How is the effect of adolescent e-cigarette use on smoking onset mediated: A longitudinal analysis

Exploring Native Hawaiian and Pacific Islander Youths' E-Cigarette Resistance Strategies: Implications for Tobacco Product Use Prevention

This study examined the e-cigarette and vaping resistance strategies used by Native Hawaiian and Pacific Islander (NHPI) youths in rural Hawai'i. Focus groups (N = 17) were conducted in eight geographically dispersed elementary, middle/intermediate, and multilevel schools in low-income communities on Hawai'i Island. Sixty-nine youths (67% NHPI, Mage = 12.5 years) participated in this study. The resistance strategies discussed across the greatest number of groups were "refuse" (saying no), "explain" (providing reasons for vaping refusal), "avoid" (avoiding people or places where e-cigarettes were used), and "leave" (walking away from a situation where e-cigarettes were being used). Participants described the challenges in using these strategies within contexts characterized by widespread peer and family vaping and strong social demands to use e-cigarettes. The findings suggest the need for multi-level interventions based on youths' resistance strategies to meaningfully reduce youth vaping use in rural and/or NHPI communities.

Comparative analysis of e-cigarette prevalence and influencing factors among adolescents in Jiangsu Province, China

Objective

The objectives of this study were to investigate electronic cigarette (e-cigarette) and cigarette use in Jiangsu Province, China, by analyzing the two-year trends of e-cigarette using and to explore the factors influencing the experimentation and use of e-cigarettes.

Methods

We conducted a cross-sectional study following the standard methodology of the Global Youth Tobacco Survey in 2019 and 2021. A three-stage cluster sampling design was applied. Eighty-two schools in 14 districts (counties) in Jiangsu Province were surveyed. All computations were performed using the SPSS 21.0 complex samples procedure. Multivariate logistic regression was used to explore the factors influencing e-cigarette experimentation and use.

Results

A total of 12,410 and 12,880 students were surveyed in 2019 and 2021, respectively. E-cigarette experimentation increased from 9.34% in 2019 to 13.07% in 2021 (P < 0.001). E-cigarette use increased from 2.23% in 2019 to 3.74% in 2021 (P < 0.001). The main factors associated with e-cigarette use were cigarette experimentation (OR = 2.700, P < 0.001); male gender (OR = 1.416, P = 0.011); junior high school students (OR = 1.551, P = 0.005) and vocational high school students (OR = 1.644, P = 0.001); more pocket money per week (OR1 = 1.214, P = 0.187; OR2 = 1.686, P = 0.001); exposure to second-hand smoke (SHS) at home (OR = 1.239, P < 0.001); exposure to e-cigarette advertising (OR = 1.855, P < 0.001); believe SHS is harmful (OR = 0.933, P = 0.026); closest friends smoking (OR = 2.501, P < 0.001); believe smoking makes youth look more attractive (OR1 = 1.469, P = 0.040; OR2 = 1.305, P = 0.049); believe tobacco helps youth feel more comfortable in social situations (OR1 = 2.161, P < 0.001; OR2 = 1.635, P = 0.001); will use an e-cigarette product if offered by best friends (OR = 1.322, P < 0.001); intend to use an e-cigarette product in the next 12 months (OR = 1.486, P < 0.001).

Conclusion

E-cigarette use among adolescents has been on the rise in recent years. E-cigarette use is associated with past cigarette use and a strong desire to smoke. It is crucial to take health education and tobacco control efforts to reduce adolescents' e-cigarette use rate.

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.

Ethnic differences in respiratory disease for Native Hawaiians and Pacific Islanders: Analysis of mediation processes in two community samples

OBJECTIVE

The prevalence of asthma and chronic obstructive pulmonary disorder (COPD) is elevated for Native Hawaiians but the basis for this differential is not well understood. We analyze data on asthma and COPD in two samples including Native Hawaiians Pacific Islanders, and Filipinos to determine how ethnicity is related to respiratory disease outcomes.

METHODS

We analyzed the 2016 and 2018 Behavioral Risk Factor Surveillance Survey (BRFSS), a telephone survey of participants ages 18 and over in the State of Hawaii. Criterion variables were a diagnosis of asthma or COPD by a health professional. Structural equation modeling tested how five hypothesized risk factors (cigarette smoking, e-cigarette use, second-hand smoke exposure, obesity, and financial stress) mediated the ethnic differential in the likelihood of disease. Age, sex, and education were included as covariates.

RESULTS

Structural modeling with 2016 data showed that Native Hawaiian ethnicity was related to higher levels of the five risk factors and each risk factor was related to a higher likelihood of respiratory disease. Indirect effects were statistically significant in almost all cases, with direct effects to asthma and COPD also observed. Mediation effects through comparable pathways were also noted for Pacific Islanders and Filipinos. These findings were replicated with data from the 2018 survey.

CONCLUSIONS

Native Hawaiian and Pacific Islander ethnicity is associated with greater exposure to five risk factors and this accounts in part for the ethnic differential in respiratory disease outcomes. The results support a social-ecological model of health disparities in this population. Implications of the findings for preventive interventions are discussed.

Associations for subgroups of E-cigarette, cigarette, and cannabis use with asthma in a population sample of California adolescents

Knowledge about the respiratory health consequences of adolescents' use of tobacco products with cannabis remains limited. We studied whether e-cigarettes, combustible cigarettes, and cannabis were independently associated with asthma in a population-based sample of 150,634 public high school students (10th and 12th graders), drawn in a two-stage design to be representative of the state of California in 2019-2020. Measures were obtained for use of e-cigarettes, combustible cigarettes, and cannabis; motives for use (three substances); method of use (for cannabis); ever being diagnosed with asthma; and having an asthma attack in past 12 months. Cross-classification indicated Nonuse for 64% of the sample; 15% Dual E-cigarette/Cannabis Use; 10% Exclusive Cannabis Use; 5% Exclusive E-cigarette Use; and 5% Triple Use. Multinomial logistic regression with a three-level criterion variable, controlling for age, sex, parental education, race/ethnicity, and three types of household use showed that compared with Nonuse, odds of Lifetime Asthma (vs. Never Had) was elevated for Triple Use (AOR = 1.14, CI 1.06-1.24), Dual E-cigarette/Cannabis Use (1.17, 1.12-1.23), Exclusive Cannabis Use (1.17, 1.11-1.23), and Exclusive E-cigarette Use (1.10, 1.02-1.18). Similar results were noted for Recent Asthma. Among persons who had used cannabis, 88% of the Triple group and 74% of the Dual E-cigarette/Cannabis group reported both smoking and vaping cannabis. Thus, co-occurrence of e-cigarette and cannabis use was a common pattern among adolescents in this study, and subgroups of cannabis and e-cigarette use showed similar associations with asthma. Preventive approaches should highlight the health implications of exclusive or combined e-cigarette and cannabis use.

