Research Article|Articles in Press

# Smoking Histories by State in the U.S.

Open AccessPublished:January 15, 2023

### Introduction

Smoking rates across U.S. states have declined at different rates over time because some states have progressive tobacco control policies, whereas others have yet to adopt them. Therefore, each state has its own unique historical experience of smoking initiation, cessation, and prevalence. This study characterizes smoking histories for each U.S. state by birth cohort.

### Methods

Using 1965–2018 National Health Interview Survey and 1992–2019 Tobacco Use Supplement to the Current Population Survey data, statistical methods applied an age‒period‒cohort modeling framework to reconstruct population-level smoking histories for each state. Smoking initiation, cessation, and intensity by age, gender, and cohort were estimated for each state. These were used to construct state-specific trends in the prevalence of current, former, and never smoking as well as the mean smoking duration and pack years. Analysis was conducted from 2017 to 2022.

### Results

California and Kentucky, respectively, are exemplar states of more and less aggressive tobacco control. Initiation probabilities were consistently lower in California than in Kentucky, and cessation probabilities were higher. Hence, the smoking prevalence derived from these parameters is higher in Kentucky. The intensity of cigarette smoking was higher in Kentucky than in California, yielding considerably higher estimated pack years when used with the other parameters. Summaries of smoking trends are given for all states.

### Conclusions

Smoking initiation, cessation, and intensity trends vary substantially across states, resulting in major differences in estimated smoking prevalence, duration, and pack years. Some states show improvements in smoking metrics over time with more recent birth cohorts, but others have shown very little.

## INTRODUCTION

Smoking rates vary substantially across the U.S.

Map of current cigarette use among adults. Centers for Disease Control and Prevention. www.cdc.gov/statesystem/cigaretteuseadult.html. Updated 2021. Accessed November 2, 2022.

In 2019, Utah and California had the nation's lowest smoking prevalence, with 7.9% and 10.0% of adults smoking, respectively, whereas nearly a quarter of adults still smoke in Kentucky (23.6%) and West Virginia (23.8%). In general, states in the Northeast and West Census regions have lower smoking prevalence than those in the South and Midwest.
• Cornelius ME
• Wang TW
• Jamal A
• Loretan CG
• Neff LJ.
Tobacco product use among adults — United States, 2019.
These geographic variations in smoking ultimately translate into state-level disparities in the total burden of smoking-related death and disease.
• Lortet-Tieulent J
• Goding Sauer A
• Siegel RL
• et al.
State-level cancer mortality attributable to cigarette smoking in the United States.
Smoking prevalence is a function of smoking initiation and cessation
• Holford TR
• Levy DT
• McKay LA
• et al.
Patterns of birth cohort–specific smoking histories, 1965–2009.
—the latter being more difficult among people who smoke with higher intensity (cigarettes smoked per day). State smoking variations reflect a combination of differences in the patterns of smoking uptake among youth and young adults, the level of smoking intensity, and the rates of successful quitting.
• Smoking cessation. A report of the Surgeon General HHS.
GA: HHS, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.
State and local tobacco control interventions can be designed to target each of these behaviors, thereby reducing smoking and related health harms. Direct historical estimates of smoking patterns could facilitate a more precise understanding of each state's smoking experience, capture the effects of factors that contribute to those behaviors, and guide future policymaking at the state and national levels.
The Cancer Intervention and Surveillance Modeling Network lung working group developed a smoking history generator (SHG) using data from the National Health Interview Survey (NHIS) to quantify the impacts of cigarette smoking on lung cancer mortality
• Moolgavkar SH
• Holford TR
• Levy DT
• et al.
Impact of reduced tobacco smoking on lung cancer mortality in the United States during 1975–2000.
,
• Jeon J
• Holford TR
• Levy DT
• et al.
Smoking and lung cancer mortality in the United States from 2015 to 2065: a comparative modeling approach.
and all-cause mortality for the U.S. population.
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
The SHG summarized the smoking history of birth cohorts by providing estimates of ever-smoker prevalence, initiation and cessation probabilities, and smoking intensity, which was used to estimate current, former, and never-smoking prevalence.
• Anderson CM
• Burns DM
• Dodd KW
• Feuer EJ
Chapter 2: Birth-cohort-specific estimates of smoking behaviors for the U.S. population.
These analyses use age‒period‒cohort (APC) models as a framework for estimating gender- and birth cohort-specific smoking histories and projecting them forward to provide a tool to evaluate future trends under status quo and other policy scenarios.
• Holford TR
• Chapter Clark LD.
4: Development of the counterfactual smoking histories used to assess the effects of tobacco control.
NHIS has collected U.S. smoking data since 1965, after the publication of the first Surgeon General's Report on Smoking and Health in 1964.
• Holford TR
• Levy DT
• McKay LA
• et al.
Patterns of birth cohort–specific smoking histories, 1965–2009.
,
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
,

