E-cigarette and waterpipe use in two adolescent cohorts: cross-sectional and longitudinal associations with conventional cigarette smoking

A systematic review and meta-analysis of the association between e-cigarette use among non-tobacco users and initiating smoking of combustible cigarettes

INTRODUCTION

The rapid increase in e-cigarette use over the past decade has triggered an important public health question on the potential association between e-cigarette use and combustible cigarette smoking. Following AMSTAR 2 and PRISMA guidelines, this evidence synthesis sought to identify and characterize any associations between e-cigarette use among individuals not smoking cigarettes and initiation of cigarette smoking.

METHODS

The protocol was registered on September 24, 2018 (PROSPERO 2018 CRD42018108540). Three databases were queried from January 01, 2007 to April 26, 2023. Search results were screened using the PICOS review method.

RESULTS

Among 55 included studies (40 "good" and 15 "fair"; evidence grade: "high") that adjusted for gender, age, and race/ethnicity between groups, generally, there was a significant association between non-regular e-cigarette use and initiation of cigarette smoking, further supported by the meta-analytic results (AOR 3.71; 95% CI 2.86-4.81). However, smoking initiation was most often measured as ever/current cigarette smoking. Two studies (quality: 2 "good") evaluated progression to regular cigarette smoking among individuals with regular use of e-cigarettes, and generally found no significant associations. One study ("good") evaluated smoking initiation among individuals with regular use of e-cigarettes, finding an increasing probability of ever smoking cigarettes with increased e-cigarette use. Twelve studies (10 "good" and two "fair") examining progression to regular smoking among individuals with non-regular use of e-cigarettes reported inconsistent findings.

CONCLUSIONS

Numerous methodological flaws in the body of literature limit the generalizability of these results to all individuals who are not smoking cigarettes with few studies measuring established/regular use/smoking of e-cigarettes and cigarettes. Further, studies did not control adequately for specific confounding variables representing common liabilities between e-cigarette use and cigarette smoking, nor did they account for sufficient follow-up durations. Collectively, these flaws limit the generalizability of findings to the question of an association between e-cigarette use and cigarette smoking initiation.

Systematic Review and Critical Analysis of Longitudinal Studies Assessing Effect of E-Cigarettes on Cigarette Initiation among Adolescent Never-Smokers

Prospective longitudinal studies mainly conclude on a causal role of e-cigarettes in the initiation of cigarettes in flagrant contradiction with conclusions drawn from epidemiology and other studies showing a sharp decline in cigarette use in parallel with the spread of e-cigarette use. This systematic review explores the reasons for this discrepancy.

METHODS

Among 84 publications on e-cigarette/cigarette association in adolescents identified in the Medline database from 2011 to 2022, 23 concern 22 never-smoker longitudinal sub-cohorts.

RESULTS

A link between e-cigarette experimentation at T1 and cigarette initiation at T2 is reported in sub-cohort analyses of never-smokers (AOR: 1.41 to 8.30). However, studies exclude 64.3% of T1 e-cigarette experimenters (because of dual-use) and 74.1% of T2 cigarette experimenters. With this study design, e-cigarettes contribute only to 5.3% of T2 cigarette experimentation, casting major doubt on the external validity of results and authors' conclusions that e-cigarettes have a significant effect on the initiation of cigarettes (Gateway effect) at the population level. This sub-cohort design prohibits highlighting any Diversion effect, which is the most likely mechanism accounting for the competition between these two products.

CONCLUSIONS

While nicotine abstinence remains the best medical option, over-regulation of e-cigarettes because of misinterpretation of longitudinal study results may be detrimental to public health and tobacco control.

Exploring the gateway hypothesis of e-cigarettes and tobacco: a prospective replication study among adolescents in the Netherlands and Flanders

BACKGROUND

Studies demonstrated that adolescent e-cigarette use is associated with subsequent tobacco smoking, commonly referred to as the gateway effect. However, most studies only investigated gateways from e-cigarettes to tobacco smoking. This study replicates a cornerstone study revealing a positive association between both adolescent e-cigarette use and subsequent tobacco use; and tobacco and subsequent e-cigarette use in the Netherlands and Flanders.

DESIGN

The longitudinal design included baseline (n=2839) and 6-month (n=1276) and 12-month (n=1025) follow-up surveys among a school-based cohort (mean age: 13.62). Ten high schools were recruited as a convenience sample. The analyses involved (1) associations of baseline e-cigarette use and subsequent tobacco smoking among never smokers; (2) associations of e-cigarette use frequency at baseline and tobacco smoking frequency at follow-up; and (3) the association of baseline tobacco smoking and subsequent e-cigarette use among non-users of e-cigarettes.

FINDINGS

Consistent with prior findings, baseline e-cigarette use was associated with higher odds of tobacco smoking at 6-month (OR=1.89; 95% CI 1.05 to 3.37) and 12-month (OR=5.63; 95% CI 3.04 to 10.42) follow-ups. More frequent use of e-cigarettes at baseline was associated with more frequent smoking at follow-ups. Baseline tobacco smoking was associated with subsequent e-cigarette use (OR=3.10; 95% CI 1.58 to 6.06 at both follow-ups).

CONCLUSION

Our study replicated the positive relation between e-cigarette use and tobacco smoking in both directions for adolescents. This may mean that the gateway works in two directions, that e-cigarette and tobacco use share common risk factors, or that both mechanisms apply.

Association of Electronic Cigarette Use by US Adolescents With Subsequent Persistent Cigarette Smoking

Importance

Many studies have reported a positive association of youth electronic cigarette (e-cigarette) use with subsequent cigarette smoking initiation, but it remains unclear whether e-cigarette use is associated with continued cigarette smoking after initiation.

Objective

To assess the association of youth baseline e-cigarette use with their continued cigarette smoking 2 years after initiation.

Design, Setting, and Participants

The Population Assessment of Tobacco and Health (PATH) Study is a national longitudinal cohort study. This sample consisted of youth who participated in waves 3, 4, and 5 of the study (wave 3 was from October 2015 to October 2016, wave 4 was from December 2016 to January 2018, and wave 5 was from December 2018 to November 2019) and had never used cigarettes (cigarette-naive) by wave 3. The current analysis used multivariable logistic regressions in August 2022 to assess the association between e-cigarette use among cigarette-naive adolescents aged 12 to 17 years in 2015 and 2016 and subsequent continued cigarette smoking. PATH uses audio computer-assisted self-interviewing and computer-assisted personal interviewing to collect data.

Exposures

Ever and current (past 30-day) use of e-cigarettes in wave 3.

Main Outcomes and Measures

Continued cigarette smoking in wave 5 after initiating smoking in wave 4.

Results

The current sample included 8671 adolescents who were cigarette naive in wave 3 and also participated in waves 4 and 5; 4823 of the participants (55.4%) were aged 12 to 14 years, 4454 (51.1%) were male, and 3763 (51.0%) were non-Hispanic White. Overall, regardless of e-cigarette use, few adolescents (362 adolescents [4.1%]) initiated cigarette smoking at wave 4, and even fewer (218 participants [2.5%]) continued smoking at wave 5. Controlling for multiple covariates, the adjusted odds ratio of baseline ever e-cigarette use, compared with never e-cigarette use, was 1.81 (95% CI, 1.03 to 3.18) for continued smoking measured as past 30-day smoking at wave 5. However, the adjusted risk difference (aRD) was small and not significant. The aRD was 0.88 percentage point (95% CI, -0.13 to 1.89 percentage points) for continued smoking, with the absolute risk being 1.19% (95% CI, 0.79% to 1.59%) for never e-cigarette users and 2.07% (95% CI, 1.01% to 3.13%) for ever e-cigarette users. Similar results were found using an alternative measure of continued smoking (lifetime ≥100 cigarettes and current smoking at wave 5) and using baseline current e-cigarette use as the exposure measure.

Conclusions and Relevance

In this cohort study, absolute and relative measures of risks yielded findings suggesting very different interpretations of the association. Although there were statistically significant odds ratios of continued smoking comparing baseline e-cigarette users with nonusers, the minor risk differences between them, along with the small absolute risks, suggest that few adolescents are likely to continue smoking after initiation regardless of baseline e-cigarette use.

The prevalence of electronic cigarettes vaping globally: a systematic review and meta-analysis

BACKGROUND

The purpose of this systematic review study was to determine the national, regional, and global prevalence of electronic cigarettes (e-cigarettes) vaping.

METHOD

The articles were searched in July 2020 without a time limit in Web of Science (ISI), Scopus, PubMed, and Ovid-MEDLINE. At first, the titles and abstracts of the articles were reviewed, and if they were appropriate, they entered the second stage of screening. In the second stage, the whole articles were reviewed and articles that met the inclusion criteria were selected. In this study, search, selection of studies, qualitative evaluation, and data extraction were performed by two authors independently, and any disagreement between the two authors was reviewed and corrected by a third author.

RESULTS

In this study, the lifetime and current prevalence of e-cigarettes vaping globally were 23% and 11%, respectively. Lifetime and current prevalence of e-cigarettes vaping in women were 16% and 8%, respectively. Also, lifetime and current prevalence of e-cigarettes vaping in men were 22% and 12%, respectively. In this study, the current prevalence of e-cigarettes vaping in who had lifetime smoked conventional cigarette was 39%, and in current smokers was 43%. The lifetime prevalence of e-cigarettes vaping in the Continents of America, Europe, Asia, and Oceania were 24%, 26%, 16%, and 25%, respectively. The current prevalence of e-cigarettes vaping in the Continents of America, Europe, Asia, and Oceania were 10%, 14%, 11%, and 6%, respectively.

