Use Of E-liquids Research Articles

The e-liquid flavoring cinnamaldehyde induces cellular stress responses in human proximal tubule (HK-2) kidney cells

Flavored e-liquid use has become popular among e-cigarette users recently, but the effects of such products outside the lung are not well characterized. In this work, acute exposure to the popular flavoring cinnamaldehyde (CIN) was performed on human proximal tubule (HK-2) kidney cells. Cells were exposed to 0–100 µM CIN for 24–48 h and cellular stress responses were assessed. Mitochondrial viability via MTT assay was significantly decreased at 20 µM for 24 and 48 h exposure. Seahorse XFp analysis showed significantly decreased mitochondrial energy output at 20 µM by 24 h exposure, in addition to significantly reduced ATP Synthase expression. Seahorse analysis also revealed significantly decreased glycolytic function at 20 µM by 24 h exposure, suggesting inability of glycolytic processes to compensate for reduced mitochondrial energy output. Cleaved caspase-3 expression, a mediator of apoptosis, was significantly increased at the 24 h mark. C/EBP homologous protein (CHOP) expression, a mediator of ER-induced apoptosis, was induced by 48 h and subsequently lost at the highest concentration of 100 µM. This decrease was accompanied by a simultaneous decrease in its downstream target cleaved caspase-3 at the 48 h mark. The autophagy marker microtubule-associated protein 1 A/1B light chain 3 (LC3B-I and LC3B-II) expression was significantly increased at 100 µM by 24 h. Autophagy-related 7 (ATG7) protein and mitophagy-related proteins PTEN-induced putative kinase 1 (PINK1) and PARKIN expression were significantly reduced at 24 and 48 h exposure. These results indicate acute exposure to CIN in the kidney HK-2 model induces mitochondrial dysfunction and cellular stress responses.

Menthol versus tobacco e-liquid flavor: Impact on acute subjective effects, puff patterns, and intentions for use among Black and White menthol smokers

BackgroundThe proposed FDA product standard to prohibit menthol as a characterizing flavor in combustible cigarettes has the potential to significantly reduce tobacco-related health disparities. Whether a menthol e-liquid product standard would improve or hinder public health is unknown. No known research has directly examined the impact of menthol vs. tobacco flavored e-liquid use on acute e-cigarette use patterns, subjective experience, behavioral intentions, and craving and withdrawal among menthol cigarette smokers. MethodsBlack (n = 47) and White (n = 4) nicotine-deprived menthol smokers with limited e-cigarette experience completed two counterbalanced in-laboratory 30-minute ad libitum vaping sessions with menthol and tobacco nicotine salt-based e-liquid in a randomized crossover pilot trial design. Questionnaires assessed reductions in craving and withdrawal and post-session subjective experience and behavioral intentions. Puff topography was measured continuously throughout each vaping session. ResultsMeasures of puff topography did not differ significantly by e-liquid flavor (all p > .40). Similarly, menthol and tobacco flavored e-cigarettes were both rated positively in terms of subjective effects and behavioral intentions (all p > .10) and about 40 % of participants reported a preference for the tobacco-flavored e-liquid. Finally, participants showed comparable reductions in craving (p = .210) and withdrawal (p = .671) from pre- and post-session regardless of e-liquid flavor. ConclusionsAmong menthol smokers in a lab-based setting, findings suggest that menthol vs tobacco e-liquid flavor has little impact on acute changes in puff patterns, subjective experience, behavioral intentions, or craving and withdrawal.

Vaping-Related Adverse Events and Perceived Health Improvements: A Cross-Sectional Survey among Daily E-Cigarette Users.