Surgeon General's Advisory Committee on Smoking and Health. Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service. U.S. Department of Health, Education, and Welfare, Public Health Service, Office of the Surgeon General. https://www.unav.edu/documents/16089811/16155256/Smokin+and+Health+the+Surgeon+General+Report+1964.pdf. Published 1964. Accessed November 1, 2022.

The ≥50-year time span covered is a major strength for estimating temporal trends, but NHIS lacks the sample size and spatial detail necessary for analyzing smoking histories by state. Tobacco Use Supplement to the Current Population Survey (TUS-CPS) provides larger, state-representative samples that can be used for state-specific analyses. These surveys began collecting data in 1992, giving a history of just 26 years, making it more challenging to identify temporal trends within a cohort. The analysis presented in this study marries the temporal strengths of NHIS with the spatial strengths of TUS-CPS to estimate state-specific smoking histories. This work provides estimates for a comprehensive SHG that can be used to model the impact of smoking for each state and to explore the impacts of health policies within states in more detail.

## METHODS

This analysis brings together data from 2 surveys to estimate smoking transition parameters that characterize populations in each state. This paper provides an overview of the approach, and the Appendix (available online) gives further details.

### Study Sample

NHIS is a nationally representative survey that collected self-reported smoking behavior among adult (aged ≥18 years) civilian, non-institutionalized U.S. residents from 1965 to 2018, with 7,000–53,000 (IQR=18,000–32,000) adults in each round (response rate ∼70%).
• Carlson SA
• Densmore D
• Fulton JE
• Yore MM
• Kohl 3rd, HW
Differences in physical activity prevalence and trends from 3 U.S. surveillance systems: NHIS, NHANES, and BRFSS.
TUS-CPS has been administered by the U.S. Census Bureau as part of the Current Population Survey and includes detailed smoking and other tobacco data for the adult population. The survey was administered every 3–4 years since 1992, with waves in 1992–1993, 1995–1996, 1998–1999, 2000, 2001–2002, 2003, 2006–2007, 2010–2011, 2014–2015, and 2018–2019 and approximately 250,000 respondents per wave (74% response rate). Behavioral Risk Factor Surveillance System data offered snapshots of each state's smoking prevalence since 1993 but did not include questions about smoking initiation—critical for understanding smoking histories. Therefore, Behavioral Risk Factor Surveillance System data were not used for this analysis.
• Lortet-Tieulent J
• Goding Sauer A
• Siegel RL
• et al.
State-level cancer mortality attributable to cigarette smoking in the United States.
,

BRFSS prevalence & trends data. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health. https://www.cdc.gov/brfss/brfssprevalence/index.html. Updated September 13, 2017. Accessed June 8, 2022.

Behavioral risk factor surveillance system, annual survey data. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health. https://www.cdc.gov/brfss/annual_data/annual_data.htm. Updated 2022. Accessed June 8, 2022.

Behavioral risk factor surveillance system, CDC-list of states conducting surveillance by year. Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Division of Population Health. https://www.cdc.gov/brfss/annual_data/all_years/states_data.htm. Updated 2021. Accessed June 8, 2022.

Figure 1 shows the time spanned by NHIS and TUS-CPS, with years of the population surveyed (x-axis) and age (y-axis). Both surveys were cross-sectional, so they only captured responses at the time of the survey. However, some surveys asked for detailed retrospective information such as age at initiation or cessation, which lengthens the time horizon by providing information on the earlier experience of individuals in a birth cohort, as shown by the diagonal lines in Figure 1.
NHIS provided smoking initiation and cessation information for cohorts born as early as 1890 from subjects aged >75 years in the earliest survey in 1965.
• Holford TR
• Levy DT
• McKay LA
• et al.
Patterns of birth cohort–specific smoking histories, 1965–2009.
,
• Holford TR
• Levy DT
• Meza R.
Comparison of smoking history patterns among African American and White cohorts in the United States born 1890 to 1990.
However, calibration was required to adjust for higher mortality among individuals who smoke, resulting in selection bias for the survey sample. The later date at which TUS-CPS started limited the earliest cohort that was represented, shown to be about 1910 in Figure 1. Smoking initiation and cessation probabilities were estimated beginning with the 1908 cohort in each state. Data for the 1908 cohort were provided by individuals aged 85 years at the survey in 1993, providing initiation and cessation information for most of the cohort's life.

