17.3% −4.0% −7.1% Dual 1.05% 1.02% 0.98% 0.90% 0.87% −3.9% −6.4% SLT 3.19% 3.00% 2.86% 2.70% 2.62% 0.3% 0.8% Media campaigns alone Cigarette 25.6% 22.8% 20.8% 18.9% 18.4% −0.6% − 0.8% Dual 1.05% 1.02% 1.01% 0.95% 0.92% −0.5% − 0.7% SLT 3.19% 2.99% 2.85% 2.68% 2.59% −0.2% − 0.3% Cessation treatment alone Cigarette 25.6% 22.6% 20.2% 18.3% 17.8% −3.4% −4.2% Dual 1.05% 1.01% 0.98% 0.92% 0.89% −3.0% −3.8% SLT 3.19% 2.98% 2.81% 2.62% 2.54% −1.6% −2.3% Health warning alone Cigarette 25.6% 22.9% 20.9% 19.1% 18.6% 0.0% 0.0% Dual 1.05% 1.02% 1.02% 0.96% 0.93% 0.0% 0.0% SLT 3.19% 3.00% 2.82% 2.64% 2.55% −1.1% −1.7% Advertising ban alone Cigarette 25.6% 22.9% 20.8% 18.9% 18.4% −0.5% −0.9% Dual 1.05% 1.02% 1.01% 0.95% 0.92% −0.5% −0.8% SLT 3.19% 3.00% 2.84% 2.67% 2.58% −0.4% −0.8% Youth access alone Cigarette 25.6% 22.8% 20.5% 18.3% 17.7% −2.0% −4.9% Dual 1.05% 1.02% 1.00% 0.93% 0.90% −1.2% −3.0% SLT 3.19% 3.00% 2.86% 2.69% 2.60% 0.0% 0.0% Female No policy change Cigarette 22.1% 19.7% 18.4% 17.1% 16.8% –– Dual 0.05% 0.03% 0.03% 0.02% 0.02% –– SLT 0.38% 0.22% 0.12% 0.08% 0.07% –– Actual/ status quo Cigarette 22.1% 16.9% 11.9% 9.3% 8.4% −35.2% −49.9% Dual 0.05% 0.03% 0.02% 0.01% 0.01% −32.5% −47.0% SLT 0.38% 0.20% 0.10% 0.07% 0.06% −16.4% −20.7% Price alone Cigarette 22.1% 17.5% 13.9% 11.3% 10.4% −24.6% −38.0% Dual 0.05% 0.03% 0.02% 0.01% 0.01% −21.8% − 35.9% SLT 0.38% 0.21% 0.11% 0.07% 0.06% −11.7% −15.8% Smoke-free air law alone Cigarette 22.1% 19.6% 17.7% 16.0% 15.6% −4.1% −7.4% Dual 0.05% 0.03% 0.02% 0.02% 0.02% −3.9% −6.8% SLT 0.38% 0.22% 0.12% 0.08% 0.07% 0.2% 1.1% Media campaign alone Cigarette 22.1% 19.6% 18.3% 17.0% 16.7% −0.6% −0.8% Levy et al. BMC Public Health (2018) 18:696 Page 11 of 17 Table 3 Prevalence by Smoking Status (Exclusive Cigarette, Dual and Smokeless Tobacco Use) Projected by SimSmoke under Multiple Scenarios for Males and Females, 1993–2067 (Continued) Prevalence Type 1993 2003 2017 2037 2067 Relative Difference 2017 2067 Dual 0.05% 0.03% 0.03% 0.02% 0.02% −0.5% −0.7% SLT 0.38% 0.22% 0.12% 0.08% 0.07% −0.2% −0.3% Cessation treatment alone Cigarette 22.1% 19.5% 17.7% 16.3% 16.0% −3.8% −5.2% Dual 0.05% 0.03% 0.02% 0.02% 0.02% −4.3% −4.6% SLT 0.38% 0.22% 0.12% 0.08% 0.07% −2.5% −2.8% Health warning alone Cigarette 22.1% 19.7% 18.4% 17.1% 16.8% 0.0% 0.0% Dual 0.05% 0.03% 0.03% 0.02% 0.02% 0.0% 0.0% SLT 0.38% 0.22% 0.12% 0.08% 0.07% −1.2% −1.9% Advertising ban alone Cigarette 22.1% 19.7% 18.3% 17.0% 16.7% −0.5% −0.9% Dual 0.05% 0.03% 0.03% 0.02% 0.02% −0.5% −0.8% SLT 0.38% 0.22% 0.12% 0.08% 0.07% −0.4% −0.8% Youth access alone Cigarette 22.1% 19.7% 18.1% 16.5% 16.0% −1.9% −4.7% Dual 0.05% 0.03% 0.03% 0.02% 0.02% −1.1% −3.8% SLT 0.38% 0.22% 0.12% 0.08% 0.07% 0.0% 0.3% Relative differences measured as the absolute difference between current prevalence and no-policy-change scenario prevalence from the same year divided by the no-policy-change prevalence for the same year deaths, including 238,852 (146,076) exclusive smokers, showed 3–4 and 2% relative reductions respectively in 7085 (364) dual users and 5243 (969) exclusive SLT 2017 increasing to 4–5 and 5% by 2067. Mass media users. Since 1993, premature deaths generally grew and campaigns and advertising bans showed 0.6 and 0.5% then declined in number, except among female dual and relative reductions respectively in 2017 increasing to 0.8 exclusive SLT users which showed continuous decline. and 0.9% reductions by 2067. For exclusive cigarettes, With no new policies implemented after 1993, SimS- taxes represented 71% of the total policy effects, moke projected that exclusive cigarette, dual and exclu- followed by smoke-free air laws at 11%, and cessation sive SLT use rates would have been 35, 32.5 