Factors associated with e-cigarette use in u.S. young adult never smokers of conventional cigarettes: A machine learning approach

Nkiruka C. Atuegwu, Cheryl Oncken, Reinhard C. Laubenbacher, Mario F. Perez, Eric M. Mortensen

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

E-cigarette use is increasing among young adult never smokers of conventional cigarettes, but the awareness of the factors associated with e-cigarette use in this population is limited. The goal of this work was to use machine learning (ML) algorithms to determine the factors associated with current e-cigarette use among US young adult never cigarette smokers. Young adult (18–34 years) never cigarette smokers from the 2016 and 2017 Behavioral Risk Factor Surveillance System (BRFSS) who reported current or never e-cigarette use were used for the analysis (n = 79,539). Variables associated with current e-cigarette use were selected by two ML algorithms (Boruta and Least absolute shrinkage and selection operator (LASSO)). Odds ratios were calculated to determine the association between e-cigarette use and the variables selected by the ML algorithms, after adjusting for age, gender and race/ethnicity and incorporating the BRFSS complex design. The prevalence of e-cigarette use varied across states. Factors previously reported in the literature, such as age, race/ethnicity, alcohol use, depression, as well as novel factors associated with e-cigarette use, such as disabilities, obesity, history of diabetes and history of arthritis were identified. These results can be used to generate further hypotheses for research, increase public awareness and help provide targeted e-cigarette education.

Original languageEnglish (US)
Article number7271
Pages (from-to)1-17
Number of pages17
JournalInternational journal of environmental research and public health
Volume17
Issue number19
DOIs
StatePublished - Oct 1 2020
Externally publishedYes

Keywords

  • Behavioral risk factor surveillance system
  • Boruta
  • E-cigarette
  • Electronic nicotine delivery system
  • LASSO
  • Machine learning
  • Never smokers of conventional cigarettes
  • Sole e-cigarette use
  • Vaping
  • Young adults

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Health, Toxicology and Mutagenesis

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