### Measures

The analysis used an established smoking model where individuals who have never smoked may transition to current smoking and then may quit smoking to become former smokers.
• Holford TR
• Levy DT
• McKay LA
• et al.
Patterns of birth cohort–specific smoking histories, 1965–2009.
,
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
,
• Anderson CM
• Burns DM
• Dodd KW
• Feuer EJ
Chapter 2: Birth-cohort-specific estimates of smoking behaviors for the U.S. population.
,
• Holford TR
• Levy DT
• Meza R.
Comparison of smoking history patterns among African American and White cohorts in the United States born 1890 to 1990.
The state-specific smoking history measures estimated by age for each gender and birth cohort include the following:
• 1.
prevalence of ever-smoking—proportion of individuals who have smoked at least 100 cigarettes in their lifetime (current or former smokers);
• 2.
initiation probability—conditional probability of transition to ever smoking by the end of a year for an individual who had never smoked at the beginning of that year;
• 3.
cessation probability—conditional probability of quitting smoking by the end of a year for an individual who was smoking at the beginning of that year (because of high relapse rates among those who recently quit, an individual was not classified as formerly smoking until having quit for at least 2 years. Relapses were censored in the year just before the interview);
• 4.
smoking intensity probability—cigarettes smoked per day (CPD) was classified into 6 categories (approximate mean CPD of each category): CPD≤5 (3), 5< CPD≤15 (10), 15<CPD≤25 (20), 25<CPD≤35 (30), 35<CPD≤45 (40), and 45<CPD (60);
• 5.
duration—length of exposure to smoking based on age at initiation and cessation; and
• 6.
pack years—calculated by multiplying cigarette packs smoked per day with smoking duration in years.

### Statistical Analysis

First, the prevalence of ever smoking after age 30 years was estimated directly from the NHIS survey data. This would capture the effect of differential mortality among those who smoke as cohort ages because initiation after age 30 years was rare.
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
,
• Anderson CM
• Burns DM
• Dodd KW
• Feuer EJ
Chapter 2: Birth-cohort-specific estimates of smoking behaviors for the U.S. population.
,
• Holford TR
• Levy DT
• Meza R.
Comparison of smoking history patterns among African American and White cohorts in the United States born 1890 to 1990.
Excess risk of death among smokers may lead to a declining prevalence of ever smoking as a cohort gets older. Still, a decline could also result from individuals forgetting or denying having smoked when they were younger. Estimating age trends required a relatively long span for each cohort. Because TUS-CPS had a history of only 26 years, estimated age trends were unstable. Instead, NHIS, with its 53-year history, was used to estimate the age effect for ever-smoking prevalence after age 30 years in the U.S., and this was assumed to be the same for each state. Similarly, when trying to simultaneously estimate period and cohort effects using TUS-CPS data, the cohort had a much longer time span than the period. It was assumed that the cohort had a more substantial temporal effect, so the period was excluded from the model.
• Holford TR
• Levy DT
• Meza R.
Comparison of smoking history patterns among African American and White cohorts in the United States born 1890 to 1990.
Hence, the model for the prevalence of ever smoking for each state included the age effect estimated from NHIS as an offset parameter, and the cohort effect was estimated using TUS-CPS data from each state.
In some TUS-CPS surveys, age at initiation was reported, which was used to obtain a crude estimate of the conditional initiation probability for each state using an APC model. To adjust for mortality differences caused by smoking, crude initiation probabilities were calibrated so the cumulative initiation probability at age 30 years was equal to the prevalence estimate at age 30 years obtained from the analysis of ever smoking.
TUS-CPS data on self-reported age at smoking cessation were also used to estimate cessation probabilities for each state. The conditional probability of a smoker at the beginning of the year quitting during that year was estimated using an APC model. The exception was for an individual quitting in the year just before the interview. These individuals were censored in the final year but coded as continuing to smoke in previous years. Estimates from the APC model were used to estimate cessation probabilities up to 2018, the last year of available data. The most recent estimate for a given age was then carried forward for future years.
For smoking intensity in each state, data from TUS-CPS on the number of CPD were used. The probability density among the six smoking intensity categories was estimated using an cumulative logistic model.
Smoking initiation and cessation probabilities were used to estimate age-specific prevalence for current, former, and never smoking; the distribution of smoking duration; and thus the mean duration of smoking exposure for each cohort. Assuming independence of duration and intensity provided an estimate of the joint distribution or pack years. This yielded estimates of mean pack years by age for each cohort.
For illustration purposes, California and Kentucky were compared and presented as exemplar states with more and less aggressive tobacco control policies. California had been more aggressive than many states in controlling smoking through public health policies, including smoke-free air laws. In contrast, Kentucky has been a tobacco-producing state that has introduced few policies to control cigarette smoking. See the Appendix (available online) for details on all states. Users can examine and compare the smoking patterns of different states at the website apps.cisnetsmokingparameters.org/states/. Analyses were conducted from 2017 to 2022.