and 16.5% treatment at 10% by 2017. higher respectively in 2017 for males, with similar rela- Similar but slightly smaller relative reductions were tive differences for females. As a result of policies, an- projected for dual use. However, much smaller effects nual tobacco-attributable deaths for males (females) were projected for exclusive SLT use, where the largest were reduced by 34,800 (21,679) in 2017 alone with a relative reductions by 2067 for males (females) were 13% cumulative impact of 268,628 (167,308) fewer (12%) for prices, followed by 1.6% (2.5%) for cessation tobacco-attributable deaths from 1993 to 2017. By 2067, treatment and 1.1% (1.2%) for health warnings. Some the relative reductions for males (females) increased to categories show increased exclusive SLT use in future 48% (50%) for exclusive cigarette, 44% (47%) for dual years, due to the larger pool of potential initiates from and 22% (21%) for exclusive SLT users, as policies con- those who would have smoked cigarettes. tinued to reduce tobacco use through increased cessa- tion and reduced initiation. Due to policies implemented Discussion between 1993 and 2017, SimSmoke projected a total of Our estimates of the increase in exclusive cigarette use 4,595,461 (2,939,392) premature deaths averted by 2067. between 1993 and 2015 from US SimSmoke generally Comparing the counterfactual for individual policies, validated well against trends found in the large scale, na- much of the reduction in exclusive cigarette use was due tionally representative TUS. However, SimSmoke to price increases. Price increases alone were predicted over-estimated reductions among male smokers for most to reduce male (female) exclusive cigarette use rates in ages, especially those 18–24, until 2002, while relative terms by 25% (25%) in 2017 and by 37% (38%) under-estimating reductions in later years. By 2015, in 2067, and to have averted 3,128,890 (1,959,661) male SimSmoke female projections of adult exclusive and dual (female) deaths in total by 2067. Smoke-free air laws cigarette use were close to TUS estimates, while male re- yielded a 4% relative reduction in exclusive cigarette use ductions were under-estimated for dual use but in 2017, which increased to a 7% reduction by 2067. over-estimated for exclusive SLT use. The deviations for Cessation treatments and youth access enforcement dual use may reflect the relatively small number of such Levy et al. BMC Public Health (2018) 18:696 Page 12 of 17 Table 4 Tobacco-Attributable Deaths by Smoking Status Projected by SimSmoke under Multiple Scenarios for Males and Females, 1993–2067 Policies Type 1993 2003 2017 2037 2067 Cumulative 1993–2017 1993–2067 Male Tobacco-Attributable Deaths with Policies Actual/ status quo Cigarette 214,536 235,471 238,852 200,634 144,977 5,850,036 15,175,074 Dual 7072 6755 7085 8195 6859 172,098 550,611 SLT 5371 5898 5243 5368 5321 141,452 406,886 Total 226,979 248,123 251,180 214,196 157,158 6,163,585 16,132,572 Lives Saved Compared to the Counterfactual of No Policy Change Actual/ status quo Cigarette – 4167 33,407 71,464 128,514 257,655 4,350,888 Dual – 126 1011 3141 5747 7520 186,594 SLT – 68 381 949 1700 3453 57,979 Total – 4362 34,800 75,553 135,961 268,628 4,595,461 Price alone Cigarette – 3058 20,160 45,179 96,264 162,609 2,959,865 Dual – 92 600 1962 4278 4644 126,743 SLT – 60 282 659 1288 2759 42,282 Total – 3210 21,042 47,801 101,831 170,013 3,128,890 Smoke-free air law alone Cigarette – 48 2288 9212 18,973 12,291 549,538 Dual – 000 00 0 SLT – 1 74 412 843 386 24,265 Total – 49 2362 9623 19,816 12,677 573,445 Media campaign alone Cigarette – 42 573 1182 2252 4033 75,506 Dual – 1 18 52 98 118 3234 SLT – 0310 22 21 667 Total – 43 