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

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.

A Mobile Health Intervention for Adolescents Exposed to Secondhand Smoke: Pilot Feasibility and Efficacy Study.

BACKGROUND: Secondhand smoke (SHS) exposure in children and adolescents has adverse health effects. For adolescents of lower socioeconomic status (SES), exposure is widespread, evidenced in the measurement of urinary cotinine, a major metabolite of nicotine. Direct intervention with exposed children has been proposed as a novel method, yet there is minimal evidence of its efficacy. Combining this approach with a mobile health (mHealth) intervention may be more time and cost-effective and feasible for adolescent populations. OBJECTIVE: In this pilot study, we assessed the feasibility and preliminary evidence of efficacy of a 30-day text message-based mHealth intervention targeted at reducing SHS exposure in adolescent populations of low SES. METHODS: For the study, 14 nonsmoking and nonvaping participants between the ages of 12-21 years exposed to SHS were enrolled. The intervention consisted of a daily text message sent to the participants over the course of a month. Text message types included facts and information about SHS, behavioral methods for SHS avoidance, or true-or-false questions. Participants were asked to respond to each message within 24 hours as confirmation of receipt. Feasibility outcomes included completion of the 30-day intervention, receiving and responding to text messages, and feedback on the messages. Efficacy outcomes included a reduction in urinary cotinine, accuracy of true-or-false responses, and participants' perceptions of effectiveness. RESULTS: Of the 14 participants that were enrolled, 13 completed the intervention. Though not required, all participants had their own cell phones with unlimited text messaging plans. Of the total number of text messages sent to the 13 completers, 91% (372/407) of them received on-time responses. Participant feedback was generally positive, with most requesting more informational and true-or-false questions. In terms of efficacy, 54% (6/11) of participants reduced their cotinine levels (however, change for the group overall was not statistically significant (P=.33) and 45% (5/11) of participants increased their cotinine levels. Of the total number of true-or-false questions sent across all completers, 77% (56/73) were answered correctly. Participants' ratings of message effectiveness averaged 85 on a scale of 100. CONCLUSIONS: In this pilot study, the intervention was feasible as the majority of participants had access to a cell phone, completed the study, and engaged by responding to the messages. The efficacy of the study requires further replication, as only half of the participants reduced their cotinine levels. However, participants answered the majority of true-or-false questions accurately and reported that the messages were helpful.