Differential Relationship between Tobacco Control Policies and U.S. Adult Current Smoking by Poverty

A systematic review and network meta-analysis of population-level interventions to tackle smoking behaviour

This preregistered systematic review and meta-analysis (PROSPERO: CRD 42022311392) aimed to synthesize the effectiveness of all available population-level tobacco policies on smoking behaviour. Our search across 5 databases and leading organizational websites resulted in 9,925 records, with 476 studies meeting our inclusion criteria. In our narrative summary and both pairwise and network meta-analyses, we identified anti-smoking campaigns, health warnings and tax increases as the most effective tobacco policies for promoting smoking cessation. Flavour bans and free/discounted nicotine replacement therapy also showed statistically significant positive effects on quit rates. The network meta-analysis results further indicated that smoking bans, anti-tobacco campaigns and tax increases effectively reduced smoking prevalence. In addition, flavour bans significantly reduced e-cigarette consumption. Both the narrative summary and the meta-analyses revealed that smoking bans, tax increases and anti-tobacco campaigns were associated with reductions in tobacco consumption and sales. On the basis of the available evidence, anti-tobacco campaigns, smoking bans, health warnings and tax increases are probably the most effective policies for curbing smoking behaviour.

Social Ecological Influences on Nicotine/Tobacco Use Among Gender-Varying and Gender-Stable Adolescents and Adults in the USA

BACKGROUND AND PURPOSE

Our study examined individual-, interpersonal-, community-, and policy-level associations with nicotine/tobacco use among gender-varying and gender-stable U.S. individuals.

METHODS

Data from Waves 2-4 (2014/15-2016/18) of the Population Assessment of Tobacco and Health (n = 33,197 U.S. adolescents and adults aged ≥14 years) and state-level gender minority policy data were used. Using multivariable logistic regression, the odds of past-30-day nicotine/tobacco use at W4 were estimated as a function of gender stability/variability, psychological distress, number of tobacco products used by family/friends, anti-tobacco marketing exposure, and change in gender minority-related policies from 2015 to 2017.

RESULTS

Gender-varying individuals had higher odds of nicotine/tobacco use compared with gender-stable individuals (AOR range = 1.7-2.3, p < .01). In the overall sample, positive change in gender minority policy protections (tallied from medium to high) was associated with lower odds of any nicotine/tobacco, other tobacco, and poly-tobacco use (AOR = 0.8, p < .05) compared to states with no change in their negative policies. Anti-tobacco marketing exposure was associated with lower odds of any tobacco, cigarette, e-cigarette, and poly-tobacco use compared with those who had no anti-tobacco marketing exposure (AOR = 0.9, p < .05). Higher psychological distress (AOR range = 1.7-2.4, p < .001) and an increasing number of tobacco products used by family/friends (AOR range = 1.1-1.3, p < .001) were associated with increased odds of nicotine/tobacco use.

CONCLUSIONS

Multilevel prevention and intervention strategies are needed to reduce the risk of nicotine/tobacco use among gender-varying and gender-stable individuals.

Good intentions, unintended outcomes: Impact of social assistance on tobacco consumption in Indonesia

INTRODUCTION

Social assistance programs create an income effect that allows low-income groups to raise their consumption to improve their well-being. However, this may unintentionally induce an increase in their consumption of temptation goods, including tobacco. By analyzing five massive social assistance programs distributed by the government since 2007, we explore whether those programs may induce increased smoking intensity in Indonesia.

METHODS

This study is a quantitative study that applies a Tobit regression, Difference-in-Differences (DiD) regression, Difference regression, and two-sample t-test, using the 2017 Susenas (National Socioeconomic Survey) and the 2007 and 2014 Indonesia Family Life Survey. Estimations using sociodemographic, regional, and social assistance dummy variables are used to explore the impact of the programs on the intensity of cigarette consumption in Indonesia, simultaneously assessing the relationship between cigarette consumption and socioeconomic conditions.

RESULTS

Our estimations using Tobit regressions confirm that social assistance recipients consume 3.39 cigarettes per capita per week more than non-recipients. The DiD regressions on IFLS panel data show that social assistance programs significantly increase cigarette consumption by 2.8 cigarettes per capita per week. We also find that: 1) smokers have lower socioeconomic indicators than non-smokers in terms of nutrition and health and education expenditures, and 2) younger household members living with smokers have less educational attainment and higher average sick days.

