Improving on estimates of the potential relative harm to health from using modern ENDS (vaping) compared to tobacco smoking

Interactions between ENDS and cigarette use: evidence from a 2022 national telephone survey in South Africa

INTRODUCTION

Electronic nicotine delivery systems (ENDS) may serve as a cessation tool for people who smoke cigarettes. However, for people who do not smoke, ENDS may be a gateway to nicotine addiction and cigarette use. This paper aims to quantify these behaviours in South Africa.

METHODS

We analysed a nationally representative telephone survey of 21 263 South Africans living in urban areas. For those respondents who had used both products (N=771), we developed a typology that describes the sequence in which cigarette and ENDS initiation occurred. 'On-rampers' describe people who used ENDS first and later initiated cigarette smoking. 'Off-rampers' describe people who used cigarettes first, took up ENDS and later quit cigarettes while still using ENDS. 'Failed off-rampers' describe people who started using ENDS while smoking cigarettes but later quit using ENDS. 'Continuing dual consumers' describe people still using both products at the time of the interview.

RESULTS

Of the overall sample (N=21 263), 1.7% used or had used ENDS but had no history of using cigarettes. Of dual consumers (N=771), 8.8% were classified as 'on-rampers', 13.9% as 'off-rampers', 20.9% as 'failed off-rampers' and 56.4% as 'continuing dual consumers'. Roughly half of those classified as off-rampers, failed off-rampers or continuing dual consumers stated that they started using ENDS to help them quit cigarettes.

CONCLUSIONS

The typology reveals a multifaceted relationship between ENDS and cigarette use in South Africa. Policy interventions should aim to minimise on-ramping and maximise off-ramping. Given the high prevalence of continued dual use and failed off-ramping, targeted cessation support should be provided for people who use ENDS and are trying to quit cigarettes.

Characteristics of second-hand exposure to aerosols from e-cigarettes: A literature review since 2010

In recent years, the use of electronic vaping products (also named e-cigarettes) has increased due to their appealing flavors and nicotine delivery without the combustion of tobacco. Although the hazardous substances emitted by e-cigarettes are largely found to be much lower than combustible cigarettes, second-hand exposure to e-cigarette aerosols is not completely benign for bystanders. This work reviewed and synthesized findings on the second-hand exposure of aerosols from e-cigarettes and compared the results with those of the combustible cigarettes. In this review, different results were integrated based upon sampling locations such as residences, vehicles, offices, public places, and experimental exposure chambers. In addition, the factors that influence the second-hand exposure levels were identified by objectively reviewing and integrating the impacts of combustible cigarettes and e-cigarettes on the environment. It is a challenge to compare the literature data directly to assess the effect of smoking/vaping on the indoor environment. The room volume, indoor air exchange rate, puffing duration, and puffing numbers should be considered, which are important factors in determining the degree of pollution. Therefore, it is necessary to calculate the "emission rate" to normalize the concentration of pollutants emitted under various experimental conditions and make the results comparable. This review aims to increase the awareness regarding the harmful effects of the second-hand exposure to aerosols coming from the use of cigarettes and e-cigarettes, identify knowledge gaps, and provide a scientific basis for future policy interventions with regard to the regulation of smoking and vaping.

Forecasting vaping health risks through neural network model prediction of flavour pyrolysis reactions

Vaping involves the heating of chemical solutions (e-liquids) to high temperatures prior to lung inhalation. A risk exists that these chemicals undergo thermal decomposition to new chemical entities, the composition and health implications of which are largely unknown. To address this concern, a graph-convolutional neural network (NN) model was used to predict pyrolysis reactivity of 180 e-liquid chemical flavours. The output of this supervised machine learning approach was a dataset of probability ranked pyrolysis transformations and their associated 7307 products. To refine this dataset, the molecular weight of each NN predicted product was automatically correlated with experimental mass spectrometry (MS) fragmentation data for each flavour chemical. This blending of deep learning methods with experimental MS data identified 1169 molecular weight matches that prioritized these compounds for further analysis. The average number of discrete matches per flavour between NN predictions and MS fragmentation was 6.4 with 92.8% of flavours having at least one match. Globally harmonized system classifications for NN/MS matches were extracted from PubChem, revealing that 127 acute toxic, 153 health hazard and 225 irritant classifications were predicted. This approach may reveal the longer-term health risks of vaping in advance of clinical diseases emerging in the general population.

