Nicotine Absorption Profile Among Regular Users of a Pod-Based Electronic Nicotine Delivery System

Nicotine Delivery of a Menthol-Flavored Heat-not-Burn Tobacco Product During Directed Use

INTRODUCTION

IQOS was authorized by the U.S. Food and Drug Administration (FDA) as a modified-risk tobacco product. We conducted a pharmacokinetic study evaluating the nicotine delivery and subjective effects of IQOS use among current menthol cigarette smokers to better understand if IQOS is an acceptable cigarette alternative in light of the proposed menthol cigarette ban.

AIMS AND METHODS

Participants were adult smokers of >4 menthol cigarettes per day. After 14-hour nicotine abstinence, participants were provided an IQOS device and menthol heatstick to puff every 20 seconds for a total of 14 puffs. Blood samples were collected at baseline and during active use to calculate nicotine boost from baseline to peak concentration. Nicotine withdrawal symptoms were collected before and after IQOS use. In addition, a modified Product Evaluation Scale for IQOS was collected after use.

RESULTS

Participants (n = 8) were a mean age of 43.9 years, 63% were female, 88% identified as White, and they smoked a mean of 17.1 menthol cigarettes per day. After IQOS use, the mean nicotine boost obtained was 15.96 ng/mL (SD = 6.91) (range 9.31 to 30.55 ng/mL). Most (75%) participants reported enjoying use of the product "a lot" or greater and more than half (62.5%) reported reduced cigarette cravings. Most participants reported no side effects after use; however, two experienced dry mouth, three experienced dizziness, one experienced throat irritation, and one experienced headache.

CONCLUSION

We found that directed use (14 puffs) of menthol IQOS delivered a mean nicotine boost of 15.96 ng/mL which reduced craving for a cigarette. The majority of participants enjoyed use of IQOS and reported mild side effects.

IMPLICATIONS

Menthol IQOS delivered a sufficient dose of nicotine perceived as satisfying by menthol cigarette smokers and it reduced craving with mild side effects. Menthol IQOS has potential to serve as a less harmful alternative for menthol cigarette smokers. The availability of modified risk products like IQOS should be considered by FDA's Comprehensive Plan for Tobacco and Nicotine Regulation.

Relationship Between Tobacco Product Use and Health-Related Quality of Life Among Individuals With COPD in Waves 1-5 (2013-2019) of the Population Assessment of Tobacco and Health Study

Introduction

We examined the association between tobacco product use and health-related quality of life (HRQoL) among individuals with chronic obstructive pulmonary disease (COPD) in Waves 1-5 of the Population Assessment of Tobacco and Health (PATH) Study.

Methods

Adults ≥40 years with an ever COPD diagnosis were included in cross-sectional (Wave 5) and longitudinal (Waves 1 to 5) analyses. Tobacco use included 13 mutually exclusive categories of past 30-day (P30D) single use and polyuse with P30D exclusive cigarette use and ≥5-year cigarette cessation as reference groups. Multivariable linear regression and generalized estimating equations (GEE) were used to examine the association between tobacco use and HRQoL as measured by the Patient-Reported Outcomes Measurement Information System (PROMIS) Global-10 questionnaire.

Results

Of 1670 adults, 79.4% ever used cigarettes; mean (standard error [SE]) pack years was 30.9 (1.1). In cross-sectional analysis, P30D exclusive cigarette use, and e-cigarette/cigarette dual use were associated with worse HRQoL compared to ≥5-year cigarette cessation. Compared to P30D exclusive cigarette use, never tobacco use and ≥5-year cigarette cessation were associated with better HRQoL, while e-cigarette/cigarette dual use had worse HRQoL. Longitudinally (n=686), e-cigarette/cigarette dual use was associated with worsening HRQoL compared to both reference groups. Only never tobacco use was associated with higher HRQoL over time compared to P30D exclusive cigarette use.

Conclusions

E-cigarette/cigarette dual use was associated with worse HRQoL compared to ≥5-year cigarette cessation and exclusive cigarette use. Never use and ≥5-year cigarette cessation were the only categories associated with higher HRQoL compared to exclusive cigarette use. Findings highlight the importance of complete smoking cessation for individuals with COPD.

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.

Human abuse liability assessment of e-cigarettes: Why, what and how?

Cigarette smoking is the world's leading cause of preventable death and disease. Alternative nicotine products such as e-cigarettes have tobacco harm reduction potential, by providing smokers with an alternative form of nicotine delivery but with either the reduced presence or absence of the numerous harmful chemicals found in combustible cigarette smoke. One aspect of importance in determining the potential of e-cigarettes to provide a viable alternative to combustible cigarettes for smokers is their ability to cause dependence, also known as their abuse liability. E-cigarettes with little or no abuse liability would be unlikely to be used as a substitute for cigarettes, whereas at least some degree of abuse liability is acknowledged as supportive both to aiding cigarette substitution or complete cessation and to preventing relapse. Given this link between abuse liability and substitution efficacy, human studies assessing the abuse liability of e-cigarettes are important to determine their true harm reduction potential. In this review, the concept of tobacco product abuse liability is discussed, along with the primary elements-pharmacokinetics and pharmacodynamics (subjective effects)-that need to be assessed to determine abuse liability. The review also presents a number of human abuse liability study design considerations and discusses what existing studies in the literature tell us about the abuse liability and harm reduction potential of e-cigarettes.

Developing a theoretical marketing framework to analyse JUUL and compatible e-cigarette product promotion on Instagram

BACKGROUND

E-cigarette promotion on social media coincided with the rapid growth of e-cigarette use among American youth, particularly with the increased JUUL pod vaporiser use. We examined commercial JUUL-related messages on Instagram to identify marketing appeals used to target users along the continuum of e-cigarette use; we mapped the appeals to existing theoretical marketing frameworks to better understand industry strategies.

METHODS

Hashtag-based keyword rules were used to collect JUUL-related posts from the Instagram application programming interface, 1 March-13 November 2018. Posts were classified as commercial or non-commercial. A combination of machine learning methods, keyword algorithms and human coding were used to characterise message themes in commercial posts.

RESULTS

Keyword filters captured 50 817 relevant posts and 41% were commercial. Among commercial posts, 91% contained recruitment/trial-based appeals (eg, combustible tobacco cessation; product sampling; giveaways) and 71% featured reinforcement/addiction-related appeals (eg, loyalty programmes). None of the commercial messages contained e-cigarette cessation-related appeals and less than 25% mentioned quitting combustible tobacco as a recruitment appeal.

CONCLUSIONS

Instagram posts featuring e-cigarette related marketing can increase exposure to persuasive messages encouraging e-cigarette trial and use particularly among susceptible youth. Stronger regulations are needed to prevent exposure to social media marketing among young social media users.

Part two: an unblinded, parallel, randomized study to assess nicotine pharmacokinetics of four Vuse Solo ENDS flavors in smokers

We report the findings from a randomized, parallel study designed to evaluate nicotine pharmacokinetics (PK) following 10 min of ad libitum use of electronic nicotine delivery system (ENDS) in four flavor variants. Subjects were randomized an investigational product (IP) and blood samples were collected for PK assessments during a test session. Primary endpoints were baseline-adjusted values of maximum plasma nicotine concentration (C_max) and area under the nicotine concentration-vs-time curve up to 60 min (AUC_nic0-60). Baseline-adjusted mean C_max ranged from 6.53 to 8.21 ng/mL, and mean AUC_nic0-60 ranged from 206.87 to 263.52 ng min/mL for all ENDS IPs. Results of geometric mean C_max and AUC_nic0-60 values were within 95% confidence intervals (CI) among the ENDS IP flavor variants tested.