Web-based samples of e-cigarette users commonly report significant vaping-related health improvements (HIs) and mild adverse events (AEs). This cross-sectional study with in-person interviewing data collection examined self-reported AEs and perceived HIs among Hungarian adult current daily exclusive e-cigarette (n = 65) and dual users (n = 127), and former daily e-cigarette users (n = 91) in 2018. Logistic regression was used to evaluate associations between reporting any AEs/HIs, vaping status, and covariates. More former users (52.7%) reported AEs than current users (39.6%; p = 0.038). Exclusive and dual daily users reported similar rates of AEs (44.6% and 37.0%, respectively; p = 0.308). More current users (46.9%) experienced HIs than former users (35.2%; p = 0.064). Exclusive daily users were more likely to report HIs than dual users (63.1% versus 38.6%; p = 0.001). Former user status and smoking cessation/reduction reasons increased the odds of reporting AEs, whereas nicotine-containing e-liquid use and older age decreased the odds of reporting AEs. Exclusive vaper status, using advanced generation devices, and smoking cessation/reduction reasons increased the odds of experiencing HIs. This study, which used a traditional data collection methodology, found a higher rate of AEs and a lower rate of HIs compared to web-based surveys. Our results highlight that experiencing AEs and HIs is affected by users’ characteristics, in addition to the device and e-liquid type.

Involuntary 5F-ADB-related intoxication following e-cigarette use

The detection of synthetic cannabinoid (SC) intoxication cases is challenging, even more when the involved SC identification is requested in a forensic context. This situation can be complicated by new modes of SC consumption, non-specific symptomatology, and analytical pitfalls. To illustrate these issues, we report the case of a 16-year-old man who presented symptoms evocating of a seizure disorder in the minutes following the use of a friend's e-cigarette. At admission in the emergency department, his electroencephalogram was interpreted as coherent with a recent seizure episode. 5F-ADB, a third generation SC, was detected in the e-liquid and in an early collected (H2 after the e-cigarette use) serum sample (0.50µg/L), but not in urine samples (H18 and H38). One 5F-ADB metabolite, O-desmethyl-5F-ADB (M5), was detectable in urine up to at least 38h after intoxication. Neither 5F-ADB nor its metabolites could be detected in victim's hair sampled 3months after the intoxication. Although leading to a non-specific symptomatology, acute SC intoxication should be considered when the case history is related to e-cigarette or e-liquid use. Early biological samples are recommended, even if analytical screening can be positive for SC metabolites in urine sampled until 2days after exposure. Accordingly, data from the literature and the present case underscore the relevance of adding both main 5F-ADB metabolites (M5 and 5-OH-pentyl-ADB) to mass spectrum databases used for toxicological screening in order to reduce the risk of false-negative results in intoxication cases involving 5F-ADB.

Choice and Variety-Seeking of E-liquids and Flavor Categories by New Zealand Smokers Using an Electronic Cigarette: A Longitudinal Study.

BackgroundLittle is currently known about how e-liquid flavor use evolves among electronic cigarette users. We describe patterns of e-liquid and flavor category use, and variety-seeking, among New Zealand adult smokers attempting to transition from smoking to e-cigarettes.MethodsData were collected in 2018–19, using a longitudinal design comprising up to five in-depth interviews over a 12–20 week period. Participants (n = 32) were current smokers aged ≥18 years, who were not currently using an e-cigarette once a week or more often, and were willing to use an e-cigarette in an attempt to stop smoking. We purchased participants a starter e-cigarette of their choice; they supplied their own e-liquids throughout the study. We extracted e-liquid use data from the verbatim interview transcripts, categorized these into flavor categories, and then explored these data for the whole sample, and by flavor category purchased at intake.ResultsMost participants (n = 12) selected a tobacco flavored e-liquid at intake; fruit (n = 7), mint/menthol (n = 6), and dessert/sweets and non-alcoholic beverage (both n = 5) were also popular. Most participants were still using their initially chosen flavor category at study exit, however, many described variety-seeking behaviors, which typically occurred during the first 12 weeks of enrolment.ConclusionMost participants did not follow a straightforward e-liquid or flavor category pathway. Evidence of a variety-seeking continuum, typically occurring within the first 12 weeks, suggests possible opportunities at specialist e-cigarette stores to couple e-liquid purchasing occasions with cessation advice.ImplicationsVariety-seeking behavior was common and typically reported within the first 12 weeks of participants' e-cigarette-assisted attempt to transition away from smoking. Policies allowing diverse e-liquid flavors at specialist stores only could support users' variety-seeking and potentially create opportunities to couple e-liquid purchasing occasions with cessation advice during the first months of a transition attempt.