Does vaping affect the taste and smell perception? An exploratory study with New Zealand young adults

OBJECTIVE

The study aimed to assess potential effects of vaping on individual taste and smell perception in a sample of young adult New Zealanders.

DESIGN

This cross-sectional study measured taste and smell perception using intensity and hedonic ratings to two olfactory (i.e., vanillin, methional) and two gustatory stimuli (i.e., sucrose, monosodium glutamate), representing sweet and savoury flavours. Detection sensitivities to sucrose and vanillin were also assessed using a forced choice detection paradigm aligned with the signal detection framework. MANCOVAs were employed to compare sensory perception between groups based on vaping use frequency. Additional regression analyses were conducted to identify potential predictors of intensity and hedonic sensory ratings.

SETTING

Participants were recruited from the University of Otago student population and surrounding neighbourhoods of Dunedin, New Zealand in 2023.

PARTICIPANTS

The study included 213 university students (98 vapers and 115 non-vapers) RESULTS: We found a significant difference in hedonic ratings for vanillin, indicating a stronger preference among non-vapers. However, no other differences between the two groups were significant. Notably, the use of tobacco and mint flavours were emerged as significant predictors for hedonic responses to the savoury smell and sweet taste stimulus, respectively. No significant differences were observed between groups in the ability to detect weak stimuli.

CONCLUSIONS

Our findings suggest that vape use, particularly with specific flavours, may be associated with alterations in hedonic responses to smells. This finding may have potential implications for how vaping affects on food preferences and dietary choices.

Population-Based Disease Odds for E-Cigarettes and Dual Use versus Cigarettes

Disease Odds for E-Cigarettes and Dual Use versus CigarettesE-cigarettes have been promoted as less harmful than cigarettes. In this meta-analysis, Glantz et al. show that for some diseases, e-cigarette disease risks were similar to cigarettes, and for others e-cigarettes were nearly as risky as cigarettes. The risks associated with dual use were higher than those for smoking alone.

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.

E-cigarette attitudes and behaviours amongst 15-30-year-olds in the UK

BACKGROUND

The use of e-cigarettes has been rising in the UK, particularly by young people. This study investigated behaviours, attitudes and beliefs about e-cigarettes amongst 15-30-year-olds in the UK.

METHODS

An online survey was administered to a sample of 1009 15-30-year-olds in the UK.

RESULTS

About one in five participants currently used e-cigarettes at least monthly, with 1 in 10 using them daily. Amongst those using e-cigarettes at least monthly, 90% had used e-cigarettes containing nicotine. E-cigarettes were mainly obtained from vape shops and used at home. Having friends who used e-cigarettes and using them to help quit/reduce smoking were the most common reasons for vaping. About half of participants had been exposed to e-cigarette advertising, especially online, and warning labels on e-cigarettes. Most participants agreed that e-cigarettes are addictive (75%), help people quitting smoking (64%) and are bad for health (63%). Previous or current tobacco smokers were 9 and 22 times more likely to use e-cigarettes than never smokers, respectively. Perceiving e-cigarettes as harmful was associated with a 40% lower likelihood of use.

CONCLUSION

Raising awareness on the uncertain long-term consequences of vaping and regulation of marketing and sales are crucial to protect young people in the UK.

Comparative risk perceptions of switching to JUUL vs. continued smoking and subsequent switching away from cigarettes: a longitudinal observational study

BACKGROUND

Evidence indicates that electronic nicotine delivery systems (ENDS) pose lower risk than cigarettes; however, many smokers harbor misperceptions that ENDS are equally or more harmful, possibly deterring them from switching. This study examines whether comparative risk perceptions of JUUL vs. smoking are associated with subsequent switching, among smokers who recently purchased JUUL.