Effects of Device Settings and E-Liquid Characteristics on Mouth-Throat Losses of Nicotine Delivered with Electronic Nicotine Delivery Systems (ENDS)

Currently it is not fully understood how the device settings and electronic liquid (e-liquid) composition, including their form of nicotine content, impact mouth and throat losses, and potentially lead to the variations in total nicotine delivery to the human lungs. An in situ size assessment method was developed for real-time measurements at the mouthpiece and outlet of a biorelevant mouth-throat to account for the dynamic nature of the aerosol. The aerosol size, temperature, and delivery through the mouth-throat replica and the exhaled aerosol between the puff intervals were measured at different wattages using various e-liquid compositions. The effects of body temperature and humidity on aerosol size and nicotine delivery were also explored to evaluate the importance of considering realistic in vivo conditions in in vitro measurements. Notably, in vitro tests with body temperature and humidity in mouth-throat model vs room conditions, resulted in larger aerosol size at the end of the throat (Dv50=5.83±0.33 μm vs 3.05±0.15 μm), significantly higher thoracic nicotine delivery (>90% vs 50-85%) potentially due to the lower exhaled amount (<10% vs 15-50%). Besides, higher VG/PG ratios resulted in significantly lower exhaled amount and higher mouth-throat nicotine deposition. One of the main outcomes of the study was finding significantly lower exhaled amount and higher thoracic nicotine delivery with nicotine salt form vs free-base. Considering body temperature and humidity also showed significant enhancement in nicotine delivery, so it is essential to account for biorelevant experimental conditions in benchtop testing.

Comparing the Effects of the EU- Versus the US-JUUL Pod in a Sample of UK Smokers: Nicotine Absorption, Satisfaction, and Other Nicotine-Related Subjective Effects

INTRODUCTION

Pod Vaping Devices (PVD) such as JUUL have become extremely popular in the United States although their uptake and use in the United Kingdom remain lower. A key difference between the United States and the United Kingdom is the nicotine strength legally permitted, typically 59 mg/mL in the United States but capped at 20 mg/mL in the United Kingdom and European Union. This may limit the ability of EU vaping devices to deliver satisfactory nicotine levels. The primary aim was to compare the EU- (18 mg/mL nicotine strength) with the U.S.-JUUL (59 mg/mL) on daily smokers' subjective experiences, craving relief, and blood nicotine levels.

AIMS AND METHODS

Double-blind, counterbalanced within-participants design with two conditions: 18 mg/mL versus 59 mg/mL. On two separate occasions, UK smokers (N =19, 10 males, 9 females) vaped ad libitum for 60 mins and provided blood samples at baseline 5, 15, 30, and 60 min. Subjective effects (incl. satisfaction) were measured at 10 and 60 min and, craving and withdrawal symptoms (WS) at baseline, 10 and 60 min.

RESULTS

Satisfaction did not differ between conditions. There was a significant interaction between Time and Nicotine concentration for Nicotine Hit (p = .045). Mean self-report of Nicotine Hit increased under the use of the 59 mg/mL from 10 to 60 min and decreased under the 18 mg/mL. Participants reported higher Throat Hits following use of the 59 mg/mL (p = .017). There were no differences in other subjective effects including craving, WS relief (ps > .05). Liquid consumption was doubled under the 18 versus the 59 mg/mL (p = .001) and nicotine boost was significantly higher in the 59 mg/mL at all time-points (p ≤ .001).

CONCLUSIONS

The results did not support our hypotheses that satisfaction, craving, and withdrawal reduction would be higher with the 59 mg/mL JUUL. This could be because of the doubling of liquid consumption in the 18 mg/mL. Whether satisfaction and craving relief persist over the longer-term outside of the lab remains to be determined.

IMPLICATIONS

In a 60-min ad-lib vaping session, the EU-JUUL was found to produce comparable satisfaction, craving- and withdrawal relief as the U.S.-JUUL in this sample of UK smokers. These findings could suggest that the higher nicotine concentrations available in PVDs in the United States are not necessary for providing satisfaction and improving craving and WS. However, this was at the expense of a considerable increase in liquid consumption indicative of compensatory puffing.

Predictors of Discontinued E-Cigarette Use at One-Year Follow-Up in a Sample of Young Adults

BACKGROUND

Currently, the research on factors associated with young adults' discontinuation of e-cigarette use behavior is limited. This study tested the predictors of self-reported e-cigarette abstinence at one-year follow-up among young adult baseline current e-cigarette users. The following variables were tested as predictors: demographics, cigarette smoking, e-cigarette use dependence, e-cigarette use duration, harm perceptions, and preferred aspects of e-cigarette use, including sensations, flavor, and device characteristics.

METHODS

Data were provided at two time-points one year apart by 435 ethnically diverse young adults (M age = 22.3, SD = 3.1; 63% women) who reported current e-cigarette use at baseline.

RESULTS

Approximately 42% of those who reported current e-cigarette use at baseline (i.e., 184 out of 435 participants) reported discontinuation of e-cigarette use at one-year follow-up. Results indicated that higher e-cigarette dependence, longer history of e-cigarette use, lower e-cigarette harm perceptions, greater preference for both menthol and sweet flavors, for open-pod-based devices, and for e-cigarette use sensations such as buzz, taste and smell of flavors, and throat hit at baseline were associated with lower likelihood of e-cigarette use discontinuation at one-year follow-up.

CONCLUSIONS

Characteristics associated with nicotine (e.g., dependence) and flavors (e.g., taste and smell) appear to drive the continuation/discontinuation of e-cigarette use among young adults. Thus, cessation strategies may need to be developed with a focus on dependence and harm perceptions related to nicotine and flavors. Furthermore, better regulating open-pod-based devices and sweet-menthol flavors may help e-cigarette use prevention.

Changes in Nicotine Dependence Among Smokers Using Electronic Cigarettes to Reduce Cigarette Smoking in a Randomized Controlled Trial

INTRODUCTION

How nicotine dependence will be affected when current smokers initiate electronic cigarette (e-cigarette) use to reduce cigarette smoking is unknown. This study evaluated cigarette, e-cigarette, and total nicotine dependence more than 6 months among smokers reducing cigarette consumption by replacing with e-cigarettes.

AIMS AND METHODS

Adult cigarette smokers were randomized to one of four conditions (36 mg/ml e-cigarette, 8 mg/ml e-cigarette, 0 mg/ml e-cigarette, or cigarette-substitute [CS] [provided at no cost]) and instructed to reduce their cigarette smoking by 75% at 1 month. Participants completed follow-up at 1, 3, and 6 months. The Penn State Nicotine Dependence Index (PSNDI) measured dependence on cigarettes (PSCDI) and e-cigarettes (PSECDI). Urine cotinine measured total nicotine exposure. Linear mixed effects models for each outcome were conducted and included interaction terms between visit and condition.

RESULTS

Participants (n = 520) were 58.8% female, 67.3% White, and 48.0 years old. At baseline, the median number of cigarettes smoked per day was 17.3 and the mean PSCDI score was 13.4, with no significant differences between conditions. Participants in the e-cigarette conditions reported significantly lower PSCDI scores, compared with baseline, and with the CS condition at all follow-up visits. Those in the 36 mg/ml e-cigarette condition reported greater PSECDI scores at 6 months, compared with baseline and the 0 mg/ml and 8 mg/ml conditions. At all follow-up visits, there were no differences in total nicotine exposure compared to baseline, nor between any conditions.

CONCLUSIONS

E-cigarette use was associated with reduced cigarette dependence, compared to the CS, without significant increases in total nicotine exposure.

IMPLICATIONS

Initiation of electronic cigarette use while continuing to smoke could potentially increase nicotine dependence. In this randomized trial aimed at helping smokers to reduce their cigarette intake, we found that use of an e-cigarette was associated with a reduction in cigarette dependence and an increase in e-cigarette dependence (in the condition with the highest nicotine concentration only), with no long term increase in total nicotine dependence or nicotine exposure.

