Substance use & misuse · 2025
Latent Structure of Past 12-Month Tobacco Use in Wave 6 of the Population Assessment of Tobacco and Health: Examining for Differential Substructure by Generational Status.
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Clifford James S, Williams Ronaldo T, Hall Caitlyn, Moya Quezada Fernanda, Blondino Courtney T
Аннотация
INTRODUCTION: Tobacco product usage patterns vary significantly across different segments of the population. Combustible tobacco product usage decreased from 19.3% to 12.5%, while electronic cigarette (ECIG) use rose from 1.8% to 3.7% for the US population from 2010 to 2020. However, age-specific estimates differ between younger and older adults. It is possible there are latent subpopulations within American adults.
METHOD: Data from Wave 6 of the Population Assessment of Tobacco and Health survey (PATH, N = 30,516) were analyzed. Participants were classified as a member of Generation Z (N = 10,920), Millennials (N = 10,450), Generation X (N = 6122), or Baby Boomers (N = 3024) via a 6-level ordinal variable collected by PATH. Latent class analysis (LCA) identified distinct groups based on 8 tobacco use variables.
RESULTS: Analysis suggests that a 4-class solution provides the optimal solution for the entire sample. These classes comprised of a low-use class, a high-use class, ECIG Plus (defined as ECIG use with less probability of other tobacco product use), and a conventional user class, defined as high probability on conventional tobacco products. A 4-class solution also provided optimal fit for each generation, though the classes were defined differently.
DISCUSSION: Understanding tobacco use patterns across different classes is crucial for public health interventions. The discovery of a possible class of social users among Generation Z and Millennials suggests that targeted interventions tailored to the social contexts and behaviors of younger generations may be effective while pharmacological treatments may be more efficacious for Baby Boomers.
METHOD: Data from Wave 6 of the Population Assessment of Tobacco and Health survey (PATH, N = 30,516) were analyzed. Participants were classified as a member of Generation Z (N = 10,920), Millennials (N = 10,450), Generation X (N = 6122), or Baby Boomers (N = 3024) via a 6-level ordinal variable collected by PATH. Latent class analysis (LCA) identified distinct groups based on 8 tobacco use variables.
RESULTS: Analysis suggests that a 4-class solution provides the optimal solution for the entire sample. These classes comprised of a low-use class, a high-use class, ECIG Plus (defined as ECIG use with less probability of other tobacco product use), and a conventional user class, defined as high probability on conventional tobacco products. A 4-class solution also provided optimal fit for each generation, though the classes were defined differently.
DISCUSSION: Understanding tobacco use patterns across different classes is crucial for public health interventions. The discovery of a possible class of social users among Generation Z and Millennials suggests that targeted interventions tailored to the social contexts and behaviors of younger generations may be effective while pharmacological treatments may be more efficacious for Baby Boomers.