CONCLUSIONS

There is reasonable evidence to support the hypothesis that social assistance programs in Indonesia have contributed to the greater intensity of tobacco consumption among the recipients. The findings call for policy reforms in social assistance programs to be warier with the eligibility conditions for social assistance recipients. Adding new conditions related to smoking behaviors might reduce the smoking intensity of those in low-income groups and, in the long run, might improve the effectiveness of social assistance programs in raising the socioeconomic welfare of the low-income population.

Associations between smoking trajectories, smoke-free laws and cigarette taxes in a longitudinal sample of youth and young adults

Cigarette smoking patterns vary within the population, with some individuals remaining never smokers, some remaining occasional users, and others progressing to daily use or quitting. There is little research on how population-level tobacco control policy interventions affect individuals within different smoking trajectories. We identified associations between tobacco control policy interventions and changes across different smoking trajectories among adolescents and young adults. Using 15 annual waves of data drawn from the National Longitudinal Survey of Youth 1997 (NLSY97), we applied a group-based trajectory model to identify associations between days smoked per month, comprehensive smoke-free laws, cigarette tax rates, and known socio-demographic risk factors for membership in different smoking trajectories. Comprehensive smoke-free laws were associated with reduced risk of initiation and reductions in days smoked per month for all trajectories other than occasional users. Higher tax rates were associated with reduced risk of initiation and days smoked for all trajectories other than established users. Overall, population-based tobacco control policies, particularly comprehensive smoke-free laws, were associated with reduced smoking. Tobacco taxes primarily reduced risk of initiation and use among never smokers, experimenters, and quitters, consistent with previous research suggesting that tobacco manufacturers lower prices after tax increases to reduce the cost of continued smoking for established users. These results provide support for expanding smoke-free laws and establishing a minimum tobacco floor price, which could improve public health by reducing the risk of initiation as well as use among occasional and established smokers.

Cigarette smoking behaviors and the importance of ethnicity and genetic ancestry

Cigarette smoking contributes to numerous diseases and is one of the leading causes of death in the United States. Smoking behaviors vary widely across race/ethnicity, but it is not clear why. Here, we examine the contribution of genetic ancestry to variation in two smoking-related traits in 43,485 individuals from four race/ethnicity groups (non-Hispanic white, Hispanic/Latino, East Asian, and African American) from a single U.S. healthcare plan. Smoking prevalence was the lowest among East Asians (22.7%) and the highest among non-Hispanic whites (38.5%). We observed significant associations between genetic ancestry and smoking-related traits. Within East Asians, we observed higher smoking prevalence with greater European (versus Asian) ancestry (P = 9.95 × 10^-12). Within Hispanic/Latinos, higher cigarettes per day (CPD) was associated with greater European ancestry (P = 3.34 × 10^-25). Within non-Hispanic whites, the lowest number of CPD was observed for individuals of southeastern European ancestry (P = 9.06 × 10^-5). These associations remained after considering known smoking-associated loci, education, socioeconomic factors, and marital status. Our findings support the role of genetic ancestry and socioeconomic factors in cigarette smoking behaviors in non-Hispanic whites, Hispanic/Latinos, and East Asians.

Area-Level Predictors of Tobacco 21 Coverage in the U.S. Before the National Law: Exploring Potential Disparities

INTRODUCTION

The goal of the paper is to characterize the geographic and sociodemographic patterns of policies prohibiting tobacco sales to people aged <21 years (i.e., Tobacco 21) at the local, county, and state levels in the U.S. before the national law.

METHODS

This study assessed area-level markers for region, race/ethnicity, education, poverty status, and smoke-free law coverage as predictors of Tobacco 21 passage as of December 20, 2019, using modified Poisson and negative binomial regression models with robust SEs. Data were analyzed in 2020.

RESULTS

Before the passage of the national policy, 191 million people were covered by Tobacco 21 laws. Counties with higher percentages of non-Hispanic Blacks and individuals living below the poverty line had a lower probability of coverage, whereas counties with higher percentages of Hispanics/Latinxs and individuals with a college degree had a higher probability of coverage. Tobacco 21 coverage also varied by region, with far greater coverage in the Northeast than in the Midwest and South.

CONCLUSIONS

The national Tobacco 21 law may address disparities in coverage by SES, race/ethnicity, and region that could have lasting implications with regard to health equity.