Predictors of E-cigarette and Cigarette Use Trajectory Classes from Early Adolescence to Emerging Adulthood Across Four Years (2013-2017) of the PATH Study

INTRODUCTION

This study examines predictors of trajectories of cigarette and e-cigarette use among a cohort of US adolescents transitioning into young adulthood. Comparing trajectories of each tobacco product is important to determine if different intervention targets are needed to prevent progression to daily use.

METHODS

Latent trajectory class analyses identified cigarette and e-cigarette use (never, ever excluding past 12-month, past 12-month (excluding past 30-day (P30D)), P30D 1-5 days, P30D 6+ days) trajectory classes, separately, among US youth (12-17; N = 10,086) using the first 4 waves (2013-2017) of data from the nationally representative PATH Study. Weighted descriptive analyses described the class characteristics. Weighted multinomial logistic regression analyses examined demographic, psychosocial, and behavioral predictors of class membership.

RESULTS

Younger adolescents 12-15 years had lower tobacco use compared to 16-17 year olds and less stable classes. In the 16-17 year group, there were five unique trajectories of cigarette smoking, including a Persistent High Frequency class. Four e-cigarette use trajectories were identified; but not a persistent use class. Shared predictors of class membership for cigarettes and e-cigarettes included mental health problems, other tobacco use, marijuana use, and poorer academic achievement. Male sex and household tobacco use were unique e-cigarette trajectory class predictors.

CONCLUSIONS

There was no evidence that initiation with e-cigarettes as the first product tried was associated with cigarette progression (nor cigarettes as first product and e-cigarette progression). Interventions should focus on well-established risk factors such as mental health and other substance use to prevent progression of use for both tobacco products.

IMPLICATIONS

Using nationally representative data and definitions of use that take into account frequency and recency of use, longitudinal 4-year trajectories of e-cigarette and cigarette use among US adolescents transitioning into young adulthood were identified. Results among 16-17-year olds revealed a class of persistent high frequency cigarette smoking that was not identified for e-cigarette use. Cigarette use progression was not associated with e-cigarettes as the first product tried. Risk factors for progression of use of both products included mental health and other substance use, which are important prevention targets for both tobacco products.

Smoking Susceptibility in Canadian Adolescent Electronic-Cigarette Users

Background: E-cigarette use is increasing among Canadian youth, with experimentation especially prevalent among never-smoking youth. Among this group, there is concern e-cigarette use contributes to future initiation of smoking through a gateway effect. However, e-cigarette use and smoking share many common risk factors; a postulated mechanism to explain the apparent causal pathway from e-cigarette use to smoking initiation in previously smoking-naïve youth. A better understanding of the relationships between smoking susceptibility and e-cigarette use among never-smoking youth is needed. Purpose/objectives: The primary aim of this study was to gain a deeper understanding of the risk factors associated with smoking susceptibility in youth who have recently used e-cigarettes. Methods: This study used data (n = 40,363) from the 2018/2019 Canadian Student Tobacco Alcohol and Drug Use Survey (CSTADS) to compare the risk factor profiles of susceptible and non-susceptible never-smoking e-cigarette users, as well as susceptible and non-susceptible never-smoking youth who have never used an e-cigarette. Results: E-cigarette use, independent of susceptibility status, was associated with a sociodemographic and behavioral risk factor profile likely to confer a higher risk of initiating smoking. Among e-cigarette users, smoking susceptibility was associated with more smoking risk factors. Conclusions/importance: Study findings support a common risk-factor model, rather than e-cigarette use itself, to explain differences in the likelihood of smoking initiation among e-cigarette users. E-cigarette use and smoking initiation may be interchangeable outcomes amongst those with smoking risk factors. The risks of e-cigarette use, and their regulatory status, need to be balanced with their potential as harm reduction tools.

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.

Concurrent Use of E-cigarettes, Combustible Cigarettes, and Marijuana

OBJECTIVE

Subgroups of adolescent single and dual e-cigarette and cigarette users have been identified, but usage patterns have changed in recent years, and there has been an increase in marijuana use. Research is needed with current data to identify subgroups of use including marijuana and determine their behavioral correlates.

METHODS

We cross classified ever and recent use of e-cigarettes, combustible cigarettes, and marijuana among US high school students in the 2019 Youth Risk Behavior Survey (YRBS), providing 8 different groups. Levels of 14 risk and protective factors were compared across groups in general linear models with demographic covariates using omnibus tests, pairwise comparisons, and planned contrasts. Replicability was tested through identical analyses for 2017 YRBS data.

RESULTS

The nonuser group was 43.9% of the sample. The most frequent user groups were triple users (ever-use proportion: 16.9%), dual (e-cigarette and marijuana) users (15.8%), and exclusive e-cigarette users (13.2%). For risk profiles on levels of psychosocial variables, the triple-user group was typically elevated above all other groups. Exclusive e-cigarette users were above nonusers in risk profile but below dual users (both cigarettes and marijuana). Results were similar for ever use and recent use. The patterning of results in 2019 YRBS data were closely replicated in 2017 YRBS data.

CONCLUSIONS

Co-occurrence of e-cigarette, cigarette, and marijuana use is currently substantial among adolescents and is associated with an elevated psychosocial risk profile. This has implications for both epidemiology and prevention studies. Further research is needed to study prevalence and identify pathways to triple use.

Balancing Consideration of the Risks and Benefits of E-Cigarettes

The topic of e-cigarettes is controversial. Opponents focus on e-cigarettes' risks for young people, while supporters emphasize the potential for e-cigarettes to assist smokers in quitting smoking. Most US health organizations, media coverage, and policymakers have focused primarily on risks to youths. Because of their messaging, much of the public-including most smokers-now consider e-cigarette use as dangerous as or more dangerous than smoking. By contrast, the National Academies of Science, Engineering, and Medicine concluded that e-cigarette use is likely far less hazardous than smoking. Policies intended to reduce adolescent vaping may also reduce adult smokers' use of e-cigarettes in quit attempts. Because evidence indicates that e-cigarette use can increase the odds of quitting smoking, many scientists, including this essay's authors, encourage the health community, media, and policymakers to more carefully weigh vaping's potential to reduce adult smoking-attributable mortality. We review the health risks of e-cigarette use, the likelihood that vaping increases smoking cessation, concerns about youth vaping, and the need to balance valid concerns about risks to youths with the potential benefits of increasing adult smoking cessation.

Trends in electronic cigarette use and conventional smoking: quantifying a possible 'diversion' effect among US adolescents

BACKGROUND AND AIMS

The impact of electronic cigarettes (ECs) on nicotine use is hotly debated: some fear that ECs are a 'catalyst' to conventional smoking, while others argue that they divert adolescents from the more harmful product. This study used simulation modeling to evaluate the plausibility of catalyst and diversion hypotheses against real-world data.