CONCLUSIONS

Based on the results of this study, it can be concluded that the popularity of e-cigarettes is increasing globally. Therefore, it is necessary for countries to have more control over the consumption and distribution of e-cigarettes, as well as to formulate the laws prohibiting about the e-cigarettes vaping in public places. There is also a need to design and conduct information campaigns to increase community awareness about e-cigarettes vaping.

Modeling the longitudinal transitions of electronic cigarettes and conventional cigarettes with time-dependent covariates among adolescents

E-cigarettes may help combustible cigarette smokers switch to a less harmful alternative, or may increase the risk of subsequent initiation of cigarettes among non-smokers. Among youth, it is not clear whether both pathways occur equally, or whether one direction is more likely than the other. We used data from a prospective cohort study of youth in Southern California followed twice annually from Fall 2013 (9th grade) to Fall 2015 (11th grade) (N = 1977). A polytomous logistic regression model was used to simultaneously estimate transition rates for initiation of and abstention from e-cigarettes and cigarettes. Use of e-cigarettes was positively associated with initiation of cigarettes (OR = 7.57; 95%CI:[5.32, 10.8]) and negatively associated with cigarette abstention (OR = 0.58; 95%CI:[0.33, 0.99]) in adjusted models; cigarette use was positively associated with e-cigarette initiation (OR = 2.54; 95%CI:[1.45, 4.47]) and negatively associated with e-cigarette abstention (OR = 0.31; 95%CI:[0.17,0.57]). Uni-directional transition from e-cigarettes only to cigarettes only occurred less frequently than expected under independence (OR = 0.33; 95% CI [0.20, 0.55]), whereas simultaneously initiating both products (OR = 9.79; 95%CI:[7.22, 13.3]) and simultaneously abstaining (OR = 2.84; 95%CI:[1.50, 5.37]) were more frequent than expected. E-cigarettes were more strongly associated with subsequent cigarette initiation than the reverse, though both models indicated that use of either product seems to encourage use of the other. Models also indicated that use of either e-cigarettes or cigarettes resulted in reduced abstention of the other product. Findings suggest that prevention efforts for that continue to focus on both e-cigarettes and cigarettes are needed.

Is Adolescent E-Cigarette Use Associated With Subsequent Smoking? A New Look

INTRODUCTION

Prospective studies have consistently reported a strong association between e-cigarette use and subsequent cigarette smoking, but many failed to adjust for important risk factors.

METHODS

Using longitudinal data from the Population Assessment of Tobacco and Health (PATH) Study, we employed multivariable logistic regressions to assess the adolescent vaping-to-smoking relationship, with four regressions (Models 1-4) sequentially adding more risk factors.Our sample included all waves (waves 1-5) of the PATH Study.

RESULTS

The association between ever e-cigarette use and subsequent cigarette smoking decreased substantially in magnitude when adding more control variables, including respondents' sociodemographic characteristics, exposure to tobacco users, cigarette susceptibility, and behavioral risk factors. Using the most recent data (waves 4-4.5 and waves 4.5-5), this association was not significant in the most complete model (Model 4). Using wave 4.5-5 data, the adjusted odds ratio (aOR) for ever e-cigarette use at initial wave and subsequent past 12-month smoking declined from 4.07 (95% confidence interval [CI, 2.86-5.81) in Model 1, adjusting only for sociodemographic characteristics, to 1.35 (95% CI, 0.84-2.16) in Model 4, adjusting for all potential risk factors. Similarly, the aOR of ever e-cigarette use and past 30-day smoking at wave 5 decreased from 3.26 (95% CI, 1.81-5.86) in Model 1 to 1.21 (95% CI, 0.59-2.48) with all covariates (Model 4).

CONCLUSIONS

Among adolescent never cigarette smokers, those who had ever used e-cigarettes at baseline, compared with never e-cigarette users, exhibited modest or non-significant increases in subsequent past 12-month or past 30-day smoking when adjusting for behavioral risk factors.

Exhalation of alternative tobacco product aerosols differs from cigarette smoke-and may lead to alternative health risks

BACKGROUND

Variation in alternative tobacco product (ATP) constituents, heating potential, and consumer behaviors have made it difficult to characterize their health risks. To date, most toxicity studies of ATPs have used established cigarette endpoints to inform study design. Furthermore, to assess where ATPs fall on the tobacco harm continuum, with cigarettes representing maximum potential risk, studies have tended to compare the relative biological responses to ATPs against those due to cigarettes.

OBJECTIVES

1) To characterize the exhalation profiles of two popular ATPs: electronic cigarettes (e-cigarettes) and hookah waterpipes (hookah) and 2) to determine if ATP exhalation patterns were representative of cigarette exhalation patterns.

METHODS

Exhalation patterns were recorded (mouth only, nose only, or both mouth and nose) among individuals observed in the New York City tri-state area using a recognizable tobacco product (cigarette, e-cigarette, or hookah). Cigarette smokers and e-cigarette vapers were observed on city streets; water-pipe smokers were observed inside Manhattan hookah bars.

RESULTS

E-cigarette vapers practiced exclusive nasal exhalation at far higher rates than did cigarette smokers (19.5% vs 4.9%). Among vapers, e-cigarette device type was also significantly associated with exhalation profile. Overall, cigarette smokers exhaled from their nose approximately half to one-third as often as ATP users (hookah and e-cigarettes, respectively).

CONCLUSIONS

Nasal exhalation of tobacco emissions appears to be a shared characteristic across several types of ATPs. It is therefore plausible that ATP-specific consumer behaviors may foster unique upper respiratory health consequences that have not been observed in smokers. Thus, product-specific behaviors should inform the prioritization of biological endpoints used in studies evaluating ATP toxicity and health effects.

Adolescents' Use of Nicotine-Free and Nicotine E-Cigarettes: A Longitudinal Study of Vaping Transitions and Vaper Characteristics

INTRODUCTION

Although adolescents' nicotine addiction from e-cigarettes is a concern, few studies differentiate between vaping with and without nicotine. This study examines the prevalence of nicotine and nicotine-free vaping, maps transitions between vaping behaviors, and assesses differences in the personal characteristics of vapers in a sample of Norwegian adolescents.

AIMS AND METHODS

Data came from a nationwide longitudinal study of adolescents (n = 2018) conducted in 2017 (T1), 2018 (T2), and 2019 (T3) (mean age: 14.2, 15.0, and 16.2). Using an online questionnaire, we measured vaping with and without nicotine, snus use, smoking, sensation-seeking, conduct problems, and levels of depression.

RESULTS

Past 12-month vaping prevalence was stable (12%, 13%, and 15%). Among adolescents reporting vaping at T1, 66% had used e-cigarettes without nicotine, 22% with nicotine, and 12% were unsure of nicotine content. Individual vaping trajectories were unstable: of nicotine-free vapers, 54% became non-users, while 14% became nicotine vapers from T1 to T2. From T2 to T3, 50% became non-users, while 17% became nicotine vapers. Of nicotine vapers, 39% became non-users from T1 to T2, while 46% became non-users from T2 to T3. Compared to nicotine-free vapers, nicotine vapers had more conduct problems (mean = 3.67 vs 2.17), had more symptoms of depression (mean = 11.38 vs 6.95), and comprised more past 30-day snus users (33% vs 14%) and cigarette users (33% vs 9%).

CONCLUSIONS

Adolescent vapers most commonly used e-cigarettes without nicotine, few of these transitioned into nicotine vaping, and a majority became non-users. Nicotine vapers were more likely to use other tobacco products and have more conduct problems and symptoms of depression compared to nicotine-free vapers.

IMPLICATIONS

Reporting the prevalence of nicotine-free vaping is critical for assessing nicotine exposure and subsequent risks of nicotine addiction. This multi-cohort longitudinal study showed that use of nicotine-free e-cigarettes is common among young vapers in Norway. Adolescents' vaping patterns-both with and without nicotine-are generally temporal and experimental. Despite the majority of nicotine vapers becoming non-users, they are characterized by having more conduct problems and poorer mental health, and they more often used other tobacco products.

Do e-cigarettes attract youths who are otherwise unlikely to use addictive substances? Cross-sectional analyses of Dutch and Flemish secondary school students

INTRODUCTION

E-cigarettes are popular among youth. There are concerns that e-cigarettes attract youth that would otherwise not use addictive substances. While e-cigarettes are thought to be less harmful than tobacco, there is reason for caution. We examined to what extent adolescent e-cigarette users have characteristics associated with increased risk of substance use.

METHODS

We collected cross-sectional survey data in 2018 among 10 schools throughout the Netherlands and Belgium (N=2794; age 10-18 years). We examined differences in characteristics and behaviors between e-cigarette ever users and never users, and former users and current users. We also explored differences in use of flavors and use of nicotine.

RESULTS

Compared to never-users, e-cigarettes users more often were boys, older, had lower education level, non-Dutch or non-Belgian ethnicity, reported more combustible tobacco use, more smoking family members or family with problematic substance use, more smoking friends, more depressive symptoms, more impulsivity, more delinquent behavior, were more susceptible to smoking, had more positive smoking expectancies, and more ever use of substances. Users of non-tobacco flavored e-cigarettes and e-cigarettes without nicotine had fewer characteristics known to be related to an increased risk of substance use, compared to users of tobacco-flavored e-cigarettes and e-cigarettes with nicotine.