METHODS

N = 16,996 current established smokers who recently purchased a JUUL Starter Kit were followed 6 times over 12 months. Comparative risk perceptions were assessed using both direct and indirect measures (i.e., contrasting JUUL and smoking directly in questions, and deriving from separate absolute scales). Repeated-measures logistic regression examined switching across follow-up (no smoking in past 30 days) as a function of baseline risk perceptions, adjusting for demographics and baseline smoking behavior.

RESULTS

Perceiving JUUL as less harmful than smoking was associated with higher switching rates, using both direct (e.g., adjusted odds ratio [AOR] = 1.48 for "JUUL much less" vs. "more/much more harmful") and indirect (AOR = 1.07, for each 10-unit increase in fraction; AOR = 1.51 for highest (6-100) vs. lowest (0 to < 1) fraction categories) comparative risk measures (all p < 0.0001). Among the subset smoking 10 + cigarettes per day, associations between risk perceptions and switching were more pronounced (AOR = 2.51 for "JUUL much less" vs. "more/much more harmful"; AOR = 1.81 for 6-100 vs. 0 to < 1 fraction, both p < 0.0001).

CONCLUSIONS

Smokers who perceive JUUL as less harmful than cigarettes have higher odds of switching. Future research should examine whether messaging which aligns comparative risk perceptions with current evidence can facilitate switching, especially among heavier smokers.

Effects of vaping on uptake and cessation of smoking: Longitudinal analysis in Aotearoa New Zealand adults

INTRODUCTION

Globally, the use of vapes, or e-cigarettes, is increasing. While vaping is less harmful than smoking and may help smokers to quit, there is also the possibility that vaping may lead to smoking. The current study aimed to determine the prevalence of vaping and smoking in Aotearoa New Zealand and explore longitudinal pathways between smoking status and vape use.

METHOD

Data related to smoking and vaping status was analysed from Times 10, 11 and 12 across 2018-2020 of the New Zealand Attitudes and Values study, a large, representative, multi-wave study of adults living in New Zealand. Weighted descriptive analyses were used to determine prevalence rates of vaping and smoking and a generalised linear modelling approach was used to examine the likelihood of changing to, or taking up, the other behaviour in the transition between time points.

RESULTS

Broadly, the prevalence of smoking was found to be decreasing over time while the prevalence of vaping was increasing. Despite these general trends, no differences were observed in the likelihood of transitioning from smoking to vaping or from vaping to smoking, indicating that either pathway was equally as likely.

DISCUSSION AND CONCLUSIONS

The current findings demonstrate that vaping appeared to be just as likely to have a gateway effect to smoking as it was to have a cessation effect. This highlights the need for greater consideration regarding vaping-related policies and restrictions.

Biomarkers of exposure and potential harm in exclusive users of electronic cigarettes and current, former, and never smokers

Electronic cigarette (EC) aerosol emissions generally contain fewer and lower concentrations of harmful and potentially harmful constituents, compared with cigarette smoke. Further studies are needed to establish whether decreased emissions translate to reduced health risks for EC users. In a cross-sectional study, biomarkers of exposure (BoE) to certain tobacco smoke toxicants and biomarkers of potential harm (BoPH), associated with biological processes linked to the potential development of smoking-related diseases and oxidative stress, were assessed in solus Vuse ECs users and current, former, and never smokers. In total, 213 participants were enrolled, and smoking status was confirmed by urinary cotinine, exhaled carbon monoxide, and N-(2-cyanoethyl)valine levels (EC users and former smokers only). During confinement participants used their usual product (EC or cigarette) as normal and BoE and BoPHs were assessed via blood, 24-h urine, and physiological assessment. Significantly lower levels of all urinary BoE; MHBMA, HMPMA, 3-HPMA, NNN, 3-OH-B[a]P, S-PMA, NNAL (all p < 0.0001), and TNeq (p = 0.0074) were observed in EC users when compared with smokers. Moreover, significantly lower levels were observed in EC users for 3 of the 7 BoPH measured, carboxyhaemoglobin (p < 0.0001), soluble intercellular adhesion molecule-1 (p = 0.0028), and 11-dehydrothromboxane B2 (p = 0.0012), when compared with smokers. As compared with smokers, solus Vuse EC users have significantly lower exposure to tobacco toxicants for the BoE, and 3 BoPH measured. These results add to the weight of evidence supporting EC as part of a tobacco harm reduction strategy.

