Longitudinal transitions in tobacco use in youth and young adults: A latent transition analysis of the population assessment of tobacco and health study from Wave 1 to 5

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Abstract

Background: Tobacco use by youth and young adults can lead to significant long-term health problems. We aim to understand transitions in tobacco use patterns among these groups and the factors that affect transition patterns. Methods: Using the five waves of data from the nationally representative Population Assessment of Tobacco and Health (PATH) Study (2013–2019), we conducted latent class analysis and latent transition analysis to understand tobacco use classes and the longitudinal transitions between classes. We also adjusted for covariates, including demographics, individual behaviors, household environment, and psychosocial factors, to capture their effects on class transition probabilities. Results: Three tobacco use behaviors were identified: non-current user (C1), moderate e-cigarette user (C2), and poly-tobacco user (C3). At baseline (Wave 1), 94.4% of participants were classified as C1, 3.2% as C2, and 2.4% as C3, and the distribution shifted towards C2 and C3 over time. Progression to the next class represented the most common transitions (14.1% C2 to C3, 10.7% C1 to C2), while the direct progression from C1 to C3 was rare (0.6%). Being male, White, adult, living in smoking-allowed households, past-year alcohol use, drug use, internalizing problems, and social media follower of tobacco brands were associated with a faster progression to poly-tobacco use. Conclusions: The transition patterns implied that e-cigarette use might be an intermediate progression from non-current use into poly-tobacco use. Individual behaviors, household environment, and psychosocial factors are associated with elevated risks of progression. The findings may inform tobacco prevention and cessation policies among youth and young adults.

Original languageEnglish (US)
Article number107548
JournalAddictive Behaviors
Volume138
DOIs
StatePublished - Mar 2023

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Clinical Psychology
  • Toxicology
  • Psychiatry and Mental health

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