594 1245 2373 4172 79,406 Cessation treatment alone Cigarette – 328 5801 13,195 16,515 38,207 693,120 Dual – 9 174 596 773 1098 30,665 SLT – 2 50 173 266 308 9589 Total – 339 6025 13,963 17,554 39,613 733,373 Health warning alone Cigarette – 000 00 0 Dual – 000 00 6 SLT – 0 17 73 134 85 4166 Total – 0 17 73 134 85 3596 Advertising ban alone Cigarette – 0 319 1069 2123 1205 62,167 Dual – 0 11 47 93 42 2703 SLT – 0 5 21 47 27 1296 Total – 0 335 1137 2263 1274 66,165 \Youth access alone Cigarette – 0 17 1824 10,683 26 189,846 Dual – 0 1 63 348 1 6343 SLT – 001 10 44 Total – 0 18 1887 11,032 27 196,232 Female Tobacco-Attributable Deaths with Policies Actual/ status quo Cigarette 125,607 140,968 146,742 142,518 102,473 3,508,793 9,961,334 Levy et al. BMC Public Health (2018) 18:696 Page 13 of 17 Table 4 Tobacco-Attributable Deaths by Smoking Status Projected by SimSmoke under Multiple Scenarios for Males and Females, 1993–2067 (Continued) Policies Type 1993 2003 2017 2037 2067 Cumulative 1993–2017 1993–2067 Dual 506 443 364 221 103 10,857 20,938 SLT 2078 1863 969 353 173 41,759 60,235 Total 128,191 143,275 148,076 143,093 102,749 3,561,410 10,042,508 Lives Saved Compared to the Counterfactual of No Policy Change Actual/ status quo Cigarette – 2617 21,559 48,462 90,074 165,934 2,932,063 Dual – 10 48 63 91 436 3845 SLT – 27 72 49 46 938 3484 Total – 2653 21,679 48,574 90,212 167,308 2,939,392 Price alone Cigarette – 1936 13,098 29,304 67,050 106,278 1,954,695 Dual – 7 28 36 68 275 2462 SLT – 23 51 32 34 751 2504 Total – 1967 13,178 29,372 67,152 107,304 1,959,661 Smoke-free air law alone Cigarette – 28 1393 6274 13,254 7360 369,202 Dual – 000 00 0 SLT – 0 3 8 13 18 451 Total – 29 1396 6282 13,267 7378 369,639 Media campaign alone Cigarette – 24 353 798 1654 2434 51,313 Dual – 011 26 65 SLT – 011 15 33 Total – 24 354 800 1656 2445 51,411 Cessation treatment alone Cigarette – 201 3676 9978 12,899 23,840 513,312 Dual – 1914 13 62 717 SLT – 1 10 10 8 81 572 Total – 202 3695 10,003 12,920 23,983 514,601 Health warning alone Cigarette – 000 00 0 Dual – 000 00 0 SLT – 044 423 218 Total – 044 423 211 Advertising ban alone Cigarette – 0 195 735 1472 724 41,862 Dual – 001 12 51 SLT – 011 17 64 Total – 0 197 738 1475 734 41,977 Youth access alone Cigarette – 0 7 822 6598 11 103,780 Dual – 001 60 100 SLT – 000 00 0 Total – 0 7 823 6604 11 103,880 Lives saved were calculated as the difference in projected deaths with the policy implemented and with no policy implemented users. Contrary to the results for exclusive cigarette use, Consistent with previous literature [8, 9], the model both male exclusive SLT use and male dual use underes- projected that overall SLT rates fell quite rapidly for timated the reductions for 1993–2002, while moving both dual and exclusive SLT use through 2002, but de- closer to the TUS estimates by 2015. These reversals celerated in recent years. However, SimSmoke were particularly apparent for the 18–24 and 35–54 age under-predicted the decline through 2002. While some groups. policies were directed at SLT use between 1993 and Levy et al. BMC Public Health (2018) 18:696 Page 14 of 17 2002, most were directed at cigarette use, including tax cigarette use. In addition, the effect sizes of policies on increases, smoke-free air laws, and media campaigns. SLT use that we used in SimSmoke, are tentative, largely These policies may have also reduced SLT use, suggest- reflecting studies prior to 2007 [17]. Better information ing the importance of strong cigarette policies in redu- is needed on policy effectiveness, especially for recent cing overall tobacco use. years since the cigarette companies came to dominate The model fails to predict well the