Predictors of electronic cigarette dependence among non-smoking electronic cigarette users: User behavior and device characteristics

INTRODUCTION

ECIGs differ in their ability to deliver nicotine to the user and, consequently, they may differ in their ability to produce dependence. This study examined individual device characteristics, device type, and user behaviors as predictors of ECIG dependence in a sample of never-smoking ECIG users.

METHODS

Participants (N = 134) completed an online survey that assessed demographics, ECIG use behavior, and ECIG dependence as measured via the Penn State Electronic Nicotine Dependence Index (PSECDI) and E-cigarette Dependence Scale (EDS-4). Participants uploaded a picture of their personal ECIG device/liquid, which was coded by raters to identify product features. Multivariable linear regressions examined device characteristics (e.g., adjustable power, nicotine concentration) and device type (e.g., vape pen, mod, pod, modern disposable) as predictors of dependence controlling for demographics and user behaviors (e.g., ECIG use duration and frequency, other tobacco use).

RESULTS

Longer durations of ECIG use and more use days/week were associated significantly with higher PSECDI (β's = 0.91 and 1.90, respectively; p's < 0.01) and EDS-4 scores (β's = 0.16 and 0.28, respectively; p's < 0.01). Higher nicotine concentrations were associated with higher PSECDI scores only (β = 0.07, p =.011). Dependence scores did not differ as a function of ECIG device types after controlling for covariates.

CONCLUSIONS

ECIG dependence was observed among the never-smoking ECIG users in this sample, regardless of their ECIG device/liquid features. Findings suggest that regulatory efforts aimed at reducing the dependence potential of ECIGs in never smokers should focus on overall nicotine emissions rather than product features.

Pod-based e-liquids impair human vascular endothelial cell function

Pod-based electronic (e-) cigarettes more efficiently deliver nicotine using a protonated formulation. The cardiovascular effects associated with these devices are poorly understood. We evaluated whether pod-based e-liquids and their individual components impair endothelial cell function. We isolated endothelial cells from people who are pod users (n = 10), tobacco never users (n = 7), and combustible cigarette users (n = 6). After a structured use, pod users had lower acetylcholine-mediated endothelial nitric oxide synthase (eNOS) activation compared with never users and was similar to levels from combustible cigarette users (overall P = 0.008, P = 0.01 pod vs never; P = 0.96 pod vs combustible cigarette). The effects of pod-based e-cigarettes and their constituents on vascular cell function were further studied in commercially available human aortic endothelial cells (HAECs) incubated with flavored JUUL e-liquids or propylene glycol (PG):vegetable glycerol (VG) at 30:70 ratio with or without 60 mg/mL nicotine salt for 90 min. A progressive increase in cell death with JUUL e-liquid exposure was observed across 0.0001-1% dilutions; PG:VG vehicle with and without nicotine salt induced cell death. A23187-stimulated nitric oxide production was decreased with all JUUL e-liquid flavors, PG:VG and nicotine salt exposures. Aerosols generated by JUUL e-liquid heating similarly decreased stimulated nitric oxide production. Only mint flavored e-liquids increased inflammation and menthol flavored e-liquids enhanced oxidative stress in HAECs. In conclusion, pod e-liquids and their individual components appear to impair endothelial cell function. These findings indicate the potential harm of pod-based devices on endothelial cell function and thus may be relevant to cardiovascular injury in pod type e-cigarette users.

Juul use among emerging adults transitioning from high school to college

Objective: Assess the prevalence, perceptions, sociodemographic/personal factors that influence Juul use among incoming freshmen.Participants: Incoming undergraduate students (N = 1,706) attending a public university in the southeastern U.S.Methods: Cross-sectional survey administered August 2018. Bivariate relationships assessed using chi-square test of association. Multinomial logistic regression to determine factors associated with Juul use status.Results: 41% had ever used Juul, 24% had used within the past month. Among current users, one-third had used 20-30 days. Risk factors for current use: heterosexual orientation (relative to other sexual orientation) AOR = 2.16, 95% CI: 1.20-3.91), those who planned to join sorority/fraternity (relative to those who did not plan to; AOR = 2.15, 95% CI: 1.59-2.90), current smokers (relative to nonsmokers; AOR = 24.39, 95% CI: 7.52-76.92), current marijuana users (compared with nonusers of marijuana; AOR = 6.45, 95% CI: 3.92-10.64) and alcohol users (compared with nondrinkers; AOR = 7.81, 95% CI: 5.75-10.54).Conclusion: Prevention and treatment efforts are needed for emerging adults transitioning to college.

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-Cigarette Aerosol Deposition and Disposition of [11C]Nicotine Using Positron Emission Tomography: A Comparison of Nicotine Uptake in Lungs and Brain Using Two Different Nicotine Formulations

Smoking is a cause of serious disease in smokers. Electronic cigarettes, delivering aerosolized nicotine, offer adult smokers a potentially less harmful alternative to combustible cigarettes. This explorative PET/CT study investigated the distribution and deposition of inhaled [¹¹C]nicotine using the myblu^TM e-cigarette with two nicotine formulations, freebase and lactate salt. Fifteen healthy adult smokers participated in the two-part study to assess the distribution and accumulation of [¹¹C]nicotine in the respiratory pathways and brain. Time-activity data for the respiratory pathways, lungs, oesophagus and brain were derived. 31–36% of both inhaled tracer formulations accumulated in the lung within 15–35 s. [¹¹C]Nicotine_freebase exhibited higher uptake and deposition in the upper respiratory pathways. For [¹¹C]nicotine_lactate, brain deposition peaked at 4–5%, with an earlier peak and a steeper decline. A different kinetic profile was obtained for [¹¹C]nicotine_lactate with lower tracer uptake and accumulation in the upper respiratory pathways and an earlier peak and a steeper decline in lung and brain. Using nicotine lactate formulations in e-cigarettes may thus contribute to greater adult smoker acceptance and satisfaction compared to freebase formulations, potentially aiding a transition from combustible cigarettes and an acceleration of tobacco harm reduction initiatives.

E-cigarette device type and combustible tobacco use: Results from a pooled analysis of 10,482 youth

INTRODUCTION

To understand whether using a certain e-cigarette device is more strongly associated with risk of combustible tobacco use among youth.

METHODS

We conducted multivariable logistic regression analyses using cross-sectional data from 4 samples of youth in Connecticut and California (N = 10,482; ages 13-24), separately for each study using the total sample and the sample of past-month e-cigarette users, to understand the association between e-cigarette device type and past-month combustible tobacco use, while controlling for age, sex, race/ethnicity, socioeconomic status, school, and past-month marijuana use. Then, we conducted meta-analyses to calculate pooled associations for adolescents, young adults, and all individuals combined.

RESULTS

Among the total sample, combustible tobacco use was associated with any e-cigarette device use (vs. no e-cigarette use) in the pooled analysis across all studies. Among past-month e-cigarette users, combustible tobacco use across all studies was 15.8%- 61.5%. Pooled associations among past-month e-cigarette users showed that using disposable devices (vs. pods; AOR=2.83, 95% CI: 1.73-4.61) and multiple devices most frequently (vs. pods; AOR=2.13, 95% CI: 1.16-3.90) was associated with greater odds of combustible tobacco use. Pooled associations also found that using multiple devices (vs. a single device) in the past month was associated with greater odds of combustible tobacco use (AOR 2.33, 95% CI: 1.74, 3.14).

DISCUSSION

Using disposable e-cigarettes and multiple devices is associated with greater likelihood of combustible tobacco use among e-cigarette using youth. Future research should elucidate the trajectory of e-cigarette device used and combustible tobacco use among youth to inform prevention and product regulation.