Electronic cigarette use among 14- to 17-year-olds in Europe.

BackgroundStudies comparing adolescent e-cigarette use in different countries are scarce. We study students’ e-cigarette and conventional cigarette ever-use, their social correlates and e-liquid use in seven EU countries.MethodsSILNE-R data (N=12 167, response rate 79.4%) of 14–17-year-olds from Amersfoort (NL), Coimbra (PT), Dublin (IR), Hanover (GE), Latina (IT), Namur (BE) and Tampere (FI) were used. E-cigarette and conventional cigarette ever-use, dual-use, type of e-liquid and social correlates were measured with a school survey and analyzed with cross-tabulations and multinomial logistic regression.ResultsAbout 34% had tried e-cigarettes, but the variation was large between the cities (Latina 50%; Hanover 23%). Of e-cigarette ever-users, 37% had used nicotine e-liquid, 43% exclusively non-nicotine liquid and 20% did not know the content. Nicotine e-liquid was more prevalent among monthly e-cigarette users and weekly smoking e-cigarette users. The social correlates were mainly the same for exclusive e-cigarette ever-use, exclusive conventional cigarette ever-use and dual-use. Boys had greater odds for exclusive e-cigarette and dual-use compared to girls. Of social correlates, low academic achievement and parental smoking were positively associated with all categories of use, but parental education and immigrant background were not. The strongest association was found between peer smoking (most/all best friends smoke) and dual-use (OR 34.29).ConclusionsStudents’ e-cigarette ever-use varies greatly between EU countries. E-cigarettes seem not to be a substitute for conventional cigarettes but more a complementary product. Tobacco control policies might also prevent e-cigarette use but specific regulations on e-cigarettes are needed to prevent nicotine addiction originating from them.

Flavor-specific enhancement of electronic cigarette liquid consumption and preference in mice

BackgroundThe use of electronic cigarettes has increased over the past decade. To determine how the abuse liability of electronic cigarette liquids (e-liquids) differs from nicotine alone, and to determine the impact of flavor, we compared nicotine-containing fruit- and tobacco-flavored e-liquids, and their nicotine-free versions, to nicotine alone in mouse models of oral consumption, reward and aversion. MethodsAdult male C57BL/6 J mice voluntarily consumed oral nicotine, equivalent nicotine concentrations of fruit- and tobacco-flavored e-liquid, and equivalent dilutions of the nicotine-free versions in 2-bottle choice tests. Conditioned place preference and place aversion were assessed with peripherally administered e-liquids or nicotine. Serum nicotine and cotinine levels were measured after subcutaneous injections of e-liquid or nicotine. ResultsMice showed higher consumption and preference for the fruit-flavored e-liquid compared with nicotine alone. This increase was not due to the flavor itself as consumption of the nicotine-free fruit-flavored e-liquid was not elevated until the highest concentration tested. The increased consumption and preference were not observed with the tobacco-flavored e-liquid. The conditioned place preference, place aversion and nicotine pharmacokinetics of the fruit-flavored e-liquid were not significantly different from nicotine alone. ConclusionsOur data suggest that fruit, but not tobacco flavor, increased the oral consumption of e-liquid compared with nicotine alone. Moreover, this enhancement was not due to increased consumption of the flavor itself, altered rewarding or aversive properties after peripheral administration, or altered pharmacokinetics. This flavor-specific enhancement suggests that some flavors may lead to higher nicotine intake and increased use of e-liquids compared with nicotine alone.