CONCLUSIONS

Adolescent e-cigarette users are more like youths who experiment with addictive substances compared to non-users. Thus, e-cigarettes users were more likely to use substances, regardless of whether they used e-cigarettes first. This may not be true for all types of e-cigarettes, as users of e-cigarettes without nicotine or with non-tobacco flavors were less like youths who experiment with substances.

Electronic cigarettes and health with special focus on cardiovascular effects: position paper of the European Association of Preventive Cardiology (EAPC)

BACKGROUND

Tobacco use is the single largest preventable risk factor for premature death of non-communicable diseases and the second leading cause of cardiovascular disease. In response to the harmful effects of tobacco smoking, the use of electronic cigarettes (e-cigarettes) has emerged and gained significant popularity over the past 15 years. E-cigarettes are promoted as safe alternatives for traditional tobacco smoking and are often suggested as a way to reduce or quit smoking. However, evidence suggests they are not harmless.

DISCUSSION

The rapid evolution of the e-cigarette market has outpaced the legislator's regulatory capacity, leading to mixed regulations. The increasing use of e-cigarettes in adolescents and young individuals is of concern. While the long-term direct cardiovascular effects of e-cigarettes remain largely unknown, the existing evidence suggests that the e-cigarette should not be regarded as a cardiovascular safe product. The contribution of e-cigarette use to reducing conventional cigarette use and smoking cessation is complex, and the impact of e-cigarette use on long-term cessation lacks sufficient evidence.

CONCLUSION

This position paper describes the evidence regarding the prevalence of e-cigarette smoking, uptake of e-cigarettes in the young, related legislations, cardiovascular effects of e-cigarettes and the impact of e-cigarettes on smoking cessation. Knowledge gaps in the field are also highlighted. The recommendations from the population science and public health section of the European Association of Preventive Cardiology are presented.

Association between electronic nicotine delivery systems and electronic non-nicotine delivery systems with initiation of tobacco use in individuals aged < 20 years. A systematic review and meta-analysis

BACKGROUND

This systematic review described the association between electronic nicotine delivery systems and electronic non-nicotine delivery systems (ENDS/ENNDS) use among non-smoking children and adolescents aged <20 years with subsequent tobacco use.

METHODS

We searched five electronic databases and the grey literature up to end of September 2020. Prospective longitudinal studies that described the association between ENDS/ENNDS use, and subsequent tobacco use in those aged < 20 years who were non-smokers at baseline were included. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess risk of bias. Data were extracted by two reviewers and pooled using a random-effects meta-analysis. We generated unadjusted and adjusted risk ratios (ARRs) describing associations between ENDS/ENNDS and tobacco use.

FINDINGS

A total of 36 publications met the eligibility criteria, of which 25 were included in the systematic review (23 in the meta-analysis) after exclusion of overlapping studies. Sixteen studies had high to moderate risk of bias. Ever users of ENDS/ENNDS had over three times the risk of ever cigarette use (ARR 3·01 (95% CI: 2·37, 3·82; p<0·001, I2: 82·3%), and current cigarette use had over two times the risk (ARR 2·56 (95% CI: 1·61, 4·07; p<0·001, I2: 77·3%) at follow up. Among current ENDS/ENNDS users, there was a significant association with ever (ARR 2·63 (95% CI: 1·94, 3·57; p<0·001, I2: 21·2%)), but not current cigarette use (ARR 1·88 (95% CI: 0·34, 10·30; p = 0·47, I2: 0%)) at follow up. For other tobacco use, ARR ranged between 1·55 (95% CI 1·07, 2·23) and 8·32 (95% CI: 1·20, 57·04) for waterpipe and pipes, respectively. Additionally, two studies examined the use of ENNDS (non-nicotine devices) and found a pooled adjusted RR of 2·56 (95% CI: 0·47, 13·94, p = 0.035).

CONCLUSION

There is an urgent need for policies that regulate the availability, accessibility, and marketing of ENDS/ENNDS to children and adolescents. Governments should also consider adopting policies to prevent ENDS/ENNDS uptake and use in children and adolescents, up to and including a ban for this group.

Reactions to sales restrictions on flavored vape products or all vape products among young adults in the US

SIGNIFICANCE

Despite increases in e-cigarette sales restrictions, support for sales restrictions and perceived impact on young adult use are unclear.

METHODS

We analyzed Feb-May 2020 data from a longitudinal study of 2,159 young adults (ages 18-34; Mage=24.75±4.71; n=550 past 30-day e-cigarette users) in 6 metropolitan areas (Atlanta, Boston, Minneapolis, Oklahoma City, San Diego, Seattle). We examined support for e-cigarette sales restrictions and - among e-cigarette users - perceived impact of flavored vape product and all vape product sales restrictions on e-cigarette and cigarette use (and potential correlates; i.e., e-cigarette/tobacco use, use-related symptoms/health concerns).

RESULTS

24.2% of e-cigarette users (and 57.6% of non-users) supported (strongly/somewhat) sales restrictions on flavored vape products; 15.1% of e-cigarette users (45.1% of non-users) supported complete vape product sales restrictions. If restricted to tobacco flavors, 39.1% of e-cigarette users reported being likely (very/somewhat) to continue using e-cigarettes (30.5% not at all likely); 33.2% were likely to switch to cigarettes (45.5% not at all). Considering complete vape product sales restrictions, equal numbers (~39%) were likely vs. not at all likely to switch to cigarettes. Greater policy support correlated with being e-cigarette non-users (aR 2=.210); among users, correlates included fewer days of use and greater symptoms and health concerns (aR 2=.393). If such restrictions were implemented, those less likely to report continuing to vape or switching to cigarettes used e-cigarettes on fewer days, were never-smokers, and indicated greater health concern (aR 2=.361).

CONCLUSIONS

While lower-risk users may be more positively impacted by such policies, other young adult user subgroups may not experience benefit.

IMPLICATIONS

Young adult e-cigarette users indicate low support for e-cigarette sales restrictions (both for flavored products and complete restrictions). Moreover, if vape product sales were restricted to tobacco flavors, 39.1% of users reported being likely to continue using e-cigarettes but 33.2% were likely to switch to cigarettes. If vape product sales were entirely restricted, e-cigarette users were equally likely to switch to cigarettes versus not (~40%). Those most likely to report positive impact of such policies being implemented were less frequent users, never-smokers, and those with greater e-cigarette-related health concerns. This research should be considered in future tobacco control initiatives.

Prospective association between use of electronic cigarettes and use of conventional cigarettes: a systematic review and meta-analysis

Objective

The aim of this systematic review and meta-analysis was to assess the association between e-cigarette use and subsequent initiation or recurrence of cigarette smoking.

Data sources

A systematic literature search was finalised on 11 November 2019 using PubMed (including MEDLINE), EMBASE, Cochrane Library, Scopus, PubMed Health, NICE Evidence Search, PROSPERO, CRD and PsycInfo.

Study selection

Studies were included if meeting the following criteria: reporting empirical results; longitudinal observational design with a minimum of 3 months of follow-up; including general population samples; allowing for the comparison between users and nonusers of e-cigarettes. Studies rated as having high risk of bias were excluded. Studies were independently assessed by at least two authors. The procedures described by PRISMA were followed, and the quality of evidence was rated using GRADE.

Data synthesis

30 longitudinal studies from 22 different cohorts assessing e-cigarette use among nonsmokers or never-smokers at baseline, and subsequent use of cigarette smoking at follow-up, were included in this review. A random-effects meta-analysis based on 89 076 participants showed a pooled unadjusted odds ratio (OR) of cigarette smoking among baseline nonsmoker e-cigarette users compared with nonusers of 4.68 (CI 3.64–6.02), while the adjusted OR was 3.37 (CI 2.68–4.24). These results were consistent irrespective of whether the outcome was measured as ever-smoking or as past 30-day smoking. The evidence was graded as moderate.

Conclusions

Use of e-cigarettes may predict the initiation or recurrence of cigarette smoking.

This meta-analysis shows that e-cigarette use increases the risk of future initiation or recurrence of cigarette smoking, even after adjusting for potential confounders, suggesting that e-cigarette use could be considered a predictor of subsequent smokinghttps://bit.ly/3buMccm

Use of waterpipes and other substances in adolescents: Prevalence and potential associations with mental and behavioral well-being, a cross-sectional study

INTRODUCTION

This study assess the prevalence and potential determinants (attitudes, behavioral and emotional conditions) associated with waterpipe tobacco smoking (WTS) and cigarette smoking in adolescents in public compulsory secondary schools.

METHODS

This was a cross-sectional study conducted in October 2017 in three secondary schools from Seville, Spain, among adolescents aged 12-18 years. We administered an ad hoc questionnaire to explore the demographic and clinical characteristics of students; in addition, it included questions on consumption of tobacco (waterpipe and/or cigarette), alcohol (usual consumption and/or drunkenness) and/or cannabis, and attitudes towards waterpipe tobacco smoking. We also administered a validated version of the Strengths and Difficulties Questionnaire (SDQ), which is used to screen children and adolescents with emotional and behavioral problems. An established usage of a substance was defined as weekly or daily use. A multivariate analysis was performed using binary logistic regression methods to determine the probability of established usage.

