Tobacco Policies in Louisiana: Recommendations for Future Tobacco Control Investment from SimSmoke, a Policy Simulation Model

Modeling the future of tobacco control: Using SimSmoke to explore the feasibility of the tobacco endgame in Korea

INTRODUCTION

We used a simulation model to assess the feasibility of reaching the tobacco endgame target (reducing the smoking prevalence to below 5% by 2050) and explored potential implementation strategies.

METHODS

The impact of strengthened tobacco-control policies on smoking prevalence was analyzed using Korea SimSmoke, a discrete-time Markov process. We considered the effects of various scenarios from 2023 and predictions were conducted until 2050. To confirm the stability of the results, deterministic and probabilistic sensitivity analyses were carried out by increasing and decreasing parameter estimates.

RESULTS

The implementation of tobacco-control policies in accordance with the WHO MPOWER (Μonitor tobacco use and prevention policies; Protect people from tobacco smoke; Offer help to quit tobacco smoking; Warn of the dangers of tobacco; Enforce bans on tobacco advertising, promotion, and sponsorship; Raise taxes on tobacco) measures were insufficient to achieve the tobacco endgame objective of 5% by 2050. The overall predicted smoking prevalence in 2050 is 4.7% if all policies are fully implemented in accordance with the FCTC guidelines together with a complete ban on the sale of cigarettes to people born after 2003 and annual 10% increases in price. Sensitivity analyses using the varying policy effect assumptions demonstrated the robustness of the simulation results.

CONCLUSIONS

For a substantive reduction in smoking prevalence, it is essential to strongly implement the MPOWER strategy. Beyond this foundational step, the eradication of smoking requires a paradigm shift in the perception of conventional tobacco-control policies, including a tobacco-free generation strategy and radical increases in the price of tobacco products.

Illuminating a Path Forward for Tobacco Nation: Projected Impacts of Recommended Policies on Geographic Disparities

Introduction

This study quantifies the impacts of strengthening 2 tobacco control policies in "Tobacco Nation," a region of the United States (U.S.) with persistently higher smoking rates and weaker tobacco control policies than the rest of the US, despite high levels of support for tobacco control policies.

Methods

We used a microsimulation model, ModelHealthTM:Tobacco, to project smoking-attributable (SA) outcomes in Tobacco Nation states and the U.S. from 2022 to 2041 under 2 scenarios: (1) no policy change and (2) a simultaneous increase in cigarette taxes by $1.50 and in tobacco control expenditures to the CDC-recommended level for each state. The simulation uses state-specific data to simulate changes in cigarette smoking as individuals age and the health and economic consequences of current or former smoking. We simulated 500 000 individuals for each Tobacco Nation state and the U.S. overall, representative of each population.

Results

Over the next 20 years, without policy changes, disparities in cigarette smoking will persist between Tobacco Nation and other U.S. states. However, compared to a scenario with no policy change, the simulated policies would lead to a 3.5% greater reduction in adult smoking prevalence, 2361 fewer SA deaths per million persons, and $334M saved in healthcare expenditures per million persons in Tobacco Nation. State-level findings demonstrate similar impacts.

Conclusions

The simulations indicate that the simulated policies could substantially reduce cigarette smoking disparities between Tobacco Nation and other U.S. states. These findings can inform tobacco control advocacy and policy efforts to advance policies that align with evidence and Tobacco Nation residents' wishes.

Identifying best modelling practices for tobacco control policy simulations: a systematic review and a novel quality assessment framework

BACKGROUND

Policy simulation models (PSMs) have been used extensively to shape health policies before real-world implementation and evaluate post-implementation impact. This systematic review aimed to examine best practices, identify common pitfalls in tobacco control PSMs and propose a modelling quality assessment framework.

METHODS

We searched five databases to identify eligible publications from July 2013 to August 2019. We additionally included papers from Feirman et al for studies before July 2013. Tobacco control PSMs that project tobacco use and tobacco-related outcomes from smoking policies were included. We extracted model inputs, structure and outputs data for models used in two or more included papers. Using our proposed quality assessment framework, we scored these models on population representativeness, policy effectiveness evidence, simulated smoking histories, included smoking-related diseases, exposure-outcome lag time, transparency, sensitivity analysis, validation and equity.

FINDINGS

We found 146 eligible papers and 25 distinct models. Most models used population data from public or administrative registries, and all performed sensitivity analysis. However, smoking behaviour was commonly modelled into crude categories of smoking status. Eight models only presented overall changes in mortality rather than explicitly considering smoking-related diseases. Only four models reported impacts on health inequalities, and none offered the source code. Overall, the higher scored models achieved higher citation rates.