increasing pattern the industry, and on the extent to which policies, such of exclusive SLT and dual use found in recent TUS sur- as media campaigns, are directed at SLT use. Better in- veys and in recent studies [6, 10, 11, 82, 83]. The failure formation is also needed about the timing of policies ef- to predict these changes in trend may reflect the chan- fects and the potential synergies or overlapping effects ging composition of the SLT industry. Reynolds Ameri- of policies as they relate to cigarette and SLT use. can acquired Conwood Smokeless Tobacco Company in Another limitation is that SimSmoke considers only 2006 and soon thereafter introduced Camel Snus, and cigarette and SLT use, and does not include the use of Altria acquired the U.S. Smokeless Tobacco Company in other nicotine delivery products, such as cigars, water 2009 and began marketing Marlboro Snus. Together pipes and e-cigarettes, that may substitute or comple- they controlled 85% of the market [13]. Industry docu- ment the use of cigarettes and SLT. Growth in ments [84, 85] indicate that cigarette companies began e-cigarette use between 2011 and 2015 [96, 97] may ex- promoting SLT products as a way for smokers to satisfy plain the rapid reduction in cigarette use and the slow- nicotine cravings in places where smoking is banned, ing growth of SLT use. and marketing expenditures, including those on price promotions [86] and flavored products [87, 88], in- Conclusions creased. The largest increases in SLT use were among While the landscape for nicotine delivery products has young adults, possibly reflecting marketing targeted to- dramatically changed in the last 10 years, some lessons ward this age group. Policies may need to be directed at can be gleaned from the modeling in this paper. With this age group in order to reduce SLT and dual use. cigarettes still being the dominant form of nicotine de- SimSmoke projected that policies implemented be- livery, cigarette-oriented policies may be an effective tween 1993 and 2017 reduced cigarette use by about means, perhaps the most effective means, of reducing 35% and SLT use by 16.5%. Consistent with earlier SimS- SLT use and possibly reducing the use of other nicotine moke analyses [89, 90], the largest percentage reductions delivery products, such as e-cigarettes. Policies directed in cigarette and SLT use and in attributable deaths were at SLT use, especially those that affect youth and young due to taxes. Smoke-free air laws were next most im- adults, may also play a role but it should be recognized portant for cigarettes, while cessation treatment was that substitution of exclusive SLT use (which is relatively next most important for SLTs. The importance of taxes low risk) for cigarette use can reduce overall harms. In and smoke-free air laws has also been found in previous developing a coherent policy approach, it will be import- US SimSmoke models of cigarette use [2, 20–22, 25, 26]. ant to monitor the use of other products, such as cigars SimSmoke also provided estimates of the health effects and e-cigarettes. In addition, it will be important to of SLT use. SimSmoke estimated 6212 deaths attributable monitor the marketing and pricing policies of cigarette to exclusive SLT use in 2017 (down from 7449 in 1993), companies, which have strong incentives to protect the but projected general increases in future years. However, we high profit margins of cigarettes. treated SLT as a homogeneous category in terms of risks, Abbreviations potentially overestimating risks (e.g., SLT users switching to FSPTCA: Smoking Prevention and Tobacco Control Act; SLT: smokeless snus) [91–95]. The number of SLT-attributable deaths paled tobacco in comparison to