Association between preference for using alcohol beverage-named e-liquids and alcohol use among high school youth

BackgroundThere are thousands of e-liquid flavors available, and some are named after alcohol beverages (e.g., “pina colada”). It is unclear whether use of e-liquids with alcohol beverage names is associated with adolescent alcohol use. E-cigarettes and alcohol are co-used in adolescents; therefore, it is important to investigate these associations. MethodsEight Southeastern Connecticut high schools were surveyed in Spring 2015 (N = 7045). We examined the association between preference for using e-liquid flavors and alcohol drinking status (i.e., no past month alcohol use, past month alcohol use but no binge drinking, and past month binge drinking) in ever e-cigarette users (N = 1311). ResultsAmong ever e-cigarette users who preferred using e-liquids with alcohol beverage names (N = 111), 30.6 % had no past month alcohol use, 19.8 % had past month alcohol use but did not binge drink in the past month, and 49.5 % binge drank in the past month. Multinomial logistic regression (controlling for demographics and including other e-cigarette flavors that were highly endorsed, i.e., fruit and candy) revealed that the preferences of alcohol beverage-named-e-liquid (OR: 2.84, CI: 1.70–4.75) and fruit flavored e-liquids (OR: 1.55, CI: 1.14–2.11), but not candy flavored e-liquids was associated with past-month binge drinking compared to no past-month alcohol use. ConclusionThis evidence suggests that the preference for using alcohol beverage- and fruit-named e-liquid flavors is associated with past-month binge drinking among adolescents. Understanding the associations between alcohol beverage-named e-liquids and alcohol use in adolescents may help inform tobacco regulatory strategies that aim to decrease the use/appeal of e-cigarettes.

High school students’ use of flavored e-cigarette e-liquids for appetite control and weight loss

BackgroundAlthough weight-related reasons for smoking and vaping have been examined in adults, research in adolescents is lacking. Thus, we examined the prevalence and correlates of using flavored e-liquids for appetite control or weight loss in high school adolescents. MethodsThe analytic sample included 529 students who completed a school-based survey in Connecticut in Spring 2017 (50.6% female, 79.5% White, mean age 16.27 [SD = 1.18], range 13–19 years). Inclusion criteria were past-30-day vaping, using ≥ 1 flavored e-liquid (past month), and having non-missing data on flavored e-liquid use for appetite control and weight loss. Participants reported on sex, age, race, past-30-day vaping and smoking frequency, nicotine e-liquid use, flavored e-liquid use (e.g., tobacco, mint, fruit, candy), and flavored e-liquid use for appetite control and/or weight loss. ResultsAdolescent e-cigarette users (past 30-days) reported vaping flavored e-liquids for appetite control (13.8%) and weight loss (9.3%). Using flavored e-liquids for appetite control or weight loss, respectively, was associated with more frequent vaping (OR = 1.21; 1.21) and using more flavored e-liquids (OR = 1.33; 1.28, p-values < 0.01). Vaping candy-flavored e-liquids (OR = 1.16, p = 0.02) uniquely was associated with vaping for appetite control. ConclusionsA subset of adolescents reported using flavored e-liquids for weight-related reasons. These adolescents reported vaping more frequently than their counterparts, raising concerns about increased nicotine exposure. Research is needed to understand where adolescents learn about weight-motivated vaping (e.g., friends, social media) and whether weight-related motives promote e-cigarette initiation among e-cigarette naïve individuals or continued/escalating use among current users.

E-liquid-related posts to Twitter in 2018: Thematic analysis

IntroductionE-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts. MethodsTwitter posts containing e-liquid-related terms (“e-liquid(s),” “e-juice(s)”) were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n = 15,927). ResultsThe most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%. ConclusionThese results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk.

