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Understanding why young people try and stop electronic cigarette (e-cigarette) use is critical to inform e-cigarette regulatory efforts. We conducted 18 focus groups (N = 127) in 1 middle school (MS), 2 high schools (HSs), and 2 colleges in Connecticut to assess themes related to e-cigarette experimentation and discontinuation. We then conducted surveys to evaluate these identified themes in 2 MSs, 4 HSs, and 1 college (N = 1,175) to explore whether reasons for e-cigarette experimentation and/or discontinuation differed by school level or cigarette smoking status. From the focus groups, we identified experimentation themes (i.e., curiosity, flavors, family/peer influence, easy access, and perceptions of e-cigarettes as \"cool\" and as a healthier/better alternative to cigarettes) and discontinuation themes (i.e., health concerns, loss of interest, high cost, bad taste, and view of e-cigarettes as less satisfying than cigarettes). The survey data showed that the top reasons for experimentation were curiosity (54.4%), appealing flavors (43.8%), and peer influences (31.6%), and the top reasons for discontinuation were responses related to losing interest (23.6%), perceiving e-cigarettes as \"uncool\" (16.3%), and health concerns (12.1%). Cigarette smokers tried e-cigarettes because of the perceptions that they can be used anywhere and to quit smoking and discontinued because they were not as satisfying as cigarettes. School level differences were detected. E-cigarette prevention efforts toward youth should include limiting e-cigarette flavors, communicating messages emphasizing the health risks of use, and changing social norms surrounding the use of e-cigarettes. The results should be interpreted in light of the limitations of this study.

Glycerin (VG) and propylene glycol (PG) are the most common nicotine solvents used in e-cigarettes (ECs). It has been shown that at high temperatures both VG and PG undergo decomposition to low molecular carbonyl compounds, including the carcinogens formaldehyde and acetaldehyde. The aim of this study was to evaluate how various product characteristics, including nicotine solvent and battery output voltage, affect the levels of carbonyls in EC vapor. Twelve carbonyl compounds were measured in vapors from 10 commercially available nicotine solutions and from 3 control solutions composed of pure glycerin, pure propylene glycol, or a mixture of both solvents (50:50). EC battery output voltage was gradually modified from 3.2 to 4.8V. Carbonyl compounds were determined using the HPLC/DAD method. Formaldehyde and acetaldehyde were found in 8 of 13 samples. The amounts of formaldehyde and acetaldehyde in vapors from lower voltage EC were on average 13- and 807-fold lower than in tobacco smoke, respectively. The highest levels of carbonyls were observed in vapors generated from PG-based solutions. Increasing voltage from 3.2 to 4.8V resulted in a 4 to more than 200 times increase in formaldehyde, acetaldehyde, and acetone levels. The levels of formaldehyde in vapors from high-voltage device were in the range of levels reported in tobacco smoke. Vapors from EC contain toxic and carcinogenic carbonyl compounds. Both solvent and battery output voltage significantly affect levels of carbonyl compounds in EC vapors. High-voltage EC may expose users to high levels of carbonyl compounds.

The purpose of this study was to evaluate sweet-flavored electronic cigarette (EC) liquids for the presence of diacetyl (DA) and acetyl propionyl (AP), which are chemicals approved for food use but are associated with respiratory disease when inhaled. In total, 159 samples were purchased from 36 manufacturers and retailers in 7 countries. Additionally, 3 liquids were prepared by dissolving a concentrated flavor sample of known DA and AP levels at 5%, 10%, and 20% concentration in a mixture of propylene glycol and glycerol. Aerosol produced by an EC was analyzed to determine the concentration of DA and AP. DA and AP were found in 74.2% of the samples, with more samples containing DA. Similar concentrations were found in liquid and aerosol for both chemicals. The median daily exposure levels were 56 μg/day (IQR: 26-278 μg/day) for DA and 91 μg/day (IQR: 20-432 μg/day) for AP. They were slightly lower than the strict NIOSH-defined safety limits for occupational exposure and 100 and 10 times lower compared with smoking respectively; however, 47.3% of DA and 41.5% of AP-containing samples exposed consumers to levels higher than the safety limits. DA and AP were found in a large proportion of sweet-flavored EC liquids, with many of them exposing users to higher than safety levels. Their presence in EC liquids represents an avoidable risk. Proper measures should be taken by EC liquid manufacturers and flavoring suppliers to eliminate these hazards from the products without necessarily limiting the availability of sweet flavors.