DESIGN

A simulation model represented life-time exclusive EC use, exclusive conventional smoking and dual use as separate subpopulations. The 'catalyst' effect was modeled as EC use increasing dual use initiation (i.e. EC users also start smoking). The 'diversion' effect was modeled as EC use decreasing exclusive cigarette initiation. The model was calibrated using data from the US National Youth Tobacco Survey (NYTS). The plausibility of each scenario was evaluated by comparing simulated trends with NYTS data. This is the first study, to our knowledge, to estimate the magnitude of a diversion effect through simulation.

SETTING

United States.

PARTICIPANTS AND MEASUREMENTS

Adolescents aged 12-17 years in NYTS, a cross-sectional study from 2000 to 2019 (n = 12 500 to 31 000 per wave). Exclusive cigarette use, exclusive EC use and dual use of both products were defined using cumulative life-time criteria (100+ cigarettes smoked and/or > 100 days vaped).

FINDINGS

A null model (no catalyst or diversion) over-predicts NYTS smoking by up to 87%. Under the conservative assumption that the catalyst effect accounts for all dual use, an exponential decay constant of 19.6% EC users/year initiating smoking is required; however, this further over-predicts actual smoking by up to 109%. A diversion effect with an exponential decay constant of 55.4%/year or 65.4%/year, with the maximum possible opposing catalyst effect also active, is required optimally to match NYTS smoking trends (root mean square error = 286 632 versus 391 396 in the null model).

CONCLUSIONS

A simulation model shows that a substantial diversion effect is needed to explain observed nicotine use trends among US adolescents, and it must be larger than any possible opposing catalyst effect, if present.

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.

Electronic cigarette use and risk of cigarette and smokeless tobacco initiation among adolescent boys: A propensity score matched analysis

INTRODUCTION

Electronic cigarette (e-cigarette) use among adolescents is associated with increased risk of subsequent cigarette smoking initiation in observational research. However, the existing research was not designed to answer causal questions about whether adolescent e-cigarette users would have initiated cigarette smoking if they had never used e-cigarettes. The current study used a causal inference framework to identify whether male adolescent e-cigarette users were at increased risk of initiating cigarette smoking and smokeless tobacco (SLT) use, compared to similar boys who had never used e-cigarettes.

METHODS

Boys from urban and Appalachian Ohio (N = 1220; ages 11-16 years at enrollment) reported use of e-cigarettes, cigarettes, and SLT at baseline and every six months for two years. A propensity score matching design was implemented, matching one e-cigarette user to two similar e-cigarette non-users. This analysis was completed in 25 multiple imputed datasets to account for missing data. Risk ratios (RRs) comparing risk of initiating cigarettes and SLT for e-cigarette users and nonusers were estimated.

RESULTS

Compared to non-users, e-cigarette users were more than twice as likely to later initiate both cigarette smoking (RR = 2.71; 95% CI: 1.89, 3.87) and SLT (RR = 2.42; 95% CI: 1.73, 3.38). They were also more likely to become current (i.e., past 30-day) cigarette smokers (RR = 2.20; 95% CI: 1.33, 3.64) and SLT users (RR = 1.64; 95% CI: 1.01, 2.64).

CONCLUSIONS

Adolescent boys who used e-cigarettes had increased risk of later initiating traditional tobacco products when compared to similar boys who had never used e-cigarettes.

E-cigarette use and respiratory disorders: an integrative review of converging evidence from epidemiological and laboratory studies

Background

Use of electronic cigarettes (e-cigarettes) is prevalent among adolescents and young adults, but there has been limited knowledge about health consequences in human populations. We conduct a systematic review and meta-analysis of results on respiratory disorders from studies of general-population samples and consider the mapping of these results to findings about biological processes linked to e-cigarettes in controlled laboratory studies.

Method

We conducted a literature search and meta-analysis of epidemiological studies on the association of e-cigarette use with asthma and with COPD. We discuss findings from laboratory studies about effects of e-cigarettes on four biological processes: cytotoxicity, oxidative stress/inflammation, susceptibility to infection and genetic expression.

Results

Epidemiological studies, both cross-sectional and longitudinal, show a significant association of e-cigarette use with asthma and COPD, controlling for cigarette smoking and other covariates. For asthma (n=15 studies), the pooled adjusted odds ratio (aOR) was 1.39 (95% CI 1.28–1.51); for COPD (n=9 studies) the aOR was 1.49 (95% CI 1.36–1.65). Laboratory studies consistently show an effect of e-cigarettes on biological processes related to respiratory harm and susceptibility to illness, with e-cigarette conditions differing significantly from clean-air controls, although sometimes less than for cigarettes.

Conclusions

The evidence from epidemiological studies meets established criteria for consistency, strength of effect, temporality, and in some cases a dose–response gradient. Biological plausibility is indicated by evidence from multiple laboratory studies. We conclude that e-cigarette use has consequences for asthma and COPD, which is of concern for respirology and public health.

Epidemiological studies show a relationship of e-cigarette use with asthma and COPD, and laboratory studies show their adverse effects on four biological processes. It can be concluded that e-cigarette use is of significant concern for public health.https://bit.ly/3drH4pj

Does having one or more smoking friends mediate the transition from e-cigarette use to cigarette smoking: a longitudinal study of Canadian youth

PURPOSE

Studies have shown consistent associations between youth e-cigarette use and subsequent smoking uptake. However, it remains unclear why, as limited evidence exists regarding the mechanisms underlying these associations. Our study investigated whether having one or more smoking friends mediated the association between e-cigarette use and cigarette smoking onset among a longitudinal sample of Canadian youth who were never smokers at baseline.

METHODS

A longitudinal sample of youth that participated in three waves of the COMPASS study (2015-2016 to 2017-2018) was identified (N = 5,535). The product of coefficients method was used to assess whether having one or more smoking friends mediated the association between: (1) past 30-day e-cigarette use and cigarette smoking onset and (2) past 30-day e-cigarette use and subsequent dual use of e-cigarettes and cigarettes.

RESULTS

Having one or more smoking friends did not mediate the association between (1) past 30-day e-cigarette use and cigarette smoking onset (β = 0.38, 95% CI - 0.12, 0.89) or (2) past 30-day e-cigarette use and subsequent dual use (β = 0.46, 95% CI - 0.16, 1.07). Post hoc tests indicated that smoking friends significantly predicted past 30-day e-cigarette use and cigarette smoking at wave 3 (aOR 1.68 and 2.29, respectively).