Reductions in biomarkers of exposure to selected harmful and potentially harmful constituents following exclusive and partial switching from combustible cigarettes to myblu™ electronic nicotine delivery systems (ENDS)

Electronic nicotine delivery systems (ENDS) offer adult combustible cigarette smokers an alternative, potentially reduced harm, mode of nicotine delivery, attributed to fewer and reduced levels of harmful and potentially harmful constituents (HPHCs) in their aerosols compared to cigarette smoke. These two identical, randomised, open label, two-part studies aimed to compare levels of 15 biomarkers of exposure (BoE) to selected HPHCs associated with tobacco smoking in healthy US adult smoker subjects (n = 72). Following 9 days of exclusive use of a range of allocated myblu™ ENDS variants, subjects' levels of 14 non-nicotine BoE were substantially reduced compared to baseline values (combustible cigarette use), in the range of 46-97%. BoE reductions were sustained in subjects who continued myblu use exclusively (n = 25) for a further 5 days, and returned to near baseline levels in subjects who returned to exclusive combustible cigarette use (n = 21). Dual users (n = 24) demonstrated reductions in BoE to a lesser extent than with exclusive myblu use. Measured nicotine equivalents did not significantly change throughout the study. These data suggest exclusive use of ENDS provides adult smokers seeking an alternative to combustible cigarettes with substantial reductions in HPHC exposures whilst achieving satisfying levels of nicotine delivery. Dual use involving substitution of cigarettes may also provide some of this advantage, but to lesser extent. Overall, the data contribute to the weight of evidence that ENDS are an important tool in tobacco harm reduction for adult smokers unwilling to or uninterested in quitting smoking. Study 1: NCT04430634, study 2: NCT04429932, clinicaltrials.gov (10-06-2020).

Intentions and Attempts to Quit JUUL E-Cigarette Use: The Role of Perceived Harm and Addiction

Introduction

Research on electronic cigarette (e-cigarette) quit intentions and attempts is limited despite the potential health benefits of quitting, especially for long-term users. The current study aimed to investigate perceptions of harm and addictiveness and tobacco use characteristics associated with quit variables among users of a popular e-cigarette brand, JUUL.

Methods

We surveyed 301 US adult JUUL users on their tobacco use characteristics, perceptions of JUUL harm and addictiveness, and quit variables at 3 time points, from July 2019 to April 2020. We used logistic regression models to assess demographic characteristics, smoking characteristics, and perceptions of JUUL harm and addictiveness as correlates of e-cigarette quit intentions, attempts, importance, and confidence.

Results

Twenty-three percent of the sample had intentions to quit using JUUL within the year, and 22.6% reported making a lifetime quit attempt. The average rating of quit importance was 4.1 and quit confidence was 5.8 on a Likert scale of 1 to 10. More than 90% of the sample indicated that JUUL was at least moderately addictive, whereas less than one-quarter indicated that JUUL was as harmful or more harmful than smoking. Higher levels of perceived JUUL addictiveness were associated with more quit intentions, attempts, and importance. Higher levels of perceived JUUL harm compared with smoking were associated with more quit importance.

Conclusion

Our findings suggest that a small proportion of adult JUUL users are interested in quitting. Self-reported perceptions of JUUL’s addiction potential may be related to more quit attempts. Findings highlight the need for evidence-based information on e-cigarette addictiveness and effective strategies for cessation.

Device features and user behaviors as predictors of dependence among never-smoking electronic cigarette users: PATH Wave 4

INTRODUCTION

Electronic cigarettes (ECIGs) vary greatly in their ability to deliver nicotine, which suggests they may also vary in their ability to produce dependence. This study examined individual and combined ECIG device features, and also user behaviors, as predictors of dependence in never-smoking ECIG users. Methods Data were collected from 711 current ECIG users who had smoked <100 cigarettes in their lifetime at Wave 4 of the Population Assessment of Tobacco and Health (PATH) Study. Multivariable linear regressions examined individual (e.g., contains nicotine, uses a tank, flavor preference) and combined (e.g., refillable tanks, refillable mods) device features, and user behaviors (e.g., uses/day) as predictors of dependence, withdrawal, and craving after accounting for demographic variables. Results Results for ECIG dependence and craving showed a similar pattern; higher levels were observed for older age, more frequent past 30-day use, using an ECIG containing nicotine (vs no nicotine), and using a non-refillable cartridge or refillable tank style (vs disposables). Higher withdrawal levels were observed for higher education levels and individual device features of tank (vs no tank), cartridge (vs no cartridge), refillable (vs non-refillable), and "other" flavor preference (vs tobacco flavor). Lower withdrawal levels were associated with a preference for sweet/fruit flavor(s) (vs tobacco flavor). Conclusions Few use behaviors and device features, whether examined alone or in combination, predicted dependence-related outcomes. Findings underscore the challenge with regulating ECIG products in the current marketplace, which is inundated with a myriad of device types.

The effect of emerging tobacco related products and their toxic constituents on thrombosis

Although conventional cigarette smoking is declining, emerging tobacco related products (ETRPs) are currently gaining ground, especially among the youth. These products include electronic cigarettes, waterpipes/hookah, cigars/cigarillo, smokeless tobacco, and heat-not-burn cigarettes. The observed increase in the use of ETRPs is multifactorial and complex but appears to be mainly driven by efforts from the major tobacco companies to reinvent themselves, and present more appealing and allegedly safe(r) tobacco products. However, it is becoming apparent that these products produce substantial amounts of toxic chemicals, many of which have been shown to exert negative health effects, including in the context of the cardiovascular system. Thus, there has been research efforts, albeit limited in general, to characterize the health impact of these products on occlusive/thrombotic cardiovascular diseases (CVD). In this review, we will discuss the potential impact of ETRPs on thrombosis-based CVD. Specifically, we will review how these products and the major chemicals they produce and/or emit can trigger key players in the process of thrombosis, namely inflammation, oxidative stress, platelets, coagulation, and the vascular endothelium, and the relationship between these effects.

Progress in quantification of nicotine content and form distribution in electronic cigarette liquids and aerosols

Each electronic cigarette (e-cigarette) is a battery-powered system which converts electronic cigarette liquids (e-liquids) into the inhalable phase by heating the solution when it is in use. After four generations of development, e-cigarettes tend to be more customized and user-operable. The main components in the e-liquid and the aerosol are vegetable glycerin, propylene glycol, nicotine, organic acid and some flavor ingredients. Among them, nicotine is closely associated with the irritation and physiological satisfaction caused by tobacco products, and it is the core functional substance of e-cigarettes. For this reason, the quantification of nicotine content and nicotine form distribution mainly focuses on the components of the e-liquid and the released aerosol. Up to now, various technologies and methods have been applied in the analysis and research of nicotine content and nicotine form distribution in the e-liquid and its aerosol. GC-MS is often used as the most viable tool for the analysis of volatile organic compounds and can be widely applied in the measurement of nicotine related chemicals; there are a number of quantitation strategies using LC-MS, LC-MS/MS or ¹H NMR for the analysis of e-cigarette samples. We also reviewed the four main methods for determining the distribution of nicotine forms, which are pH value derivation, solvent extraction, SPME and NMR methods. These research methods are of great significance to the upgrading and development of e-cigarette products.

E-Liquids from Seven European Countries–Warnings Analysis and Freebase Nicotine Content

Electronic cigarettes are available in a variety of devices with e-liquids also available in many flavors, and nicotine concentrations, albeit less than 20 mg/mL in Europe. Given the dynamics of these products, it is important to evaluate product content, including labeling, nicotine content versus labeled claim, nicotine form, and other aspects that may help policy decisions and align with the Tobacco Product Directive (TPD). Herein, we performed a study on 86 e-liquids from seven European countries (Croatia, Czech Republic, France, Germany, Italy, Poland, and the United Kingdom) with 34 different liquid brands and 57 different flavors. Nicotine content versus labeled claim, labeling, volume, pH, and nicotine form (i.e., freebase nicotine) were evaluated. From all tested products, eight of them from Germany, Poland, and UK (from 3 to 18 mg/mL), met the ±2% criteria. The ±10% criteria was fulfilled by 50 (58.1%) liquids from all countries. Among 71 liquids which contained nicotine, (one e-liquid labeled as 6 mg/mL had no nicotine level quantified), the amount of freebase nicotine differed from 0 to 97.8%, with a mean value 56.5 ± 35.7. None of the tested liquids had nicotine salt listed in the ingredients. Therefore, a low level of freebase nicotine in some liquids was most likely achieved by added flavorings. All tested liquids presented in this study met the basic requirements of the TPD. There were differences in the scope of information about harmfulness, type of warnings on packaging, attaching leaflets, placing graphic symbols, and discrepancies between the declared and quantified nicotine concentrations.