CONCLUSIONS

While fragments of good practices were widespread across the reviewed PSMs, only a few included a 'critical mass' of the good practices specified in our quality assessment framework. This framework might, therefore, potentially serve as a benchmark and support sharing of good modelling practices.

The Minnesota SimSmoke Tobacco Control Policy Model of Smokeless Tobacco and Cigarette Use

INTRODUCTION

A previous Minnesota SimSmoke tobacco control policy model is extended to more recent years and to include smokeless tobacco use.

METHODS

Using data from the 1993 Tobacco Use Supplement and information on state policies, the Minnesota SimSmoke model was updated and extended to incorporate smokeless tobacco (both exclusive and dual use) and smokeless tobacco-attributable deaths. The model was then validated against the 2002, 2006/2007, and 2014/2015 Tobacco Use Supplement and the 1999, 2007, 2014, and 2018 Minnesota Adult Tobacco Survey and used to estimate the impact of policies implemented between 1993 and 2018. Analysis was conducted in April 2019.

RESULTS

The model validated well for cigarette and earlier smokeless tobacco use, but it predicted smokeless tobacco use less well in recent years. The model projected that male (female) smoking prevalence was 35% (36%) lower in relative terms by 2018 and 43% (44%) lower by 2040 owing to policies, with lesser reductions projected for male smokeless tobacco use. Tobacco-attributable deaths were reduced by 7,800 by 2018 and 46,900 by 2040. Price increases, primarily through taxes, were projected to have had the greatest impact on cigarette use followed by smoke-free air laws, cessation treatment policies, tobacco control campaign expenditures, and youth access enforcement. Similar effects were projected for smokeless tobacco use, except that smoke-free air laws had smaller effects.

CONCLUSIONS

As cigarettes remain the dominant form of nicotine delivery product, cigarette-oriented policies may be an effective means of reducing the use of all nicotine delivery products. However, noncigarette-oriented policies may also play an important role.

Youth smoking and anti-smoking policies in North Dakota: a system dynamics simulation study

BACKGROUND

The current study utilizes system dynamics to model the determinants of youth smoking and simulate effects of anti-smoking policies in the context of North Dakota, a state with one of the lowest cigarette tax rates in the USA.

METHODS

An explanatory model was built to replicate historical trends in the youth smoking rate. Three different policies were simulated: 1) an increase in cigarette excise taxes; 2) increased funding for CDC-recommended comprehensive tobacco control programs; and 3) enforcement of increased retailer compliance with age restrictions on cigarette sales.

RESULTS

The explanatory model successfully replicated historical trends in adolescent smoking behavior in North Dakota from 1992 to 2014. The policy model showed that increasing taxes to $2.20 per pack starting in 2015 was the most effective of the three policies, producing a 32.6% reduction in youth smoking rate by 2032. Other policies reduced smoking by a much lesser degree (7.0 and 3.2% for comprehensive tobacco control program funding and retailer compliance, respectively). The effects of each policy were additive.

CONCLUSIONS

System dynamics modeling suggests that increasing cigarette excise taxes are particularly effective at reducing adolescent smoking rates. More generally, system dynamics offers an important complement to conventional analysis of observational data.

Cigarette tax rates, behavioral disengagement, and quit ratios among daily smokers

Cigarette taxation is an economics-based policy associated with increased population-level quit ratios. However, the estimated effects of tax increase on smoking behavior vary substantially, underscoring the need to identify moderating variables. We examined whether behavioral disengagement - the tendency to abandon goals when experiencing stress - modified the association between cigarette taxes and daily smoking behavior. We connected state-level cigarette tax rate data with individual-level behavioral data, including a national sample of 725 US adults who smoked daily at baseline and reported follow-up data approximately 10 years later, and 376 who were resampled a third time after another 10 years. Analyses involved multilevel logistic regression (with time as a nested variable and anonymized state codes as a grouping variable), where current smoking status (dichotomous) was regressed on behavioral disengagement, state-level cigarette tax at baseline and current time, and the interaction between disengagement and current tax. Consistent with hypotheses, tax rate interacted with disengagement (OR=0.95, 95% CI=0.90,0.99, p=.0255): Among those one SD above the mean for disengagement, tax rate was unassociated with quit ratio (OR=0.99, 95% CI=0.85,1.16, p=.6975). However, among those one SD below the mean, tax rate was significantly associated with higher quit ratio (OR=1.22, 95% CI=1.04,1.43, p=.0163). Our data suggest the possibility that cigarette taxes may be more effective in facilitating cessation among smokers low in behavioral disengagement or when accompanied by interventions that reduce stress or maintain goal pursuit. Identifying psychological moderators of policy effectiveness holds promise for improving policy design and targeting.