## RESULTS

Figure 2A and B shows the birth-cohort trends in age-specific smoking initiation and cessation probabilities for females and males. Initiation probabilities in Kentucky were consistently higher than those in California over the entire time considered; however, probabilities reached their highest levels for females born in the 1940s and males born in the 1920s or 1930s and declined after that. This was especially true in California, but Kentucky has maintained considerably higher initiation probabilities. Before 2018, cessation increases with age for each cohort, and declines subsequently arise from carrying forward estimates from earlier cohorts for individuals who reach a given age after 2018. For cohorts born after 1950, cessation probabilities are considerably higher for California.
Initiation and cessation probability estimates with adjustment for differential mortality yield current smoker prevalence trends by cohort (Figure 2C). Higher initiation and lower cessation for Kentucky resulted in consistently higher prevalence estimates than in California. An exception occurs for the 1910 cohort when Kentucky's prevalence becomes lower than California's in older ages because cessation probabilities in this cohort increase more rapidly in Kentucky than in California (Figure 2B). In subsequent cohorts, the prevalence difference becomes more pronounced, a result of Kentucky's consistently lower cessation probabilities.
The mean number of CPD consistently declines with age (Appendix Figure 2, available online). Before 1960–1970, levels were similar for California and Kentucky, but more recently, California has considerably lower mean CPD. Appendix Figures 3 and 4 (available online) provide the estimates of the mean duration of smoking and pack years, respectively.
Full details for all the 50 states and the District of Columbia are conveniently displayed for user-selected comparison at the website apps.cisnetsmokingparameters.org/states/. Estimates are provided by single years of age (0–99) and by birth cohort (1908–2065).
Cumulative initiation probabilities at age 25 years, when most initiation will have occurred, standardized for the 2000 U.S. population, provide a summary of initiation for each cohort. Figure 3 shows trends in initiation up to age 25 years by birth cohort and gender, with a tile for each state. Female initiation is much lower than that of males for early cohorts, although recent differences are smaller. The pattern for females is similar to that for males in some states, for example, California, but the peak is lower. However, in Kentucky, the temporal variation by cohort is much smaller for females. This difference is apparent in several states with a recent higher prevalence of cigarette smoking.
Figure 4 shows the cumulative cessation probabilities for each cohort standardized for the 2000 U.S. population at age 60 years when the harmful impacts of smoking begin to have a substantial effect on personal health. These probabilities have increased substantially, and for most states, the probabilities are similar for males and females. For earlier cohorts, many states have lower cessation probabilities for females; however, a few states also have lower probabilities for females in recent cohorts, for example, Alabama, Rhode Island, and West Virginia. A careful study of Figures 3 and 4 provides insight into the history of initiation and cessation by the cohort that has resulted in the current prevalence of smoking in each state. Appendix Figure 5 (available online) provides current smoker prevalence estimates for all states.
Figure 5 shows the estimates of the mean duration among adults standardized for the 2000 population of the U.S. by calendar year. Estimates for California are low compared with those for Kentucky and are projected to continue decreasing. By contrast, in South Dakota and West Virginia, duration estimates are high and are projected to change very little. Standardized average pack years are shown by calendar year for each state in Figure 6, which shows substantial differences in the spatial patterns across states and over time. Trends decline with time; for most states, recent and projected values are similar by gender. However, some states have substantial gender differences, for example, Kentucky and Oklahoma.