Tracing the movement of electronic cigarette flavor chemicals and nicotine from refill fluids to aerosol, lungs, exhale, and the environment

BACKGROUND

Given the high concentrations of nicotine and flavor chemicals in EC (electronic cigarette) fluids, it is important to determine how efficiently they transfer to aerosols, how well they are retained by users (exposure), and if they are exhaled into the environment where they settle of surfaces forming ECEAR (EC exhaled aerosol residue).

OBJECTIVES

To quantify the flavor chemicals and nicotine in refill fluids, inhaled aerosols, and exhaled aerosols. Then deduce their retention and contribution to ECEAR.

METHODS

Flavor chemicals and nicotine were identified and quantified by GC-MS in two refill fluids, smoking machine-generated aerosols, and aerosols exhaled by 10 human participants (average age 21; 7 males). Machine generated aerosols were made with varying puff durations and two wattages (40 and 80). Participants generated exhale ad libitum; their exhale was quantified, and chemical retention and contribution to ECEAR was modeled.

RESULTS

"Dewberry Cream" had five dominant (≥1 mg/mL) flavor chemicals (maltol, ethyl maltol, vanillin, ethyl vanillin, furaneol), while "Cinnamon Roll" had one (cinnamaldehyde). Nicotine transferred well to aerosols irrespective of topography; however, transfer efficiencies of flavor chemicals depended on the chemical, puff volume, puff duration, pump head, and EC power. Participants could be classified as "mouth inhalers" or "lung inhalers" based on their exhale of flavor chemicals and nicotine and retention. Lung inhalers had high retention and exhaled low concentrations of EC chemicals. Only mouth inhalers exhaled sufficient concentrations of flavor chemicals/nicotine to contribute to chemical deposition on environmental surfaces (ECEAR).

CONCLUSION

These data help distinguish two types of EC users, add to our knowledge of chemical exposure during vaping, and provide information useful in regulating EC use.

Drug and alcohol dependence acute effects of pod-style e-cigarettes in vaping-naïve smokers

BACKGROUND

This study investigated the acute effects of exposure to pod-style e-cigarettes on subjective, behavioral, and physiological outcomes indicative of the potential to encourage vaping-naïve smokers to switch to e-cigarettes.

METHODS

In a within-subject experiment, never-vaping adult smokers interested in trying e-cigarettes (n = 24) completed 4 laboratory visits following 16-hr tobacco abstinence. Visits involved controlled puffing from preferred brand cigarettes (OwnCig) or a standardized pod-style e-cigarette with either no nicotine (NoNic), nicotine freebase (NicFreebase; 0.5% nicotine concentration), or nicotine salt (NicSalt E-Cig; 2.8% concentration) solutions. Outcomes included smoking urge, mood, user experience, plasma nicotine, and a behavioral task assessing ability to delay smoking.

RESULTS

NoNic, NicFreebase, and NicSalt pod-style e-cigarettes were significantly less effective than OwnCig at reducing smoking urge and increasing plasma nicotine, positive affect, satisfying user experience ratings, and ability to delay smoking on the behavioral task. Differences among pod-style e-cigarette conditions were limited to: (a) NicFreebase (vs. NoNic) preferentially suppressed participants' urge to smoke to alleviate negative mood, (b) NicFreebase (vs. NicSalt) slightly preferentially increased plasma nicotine; and (c) NicFreebase and NicSalt (vs. NoNic) produced higher aversive user experience ratings.

CONCLUSIONS

In tobacco deprived smokers' initial vaping experience, controlled administration of certain pod-style e-cigarettes with 0.5% NicFreebase or 2.8% NicSalt may be deficient comparators to cigarettes in terms of their capacity to acutely improve mood, deliver nicotine, suppress smoking motivation, and offer a satisfying user experience. Future research is needed to test pod-style e-cigarettes with higher nicotine doses and confirm whether NicFreebase vs. NicSalt enhances nicotine absorption.

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.

Further pharmacological characterization of a preclinical model of the early development of nicotine withdrawal

BACKGROUND

Establishing preclinical models of the development of nicotine withdrawal following acute nicotine exposure could inform tobacco addiction-related research, treatment, and policy. To this end, this lab has previously reported that rats exhibit withdrawal-like elevations in intracranial self-stimulation (ICSS) thresholds (anhedonia-like behavior) following acute nicotine exposure. The goal of this study was to provide further pharmacological characterization of ICSS as a measure of spontaneous and antagonist-precipitated withdrawal from acute nicotine.

METHODS AND RESULTS

Rats exhibited a small increase in ICSS thresholds over time following a single nicotine injection (1.0 mg/kg, s.c.), suggesting a modest spontaneous withdrawal effect (Experiment 1). In Experiment 2, the antidepressant bupropion (5.0 mg/kg, i.p.), which is used to treat tobacco addiction and attenuates nicotine withdrawal in both humans and rodents, blocked elevations in ICSS thresholds induced by a single injection of nicotine (0.5 mg/kg, s.c.) followed ≈ 2 h later by the non-selective, non-competitive nicotinic acetylcholine receptor (nAChR) antagonist mecamylamine (3.0 mg/kg, s.c.). In Experiment 3a, s.c. administration of the competitive, relatively selective α4ß2 nAChR antagonist dihydro-beta-erythroidine (DHßE) (5.6 mg/kg, but not 3.0 mg/kg) following each of 5 daily injections of nicotine (0.5 mg/kg, s.c.) elevated ICSS thresholds. Mecamylamine (3.0 mg/kg, s.c.) also elevated ICSS thresholds when administered following all 5 daily nicotine injections (0.5 mg/kg, s.c., Experiment 3b).

CONCLUSIONS

These findings provide further characterization of elevations in ICSS thresholds as a measure of withdrawal from acute nicotine exposure. Further use of these models may be useful for understanding the early development of nicotine withdrawal.

Predicting molecular mechanisms, pathways, and health outcomes induced by Juul e-cigarette aerosol chemicals using the Comparative Toxicogenomics Database

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Vaping chemicals of Juul aerosols were analyzed using CTD.

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CTD can be used to predict disease associations of Juul aerosol chemicals.

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Predictive pathways that relate vaping aerosols to diseases are described.

There is a critical need to understand the health risks associated with vaping e-cigarettes, which has reached epidemic levels among teens. Juul is currently the most popular type of e-cigarette on the market. Using the Comparative Toxicogenomics Database (CTD; http://ctdbase.org), a public resource that integrates chemical, gene, phenotype and disease data, we aimed to analyze the potential molecular mechanisms of eight chemicals detected in the aerosols generated by heating Juul e-cigarette pods: nicotine, acetaldehyde, formaldehyde, free radicals, crotonaldehyde, acetone, pyruvaldehyde, and particulate matter. Curated content in CTD, including chemical-gene, chemical-phenotype, and chemical-disease interactions, as well as associated phenotypes and pathway enrichment, were analyzed to help identify potential molecular mechanisms and diseases associated with vaping. Nicotine shows the most direct disease associations of these chemicals, followed by particulate matter and formaldehyde. Together, these chemicals show a direct marker or mechanistic relationship with 400 unique diseases in CTD, particularly in the categories of cardiovascular diseases, nervous system diseases, respiratory tract diseases, cancers, and mental disorders. We chose three respiratory tract diseases to investigate further, and found that in addition to cellular processes of apoptosis and cell proliferation, prioritized phenotypes underlying Juul-associated respiratory tract disease outcomes include response to oxidative stress, inflammatory response, and several cell signaling pathways (p38MAPK, NIK/NFkappaB, calcium-mediated).

