A comparison of the electrical characteristics, liquid composition, and toxicant emissions of JUUL USA and JUUL UK e-cigarettes

Does the time to nicotine dependence vary by internalizing symptoms for young people who use e-cigarettes? An analysis of the Population Assessment of Tobacco and Health (PATH) study, (Waves 1-5; 2013-2019)

OBJECTIVE

To determine the relationship between past-year internalizing symptoms and the time to first report of signs of nicotine dependence among young people.

METHODS

Secondary analysis using data from the Population Assessment of Tobacco and Health (PATH) (Waves 1-5; 2013-2019). The study included 2,102 (N = 5,031,691) young people (age 12-23 years) who reported past-30-day (P30D) e-cigarette use in one or more waves. Kaplan Meier curves, stratified by past year internalizing symptoms were used to estimate the time to the first report of three nicotine dependence symptoms (i.e., use within 30 min of waking, cravings, and really needing to use) following the first P30D e-cigarette use. Cox proportional hazard models were used to estimate crude and adjusted hazard ratios (AHR), comparing any past year internalizing symptoms to no past year internalizing symptoms.

RESULTS

We found no significant differences between past year internalizing symptoms and the time to the first report of cravings (AHR = 1.30, 95 % CI = 92-1.85), really needing to use (AHR = 1.31; 95 % CI = 0.92-1.89) and use within 30 min of waking for follow-up times 0-156 weeks (AHR = 0.84; 95 % CI = 0.55-1.30) and > 156 weeks (AHR = 0.41; 95 % CI = 0.04-4.67) respectively.

CONCLUSION

Past year internalizing symptoms did not modify the time to the first report of nicotine dependence among youth with P30D e-cigarette use. Further research is needed to understand how changing internalizing symptoms and e-cigarette use frequency influence nicotine dependence over time and, how this relationship impacts cessation behavior.

Ultrasonic Cigarettes: Chemicals and Cytotoxicity are Similar to Heated-Coil Pod-Style Electronic Cigarettes

Our purpose was to test the hypothesis that ultrasonic cigarettes (u-cigarettes), which operate at relatively low temperatures, produce aerosols that are less harmful than heated-coil pod-style electronic cigarettes (e-cigarettes). The major chemicals in SURGE u-cigarette fluids and aerosols were quantified, their cytotoxicity and cellular effects were assessed, and a Margin of Exposure risk assessment was performed on chemicals in SURGE fluids. Four SURGE u-cigarette flavor variants ("Blueberry Ice," "Watermelon Ice," "Green Mint," and "Polar Mint") were evaluated. Flavor chemicals were quantified in fluids and aerosols using gas chromatography/mass spectrometry. Cytotoxicity and cell dynamics were assessed using the MTT assay, live-cell imaging, and fluorescence microscopy. WS-23 (a coolant) and total flavor chemical concentrations in SURGE were similar to e-cigarettes, while SURGE nicotine concentrations (13-19 mg/mL) were lower than many fourth generation e-cigarettes. Transfer efficiencies of dominant chemicals to aerosols in SURGE ranged from 44-100%. SURGE fluids and aerosols had four dominant flavor chemicals (>1 mg/mL). Toxic aldehydes were usually higher in SURGE aerosols than in SURGE fluids. SURGE fluids and aerosols had aldehyde concentrations significantly higher than pod-style e-cigarettes. Chemical constituents, solvent ratios, and aldehydes varied among SURGE flavor variants. SURGE fluids and aerosols inhibited cell growth and mitochondrial reductases, produced attenuated and round cells, and depolymerized actin filaments, effects that depended on pod flavor, chemical constituents, and concentration. The MOEs for nicotine, WS-23, and propylene glycol were <100 based on consumption of 1-2 SURGE u-cigarettes/day. Replacing the heating coil with a sonicator did not eliminate chemicals, including aldehydes, in aerosols or diminish toxicity in comparisons between SURGE and other e-cigarette pod products. The high concentrations of nicotine, WS-23, flavor chemicals, and aldehydes and the cytotoxicity of SURGE aerosols do not support the hypothesis that aerosols from u-cigarettes are less harmful than those from e-cigarettes.

Physical and Chemical Characterization of Aerosols Produced from Experimentally Designed Nicotine Salt-Based E-Liquids

Nicotine salt-based e-liquids deliver nicotine more rapidly and efficiently to electronic nicotine delivery system (ENDS) users than freebase nicotine formulations. Nicotine salt-based products represent a substantial majority of the United States ENDS market. Despite the popularity of nicotine salt formulations, the chemical and physical characteristics of aerosols produced by nicotine salt e-liquids are still not well understood. To address this, this study reports the harmful and potentially harmful constituents (HPHCs) and particle sizes of aerosols produced by laboratory-made freebase nicotine and nicotine salt e-liquids. The nicotine salt e-liquids were formulated with benzoic acid, citric acid, lactic acid, malic acid, or oxalic acid. The nicotine salt aerosols had different HPHC profiles than the freebase nicotine aerosols, indicating that the carboxylic acids were not innocent bystanders. The polycarboxylic acid e-liquids containing citric acid, malic acid, or oxalic acid produced higher acrolein yields than the monocarboxylic acid e-liquids containing benzoic acid or lactic acid. Across most PG:VG ratios, nicotine benzoate or nicotine lactate aerosols contained the highest nicotine quantities (in %) and the highest nicotine yields (per milligram of aerosol). Additionally, the nicotine benzoate and nicotine lactate e-liquids produced the highest carboxylic acid yields under all tested conditions. The lower acid yields of the citric, malic, and oxalic acid formulations are potentially due to a combination of factors such as lower transfer efficiencies, lower thermostabilities, and greater susceptibility to side reactions because of their additional carboxyl groups serving as new sites for reactivity. For all nicotine formulations, the particle size characteristics were primarily controlled by the e-liquid solvent ratios, and there were no clear trends between nicotine salt and freebase nicotine aerosols that indicated nicotine protonation affected particle size. The carboxylic acids impacted aerosol output, nicotine delivery, and HPHC yields in distinct ways such that interchanging them in ENDS can potentially cause downstream effects.

Composition of e-cigarette aerosols: A review and risk assessment of selected compounds

The potential harms and benefits of e-cigarettes, or electronic nicotine delivery systems (ENDS), have received significant attention from public health and regulatory communities. Such products may provide a reduced risk means of nicotine delivery for combustible cigarette smokers while being inappropriately appealing to nicotine naive youth. Numerous authors have examined the chemical complexity of aerosols from various open- and closed-system ENDS. This body of literature is reviewed here, with the risks of ENDS aerosol exposure among users evaluated with a margin of exposure (MoE) approach for two non-carcinogens (methylglyoxal, butyraldehyde) and a cancer risk analysis for the carcinogen N-nitrosonornicotine (NNN). We identified 96 relevant papers, including 17, 13, and 5 reporting data for methylglyoxal, butyraldehyde, and NNN, respectively. Using low-end (minimum aerosol concentration, low ENDS use) and high-end (maximum aerosol concentration, high ENDS use) assumptions, estimated doses for methylglyoxal (1.78 × 10-3-135 μg/kg-bw/day) and butyraldehyde (1.9 × 10-4-66.54 μg/kg-bw/day) corresponded to MoEs of 227-17,200,000 and 271-280,000,000, respectively, using identified points of departure (PoDs). Doses of 9.90 × 10-6-1.99 × 10-4 μg/kg-bw/day NNN corresponded to 1.4-28 surplus cancers per 100,000 ENDS users, relative to a NNN-attributable surplus of 7440 per 100,000 cigarette smokers. It was concluded that methylglyoxal and butyraldehyde in ENDS aerosols, while not innocuous, did not present a significant risk of irritant effects among ENDS users. The carcinogenic risks of NNN in ENDS aerosols were reduced, but not eliminated, relative to concentrations reported in combustible cigarette smoke.

Analytical methods and experimental quality in studies targeting carbonyls in electronic cigarette aerosols

We provide an extensive review of 14 studies (11 independent and three industry-funded) on emissions generated by Electronic Cigarettes (ECs), specifically focusing on the evaluation of carbonyls present in these emissions and emphasizing a meticulous evaluation of their analytical methods and experimental procedures. Since the presence of carbonyl by-products in EC aerosol is concerning, it is important to evaluate the reliability of emission studies quantifying these compounds by verifying their compliance with the following criteria of experimental quality: authors must 1) supply sufficient information on the devices and experimental procedures to allow for potentially reproducing or replicating the experiments, 2) use of appropriate puffing protocols that approach consumer usage as best as possible, 3) use of appropriate analytical methods and 4) usage of blank samples to avoid false positive detection. Outcomes were classified in terms of the fulfilment of these conditions as reliable in seven studies, partially reliable in five studies, and unreliable in two studies. However, only five studies used blank samples and six studies failed the reproducibility criterion. Carbonyl yields were far below their yields in tobacco smoke in all reproducible studies, even in the partially reliable ones, thus supporting the role of ECs (when properly tested and operated) as harm reduction products. This review highlights the necessity to evaluate the quality of laboratory standards in testing EC emissions to achieve an objective assessment of the risk profile of ECs.

Understanding the nicotine dose delivered by electronic nicotine delivery systems in a single puff: the importance of nicotine flux and puff duration

Electronic nicotine delivery systems (ENDS) may lead to public health benefit if they help people who smoke quit smoking, and may lead to public health harm if they recruit a new generation of nicotine-dependent people. Regulators intent on maximising ENDS' public health benefit and minimising harm may be interested in regulating the nicotine dose delivered by ENDS in a single puff. The per-puff nicotine dose is the product of ENDS nicotine emission rate (or 'nicotine flux') and the duration of the puff taken by the person using the ENDS (or 'puff duration'). Nicotine flux can be measured or predicted mathematically for any ENDS device/liquid combination. Puff duration can be controlled electronically, as demonstrated by several ENDS marketed today. Combining nicotine flux and puff duration regulation is feasible today and provides authorities the means to limit nicotine dose per puff to a level that may help people who smoke quit smoking while reducing the possibility that nicotine-naive individuals will engage in repeated ENDS use. Tobacco regulatory science and product regulation will both be improved by a rigorous approach to understanding, characterising, and reporting the nicotine dose emitted by ENDS.