CONCLUSION

Having smoking friends did not explain the association between e-cigarette use and smoking uptake despite being a common risk factor for both e-cigarette use and cigarette smoking. Prevention efforts should consider how best to incorporate effective programming to address these social influences.

The Relationship Between Electronic Cigarette Use and Conventional Cigarette Smoking Is Largely Attributable to Shared Risk Factors

INTRODUCTION

The growing popularity of electronic cigarettes (e-cigarettes) among youth raises concerns about possible causal effects on conventional cigarette smoking. However, past research remains inconclusive due to heavy confounding between cigarette and e-cigarette use. This study uses propensity score methods to robustly adjust for shared risk in estimating the relationship between e-cigarette use and conventional smoking.

METHODS

Cross-sectional data from 8th and 10th graders were drawn from the 2015-2016 waves of Monitoring the Future (n = 12 421). The effects of (1) lifetime and (2) current e-cigarette use on (A) lifetime and (B) current conventional cigarette smoking were examined using logistic regression analyses with inverse propensity weighting based on 14 associated risk factors.

RESULTS

After accounting for the propensity for using e-cigarettes based on 14 risk factors, both lifetime and current e-cigarette use significantly increased the risk of ever smoking a conventional cigarette (OR = 2.49, 95% CI = 1.77 to 3.51; OR = 2.32, 95% CI = 1.66 to 3.25, respectively). However, lifetime (OR = 2.17, 95% CI = 0.62 to 7.63) and current e-cigarette use (OR = 0.95, 95% CI = 0.55 to 1.63) did not significantly increase the risk of current conventional cigarette smoking.

CONCLUSIONS

E-cigarette use does not appear to be associated with current, continued smoking. Instead, the apparent relationship between e-cigarette use and current conventional smoking is fully explained by shared risk factors, thus failing to support claims that e-cigarettes have a causal effect on concurrent conventional smoking among youth. E-cigarette use has a remaining association with lifetime cigarette smoking after propensity score adjustment; however, future research is needed to determine whether this is a causal relationship or merely reflects unmeasured confounding.

IMPLICATIONS

This study examines the relationship between e-cigarette use and conventional smoking using inverse propensity score weighting, an innovative statistical method that produces less-biased results in the presence of heavy confounding. Our findings show that the apparent relationship between e-cigarette use and current cigarette smoking is entirely attributable to shared risk factors for tobacco use. However, e-cigarette use is associated with lifetime cigarette smoking, though further research is needed to determine whether this is a causal relationship or merely reflects unaccounted-for confounding. Propensity score weighting produced significantly weaker effect estimations compared to conventional regression control.

E-cigarette use and respiratory disorders: an integrative review of converging evidence from epidemiological and laboratory studies

BACKGROUND

Use of electronic cigarettes (e-cigarettes) is prevalent among adolescents and young adults, but there has been limited knowledge about health consequences in human populations. We conduct a systematic review and meta-analysis of results on respiratory disorders from studies of general-population samples and consider the mapping of these results to findings about biological processes linked to e-cigarettes in controlled laboratory studies.

METHOD

We conducted a literature search and meta-analysis of epidemiological studies on the association of e-cigarette use with asthma and with COPD. We discuss findings from laboratory studies about effects of e-cigarettes on four biological processes: cytotoxicity, oxidative stress/inflammation, susceptibility to infection and genetic expression.

RESULTS

Epidemiological studies, both cross-sectional and longitudinal, show a significant association of e-cigarette use with asthma and COPD, controlling for cigarette smoking and other covariates. For asthma (n=15 studies), the pooled adjusted odds ratio (aOR) was 1.39 (95% CI 1.28-1.51); for COPD (n=9 studies) the aOR was 1.49 (95% CI 1.36-1.65). Laboratory studies consistently show an effect of e-cigarettes on biological processes related to respiratory harm and susceptibility to illness, with e-cigarette conditions differing significantly from clean-air controls, although sometimes less than for cigarettes.

CONCLUSIONS

The evidence from epidemiological studies meets established criteria for consistency, strength of effect, temporality, and in some cases a dose-response gradient. Biological plausibility is indicated by evidence from multiple laboratory studies. We conclude that e-cigarette use has consequences for asthma and COPD, which is of concern for respirology and public health.

Adverse Childhood Experiences and Prevalence of Cigarette and E-Cigarette Use Among Adolescents in Bangkok, Thailand

Currently, e-cigarettes are the most popular tobacco product among adolescents. The purpose of this study was to explore the relationship between exposure to adverse childhood experiences (ACEs) and use of cigarettes, e-cigarettes, and dual use in a sample of adolescents in Bangkok, Thailand. The sample comprises 6167 students from 48 schools (grades 9, 11, and vocational year 2) who participated in the 2019 round of the Behavior Surveillance Survey. History of 11 ACEs was used to calculate a cumulative ACE score (range 0-11). Multinomial logistic regression was used to assess the relationship between history of ACEs and smoking. In the sample, 7.0% reported using e-cigarettes only and 9.5% used e-cigarettes and cigarettes (dual use). After controlling for sociodemographic characteristics, history of ACEs was associated with increased odds of dual use. The odds of cigarette, e-cigarette, and dual use was significantly greater if the adolescent had a history of ≥4 ACEs. Special attention is needed to prevent smoking of different types among those with a history of ACEs.

Are E-cigarette Users a Unique Group of Smokers? Latent Class Analysis of the National Youth Tobacco Survey

We used data from the 2014 National Youth Tobacco Survey to examine patterns of cigarette smoking behavior and tobacco use. In light of the recent upsurge in e-cigarette use, we modeled current use and future intentions to use vape products along with combustible cigarette smoking and other tobacco products (i.e., cigars, cigarillos, chew, snuff, and dip). Latent class analyses indicated four discrete classes of smokers including a nominally involved class with very modest levels of tobacco product use, a class blending e-cigarette and cigars, a class of youth who predominantly use combustible cigarettes, and a group reporting indiscriminate use of almost all tobacco products excluding chew. Tests of invariance in item response probabilities and latent class proportions showed little variation across race and gender, albeit a new class of combustible cigarette and e-cigarette users emerged when examined by grade. Members of the heavy smoking and tobacco use class were more likely to be male, White, and older. Predictors of class membership included expectancies (perceived benefits of use), perceived harm (risk), media exposure, tobacco dependence, and the desire to quit. Findings are discussed in terms of characterizing risk among already smoking youth and how actionable prevention measures can be incorporated into existing universal and indicated programs that target reducing tobacco use and smoking behaviors.

Longitudinal e-Cigarette and Cigarette Use Among US Youth in the PATH Study (2013-2015)

BACKGROUND

Evidence is accumulating that youth who try Electronic Nicotine Delivery Systems (ENDS, e-cigarettes) may go on to try cigarettes. This analysis examines the bidirectional patterns of ENDS and cigarette use among US youth over one year and uses propensity score matching (PSM) to examine frequency of ENDS use on changes in cigarette smoking.

