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* https://www.cdc.gov/tobacco/basic_information/e-cigarettes/severe-lungdisease/health-departments/index.html#primary-case-def. * Patients who reported using THC-containing e-cigarette, or vaping, products on initial structured questionnaire or follow-up interview. † Patients who reported not using THC-containing e-cigarette, or vaping, products on initial structured questionnaire and follow-up interview. § Subgroup of patients who reported not using THC-containing products who also had no indication of use of any other THC-containing substance (e.g., reported not smoking combustible marijuana, had negative toxicology testing, if performed). ¶ P-values for comparisons, using Pearson's chi-squared test or Fisher's exact test (for cells with <5 observations). Statistical tests compared EVALI patients who reported THC-containing product use with EVALI patients who reported no THC-containing product use and with EVALI patients with no indication of any THC use. ** Data were not available for all variables for all patients. Differing denominators reflect missing data. † † Only patients who used nicotine-containing e-cigarette, or vaping, products and reported a frequency of use are included in the denominator. § § Six patients reported purchasing nicotine-containing e-cigarette, or vaping, products from more than one source: vape/tobacco shop and convenience store (three) and vape/tobacco shop and online (three).

Electronic cigarette (e-cigarette) conventions are trade shows held across the globe to promote e-cigarette products and provide a venue for users to socialize. E-cigarette users that attend these events likely represent the most intensive e-cigarette user group. No study has characterized addiction and behavior characteristics in this population. We surveyed 131 e-cigarette users attending a large Southeastern e-cigarette convention in Fall 2015. All questions from the Fagerstrom Test for Nicotine Dependence (FTND), select questions from the Penn State Electronic Cigarette Dependence Index, and novel user behavior questions were included. In total, 25 questions were included in the survey. FTND scores were calculated for each respondent who answered all six FTND questions (n = 117). Fisher's Exact Chi square test was used to assess the relationship between addiction and behavior characteristics and FTND scores. Most respondents were classified as moderately dependent (score 5-7, 45.3% of respondents). Length of use, waking at night to use an e-cigarette, strength of cravings, strength of urges over the past week, and frequency of visiting e-cigarette blogs were significantly associated with FTND scores. E-cigarettes users have average FTND scores higher than tobacco smokers. Scores were not significantly associated with prior tobacco cigarette use. Characteristics associated with tobacco smokers' nicotine addiction, such as waking at night to smoke and strength of cravings experienced, are relevant to e-cigarette users. E-cigarettes do not contain the magnitude of toxicants in tobacco cigarettes, but e-cigarettes may produce new chemical exposures evidenced by the adverse health effects reported by some respondents.

Background: Electronic cigarette (e-cigarette) conventions regularly bring together thousands of users around the world. In these environments, secondhand exposures to high concentrations of ecigarette emissions are prevalent. Some biomarkers for tobacco smoke exposure may be used to characterize secondhand e-cigarette exposures in such an environment. Methods: Participants who did not use any tobacco product attended four separate e-cigarette events for approximately six hours. Urine and saliva samples were collected from participants prior to the event, immediately after the event, 4-h after the event, and the next morning (first void). Urine samples from 34 participants were analyzed for cotinine, trans-3′-hydroxycotinine, S-(3-hydroxypropyl)-N-acetylcysteine (3-HPMA), S-carboxyethyl-N-acetylcysteine (CEMA), select tobacco-specific nitrosamines (TSNAs), and 8-isoprostane. Saliva samples were analyzed for cotinine and trans-3′-hydroxycotinine. Results: Data from 28 of 34 participants were used in the data analysis. Creatinine-adjusted urinary cotinine concentrations increased up to 13-fold and peaked 4-h after completed exposure (range of adjusted geometric means [AGMs] = 0.352-2.31 μg/g creatinine). Salivary cotinine concentrations were also the highest 4-h after completed exposure (range of AGMs = 0.0373-0.167 ng/mL). Salivary cotinine and creatinine-corrected concentrations of urinary cotinine, *

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