Time to first report of signs of nicotine dependence among youth who use e-cigarettes and cigarettes in the United States: A nationally representative cohort study, findings from the Population Assessment of Tobacco and Health, 2013-2019

OBJECTIVE

To determine the time to first report of signs of nicotine dependence among youth exclusive e-cigarette users and compare this time to that for exclusive cigarette users.

METHODS

Secondary analysis of data (Waves 1-5; 2013-2019) from the Population Assessment of Tobacco and Health was conducted. Youth never tobacco users in the United States who reported exclusive past-30-day (P30D) e-cigarette or cigarette use (n = 2940, N = 5,391,642) in at least one wave were included in the current analysis. Survival analysis was used to estimate the time to the first report of three nicotine dependence indicators (i.e., "use within 30 minutes of waking"; "cravings" and "really needing to use") following the first report of P30D use. Multivariable Cox proportional hazard models were used to estimate adjusted hazard ratios (aHR).

RESULTS

There were no significant differences in the time to first report of "use within 30 minutes of waking" (aHR = 1.1, 95% CI = 0.87-1.40) and "cravings" (aHR = 1.09, 95% CI = 0.81-1.47) between exclusive P30D e-cigarette use and exclusive P30D cigarette use. However, compared to exclusive P30D e-cigarette use, the hazard of first reporting "really needing to use" tobacco was 39% (aHR 1.39; 95% CI: 1.05-1.84) times higher for those who reported exclusive P30D cigarette use after controlling for covariates.

CONCLUSION

Compared to exclusive P30D cigarette use, no differences in the time to first report of signs of nicotine dependence ("use within 30 minutes" and "cravings") were observed among exclusive P30D e-cigarette users. Policymakers and regulatory agencies should consider this evidence when assessing the abuse liability of e-cigarette products.

In vitro toxicological evaluation of aerosols generated by a 4th generation vaping device using nicotine salts in an air-liquid interface system

BACKGROUND

Electronic cigarettes (EC) have gained popularity, especially among young people, with the introduction of fourth-generation devices based on e-liquids containing nicotine salts that promise a smoother vaping experience than freebase nicotine. However, the toxicological effects of nicotine salts are still largely unknown, and the chemical diversity of e-liquids limits the comparison between different studies to determine the contribution of each compound to the cytotoxicity of EC aerosols. Therefore, the aim of this study was to evaluate the toxicological profile of controlled composition e-liquid aerosols to accurately determine the effects of each ingredient based on exposure at the air-liquid interface.

METHODS

Human lung epithelial cells (A549) were exposed to undiluted aerosols of controlled composition e-liquids containing various ratios of propylene glycol (PG)/vegetable glycerin (VG) solvents, freebase nicotine, organic acids, nicotine salts, and flavoured commercial e-liquids. Exposure of 20 puffs was performed at the air-liquid interface following a standard vaping regimen. Toxicological outcomes, including cytotoxicity, inflammation, and oxidative stress, were assessed 24 h after exposure.

RESULTS

PG/VG aerosols elicited a strong cytotoxic response characterised by a 50% decrease in cell viability and a 200% increase in lactate dehydrogenase (LDH) production, but had no effects on inflammation and oxidative stress. These effects occurred only at a ratio of 70/30 PG/VG, suggesting that PG is the major contributor to aerosol cytotoxicity. Both freebase nicotine and organic acids had no greater effect on cell viability and LDH release than at a 70/30 PG/VG ratio, but significantly increased inflammation and oxidative stress. Interestingly, the protonated form of nicotine in salt showed a stronger proinflammatory effect than the freebase nicotine form, while benzoic acid-based nicotine salts also induced significant oxidative stress. Flavoured commercial e-liquids was found to be cytotoxic at a threshold dose of ≈ 330 µg/cm².

CONCLUSION

Our results showed that aerosols of e-liquids consisting only of PG/VG solvents can cause severe cytotoxicity depending on the concentration of PG, while nicotine salts elicit a stronger pro-inflammatory response than freebase nicotine. Overall, aerosols from fourth-generation devices can cause different toxicological effects, the nature of which depends on the chemical composition of the e-liquid.

Symptoms of nicotine dependence by e-cigarette and cigarette use behavior and brand: A population-based, nationally representative cross-sectional study

BACKGROUND

Many modern e-cigarette brands contain equivalent or higher nicotine levels than traditional cigarettes.

OBJECTIVE

To examine differences in four nicotine dependence indicators (i.e., use within 30minutes of waking, cravings, needing to use, and frequent use) among adolescents (aged 12-17 years) with past 30-day (P30D) exclusive use of e-cigarettes, cigarettes, or dual use of both.

METHODS

Data were from Wave 5 (2018-2019) of the Population Assessment of Tobacco and Health (PATH) study (n=1060; N=2053,659). Multivariable logistic regression was performed to determine differences in indicators by P30D e-cigarette and cigarette use behavior (exclusive vs. dual use) and brand (e-cigarette use: JUUL vs. non-JUUL vs. Unknown).

RESULTS

The odds of frequent use among adolescents with JUUL (AOR: 2.11; 95% CI=1.02-4.37) and non-JUUL (AOR: 2.12; 95% CI=0.95-4.77) use were similar and paralleled that for dual use (AOR: 3.50; 95% CI=1.46-8.43) but were stronger (JUUL only) than exclusive cigarette use. The odds of using within 30minutes of waking for adolescents with JUUL (AOR: 2.23; 95% CI=0.80-6.25) and non-JUUL (AOR:1.42; 95% CI=0.47-4.32) use were similar and paralleled that for both dual (AOR=3.00; 95% CI=1.01-8.88) and exclusive cigarette use. For adolescents who used unknown brands, the odds of all indicators paralleled exclusive cigarette use but were lower than JUUL, non-JUUL, and dual use.

CONCLUSION

Compared to exclusive cigarette use, symptoms of nicotine dependence are similar for adolescents with exclusive e-cigarette use, irrespective of brand. Symptoms of nicotine dependence for JUUL and non-JUUL use parallel dual use. Tobacco regulation should consider these findings when assessing the abuse liability of e-cigarettes.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol by heating an e-liquid. People who smoke, healthcare providers and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review.

OBJECTIVES

To examine the safety, tolerability and effectiveness of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence, in comparison to non-nicotine EC, other smoking cessation treatments and no treatment.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register to 1 February 2023, and Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 July 2023, and reference-checked and contacted study authors.

SELECTION CRITERIA

We included trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention as these studies have the potential to provide further information on harms and longer-term use. Studies had to report an eligible outcome.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Critical outcomes were abstinence from smoking after at least six months, adverse events (AEs), and serious adverse events (SAEs). We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in pairwise and network meta-analyses (NMA).

MAIN RESULTS

We included 88 completed studies (10 new to this update), representing 27,235 participants, of which 47 were randomized controlled trials (RCTs). Of the included studies, we rated ten (all but one contributing to our main comparisons) at low risk of bias overall, 58 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There is high certainty that nicotine EC increases quit rates compared to nicotine replacement therapy (NRT) (RR 1.59, 95% CI 1.29 to 1.93; I2 = 0%; 7 studies, 2544 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6 more). There is moderate-certainty evidence (limited by imprecision) that the rate of occurrence of AEs is similar between groups (RR 1.03, 95% CI 0.91 to 1.17; I2 = 0%; 5 studies, 2052 participants). SAEs were rare, and there is insufficient evidence to determine whether rates differ between groups due to very serious imprecision (RR 1.20, 95% CI 0.90 to 1.60; I2 = 32%; 6 studies, 2761 participants; low-certainty evidence). There is moderate-certainty evidence, limited by imprecision, that nicotine EC increases quit rates compared to non-nicotine EC (RR 1.46, 95% CI 1.09 to 1.96; I2 = 4%; 6 studies, 1613 participants). In absolute terms, this might lead to an additional three quitters per 100 (95% CI 1 to 7 more). There is moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 1840 participants). There is insufficient evidence to determine whether rates of SAEs differ between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 9 studies, 1412 participants; low-certainty evidence). Due to issues with risk of bias, there is low-certainty evidence that, compared to behavioural support only/no support, quit rates may be higher for participants randomized to nicotine EC (RR 1.88, 95% CI 1.56 to 2.25; I2 = 0%; 9 studies, 5024 participants). In absolute terms, this represents an additional four quitters per 100 (95% CI 2 to 5 more). There was some evidence that (non-serious) AEs may be more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low-certainty evidence; 4 studies, 765 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 0.89, 95% CI 0.59 to 1.34; I2 = 23%; 10 studies, 3263 participants; very low-certainty evidence). Results from the NMA were consistent with those from pairwise meta-analyses for all critical outcomes, and there was no indication of inconsistency within the networks. Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued EC use. Very few studies reported data on other outcomes or comparisons, hence, evidence for these is limited, with CIs often encompassing both clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that ECs with nicotine increase quit rates compared to NRT and moderate-certainty evidence that they increase quit rates compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain due to risk of bias inherent in the study design. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but the longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Effects of Aftermarket Electronic Cigarette Pods on Device Power Output and Nicotine, Carbonyl, and ROS Emissions

Aftermarket pods designed to operate with prevalent electronic nicotine delivery system (ENDS) products such as JUUL are marketed as low-cost alternatives that allow the use of banned flavored liquids. Subtle differences in the design or construction of aftermarket pods may intrinsically modify the performance of the ENDS device and the resulting nicotine and toxicant emissions relative to the original equipment manufacturer's product. In this study, we examined the electrical output of a JUUL battery and the aerosol emissions when four different brands of aftermarket pods filled with an analytical-grade mixture of propylene glycol, glycerol, and nicotine were attached to it and puffed by machine. The aerosol emissions examined included total particulate matter (TPM), nicotine, carbonyl compounds (CCs), and reactive oxygen species (ROS). We also compared the puff-resolved power and TPM outputs of JUUL and aftermarket pods. We found that all aftermarket pods drew significantly greater electrical power from the JUUL battery during puffing and had different electrical resistances and resistivity. In addition, unlike the case with the original pods, we found that with the aftermarket pods, the power provided by the battery did not vary greatly with flow rate or puff number, suggesting impairment of the temperature control circuitry of the JUUL device when used with the aftermarket pods. The greater power output with the aftermarket pods resulted in up to three times greater aerosol and nicotine output than the original product. ROS and CC emissions varied widely across brands. These results highlight that the use of aftermarket pods can greatly modify the performance and emissions of ENDS. Consumers and public health authorities should be made aware of the potential increase in the level of toxicant exposure when aftermarket pods are employed.