RESULTS

Of the 1135 adolescents, 72.1% lived with at least one smoker; the established usage was 13.4% for waterpipe; 9.2% for cigarettes and 3.2% for dual use. Of those with established usage of waterpipe, 38.2% had established alcohol usage, 12.7% were drunk weekly or daily, and 27.4% used cannabis. Students consolidating the consumption of waterpipes were three times more likely to have established cigarette use than those not having an established usage (OR=3.7; p=0.0005). The overall SDQ score increased the likelihood of established usage of both waterpipes and cigarettes (p=0.0005).

CONCLUSIONS

The probability of established usage of cigarettes (multivariate analysis) is associated with increasing age (course), cohabitation with smokers, established usage of waterpipe, established use of alcohol and a borderline score in the behavioral dimension (SDQ). Addiction to waterpipes among teens is significantly associated with their behavioral and emotional difficulties.

Association between electronic cigarette use and tobacco cigarette smoking initiation in adolescents: a systematic review and meta-analysis

BACKGROUND

This systematic review of prospective longitudinal primary studies sought to determine whether electronic cigarette (e-cigarette) use by teenagers who had never smoked conventional tobacco cigarettes (tobacco cigarettes) at baseline was associated with subsequently commencing tobacco cigarette smoking.

METHODS

The review followed the principles of a systematic review and meta-analysis. A key word search identified peer-reviewed articles published between 1 January 2005 and 2 October 2019 from seven bibliographic databases and one search engine. Using pre-prepared inclusion/exclusion criteria two researchers independently screened abstracts, and subsequently, full text papers. Selected articles were quality assessed in duplicate. Data on study participants characteristics, exposure and outcome measures were recorded in an adapted Cochrane Data Extraction Form. Feasibility assessment was done to detect clinical heterogeneity and choose an approach to meta-analysis. Analysis comprised pairwise random effects meta-analyses, and sensitivity and subgroup analyses.

RESULTS

From the 6619 studies identified, 14 one-off primary studies in 21 articles were suitable for inclusion. The participants ages ranged from 13 to 19 years and comprised teenagers based in Europe and North America. Nine of the 14 one-off studies, with follow-up periods between 4 and 24 months, met the criteria for inclusion in a meta-analysis of the association between ever use of e-cigarettes and subsequent initiation of tobacco cigarette use. Based on primary study adjusted odds ratios, our meta-analysis calculated a 4.06 (95% confidence interval (CI): 3.00-5.48, I2 68%, 9 primary studies) times higher odds of commencing tobacco cigarette smoking for teenagers who had ever used e-cigarettes at baseline, though the odds ratio were marginally lower (to 3.71 times odds, 95%CI: 2.83-4. 86, I2 35%, 4 primary studies) when only the four high-quality studies were analysed.

CONCLUSION

The systematic review found that e-cigarette use was associated with commencement of tobacco cigarette smoking among teenagers in Europe and North America, identifying an important health-related harm. Given the availability and usage of e-cigarettes, this study provides added support for urgent response by policymakers to stop their use by teenagers to decrease direct harms in this susceptible population group, as well as to conserve achievements in diminishing tobacco cigarette initiation.

E-cigarette use and combustible tobacco cigarette smoking uptake among non-smokers, including relapse in former smokers: umbrella review, systematic review and meta-analysis

OBJECTIVE

To review and summarise the current evidence on the uptake of combustible cigarette smoking following e-cigarette use in non-smokers-including never-smokers, people not currently smoking and past smokers-through an umbrella review, systematic review and meta-analysis.

DESIGN

Umbrella review, systematic review and meta-analysis.

DATA SOURCES

PubMed, Scopus, Web of Science, PsychINFO (Ovid), Medline (Ovid) and Wiley Cochrane Library up to April 2020.

RESULTS

Of 6225 results, 25 studies of non-smokers-never, not current and former smokers-with a baseline measure of e-cigarette use and an outcome measure of combustible smoking uptake were included. All 25 studies found increased risk of smoking uptake with e-cigarette exposure, although magnitude varied substantially. Using a random-effects model, comparing e-cigarette users versus non-e-cigarette users, among never-smokers at baseline the OR for smoking initiation was 3.25 (95% CI 2.61 to 4.05, I2 85.7%) and among non-smokers at baseline the OR for current smoking was 2.87 (95% CI 1.97 to 4.19, I2 90.1%). Among former smokers, smoking relapse was higher in e-cigarette users versus non-users (OR=2.40, 95% CI 1.50 to 3.83, I2 12.3%).

CONCLUSIONS

Across multiple settings, non-smokers who use e-cigarettes are consistently more likely than those avoiding e-cigarettes to initiate combustible cigarette smoking and become current smokers. The magnitude of this risk varied, with an average of around three times the odds. Former smokers using e-cigarettes have over twice the odds of relapse as non-e-cigarettes users. This study is the first to our knowledge to review and pool data on the latter topic.

PROSPERO REGISTRATION NUMBER

CRD42020168596.

Machine Learning-Based Nicotine Addiction Prediction Models for Youth E-Cigarette and Waterpipe (Hookah) Users

Despite the harmful effect on health, e-cigarette and hookah smoking in youth in the U.S. has increased. Developing tailored e-cigarette and hookah cessation programs for youth is imperative. The aim of this study was to identify predictor variables such as social, mental, and environmental determinants that cause nicotine addiction in youth e-cigarette or hookah users and build nicotine addiction prediction models using machine learning algorithms. A total of 6511 participants were identified as ever having used e-cigarettes or hookah from the National Youth Tobacco Survey (2019) datasets. Prediction models were built by Random Forest with ReliefF and Least Absolute Shrinkage and Selection Operator (LASSO). ReliefF identified important predictor variables, and the Davies–Bouldin clustering evaluation index selected the optimal number of predictors for Random Forest. A total of 193 predictor variables were included in the final analysis. Performance of prediction models was measured by Root Mean Square Error (RMSE) and Confusion Matrix. The results suggested high performance of prediction. Identified predictor variables were aligned with previous research. The noble predictors found, such as ‘witnessed e-cigarette use in their household’ and ‘perception of their tobacco use’, could be used in public awareness or targeted e-cigarette and hookah youth education and for policymakers.

National, regional, and global prevalence of cigarette smoking among women/females in the general population: a systematic review and meta-analysis

Background

This systematic and meta-analysis review aimed to provide an updated estimate of the prevalence of ever and current cigarette smoking in women, in geographic areas worldwide, and demonstrate a trend of the prevalence of smoking over time by using a cumulative meta-analysis.

Methods

Following PRISMA guidelines, we conducted a systematic review and meta-analysis of studies published on the prevalence of ever and current cigarette smoking in women. We searched PubMed, Web of Science (ISI), Scopus, and Ovid from January 2010 to April 2020. The reference lists of the studies included in this review were also screened. Data were reviewed and extracted independently by two authors. A random effects model was used to estimate the pooled prevalence of ever and current cigarette smoking in women. Sources of heterogeneity among the studies were determined using subgroup analysis and meta-regression.

Results

The pooled prevalence of ever and current cigarette smoking in women was 28% and 17%, respectively. The pooled prevalence of ever cigarette smoking in adolescent girls/students of the school, adult women, pregnant women, and women with the disease was 23%, 27%, 32%, and 38%, respectively. The pooled prevalence of ever cigarette smoking in the continents of Oceania, Asia, Europe, America, and Africa was 36%, 14%, 38%, 31%, and 32%, respectively.

Conclusions

The prevalence of cigarette smoking among women is very high, which is significant in all subgroups of adolescents, adults, and pregnant women. Therefore, it is necessary to design and implement appropriate educational programs for them, especially in schools, to reduce the side effects and prevalence of smoking among women.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12199-020-00924-y.

Further investigation of gateway effects using the PATH study

Background: Interest exists in whether youth e-cigarette use (“vaping”) increases risk of initiating cigarette smoking. Using Waves 1 and 2 of the US PATH study we previously reported adjustment for vaping propensity using Wave 1 variables explained about 80% of the unadjusted relationship. Here data from Waves 1 to 3 are used to avoid over-adjustment if Wave 1 vaping affected variables recorded then.

Methods: Main analyses M1 and M2 concerned Wave 2 never smokers who never vaped by Wave 1, linking Wave 2 vaping to Wave 3 smoking initiation, adjusting for predictors of vaping based on Wave 1 data using differing  propensity indices.  M3 was similar but derived the index from Wave 2 data.  Sensitivity analyses excluded Wave 1 other tobacco product users, included other product use as another predictor, or considered propensity for smoking or any tobacco use, not vaping. Alternative analyses used exact age (not previously available) as a confounder not grouped age, attempted residual confounding adjustment by modifying predictor values using data recorded later, or considered interactions with age.

Results: In M1, adjustment removed about half the excess OR (i.e. OR–1), the unadjusted OR, 5.60 (95% CI 4.52-6.93), becoming 3.37 (2.65-4.28), 3.11 (2.47-3.92) or 3.27 (2.57-4.16), depending whether adjustment was for propensity as a continuous variable, as quintiles, or the variables making up the propensity score. Many factors had little effect: using grouped or exact age; considering other products; including interactions; or using predictors of smoking or tobacco use rather than vaping. The clearest conclusion was that analyses avoiding over-adjustment explained about half the excess OR, whereas analyses subject to over-adjustment explained about 80%.

Conclusions: Although much of the unadjusted gateway effect results from confounding, we provide stronger evidence than previously of some causal effect of vaping, though doubts still remain about the completeness of adjustment.