## DISCUSSION

This study presents a comprehensive analysis of historical smoking experiences within each of the 50 U.S. states and the District of Columbia. These detailed smoking behavior profiles are useful for understanding the health consequences expected to flow from each state's smoking history. In California and Kentucky, initiation probabilities in males began to decline with the 1940 birth cohort and continued to steadily decline until the current birth cohorts. California females had a similar pattern, but the decline was somewhat later for Kentucky females. The Surgeon General's Report

Surgeon General's Advisory Committee on Smoking and Health. Smoking and Health: Report of the Advisory Committee to the Surgeon General of the Public Health Service. U.S. Department of Health, Education, and Welfare, Public Health Service, Office of the Surgeon General. https://www.unav.edu/documents/16089811/16155256/Smokin+and+Health+the+Surgeon+General+Report+1964.pdf. Published 1964. Accessed November 1, 2022.

on smoking and health appeared in 1964 when the 1940 birth cohort was aged 25 years, slightly later than the peak age for smoking initiation. The effect of this report appears to have been more consistently seen in males, but the impact on females is more complex. These results are consistent with results from earlier analyses for the whole U.S.,
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
which noted that some of the earliest studies on the health impacts of smoking appeared well before 1964, that is, public awareness had already begun to affect smoking behavior by the time the report was published.
• Holford TR
• Meza R
• Warner KE
• et al.
Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964–2012.
However, the decline in initiation probabilities varies among the states.
There is wide variability in tobacco control policies, with some states and localities enacting aggressive interventions that raise cigarette taxes, fund educational media campaigns,
• Colston DC
• Xie Y
• Thrasher JF
• et al.
Examining truth and state-sponsored media campaigns as a means of decreasing youth smoking and related disparities in the United States.
or restrict smoking in public places, whereas other states have yet to implement them. Georgia has the lowest average state cigarette tax at $0.37, whereas the District of Columbia and New York boast an average of$4.50 and \$4.35 per cigarette pack, respectively (Georgia and New York have not increased their tax since 2012).

Minosa MK. Key state-specific tobacco related data & rankings. Washington, DC: Campaign for Tobacco-Free Kids. https://www.tobaccofreekids.org/assets/factsheets/0176.pdf. Published July 13, 2022. Accessed January 11, 2022.

Today, 28 states and Washington, District of Columbia have comprehensive smoke-free air laws in place, yet 38% of the U.S. population remains without protection from clean air in workplaces, restaurants, and bars.

American Nonsmokers’ Rights Foundation. Summary of 100% Smokefree State laws and population protected by 100% U.S. Smokefree laws. American nonsmokers’ rights foundation. Berkeley, CA: American Nonsmokers’ Rights Foundation. https://no-smoke.org/wp-content/uploads/pdf/SummaryUSPopList.pdf. Published October 1, 2022. Accessed November 2, 2022.

This study provides detailed smoking histories for each state, allowing future research to explore the impact of these policy differences on geographic smoking disparities. These data also offer a starting point for assessing the potential impact of future state-level tobacco control efforts on public health.
Public health policies are not the only factors affecting the smoking behavior of individuals in a state. Differences in demographics and rurality can also influence smoking behavior; for example, overall smoking prevalence could be skewed downward by a high proportion of Hispanics in the population because of their lower-than-average smoking rates or skewed upward if the population is disproportionately rural given higher-than-average rural smoking rates.
• Tam J
• Warner KE
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• Gillespie JA.
Impact of changing U.S. demographics on the decline in smoking prevalence, 1980–2010.
Furthermore, social and cultural differences across the country may contribute to different attitudes toward tobacco use and the acceptability of tobacco control policies. For example, North Carolina, Kentucky, and Virginia are major tobacco-producing states.

Shahbandeh M. Major U.S. states in tobacco production 2015–2020. New York, NY: Statistica. https://www.statista.com/statistics/192022/top-10-tobacco-producing-us-states/. Published January 17, 2022. Accessed November 2, 2022.

These issues highlight the need for the state-level estimates of smoking behaviors provided by this study.

