Electronic Cigarette Use and Smoking Initiation in Taiwan: Evidence from the First Prospective Study in Asia

Association of Smoking Media Literacy with Vietnamese and South Korean Adolescents' Susceptibility to Smoking

Studies on how smoking media literacy (SML) is associated with susceptibility to smoking among adolescents in South Korea and Vietnam are scarce. Thus, we examined the association of SML with susceptibility to smoking among adolescents in these countries to initiate a collaborative global health program. In total, 460 adolescents (Vietnam: 277, South Korea: 183) aged 15-18 completed an online cross-sectional survey. SML was measured using the 15-item SML scale. Susceptibility to smoking was measured by three questions on future smoking and if offered a cigarette by a friend. A multiple logistic regression model explored the association of SML with susceptibility to smoking. The study revealed that higher SML was significantly associated with lower susceptibility to smoking among Vietnamese, but not South Korean adolescents. Further studies to identify pathways between other factors associated with SML and susceptibility to smoking are needed to develop culture-specific intervention strategies for smoking prevention.

Longitudinal bidirectional association between youth electronic cigarette use and tobacco cigarette smoking initiation in Thailand

INTRODUCTION

This study quantifies the longitudinal association between e-cigarette use and subsequent conventional cigarette initiation and vice versa among Thai youths.

METHODS

Data from a longitudinal survey of 6045 Thai seventh grade students with baseline in 2019 and the 12-month follow-up in 2020 were analysed using complex survey multivariate logistic regressions to assess whether e-cigarette use was associated with subsequent cigarette smoking (ever, current and dual product users at follow-up) among baseline never smokers.

RESULTS

Consistent with prior findings from other countries, among those who had never smoked cigarettes at baseline, ever e-cigarette users were more likely to try cigarette smoking (adjusted OR 4.44; 95% CI 2.23 to 8.86; p<0.001), or become dual users (adjusted OR 5.31; 95% CI 2.63 to 10.74; p<0.001) 1 year later. Baseline current e-cigarette users were more likely to become ever smokers (adjusted OR 5.37; 95% CI 1.82 to 15.90; p=0.005), current smokers (OR 3.92; 95% CI 1.69 to 9.14; p=0.003) and dual product users (adjusted OR 6.96; 95% CI 1.54 to 31.38; p=0.015) at the 12-month follow-up than non-e-cigarette users. Similarly, among never e-cigarette users at baseline, ever cigarette smoking were more likely to try e-cigarettes (adjusted OR 3.38; 95% CI 1.66 to 6.88; p=0.002), currently use e-cigarettes (adjusted OR 2.75; 95% CI 1.47 to 5.13; p=0.003) and currently use both e-cigarettes and cigarettes (adjusted OR 4.87; 95% CI 2.92 to 8.13; p<0.001) at the follow-up than never smokers. Among never e-cigarette users at baseline, current-cigarette smoking were more likely to try e-cigarettes (adjusted OR 6.21; 95% CI 2.58 to 14.95; p<0.001), currently use e-cigarettes (adjusted OR 2.80; 95% CI 1.27 to 6.14; p=0.014) and currently use both e-cigarettes and cigarettes (adjusted OR 7.70; 95% CI 3.45 to 17.19; p<0.001) at the follow-up than never smokers.

CONCLUSIONS

This longitudinal study in Asian low-income and middle-income countries supports the prospective association of youth e-cigarette use with subsequent smoking initiation and youth cigarette use with subsequent e-cigarette initiation that is similar to that observed in high-income Western countries.

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.

Prediction and potential risk factors for electronic cigarette use behaviors among adolescents: a pilot study in Chiayi, Taiwan

Introduction

Electronic cigarette (e-cigarette) use among adolescents has become increasingly common; therefore, effectively reducing adolescent e-cigarette use is an urgent issue. We aimed to predict and identify potential factors related to adolescent e-cigarette use behaviors.

Methods

This cross-sectional study was conducted using anonymous questionnaires given to Taiwanese high school students in 2020. Approximately 1,289 adolescent students completed questions on e-cigarette use, personal characteristics, family environment, and substances used. We performed multivariate logistic regression analyses to assess the model's predictive performance in terms of the area under the receiver operating characteristic curve.

Results

We found that 9.3% of adolescent students used e-cigarettes. Tobacco smoking, close friends' reactions to e-cigarette use, and the use of other substances were independent risk factors for adolescent e-cigarette use. Furthermore, relative to tobacco nonuse, tobacco use and tobacco smoking dependence had odds ratios of 76.49 and 113.81, respectively. The predictive accuracy of adolescent e-cigarette use from personal characteristics, family environment, and substance use status was 73.13, 75.91, and 93.80%, respectively.