METHODS

Our analysis included 11 996 participants who had two waves of available data (Wave 1 [W1] 2013-2014; Wave 2 [W2] 2014-2015) drawn from the longitudinal Population Assessment of Tobacco and Health Study. Cross-sectional weighted prevalence estimates are reported for cigarettes and ENDS. We used PSM to estimate the likelihood of ENDS use at W1 and to draw matched analytic samples, then used regression (logistic or linear) models to examine the effect of W1 ENDS use on W2 cigarette smoking. All statistical tests were two-sided.

RESULTS

In weighted analyses, 69.3% of W1 past-30-day cigarette smokers exhibited past-30-day smoking at W2; 42.2% of W1 past-30-day ENDS users were using ENDS at W2. W1 ever use of either product was similarly associated with W2 new use of the other product. Unweighted PSM models indicated W1 cigarette-naïve ENDS use was associated with W2 ever-cigarette smoking (n = 676; adjusted odds ratio = 3.21, 95% confidence interval [CI] = 1.95 to 5.45, P < .001); W1 ever-ENDS use did not affect change in cigarette frequency at W2 (n = 1020, beta = 0.31, 95% CI = -0.76 to 1.39, P = .57); 1-5 days ENDS use compared with ever, no past-30-day ENDS use was associated with a statistically significant decrease of W2 smoking days (n = 256, beta = -2.64, 95% CI = -4.96 to -0.32; P = .03); and W1 6+ day ENDS users did not show a decrease in frequency of cigarette smoking.

CONCLUSIONS

Ever-ENDS use predicts future cigarette smoking, and frequency of ENDS use has a differential impact on subsequent cigarette smoking uptake or reduction. These results suggest that both cigarettes and ENDS should be targeted in early tobacco prevention efforts with youth.

Electronic nicotine delivery system use is related to higher odds of alcohol and marijuana use in adolescents: Meta-analytic evidence

Research suggests that electronic nicotine delivery system (ENDS) use is associated with other substance use in adolescents; however, the magnitude of this association and whether this differs between adolescents and adults is not yet well understood. This meta-analysis aimed to quantify the extent to which ENDS use is associated with alcohol and marijuana use among adolescents and to compare the odds across adolescent samples and a comparison group of adult samples. A comprehensive literature review was conducted examining the relationship between ENDS use and alcohol (adolescent k = 40 from 19 independent studies; adult k = 35 from 12 independent studies) and marijuana (adolescent k = 24 from 14 independent studies; adult k = 6 from 3 independent studies) use. Adolescents who use ENDS had greater odds of reporting co-occurring alcohol use (OR = 4.50, p < .001), particularly binge drinking (OR = 4.51), and marijuana use (OR = 6.04, p < .001) than adolescent who did not use ENDS. Adults who use ENDS were also more likely to use alcohol (OR = 1.57, p < .001) and marijuana (OR = 2.04, p < .001) than those who did not use ENDS. ENDS use was associated with significantly greater odds of alcohol use (log odds ratio; LOR = 0.96 (OR = 2.61), p < .001) and a trend of greater marijuana use (LOR = 0.93 (OR = 2.53), p = 0.08) in adolescents than in adults. Effects were large in adolescents and small in adults. Findings suggest that ENDS use should be assessed in adolescents in both research and clinical settings. Importantly, ENDS use is strongly associated with co-occurring alcohol or marijuana use in adolescents.

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.

Disentangling Within- and Between-Person Effects of Shared Risk Factors on E-cigarette and Cigarette Use Trajectories From Late Adolescence to Young Adulthood

BACKGROUND

Longitudinal studies report associations between use of electronic cigarettes (ECs) and cigarettes over time among young people, but do not distinguish within- from between-person effects, which complicates interpretation of findings. Further, the role of shared risk factors, such as substance use and mental health, in explaining longitudinal associations between EC and cigarette use remains unclear. This study used within- and between-person analyses to assess longitudinal associations between youths' EC and cigarette use and shared risk factors.

METHODS

Between 2015 and 2017, 2039 youths completed three Web-based surveys, allowing us to model EC and cigarette use from ages 16 to 20. Auto-regressive latent growth models with structured residuals (ALT-SR) examined both between-person and within-person associations between past-month frequency of EC use, cigarette use, and third variables (alcohol and marijuana use, mental health symptoms) over time.

RESULTS

Models revealed robust reciprocal associations between EC and cigarette use, such that more frequent EC use at one time predicted more frequent cigarette use at the subsequent time, and vice versa. Between-person analyses showed associations between shared risk factors and both EC and cigarette use. However, shared risk factors did not predict frequency of subsequent EC and cigarette use in within-person analyses.

CONCLUSIONS

Findings add to a growing body of research suggesting that EC use among youth is prospectively associated with progression toward greater cigarette use. Shared risk factors may help explain differences in EC and cigarette use patterns between young people, but do not appear to influence longitudinal trajectories of EC and cigarette use within individuals.

IMPLICATIONS

This study examined within- and between-person associations between e-cigarette use, cigarette use, and shared risk factors (alcohol use, marijuana use, mental health symptoms) in a longitudinal cohort of youths. Within- and between-person analyses revealed reciprocal prospective associations between e-cigarette and cigarette use, suggesting a progression toward more frequent use of both products over time. The shared risk factors examined here did not affect escalations in e-cigarette or cigarette use over time within individuals, but likely influence which youths use these products. Findings add to a growing body of evidence suggesting that e-cigarette use increases subsequent cigarette use in young people.

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.

E-Cigarette Use, Polytobacco Use, and Longitudinal Changes in Tobacco and Substance Use Disorder Symptoms Among U.S. Adolescents

PURPOSE

The objective of this study was to examine the combinations of e-cigarette use, cigarette use, and other tobacco use over time and the relationship these longitudinal use patterns have with symptoms of tobacco use disorder (TUD) and substance use disorders (SUDs) among a sample of adolescents.

METHODS

Data from U.S. adolescents (aged 12-17 years) who were surveyed for the Population Assessment of Tobacco and Health Study at baseline, first follow-up, and second follow-up (2013-2014, 2014-2015, and 2015-2016; n = 7,595) was used to analyze symptoms of TUD and SUDs based on longitudinal combinations of tobacco/nicotine use.

RESULTS

The most common combination of tobacco/nicotine use across the three waves was "no use of any tobacco/nicotine products" at baseline and first follow-up to "e-cigarette use only" at the second follow-up. Multivariable analyses found that past 30-day cigarette use and other tobacco use at the most recent follow-up was associated with an increase in both current TUD and SUD symptoms, whereas past 30-day e-cigarette use at the most recent follow-up was modestly associated with an increase in current SUD symptoms.