Limited utility of detailed e-cigarette use measures: An analysis of NESARC-III

IntroductionThe heterogeneity of e-cigarette products and e-liquids pose challenges to surveillance of e-cigarette exposure. The goal of this study was to evaluate the internal consistency of e-cigarette use frequency, quantity, and duration measures in a national population-based survey. MethodsData were drawn from the 2012–2013 for the National Epidemiologic Survey on Alcohol and Related Conditions-III (n = 36,309; NESARC-III). Adults who used e-cigarettes/e-liquid during the past year (≤18 years old; n = 1,229) were asked about their age of first use, recency of use, quantity (i.e., cartridges, drops), nicotine concentration, and duration (hours). Several internal consistency parameters were compared for e-cigarette measures in past-year (n = 750) and past 30-day e-cigarette users (n = 472) overall, and by frequency of use (i.e., infrequent [≤3 days/month], non-daily [1–6 days/week], daily). ResultsThere were no significant differences in quantity, nicotine concentration, or duration by frequency of use in past 30-day e-cigarette users. One-third of past 30-day and almost half of past-year users did not know the nicotine concentration of their cartridge or e-liquid. Correlations between all e-cigarette use measures were low, with the highest correlations seen between e-liquid quantity and cartridge quantity in all past 30-day users (r = 0.28) and those reporting any e-liquid use (r = 0.40). Cronbach's alpha and mean interitem correlations were low across all user groups. ConclusionsLow to moderate correlation across e-cigarette measures in e-cigarette users implies low internal consistency of these measures in a population survey. Findings suggest measures such as quantity and nicotine concentration might more appropriate in samples of recent experienced e-cigarette users than in general population samples.

5F-Cumyl-PINACA in \u2018e-liquids\u2019 for electronic cigarettes: comprehensive characterization of a new type of synthetic cannabinoid in a trendy product including investigations on the in vitro and in vivo phase I metabolism of 5F-Cumyl-PINACA and its non-fluorinated analog Cumyl-PINACA

PurposeIn recent years e-liquids used in electronic cigarettes have become an attractive alternative to smoking tobacco. A new trend is the use of e-liquids containing synthetic cannabinoids (SCs) instead of smoking cannabis or herbal mixtures laced with SCs. In the frame of a systematic monitoring of the online market of ‘legal high’ products, e-liquids from online retailers who also sell herbal blends were bought.MethodsThe products were analyzed by gas chromatography-mass spectrometry. In some of the e-liquids an unknown compound was detected which was identified as the SC 5F-Cumyl-PINACA (1-(5-fluoropentyl)-N-(2-phenylpropan-2-yl)-1H-indazole-3-carboxamide) by nuclear magnetic resonance analysis. To investigate the phase I metabolism of this new class of compounds, 5F-Cumyl-PINACA and its non-fluorinated analog Cumyl-PINACA were incubated with pooled human liver microsomes (pHLM). Cumyl-PINACA was additionally ingested orally (0.6 mg) by a volunteer in a controlled self-experiment. To assess the relative potency of Cumyl-PINACA a set of SCs were characterized using a cAMP assay.ResultsMetabolism of 5F-Cumyl-PINACA and Cumyl-PINACA showed similarities with AM-2201 and JWH-018. The main metabolites were formed by hydroxylation at the N-pentyl side chain. The main metabolites detected in the volunteer’s urine sample were the same as in the pHLM assay. All SCs tested with the cAMP assay were full agonists at the CB1 receptor. Cumyl-PINACA was the most potent SC among the tested compounds and showed an EC50 value of 0.06 nM.ConclusionsThe increasing popularity of e-liquids particularly among young people, and the extreme potency of the added SCs, pose a serious threat to public health. To our knowledge, this is the first report describing the tentative identification of human in vivo metabolites of Cumyl-PINACA and 5F-Cumyl-PINACA.

Understanding Users' Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques.

BackgroundE-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications.ObjectiveThis study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production).MethodsWe collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids.ResultsWe found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy.ConclusionsThis study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.