Smartphone technology is ideally suited to provide tailored smoking cessation support, yet it is unclear to what extent currently existing smartphone \"apps\" use tailoring, and if tailoring is related to app popularity and user-rated quality. We conducted a content analysis of Android smoking cessation apps (n = 225), downloaded between October 1, 2013 to May 31, 2014. We recorded app popularity (>10,000 downloads) and user-rated quality (number of stars) from Google Play, and coded the existence of tailoring features in the apps within the context of using the 5As (\"ask,\" \"advise,\" \"assess,\" \"assist,\" and \"arrange follow-up\"), as recommended by national clinical practice guidelines. Apps largely provided simplistic tools (eg, calculators, trackers), and used tailoring sparingly: on average, apps addressed 2.1 ± 0.9 of the 5As and used tailoring for 0.7 ± 0.9 of the 5As. Tailoring was positively related to app popularity and user-rated quality: apps that used two-way interactions (odds ratio [OR] = 5.56 [2.45-12.62]), proactive alerts (OR = 3.80 [1.54-9.38]), responsiveness to quit status (OR = 5.28 [2.18-12.79]), addressed more of the 5As (OR = 1.53 [1.10-2.14]), used tailoring for more As (OR = 1.67 [1.21-2.30]), and/or used more ways of tailoring 5As content (OR = 1.35 [1.13-1.62]) were more likely to be frequently downloaded. Higher star ratings were associated with a higher number of 5As addressed (b = 0.16 [0.03-0.30]), a higher number of 5As with any level of tailoring (b = 0.14 [0.01-0.27]), and a higher number of ways of tailoring 5As content (b = 0.08 [0.002-0.15]). Publically available smartphone smoking cessation apps are not particularly \"smart\": they commonly fall short of providing tailored feedback, despite users' preference for these features.

Electronic cigarettes (e-cigarettes) are purported to deliver nicotine aerosol without any toxic combustion products present in tobacco smoke. In this longitudinal within-subjects observational study, we evaluated the effects of e-cigarettes on nicotine delivery and exposure to selected carcinogens and toxicants. We measured seven nicotine metabolites and 17 tobacco smoke exposure biomarkers in the urine samples of 20 smokers collected before and after switching to pen-style M201 e-cigarettes for 2 weeks. Biomarkers were metabolites of 13 major carcinogens and toxicants in cigarette smoke: one tobacco-specific nitrosamine (NNK), eight volatile organic compounds (1,3-butadiene, crotonaldehyde, acrolein, benzene, acrylamide, acrylonitrile, ethylene oxide, and propylene oxide), and four polycyclic aromatic hydrocarbons (naphthalene, fluorene, phenanthrene, and pyrene). Changes in urine biomarkers concentration were tested using repeated measures analysis of variance. In total, 45% of participants reported complete abstinence from cigarette smoking at 2 weeks, while 55% reported continued smoking. Levels of total nicotine and some polycyclic aromatic hydrocarbon metabolites did not change after switching from tobacco to e-cigarettes. All other biomarkers significantly decreased after 1 week of using e-cigarettes (p < .05). After 1 week, the greatest percentage reductions in biomarkers levels were observed for metabolites of 1,3-butadiene, benzene, and acrylonitrile. Total NNAL, a metabolite of NNK, declined by 57% and 64% after 1 and 2 weeks, respectively, while 3-hydroxyfluorene levels declined by 46% at week 1, and 34% at week 2. After switching from tobacco to e-cigarettes, nicotine exposure remains unchanged, while exposure to selected carcinogens and toxicants is substantially reduced. To our knowledge, this is the first study that demonstrates that substituting tobacco cigarettes with an e-cigarette may reduce user exposure to numerous toxicants and carcinogens otherwise present in tobacco cigarettes. Data on reduced exposure to harmful constituents that are present in tobacco cigarettes and e-cigarettes can aid in evaluating e-cigarettes as a potential harm reduction device.