Metal Concentrations in E-Cigarette Aerosol Samples: A Comparison by Device Type and Flavor

BACKGROUND

The rapid evolution of electronic cigarette (e-cigarette) products warrants surveillance of the differences in exposure across device types-modifiable devices (MODs), cartridge ("pod")-containing devices (PODs), disposable PODs (d-PODs)-and flavors of the products available on the market.

OBJECTIVE

This study aimed to measure and compare metal aerosol concentrations by device type and common flavors.

METHODS

We collected aerosol from 104 MODs, 67 PODs (four brands: JUUL, Bo, Suorin, PHIX), and 23 d-PODs (three brands: ZPOD, Bidi, Stig) via droplet deposition in a series of conical pipette tips. Metals and metalloids [aluminum (Al), arsenic (As), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), lead (Pb), antimony (Sb), tin (Sn), and zinc (Zn)] were measured using inductively coupled plasma mass spectrometry (ICP-MS), results were log-transformed for statistical analysis, and concentrations are reported in aerosol units (mg / m 3 ).

RESULTS

Of the 12 elements analyzed, concentrations were statistically significantly higher in MOD devices, except for Co and Ni, which were higher in PODs and d-PODs. Of the POD brands analyzed, PHIX had the highest median concentrations among four metals (Al, Ni, Pb, and Sn) compared to the rest of the POD brands. According to POD flavor, seven metals were three to seven orders of magnitude higher in tobacco-flavored aerosol compared to those in mint and mango flavors. Among the d-POD brands, concentrations of four metals (Al, Cu, Ni, and Pb) were higher in the ZPOD brand than in Bidi Stick and Stig devices. According to d-POD flavor, only Cr concentrations were found to be statistically significantly higher in mint than tobacco-flavored d-PODs.

DISCUSSION

We observed wide variability in aerosol metal concentrations within and between the different e-cigarette device types, brands, and flavors. Overall, MOD devices generated aerosols with higher metal concentrations than PODs and d-PODs, and tobacco-flavored aerosols contained the highest metal concentrations. Continued research is needed to evaluate additional factors (i.e., nicotine type) that contribute to metal exposure from new and emerging e-cigarette devices in order to inform policy. https://doi.org/10.1289/EHP11921.

Vaping-Induced Proteolysis Causes Airway Surface Dehydration

Proteases such as neutrophil elastase cleave and activate the epithelial sodium channel (ENaC), causing airway dehydration. Our current study explores the impact of increased protease levels in vapers' airways on ENaC activity and airway dehydration. Human bronchial epithelial cultures (HBECs) were exposed to bronchoalveolar lavage fluid (BALF) from non-smokers, smokers and vapers. Airway surface liquid (ASL) height was measured by confocal microscopy as a marker of hydration. ENaC cleavage was measured by Western blotting. Human peripheral blood neutrophils were treated with a menthol-flavored e-liquid (Juul), and the resulting secretions were added to HBECs. BALF from smokers and vapers significantly and equally increased ENaC activity and decreased ASL height. The ASL height decrease was attenuated by protease inhibitors. Non-smokers' BALF had no effect on ENaC or ASL height. BALF from smokers and vapers, but not non-smokers, induced ENaC cleavage. E-liquid-treated neutrophil secretions cleaved ENaC and decreased ASL height. Our study demonstrated that elevated protease levels in vapers' airways have functional significance since they can activate ENaC, resulting in airway dehydration. Lung dehydration contributes to diseases like cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD) and asthma. Thus, our data predict that vaping, like smoking, will cause airway surface dehydration that likely leads to lung disease.

Effects of E-Cigarette Liquid Ratios on the Gravimetric Filter Correction Factors and Real-Time Measurements

Electronic cigarettes (ECIGs) generate high concentrations of particulate matter (PM), impacting the air quality inhaled by humans through secondhand exposure. ECIG liquids are available commercially and some users create their own "do-it-yourself" liquids, and these liquids often vary in the amounts of their chemical ingredients, including propylene glycol (PG) and vegetable glycerin (VG). Previous studies have quantified PM concentrations in ECIG aerosol generated from liquids containing different PG/VG ratios. However, the effects of these ratios on aerosol instrument filter correction factors needed to measure PM concentrations accurately have not been assessed. Thus, ECIG aerosol filter correction factors for multiple aerosol instruments (SMPS + APS, MiniWRAS, pDR, and SidePak) were determined for five different PG/VG ratios 1) 0PG/100VG, 2) 15PG/85VG, 3) 50PG/50VG, 4) 72PG/28VG, and 5) 90PG/10VG and two different PM sizes, PM1 (1 μm and smaller) and PM2.5 (2.5 μm and smaller). ECIG aerosols were generated inside a controlled exposure chamber using a diaphragm pump and a refillable ECIG device for all the ratios. In addition, the aerosol size distribution and mass median diameter were measured for all five ECIG ratios. PM2.5 correction factors (5-7.6) for ratios 1, 2, 3, and 4 were similar for the SMPS + APS combined data, and ratios 1, 2, 3 were similar for the MiniWRAS (~2), pDR (~0.5), and SidePak (~0.24). These data suggest different correction factors may need to be developed for aerosol generated from ECIGs with high PG content. The higher correction factor values for the 90PG/10VG ratio may have resulted from greater PG volatility relative to VG and sensor losses. The correction factors (ratios 1-4) for PM2.5 were SMPS + APS data (4.96-7.62), MiniWRAS (2.02-3.64), pDR (0.50-1.07), and SidePak (0.22-0.40). These data can help improve ECIG aerosol measurement accuracy for different ECIG mixture ratios.

Electronic Cigarette Users' Reactions and Responses to a Hypothetical Nicotine Concentration Reduction in Electronic Cigarette Liquids

Background: Regulations limiting nicotine in electronic cigarettes (e-cigarettes) have been proposed or implemented. Little is known about e-cigarette users' reactions to reducing e-cigarette liquid nicotine concentration. Methods: We used concept mapping to describe e-cigarette users' reactions to a 50% reduction in the nicotine concentration of their e-cigarette liquids. In 2019, current e-cigarette users who used e-cigarette liquid with greater than 0 mg/ml nicotine concentration completed an online study. Participants (n = 71, mean age = 34.9 (SD = 11.0), 50.7% women), brainstormed statements completing a prompt: "If the e-liquid that I use now in my e-cigarette/vaping device was only available in half the nicotine concentration or amount that I use now, a specific action I would take or a specific reaction I would have is…", Participants then sorted a final list of 67 statements into piles of similar content and rated statements on how true the statements would be for them. Multidimensional scaling and hierarchical cluster analyses identified thematic clusters. Results: Eight clusters were identified: (1) Replacement Product Seeking, (2) Mental Preparations and Expectations, (3) Use the New Liquid, (4) Information Seeking, (5) Compensation Behaviors, (6) Opportunity for E-Cigarette Reduction, (7) Physical and Psychological Effects, and (8) Replacement with non-E-Cigarette Products and Behaviors. Cluster ratings suggested many participants would search for other e-cigarette products/liquids to replace their current liquids, but using other tobacco products (e.g., cigarettes) may be less likely. Conclusions: If nicotine concentrations were decreased in e-cigarette liquids, e-cigarette users may attempt to purchase different e-cigarette products or modify their products to achieve desired effects.

Interactive effects of protonated nicotine concentration and device power on ENDS nicotine delivery, puff topography, and subjective effects

Electronic nicotine delivery systems (ENDSs) produce an aerosol by heating a liquid that often contains nicotine. The nicotine can be protonated that may make the aerosol easier to inhale than freebase nicotine. This study's purpose is to determine, in cigarette smokers and ENDS users, the effects of three concentrations of protonated nicotine aerosolized at two different power settings. Forty-five participants (22 cigarette smokers and 23 ENDS users) completed some or all of six sessions that varied by liquid nicotine concentration (10, 15, or 30 mg/ml protonated nicotine) and device power (15 or 30 W). Participants took 10 puffs from each product and then used each product for 90 min ad libitum. Plasma nicotine concentration, subjective effects, and puff topography were measured. Results showed increases in plasma nicotine concentration in all conditions, with greater plasma nicotine increases in higher watt, higher nicotine concentration conditions, as well as greater nicotine delivery for ENDS users compared to cigarette smokers. For puff topography, puff duration and volume decreased as nicotine concentration and power increased, and ENDS users took longer and larger puffs than cigarette smokers. Participants rated the higher watt, higher nicotine concentration conditions as harsher and with more throat hit. Overall, these results suggest that device characteristics and liquid constituents interact to influence users' plasma nicotine delivery and should be considered together when regulating ENDS. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Electronic Nicotine Delivery Systems (ENDS) use Among Members of a Community Engagement Program

Electronic nicotine delivery systems (ENDS) are relatively new and ENDS use data from community engagement programs may help us understand usage patterns and facilitate targeted longitudinal studies. Community members in Florida, USA, were asked about ENDS use, tobacco use, and health history/concerns by Community Health Workers. Among 7253 members recruited during 2014 to 2021 into our HealthStreet program, 1177 had ever used ENDS; the proportion increased from 12 to 27% from 2014 to 2021 (adjusted odds ratio (aOR) 2.5; 95% CI 1.7-3.5; Ever versus never used ENDS). Ever tobacco use was strongly associated with ENDS use; 69% of ever users were current tobacco users. Demographic determinants (sex, age, race) and food insecurity were strongest predictors of ENDS use. Most who had ever used ENDS were aged 18-25 (aOR 5.9; 95% CI 4.6-7.6; vs. aged 60 + years), White (aOR 3.7; 95% CI 3.2-4.3; vs. Black/African American), male (aOR 1.5; 95% CI 1.3-1.7; vs. female), and recently food insecure (aOR 1.8; 95% CI 1.5-2.0; vs. not recently food insecure). Those with respiratory issues were more likely to have used ENDS compared to those without (aOR 2.0; 95% CI 1.6-2.6; aOR 1.3; 95% CI 1.1-1.5). Members concerned about hypertension were less likely to have used ENDS (aOR 0.7; 95% CI 0.5-0.9). In this relatively rural, micropolitan sample, tobacco use, socio-economic determinants, and certain health history/concerns were strongly associated with ENDS use. Community outreach approaches are needed to further understand these factors and implement interventions.