Characterization of puff topography of a prototype electronic cigarette in adult exclusive cigarette smokers and adult exclusive electronic cigarette users

Puff topography is an important measure of how consumers use e-vapor products. The purpose of this study was to evaluate the feasibility of using SODIM Smoking Puff Analyzer Mobile Device (SPA/M) to measure puff topography during use of a prototype e-cigarette (e-cig) in exclusive cigarette smokers (CS) and e-cig users (EC) under ad lib conditions in a clinic. Adult CS (n = 13) and EC (EC; n = 10) completed a 7-hr use session with the e-cig (2% tobacco-derived nicotine by weight, cartridge based system approximately the size of a king size cigarette). E-liquid usage was determined from cartridge weight. CS also smoked a single cigarette with the SPA/M. The SPA/M reliably recorded puff parameters throughout the study period, with CS puffs averaging 47.9 ± 18.2 ml volume, 2.3 ± 0.8 s duration, and 21.5 ± 4.6 ml/s flow rate. EC puffs averaged 53.4 ± 19.2 ml volume, 3.0 ± 1.3 s duration, and 19.6 ± 5.0 flow rate. CS average e-liquid use was 292 ± 214 mg and EC averaged 415 ± 305 mg over 7 h. When compared to a single use of their own brand cigarettes, CS took longer (2.3 ± 0.8 vs.1.7 ± 0.4 s) puffs with similar puff volume (47.9 ± 18.2 vs. 44.1 ± 10.5 ml) from the e-cig prototype. The puff duration, flow rate and peak flow were significantly lower (p < 0.05) with the e-cigs compared to cigarettes. Experienced EC and CS appeared to use the e-cig prototype differently, which is consistent with the literature. The SPA/M could be a useful tool in assessing e-cig use behavior for regulatory purposes.

Assessing nicotine dependence in adolescent E-cigarette users: The 4-item Patient-Reported Outcomes Measurement Information System (PROMIS) Nicotine Dependence Item Bank for electronic cigarettes

BackgroundAdolescent e-cigarette use (i.e., “vaping”) likely confers risk for developing nicotine dependence. However, there have been no studies assessing e-cigarette nicotine dependence in youth. We evaluated the psychometric properties of the 4-item Patient-Reported Outcomes Measurement Information System Nicotine Dependence Item Bank for E-cigarettes (PROMIS-E) for assessing youth e-cigarette nicotine dependence and examined risk factors for experiencing stronger dependence symptoms. MethodsIn 2017, 520 adolescent past-month e-cigarette users completed the PROMIS-E during a school-based survey (50.5% female, 84.8% White, 16.22[1.19] years old). Adolescents also reported on sex, grade, race, age at e-cigarette use onset, vaping frequency, nicotine e-liquid use, and past-month cigarette smoking. Analyses included conducting confirmatory factor analysis and examining the internal consistency of the PROMIS-E. Bivariate correlations and independent-samples t-tests were used to examine unadjusted relationships between e-cigarette nicotine dependence and the proposed risk factors. Regression models were run in which all potential risk factors were entered as simultaneous predictors of PROMIS-E scores. ResultsThe single-factor structure of the PROMIS-E was confirmed and evidenced good internal consistency. Across models, larger PROMIS-E scores were associated with being in a higher grade, initiating e-cigarette use at an earlier age, vaping more frequently, using nicotine e-liquid (and higher nicotine concentrations), and smoking cigarettes. ConclusionAdolescent e-cigarette users reported experiencing nicotine dependence, which was assessed using the psychometrically sound PROMIS-E. Experiencing stronger nicotine dependence symptoms was associated with characteristics that previously have been shown to confer risk for frequent vaping and tobacco cigarette dependence.