Trends in the Age of Cigarette Smoking Initiation Among Young Adults in the US From 2002 to 2018

IMPORTANCE

Success in reducing the prevalence of adolescent smoking could reflect complete prevention of smoking initiation or a shift in the age of cigarette smoking initiation from adolescence into early adulthood.

OBJECTIVE

To assess trends in early adult (ages 18-23 years) vs adolescent (age <18 years) cigarette smoking initiation and transition to daily cigarette smoking from 2002 to 2018.

DESIGN, SETTING, AND PARTICIPANTS

Ages at initiation of smoking and the transition to daily smoking were ascertained from the National Survey on Drug Use and Health (2002-2018), an annual, population-based, repeated cross-sectional study representative of the US population. This cross-sectional analysis was restricted to young adults who completed the survey at ages 22 to 23 years during survey years 2002 to 2018 to limit potential age-related recall bias. Retrospectively collected age of cigarette smoking initiation was assessed among ever cigarette smokers; age of transition to daily smoking was assessed among ever daily cigarette smokers. Data analysis was performed from June 2019 to July 2020.

EXPOSURES

Calendar year of survey (2002 to 2018).

MAIN OUTCOMES AND MEASURES

The main outcomes were population-weighted cigarette smoking prevalence and cigarette smoking initiation and transition to daily smoking in adolescence (age <18 years) vs early adulthood (ages 18-23 years).

RESULTS

Among 71 756 young adults aged 22 to 23 years (38 226 women [50.5%]), ever cigarette smoking prevalence decreased from a population-weighted estimate of 74.6% (95% CI, 73.1%-75.9%) in 2002 to 51.4% (95% CI, 49.3%-53.5%) in 2018 (P < .001). Daily smoking prevalence rates similarly decreased from 41.1% (95% CI, 39.1%-43.1%) in 2002 to 20.2% (95% CI, 18.6%-21.8%) in 2018 (P < .001). However, among 48 015 ever smokers, the proportion initiating smoking in early adulthood (ages 18-23 years) increased over this time, from 20.6% (95% CI, 18.5%-22.8%) in 2002 to 42.6% (95% CI, 39.6%-45.7%) in 2018 (P < .001). Similarly, among 24 490 daily cigarette smokers, the proportion who transitioned to daily smoking in early adulthood increased from 38.7% (95% CI, 35.9%-41.6%) in 2002 to 55.9% (95% CI, 52.0%-59.8%) in 2018 (P < .001).

CONCLUSIONS AND RELEVANCE

A substantial proportion of beginning smokers and most new daily smokers are now young adults, reflecting a shift from adolescence to early adulthood, a population segment once considered beyond the critical risk period for cigarette smoking onset. Expanding the long-standing emphasis on adolescent surveillance and prevention in adolescence to include the young adult population is warranted.

Patterns of electronic cigarette, conventional cigarette, and hookah use and related passive exposure among adolescents in Kuwait: A cross-sectional study

INTRODUCTION

Use of tobacco products among adolescents is a major global public health concern. Given the changing landscape of tobacco product use and the lack of epidemiologic data to inform tobacco prevention and control strategies in Kuwait, this study sought to estimate the prevalence and patterns of electronic cigarette (e-cigarette), conventional cigarette, and hookah use among adolescents in Kuwait. Moreover, exposure to secondhand smoke (SHS) and secondhand aerosol (SHA) from e-cigarettes was assessed.

METHODS

This cross-sectional study enrolled high school students (n=1565; 16–19 years) across Kuwait. Current (past 30-day) use of e-cigarettes, conventional cigarettes, and hookah were assessed through self-reported data. Additionally, current (past 7-day) exposure to SHS and SHA in households and public places were ascertained. Associations were evaluated using Poisson regression, and adjusted prevalence ratios (APRs) and 95% confidence intervals (CIs) were estimated.

RESULTS

Overall, 26.4% (402/1525), 25.1% (383/1525), and 20.9% (318/1525) of the study participants were current e-cigarette users, conventional cigarette smokers, and hookah smokers, respectively. Current use of any tobacco product was reported by 35.1% (535/1525) of the total study participants. The prevalence of concurrent triple use of ‘e-cigarettes, conventional cigarettes, and hookah’ was estimated to be 12.8% (195/1525). Also, among the study participants, 41.9% (619/1479) were exposed to household SHS, 32.0% (469/1465) were exposed to household SHA, and 62.2% (916/1472) were exposed to SHS and/or SHA in public places. Male adolescents were more likely than females to be current e-cigarette users (APR=5.19; 95% CI: 4.09–6.57), conventional cigarette smokers (APR=5.42; 95% CI: 4.26–6.90), and hookah smokers (APR=3.43; 95% CI: 2.72– 4.32).

CONCLUSIONS

A substantial proportion of adolescents in Kuwait are currently using tobacco products and being exposed to SHS/SHA. The findings emphasize the need to continue monitoring all forms of tobacco product use among adolescents and to strengthen tobacco prevention and control programs.

Youth vaping and smoking and parental vaping: a panel survey

BACKGROUND

Concerns remain about potential negative impacts of e-cigarettes including possibilities that: youth e-cigarette use (vaping) increases risk of youth smoking; and vaping by parents may have impacts on their children's vaping and smoking behaviour.

METHODS

With panel data from 3291 youth aged 10-15 years from the 7th wave of the UK Understanding Society Survey (2015-2017), we estimated effects of youth vaping on youth smoking (ever, current and past year initiation), and of parental vaping on youth smoking and vaping, and examined whether the latter differed by parental smoking status. Propensity weighting was used to adjust for measured confounders and estimate average effects of vaping for all youth, and among youth who vaped. E-values were calculated to assess the strength of unmeasured confounding influences needed to negate our estimates.

RESULTS

Associations between youth vaping and youth smoking were attenuated considerably by adjustment for measured confounders. Estimated average effects of youth vaping on youth smoking were stronger for all youth (e.g. OR for smoking initiation: 32.5; 95% CI: 9.8-107.1) than among youth who vaped (OR: 4.4; 0.6-30.9). Relatively strong unmeasured confounding would be needed to explain these effects. Associations between parental vaping and youth vaping were explained by measured confounders. Estimates indicated effects of parental vaping on youth smoking, especially for youth with ex-smoking parents (e.g. OR for smoking initiation: 11.3; 2.7-46.4) rather than youth with currently smoking parents (OR: 1.0; 0.2-6.4), but these could be explained by relatively weak unmeasured confounding.

CONCLUSIONS

While measured confounding accounted for much of the associations between youth vaping and youth smoking, indicating support for underlying propensities, our estimates suggested residual effects that could only be explained away by considerable unmeasured confounding or by smoking leading to vaping. Estimated effects of youth vaping on youth smoking were stronger among the general youth population than among the small group of youth who actually vaped. Associations of parental vaping with youth smoking and vaping were either explained by measured confounding or could be relatively easily explained by unmeasured confounding.

Waterpipe use among the youth in Ghana: Lessons from the Global Youth Tobacco Survey (GYTS) 2017

INTRODUCTION

The Global Youth Tobacco Survey’s findings have been used to support Ghana’s tobacco control legislation, monitor tobacco use among the youth and also used in meeting various Articles of the World Health Organization (WHO) Framework Convention on Tobacco Control (FCTC). These Articles include: Article 8 (Protection for exposure to tobacco smoke); Article 12 (Education, communication, training and public awareness); Article 13 (Tobacco advertising, promotion, and sponsorship); Article 14 (Demand reduction measures concerning tobacco dependence and cessation); and Article 16 (Sales to and by minors). Among the four waves of GYTS in Ghana, the 2017 GYTS was the first to assess waterpipe smoking, through optional questions included in the GYTS questionnaire. We assessed sex, age and regional differentials in waterpipe smoking among the youth in Ghana, and also explored the association between the use of other tobacco products and waterpipe use.

METHODS

The GYTS employs a standardized methodology with self-administered questionnaires, consisting of core, optional, and country specific questions. Fourteen questions, out of the seventy-four (74) questions administered for the entire GYTS, assessed waterpipe tobacco smoking (WTS). Chi-squared test was used to assess sex, age, grade/form and regional differentials in waterpipe use. Furthermore, the association between smoking cigarettes, smokeless tobacco, electronic cigarettes and waterpipe smoking, was explored by employing a chi-squared test with a 5% significance level.

RESULTS

Of a total of 5664 students who participated in the study, 90.9% were aged 13–15 years. The respondents were almost equally distributed among males and females. Overall, 3.1% of the respondents had ever smoked waterpipe. The overall prevalence of current waterpipe use was 1.7%; with 2.1% in girls (95% CI: 0.9–4.7%) and 0.9% in boys (95% CI: 0.5–1.6%), p=0.033. Additionally, more than half (55.0%) of the current waterpipe users smoked three or more sessions per day. Surprisingly, close to half (46.9%) of the current waterpipe users smoked at home.

CONCLUSIONS

Waterpipe use, particularly among the female student population, represents an emerging tobacco epidemic and hence deserves immediate attention from authorities. This study revealed that waterpipe is being used among Junior High students in Ghana. Education on the health implications of waterpipe use should be intensified among the youth, to help minimize its use and to prevent its associated health harms.