Influence of puff topographies on e-liquid heating temperature, emission characteristics and modeled lung deposition of Puff Bar™

Puff Bar™, one of the latest designs of e-cigarettes, heats a mixture of liquid using a battery-powered coil at certain temperatures to emit aerosol. This study presents a mass-based characterization of emissions from seven flavors of Puff Bar™ devices by aerosolizing with three puff topographies [(puff volume: 55 < 65 < 75-mL) within 4-seconds at 30-seconds interval]. We evaluated the effects of puff topographies on heating temperatures; characterized particles using a cascade impactor; and measured volatile carbonyl compounds (VCCs). Modeled dosimetry and calculated mass median aerodynamic diameters (MMADs) were used to estimate regional, total respiratory deposition of the inhaled aerosol and exhaled fractions that could pose secondhand exposure risk. Temperatures of Puff Bar™ e-liquids increased with increasing puff volumes: 55mL (116.6 °C), 65 mL (128.3 °C), and 75mL (168.9 °C). Flavor types significantly influenced MMADs, total mass of particles, and VCCs (μg/puff: 2.15-2.30) in Puff Bar™ emissions (p < 0.05). Increasing puff volume (mL:55 < 65 < 75) significantly increased total mass (mg/puff: 4.6 < 5.6 < 6.2) of particles without substantially changing MMADs (~1μm:1.02~0.99~0.98). Aerosol emissions were estimated to deposit in the pulmonary region of e-cigarette user (41-44%), which could have toxicological importance. More than 2/3 (67-77%) of inhaled particles were estimated to be exhaled by users, which could affect bystanders. The VCCs measured contained carcinogens-formaldehyde (29.6%) and acetaldehyde (16.4%)-as well as respiratory irritants: acetone (23.9%), isovaleraldehyde (14.5%), and acrolein (4.9%). As Puff Bar™ emissions contain respirable particles and harmful chemicals, efforts should be made to minimize exposures, especially in indoor settings where people (including vulnerable populations) spend most of their life-time.

Fraction of Free-Base Nicotine in Simulated Vaping Aerosol Particles Determined by X-ray Spectroscopies

A new generation of electronic cigarettes is exacerbating the youth vaping epidemic by incorporating additives that increase the acidity of generated aerosols, which facilitate uptake of high nicotine levels. We need to better understand the chemical speciation of vaping aerosols to assess the impact of acidification. Here we used X-ray photoelectron spectroscopy (XPS) and near-edge X-ray absorption fine structure (NEXAFS) spectroscopy to probe the acid-base equilibria of nicotine in hydrated vaping aerosols. We show that, unlike the behavior observed in bulk water, nicotine in the core of aqueous particles was partially protonated when the pH of the nebulized solution was 10.4, with a fraction of free-base nicotine (α_FB) of 0.34. Nicotine was further protonated by acidification with equimolar addition of benzoic acid (α_FB = 0.17 at pH 6.2). By contrast, the degree of nicotine protonation at the particle surface was significantly lower, with 0.72 < α_FB < 0.80 in the same pH range. The presence of propylene glycol and glycerol completely eliminated protonation of nicotine at the surface (α_FB = 1) while not affecting significantly its acid-base equilibrium in the particle core. These results provide a better understanding of the role of acidifying additives in vaping aerosols, supporting public health policy interventions.

Electronic cigarette use intensity measurement challenges and regulatory implications

Assessing tobacco use intensity allows researchers to examine tobacco use in greater detail than assessing ever or current use only. Tobacco use intensity measures have been developed that are specific to tobacco products, such as asking smokers to report number of cigarettes smoked per day. However, consensus on electronic cigarette use intensity measures that can be used for survey research has yet to be established due to electronic cigarette product and user behavior heterogeneity. While some survey measures that attempt to assess electronic cigarette use intensity exist, such as examining number of 'times' using an electronic cigarette per day, number of puffs taken from an electronic cigarette per day, volume of electronic cigarette liquid consumed per day, or nicotine concentration of electronic cigarette liquid, most measures have limitations. Challenges in electronic cigarette measurement often stem from variations across electronic cigarette device and liquid characteristics as well as the difficulty that many electronic cigarette users have regarding answering questions about their electronic cigarette device, liquid, or behavior. The inability for researchers to measure electronic cigarette use intensity accurately has important implications such as failing to detect unintended consequences of regulatory policies. Development of electronic cigarette use intensity measures, though not without its challenges, can improve understanding of electronic cigarette use behaviors and associated health outcomes and inform development of regulatory policies.

Trends in e-cigarette brands, devices and the nicotine profile of products used by youth in England, Canada and the USA: 2017-2019

BACKGROUND

The e-cigarette market has rapidly evolved, with a shift towards higher nicotine concentration and salt-based products, such as JUUL; however, the implications for youth vaping remain unclear.

METHODS

Repeat cross-sectional online surveys were conducted in 2017, 2018 and 2019, with national samples of youth aged 16-19 years recruited from commercial panels in Canada (n=12 018), England (n=11 362) and the USA (n=12 110). Regression models examined differences between countries and over time in the types of e-cigarette products used (design and nicotine content), reasons for using brands and differences in patterns of use, sociodemographics and dependence symptoms by brand/nicotine content.

RESULTS

In 2019, the use of pod- or cartridge-style e-cigarettes was greater in Canada and the USA than England, with Smok and JUUL the leading brands in all countries. In 2019, youth vapers in England were less likely to report using e-cigarettes with ≥2% nicotine (12.8%) compared with Canada (40.5%; adjusted OR (AOR)=4.96; 95% CI 3.51 to 7.01) and the USA (37.0%; AOR=3.99, 95% CI 2.79 to 5.71) and less likely to report using nicotine salt-based products (12.3%) compared with Canada (27.1%; AOR=2.77, 95% CI 1.93 to 3.99) and the USA (21.9%; AOR=2.00, 95% CI 1.36 to 2.95). In 2019, self-reported use of products with higher nicotine concentration was associated with significantly greater frequency of vaping, urges to vape and perceived vaping addiction (p<0.05 for all).

CONCLUSIONS

The use of high-nicotine salt-based products is associated with greater symptoms of dependence, including JUUL and other higher-nicotine brands. Greater use of high-nicotine salt-based products may account for recent increases in the frequency of vaping among youth in Canada and the USA.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, although some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit smoking, and if they are safe to use for this purpose. This is a review update conducted as part of a living systematic review.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 July 2022, and reference-checked and contacted study authors.  SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants, or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses.

MAIN RESULTS

We included 78 completed studies, representing 22,052 participants, of which 40 were RCTs. Seventeen of the 78 included studies were new to this review update. Of the included studies, we rated ten (all but one contributing to our main comparisons) at low risk of bias overall, 50 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was high certainty that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (RR 1.63, 95% CI 1.30 to 2.04; I2 = 10%; 6 studies, 2378 participants). In absolute terms, this might translate to an additional four quitters per 100 (95% CI 2 to 6). There was moderate-certainty evidence (limited by imprecision) that the rate of occurrence of AEs was similar between groups (RR 1.02, 95% CI 0.88 to 1.19; I2 = 0%; 4 studies, 1702 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.12, 95% CI 0.82 to 1.52; I2 = 34%; 5 studies, 2411 participants). There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 5 studies, 1840 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.00, 95% CI 0.56 to 1.79; I2 = 0%; 8 studies, 1272 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.66, 95% CI 1.52 to 4.65; I2 = 0%; 7 studies, 3126 participants). In absolute terms, this represents an additional two quitters per 100 (95% CI 1 to 3). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that (non-serious) AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants) and, again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.03, 95% CI 0.54 to 1.97; I2 = 38%; 9 studies, 1993 participants).  Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued EC use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is high-certainty evidence that ECs with nicotine increase quit rates compared to NRT and moderate-certainty evidence that they increase quit rates compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs nor between nicotine ECs and NRT. Overall incidence of SAEs was low across all study arms. We did not detect evidence of serious harm from nicotine EC, but longest follow-up was two years and the number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Non-Targeted Chemical Characterization of JUUL-Menthol-Flavored Aerosols Using Liquid and Gas Chromatography

The aerosol constituents generated from JUUL Menthol pods with 3.0% and 5.0% nicotine by weight (Me3 and Me5) are characterized by a non-targeted approach, which was developed to detect aerosol constituents that are not known to be present beforehand or that may be measured with targeted methods. Three replicates from three production batches (n = 9) were aerosolized using two puffing regimens (intense and non-intense). Each of the 18 samples were analyzed by gas chromatography electron ionization mass spectrometry and by liquid chromatography electrospray ionization high-resolving power mass spectrometry. All chemical constituents determined to differ from control were identified and semi-quantified. To have a complete understanding of the aerosol constituents and chemistry, each chemical constituent was categorized into one of five groups: (1) flavorants, (2) harmful and potentially harmful constituents, (3) leachables, (4) reaction products, and (5) chemical constituents that were unable to be identified or rationalized (e.g., chemical constituents that could not be categorized in groups (1–4). Under intense puffing, 74 chemical constituents were identified in Me3 aerosols and 68 under non-intense puffing, with 53 chemical constituents common between both regimens. Eighty-three chemical constituents were identified in Me5 aerosol using an intense puffing regimen and seventy-five with a non-intense puffing regimen, with sixty-two chemical constituents in common. Excluding primary constituents, reaction products accounted for the greatest number of chemical constituents (approximately 60% in all cases, ranging from about 0.05% to 0.1% by mass), and flavorants—excluding menthol—comprised the second largest number of chemical constituents (approximately 25%, ranging consistently around 0.01% by mass). The chemical constituents detected in JUUL aerosols were then compared to known constituents from cigarette smoke to determine the relative chemical complexities and commonalities/differences between the two. This revealed (1) a substantial decrease in the chemical complexity of JUUL aerosols vs. cigarette smoke and (2) that there are between 55 (Me3) and 61 (Me5) unique chemical constituents in JUUL aerosols not reported in cigarette smoke. Understanding the chemical complexity of JUUL aerosols is important because the health effects of combustible cigarette smoke are related to the combined effect of these chemical constituents through multiple mechanisms, not just the effects of any single smoke constituent.