Death from Ingestion of E-Liquid

BackgroundThe use of e-liquids is becoming more prevalent. There is a risk that such liquids may be ingested by mouth rather than being vaped/ inhaled. Due to the high concentration of drugs such as nicotine in these liquids, there may be toxic, and possibly fatal consequences. Case ReportWe report the death of a 32-year-old male who ingested nicotine-containing e-liquid while under the influence of alcohol. A serum sample taken 24 h after collapse contained nicotine at a concentration of 1600 ng/mL of nicotine. Why Should an Emergency Physician Be Aware of This?Death secondary to e-liquid ingestion is still very rare, but has the potential for causing deaths due to the easy access of such liquids to the general public. Such toxicity should be considered in individuals who present in the early phases with symptoms of stimulant toxicity, but also in the latter phase where there may be autonomic depressive effects.

Changes in Electronic Cigarette Use from 2013 to 2015 and Reasons for Use among Finnish Adolescents.

Electronic cigarettes are quite a new potential source of nicotine addiction among youth. More research is needed, particularly on e-liquid use and socioeconomic factors as potential determinants. We studied changes from 2013 to 2015 in adolescent e-cigarette awareness and ever-use, types of e-liquids, and determinants in Finland. In 2015, we studied weekly use and reasons for ever-use. Data were from two national surveys of 12–18-year-old Finns (2013, n = 3535, response rate 38%; 2015, n = 6698, 41%). Descriptive statistics and logistic regression analysis were used. Awareness and ever-use of e-cigarettes increased significantly from 2013 to 2015 in all age and gender groups. Ever-use increased from 17.4% to 25%, with half having tried nicotine e-liquids. In 2015, weekly use was rare (1.5%). Daily cigarette smoking was the strongest determinant (OR 51.75; 95% CI 38.18–70.14) for e-cigarette ever-use, as for e-cigarette weekly use, but smoking experimentation and ever-use of snus (Swedish type moist snuff) and waterpipes alongside parental smoking and poor academic achievement also increased the odds for ever-use. The most common reason behind e-cigarette ever-use was the desire to try something new. To conclude, adolescent e-cigarette ever-use is increasing, and also among never-smokers. Tobacco-related factors are stronger determinants for e-cigarette use than socioeconomic factors.

P.6.f.003 Management of smoking reduction and cessation in inpatients with schizophrenia: impact of electronic cigarettes

Puff topography is an important measure of how consumers use e-vapor products. The purpose of this study was to evaluate the feasibility of using SODIM Smoking Puff Analyzer Mobile Device (SPA/M) to measure puff topography during use of a prototype e-cigarette (e-cig) in exclusive cigarette smokers (CS) and e-cig users (EC) under ad lib conditions in a clinic. Adult CS (n = 13) and EC (EC; n = 10) completed a 7-hr use session with the e-cig (2% tobacco-derived nicotine by weight, cartridge based system approximately the size of a king size cigarette). E-liquid usage was determined from cartridge weight. CS also smoked a single cigarette with the SPA/M. The SPA/M reliably recorded puff parameters throughout the study period, with CS puffs averaging 47.9 ± 18.2 ml volume, 2.3 ± 0.8 s duration, and 21.5 ± 4.6 ml/s flow rate. EC puffs averaged 53.4 ± 19.2 ml volume, 3.0 ± 1.3 s duration, and 19.6 ± 5.0 flow rate. CS average e-liquid use was 292 ± 214 mg and EC averaged 415 ± 305 mg over 7 h. When compared to a single use of their own brand cigarettes, CS took longer (2.3 ± 0.8 vs.1.7 ± 0.4 s) puffs with similar puff volume (47.9 ± 18.2 vs. 44.1 ± 10.5 ml) from the e-cig prototype. The puff duration, flow rate and peak flow were significantly lower (p < 0.05) with the e-cigs compared to cigarettes. Experienced EC and CS appeared to use the e-cig prototype differently, which is consistent with the literature. The SPA/M could be a useful tool in assessing e-cig use behavior for regulatory purposes.