the total deaths attributable to dual and exclusive cigarette use, which were estimated as 7449 and Acknowledgements We would like to thank Frank Chaloupka and Raymond Boyle for comments 385,594 respectively in 2017. The model did not distinguish on a previous draft of this paper. the relative risks of dual use from that of exclusive cigarette use, although dual use may reduce the number of cigarettes Funding smoked over a lifetime and, thereby, reduce mortality risks. Funding was received from the Food and Drug Administration through the National Institute on Drug Abuse, National Institute of Health, under grant Like all models, SimSmoke estimates are only as strong R01DA036497. The funding sponsors had no role in the design of the study; as the assumptions and underlying data. In particular, in the collection, analyses, or interpretation of data; in the writing of the the projections of cigarette use were based on initiation manuscript, and in the decision to publish the results. and cessation rates derived in 1993 subject to policy Availability of data and materials changes over time. Cessation rates for exclusive SLT The datasets used during the current study are publicly available and the users were not available, and we were not able to distin- formats used in this study are available from the corresponding author on guish cessation rates for dual as compared to exclusive reasonable request. Levy et al. BMC Public Health (2018) 18:696 Page 15 of 17 Authors’ contributions 17. Levy DT, Bauer JE, Lee HR. Simulation modeling and tobacco control: DTL conceived of the idea, wrote the initial draft, and revised the paper, creating more robust public health policies. Am J Public Health. while ZY and YL helped in developing the analysis, conducted the data 2006;96(3):494–8. analyses, wrote the initial methods and results section, and reviewed the 18. Levy D, de Almeida LM, Szklo A. The Brazil SimSmoke policy simulation final manuscript. All authors read and approved the final manuscript. model: the effect of strong tobacco control policies on smoking prevalence and smoking-attributable deaths in a middle income nation. PLoS Med. 2012;9(11):e1001336. Ethics approval and consent to participate 19. Levy D, Rodriguez-Buno RL, Hu TW, Moran AE. The potential effects of Not applicable, All data is publicly available. tobacco control in China: projections from the China SimSmoke simulation model. BMJ. 2014;348:g1134. Competing interests 20. Levy D, Tworek C, Hahn E, Davis R. The Kentucky SimSmoke tobacco policy The authors declare that they have no competing interests. simulation model: reaching healthy people 2010 goals through policy change. South Med J. 2008;101(5):503–7. 21. Levy DT, Benjakul S, Ross H, Ritthiphakdee B. The role of tobacco control Publisher’sNote policies in reducing smoking and deaths in a middle income nation: results Springer Nature remains neutral with regard to jurisdictional claims in from the Thailand SimSmoke simulation model. Tob Control. 2008;17(1):53–9. published maps and institutional affiliations. 22. Levy DT, Boyle RG, Abrams DB. The role of public policies in reducing smoking: the Minnesota SimSmoke tobacco policy model. Am J Prev Med. Received: 31 October 2017 Accepted: 24 May 2018 2012;43(5 Suppl 3):S179–86. 23. Levy DT, Huang AT, Currie LM, Clancy L. The benefits from complying with the framework convention on tobacco control: a SimSmoke analysis of 15 References European nations. Health Policy Plan. 2014;29(8):1031–42. 1. The 2014-2015 Tobacco Use Supplement to the Current Population Survey 24. Levy DT, Huang AT, Havumaki JS, Meza R. The role of public policies in (TUS-CPS). 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