Nicotine delivery and cigarette equivalents from vaping a JUULpod

With patented nicotine salt technology, JUUL dominates the e-cigarette market. We reviewed studies of JUUL's nicotine pharmacokinetic profile and studies quantifying nicotine in a JUULpod, emitted in the aerosol and absorbed by users. Examined in eight studies, JUUL's peak nicotine levels were half to three-quarters that of a combustible cigarette in industry-conducted studies with JUUL-naïve users, while comparable to or greater than combustible cigarettes in independent studies of experienced e-cigarette users. JUUL Labs reports each 5% (nicotine-by-weight) cartridge contains approximately 40 mg nicotine per pod and is 'approximately equivalent to about 1 pack of cigarettes.' In five independent studies, nicotine in the liquid in a JUULpod ranged from 39.3 to 48.3 mg. Seven studies measured nicotine delivery via vaping-machine generated aerosols, varying in puffing regimes and equipment. One study estimated 68% transfer efficiency to the aerosol, measuring 28.8 mg nicotine per JUULpod. The other studies reported nicotine values ranging from 72 to 164 µg/puff. At 200 puffs, this is 14.4-32.8 mg of nicotine per pod with equivalence to 13-30 cigarettes. A study measuring nicotine levels in JUUL users during a 5-day controlled switch found equivalence to 18 cigarettes. One JUULpod appears capable of delivering the nicotine equivalent to smoking about a pack of cigarettes, with variability. In JUUL-naïve smokers, JUUL's nicotine boost was lower than that of combustible cigarettes; while in experienced users, JUUL was comparable. Minimising harshness and adaptive to user experience, JUUL's design facilitates initiation to a high nicotine, and ultimately, highly addictive vaping product.

On the toxicity of e-cigarettes consumption: Focus on pathological cellular mechanisms

Tobacco smoking remains without a doubt one of the leading causes of premature death worldwide. In combination with conventional protocols for smoking cessation, e-cigarettes have been proposed as a useful tool to quit smoking. Advertised as almost free of toxic effects, e-cigarettes have rapidly increased their popularity, becoming a sought-after device, especially among young people. Recently some health concerns about e-cigarette consumption are being raised. It is well known that they can release several toxic compounds, some of which are carcinogenic to humans, and emerging results are now outlining the risks related to the onset of respiratory and cardiovascular diseases and even cancer. The present review shows the emerging evidence about the role of technical components of the devices, the e-liquid composition as well as customization by consumers. The primary topics we discuss are the main toxicological aspects associated with e-cigarette consumption, focusing on the molecular pathways involved. Here it will be shown how exposure to e-cigarette aerosol induces stress/mitochondrial toxicity, DNA breaks/fragmentation following the same pathological pathways triggered by tobacco smoke, including the deregulation of molecular signalling axis associated with cancer progression and cell migration. Risk to fertility and pregnancy, as well as cardiovascular risk associated with e-cigarette use, have also been reported.

Toward Better Characterization of a Free-Base Nicotine Fraction in e-Liquids and Aerosols

Given that nicotine salts are a growing market, methods are needed to characterize nicotine forms in e-cigarette vaping products. By lowering the free-base nicotine fraction (α_fb) in favor of protonated forms, the addition of organic acids to the e-liquid mix greatly modulates nicotine pharmacokinetics and improves vapers' craving. This research investigated (1) the performance of pH measurement, liquid-liquid extraction (LLE), and acid/nicotine molar ratio calculation methods for α_fb estimation in 6 nicotine benzoate and nicotine salicylate e-liquids and (2) nicotine protonation in the aerosol post vaporization. Aerosols were generated with a JUUL device and another mod-pod on a vaping machine to assess device effects. E-liquid and aerosol samples were then analyzed after further analytical optimization of previous methods and careful consideration of biases. Globally, performances were comparable between methods. α_fb accounted for less than 5% of nicotine content regardless of experimental conditions. α_fb were consistent between e-liquids and aerosols irrespective of e-cigarette devices. Hence, e-liquids are adequate surrogates for aerosols, facilitating the establishment of regulations. pH measurement is one of the most used methods and enables the establishment of relative scales for e-liquid classification but lacks automation possibility. Until now, the extent of sample dilution remained arbitrary. The dilution factor was fixed at 10, as usually achieved, since no effect of dilution was noted. pH values ranged from 5.3 to 6.3 in accordance with the literature. By contrast, LLE relies on the specificity of organic solvent for free-base nicotine extraction, causing discrepancies in previous studies. Here, the results were similar to α_fb values from pH determination. Yet, LLE presented the highest variability and was the most time-consuming protocol. Finally, α_fb calculation from molar ratio was the most robust and versatile method. Estimations can be made in silico from reported composition data and/or after liquid chromatography routine analysis.

Laboratory Determination of Gravimetric Correction Factors for Real-time Area Measurements of Electronic Cigarette Aerosols

Research on secondhand electronic cigarette (ECIG) aerosol exposure using aerosol monitors has demonstrated that ECIG use can generate high concentrations of particulate matter (PM) and impact indoor air quality. However, quantifying indoor air PM concentrations using real-time optical monitors with on-site calibration specifically for different PM exposures has not been established. Therefore, the ECIG aerosol filter correction factors were calculated for different PM sizes (PM1, PM2.5, and PM10) and different aerosol optical monitors, the MiniWRAS, pDR, and SidePak. ECIG aerosol generation was achieved using five ECIGs representing three ECIG types, disposable, pod-mod, and box mod. The aerosol size distribution by mass was measured for the five ECIGs during PM generation. Compared to the discrete filter measurements, the MiniWRAS performed the best when the concentrations were low, followed by the pDR and SidePak. The average PM concentrations and correction factor ranges for the different ECIGs were 323-1,775 μg/m3 and 0.64-6.01 for the MiniWRAS, 1,388-13,365 μg/m3 and 0.41-0.80 for the pDR, and 4,632-55,339 μg/m3 and 0.13-0.20 for the SidePak, respectively. The mass median diameter ranged from 0.41 and 0.62 μm, and most particles generated from the ECIGs were smaller than 1 μm. This study demonstrates that aerosol size distribution varies between ECIGs. Likewise, the correction factors developed for the real-time aerosol monitors are specific to the ECIG used. Thus, these data can help improve ECIG aerosol exposure measurement accuracy.

Influence of Flavors and Nicotine Concentration on Nicotine Dependence in Adolescent and Young Adult E-Cigarette Users

Objective: The objective of this study is to examine the relationships between e-cigarette flavors, nicotine concentration, and their interaction on measures of nicotine dependence.Methods: Survey data are drawn from a cross-sectional convenience sample of past 30-day e-cigarette users aged 15 to 24 years (N = 2037) collected between October 2020 and November 2020. Participants were asked to provide information about the e-cigarette products they used most regularly. Only those with available information on flavors (fruit, mint, menthol/ice, and tobacco), nicotine concentration (0-2.9%, 3-4.9%, and 5% or greater), and time to first vape after waking (within 30 minutes, greater than 30 minutes) were included in analyses (N = 1430). Generalized linear regression models were used with log link and binary distribution to assess the relationship between flavors, nicotine concentration, and nicotine dependence. Effect modification by nicotine concentration was assessed using an interaction term for flavors by nicotine concentration. Models were adjusted for age, race/ethnicity, gender, and financial situation.Findings: Fruit, mint, and menthol flavor user groups had a very similar dose-response relationship between nicotine concentration and prevalence of vaping within 30 minutes. These groups showed that the prevalence of vaping within 30 minutes gradually increased as nicotine concentration increased. Meanwhile, tobacco flavor user groups demonstrated a decrease in prevalence of vaping within 30 minutes, as nicotine concentration increased.Conclusion: Results highlight the need for understanding how e-cigarette product characteristics like flavors and nicotine concentration can facilitate nicotine dependence to e-cigarettes. Findings suggest that comprehensive e-cigarette product regulation of all flavors and reducing nicotine concentration will help to reduce the risk for nicotine dependence among young people.

E-cigarette device and liquid characteristics and E-cigarette dependence: A pilot study of pod-based and disposable E-cigarette users

BACKGROUND

E-cigarette device and liquid characteristics, such as electrical power output and liquid nicotine concentration, determine the rate at which nicotine is emitted from the e-cigarette (i.e., nicotine flux), and thus are likely to influence user nicotine dependence. We hypothesize that nicotine flux would be associated with the E-cigarette Dependence Scale (EDS) among pod-based and disposable e-cigarette products.

METHODS

Data were obtained from online panel participants between 18 and 65 years of age, who had indicated that they were either former or current e-cigarette users and resided within the United States (N = 1036). To be included in these analyses, participants had to provide information regarding device type (pod-based or disposable), power (watts), and nicotine concentration (mg/mL), from which we could determine nicotine flux (µg/s) (N = 666). To assess the relationship between nicotine flux and EDS, a series of multivariable linear regressions were conducted. Each model was separated by device type and adjusted for by age and past 30-day e-cigarette use.