Conclusion

The present study highlights the need for early prevention of e-cigarette use among adolescents, particularly those with a history of using tobacco and other substances and those who have close friends with positive attitudes towards e-cigarette use.

E-cigarettes and smoking cessation among adolescent smokers

Smokers of any age can reap substantial health benefits from quitting or reducing their smoking. E-cigarettes have been promoted as a potentially promising product for tobacco harm reduction because e-cigarettes deliver nicotine vapor without many of the hazardous chemical combustion byproducts produced by combustible cigarette smoking. However, there remains an ongoing debate on whether the use of e-cigarettes is effective in combustible cigarette smoking cessation or reduction in both adolescents and adults. Our study uses data from the 2015 (baseline) and from the 2017 (follow-up) waves of the Taiwan Adolescent to Adult Longitudinal Study (TAALS), which is a large nationwide representative cohort study of health behaviors among adolescents in Taiwan. We analyzed the data using logistic regression and multivariate regression with a post-stratification weighting procedure. Among the 474 adolescent combustible cigarette users at baseline, the use of e-cigarettes had no association with smoking cessation (aRR = 0.99, 95% CI = 0.66, 1.50). Furthermore, the use of e-cigarettes was also not associated with change in combustible cigarette consumption among all adolescent combustible cigarette users at follow-up (Coef. = 0.62, 95% CI =  - 36.85, 38.09). In summary, our findings suggest that e-cigarettes may not aid tobacco control among adolescent smokers. Policy makers should be cautious of the potential harms that e-cigarette may bring to young people when they are developing e-cigarette regulations.

E-Cigarette Markets and Policy Responses in Southeast Asia: A Scoping Review

BACKGROUND

The global e-cigarette market has proliferated and is increasingly dominated by transnational tobacco companies. While Southeast Asian countries have received relatively little attention in e-cigarette research, the region represents an area of potentially untapped growth for the industry. We review the e-cigarette situation in Southeast Asia in terms of the e-cigarette markets, advertising and promotion of e-cigarettes, reported health impacts of e-cigarette use, and policy responses in the region.

METHODS

We examined e-cigarette market data from the Euromonitor Global Market Information Database (GMID) Passport database, searched in the academic literature, grey literature and news archives for any reports or studies of e-cigarette related diseases or injuries, e-cigarette marketing, and e-cigarette policy responses in Southeast Asian countries, and browsed the websites of online e-cigarette retailers catering to the region's active e-cigarette markets.

RESULTS

In 2019, e-cigarettes were sold in six Southeast Asian markets with a total market value of $595 million, projected to grow to $766 million by 2023. E-commerce is a significant and growing sales channel in the region, with most of the popular or featured brands in online shops originating from China. Southeast Asian youth are targeted with a wide variety of flavours, trendy designs and point of sale promotions, and several e-cigarette related injuries and diseases have been reported in the region. Policy responses vary considerably between countries, ranging from strict bans to no or partial regulations.

CONCLUSION

Although Southeast Asia's e-cigarette market is relatively nascent, this is likely to change if transnationals invest more heavily in the region. Populous countries with weak e-cigarette regulations, notably Indonesia, Malaysia, Vietnam and the Philippines, are desirable targets for the transnationals. Regulatory action is needed to prevent e-cigarette use from becoming entrenched into these societies, especially among young people.

Bidirectionality of smoking and depression in adolescents: a systematic review

INTRODUCTION

Recently, evidence has been accumulating that both smoking and mental health disorders are continuously increasing among adolescents. This systematic review elucidates the research into evidence of the direction of the association and risk factors influencing the relationship between smoking and depression. We also highlight recent studies on the effects of electronic cigarettes and developments on the association between depression and smoking.

METHODS

A literature search was conducted on databases including PubMed, Ovid Medline, EMBASE, and PsycINFO and in relevant neurology and psychiatry journals. Terms used for electronic searches included smoking, tobacco, cigarettes; depression; adolescent, youth; direction. Relevant information was then utilized to synthesize findings on the association between smoking and depression among adolescent population.

RESULTS

The initial database searches yielded 2,738 related articles. After screening and cross-referencing, duplicate articles, articles published in languages other than English, and studies on animals, social and lifestyle factors, mood disorders, and substance use were excluded. Of these, a total of 122 publications only focusing on smoking and depression in the adolescent population were selected for synthesis in this qualitative systemic review. These include 110 original research articles, eight meta-analyses and reviews, and four reports and websites.

CONCLUSION

The relationship between smoking and depression in the literature does not reflect the cause-effect relationship. The lack of evidence on the direction of the association may reflect futile study designs, confounding factors and/or use of indirect measures of depression and quantification of smoking. Future prospective randomized studies should target elucidation of the causal association.