Disposable E-Cigarette Use Prevalence, Correlates, and Associations with Previous Tobacco Product Use in Young Adults

INTRODUCTION

Novel, inexpensive disposable e-cigarettes widely sold in attractive flavors might be exempt from U.S. federal regulations. To inform regulatory and public health priorities, this study examined young adult disposable e-cigarette use uptake among existing tobacco users vs. non-users and possible use correlates that could be potential regulatory targets.

METHODS

Prospective cohort data were analyzed in 2021. Among baseline (2018-2019) never disposable e-cigarette users (n=1903; Mean[SD]:19.3[0.8] years-old), we tested prospective associations of baseline tobacco product use with follow-up (2020) disposable e-cigarette use initiation, followed by stratified analyses distinguishing baseline exclusive and dual e-cigarette/combustible tobacco use. Exploratory cross-sectional associations of tobacco-related correlates with vaping frequency among current disposable users (n=266) were tested.

RESULTS

Follow-up ever disposable e-cigarette use initiation was higher among baseline former (22.1%) and current (50.2%) vs. never (6.3%) rechargeable (non-disposable) e-cigarette users. In stratified analyses, follow-up disposable e-cigarette use initiation was 0% in baseline never-vaping exclusive current smokers, higher in baseline never-vaping former smokers vs. never users of any tobacco product (18.2% vs. 5.7%; adjusted odds ratio[AOR][95%CI]=3.9[2.1-7.5]), and higher among baseline current dual users vs. never-smoking exclusive current vapers (61.3% vs. 42.2%; AOR[95%CI]=3.0[1.5-6.0]). Among follow-up current disposable e-cigarette users (overall prevalence=10.9%), using ice-flavored (vs. fruit/sweet-flavored) e-cigarettes (adjusted rate ratio[95%CI]=1.5[1.0-2.1]) and vaping dependence symptoms (adjusted rate ratio[95%CI]=2.2[1.5-3.2]) were cross-sectionally associated with more past-month disposable e-cigarette use days.

CONCLUSIONS

Young adult disposable e-cigarette use was of appreciable prevalence, including among tobacco product never users and former smokers. Regulation of disposable e-cigarettes, including ice-flavored products, might benefit young adult health.

IMPLICATIONS

Sales of disposable e-cigarette products increased significantly in the United States from 2019 to 2020. These products contain high nicotine concentrations and various flavors that may appeal to young people. This study provides the first evidence that disposable e-cigarette use may be common among young adults, including among tobacco product never users and former smokers. Frequency of disposable e-cigarette use was positively associated with using ice-flavored e-cigarettes and vaping dependence. Regulatory policies and enforcement strategies addressing disposable e-cigarettes merit consideration in young adult health policy and prevention priorities.

Pneumothorax secondary to vaping

Pneumothorax is the presence of air in the pleural space that can result in the partial or complete collapse of a lung. Cigarette and cannabis smoking are also well-known risk factors. Vaping, on the other hand, is not as well-established as little is known about the impact electronic cigarettes have on the development of pneumothoraces despite their use rapidly increasing over the past decade. While the long-term adverse health effects of vaping are still unknown, the acute adverse events of vaping that have occurred are concerning. Pneumothoraces due to electronic cigarettes have been rarely reported so far but the body of literature illustrating an association is growing. We hope to contribute to it by presenting a case of a 19-year-old male who presented with an e-cigarette induced pneumothorax. It is our hope that this case brings more evidence to the dangers of e-cigarette use.

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.

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.

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.

Potential factors affecting free base nicotine yield in electronic cigarette aerosols

BACKGROUND

The free base and protonated nicotine forms in e-cigarette aerosol have shown different absorption profiles in users. Therefore, it is also important to identify the factors which can affect the ratio of these nicotine forms in the aerosol. Such factors may include nicotine concentrations, flavors, PG:VG ratios, types of nicotine chemical compounds and e-cigarette battery power outputs. The current study attempts to identify such factors using a controlled experiment.

RESEARCH DESIGNS AND METHODS

The aerosol was generated using validated aerosol generating model. Various factors were tested for their effect on nicotine forms. Additionally, a degradation study of one of the nicotine compounds, nicotine salicylate, was also carried out using mass spectrometry.

RESULTS

The free base nicotine in the aerosol was found to be affected by flavors, battery power output, nicotine compound type and PG:VG ratios. Based on the preliminary mass spectrometry data, degradation of nicotine salicylate was found to be one of the significant factors affecting free base nicotine in aerosol.

CONCLUSIONS

Potential factors affecting free base nicotine in e-cigarette aerosol have been identified in this study. These findings would help in understanding the nicotine delivery better and assist for better regulations.

Vaping epidemic in US teens: problem and solutions

PURPOSE OF REVIEW

Over the last decade, vaping has emerged into an epidemic of alarming proportions among US teens. This review evaluates the factors leading to the rise of vaping, reasons for its striking popularity among US teens, health consequences of vaping, and measures to mitigate the vaping epidemic.

RECENT FINDINGS

Contemporary research highlights the continued rise of vaping amongst US teens and explains the reasons for its popularity, such as the variety of devices, a wide range of available flavors, youth-targeted advertisements, and lack of awareness of adverse consequences from vaping. This publication highlights current research findings of health consequences of vaping, including a discussion of EVALI (e-cigarette or vaping product use-associated lung injury) and provides an update on strategies to curtail the vaping epidemic.

SUMMARY

Vaping has risen to epidemic proportions amongst US teens. This poses a clear and present danger to teens' health with adverse effects ranging from acute lung injury to long-term addiction. This article summarizes key research findings that explain the reasons for the epidemic, health consequences of vaping, and provides an overview of efforts to mitigate the vaping threat to US teens.

Biomarkers of Toxicant Exposure and Inflammation Among Women of Reproductive Age Who Use Electronic or Conventional Cigarettes

Background: Electronic cigarettes (e-cigarettes) generally have a more favorable toxicant profile than conventional cigarettes; however, limited information exists for women of reproductive age (WRA). Our aim was to compare biomarkers of toxicant exposure, inflammation, and oxidative stress among WRA who self-report exclusive e-cigarette use, exclusive cigarette smoking, or never tobacco use (controls). Methods: Multivariable linear regression models were used to compare the geometric means of urinary biomarkers of toxicant exposure and their metabolites, serum markers of inflammation [highly sensitive C-reactive protein, soluble intercellular adhesion molecule (sICAM), interleukin 6, fibrinogen], and a measurement of oxidative stress [prostaglandin F2a-8-isoprostane (F2PG2a)] among WRA from the Population Assessment of Tobacco and Health survey. Results: E-cigarette users had higher levels of lead, tobacco-specific nitrosamines, nicotine metabolites, and some volatile organic compounds (VOCs) than controls. Except for cadmium and lead, e-cigarette users had lower levels of the analyzed urinary toxicant biomarkers compared with cigarette smokers. Cigarette smokers had higher levels of all the biomarkers of toxicant exposure than controls. There were no significant differences in the levels of markers of inflammation and oxidative stress between e-cigarette users and controls. E-cigarette users and controls had lower levels of sICAM and F2PG2a than cigarette smokers. Conclusion: WRA who use e-cigarettes had lower levels of some of the evaluated urinary biomarkers of toxicant exposure and serum biomarkers of inflammation and oxidative stress than those who smoke cigarettes, but higher lead, nicotine metabolites, and some VOCs than controls, which can increase health risks.

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.