RESULTS

Greater nicotine flux was associated with higher EDS scores among pod-based e-cigarette users (beta = 0.19, SE = 0.09, p-value = 0.043), but not users of disposable e-cigarettes. Neither power nor nicotine concentration were associated with EDS scores among users of either e-cigarette device type.

CONCLUSION

Results support the hypothesis that nicotine flux is positively associated with nicotine dependence in a sample of current users of pod-based and disposable e-cigarettes.

Effect of Puffing Behavior on Particle Size Distributions and Respiratory Depositions From Pod-Style Electronic Cigarette, or Vaping, Products

The current fourth generation ("pod-style") electronic cigarette, or vaping, products (EVPs) heat a liquid ("e-liquid") contained in a reservoir ("pod") using a battery-powered coil to deliver aerosol into the lungs. A portion of inhaled EVP aerosol is estimated as exhaled, which can present a potential secondhand exposure risk to bystanders. The effects of modifiable factors using either a prefilled disposable or refillable pod-style EVPs on aerosol particle size distribution (PSD) and its respiratory deposition are poorly understood. In this study, the influence of up to six puff profiles (55-, 65-, and 75-ml puff volumes per 6.5 and 7.5 W EVP power settings) on PSD was evaluated using a popular pod-style EVP (JUUL® brand) and a cascade impactor. JUUL® brand EVPs were used to aerosolize the manufacturers' e-liquids in their disposable pods and laboratory prepared "reference e-liquid" (without flavorings or nicotine) in refillable pods. The modeled dosimetry and calculated aerosol mass median aerodynamic diameters (MMADs) were used to estimate regional respiratory deposition. From these results, exhaled fraction of EVP aerosols was calculated as a surrogate of the secondhand exposure potential. Overall, MMADs did not differ among puff profiles, except for 55- and 75-ml volumes at 7.5 W (p < 0.05). For the reference e-liquid, MMADs ranged from 1.02 to 1.23 μm and dosimetry calculations predicted that particles would deposit in the head region (36-41%), in the trachea-bronchial (TB) region (19-21%), and in the pulmonary region (40-43%). For commercial JUUL® e-liquids, MMADs ranged from 0.92 to 1.67 μm and modeling predicted that more particles would deposit in the head region (35-52%) and in the pulmonary region (30-42%). Overall, 30-40% of the particles aerosolized by a pod-style EVP were estimated to deposit in the pulmonary region and 50-70% of the inhaled EVP aerosols could be exhaled; the latter could present an inhalational hazard to bystanders in indoor occupational settings. More research is needed to understand the influence of other modifiable factors on PSD and exposure potential.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update conducted as part of a living systematic review.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke tobacco achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 May 2021, and reference-checked and contacted study authors. We screened abstracts from the Society for Research on Nicotine and Tobacco (SRNT) 2021 Annual Meeting.   SELECTION CRITERIA: We included randomized controlled trials (RCTs) and randomized cross-over trials, in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. Studies had to report abstinence from cigarettes at six months or longer or data on safety markers at one week or longer, or both.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included the proportion of people still using study product (EC or pharmacotherapy) at six or more months after randomization or starting EC use, changes in carbon monoxide (CO), blood pressure (BP), heart rate, arterial oxygen saturation, lung function, and levels of carcinogens or toxicants or both. We used a fixed-effect Mantel-Haenszel model to calculate risk ratios (RRs) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data in meta-analyses.

MAIN RESULTS

We included 61 completed studies, representing 16,759 participants, of which 34 were RCTs. Five of the 61 included studies were new to this review update. Of the included studies, we rated seven (all contributing to our main comparisons) at low risk of bias overall, 42 at high risk overall (including all non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.53, 95% confidence interval (CI) 1.21 to 1.93; I2 = 0%; 4 studies, 1924 participants). In absolute terms, this might translate to an additional three quitters per 100 (95% CI 1 to 6). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs were rare, but there was insufficient evidence to determine whether rates differed between groups due to very serious imprecision (RR 1.30, 95% CI 0.89 to 1.90: I2 = 0; 4 studies, 1424 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.94, 95% CI 1.21 to 3.13; I2 = 0%; 5 studies, 1447 participants). In absolute terms, this might lead to an additional seven quitters per 100 (95% CI 2 to 16). There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 1.06, 95% CI 0.47 to 2.38; I2 = 0; 5 studies, 792 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.61, 95% CI 1.44 to 4.74; I2 = 0%; 6 studies, 2886 participants). In absolute terms this represents an additional six quitters per 100 (95% CI 2 to 15). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was some evidence that non-serious AEs were more common in people randomized to nicotine EC (RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants), and again, insufficient evidence to determine whether rates of SAEs differed between groups (RR 1.51, 95% CI 0.70 to 3.24; I2 = 0%; 7 studies, 1303 participants).  Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons, hence evidence for these is limited, with CIs often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to NRT and compared to ECs without nicotine. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the effect size. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, with no difference in AEs between nicotine and non-nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect  evidence of harm from nicotine EC, but longest follow-up was two years and the  number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates, but further RCTs are underway. To ensure the review continues to provide up-to-date information to decision-makers, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Characterising vaping products in the United Kingdom: an analysis of Tobacco Products Directive notification data

AIMS

To analyse content and emission data submitted by manufacturers for nicotine-containing vaping products in the United Kingdom (UK) in accordance with the European Union Tobacco Products Directive.

DESIGN

Analysis of ingredient and emission data reported for all e-liquid-containing e-cigarettes, cartridges or refill containers notified to the Medicines and Healthcare Regulatory Agency (MHRA) from November 2016 to October 2017.

SETTING

United Kingdom CASES: A total of 40 785 e-liquid containing products.

MEASUREMENTS

The average number of ingredients per product, nicotine concentrations, frequency of occurrence ingredients and frequency and levels of chemical emissions.

FINDINGS

Reports were not standardised in relation to units of measurement or constituent nomenclature. Products listed an average of 17 ingredients and 3.3% were reported not to contain nicotine. A total of 59% of products contained <12 mg nicotine per mL, and <1% were reported to have nicotine concentrations above the legal limit of 20 mg/mL. Over 1500 ingredients were reported, and other than nicotine the most commonly reported non-flavour ingredients were propylene glycol (97% of products) and glycerol (71%). The most common flavour ingredients were ethyl butyrate (42%), vanillin (35%) and ethyl maltol (33%). The most frequently reported chemical emissions were nicotine (65%), formaldehyde (48%) and acetaldehyde (40%). The reporting of the concentration of emissions was not standardised; emissions were reported in a format allowing analysis of median estimated concentration for between 13% and 100% of products for each reported emission. Most of the frequently reported emissions, other than nicotine, were present in median estimated concentrations below 1 μg/L of inspired air, and with the exception of nicotine, acrolein and diacetyl, at median levels below European Chemicals Agency Long Term Exposure and United States (US) Department of Labor Occupational Safety and Health Administration (OSHA) limits, where these were available.

CONCLUSIONS

An analysis of reports to the United Kingdom's Medicines and Healthcare products Regulatory Agency by manufacturers of vaping products shows that (i) these products have a large range of ingredients and emissions, (ii) the reporting system is unstandardized in terms of reporting requirements, and (iii) for quantified emissions, median levels are for the most part below published safe limits for ambient air.

Non-Targeted Chemical Characterization of JUUL Virginia Tobacco Flavored Aerosols Using Liquid and Gas Chromatography

The chemical constituents of JUUL Virginia Tobacco pods with 3.0% and 5.0% nicotine by weight (VT3 and VT5) were characterized by non-targeted analyses, an approach to detect chemicals that are not otherwise measured with dedicated methods or that are not known beforehand. Aerosols were generated using intense and non-intense puffing regimens and analyzed by gas chromatography electron ionization mass spectrometry and liquid chromatography electrospray ionization high resolving power mass spectrometry. All compounds above 0.7 µg/g for GC–MS analysis or above 0.5 µg/g for LC–HRMS analysis and differing from blank measurements were identified and semi-quantified. All identifications were evaluated and categorized into five groups: flavorants, harmful and potentially harmful constituents, extractables and/or leachables, reaction products, and compounds that could not be identified/rationalized. For VT3, 79 compounds were identified using an intense puffing regimen and 69 using a non-intense puffing regimen. There were 60 compounds common between both regimens. For VT5, 85 compounds were identified with an intense puffing regimen and 73 with a non-intense puffing regimen; 67 compounds were in common. For all nicotine concentrations, formulations and puffing regimens, reaction products accounted for the greatest number of compounds (ranging from 70% to 75%; 0.08% to 0.1% by mass), and flavorants comprised the second largest number of compounds (ranging from for 15% to 16%; 0.1 to 0.2% by mass). A global comparison of the compounds detected in JUUL aerosol to those catalogued in cigarette smoke indicated an approximate 50-fold decrease in chemical complexity. Both VT3 and VT5 aerosols contained 59 unique compounds not identified in cigarette smoke.

The consequential impact of JUUL on youth vaping and the landscape of tobacco products: The state of play in the COVID-19 era

JUUL is a groundbreaking electronic cigarette (e-cig) and the preeminent vaping product on the market. We present an overview of the rapid and spectacular rise of JUUL and its remarkable fall within the timespan of 2015 - 2020. We highlight JUUL's entering the market in June 2015, becoming the industry leader in mid 2017, and experiencing a litany of setbacks by late 2019 through to early 2020. We address the role played by JUUL in the ongoing epidemic of youth vaping. We also feature competing views on the public health impact of JUUL use (in particular), and e-cig vaping (in general). We further highlight the latest trends in youth vaping and sales records for JUUL and tobacco cigarettes. In view of the ongoing pandemic of COVID-19, we briefly summarize the existing evidence on the relationship between vaping and smoking and the prevalence, disease course, and clinical outcomes of COVID-19.

Electrical features, liquid composition and toxicant emissions from 'pod-mod'-like disposable electronic cigarettes

INTRODUCTION

Use of flavoured pod-mod-like disposable electronic cigarettes (e-cigarettes) has grown rapidly, particularly among cost-sensitive youth and young adults. To date, little is known about their design characteristics and toxicant emissions. In this study, we analysed the electrical and chemical characteristics and nicotine and pulmonary toxicant emission profiles of five commonly available flavoured disposable e-cigarettes and compared these data with those of a JUUL, a cartridge-based e-cigarette device that pod-mod-like disposables emulate in size and shape.

