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Objective: This study is the first to examine the influence of e-cigarette emission phrasing on perceived harm of secondhand exposure, and whether harm perception was associated with support for a tobacco-free campus policy. Participants: In the fall 2018 and spring 2019 semesters, 52 sections of a college English course (N = 791 students) were cluster randomized to one of three conditions ("vapor," "aerosol," or "chemicals") assessing harm of secondhand exposure to e-cigarette emissions. Methods: Regression models adjusted for demographic characteristics, tobacco use, and other potential confounders. Results: Compared to the "vapor" condition, "chemicals" and "aerosol" conditions were associated with increased odds of perceiving secondhand exposure to e-cigarettes to be harmful/very harmful (AOR = 2.0, p < 0.01). Greater perceived harm of secondhand e-cigarette exposure was associated with increased odds of supporting a tobacco-free campus policy (AOR = 2.22, p < 0.001). Conclusions: Health campaigns should use accurate terminology to describe e-cigarette emissions, rather than jargon that conveys lower risk.

Objective: To examine the association between fraternity/sorority membership and athlete status with tobacco use by tobacco product type. Participants: Undergraduate college students who participated in the Spring 2017 National College Health Assessment-II Survey (n = 47,821). Methods: Prevalence of current (past-30 day) cigarette smoking, waterpipe tobacco smoking (WTS), and e-cigarette (ECIG) use was examined. Logistic regressions examined associations between fraternity/sorority membership and participation in collegiate athletics with tobacco use. Results: Fraternity/sorority members had the highest current use rates for cigarettes, waterpipe tobacco, and ECIGs and were nearly twice as likely to report cigarette smoking, WTS, and ECIG use relative to non-fraternity/sorority members. Relative to non-varsity athletes, varsity athletes were less likely to report cigarette smoking and WTS, but not ECIG use. Conclusions: Fraternity/sorority members appear to be at risk for use of multiple tobacco products. Varsity athlete status may be protective for some tobacco products, but does not appear no for ECIG use. ECIGs may appeal to groups typically at low risk for other tobacco products.

Flavor additives are commonly used in combustible tobacco products to mask harshness and increase appeal. However, research on the availability of flavored waterpipe tobacco (WT) is lacking, yet is important to support implementation of policies. We completed a comprehensive online search in 2020 to identify WT brands and flavors sold online in the USA. We conducted a descriptive content analysis categorizing flavors as explicit (i.e., clear taste/flavor) or concept (i.e., no clear taste/flavor); and coded for 23 flavor descriptors (e.g., fruit, mint/menthol, tobacco). Flavor names were double-coded and discrepancies were resolved by a third coder. We identified 66 WT brands with 118 product lines (i.e., sub-brands). We found 2953 flavors, including 1871 unique flavors. Brands averaged 45 flavors (range: 1–183). Almost three quarters (73.5%, n = 2171) used explicit flavor names and 26.5% (n = 782) used concept flavor names. Concept flavors varied widely, and included names such as 1001 Nights and California Dream. The most common flavor descriptors were fruit (54.1%) and mint/menthol (12.5%). Tobacco was rarely (0.2%) used as a flavor descriptor. Flavor descriptors also included location (10.7%), color (11.1%), candy (6.3%), cool/ice (5.3%), and alcohol (5.5%). WT is available in 1871 unique flavors, likely contributing to product appeal and use. Like other tobacco products, fruit and mint/menthol are common flavors. Given the significant health consequences associated with WT smoking and the role of flavors in product use, regulatory action specifically targeting WT flavors is urgently needed. [ABSTRACT FROM AUTHOR]

Introduction Electronic cigarettes (ECIGs) heat a nicotine-containing liquid to produce an inhalable aerosol. ECIG power (wattage) and liquid nicotine concentration are two factors that predict nicotine emission rate ("flux"). These factors can vary greatly across devices and users. Aims and Methods The purpose of this study was to examine ECIG device and liquid heterogeneity in "real world" settings and the association with predicted nicotine flux, nicotine yield, and total particulate matter (TPM) emissions. Past 30-day ECIG users (n = 84; mean age = 23.8 years [SD = 9.6]) reported device and liquid characteristics. Device power was measured via multimeter, device display screens, or obtained via labeling. Liquid nicotine concentration was obtained via labeling or through chemical analysis. Predicted nicotine flux, nicotine yield, and TPM associated with 10 4-second puffs were calculated for participants' primary devices. Results Participants' primary devices were box mods (42.9%), disposable vapes (20.2%), and pod mods (36.9%). Most participants (65.5%) reported not knowing their primary device wattage. Rebuildable/box mods had the greatest power range (11.1–120.0 W); pod mod power also varied considerably (4.1–21.7 W). Unlike device wattage, most participants (95.2%) reported knowing their liquid nicotine concentration, which ranged from 3.0 to 86.9 mg/ml (M = 36.0, SD = 29.3). Predicted nicotine flux varied greatly across products (range =12.0–160.1 μg/s, M = 85.6 μg/s, SD = 34.3). Box mods had the greatest variability in wattage and predicted nicotine flux, nicotine yield, and TPM yield. Conclusions ECIG device and liquid heterogeneity influence nicotine and other toxicant emissions. Better measurement of ECIG device and liquid characteristics is needed to understand nicotine and toxicant emissions and to inform regulatory policy. Implications ECIG device and liquid heterogeneity cause great variability in nicotine flux and toxicants emitted. These data demonstrate the need to examine device and liquid characteristics to develop empirically informed, health-promoting regulatory policies. Policies may include setting product standards such that ECIG products cannot (1) have nicotine fluxes much greater than that of a cigarette to decrease the risk of dependence, (2) have nicotine fluxes that are very low and thus would have minimal appeal to cigarette smokers and may serve as starter products for youth or nontobacco users, and (3) emit large amounts of particulate matter and other toxicants. [ABSTRACT FROM AUTHOR]

Objective: This study is the first to examine the influence of e-cigarette emission phrasing on perceived harm of secondhand exposure, and whether harm perception was associated with support for a tobacco-free campus policy. Participants: In the fall 2018 and spring 2019 semesters, 52 sections of a college English course (N = 791 students) were cluster randomized to one of three conditions ("vapor," "aerosol," or "chemicals") assessing harm of secondhand exposure to e-cigarette emissions. Methods: Regression models adjusted for demographic characteristics, tobacco use, and other potential confounders. Results: Compared to the "vapor" condition, "chemicals" and "aerosol" conditions were associated with increased odds of perceiving secondhand exposure to e-cigarettes to be harmful/very harmful (AOR = 2.0, p < 0.01). Greater perceived harm of secondhand e-cigarette exposure was associated with increased odds of supporting a tobacco-free campus policy (AOR = 2.22, p < 0.001). Conclusions: Health campaigns should use accurate terminology to describe e-cigarette emissions, rather than jargon that conveys lower risk. [ABSTRACT FROM AUTHOR]