[Risk of initiation to smoking with the use of electronic cigarettes: systematic review and meta-analysis]

This article aims to evaluate the association between the use of electronic cigarettes and initiation to smoking, through a systematic review with meta-analysis of longitudinal studies. A bibliographic search was performed on the MEDLINE, Embase, LILACS and PsycInfo databases. Reference selection, data extraction and risk of bias assessment of the studies were independently carried out in pairs, and the disagreements were discussed with a third researcher to reach a consensus. Meta-analysis was performed using the Mantel-Haenszel random effects model. Among the 25 studies included, 22 evaluated the outcome of conventional cigarette experimentation and nine assessed the outcome of current smoking (in the last 30 days). The meta-analysis showed that the use of electronic cigarettes increased the risk of conventional cigarette experimentation by almost three and a half times (RR=3.42; 95%CI 2.81-4.15), and by more than four times the risk of current smoking (RR=4.32; 95%CI 3.13-5.94). The risk of smoking initiation is significantly higher among electronic cigarette users. The marketing authorization of such devices may represent a threat to public health policies in Brazil.

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.

Gateway or common liability? A systematic review and meta-analysis of studies of adolescent e-cigarette use and future smoking initiation

BACKGROUND AND AIMS

Studies have consistently found a longitudinal association between e-cigarette use (vaping) and cigarette smoking. Many have interpreted such association as causal. This systematic review and meta-analysis evaluated the plausibility of a causal interpretation by (1) estimating the effect of adolescent vaping on smoking initiation, adjusted for study quality characteristics, (2) evaluating the sufficiency of adjustment for confounding based on the social development model (SDM) and the social ecological model (SEM) and E-value analyses and (3) investigating sample attrition and publication bias.

METHODS

Systematic review and meta-analysis of longitudinal studies that examined the association between e-cigarette use at baseline and smoking at follow-up. Participants were non-smokers aged < 18 at baseline.

RESULTS

Meta-analysis of 11 studies showed a significant longitudinal association between vaping and smoking [adjusted odds ratio (aOR) = 2.93, 95% confidence interval (CI) = 2.22, 3.87]. Studies with sample sizes < 1000 had a significantly higher odds ratio (OR = 6.68, 95% CI = 3.63, 12.31) than studies with sample sizes > 1000 (OR = 2.49, 95% CI = 1.97, 3.15). Overall, the attrition rate was very high (median = 30%). All but one study reported results from complete sample analysis, despite those dropping out having higher risk profiles. Only two studies comprehensively adjusted for confounding. The median E-value was 2.90, indicating that the estimates were not robust against unmeasured confounding.

CONCLUSIONS

There is a longitudinal association between adolescent vaping and smoking initiation; however, the evidence is limited by publication bias, high sample attrition and inadequate adjustment for potential confounders.

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.

Factors associated with smoking susceptibility among high school students in western Spain

The Expanded Susceptibility to Smoking Index (ESSI) is based on the combination of susceptibility to smoking and curiosity about smoking. The ESSI can identify young people who are at risk of starting to smoke cigarettes and related products. The objective of this study was to analyse the ESSI results and to examine factors associated with ESSI scores in students between 12 and 16 years of age. Sociodemographic, social/environmental and personal variables were analysed, and the ESSI value was determined for non-smoking students recruited from three schools in western Spain. Regression models were used to examine the factors associated with smoking for the entire sample and the factors associated with ESSI scores in the non-smoking population. Of the 377 participants who were analysed, 20.4% were smokers. Among the non-smokers, 53.5% and 55.3% presented medium-high ESSI scores for cigarettes and e-cigarettes, respectively, and 39.8% presented medium-high ESSI scores for hookah use. A higher ESSI score was associated with greater exposure to people smoking in the home, having more friends who smoke, alcohol consumption, and a higher impulsivity scale score. These findings reinforce the importance of reducing peer pressure and suggest the important role of resolve under conditions of positive affect on reducing impulsivity. Approaches based on self-efficacy could be addressed in preventive programmes developed in educational settings.

The effect of e-cigarettes on smoking cessation and cigarette smoking initiation: An evidence-based rapid review and meta-analysis

INTRODUCTION

The contribution made by e-cigarettes to smoking cessation continues to be controversial. Reports suggest that teenagers are becoming increasingly addicted to e-cigarettes and that e-cigarette use in adolescents is associated with subsequent cigarette smoking.