Patterns of E-Cigarette Use Among Youth and Young Adults: Review of the Impact of E-Cigarettes on Cigarette Smoking

There is concern that e-cigarette use among youth and young adults (YAs) may lead to future cigarette or other combustible tobacco product use. A synthesis of the literature on this topic is needed because existing longitudinal studies are limited in number and not consistent in their conclusions. We conducted a search in PubMed through December 31, 2017 for peer-reviewed studies related to e-cigarette patterns of use. Of 588 relevant studies, 26 had a youth or YA sample, were longitudinal in design, and assessed e-cigarette use at baseline and cigarette smoking at follow-up. Most studies followed a sample over time and compared cigarette smoking at follow-up between baseline e-cigarette users and nonusers. Other studies examined the difference at follow-up in cigarette smoking status among smokers according to e-cigarette use at baseline. Results suggest that, among never smokers, e-cigarette use is associated with the future (6 months to 2.5 years) cigarette trial; however, firm conclusions cannot be drawn because of limitations including small sample size, measurement of experimental use (ie, ever use, past 30-day use) rather than established use, and inadequate controls for potentially confounding variables. Conclusions also cannot be drawn from studies examining the impact of e-cigarette use among smokers due to the limited number of studies and additional limitations. A comprehensive understanding of this literature is needed to inform policy makers and consumers for evidence-based decision-making and to guide future research on e-cigarette use among youth and young adults.

IMPLICATIONS

The present article provides a review of the impact of e-cigarette use on subsequent cigarette smoking among youth and YAs. Studies presented here suggest that e-cigarette use among nonsmokers is associated with subsequent cigarette smoking, but study designs are subject to numerous limitations. Future research should focus on addressing the characteristics that put youth and YAs at the risk of using either product and how appeal and accessibility of these products are related to product use in order to inform future policy-making.

Objectives, design and main findings until 2020 from the Rotterdam Study

The Rotterdam Study is an ongoing prospective cohort study that started in 1990 in the city of Rotterdam, The Netherlands. The study aims to unravel etiology, preclinical course, natural history and potential targets for intervention for chronic diseases in mid-life and late-life. The study focuses on cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. Since 2016, the cohort is being expanded by persons aged 40 years and over. The findings of the Rotterdam Study have been presented in over 1700 research articles and reports. This article provides an update on the rationale and design of the study. It also presents a summary of the major findings from the preceding 3 years and outlines developments for the coming period.

E-cigarette Product Characteristics and Subsequent Frequency of Cigarette Smoking

BACKGROUND

There is a dearth of evidence regarding the association of use of electronic cigarettes (e-cigarettes) with certain product characteristics and adolescent and young adult risk of unhealthy tobacco use patterns (eg, frequency of combustible cigarette smoking), which is needed to inform the regulation of e-cigarettes.

METHODS

Data were collected via an online survey of participants in the Southern California Children's Health Study from 2015 to 2016 (baseline) and 2016 to 2017 (follow-up) (N = 1312). We evaluated the association of binary categories of 3 nonmutually exclusive characteristics of the e-cigarette used most frequently with the number of cigarettes smoked in the past 30 days at 1-year follow-up. Product characteristics included device (vape pen and/or modifiable electronic cigarette [mod]), use of nicotine in electronic liquid (e-liquid; yes or no), and use for dripping (directly dripping e-liquid onto the device; yes or no).

RESULTS

Relative to never e-cigarette users, past-30-day e-cigarette use was associated with greater frequency of past-30-day cigarette smoking at follow-up. Among baseline past-30-day e-cigarette users, participants who used mods (versus vape pens) smoked >6 times as many cigarettes at follow-up (mean: 20.8 vs 1.3 cigarettes; rate ratio = 6.33; 95% confidence interval: 1.64-24.5) after adjustment for sociodemographic characteristics, baseline frequency of cigarette smoking, and number of days of e-cigarette use. After adjustment for device, neither nicotine e-liquid nor dripping were associated with frequency of cigarette smoking.

CONCLUSIONS

Baseline mod users (versus vape pen users) smoked more cigarettes in the past 30 days at follow-up. Regulation of e-cigarette device type warrants consideration as a strategy to reduce cigarette smoking among adolescents and young adults who vape.

Genetic Vulnerability for Smoking and Cannabis Use: Associations With E-Cigarette and Water Pipe Use

INTRODUCTION

Cigarette smoking and cannabis use are heritable traits and share, at least in part, a common genetic substrate. In recent years, the prevalence of alternative methods of nicotine intakes, such as electronic cigarette (e-cigarette) and water pipe use, has risen substantially. We tested whether the genetic vulnerability underlying cigarettes smoking and cannabis use explained variability in e-cigarette and water pipe use phenotypes, as these vaping methods are alternatives for smoking tobacco cigarettes and joints.

METHODS

On the basis of the summary statistics of the International Cannabis Consortium and the Tobacco and Genetics Consortium, we generated polygenic risk scores (PRSs) for smoking and cannabis use traits, and used these to predict e-cigarette and water pipe use phenotypes in a sample of 5025 individuals from the Netherlands Twin Register.

RESULTS

PRSs for cigarettes per day were positively associated with lifetime e-cigarette use and early initiation of water pipe use, but only in ex-smokers (odds ratio = 1.43, R2 = 1.56%, p = .011) and never cigarette smokers (odds ratio = 1.35, R2 = 1.60%, p = .013) respectively.

CONCLUSIONS

Most associations of PRSs for cigarette smoking and cannabis use with e-cigarette and water pipe use were not significant, potentially due to a lack of power. The significant associations between genetic liability to smoking heaviness with e-cigarette and water pipe phenotypes are in line with studies indicating a common genetic background for substance-use phenotypes. These associations emerged only in nonsmokers, and future studies should investigate the nature of this observation.

IMPLICATIONS

Our study showed that genetic vulnerability to smoking heaviness is associated with lifetime e-cigarette use and age at initiation of water pipe use. This finding has implications for the current debate on whether alternative smoking methods, such as usage of vaping devices, predispose to smoking initiation and related behaviors.

Use of Electronic Cigarettes in European Populations: A Narrative Review

The increasing popularity of electronic cigarettes in past decades has aroused public health concern. This study aims to review the literature on the prevalence of e-cigarette use among the general adult and young populations in Europe. We searched Medline and Google Scholar from September 2019, and included "prevalence of e-cigarettes", "electronic cigarettes" or "e-cigarettes", and "electronic nicotine delivery system" or "vaping". The prevalence of current e-cigarette use ranged from 0.2% to 27%, ever-use ranged from 5.5% to 56.6% and daily use ranged from 1% to 2.9%. Current smokers of conventional cigarettes showed the highest prevalence for the use of e-cigarettes, ranging from 20.4% to 83.1%, followed by ex-smokers, with ranges from 7% to 15%. The following socio-demographic factors were associated with a higher chance of using e-cigarettes: male sex and younger age groups; results for economic status were inconclusive. In European countries, there is a higher prevalence of e-cigarette use among males, adolescents and young adults, smokers of conventional cigarettes, and former smokers.

Is e-cigarette use in non-smoking young adults associated with later smoking? A systematic review and meta-analysis

OBJECTIVE

The aim of this review was to investigate whether e-cigarette use compared with non-use in young non-smokers is associated with subsequent cigarette smoking.

DATA SOURCES

PubMed, Embase, Web of Science, Wiley Cochrane Library databases, and the 2018 Society for Research on Nicotine and Tobacco and Society for Behavioural Medicine conference abstracts.

STUDY SELECTION

All studies of young people (up to age 30 years) with a measure of e-cigarette use prior to smoking and an outcome measure of smoking where an OR could be calculated were included (excluding reviews and animal studies).

DATA EXTRACTION

Independent extraction was completed by multiple authors using a preprepared extraction form.

DATA SYNTHESIS

Of 9199 results, 17 studies were included in the meta-analysis. There was strong evidence for an association between e-cigarette use among non-smokers and later smoking (OR: 4.59, 95% CI: 3.60 to 5.85) when the results were meta-analysed in a random-effects model. However, there was high heterogeneity (I2 =88%).

CONCLUSIONS

Although the association between e-cigarette use among non-smokers and subsequent smoking appears strong, the available evidence is limited by the reliance on self-report measures of smoking history without biochemical verification. None of the studies included negative controls which would provide stronger evidence for whether the association may be causal. Much of the evidence also failed to consider the nicotine content of e-liquids used by non-smokers meaning it is difficult to make conclusions about whether nicotine is the mechanism driving this association.

Socioeconomic patterning of vaping by smoking status among UK adults and youth

BACKGROUND

Smoking contributes significantly to socioeconomic health inequalities. Vaping has captured much interest as a less harmful alternative to smoking, but may be harmful relative to non-smoking. Examining inequalities in vaping by smoking status, may offer insights into potential impacts of vaping on socioeconomic inequalities in health.

METHODS

Data were from 3291 youth (aged 10-15) and 35,367 adults (aged 16+) from wave 7 (2015-17) of the UK Household Longitudinal Study. In order to adjust for biases that could be introduced by stratifying on smoking status, marginal structural models were used to estimate controlled direct effects of an index of socioeconomic disadvantage (incorporating household education, occupation and income) on vaping by smoking status (among adults and youth), adjusting for relevant confounders and for selection into smoking states. We also estimated controlled direct effects of socioeconomic disadvantage on being an ex-smoker by vaping status (among adult ever-smokers; n = 18,128).

