In the first set of models (model 1), we evaluated the association of e-cigarettes use across different strata of a given product characteristic at baseline in the entire sample (eg, never use, previous e-cigarettes use, e-cigarettes use in the past 30 days using a vape pen, and e-cigarettes use in the past 30 days using a mod) with the number of cigarettes smoked in the past 30 days at follow-up (adjusted for demographic characteristics), number of cigarettes smoked at baseline, and number of days e-cigarettess were used in the past 30 days at baseline. A second set of models (model 2) was restricted to past-30-day e-cigarettes users at baseline to compare the effect of each product characteristic (eg, for device type: vape pen versus mod) among recent users on subsequent frequency of cigarette smoking. In a third set of models (model 3), we included statistically significant product characteristics identified in model 2 to examine whether some product characteristics were stronger risk factors for cigarette-smoking frequency after adjusting for other product characteristics. For all models, rate ratio (RR) estimates were calculated by exponentiating each β estimate; 95% confidence intervals (CIs) are also reported.

All models were adjusted for sex, race and/or ethnicity (collapsed to a 3-level variable: non-Hispanic white, Hispanic white, and other), highest parental education, number of cigarettes smoked at baseline, and number of days of e-cigarettes use at baseline; a random effect for community was included when statistically significant. All statistical analyses were based on 2-sided hypotheses tested at a 0.05 level of significance. Analyses were performed by using SAS version 9.4 (SAS Institute, Inc, Cary, NC), and data manipulation and graphics were generated by using the ggplot2 package in R version 3.4.4.

The number of cigarettes smoked in the past 30 days at follow-up was higher for male participants (versus female participants) and for those with parents who had some college or a college degree or higher (versus a high school degree or less) (Supplemental Fig 3A, Table 1). No differences were observed by ethnicity. Similar patterns emerged in the sample restricted to past-30-day e-cigarettes users at baseline.

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