Marketing claims on the websites of leading e-cigarette brands in England

INTRODUCTION

Exposure to electronic cigarette (EC) marketing is associated with EC use, particularly among youth. In England, the Tobacco and Related Products Regulations and Committee of Advertising Practice (CAP) regulate EC marketing to reduce appeal to youth; however, there are little published data on EC marketing claims used online. This study therefore provides an overview of marketing claims present on the websites of EC brands popular in England.

METHODS

From January to February 2022, a content analysis of 10 of England's most popular EC brand websites was conducted, including violation of CAP codes.

RESULTS

Of the 10 websites, all presented ECs as an alternative to smoking, 8 as a smoking cessation aid and 6 as less harmful than smoking. Four websites presented ECs as risk-free. All mentioned product quality, modernity, convenience, sensory experiences and vendor promotions. Nine featured claims about flavours, colours, customisability and nicotine salts. Seven featured claims concerning social benefits, personal identity, sustainability, secondhand smoke and nicotine strength. Six featured claims about fire safety. Some claimed ECs are cheaper than tobacco (n=5), cited health professionals (n=4) or featured collaborations with brands/icons (n=4). All were assessed by the research team to violate one or more CAP code(s) by featuring medicinal claims (n=8), contents which may appeal to non-smokers (n=7), associations with youth culture (n=6), depictions of youth using ECs (n=6) or media targeting youth (n=5).

CONCLUSION

Among 10 top EC brand websites in England, marketing elements that might appeal to youth were commonly identified and CAP code compliance was low.

Predicting the long-term effects of electronic cigarette use on population health: a systematic review of modelling studies

OBJECTIVE

To systematically review and synthesise the findings of modelling studies on the population impacts of e-cigarette use and to identify potential gaps requiring future investigation.

DATA SOURCE AND STUDY SELECTION

Four databases were searched for modelling studies of e-cigarette use on population health published between 2010 and 2023. A total of 32 studies were included.

DATA EXTRACTION

Data on study characteristics, model attributes and estimates of population impacts including health outcomes and smoking prevalence were extracted from each article. The findings were synthesised narratively.

DATA SYNTHESIS

The introduction of e-cigarettes was predicted to lead to decreased smoking-related mortality, increased quality-adjusted life-years and reduced health system costs in 29 studies. Seventeen studies predicted a lower prevalence of cigarette smoking. Models that predicted negative population impacts assumed very high e-cigarette initiation rates among non-smokers and that e-cigarette use would discourage smoking cessation by a large margin. The majority of the studies were based on US population data and few studies included factors other than smoking status, such as jurisdictional tobacco control policies or social influence.

CONCLUSIONS

A population increase in e-cigarette use may result in lower smoking prevalence and reduced burden of disease in the long run, especially if their use can be restricted to assisting smoking cessation. Given the assumption-dependent nature of modelling outcomes, future modelling studies should consider incorporating different policy options in their projection exercises, using shorter time horizons and expanding their modelling to low-income and middle-income countries where smoking rates remain relatively high.

Development and implementation of the ECHO model in a school setting to address youth electronic cigarette use in Kansas: A protocol

Introduction

Schools remain at the frontlines of addressing issues, such as e-cigarette use, that impact students. Despite e-cigarette use remaining a significant public health concern in the U.S., schools have limited resources (e.g., staff, capacity, programming) to address it, especially in rural and frontier areas. This ECHO Pilot Project aimed to build capacity and equip schools and school staff in the state of Kansas to address high rates of youth e-cigarette use by providing prevention support and information on best practices for e-cigarette cessation.