RESULTS

Socioeconomic disadvantage was associated with vaping among never smoking youth (OR for a unit increase in the socioeconomic index: 1.17; 95%: 1.03-1.34), and among ex-smoking adults (OR: 1.17; 95% CI: 1.09-1.26), with little to no association among never smoking (OR: 0.98; 95% CI: 0.91-1.07) and current smoking (OR: 1.00; 95% CI: 0.93-1.07) adults. Socioeconomic disadvantage was also associated with reduced odds of being an ex-smoker among adult ever-smokers, but this association was moderately weaker among those who vaped (OR: 0.88; 95% CI: 0.82-0.95) than those who did not (OR: 0.82; 95% CI: 0.80-0.84; p-value for difference = 0.081).

CONCLUSIONS

Inequalities in vaping among never smoking youth and adult ex-smokers, suggest potential to widen health inequalities, while weaker inequalities in smoking cessation among adult vapers indicate e-cigarettes could help narrow inequalities. Further research is needed to understand the balance of these opposing potential impacts, and how any benefits can be maximised whilst protecting the vulnerable.

Risk factors associated with subsequent initiation of cigarettes and e-cigarettes in adolescence: A structural equation modeling approach

BACKGROUND

Previous youth tobacco research has identified multiple correlated risk factors for initiation of cigarette and e-cigarette use; whether these factors are independently associated with initiation is not known, due to challenges with disentangling the independent effects of these correlated risk factors.

METHODS

Students in 11th/12th grade enrolled in the Southern California Children's Health Study were surveyed in 2014 (baseline) and again in 2015 (N = 1553). Structural equation models (SEM) were developed to investigate associations of susceptibility, marketing, and the social environment (as latent factors), and other tobacco use at baseline with cigarette or e-cigarette initiation between baseline and follow-up. Analyses were restricted to baseline never cigarette users (N = 1293) for models evaluating cigarette initiation, and to never e-cigarette users (N = 1197) for models evaluating e-cigarette initiation.

RESULTS

In fully-adjusted prospective SEM models, latent factors for cigarette susceptibility, marketing, and the social environment, along with ever e-cigarette use and ever hookah use at baseline were independently associated with cigarette initiation between baseline and follow-up (P < 0.05). Similarly, latent factors for e-cigarette susceptibility, marketing, and the social environment, along with ever hookah use at baseline were associated with e-cigarette initiation between baseline and follow-up (P < 0.05); however, cigarette use at baseline was not associated with e-cigarette initiation in SEM models (P = 0.16).

CONCLUSIONS

We identified independent effects of multiple risk factors in SEM models on initiation of cigarettes and e-cigarettes. E-cigarette use was associated with cigarette initiation, but cigarette use was not associated with e-cigarette initiation in fully adjusted models. Research to identify underlying causal mechanisms is warranted.

Ethnic Differences in Patterns of Cigarette and E-Cigarette Use Over Time Among Adolescents

PURPOSE

Little is known about whether adolescent cigarette and e-cigarette use patterns over time differ by ethnicity.

METHODS

Data were pooled from three prospective cohort studies of adolescents in California and Connecticut (baseline: 2013-2014; 12-month follow-up: 2014-2015; N = 6,258). Adjusted polytomous regression models evaluated the association of baseline exclusive ever e-cigarette use, exclusive ever cigarette use, ever use of both e-cigarettes and cigarettes (dual use) with past 30-day use at follow-up (exclusively e-cigarettes, exclusively cigarettes, dual use; no use at baseline/follow-up were the referent groups). Interaction analyses evaluated differences by race/ethnicity (Hispanic white [HW], non-Hispanic white [NHW], Other).

RESULTS

A significant global interaction was observed for the association of baseline with follow-up tobacco use by ethnicity (p = .009). Among NHW participants, ever e-cigarette or cigarette users at baseline (vs. never users) had significantly higher odds of every past 30-day use tobacco use pattern at follow-up. Among HW participants, compared with never users, exclusive e-cigarette users at baseline had increased odds of continued e-cigarette use (OR_{exclusive e-cigarettes} = 5.22; 95% confidence interval [CI]: 3.50, 7.79; OR_{dual use} = 3.64; 95% CI: 1.62, 8.18) but not of transition to exclusive cigarette use at follow-up (OR_{exclusive cigarettes} = 1.27; 95% CI: .47, 3.46), and HW exclusive cigarette users at baseline had greater odds of continued cigarette use (OR_{exclusive e-cigarettes} = 12.3; 95% CI: 5.87, 25.8; OR_{dual use} = 3.82; 95% CI: 1.06, 13.7) but not of transition to exclusive e-cigarette use at follow-up (OR_{exclusive cigarettes} = 1.61; 95% CI: .62, 4.18).

CONCLUSIONS

Findings that NHW youth report more transitional use patterns and HW youth report more stable use patterns suggest a potential for differential impacts of e-cigarettes, by ethnicity, in increasing subsequent transition to or cessation from cigarette smoking.

Nicotine matters in predicting subsequent smoking after e-cigarette experimentation: A longitudinal study among Finnish adolescents

BACKGROUND

Several studies indicate an association between e-cigarette use and subsequent smoking among youth. However, most previous studies lack measures of the nicotine content of e-liquid and have not usually measured regular smoking.

METHODS

We tested the association between e-cigarette use, with and without nicotine, and subsequent daily use of conventional cigarettes and nicotine e-cigarettes among study population of 3474 students. A survey was conducted in lower secondary schools of the Helsinki metropolitan area, Finland, with 15 - 16-year-olds in 2014 (baseline) and in upper secondary schools in 2016 when the cohort was 17 - 18-year-olds (follow-up). Firth logistic regression and generalized linear mixed models (GLMM) were used.

RESULTS

Of students, 25% had experimented with nicotine e-cigarettes at baseline and 40% at follow-up. Among baseline never-smokers, experimentation with or use of nicotine e-cigarettes predicted the uptake of daily smoking at follow-up (AOR 2.92; 95% CI 1.09-7.85), but baseline experimentation with non-nicotine e-cigarettes did not when compared with the non-e-cigarette experimenters. Nicotine e-cigarette experimentation at baseline predicted daily nicotine e-cigarette use at follow-up (AOR 2.96; 95% CI 1.22-7.22). Non-nicotine e-cigarette experimentation at baseline did not predict statistically significantly daily nicotine e-cigarette use at follow-up (AOR 3.13; 95% CI 0.98-10.02). The small number of cases may have diminished the statistical significance.

CONCLUSIONS

The findings suggest that experimentation with nicotine e-cigarettes serves as a gateway to subsequent use of conventional cigarettes as well as nicotine e-cigarettes. Our results support the actions to limit youths' access to e-cigarettes in order to prevent nicotine addiction.

Investigating gateway effects using the PATH study

BACKGROUND

A recent meta-analysis of nine cohort studies in youths reported that baseline ever e-cigarette use strongly predicted cigarette smoking initiation in the next 6-18 months, with an adjusted odds ratio of 3.62 (95% confidence interval 2.42-5.41).  A recent review of e-cigarettes agreed there was substantial evidence for this "gateway effect".  However, the number of confounders considered in the studies was limited, so we investigated whether the effect might have resulted from inadequate adjustment, using Waves 1 and 2 of the Population Assessment of Tobacco and Health study.

METHODS

Our main analyses considered Wave 1 never cigarette smokers who, at Wave 2, had information available on smoking initiation.  We constructed a propensity score for ever e-cigarette use from Wave 1 variables, using this to predict ever cigarette smoking.  Sensitivity analyses accounted for use of other tobacco products, linked current e-cigarette use to subsequent current smoking, or used propensity scores for ever smoking or ever tobacco product use as predictors.  We also considered predictors using data from both waves to attempt to control for residual confounding from misclassified responses.

RESULTS

Adjustment for propensity dramatically reduced the unadjusted odds ratio (OR) of 5.70 (4.33-7.50) to 2.48 (1.85-3.31), 2.47 (1.79-3.42) or 1.85 (1.35-2.53), whether adjustment was made as quintiles, as a continuous variable or for the individual variables.  Additional adjustment for other tobacco products reduced this last OR to 1.59 (1.14-2.20).  Sensitivity analyses confirmed adjustment removed most of the gateway effect.  Control for residual confounding also reduced the association.

CONCLUSIONS

We found that confounding is a major factor, explaining most of the observed gateway effect.  However, our analyses are limited by small numbers of new smokers considered and the possibility of over-adjustment if taking up e-cigarettes affects some predictor variables.  Further analyses are intended using Wave 3 data which should avoid these problems.

Investigating gateway effects using the PATH study

BACKGROUND

A recent meta-analysis of nine cohort studies in youths reported that baseline ever e-cigarette use strongly predicted cigarette smoking initiation in the next 6-18 months, with an adjusted odds ratio of 3.62 (95% confidence interval 2.42-5.41).  A recent review of e-cigarettes agreed there was substantial evidence for this "gateway effect".  However, the number of confounders considered in the studies was limited, so we investigated whether the effect might have resulted from inadequate adjustment, using Waves 1 and 2 of the Population Assessment of Tobacco and Health study.

METHODS

Our main analyses considered Wave 1 never cigarette smokers who, at Wave 2, had information available on smoking initiation.  We constructed a propensity score for ever e-cigarette use from Wave 1 variables, using this to predict ever cigarette smoking.  Sensitivity analyses accounted for use of other tobacco products, linked current e-cigarette use to subsequent current smoking, or used propensity scores for ever smoking or ever tobacco product use as predictors.  We also considered predictors using data from both waves to attempt to control for residual confounding from misclassified responses.