CONCLUSIONS

Individuals who transitioned to e-cigarette use were at relatively low risk for increased TUD and SUD symptoms. However, individuals who transitioned or continually used cigarettes were typically at greater risk for indicating more TUD and SUD symptoms. Given the low risk of e-cigarette only users to indicate TUD and SUD symptoms, prevention efforts need to be made to target these youth before they transition to cigarettes and other types of tobacco use.

Initiation Patterns and Trends of E-Cigarette and Cigarette Use Among U.S. Adolescents

PURPOSE

The primary objectives were to (1) examine the initiation patterns of e-cigarette and cigarette smoking, (2) compare recent trends in initiation patterns for 2015, 2016, and 2017, (3) examine sociodemographic differences in initiation patterns over time and, (4) examine how initiation patterns are associated with cigarette-related perceptions, behaviors, and intentions.

METHODS

Data were collected via self-administered questionnaires from 2015 to 2017 nationally representative samples of eighth-grade (modal ages 13-14 years) and 10th-grade (modal ages 15-16 years) students (N = 36,506) attending U.S. secondary public and private schools.

RESULTS

Among lifetime e-cigarette or cigarette users (n = 9,858), initiating e-cigarettes only was the most common (47.45%). This was followed by cigarette before e-cigarette initiation (18.50%), which decreased in prevalence from 2015 to 2017. E-cigarette before cigarette initiation was the smallest group (6.89%) but increased from 2015 to 2017. E-cigarette before cigarette users were more likely to perceive cigarette use as risky (adjusted odds ratios [aOR]: 1.40; 95% CI: 1.11-1.77) but also more likely to currently smoke cigarettes (aOR:1.30; 95% CI: 1.03-1.63) compared with those who initiated cigarettes before e-cigarettes. Both cigarette only initiators (aOR: .52; 95% CI: .33-.80) and e-cigarette only initiators (aOR: .22; 95% CI: .07-.16) were less likely to report future intentions to smoke compared with those who initiated cigarettes before e-cigarettes.

CONCLUSIONS

Initiation patterns related to e-cigarette and cigarette use among U.S. youth appears to be changing rapidly. Furthermore, patterns of initiation should be considered in future research as cigarette-related risk among different e-cigarette and cigarette use initiation patterns is heterogeneous.

How to Think-Not Feel-about Tobacco Harm Reduction

INTRODUCTION

The debate over tobacco harm reduction (THR) has divided the tobacco control community into two camps, one expressing serious reservations about THR whereas the other believes that reduced-risk products like e-cigarettes will disrupt the cigarette market. The often emotional debate would benefit from dispassionate data-based evaluation of evidence.

METHODS

After briefly discussing harm reduction in public health and specifically in tobacco control, this paper identifies major issues concerning e-cigarettes and reviews relevant evidence. Issues include: e-cigarettes' risks compared to cigarette smoking; the effect of vaping on youth smoking; vaping's impact on adult smoking cessation; the net long-term public health implications of vaping; and differences in views on policy issues. The intent is to provide a broad overview of issues and evidence, directing readers to more detailed reviews of specific issues.

FINDINGS

Principal findings include the following: (1) while longitudinal studies suggest that vaping increases never-smoking young people's odds of trying smoking, national survey data indicate that adolescents' 30-day smoking prevalence decreased at an unprecedented rate precisely whereas vaping increased. Use of all other tobacco products also declined. (2) Recent population-level studies add evidence that vaping is increasing adult smoking cessation. (3) Vaping is likely to make a positive contribution to public health.

CONCLUSIONS

THR can be a complement to, not a substitute for, evidenced-based tobacco control interventions. Tobacco control professionals need to focus on objective assessment of and discussion about the potential costs and benefits of THR.

IMPLICATIONS

Participants on both sides of the divisive THR debate need to examine the complicated issues and evidence more objectively. This entails considering both the potential benefits and costs associated with reduced-risk products like e-cigarettes. Furthermore, it requires examining different kinds of evidence when considering specific issues. For example, those concerned by longitudinal study findings that vaping increases students' trial of cigarettes should consider US national survey evidence that youth smoking has decreased at an unprecedented rate. A review of the major issues suggests that the potential of vaping to assist adult smokers to quit outweighs the potential negatives.

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.

The moderating effect of gender on the association between E-cigarette use and smoking status: A cross-sectional study

INTRODUCTION

The novel features of e-cigarettes in the recent vaping boom are appealing to females. Given increasing concerns about using e-cigarettes among females, understanding the patterns of using e-cigarettes in females compared to males is critical. We investigate the moderating effect of gender on the association between ever vaping and smoking status and gender differences in reason for ever vaping and in having ever stopped smoking.

METHODS

We used population data (n = 38,661) from the 2015, 2016, and 2017 Texas Behavioral Risk Factor Surveillance System (BRFSS) to examine a gender difference in ever vaping associated with smoking status. Additionally, we restricted the sample to current smokers who have ever vaped (n = 4733) to examine the association of gender with quitting smoking as reason for ever vaping and with having ever stopped smoking.

RESULTS

We found a significant association between ever vaping and gender (OR = 0.77, 95%CI = 0.65, 0.91). When smoking status was considered, female never-smokers had a significantly lower likelihood of ever vaping than male never-smokers (OR = 0.43, 95%CI = 0.27, 0.76). No significant gender difference was found in ever vaping to quit smoking (OR = 1.12, 95%CI = 0.73, 1.74) and having ever stopped smoking (OR = 1.41, 95%CI = 0.95, 2.10).

CONCLUSIONS

The findings of this study provide evidence of gender differences in vaping patterns. Female never-smokers are less likely than male never-smokers to experiment with e-cigarettes. However, there is no evidence of a gender difference in both ever vaping to quit smoking and having ever stopped smoking. Consistent monitoring of gender differences in using e-cigarettes and stratified policy approaches tailored for genders are necessary.

Initiation Sequence of E-Cigarette and Cigarette Smoking among US Adolescents: A National Study

BACKGROUND AND OBJECTIVES

The primary objectives were to: (1) examine the initiation sequence of e-cigarette use and cigarette smoking; (2) assess other substance use as a function of the initiation sequence of e-cigarettes and cigarettes; and (3) investigate the role of early e-cigarette initiation among US secondary school students.

METHODS

Data were collected via self-administered questionnaires from independent 2015 and 2016 nationally representative cross-sectional samples of 8th grade, 10th grade, and 12th grade students (N = 36 410).