Dependence and Use Characteristics of Adult JUUL Electronic Cigarette Users

JUUL is a popular electronic cigarette (e-cig) that is capable of delivering nicotine similarly to a cigarette. While known to deliver high doses of nicotine, there is little systematic evidence to show how the nicotine delivery of JUUL translates to user dependence. Purpose: The purpose of the study was to evaluate self-reported dependence of JUUL users and examine the relationship of dependence to user behaviors. Methods: Current JUUL users were recruited via Amazon Mechanical Turk to complete an online survey about their use of JUUL. Participants were asked to complete the Penn State Electronic Cigarette Dependence Index (PSECDI) and to answer questions about their use patterns and other tobacco use. Means and frequencies were used to describe the sample. A linear regression model was used to predict user dependence. Results: Participants (n = 76) were 65.4% male with a mean age of 31.9 (SD = 8.3) years. The mean PSECDI score was 7.8 (SD = 4.2) and ranged from no (15.8%) to high (14.5%) dependence. Overall predictors of a greater PSECDI score included reporting ever stealth vaping (β = 2.8, p < .01) and reporting greater use days in the past 30 (β = 3.5, p < .01). Conclusions: On average, JUUL users reported low to medium nicotine dependence on the PSECDI. JUUL user dependence may be more similar to e-cig user dependence than cigarette smoker dependence. These preliminary findings should be followed up in studies of larger samples of Juul users, collecting multiple measures of dependence, as well as biomarkers of nicotine intake (e.g. cotinine).

Response to Flavored Cartridge/Pod-Based Product Ban among Adult JUUL Users: "You Get Nicotine However You Can Get It"

In order to curb increasing youth electronic cigarette (e-cig) use, the United States Food and Drug Administration (FDA) banned the sale of flavored cartridge/pod-based products in February 2020. This mixed-methods study aimed to evaluate the impact of the FDA ban on adult JUUL users. The samples of current adult JUUL users were surveyed via Amazon Mechanical Turk at three time-points n = 76 (Sample 1); n = 128 (Sample 2); n = 86 (Sample 3) before and after the FDA flavored/pod ban. The participants were asked to report the JUUL flavored pod used most often and answer questions on purchasing generic pods or refilling (Quantitative). JUUL users were then interviewed in order to explore their perceptions and behaviors related to the FDA ban of flavored cartridge/pod-based products (Qualitative; n = 16). Quantitative data analysis evaluated the differences in variables by time-point. Qualitative data were coded into themes while using the constant comparative method. We found a significant decrease in the use of mint pods (43.4%, 22.7%, 16.3%) (p < 0.01), while there was a significant increase in the use of menthol pods (6.6%, 26.6%, 37.2%) (p < 0.01). Themes that emerged from the qualitative data included switching from mint to menthol pods, refilling pods, and switching to other products that are available in the desired flavors, such as generic pods or disposable e-cigs. Future research is needed in order to evaluate the impact of these behaviors on public health.

Nicotine pharmacokinetics of electronic cigarettes: A pooled data analysis from the literature

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Evaluating the pharmacokinetics of nicotine absorption from electronic cigarettes.

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Nicotine absorption into the blood is influenced by several factors.

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These include e-liquid composition, user behavior and device characteristics.

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Any regulation of nicotine levels in e-liquids should reflect this heterogeneity.

Several regulatory initiatives around the world restrict the amount of nicotine permitted in electronic cigarette liquids in an attempt to reproduce the nicotine delivery of combusted tobacco products, such as cigarettes, and or reduce the risk of consumers absorbing too much nicotine into their body at one time. Such an approach, however, assumes that (i) there is a strong correlation between the levels of nicotine in electronic cigarette liquids and nicotine intake into the body and (ii) that this correlation holds true across the various different types of electronic cigarette devices currently available on the market. In order to test these hypotheses, this study examines the available scientific literature on nicotine intake from electronic cigarettes, as measured by levels in the blood. Analysis of the published data reveals that nicotine absorption into the body is influenced by a combination of many factors, including electronic cigarette liquid composition, user behavior and device characteristics. Notably, it was observed that open-tank (refillable) electronic cigarettes, which often enable users to vary device power, can deliver high nicotine levels to consumers, sometimes at greater doses than a conventional tobacco cigarette, even at the lower nicotine liquid concentrations typically available. For electronic cigarettes to be viable alternative choices to smoking, they should provide consumers with an equally satisfying experience, including in terms of nicotine absorption into the body. Therefore, any regulation seeking to restrict the amount of nicotine in electronic cigarette liquids should take all the factors influencing nicotine intake into account.

Prospective associations of e-cigarette use with cigarette, alcohol, marijuana, and nonmedical prescription drug use among US adolescents

BACKGROUND

As e-cigarette use continues to increase in the U.S., research is needed to understand its prospective risk for cigarette smoking and other substance use in young adulthood, including alcohol, marijuana, and nonmedical prescription drugs (NMPDs).

METHODS

This study used data from the Monitoring the Future (MTF) study a nationally representative annual survey of 12^th graders (modal age 18) in the US. The analytic sample included 2014-2016 MTF cohorts that were selected and completed follow up one year later (modal age 19; n = 717). Using logistic regression, we examined cross-sectional and prospective associations of past 30-day e-cigarette use with past 30-day cigarette, alcohol, marijuana, and NMPD use. We examined prospective associations among the full sample and associations with incidence of each of these substances among those who reported no history of use in 12^th grade.

RESULTS

In cross-sectional analysis, those who reported past 30-day e-cigarette use at age 18 were more likely to report past 30-day cigarette use, alcohol use, marijuana use, and NMPD use at age 19. In multivariable longitudinal analysis, past 30-day e-cigarette users at age 18 were more likely to report past 30-day cigarette, marijuana, and NMPD use at age 19, including e-cigarette users who had no history of using these substances at age 18.

CONCLUSIONS

This study suggests that e-cigarette use may be an indicator of future substance use risk in young adulthood. Adolescent e-cigarette users may benefit from secondary prevention efforts to mitigate this risk.

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.

Nicotine forms: why and how do they matter in nicotine delivery from electronic cigarettes?

INTRODUCTION

Unregulated e-cigarette devices and their nicotine content have amplified the potential of e-cigarettes as addictive agents. Several e-cigarette-related parameters have been identified altering nicotine's absorption profile, so their potential effects on addiction should be considered. Of these factors, nicotine forms (protonated and free base) play a significant role in the addiction potential yet their impact on nicotine's absorption has been studied with limited research.

AREAS COVERED

Current review aims to emphasize on the possible mechanism behind different absorption profiles of nicotine forms considering their physical states (droplet and vapor phase) and the aerosol particle size, their analysis in e-cigarette research and the regulatory attention warranted by them to combat nicotine addiction in the population due to e-cigarettes.

EXPERT OPINION

The protonated form of nicotine is being correlated with the smooth sensory effects and high nicotine absorption as compared to free base nicotine. With the introduction of nicotine salts, which yield mostly the protonated form, the youth popularity of e-cigarettes has spiked exponentially. While it is important to control nicotine levels in e-cigarette products, attention should also be given to the nicotine forms present in these products in order to address nicotine addiction in the population.

