Introduction: E-cigarettes are the most commonly used tobacco product among US youth, with an estimated 3 million youth users. Health effects associated with e-cigarette use are not well understood but may include heart and lung effects. Despite the prevalence of use and potential health effects, factors related to e-cigarette use among youth are not yet established. Past predictive models for traditional cigarette use among youth included variables such as age, sex, self-esteem, use of other tobacco products, living with a smoker, friends’ tobacco use, appeal of ads and flavors, and knowledge of health effects related to use, but it is unknown if such predictive models apply to e-cigarette use.
Specific Aims: This study aimed to 1) evaluate the relationship between established predictive factors related to cigarette use with e-cigarette use in our population and 2) model these factors to determine which are associated with e-cigarette use in the presence of others.
Methods: A survey of tobacco use and perceptions was conducted with youth in the Appalachian regions of three states (N=936). Logistic regression was used to examine the combined relationship between multiple factors related to traditional cigarette use and the odds of e-cigarette use.
Results: Eighty-seven participants (9.3%) reported current e-cigarette use. Use of other tobacco products (AOR range 1.9-2.1), friends’ e-cigarette use (AOR 3.9), appeal of e-cigarette flavors (AOR 4.7) and ads (AOR 1.8), and beliefs that e-cigarettes do not cause health problems (AOR 1.3) were all significantly related to increased odds of current e-cigarette use. Factors previously associated with traditional cigarette use such as age, sex, self-esteem, and living with tobacco users were not significantly associated with e-cigarette use in this model.
Conclusions: Similarities exist between variables used in predictive models for cigarette use and those associated with e-cigarette use in this sample; however, some of the cigarette demographic predictors were not associated with e-cigarette use. Additional research concerning factors associated with e-cigarette use, especially among at-risk populations such as youth, is needed in order to build a model to predict those vulnerable for e-cigarette use.