RESULTS

The lifetime initiation sequence included: (1) e-cigarette use before cigarette smoking (1.7%); (2) e-cigarette use and cigarette smoking in same grade (4.2%); (3) cigarette smoking before e-cigarette use (6.1%); (4) e-cigarette use only (12.6%); (5) cigarette smoking only (3.6%); and (6) no e-cigarette use or cigarette smoking (71.8%). The risk of substance use was highest among dual users (regardless of initiation sequence), followed by cigarette smokers, e-cigarette users, and no e-cigarette use or cigarette smoking. The most prevalent initiation sequence of e-cigarette use involved initiating other substances before e-cigarettes, especially among older adolescents. Early initiation of e-cigarette use was associated with increased odds of substance use behaviors for all three age groups.

DISCUSSION AND CONCLUSIONS

Adolescents who report a history of both e-cigarette use and cigarette smoking should be considered at high risk for substance-related problems. Early initiation of e-cigarette use is a signal for other substance use.

SCIENTIFIC SIGNIFICANCE

Youth substance use prevention programs and prospective studies must take into account polysubstance use when addressing the relationships between e-cigarette use and cigarette smoking. (Am J Addict 2019;28:285-294).

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

A growing literature indicates that electronic cigarette use increases the risk of subsequent initiation of conventional smoking among cigarette-naïve adolescents in several Western countries. This research assesses the same relationship in an Asian country, Taiwan. The Taiwan Adolescent to Adult Longitudinal Study is a school-based survey that was carried out in two waves in 2014 (baseline) and in 2016 (follow-up). It employs probability sampling to create nationally representative samples of students in junior high school (mean age 13, 7th grade at baseline) and in senior high school (mean age 16, 10th grade at baseline). Data from this survey were analyzed via logistic regression to estimate the association between ever use of e-cigarettes at baseline and smoking initiation at follow-up, accounting for susceptibility to smoking, socio-demographic profile, depression status, and peer support. Among the 12,954 cigarette-naïve students surveyed, those with e-cigarette experience at baseline exhibited higher odds of smoking initiation at follow-up (Odds Ratio = 2.14, 95% CI (1.66, 2.75), p < 0.001). For the first time, we confirmed, through a longitudinal survey, a prospective association between ever use of e-cigarettes and smoking initiation in an Asian adolescent population. The restrictive policy on e-cigarettes currently in force in Taiwan is justified to prevent both e-cigarette and cigarette use among adolescents.

The Relationship Between Tobacco and Cannabis Use: A Review

BACKGROUND

Based on the prevalence and health implications of tobacco and cannabis use, aiming to reduce their use, especially among youth, is a sound objective at both the individual and public health level. A proper understanding of the relationships between tobacco and cannabis use may help to achieve this goal.

OBJECTIVES

To review the relationships between tobacco and cannabis use.

METHODS

A selective review of the literature.

RESULTS

We present an overview of the motivations for tobacco and cannabis use, and their perceived harmfulness. The article then reviews the gateway theory, reverse gateway theory, route of administration theory, and common liability theory. We describe the link between co-use and dependence symptoms, and the substitution phenomenon between tobacco and cannabis use. Three forms of simultaneous use-mulling, blunt smoking, and chasing-and their impacts are explained. We summarize the impact of tobacco use on cannabis (and vice versa) treatment outcomes, and, finally, review new treatments that simultaneously target tobacco and cannabis dependence. Most of the literature reviewed here relates to substance use among adolescents and young adults.

CONCLUSIONS

The use of tobacco and cannabis-two of the most widely used substances around the world-are strongly intertwined in several respects. Both health professionals and researchers should have well-informed views on this issue to better evaluate, understand, inform, and provide care to their patients.

Managing nicotine without smoke to save lives now: Evidence for harm minimization

Tobacco control has made strides in prevention and cessation, but deaths will not decline rapidly without massive behavior change. Currently, inhaled smoke from combusting tobacco is chiefly responsible for prematurely killing 7.2 million people worldwide and 530,000 in the United States annually. An array of noncombustible nicotine products (NNPs) has emerged and has disrupted the marketplace. Saving lives more speedily will require societal acceptance of locating a "sweet spot" within a three-dimensional framework where NNPs are simultaneously: 1. Less toxic, 2. Appealing (can reach smokers at scale), and 3. Satisfying (adequate nicotine delivery) to displace smoking. For this harm minimization framework to eliminate smoking, a laser focus on "smoking control" (not general tobacco control) is needed. By adopting these economically viable NNPs as part of the solution, NNPs can be smoking control's valued ally. Synthesis of the science indicates that policy and regulation can sufficiently protect youth while speeding the switch away from smoking. Despite some risks of nicotine dependence that can be mitigated but not eliminated, no credible evidence counters the assertion that NNPs will save lives if they displace smoking. But scientific evidence and advocacy has selectively exaggerated NNP harms over benefits. Accurate communication is crucial to dispel the misperception of NNPs harms and reassure smokers they can successfully replace smoking cigarettes with NNPs. Saving more lives now is an attainable and pragmatic way to call for alignment of all stakeholders and factions within traditional tobacco control rather than perpetuate the unrealized and unrealizable perfection of nicotine prohibition.

Tobacco product initiation is correlated with cross-product changes in tobacco harm perception and susceptibility: Longitudinal analysis of the Population Assessment of Tobacco and Health youth cohort

Youth initiation with one tobacco product is associated with risk of using additional tobacco types. How use of one product potentially encourages use of others could result from changing tobacco-related perceptions. This study aimed to evaluate how tobacco product initiation correlates with changes in susceptibility (curiosity and willingness) and perceived harm of other tobacco products. For each of cigarettes, e-cigarettes, hookah, and smokeless tobacco, youth (ages 12-16; N = 8005) rated perceived harm, curiosity, and willingness to try in Waves 1 and 2 of the Population Assessment of Tobacco and Health (United States, 2013-2015). For each product, we estimated associations between decreased harm rating, increased curiosity, or increased willingness with initiation (from never- to ever-use) of cigarettes, e-cigarettes, hookah, smokeless tobacco, or other combustible products using multivariate (multiple outcomes) regression, adjusting for other tobacco risk factors. Tobacco product initiation was associated with decreased perceived harm for that product and with decreased perceived harm, increased curiosity, and increased willingness in some, but not all, cross-product combinations. Most cross-product combinations of initiation and susceptibility yielded positive associations. For example, trying e-cigarettes was associated with concomitant increases in curiosity about cigarettes (OR: 5.69; 95% CI: 3.68, 8.79) and hookah (OR: 4.19; 95% CI: 2.55, 6.88) and with increased willingness to try cigarettes (OR: 9.61; 95% CI: 5.67, 16.3), hookah (OR: 8.46; 95% CI: 4.76, 15.0), and smokeless tobacco (OR: 3.48; 95% CI: 1.75, 6.94). New use of one tobacco product may catalyze subsequent use of others through cross-product changes in perceptions and susceptibility.