Electronic cigarette (e-cigarette) use is increasing worldwide and is highest among both daily and nondaily smokers. E-cigarettes are perceived as a healthier alternative to combustible tobacco products, but their health risk factors have not yet been established, and one of them is lack of data on aerosol size generated by e-cigarettes. We applied a real-time, high-resolution aerosol differential mobility spectrometer to monitor the evolution of aerosol size and concentration during puff development. Particles generated by e-cigarettes were immediately delivered for analysis with minimal dilution and therefore with minimal sample distortion, which is critically important given the highly dynamic aerosol/vapor mixture inherent to e-cigarette emissions. E-cigarette aerosols normally exhibit a bimodal particle size distribution: nanoparticles (11-25nm count median diameter) and submicron particles (96-175nm count median diameter). Each mode has comparable number concentrations (10(7)-10(8) particles/cm(3)). \"Dry puff\" tests conducted with no e-cigarette liquid (e-liquid) present in the e-cigarette tank demonstrated that under these conditions only nanoparticles were generated. Analysis of the bulk aerosol collected on the filter showed that e-cigarette emissions contained a variety of metals. E-cigarette aerosol size distribution is different from that of combustible tobacco smoke. E-cigarettes generate high concentrations of nanoparticles and their chemical content requires further investigation. Despite the small mass of nanoparticles, their toxicological impact could be significant. Toxic chemicals that are attached to the small nanoparticles may have greater adverse health effects than when attached to larger submicron particles. The e-cigarette aerosol size distribution is different from that of combustible tobacco smoke and typically exhibits a bimodal behavior with comparable number concentrations of nanoparticles and submicron particles. While vaping the e-cigarette, along with submicron particles the user is also inhaling nano-aerosol that consists of nanoparticles with attached chemicals that has not been fully investigated. The presence of high concentrations of nanoparticles requires nanotoxicological consideration in order to assess the potential health impact of e-cigarettes. The toxicological impact of inhaled nanoparticles could be significant, though not necessarily similar to the biomarkers typical of combustible tobacco smoke.

Electronic cigarette (e-cigarette) marketing has increased considerably since the product entered the US market in 2007, thereby warranting additional surveillance to monitor recent trends in population-level awareness and utilization. We assessed the prevalence, characteristics, and trends in e-cigarette awareness and use among nationally representative samples of US adults during 2010-2013. Data came from the 2010-2013 HealthStyles survey, an annual consumer-based web survey of US adults aged ≥ 18 years. Sample sizes ranged from 2,505 (2010) to 4,170 (2012). Descriptive statistics were used to assess e-cigarette awareness, ever use, and current use (use within the past 30 days) overall and by sex, age, race/ethnicity, education, income, US region, and cigarette smoking status. Trends were assessed using logistic regression. During 2010-2013, increases (p < .05) were observed for e-cigarette awareness (40.9%-79.7%), ever use (3.3%-8.5%), and current use (1.0%-2.6%). Awareness increased among all socio demographic subpopulations during 2010-2013 (p < .05); an increase in ever use of e-cigarettes occurred among all sociodemographic groups except those aged 18-24 years, Hispanics, and those living in the Midwest (p < .05). During 2010-2013, ever use increased among current (9.8%-36.5%) and former (2.5%-9.6%) cigarette smokers (p < .05), but it remained unchanged among never smokers (1.3%-1.2%). Awareness and use of e-cigarettes increased considerably among US adults during 2010-2013. In 2013, more than one-third of current cigarette smokers reported having ever used e-cigarettes. Given the uncertain public health impact of e-cigarettes, continued surveillance of emerging use patterns is critical for public health planning.