RESULTS

Adjustment for propensity dramatically reduced the unadjusted odds ratio (OR) of 5.70 (4.33-7.50) to 2.48 (1.85-3.31), 2.47 (1.79-3.42) or 1.85 (1.35-2.53), whether adjustment was made as quintiles, as a continuous variable or for the individual variables.  Additional adjustment for other tobacco products reduced this last OR to 1.59 (1.14-2.20).  Sensitivity analyses confirmed adjustment removed most of the gateway effect.  Control for residual confounding also reduced the association.

CONCLUSIONS

We found that confounding is a major factor, explaining most of the observed gateway effect.  However, our analyses are limited by small numbers of new smokers considered and the possibility of over-adjustment if taking up e-cigarettes affects some predictor variables.  Further analyses are intended using Wave 3 data which should avoid these problems.

E-cigarette use and respiratory disorder in an adult sample

OBJECTIVES

Little evidence is available on the association of e-cigarettes with health indices. We investigated the association of e-cigarette use with diagnosed respiratory disorder among adults in data from the Behavioral Risk Factor Surveillance Survey (BRFSS).

METHODS

The 2016 Hawaii BRFSS, a cross-sectional random-dial telephone survey, had 8087 participants; mean age was 55 years. Items asked about e-cigarette use, cigarette smoking, and being diagnosed by a health professional with (a) asthma or (b) chronic obstructive pulmonary disease. Multivariable analyses tested associations of e-cigarette use with the respiratory variables controlling for smoking and for demographic, physical, and psychosocial variables.

RESULTS

Controlling for the covariates and smoking there was a significant association of e-cigarette use with chronic pulmonary disorder in the total sample (AOR = 2.58, CI 1.36-4.89, p < 0.01) and a significant association with asthma among nonsmokers (AOR = 1.33, CI 1.00-1.77, p <  0.05). The associations were stronger among nonsmokers than among smokers. Results were similar for analyses based on relative risk and absolute risk. There was also a greater likelihood of respiratory disorder for smokers, females, and persons with overweight, financial stress, and secondhand smoke exposure.

CONCLUSIONS

This is the first study to show a significant independent association of e-cigarette use with chronic respiratory disorder. Several aspects of the data are inconsistent with the possibility that e-cigarettes were being used for smoking cessation by persons with existing respiratory disorder. Theoretical mechanisms that might link e-cigarettes use and respiratory symptoms are discussed.

Considerations related to vaping as a possible gateway into cigarette smoking: an analytical review

Background: Toxicant levels are much lower in e-cigarettes than cigarettes. Therefore, introducing e-cigarettes into the market seems likely to reduce smoking-related diseases (SRD). However, vaping might provide a gateway into cigarette smoking for those who otherwise would never have smoked, a concern fuelled by cohort studies showing vaping predicts subsequent smoking initiation in young people. Methods: In this discussion paper, we consider various aspects of the gateway issue in youths. We provide a descriptive critical review of results from prospective studies relating to the gateway effect and the extent to which the studies considered other potential confounding variables associated with smoking initiation. We then estimate the effects of omitting a confounding variable, or misclassifying it, on the association between vaping and subsequent smoking initiation, and determine how the prevalence of smoking might be affected by any true gateway effects of vaping. Finally, we examine trends in e-cigarette and smoking prevalence in youths based on national surveys. Results: First, we demonstrate that although studies report that vaping significantly predicts smoking initiation following adjustment for various other predictors, the sets of predictors considered are quite incomplete. Furthermore, no study considered residual confounding arising from inaccurate measurement of predictors. More precise adjustment may substantially reduce the association. Second, we show any true gateway effect would likely affect smoking prevalence only modestly. Third, we show smoking prevalence in U.S. and U.K. youths in 2014-2016 declined somewhat faster than predicted by the preceding trend; a substantial gateway effect suggests the opposite. Finally, we argue that even if some gateway effect exists, introducing e-cigarettes still likely reduces SRDs. Conclusions: Given that the existence of any true gateway effect in youth is not yet clearly demonstrated the population health impact of introducing e-cigarettes is still likely to be beneficial.

Considerations related to vaping as a possible gateway into cigarette smoking: an analytical review

Background: Toxicant levels are much lower in e-cigarettes than cigarettes. Therefore, introducing e-cigarettes into the market seems likely to reduce smoking-related diseases (SRD). However, vaping might provide a gateway into cigarette smoking for those who otherwise would never have smoked, a concern fueled by cohort studies showing vaping predicts subsequent smoking initiation in young people. Methods: In this discussion paper, we consider various aspects of the gateway issue in youths. We provide a descriptive critical review of results from prospective studies relating to the gateway effect and the extent to which the studies considered other potential confounding variables associated with smoking initiation.  We then estimate the effects of omitting a confounding variable, or misclassifying it, on the association between vaping and subsequent smoking initiation, and determine how the prevalence of smoking might be affected by any true gateway-in effects of vaping. Finally, we examine trends in e-cigarette and smoking prevalence in youths based on national surveys. Results:  First, we demonstrate that although studies report that vaping significantly predicts smoking initiation following adjustment for various other predictors, the sets of predictors considered are quite incomplete. Furthermore, no study considered residual confounding arising from inaccurate measurement of predictors. More precise adjustment may substantially reduce the association. Second, we show any true gateway effect would likely affect smoking prevalence only modestly. Third, we show smoking prevalence in U.S. and U.K. youths in 2014-2016 declined somewhat faster than predicted by the preceding trend; a substantial gateway effect suggests the opposite. Finally, we argue that even if some gateway effect exists, introducing e-cigarettes still likely reduces SRDs. Conclusions: We have shown that the existence of any true gateway-in effect in youth is not yet clearly demonstrated and that the population health impact of introducing e-cigarettes is still likely to be beneficial.

Considerations related to vaping as a possible gateway into cigarette smoking: an analytical review

Background: Compared to cigarette smoking, e-cigarette use is likely to present a reduced risk of smoking-related disease (SRD). However, several studies have shown that vaping predicts smoking initiation and might provide a gateway into smoking for those who otherwise would never have smoked. This paper considers various aspects of the gateway issue in youths. Methods: Here, we reviewed studies (N=15) of the gateway effect examining how extensively they accounted for confounders associated with smoking initiation in youths. We estimated how omitting a confounder, or misclassifying it, might bias the association between vaping and smoking initiation. We assessed how smoking prevalence might be affected by any true gateway effect, and examined trends in youth smoking and e-cigarette use from national surveys. Results: The list of smoking predictors adjusted for in studies reporting a significant gateway effect is not comprehensive, rarely considering internalising/externalising disorders, outcome expectancies, school performance, anxiety, parental smoking and peer attitudes. Furthermore, no study adjusted for residual confounding from inaccurately measured predictors. Better adjustment may substantially reduce the estimated gateway effect. Calculations showed that as any true gateway effects increase, there are much smaller increases in smoking prevalence, and that gateway effects increase only if initiating vaping is more frequent than initiating smoking. These effects on prevalence also depend on the relative odds of quitting vs. initiation. Data from five surveys in US/UK youths all show that, regardless of sex and age, smoking prevalence in 2014-2016 declined faster than predicted by the preceding trend, suggesting the absence of a substantial gateway effect. We also present arguments suggesting that even with some true gateway effect, introducing e-cigarettes likely reduces SRD risk. Conclusions: A true gateway effect in youths has not yet been demonstrated. Even if it were, e-cigarette introduction may well have had a beneficial population health impact.

E-cigarette Use and Subsequent Smoking Frequency Among Adolescents

: media-1vid110.1542/5839992666001PEDS-VA_2018-0486Video Abstract BACKGROUND AND OBJECTIVES: Electronic cigarette (e-cigarette) use is associated with cigarette initiation among adolescents. However, it is unclear whether e-cigarette use is associated with more frequent cigarette use after initiation. Also, the extent to which cigarette or dual cigarette and e-cigarette users transition to exclusive e-cigarette use or to the nonuse of either product is not yet known.

METHODS

Data were pooled from 3 prospective cohort studies in California and Connecticut (baseline: 2013-2014; follow-up: 2014-2016; N = 6258). Polytomous regression models were used to evaluate the association of baseline e-cigarette use (never or ever) with cigarette use frequency at follow-up (experimental: initiation but no past-30-day use; infrequent: 1-2 of the past 30 days; frequent: 3-5 or more of the past 30 days). Polytomous regression models were also used to evaluate transitions between baseline ever or past-30-day single or dual product use and past-30-day single or dual product use at follow-up.

RESULTS

Among baseline never smokers, e-cigarette users had greater odds of subsequent experimental (odds ratio [OR] = 4.58; 95% confidence interval [CI]: 3.56-5.88), infrequent (OR = 4.27; 95% CI: 2.75-6.62) or frequent (OR = 3.51; 95% CI: 1.97-6.24) cigarette use; the 3 OR estimates were not significantly different. Baseline past-30-day exclusive cigarette use was associated with higher odds at follow-up of exclusive cigarette or dual product use than of exclusive e-cigarette use.

CONCLUSIONS

Tobacco control policy to reduce adolescent use of both e-cigarettes and cigarettes is needed to prevent progression to more frequent tobacco use patterns and reduce combustible cigarette use (with or without concurrent e-cigarette use) to lessen the adverse public health impact of e-cigarettes.