Article Text

Healthy People Countdown 2030: reaching 5% cigarette smoking prevalence among US adults through state cigarette excise tax increases
1. Nigar Nargis
1. Department of Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia, USA
1. Correspondence to Dr Nigar Nargis, Department of Surveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA; nigar.nargis{at}cancer.org

## Abstract

Objective The Healthy People 2030 goal is to reduce US current adult cigarette smoking prevalence to 5% by 2030. The objective of this report is to investigate if this goal is achievable using state cigarette excise tax increases.

Methods State-specific linear trends in smoking prevalence over 2011–2019 were determined using fractional logit regression and compared with the desired linear trends for achieving 5% smoking prevalence by 2030 in individual states and the District of Columbia (DC). The gaps between price-adjusted and desired trends were used in a simulation model for identifying state-specific systematic annual increases in state cigarette excise tax rates based on state-specific price elasticity of smoking prevalence, maintaining the status quo in other non-tax tobacco control measures.

Results The price-adjusted trends in smoking prevalence observed over 2011–2019 exceed the desired trends for achieving 5% smoking prevalence target by 2030 in only five states (eg, Washington, Utah, Rhode Island, Massachusetts and Maryland) and the DC. It suggests that majority of states and USA overall will miss the target smoking prevalence at the current rate of reduction in smoking. 45 states would need systematic annual increases in cigarette excise tax rate in a range of $0.02–$1.37 per pack over 2022–2030 to meet the target.

Conclusions The feasibility of reaching the Healthy People 2030 goal would critically depend on the acceleration of progress in tobacco control. Tax increases tailored to the needs of individual states combined with scaled-up non-tax tobacco control policy interventions can help achieve the desired progress.

• economics
• end game
• price
• taxation

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## Introduction

USA experienced two-thirds reduction in adult smoking prevalence from 42.4% to 13.7% over 1965–2018.1 The Healthy People goal is to reduce it to 5% by 2030.2 The feasibility of achieving this goal is yet to be tested in view of the recent progress in tobacco control. In this report, state-specific trends in smoking prevalence over 2011–2019 were compared with the desired trends for achieving 5% smoking prevalence by each state. The gaps between price-adjusted and desired trends were used as the basis for state-specific interventions through systematic annual increases in state cigarette excise tax, maintaining the status quo in non-tax tobacco control measures.

Previous research applied several microsimulation and macrosimulation models to project the effects of tobacco tax increases on population health and economic outcomes.3–12 Only one of these studies explored the potential of reaching the Healthy People 2010 goal of reducing smoking prevalence to 12% by simulating the combined effect of national level tax and price increase, smoke-free indoor air law, mass media campaign and cessation support.12 The present study simulates the effect of cigarette tax and price increases only in reducing adult cigarette smoking prevalence to 5% by 2030. The major innovation in this paper is to make state-specific projections that can better inform state-level tobacco control interventions.

## Methods

The analysis was conducted in three stages in a simulation model using STATA (V.15; Stata) and Microsoft Excel. First, the existing trends in smoking prevalence in state s in terms of average annual change in percentage points (pp) adjusted for price changes were determined using fractional logit regression (a generalised linear model for dependent variables bounded between 0 and 1) of smoking prevalence on the year variable and average state-level cigarette prices based on historical annual data from the Behavioral Risk Factor Surveillance System (BRFSS) and the Tax Burden on Tobacco (TBOT) database over 2011–2019.13–15 The regression equation estimated for each state separately is given by: Yst=αsp+βsept+βspPst+vst, where Yst is adult cigarette smoking prevalence (%) in state s in year t, αsp is the state-specific intercept, βsep represents the existing trend adjusted for the effects of price changes, Pst is the average cigarette price per pack in state s in year t, βsp is the state-specific coefficient of price changes and vst is the random disturbance term and t=2011, 2012, …, 2019. Thus, the sample size for each regression run for individual states was nine to allow for nine data points between 2011 and 2019.

Second, the state-wise desired trends (in pp) were determined by the linear trend required to reduce smoking prevalence from the baseline level to the 5% target by 2030. Suppose the desired annual trend is βsd pp. So, Ys,2021–9βsd=Ys,2030=5 or βsd=(Ys,2021 − 5)/9. The price-adjusted trends (βsep) were used to calculate the ‘gap’ (βsep − βsd).

