Characterization of e-cigarette users according to device type, use behaviors, and self-reported health outcomes: Findings from the EMIT study

INTRODUCTION: Electronic cigarettes (e-cigarettes) rapidly evolved from large modifiable (MOD) devices, to small and affordable ‘POD’ devices. Detailed information on user demographics and preferences according to device type, which can inform potential chemical exposure and policy recommendations, is currently limited. The goal of this study is to describe user demographics, use behaviors and preferences, as well as self-reported health outcomes according to the e-cigarette device type used. METHODS: From April 2019 to March 2020, 91 participants from Maryland (18 MOD users, 26 POD users, 16 dual users (use of both combustible and e-cigarettes), and 31 non-users (never e-cigarette users and never smokers or >6 months former use) were recruited. A comprehensive questionnaire collected sociodemographic characteristics, e-cigarette/tobacco use behaviors, self-reported health outcomes, device characteristics and preferences. Chi-squared tests for categorical variables, ANOVA for continuous variables, qualitative thematic analysis, linear and logistic regressions were used to assess relationships between variables and groups. RESULTS: POD users were younger (average 22.5 years) than MOD users (30.8 years) or dual users (34.3 years) (p<0.001). MOD users reported more puffs per day (mean ± SD: 373 ± 125 puffs) compared to POD users (123.0 ± 172.5). E-cigarette users who were former smokers used 1.16 mg/mL lower nicotine concentrations compared to lifetime exclusive e-cigarette users (p=0.03) in linear models. Exclusive POD users self-reported more coughing than exclusive MOD or dual users (p=0.02). E-cigarette users reported more shortness of breath, headaches, and fatigue from their e-cigarette use compared to non-users. CONCLUSIONS: We found significant differences between user demographics, e-cigarette preferences, device characteristics, and use behaviors by user group. This information can help explain exposure to chemicals from e-cigarettes, including compounds with known toxic effects (e.g. metals, formaldehyde), and help inform the design of prevention and intervention strategies and policy decisions.