METHODS

Device construction, electrical power and liquid composition were determined. Machine-generated aerosol emissions including particulate matter, nicotine, carbonyl compounds and heavy metals were also measured. Liquid and aerosol composition were measured by high-performance liquid chromatography, gas chromatography-mass spectrometry/flame ionisation detection, and inductively coupled plasma mass spectrometry.

RESULTS

We found that unlike JUUL, disposable devices did not incorporate a microcontroller to regulate electrical power to the heating coil. Quality of construction varied widely. Disposable e-cigarette power ranged between 5 and 9 W and liquid nicotine concentration ranged between 53 and 85 mg/mL (~95% in the protonated form). In 15 puffs, total nicotine yield for the disposables ranged between 1.6 and 6.7 mg, total carbonyls ranged between 28 and 138 µg, and total metals ranged between 1084 and 5804 ng. JUUL emissions were near the floors of all of these ranges.

CONCLUSIONS

Disposable e-cigarettes are designed with high nicotine concentration liquids and are capable of emitting much higher nicotine and carbonyl species relative to rechargeable look-alike e-cigarettes. These differences are likely due to the lower quality in construction, unreliable labelling and lack of temperature control regulation that limits the power during operation. From a public health perspective, regulating these devices is important to limit user exposure to carbonyls and nicotine, particularly because these devices are popular with youth and young adults.

JUUL 'new technology' pods exhibit greater electrical power and nicotine output than previous devices

In 2019, JUUL Labs began marketing in the European Union 'new technology' pods that incorporated a new wick that it claimed provided 'more satisfaction'. In this study, we compared design and materials of construction, electrical characteristics, liquid composition and nicotine and carbonyl emissions of new technology JUUL pods to their predecessors. Consistent with manufacturer's claims, we found that the new pods incorporated a different wicking material. However, we also found that the new pod design resulted in 50% greater nicotine emissions per puff than its predecessor, despite exhibiting unchanged liquid composition, device geometry and heating coil resistance. We found that when connected to the new technology pods, the JUUL power unit delivered a more consistent voltage to the heating coil. This behaviour suggests that the new coil-wick system resulted in better surface contact between the liquid and the temperature-regulated heating coil. Total carbonyl emissions did not differ across pod generations. That nicotine yields can be greatly altered with a simple substitution of wick material underscores the fragility of regulatory approaches that centre on product design rather than product performance specifications.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. Some people who smoke use ECs to stop or reduce smoking, but some organizations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This is an update of a review first published in 2014.

OBJECTIVES

To examine the effectiveness, tolerability, and safety of using electronic cigarettes (ECs) to help people who smoke achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO to 1 February 2021, together with reference-checking and contact with study authors.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and randomized cross-over trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. To be included, studies had to report abstinence from cigarettes at six months or longer and/or data on adverse events (AEs) or other markers of safety at one week or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, adverse events (AEs), and serious adverse events (SAEs). Secondary outcomes included changes in carbon monoxide, blood pressure, heart rate, blood oxygen saturation, lung function, and levels of known carcinogens/toxicants. We used a fixed-effect Mantel-Haenszel model to calculate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data from these studies in meta-analyses.

MAIN RESULTS

We included 56 completed studies, representing 12,804 participants, of which 29 were RCTs. Six of the 56 included studies were new to this review update. Of the included studies, we rated five (all contributing to our main comparisons) at low risk of bias overall, 41 at high risk overall (including the 25 non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.69, 95% confidence interval (CI) 1.25 to 2.27; I2 = 0%; 3 studies, 1498 participants). In absolute terms, this might translate to an additional four successful quitters per 100 (95% CI 2 to 8). There was low-certainty evidence (limited by very serious imprecision) that the rate of occurrence of AEs was similar) (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs occurred rarely, with no evidence that their frequency differed between nicotine EC and NRT, but very serious imprecision led to low certainty in this finding (RR 1.37, 95% CI 0.77 to 2.41: I2 = n/a; 2 studies, 727 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.70, 95% CI 1.03 to 2.81; I2 = 0%; 4 studies, 1057 participants). In absolute terms, this might again lead to an additional four successful quitters per 100 (95% CI 0 to 11). These trials mainly used older EC with relatively low nicotine delivery. There was moderate-certainty evidence of no difference in the rate of AEs between these groups (RR 1.01, 95% CI 0.91 to 1.11; I2 = 0%; 3 studies, 601 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.60, 95% CI 0.15 to 2.44; I2 = n/a; 4 studies, 494 participants). Compared to behavioral support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.70, 95% CI 1.39 to 5.26; I2 = 0%; 5 studies, 2561 participants). In absolute terms this represents an increase of seven per 100 (95% CI 2 to 17). However, this finding was of very low certainty, due to issues with imprecision and risk of bias. There was no evidence that the rate of SAEs differed, but some evidence that non-serious AEs were more common in people randomized to nicotine EC (AEs: RR 1.22, 95% CI 1.12 to 1.32; I2 = 41%, low certainty; 4 studies, 765 participants; SAEs: RR 1.17, 95% CI 0.33 to 4.09; I2 = 5%; 6 studies, 1011 participants, very low certainty). Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate with continued use. Very few studies reported data on other outcomes or comparisons and hence evidence for these is limited, with confidence intervals often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to ECs without nicotine and compared to NRT. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the size of effect, particularly when using modern EC products. Confidence intervals were for the most part wide for data on AEs, SAEs and other safety markers, though evidence indicated no difference in AEs between nicotine and non-nicotine ECs. Overall incidence of SAEs was low across all study arms. We did not detect any clear evidence of harm from nicotine EC, but longest follow-up was two years and the overall number of studies was small. The evidence is limited mainly by imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information, this review is now a living systematic review. We run searches monthly, with the review updated when relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Effects of Manufacturing Variation in Electronic Cigarette Coil Resistance and Initial Pod Mass on Coil Lifetime and Aerosol Generation

This work investigated the effects of manufacturing variations, including coil resistance and initial pod mass, on coil lifetime and aerosol generation of Vuse ALTO pods. Random samples of pods were used until failure (where e-liquid was consumed, and coil resistance increased to high value indicating a coil break). Initial coil resistance, initial pod mass, and e-liquid net mass ranged between 0.89 to 1.14 [Ω], 6.48 to 6.61 [g], and 1.88 to 2.00 [g] respectively. Coil lifetime was µ (mean) = 158, σ (standard deviation) = 21.5 puffs. Total mass of e-liquid consumed until coil failure was µ = 1.93, σ = 0.035 [g]. TPM yield per puff of all test pods for the first session (brand new pods) was µ = 0.0123, σ = 0.0003 [g]. Coil lifetime and TPM yield per puff were not correlated with either variation in initial coil resistance or variation in initial pod mass. The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. This work suggests that further work is required to investigate the effect of e-liquid composition on coil lifetime and TPM yield per puff.

A Single-Arm, Open-Label, Pilot, and Feasibility Study of a High Nicotine Strength E-Cigarette Intervention for Smoking Cessation or Reduction for People With Schizophrenia Spectrum Disorders Who Smoke Cigarettes

Introduction

An estimated 60%–90% of people with schizophrenia smoke, compared with 15%–24% of the general population, exacerbating the already high morbidity and mortality rates observed in this population.

Aims and Methods

This study aimed to assess the feasibility of using a new-generation high strength nicotine e-cigarette to modify smoking behavior in individuals with schizophrenia spectrum disorders who smoke cigarettes. A single-arm pilot study was conducted with 40 adults with schizophrenia spectrum disorders who smoked and did not intend to reduce or quit smoking. Participants were given a 12-week supply of a JUUL e-cigarette loaded with a 5% nicotine pod. The primary outcome was smoking cessation at week 12. Additional outcomes included: smoking reduction, continuous abstinence at week 24, adoption rate, adherence to the e-cigarette, feasibility, acceptability, and subjective effects.

Results

Sixteen (40%) participants quit by the end of 12 weeks. For the whole sample, we observed an overall, sustained 50% reduction in smoking or smoking abstinence in 37/40 (92.5%) of participants and an overall 75% reduction in median cigarettes per day from 25 to six was observed by the end of the 12 weeks (p < .001).

Conclusions

A high strength nicotine e-cigarette has the potential to help people with schizophrenia spectrum disorders to quit or reduce smoking. Further research with a larger sample and a comparator group is needed. The results provide useful information and direction to augment the existing body of knowledge on smoking cessation for people with schizophrenia spectrum disorders.

Implications

Considering that most people with schizophrenia spectrum disorders continue smoking, alternative and efficient interventions to reduce or prevent morbidity and mortality are urgently needed. This study showed that adults who smoke and were not motivated to quit, when provided a new-generation e-cigarette with high nicotine content, demonstrated substantially decreased cigarette consumption without causing significant side effects. Although not specifically measured in this study, nicotine absorption in new-generation devices has been shown to be consistently superior compared with the first generation of e-cigarette devices, and this may help explain the lower quit rates in studies using earlier generation devices.

Nicotine delivery and user reactions to Juul EU (20 mg/ml) compared with Juul US (59 mg/ml), cigarettes and other e-cigarette products

RATIONALE

The degree to which the EU version of Juul with 20 mg/ml nicotine (Juul EU) delivers nicotine to users is likely to determine its treatment potential.

OBJECTIVES

To compare the pharmacokinetic profile and user ratings of Juul EU, Juul US (59 mg/ml nicotine), cigarettes and other e-cigarette (EC) products.

METHODS

In a within-subjects crossover design, 18 vapers used, at separate sessions, their own brand cigarette (OBC), Juul US and Juul EU for 5 min ad libitum, after overnight abstinence. Seven of the participants also tested eight other EC previously. Blood samples were taken at baseline and 2, 4, 6, 8, 10 and 30 min after initiating product use. Products were rated on a range of characteristics.