### Limitations

This analysis showed a rapid rise in cessation probabilities in recent cohorts compared with increases seen at comparable ages in older cohorts. In some cases, this yields a peak in the age trend for more recent cohorts (e.g., California in Figure 2B). However, cessation probabilities for recent birth cohorts are based on limited information (data available only for young people) and may therefore be less reliable. Recent cessation trends are challenging to estimate because the dynamics of smoking histories have changed greatly
• Jeon J
• Holford TR
• Levy DT
• et al.
Smoking and lung cancer mortality in the United States from 2015 to 2065: a comparative modeling approach.
,
• Méndez D
• Tam J
• Giovino GA
• Tsodikov A
• Warner KE.
Has smoking cessation increased? An examination of the U.S. Adult Smoking Cessation Rate 1990–2014.
owing in part to tobacco policies and the emergence of E-cigarettes in the tobacco product landscape.
• Brouwer AF
• Jeon J
• Cook SF
• et al.
The impact of menthol cigarette flavor in the U.S.: cigarette and ENDS transitions by sociodemographic group.
,
• Gentzke AS
• Creamer M
• Cullen KA
• et al.
Vital Signs: Tobacco product use among middle and high school students–United States, 2011-2018.
Another limitation is that both NHIS and TUS-CPS rely on self-reported smoking behavior, which may be subject to bias. Finally, the age effect estimated from the NHIS was assumed to be the same for each state, but it is possible that age effects could differ by state.

## CONCLUSIONS

This study describes temporal patterns by state, showing ongoing geographic disparities in smoking behaviors that have downstream health consequences. The burden of lung cancer differs by state,
• Lee YC
• Calderon-Candelario RA
• Holt GE
• Campos MA
• Mirsaeidi M.
State-level disparity in lung cancer survival in the United States.
and the pack-year estimates produced by this study could be useful for states in determining low-dose computed tomography eligibility and cancer control plans.
• Fedewa SA
• Kazerooni EA
• Studts JL
• et al.
State variation in low-dose computed tomography scanning for lung cancer screening in the United States.
The estimates can also inform tobacco simulation models to analyze the potential impact of tobacco control efforts—past, present, and future—without discounting differences in state experiences that would otherwise be masked by a country-level analysis.
• Levy DT
• Huang AT
• Havumaki JS
• Meza R.
The role of public policies in reducing smoking prevalence: results from the Michigan SimSmoke tobacco policy simulation model.
• Levy DT
• Yuan Z
• Li Y
• St Claire AW
• Schillo BA.
The Minnesota SimSmoke tobacco control policy model of smokeless tobacco and cigarette use.
• Sánchez-Romero LM
• Yuan Z
• Li Y
• Levy DT.
The Kentucky SimSmoke tobacco control policy model of smokeless tobacco and cigarette use.
• Levy DT
• Hyland A
• Higbee C
• Remer L
• Compton C.
The role of public policies in reducing smoking prevalence in California: results from the California tobacco policy simulation model.
Tam et al.
• Tam J
• Levy DT
• Jeon J
• et al.
Projecting the effects of tobacco control policies in the USA through microsimulation: a study protocol.
describe a web tool that considers the potential impact of specific state-level policy changes; this work used estimates that summarize smoking histories for the entire country,
• Holford TR
• Levy DT
• McKay LA
• et al.
Patterns of birth cohort–specific smoking histories, 1965–2009.
inferring parameters for a state based on policies that have been in place. Future extensions of these types of tools could rely on the parameters generated by this study. Decision makers and researchers who aim to evaluate the impact of programs and policies on population health can use these estimates to better address the harmful consequences of tobacco use in their states.

### ACKNOWLEDGMENTS

The study sponsor had no role in the study design; collection, analysis, and interpretation of data; writing of the report; or the decision to submit the report for publication.
This project was funded through National Cancer Institute Grants U01CA199284 and U01CA253858. The authors also acknowledge support from NCI grant U54CA229974.
No financial disclosures were reported by the authors of this paper.

### CRediT AUTHOR STATEMENT

Theodore R. Holford: Conceptualization, Formal analysis, Funding acquisition, Methodology, Project administration, Software, Supervision, Visualization, Writing – original draft. Lisa McKay: Data curation, Formal analysis, Methodology, Resources, Software, Visualization, Writing – review and editing. Jihyoun Jeon: Data curation, Methodology, Resources, Visualization, Writing – review and editing. Jamie Tam: Writing – original draft. Pianpian Cao: Data curation, Methodology, Resources, Visualization. Nancy L. Fleischer: Conceptualization, Writing – review and editing. David T. Levy: Conceptualization, Funding acquisition, Project administration, Writing – review and editing. Rafael Meza: Conceptualization, Funding acquisition, Methodology, Project administration, Writing – review and editing.

## SUPPLEMENT NOTE

This article is part of a supplement entitled Patterns of Birth Cohort-Specific Smoking Histories by Sociodemographic Group in the U.S., which is sponsored by the National Cancer Institute (NCI) Grants U01CA199284 and U01CA253858. Authors also acknowledge support from NCI grant U54CA229974. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of NCI.

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