Methods and analysis

The pilot used the established Project ECHO model to disseminate evidence-based strategies for e-cigarette prevention and cessation among youth to schools across Kansas. The pilot selected 20 interdisciplinary school teams representing both rural and urban middle and high schools across the state to participate in seven ECHO sessions. ECHO sessions proceeded throughout Fall 2021, with the final session in Spring 2022. School participants completed pre-post surveys as well as component-specific surveys following each ECHO session. In addition, each school team created an individualized action plan to comprehensively address e-cigarette use at their school based on the information provided throughout the ECHO. Survey data, school tobacco/nicotine policies, and action plans will be analyzed to assess process and final outcomes.

Discussion

If successful, this pilot will demonstrate that the ECHO model is an effective platform for building school staff knowledge and skills to implement evidence-based strategies in both urban and rural settings. It is anticipated that the pilot will build capacity and equip schools and school staff to address high rates of youth e-cigarette use by providing support for school-based prevention programs and referrals for e-cigarette cessation which will lessen the burden of nicotine-related problems in Kansas schools and communities. Finally, the pilot will provide evidence that the ECHO model can be successfully and equitably applied in a school setting and may be a viable method for addressing other public health-related issues faced by schools.

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.

E-Cigarettes Reexamined: Product Toxicity

The introduction of e-cigarettes, or electronic nicotine delivery systems (ENDS), has been accompanied by controversy regarding their safety and effectiveness as a cessation aid and by an explosion in their use by youth. Their use does not involve the combustion of tobacco and the creation of harmful combustion products; they have been seen as a "harm reduction" tool that may be of assistance in promoting smoking cessation. Recognition that ENDS can deliver an array of chemicals and materials with known adverse consequences has spurred more careful examination of these products. Nicotine, nitrosamines, carbonyl compounds, heavy metals, free radicals, reactive oxygen species, particulate matter, and "emerging chemicals of concern" are among the constituents of the heated chemical aerosol that is inhaled when ENDS are used. They raise concerns for cardiovascular and respiratory health that merit the attention of clinicians and regulatory agencies. Frequently cited concerns include evidence of disordered respiratory function, altered hemodynamics, endothelial dysfunction, vascular reactivity, and enhanced thrombogenesis. The absence of evidence of the consequences of their long-term use is of additional concern. Their effectiveness as cessation aids and beneficial impact on health outcomes continue to be examined. It is important to ensure that their production and availability are thoughtfully regulated to optimise their safety and permit their use as harm reduction devices and potentially as smoking-cessation aids. It is equally vital to effectively prevent them from becoming ubiquitous consumer products with the potential to rapidly induce nicotine addiction among large numbers of youth. Clinicians should understand the nature of these products and the implications of their use.

Transfer of Metals to the Aerosol Generated by an Electronic Cigarette: Influence of Number of Puffs and Power

Electronic cigarettes (e-cigarettes) are increasing in popularity despite uncertainties about their health hazards. Literature studies have shown that e-cigarettes may be a source of toxic heavy metal exposure to the user, but the mechanism by which metals are transferred from the e-cigarette parts into the aerosol plume that is inhaled by the user is poorly understood. The goal of this study was to quantify the potentially harmful heavy metals chromium, nickel, copper, and lead systematically during the simulated use of a mod-type e-cigarette in order to better understand the mechanism of metal transfer from the e-cigarette parts into the aerosol plume and into the liquid in the storage tank. Aerosol was collected and aliquots of the remaining liquid in the storage tank were collected from 0 to 40 puffs in 10 puff increments and analyzed with atomic absorption spectroscopy. It was found that the concentration of metals increased in both the aerosol and tank liquid the more times the e-cigarette was puffed, but at varying rates for each element and depending on the power applied to the heating coil. For copper, lead, and nickel, the concentrations of metals in the aerosol and tank increased with increasing power but for chromium, the concentration varied with power. Additionally, it was observed that chromium and nickel concentrations were greater in the aerosol than in tank liquid, consistent with the direct transfer of those metals to the aerosol from heating of the nichrome coil element used in this study. For copper and lead, the concentrations were similar or greater in the tank compared to the aerosol, consistent with transfer first into the storage tank liquid, followed by vaporization into the aerosol.