Review of Health Consequences of Electronic Cigarettes and the Outbreak of Electronic Cigarette, or Vaping, Product Use-Associated Lung Injury

Electronic cigarettes (e-cigarettes) are battery-operated devices to insufflate nicotine or other psychoactive e-liquid aerosols. Despite initial claims of e-cigarettes as a nicotine-cessation device, aggressive marketing of e-cigarettes has led to an explosion in adolescents' and young adults' use over the last few years. Coupled with a lack of adequate investigation and regulation of e-cigarettes, the USA is facing an outbreak of e-cigarette, or vaping, product use-associated lung injury (EVALI) starting in mid-2019. While little long-term health hazard data are available, the components and constituents of e-cigarettes may adversely impact health. Propylene glycol and glycerin are humectants (water-retaining excipients) that generate pulmonary irritants and carcinogenic carbonyl compounds (e.g., formaldehyde, acetaldehyde, and acrolein) when heated in e-cigarettes. Metals contained in heating coils and cartridge casings may leach metals such as aluminum, chromium, iron, lead, manganese, nickel, and tin. Flavoring agents are considered safe for ingestion but lack safety data for inhalational exposures. Diacetyl, a common buttery flavoring agent, has known pulmonary toxicity with inhalational exposures leading to bronchiolitis obliterans. In 2019, clusters of lung injury associated with e-cigarette use were identified in Wisconsin and Illinois. Patients with EVALI present with a constellation of respiratory, gastrointestinal, and constitutional symptoms. Radiographically, patients have bilateral ground glass opacifications. As of February 18, 2020, the Centers for Disease Control has identified 2807 hospitalized patients diagnosed with either "confirmed" or "probable" EVALI in the US. Currently, vitamin E acetate (VEA) used as a diluent in tetrahydrocannabinol vape cartridges is implicated in EVALI. VEA cuts tetrahydrocannabinol oil without changing the appearance or viscosity. When inhaled, pulmonary tissue lacks the mechanism to metabolize and absorb VEA, which may lead to its accumulation. While most EVALI patients were hospitalized, treatment remains largely supportive, and use of corticosteroids has been associated with clinical improvement. The outbreak of EVALI highlights the need for regulation of e-cigarette devices and e-liquids. Clinicians need to be aware of the health hazards of e-cigarettes and be vigilant in asking about vaping.

Recent findings in the pharmacology of inhaled nicotine: Preclinical and clinical in vivo studies

INTRODUCTION

The rise of vaping in adolescents, the recent entrance of new inhaled nicotine products such as iQOS on the market and e-cigarette or vaping product use-associated lung injury cases has created concern for the use of inhaled non-combustible nicotine products. This narrative review discusses recent experimental in vivo studies that utilize human, rat and mouse models to understand the pharmacological impact of nicotine from non-combustible products.

METHODS

The search engine PubMed was utilized with the following search terms: inhaled nicotine, nicotine e-cigarette, heated tobacco products, iQOS, electronic cigarette, nicotine inhaler, nicotine vaping. This review highlights recent primary in vivo studies of inhaled nicotine administration experimental paradigms that occurred in laboratory settings using human and rodent (rats and mice) models that have been published from January 2017-December 2019.

RESULTS

The pharmacokinetics of nicotine via e-cigarettes is influenced by the PG/VG and flavor constituents in e-liquids, the presence of nicotine salts in e-liquids, puff topography of nicotine and tobacco product users and the power of the e-cigarette device. The pharmacodynamic impact of inhaled nicotine has cardiovascular, pulmonary and central nervous system implications.

CONCLUSION

The articles reviewed here highlight the importance of both animal and human models to fully understand the impact of inhaled nicotine pharmacology There is a need for more rodent pharmacokinetic inhaled nicotine studies to understand the influences of factors such as flavor and nicotine salts. Additionally, consensus on nicotine measurement in both human and rodent studies is greatly needed.

Vaping in adolescents: epidemiology and respiratory harm

PURPOSE OF REVIEW

This review highlights epidemiologic changes in e-cigarette use in adolescents, discusses recent advances in aerosolized nicotine delivery, and provides and updated profile of research related to the lung-specific harm of e-cigarettes.

RECENT FINDINGS

In the past decade, nicotine-containing e-cigarettes have emerged as the most popular tobacco and nicotine delivery modality among adolescents in the United States. The surge in popularity of these devices has coincided with an outbreak of vaping-related lung injury, bringing e-cigarette use to national attention, and creating a great deal of confusion regarding their potential for respiratory harm. Newer pod-based devices and formulations of e-liquids have resulted in products appeal to youth and deliver nicotine with increasing efficiency. E-liquid aerosols are associated with direct harm to respiratory epithelium and have been shown to alter pulmonary function, inflammation, mucociliary clearance, and lung histology.

SUMMARY

Although the long-term harms of regular e-cigarette use are unknown, numerous studies including early longitudinal data suggest e-cigarette use is associated with incidence of respiratory disease, independent of concurrent traditional cigarette use. Improved understanding and recognition of harm will contribute to the basis of further studies examining the role of e-cigarettes on chronic respiratory disease and will inform future prevention education.

An Electronic Aerosol Delivery System for Functional Magnetic Resonance Imaging

Background:

Public health concerns over the addictive potential of electronic cigarettes (e-cigs) have heightened in recent years. Brain function during e-cig use could provide an objective measure of the addictive potential of new vaping products to facilitate research; however, there are limited methods for delivering e-cig aerosols during functional magnetic resonance imaging (fMRI). The current study describes the development and feasibility testing of a prototype to deliver up to four different e-cig aerosols during fMRI.

Methods:

Standardized methods were used to test the devices’ air flow variability, nicotine yield, and free radical production. MRI scans were run with and without the device present to assess its safety and effects on MRI data quality. Five daily smokers were recruited to assess plasma nicotine absorption from e-liquids containing nicotine concentrations of 8, 11, 16, 24, and 36 mg/ml. Feedback was collected from participants through a semi-structured interview and computerized questionnaire to assess comfort and subjective experiences of inhaling aerosol from the device.

Results:

Nicotine yield captured from the aerosol produced by the device was highly correlated with the nicotine concentration of the e-liquids used (R² = 0.965). Nicotine yield was reduced by a mean of 48% and free radical production by 17% after traveling through the device. The e-liquid containing the highest nicotine concentration tested (36 mg/ml) resulted in the highest plasma nicotine boost (6.6 ng/ml). Overall, participants reported that the device was comfortable to use and inhaling the e-cig aerosols was tolerable. The device was determined to be safe for use during fMRI and had insignificant effects on scan quality.

Conclusions:

With the current project, we were able to design a working prototype that safely and effectively delivers e-cig aerosols during fMRI. The device has the potential to be used to assess brain activation during e-cig use and to compare brain reactivity to varying flavors, nicotine concentrations, and other e-cig characteristics.

Acute effects of JUUL and IQOS in cigarette smokers

BACKGROUND

JUUL is an electronic cigarette that aerosolises a nicotine-containing liquid, while IQOS heats tobacco to produce an aerosol. Both are marketed to smokers, but their effects have seldom been examined in this population.

METHODS

Eighteen cigarette smokers (13 men) with no JUUL or IQOS experience completed a within-subject, laboratory study assessing nicotine delivery and subjective effects after controlled (10 puffs, ~30 s interpuff interval) and ad libitum (90 min) use of JUUL, IQOS or own-brand (OB) cigarettes.

RESULTS

JUUL increased mean plasma nicotine concentration significantly from 2.2 (SD=0.7) ng/mL to 9.8 (4.9) ng/mL after 10 puffs and to 11.5 (9.3) ng/mL after ad libitum use. IQOS increased mean plasma nicotine significantly from 2.1 (0.2) ng/mL to 12.7 (6.2) ng/mL after 10 puffs and to 11.3 (8.0) ng/mL after ad libitum use. OB increased mean plasma nicotine significantly from 2.1 (0.2) ng/mL to 20.4 (11.4) ng/mL after 10 puffs and to 21.0 (10.2) ng/mL after ad libitum use. Mean OB plasma nicotine concentration was significantly higher than JUUL and IQOS. OB increased expired carbon monoxide concentration, but IQOS and JUUL did not. 'Craving a cigarette/nicotine' and 'Urges to smoke' were reduced significantly for all products following the directed bout.

CONCLUSIONS

Among smokers, JUUL and IQOS delivered less nicotine than cigarettes. Also, in this sample, IQOS and OB reduced abstinence symptoms more effectively than JUUL. Additional work with experienced JUUL and IQOS users is needed, as their nicotine delivery profiles and subjective experiences may differ.