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INTRODUCTION E-cigarette use among youth and young adults remains of public health concern. Pod-based e-cigarettes, including JUUL, significantly changed the e-cigarette landscape in the US. Using an online survey, we explored the socio-behavioral correlates, predisposing factors, and addictive behaviors, among young adult pod-mod users within a University in Maryland, USA. METHODS In total, 112 eligible college students aged 18--24 years, recruited from a University in Maryland, who reported using pod-mods were included in this study. Participants were categorized into current/non-current users based on past- 30-day use. Descriptive statistics were used to analyze participants' responses. RESULTS The mean age of the survey participants was 20.5 ± 1.2 years, 56.3% were female, 48.2% White, and 40.2% reported past-30-day (current) use of pod-mods. The mean age of first experimentation with pod-mods was 17.8 ± 1.4 years, while the mean age of regular use was 18.5 ± 1.4 years, with the majority (67.9%) citing social influence as the reason for initiation. Of the current users, 62.2% owned their own devices, and 82.2% predominantly used JUUL and menthol flavor (37.8%). A significant proportion of current users (73.3%) reported buying pods in person, 45.5% of whom were aged <21 years. Among all participants, 67% had had a past serious quit attempt. Among them, 89.3% neither used nicotine replacement therapy nor prescription medications. Finally, current use (adjusted odds ratio, AOR=4.52; 95% CI: 1.76--11.64), JUUL use (AOR=2.56; 95% CI: 1.08-6.03), and menthol flavor (AOR=6.52; 95% CI: 1.38-30.89) were associated with reduced nicotine autonomy, a measure of addiction. CONCLUSIONS Our findings provide specific data to inform the development of public health interventions targeted at college youth, including the need for more robust cessation support for pod-mod users. [ABSTRACT FROM AUTHOR]

The e-cigarette or vaping product-use-associated lung injury (EVALI) epidemic was primarily associated with the use of e-cigarettes containing tetrahydrocannabinol (THC)- the principal psychoactive substance in cannabis, and vitamin-E-acetate- an additive sometimes used in informally sourced THC-containing e-liquids. EVALI case burden varied across states, but it is unclear whether this was associated with state-level cannabis vaping prevalence. We, therefore, used linear regression models to assess the cross-sectional association between state-level cannabis vaping prevalence (obtained from the 2019 behavioral Risk Factor Surveillance System) and EVALI case burden (obtained from the Centers for Disease Control and Prevention) adjusted for state cannabis policies. Cannabis vaping prevalence ranged from 1.14%(95%CI, 0.61%-2.12%) in Wyoming to 3.11%(95%CI, 2.16%-4.44%) in New Hampshire. EVALI cases per million population ranged from 1.90(0.38–3.42) in Oklahoma to 59.10(19.70–96.53) in North Dakota. There was no significant positive association but an inverse association between state cannabis vaping prevalence and EVALI case burden (Coefficient, -18.6; 95%CI, -37.5–0.4; p-value, 0.05). Thus, state-level cannabis vaping prevalence was not positively associated with EVALI prevalence, suggesting that there may not be a simple direct link between state cannabis vaping prevalence and EVALI cases, but rather the relationship is likely more nuanced and possibly reflective of access to informal sources of THC-containing e-cigarettes. [ABSTRACT FROM AUTHOR]

