Disparities in Cigarette, E-cigarette, Cigar, and Smokeless Tobacco Use at the Intersection of Multiple Social Identities in the US Adult Population. Results From the Tobacco Use Supplement to the Current Population Survey 2018–2019 Survey

Abstract

Abstract Introduction Sociodemographic disparities in tobacco use are prevalent and persistent in the United States. Nevertheless, few studies have examined disparities in tobacco use from an intersectionality perspective. We developed a visualization tool to identify disparities in cigarette, e-cigarette, cigar, and smokeless tobacco use at the intersection of multiple social identities. Aims and Methods We used the 2018–2019 Tobacco Use Supplement to the Current Population Survey (TUS-CPS) to estimate the prevalence of tobacco product use at the intersection of age (18–34, 35–54, ≥55 years), sex (male, female), race/ethnicity (Non-Hispanic [NH] White, NH Black, Hispanic, NH Other), and annual household income (<$50 000, $50 000–$99 999, and ≥$100 000). Estimates accounted for the complex survey design. Results For cigarettes, the most defining characteristic was income, with the highest prevalence among low-income NH White male adults aged 35–54 years (30.7%) and low-income NH White female adults aged 35–54 years (29.7%). For e-cigarettes, the most defining characteristic was age, with adults 18–34 years old having the highest prevalence. High prevalence groups for cigars included young- and middle-aged NH Black and NH White males, while NH White males had the highest prevalence of smokeless tobacco use. Conclusions Our intersectionality visualization tool is helpful to uncover complex patterns of tobacco use, facilitating the identification of high-risk groups. Implications We created a visualization tool to identify disparities in cigarette, e-cigarette, cigar, and smokeless tobacco use at the intersection of age, sex, race/ethnicity, and income. Our visualization tool helps uncover complex patterns of tobacco use, facilitating the identification of high-risk population groups that would otherwise be masked. These results can be used to implement tobacco control policies targeted at factors that promote or sustain tobacco use disparities.