Nicotine Intake in Adult Pod E-cigarette Users: Impact of User and Device Characteristics

Abstract

Introduction: This study examined user behavior, e-cigarette dependence, and device characteristics on nicotine intake among users of pod-mod e-cigarettes.

Aims and methods: In 2019-2020, people who use pod-mods in the San Francisco Bay Area completed questionnaires and provided a urine sample for analysis of total nicotine equivalents (TNE). The relationship between TNE and e-cigarette use, e-cigarette brands, e-liquid nicotine strength, e-cigarette dependence, and urine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), as a measure of combustible cigarette exposure, were examined.

Results: Of 100 participants (64% male, 71% in the 18-34 age group, 45% white), 53 used JUUL primarily, 12 used Puff Bar primarily, and 35 used other brands, including Suorin; 48 participants reported current cigarette smoking. Participants most often reported use of e-liquid with 4.5%-6.0% nicotine (68%), fruit (35%), tobacco (28%), and menthol or mint flavors (26%), used e-cigarettes on 25.5 (SD = 6.3) days a month, 10.2 (SD = 14.2) times a day, and 40% used 1-2 pods/cartridges per week. In bivariate analysis, urinary TNE was higher with greater frequency (days used) and intensity (number of pods used) of e-cigarette use, e-cigarette dependence, and combustible cigarette use. In multivariable analysis, days of e-cigarette use in the last 30 days, number of pods used per week, and NNAL levels were significantly associated with TNE. There was no significant impact of e-liquid nicotine strength on TNE.

Conclusions: Nicotine intake among people who used pod-mod e-cigarettes increased with e-cigarette consumption and e-cigarette dependence, but not with e-liquid nicotine strength. Our findings may inform whether FDA adopts a nicotine standard for e-cigarettes.

Implications: The study examined how device and user characteristics influence nicotine intake among pod-mod e-cigarette users. Nicotine intake increased with frequency (days of e-cigarette use in past 30 days) intensity of use (number of pods used per day) and e-cigarette dependence but not with the flavor or nicotine concentration of the e-liquids. Regulation of nicotine concentration of e-liquids is unlikely to influence nicotine exposure among adult experienced pod-mod users.

Figure 1.

Differences in average urinary total nicotine equivalents (TNE) across (A) number of days vaped in the last 30 days; (B) number of pods/cartridges used per week; (C) e-cigarette dependence, as measured by the Penn State Electronic Cigarette Dependence Index (PSECDI); (D) NNAL-verified smoking status (cigarette nonsmoker vs. cigarette smoker); (E) brand of pod-mod; and (F) e-liquid nicotine concentration. Bars indicate significant differences in urinary TNE across categories of each variable (α < 0.05). The TNE measured was TNE7, the molar sum of nicotine and 6 of its metabolites. SD = standard deviation.