RESULTS

Juul EU delivered less nicotine than OBC (t(13) = -4.64 p < .001) and than Juul US (t(13) = -6.40, p < .001): AUC0 ≥ 30 77.3, 324.8 and 355.9, respectively. Maximum nicotine concentration (Cmax) was also much lower for Juul EU than Juul US (z = -3.59, p < .001): Cmax 3.8 ng/ml vs 21.1 ng/ml, respectively. Juul EU was perceived to relieve urges to smoke less than Juul US (z = -2.29, p = .022) and to provide less nicotine (z = -2.57. p = 0.010). Juul EU delivered less nicotine than refillable EC (Cmax: t(6) = 3.02, p = 0.023; AUC0 ≥ 30: z = -2.20, p = 0.028) and also less than cig-a-like EC, though the difference did not reach significance (Cmax: t(6) = 2.49, p = 0.047; AUC0 ≥ 30: z = -1.99, p = 0.046). Subjective ratings of Juul EU and other EC products were similar.

CONCLUSIONS

Juul EU delivers much less nicotine to users than Juul US, and also less than refillable EC products. It may thus have more limited potential to help smokers quit.

An Open-Label, Randomized, Controlled, Crossover Study to Assess Nicotine Pharmacokinetics and Subjective Effects of the JUUL System with Three Nicotine Concentrations Relative to Combustible Cigarettes in Adult Smokers

Introduction

This randomized, open-label, crossover clinical study evaluated nicotine pharmacokinetics (PK) and subjective effects of the JUUL System (JS; Juul Labs, Inc.) with three nicotine concentrations compared to the usual brand (UB) cigarettes in 24 adult smokers.

Methods

At five study visits, subjects used either the JS in 59 mg/mL, JS 18 mg/mL (two visits), and JS 9 mg/mL (all tobacco-flavored) or smoked their UB cigarette first during a controlled puffing sequence (CPS) and then ad libitum (5 min) use sessions. Blood samples were taken at specified timepoints for 60 min in each session. The modified Product Evaluation Scale assessed subjective effects 30-min post-use in the CPS session.

Results

Maximum plasma nicotine concentration (C_max-BL), total nicotine exposure (AUC_0-60-BL), and rate of plasma nicotine rise were significantly lower for all JS products compared to subjects' UB cigarette in CPS and ad libitum use sessions. In both use sessions these PK parameters were significantly higher for JS 59 mg/mL compared to 18 and 9 mg/mL. Subjective measures of cigarette craving relief and “Enough Nicotine” for JS 59 mg/mL did not differ significantly from UB cigarettes, but JS 18 and 9 mg/mL were rated significantly lower than JS 59 mg/mL and UB cigarettes.

Conclusions

Nicotine exposure and subjective relief were directly related to JS nicotine concentration: higher nicotine concentrations gave rise to significantly greater plasma nicotine levels and relief from craving. Heavier and more dependent smokers may require the greater nicotine delivery of JS 59 mg/mL to successfully transition away from cigarettes.

Implications

It has been suggested that electronic nicotine delivery systems (ENDS) and other alternative nicotine delivery products that more closely mimic the nicotine pharmacokinetics (PK) of cigarettes may facilitate smokers transitioning away from cigarettes. We examined nicotine PK and subjective effects of JUUL System (JS) ENDS with three nicotine concentrations (59, 18 and 9 mg/mL) compared to combustible cigarettes. Nicotine delivery from JS ENDS was nicotine concentration dependent, with higher nicotine concentrations giving rise to higher nicotine exposure. These findings suggest that heavier and more dependent smokers may require ENDS with nicotine concentrations greater than 20 mg/mL to successfully transition away from cigarettes.

Electronic cigarettes for smoking cessation

BACKGROUND

Electronic cigarettes (ECs) are handheld electronic vaping devices which produce an aerosol formed by heating an e-liquid. People who smoke report using ECs to stop or reduce smoking, but some organisations, advocacy groups and policymakers have discouraged this, citing lack of evidence of efficacy and safety. People who smoke, healthcare providers and regulators want to know if ECs can help people quit and if they are safe to use for this purpose. This review is an update of a review first published in 2014.

OBJECTIVES

To evaluate the effect and safety of using electronic cigarettes (ECs) to help people who smoke achieve long-term smoking abstinence.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group's Specialized Register, the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PsycINFO for relevant records to January 2020, together with reference-checking and contact with study authors.

SELECTION CRITERIA

We included randomized controlled trials (RCTs) and randomized cross-over trials in which people who smoke were randomized to an EC or control condition. We also included uncontrolled intervention studies in which all participants received an EC intervention. To be included, studies had to report abstinence from cigarettes at six months or longer and/or data on adverse events (AEs) or other markers of safety at one week or longer.

DATA COLLECTION AND ANALYSIS

We followed standard Cochrane methods for screening and data extraction. Our primary outcome measures were abstinence from smoking after at least six months follow-up, AEs, and serious adverse events (SAEs). Secondary outcomes included changes in carbon monoxide, blood pressure, heart rate, blood oxygen saturation, lung function, and levels of known carcinogens/toxicants. We used a fixed-effect Mantel-Haenszel model to calculate the risk ratio (RR) with a 95% confidence interval (CI) for dichotomous outcomes. For continuous outcomes, we calculated mean differences. Where appropriate, we pooled data from these studies in meta-analyses.

MAIN RESULTS

We include 50 completed studies, representing 12,430 participants, of which 26 are RCTs. Thirty-five of the 50 included studies are new to this review update. Of the included studies, we rated four (all which contribute to our main comparisons) at low risk of bias overall, 37 at high risk overall (including the 24 non-randomized studies), and the remainder at unclear risk. There was moderate-certainty evidence, limited by imprecision, that quit rates were higher in people randomized to nicotine EC than in those randomized to nicotine replacement therapy (NRT) (risk ratio (RR) 1.69, 95% confidence interval (CI) 1.25 to 2.27; I2 = 0%; 3 studies, 1498 participants). In absolute terms, this might translate to an additional four successful quitters per 100 (95% CI 2 to 8). There was low-certainty evidence (limited by very serious imprecision) of no difference in the rate of adverse events (AEs) (RR 0.98, 95% CI 0.80 to 1.19; I2 = 0%; 2 studies, 485 participants). SAEs occurred rarely, with no evidence that their frequency differed between nicotine EC and NRT, but very serious imprecision led to low certainty in this finding (RR 1.37, 95% CI 0.77 to 2.41: I2 = n/a; 2 studies, 727 participants). There was moderate-certainty evidence, again limited by imprecision, that quit rates were higher in people randomized to nicotine EC than to non-nicotine EC (RR 1.71, 95% CI 1.00 to 2.92; I2 = 0%; 3 studies, 802 participants). In absolute terms, this might again lead to an additional four successful quitters per 100 (95% CI 0 to 12). These trials used EC with relatively low nicotine delivery. There was low-certainty evidence, limited by very serious imprecision, that there was no difference in the rate of AEs between these groups (RR 1.00, 95% CI 0.73 to 1.36; I2 = 0%; 2 studies, 346 participants). There was insufficient evidence to determine whether rates of SAEs differed between groups, due to very serious imprecision (RR 0.25, 95% CI 0.03 to 2.19; I2 = n/a; 4 studies, 494 participants). Compared to behavioural support only/no support, quit rates were higher for participants randomized to nicotine EC (RR 2.50, 95% CI 1.24 to 5.04; I2 = 0%; 4 studies, 2312 participants). In absolute terms this represents an increase of six per 100 (95% CI 1 to 14). However, this finding was very low-certainty, due to issues with imprecision and risk of bias. There was no evidence that the rate of SAEs varied, but some evidence that non-serious AEs were more common in people randomized to nicotine EC (AEs: RR 1.17, 95% CI 1.04 to 1.31; I2 = 28%; 3 studies, 516 participants; SAEs: RR 1.33, 95% CI 0.25 to 6.96; I2 = 17%; 5 studies, 842 participants). Data from non-randomized studies were consistent with RCT data. The most commonly reported AEs were throat/mouth irritation, headache, cough, and nausea, which tended to dissipate over time with continued use. Very few studies reported data on other outcomes or comparisons and hence evidence for these is limited, with confidence intervals often encompassing clinically significant harm and benefit.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that ECs with nicotine increase quit rates compared to ECs without nicotine and compared to NRT. Evidence comparing nicotine EC with usual care/no treatment also suggests benefit, but is less certain. More studies are needed to confirm the degree of effect, particularly when using modern EC products. Confidence intervals were wide for data on AEs, SAEs and other safety markers. Overall incidence of SAEs was low across all study arms. We did not detect any clear evidence of harm from nicotine EC, but longest follow-up was two years and the overall number of studies was small. The main limitation of the evidence base remains imprecision due to the small number of RCTs, often with low event rates. Further RCTs are underway. To ensure the review continues to provide up-to-date information for decision-makers, this review is now a living systematic review. We will run searches monthly from December 2020, with the review updated as relevant new evidence becomes available. Please refer to the Cochrane Database of Systematic Reviews for the review's current status.

Hot Wires and Film Boiling: Another Look at Carbonyl Formation in Electronic Cigarettes

Electronic cigarettes (ECIGs) are a class of tobacco products that emit a nicotine-containing aerosol by heating and vaporizing a liquid. Apart from initiating nicotine addiction in nonsmokers, a persistent concern about these products is that their emissions often include high levels of carbonyl species, toxicants thought to cause most noncancer pulmonary diseases in smokers. This study examined whether the phenomenon of film boiling can account for observations of high carbonyl emissions under certain operating conditions and, if so, whether film boiling theory can be invoked to predict conditions where high carbonyl emissions are likely. We measured the critical heat flux for several common heating materials and liquids and carbonyl emissions for several ECIG types while varying the power. We found that emissions rise drastically whenever the power exceeds the value corresponding to the critical heat flux. While limiting the heat flux to below this threshold can greatly reduce carbonyl exposure, ECIG manufacturer operating instructions often exceed it. Product regulations that limit heat flux may reduce the public health burden of electronic cigarette use.