METHODS

Systematic searches of eleven databases were conducted (January 2015 to June 2020). Systematic reviews, randomized controlled trials (RCTs) and cohort studies comparing e-cigarettes with placebo e-cigarettes, nicotine replacement therapy (NRT) or no e-cigarette use were included. The two primary outcomes were smoking cessation among smokers and smoking initiation among non-smoking teenagers. The secondary outcome was adverse events. Data were synthesized using risk ratio (RR) or adjusted odds ratio (AOR) with 95% confidence interval (CI).

RESULTS

Six systematic reviews, 5 RCTs and 24 cohort studies were identified. For smoking cessation, findings from 4 systematic reviews indicated that e-cigarettes contributed to cessation while one found the opposite. Meta-analysis of 5 RCTs suggested that e-cigarettes were superior to NRT or placebo for smoking cessation (RR=1.55; 95% CI: 1.00–2.40; I²=57.6%; low certainty; 5 trials, n=4025). Evidence from 9 cohort studies showed that e-cigarette use was not associated with cessation (AOR=1.16; 95% CI: 0.88–1.54; I²=69.0%; n=22220). Subgroup analysis suggested that intensive e-cigarette use may be associated with cessation. In terms of smoking initiation, adolescents who ever used e-cigarettes had a greater risk for smoking initiation than non-users (AOR=2.91; 95% CI: 2.61–3.23; I²=61.0%; 15 trials, n=68943), the findings were consistent with one included systematic review. No serious adverse events were reported in the included studies.

CONCLUSIONS

Low certainty evidence suggests that e-cigarettes appear to be potentially effective for smoking cessation. The use of e-cigarettes in adolescents may be associated with smoking initiation. No serious adverse events were reported.

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.

Tobacco use and E-cigarette regulation: Perspectives of University Students in the Asia-Pacific

INTRODUCTION

The Asia-Pacific is home to 30% of the world's smokers. Additional efforts are needed to reduce negative health impacts of tobacco, including e-cigarettes. The study objectives were to 1. Investigate Asian-Pacific students' knowledge, attitudes, and use of tobacco products; 2. Determine the level of student support for tobacco control policies; and 3. Examine differences in students' attitudes by the strength of national tobacco control policies based on implementation of WHO's MPOWER package, and e-cigarette regulation in their countries.

METHODS

A total of 1953 students from members of the Association of Pacific Rim Universities in 13 countries completed the online survey. We compared the results by the Fisher-Freeman-Halton test.

RESULTS

While about 83% of students had heard of e-cigarettes; only 14.1% had tried them. Students in countries with e-cigarette bans were the least likely to report having experimented with e-cigarettes (8.1%). While the vast majority of students (87.9%) reported having seen health campaigns targeting combustible cigarettes, far fewer (42.5%) had seen any health campaigns targeting e-cigarettes. About 80% of students supported smoke-free campuses, with the most support coming from those in countries with the weakest adoption of MPOWER policies (88.7%) and no e-cigarette regulations (80.4%). Students in countries with the weakest MPOWER policies were also the most likely to support campus bans and government regulation of e-cigarettes.

CONCLUSIONS

The adoption of tobacco control polices by government may have an impact on e-cigarette smoking behavior among students, and student support for tobacco control, including noncombustible products, is high. Universities should take action by adopting comprehensive tobacco control measures that include e-cigarette regulations.

Are e-cigarettes reviving the popularity of conventional smoking among Taiwanese male adolescents? A time-trend population-based analysis for 2004-2017

INTRODUCTION

In Taiwan, national tobacco use surveys show that e-cigarette use has increased since 2014 among youth, while, at the same time, conventional cigarette smoking has continuously decreased. The purpose of this study is to examine whether the increased popularity of e-cigarettes has undermined this favourable declining trend for cigarette smoking.

METHODS

We examined conventional cigarette and e-cigarette prevalence among male high school students (aged 16-18 years) and adults from 2004 to 2017, using data from cross-sectional nationally representative surveys. Applying interrupted time series analysis, we assessed whether there was a change in trend in 2014, when e-cigarette use started to gain popularity from long-term trends in prior years (2004-2013).

RESULTS

E-cigarette use prevalence increased from 2.5% in 2014 to 6.4% in 2017 among male high school students but was negligible among male adults, declining from 1.4% in 2015 to 0.8% in 2017. The annual relative decline in the cigarette smoking rate after e-cigarettes started to gain popularity was greater (-10%) than the long-term trend (-2%) among high school students. Among adults, the change in trend over time after e-cigarettes started to gain popularity was not significant (ie, not significantly different from 0).

CONCLUSIONS

The increased popularity of e-cigarettes since 2014 is associated with a greater decline in youth smoking, compared with previous years. On the contrary, e-cigarette use has remained very low among Taiwanese male adults and no additional impact on the conventional smoking trend is found.

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.