Use of substances other than nicotine in e-cigarettes, especially marijuana, is becoming increasingly popular in the US. However, population-representative data on such poly-use (nicotine and marijuana) remains limited. We therefore conducted a cross-sectional logistic regression analysis of the 2018 Behavioral Risk Factor Surveillance System among 16 US states/territories with data on past 30-day marijuana use to describe the emerging dual nicotine and marijuana vaping population. We additionally examined trends in marijuana use, including marijuana vaping, from 2016 to 2018. Of the 131,807 participants studied, 3068 were current e-cigarette users, among whom 7.1% also vaped marijuana. Prevalence of nicotine-predominant, dual nicotine marijuana, and marijuana-predominant vaping was 3.36%, 0.38% and 1.09%, respectively. Compared to nicotine-predominant vapers, dual and marijuana-predominant vapers were older, had greater proportions of non-Whites, particularly Hispanics, and less likely to be current smokers (nicotine-predominant vs dual vs marijuana-predominant vaping: current tobacco use 44.7 vs 23.7 vs 11.1%). Proportion of dual vapers among current e-cigarette users was 8.6%, 2.6% and 7.1% for 2016, 2017 and 2018, respectively. Prevalence of marijuana use increased from 8.97% (2016) to 13.1% (2018) while no clear trend was observed for marijuana vaping. Dual nicotine and marijuana vaping is prevalent in the US, and compared to predominantly nicotine vapers such users have higher mean ages, and are more likely to be Blacks, Hispanics, and never cigarette smokers. Marijuana use overall increased from 2016 to 2018. Dual vapers represent a large and important emerging population that will require dedicated study of health effects and tailored regulatory strategies. [ABSTRACT FROM AUTHOR]

Background: The popularity of electronic cigarettes (E-cigarettes) has risen considerably. Several studies have suggested that nicotine may affect insulin resistance, however, the impact of E-cigarette exposure on insulin resistance, an early measure of cardiometabolic risk, is not known. Methods and results: Using experimental animals and human data obtained from 3,989 participants of the United States National Health and Nutrition Examination Survey (NHANES), respectively, we assessed the association between E-cigarette and conventional cigarette exposures and insulin resistance, as modelled using the homeostatic model assessment of insulin resistance (HOMA-IR) and glucose tolerance tests (GTT). C57BL6/J mice (on standard chow diet) exposed to E-cigarette aerosol or mainstream cigarette smoke (MCS) for 12 weeks showed HOMA-IR and GTT levels comparable with filtered air-exposed controls. In the NHANES cohort, there was no significant association between defined tobacco product use categories (non-users; sole E-cigarette users; cigarette smokers and dual users) and insulin resistance. Compared with non-users of e-cigarettes/conventional cigarettes, sole E-cigarette users showed no significant difference in HOMA-IR or GTT levels following adjustment for age, sex, race, physical activity, alcohol use and BMI. Conclusion: E-cigarettes do not appear to be linked with insulin resistance. Our findings may inform future studies assessing potential cardiometabolic harms associated with E-cigarette use. [ABSTRACT FROM AUTHOR]

Background: E-cigarettes are a consumer product designed to deliver nicotine by heating a liquid produced from tobacco. Usage in the US is growing rapidly and is common among combustible cigarette users (dual use). The impact of E-cigarettes on cardiovascular disease is unknown. Aim: A cross-sectional examination of e-cigarette use with self-reported cardiovascular disease, according to smoking status, using the nationally representative health survey - the Behavioral Risk Factor Surveillance System (BRFSS) 2016 Methods: We included 404,332 BRFSS 2016 participants with information on the history of CVD and e-cigarette use. E-cigarette use was categorized as never (reference), occasional, and daily with daily +occasional e-cigarette users considered current e-cigarette users. The association of e-cigarette use and CVD (defined as self-reported coronary heart disease, myocardial infarction, or stroke) was assessed using multivariable logistic regression models stratified by smoking status (never, former, current [occasional or daily]), adjusted for age, sex and race. Results: Of the total population, there were 15,240 e-cigarette users and 85,402 with CVD. Compared to those who never used e-cigarettes, current e-cigarette users had significantly higher odds of having CVD among current smoker groups (occasional smoker: Odds Ratio (OR)= 1.36 (95% CI= 1.06 - 1.76); daily smoker: OR=1.34 (1.12 - 1.62)). Daily use of e-cigarettes among occasional smokers was significantly associated with higher odds of having CVD (OR=1.64 (1.05 - 2.57)). (Table) There was no association between e-cigarette use and CVD among never and former smokers. Strengths and Limitations: Because of large sample size, we were powered to stratify e-cigarette use by smoking status. However, BRFSSS does contain directly measured risk factors or pack-years of smoking. Conclusions: Dual use of e-cigarette and combustible cigarettes is a new pattern of tobacco product use that may be associated with more CVD. [ABSTRACT FROM AUTHOR]