adults who exclusively vape E-cigarettes or dual use with cigarettes

BACKGROUND

Identifying the correlates of using e-cigarettes with high nicotine concentrations in exclusive and dual-using vapers can elucidate which subpopulations might be most impacted by e-cigarette regulatory activities related to nicotine concentration.

METHODS

Data are drawn from Wave 5 (December 2018-November 2019) of the Population Assessment of Tobacco and Health (PATH) study. Self-reported nicotine concentration was grouped as high (5.0 %+), moderate (1.8-4.9 %), low (0.1-1.7 %), 0 %, and "I don't know." Multivariable logistic regressions estimated associations of sociodemographic factors, tobacco use status, and e-cigarette use patterns of high nicotine concentration vs. other nicotine levels, stratified by current exclusive e-cigarette use and dual use of e-cigarettes and cigarettes.

RESULTS

In the study samples (exclusive e-cigarette use [n = 1,755], dual-use [n = 1,200]), higher proportions of exclusive e-cigarette users reported using high nicotine concentrations than dual users (18.3 % vs. 8.6 %). Among exclusive e-cigarette users, never vs. former smokers and daily (vs. someday) e-cigarette users were more likely to use high vs. low nicotine. In both exclusive and dual users, younger (vs. older) adults were more likely to report using high nicotine concentration e-cigarettes than most other nicotine levels. Current dual users who did vs. did not report using e-cigarettes to quit smoking had higher odds of using high vs. 0 % nicotine concentrations.

CONCLUSIONS

High-nicotine e-cigarette use might be elevated in subpopulations that face greater risks for vaping (e.g., never smokers, young adults) than groups who benefit from the potential harm reduction. Regulatory restrictions on high-nicotine products may selectively affect some subgroups adversely impacted by vaping.

E-cigarette device and liquid characteristics and E-cigarette dependence: A pilot study of pod-based and disposable E-cigarette users

BACKGROUND

E-cigarette device and liquid characteristics, such as electrical power output and liquid nicotine concentration, determine the rate at which nicotine is emitted from the e-cigarette (i.e., nicotine flux), and thus are likely to influence user nicotine dependence. We hypothesize that nicotine flux would be associated with the E-cigarette Dependence Scale (EDS) among pod-based and disposable e-cigarette products.

METHODS

Data were obtained from online panel participants between 18 and 65 years of age, who had indicated that they were either former or current e-cigarette users and resided within the United States (N = 1036). To be included in these analyses, participants had to provide information regarding device type (pod-based or disposable), power (watts), and nicotine concentration (mg/mL), from which we could determine nicotine flux (µg/s) (N = 666). To assess the relationship between nicotine flux and EDS, a series of multivariable linear regressions were conducted. Each model was separated by device type and adjusted for by age and past 30-day e-cigarette use.

RESULTS

Greater nicotine flux was associated with higher EDS scores among pod-based e-cigarette users (beta = 0.19, SE = 0.09, p-value = 0.043), but not users of disposable e-cigarettes. Neither power nor nicotine concentration were associated with EDS scores among users of either e-cigarette device type.

CONCLUSION

Results support the hypothesis that nicotine flux is positively associated with nicotine dependence in a sample of current users of pod-based and disposable e-cigarettes.

Discrimination of nicotine content in electronic cigarettes

INTRODUCTION

Behavioral discrimination of nicotine has only recently been assessed in humans, administered mostly by nasal spray before the newly available Spectrum research cigarettes differing in nicotine content. Here we wanted to explore applicability of these procedures to assess discrimination of nicotine administered by e-cigarettes.

METHODS

In this feasibility study, 16 adult smokers were tested on ability to discriminate e-cigarettes with nicotine concentrations of 36, 24, and 12 mg/ml, one per session (in that order), from a placebo (0 mg/ml), each identified only by letter code. Reliable discrimination was defined by accurately identifying which was which (i.e. nicotine vs placebo) on >85% of trials (i.e. ≥7 of 8; p < .05). Subjective perceptions were also assessed.

RESULTS

Discrimination from placebo was shown with 36 mg/ml and with 24 mg/ml nicotine in 15 of 16 subjects, but only 10 discriminated placebo from 12 mg/ml nicotine. Subjective items previously related to acute nicotine exposure ("how much nicotine", "head rush/buzzed" on 0-100 VAS) generally showed nicotine concentration-dependent effects, as expected, but so did "throat irritation".

CONCLUSIONS

Preliminary results confirm feasibility of using our behavioral procedure to assess ability to discriminate nicotine administered via these e-cigarettes, broadening generalizability of this procedure beyond nicotine via nasal spray and smoked tobacco cigarettes. Findings also suggest its applicability with testing discrimination of nicotine via other methods of rapid dosing (e.g., hookah, novel products), including the newer e-cigarette products. Further study with larger samples may identify individual difference and other factors influencing nicotine discrimination administered via e-cigarettes and other products.