Third, the marginal effects of price on smoking prevalence among US adults by age group estimated by Sloan and Trogdon based on BRFSS data for 1992–2002 were used to obtain average marginal effect size (β1) of −0.0096 for the overall population.16 It was then used to estimate state-specific price elasticity of smoking prevalence for each year as Єst=β1×(Pst/Yst). Thus, the price elasticity estimates were adjusted for higher prices and lower smoking prevalence in each successive year. The price elasticity estimates in year t were then used to estimate the required percentage increase in price to achieve the target reduction in smoking prevalence in year t+1 for each year from 2022 through 2030 using the formula:

The year-on-year increase in price necessary to achieve a target reduction in smoking prevalence was then translated into year-on-year increase in state cigarette excise tax under the assumption of full pass-through of tax increase to price. In other words, TAXs,t+1=TAXst+(Ps,t+1Pst), where TAXst is state cigarette excise tax per pack in state s in year t.

The baseline for the projection of tax and price increases was set in 2021. The unadjusted trends in smoking prevalence estimated from the equation Ysts+βset +ust, where αs is the state-specific intercept, βse is the unadjusted trend in smoking prevalence in state s, and ust is the random disturbance term, which were used to extrapolate from 2019 to initialise smoking prevalence in the baseline year 2021. The smoking prevalence in the baseline year 2021 was thus estimated using the equation: Ys,2021=Ys,2019+2βse, where Ys,2019 is the latest smoking prevalence data for state s in 2019 available from the BRFSS. The unadjusted trend βse was multiplied with 2 to account for 2 years from 2019 to 2021. The projections were adjusted for tax increases in Colorado and Oregon in 2021 and in Virginia in 2020. The projections for Colorado and Oregon states were given by Ys,2021=(Ys,2019+βse)(1+ Єs,2020×(Ps,2021Ps,2020)/Ps,2020)+βsep. The projection for Virginia was given by Ys,2021=Ys,2019 (1+ Єs,2019×(Ps,2020Ps,2019)/Ps,2019)+βsep+βse.

As TBOT data on tax and prices are available only up to 2019, the tax rates were updated up to the baseline year 2021 based on the announcements of tax increases by state revenue authorities. The state average cigarette prices for 2020 and 2021 were predicted based on a price regression given by: Pst=γ0+γ1 TAXst+γ2Est+γs+Σsγ3Dst, where γs is the state fixed effect, Dst represents the state-specific time trend and Pst, TAXst and Est are the price, tax and median earnings of state s in year t as defined before.

## Results

The baseline cigarette smoking prevalence varies widely from a low of 7.1% in Utah to 22.7% in West Virginia in 2021 (table 1). The price-adjusted trends over 2011–2019 also varies widely from −1.13 pp in the District of Columbia (DC) to 0.00 pp in Hawaii and Montana. The desired annual trend varies from −0.23 pp in Utah to −1.97 pp in West Virginia. The price-adjusted trends exceed the desired trends for only five states (eg, Washington, Utah, Rhode Island, Massachusetts and Maryland) and the DC which are on target. Among the remaining states, California with a trend gap of −0.02 pp is closest to the target, while West Virginia with a trend gap of −1.31 pp needs to catch up most.

Table 1

#### What important gaps in knowledge exist on this topic

• The feasibility of achieving the Healthy People 2030 goal is yet to be tested in view of the recent progress in tobacco control made in the USA.

• Previous research explored the potential of reaching the Healthy People goal by simulating the combined effect of tax and price increase, smoke-free indoor air law, mass media campaign and cessation support at the national level. Far less is known about how state-level tobacco control interventions can be tailored to help achieve a target level of smoking prevalence across all US states.

• In the USA, 45 states need systematic annual increases in cigarette excise tax rate in a range of $0.02−$1.37 per pack over 2022–2030 to meet the 5% smoking prevalence target.

• Tax increases tailored to the needs of individual states with scaled-up non-tax interventions can help achieve the desired progress in tobacco control.

## Acknowledgments

The author benefitted greatly from the comments of the participants during the e-poster presentation of this report at the Society for Research on Nicotine and Tobacco Research (SRNT) Virtual Annual Meeting, 2427 February 2021 and the oral presentation at the International Health Economic Association (iHEA) Congress, 1215 July 2021. The author would also like to acknowledge the feedback received from her colleagues at the American Cancer Society that helped improved the manuscript to a great extent. The author is thankful to three anonymous reviewers for their valuable comments.

• ## Supplementary Data

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• ## Supplementary Data

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

## Footnotes

• Correction notice The article has been corrected since it was published online first. The row for Tennessee under table 1 was changed to reflect the correct entry for each column.

• Contributors NN designed the study, analysed data, drafted and revised the manuscript.

• Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

• Competing interests No, there are no competing interests.

• Provenance and peer review Not commissioned; externally peer reviewed.

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