Investigating Risk Factors for Racial Disparity in E-Cigarette Use with PATH Study

Amy Liu, Kennedy Dorsey, Almetra Granger, Ty-Runet Bryant, Tung-Sung Tseng, Michael Celestin and Qingzhao Yu ()
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Amy Liu: Statistics and Computer Science, Duke University, Trinity College of Arts and Sciences, Durham, NC 27708, USA
Kennedy Dorsey: Behavioral and Community Health Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70112, USA
Almetra Granger: Behavioral and Community Health Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70112, USA
Ty-Runet Bryant: Behavioral and Community Health Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70112, USA
Tung-Sung Tseng: Behavioral and Community Health Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70112, USA
Michael Celestin: Behavioral and Community Health Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70112, USA
Qingzhao Yu: Biostatistics and Data Sciences, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA 70122, USA

Stats, 2024, vol. 7, issue 3, 1-14

Abstract: Background: Previous research has identified differences in e-cigarette use and socioeconomic factors between different racial groups However, there is little research examining specific risk factors contributing to the racial differences. Objective: This study sought to identify racial disparities in e-cigarette use and to determine risk factors that help explain these differences. Methods: We used Wave 5 (2018–2019) of the Adult Population Assessment of Tobacco and Health (PATH) Study. First, we conducted descriptive statistics of e-smoking across our risk factor variables. Next, we used multiple logistic regression to check the risk effects by adjusting all covariates. Finally, we conducted a mediation analysis to determine whether identified factors showed evidence of influencing the association between race and e-cigarette use. All analyses were performed in R or SAS. The R package mma was used for the mediation analysis. Results: Between Hispanic and non-Hispanic White populations, our potential risk factors collectively explain 17.5% of the racial difference, former cigarette smoking explains 7.6%, receiving e-cigarette advertising 2.6%, and perception of e-cigarette harm explains 27.8% of the racial difference. Between non-Hispanic Black and non-Hispanic White populations, former cigarette smoking, receiving e-cigarette advertising, and perception of e-cigarette harm explain 5.2%, 1.8%, and 6.8% of the racial difference, respectively. E-cigarette use is most prevalent in the non-Hispanic White population compared to non-Hispanic Black and Hispanic populations, which may be explained by former cigarette smoking, exposure to e-cigarette advertising, and e-cigarette harm perception. Conclusions: These findings suggest that racial differences in e-cigarette use may be reduced by increasing knowledge of the dangers associated with e-cigarette use and reducing exposure to e-cigarette advertisements. This comprehensive analysis of risk factors can be used to significantly guide smoking cessation efforts and address potential health burden disparities arising from differences in e-cigarette usage.

Keywords: e-cigarettes; smoking cessation; disparities (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2024
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