What Factors are Associated with Electronic Cigarette, Shisha-Tobacco and Conventional Cigarette Use? Findings from a Cross-Sectional Survey of Australian Adolescents?

BACKGROUND

Adolescents' use of electronic cigarettes and shisha-tobacco increased in several countries during the 2000s, including in the United States, United Kingdom and Canada. Few studies have examined the factors associated with exclusive e-cigarette or shisha-tobacco use and whether adolescents using these substances exclusively differ from those using traditional cigarettes.

OBJECTIVES

To examine the socio-demographic and behavioural correlates of exclusive e-cigarette and exclusive shisha-tobacco use to those found for users of tobacco cigarettes and multiple nicotine products in Australian adolescents.

METHODS

Cross-sectional survey of smoking behaviours of a random sample of 4,576 students in the Australian state of Victoria aged 12-17 conducted between June 2014 and December 2014.

RESULTS

Overall, 14% of students had used an e-cigarette with 3% using e-cigarettes exclusively. 13% had used shisha-tobacco, with 2% using shisha-tobacco exclusively. Most students (65%) using e-cigarette and shisha-tobacco (67%) had also used tobacco cigarettes. After adjusting for demographic factors, students using e-cigarettes only were more likely to have never used cannabis or drink alcohol in the past year compared to tobacco cigarette users. Compared to tobacco cigarette users, students using only shisha-tobacco were younger, less likely to use cannabis or alcohol or have friends or parents who smoke.

CONCLUSIONS

Most Australian adolescents who use alternative nicotine and tobacco-related products do so in conjunction with tobacco cigarettes. Students using e-cigarettes or shisha-tobacco exclusively were less likely to use other substances. Australian longitudinal studies are needed to determine whether this group of students are on a pathway to traditional tobacco use.

The Association Between Smoking and Electronic Cigarette Use in a Cohort of Young People

PURPOSE

Electronic cigarette (e-cigarette) use is associated with smoking initiation among young people; however, it is also possible that smoking is associated with e-cigarette initiation. This study explores these associations among young people in Great Britain.

METHODS

A longitudinal survey of 1,152 11- to 18-year-olds was conducted with baseline in April 2016 and follow-up between August and October 2016. Logistic regression models and causal mediation analyses assessed whether (1) ever e-cigarette use and escalation were associated with smoking initiation (ever smoking at follow-up) among baseline never smokers (n = 923), and (2) ever smoking and escalation were associated with e-cigarette initiation (ever e-cigarette use at follow-up) among baseline never e-cigarette users (n = 1,020).

RESULTS

At baseline, 19.8% were ever smokers and 11.4% were ever e-cigarette users. Respondents who were ever e-cigarette users (vs. never users, 53% vs. 8%, odds ratio [OR] = 11.89, 95% confidence interval [CI] = 3.56-39.72) and escalated their e-cigarette use (vs. did not, 41% vs. 8%, OR = 7.89, 95% CI = 3.06-20.38) were more likely to initiate smoking. Respondents who were ever smokers (vs. never smokers, 32% vs. 4%, OR = 3.54, 95% CI = 1.68-7.45) and escalated their smoking (vs. did not, 34% vs. 6%, OR = 5.79, 95% CI = 2.55-13.15) were more likely to initiate e-cigarette use. There was a direct effect of ever e-cigarette use on smoking initiation (OR = 1.34, 95% CI = 1.05-1.72), and ever smoking on e-cigarette initiation (OR = 1.08, 95% CI = 1.01-1.17); e-cigarette and smoking escalation, respectively, did not mediate these effects.

CONCLUSIONS

Among young people in Great Britain, ever e-cigarette use is associated with smoking initiation, and ever smoking is associated with e-cigarette initiation.

E-Cigarettes: Use, Effects on Smoking, Risks, and Policy Implications

Since e-cigarettes appeared in the mid-2000s, some practitioners, researchers, and policy makers have embraced them as a safer alternative to conventional cigarettes and an effective way to stop smoking. While e-cigarettes deliver lower levels of carcinogens than do conventional cigarettes, they still expose users to high levels of ultrafine particles and other toxins that may substantially increase cardiovascular and noncancer lung disease risks, which account for more than half of all smoking-caused deaths, at rates similar to conventional cigarettes. Moreover, rather than stimulating smokers to switch from conventional cigarettes to less dangerous e-cigarettes or quitting altogether, e-cigarettes are reducing smoking cessation rates and expanding the nicotine market by attracting youth.

Harm Minimization and Tobacco Control: Reframing Societal Views of Nicotine Use to Rapidly Save Lives

Inhalation of the toxic smoke produced by combusting tobacco products, primarily cigarettes, is the overwhelming cause of tobacco-related disease and death in the United States and globally. A diverse class of alternative nicotine delivery systems (ANDS) has recently been developed that do not combust tobacco and are substantially less harmful than cigarettes. ANDS have the potential to disrupt the 120-year dominance of the cigarette and challenge the field on how the tobacco pandemic could be reversed if nicotine is decoupled from lethal inhaled smoke. ANDS may provide a means to compete with, and even replace, combusted cigarette use, saving more lives more rapidly than previously possible. On the basis of the scientific evidence on ANDS, we explore benefits and harms to public health to guide practice, policy, and regulation. A reframing of societal nicotine use through the lens of harm minimization is an extraordinary opportunity to enhance the impact of tobacco control efforts.

E-cigarette use and quantity of cigarette smoking among adolescent cigarette smokers: A finite mixture model analysis

BACKGROUND

E-cigarette use is popular among adolescents and youth, but its long-term public health implications remain largely unknown. Much of the literature has focused on understanding the relationship between e-cigarette use and youth cigarette initiation. However, very little is known about e-cigarette use and cigarette quantity among those who continue to smoke cigarettes. The objective of the present study was to examine the association between current e-cigarette use and quantity of cigarette smoking.

METHODS

Cross-sectional data on current smokers were drawn from the 2014-2015 Canadian Student Tobacco, Alcohol and Drugs Survey among high school students (n = 1411). A finite mixture model (FMM) was employed to account for unobserved heterogeneity due to clusters of finite sub-populations.

RESULTS

Current e-cigarette users reported smoking more conventional cigarettes in the past week compared to non-e-cigarette users (t [1409] = 4.7998; p < 0.001 in unadjusted analysis). Results from a finite mixture regression showed that current e-cigarette use was significantly associated with the number of cigarettes smoked in the past week, but only among light smokers (IRR = 1.40; CI = 1.05-1.85). However, additional analyses found that the association between e-cigarette use and quantity of cigarette smoked varied by individual smoking pattern. An FMM with a group or class modelling using individual smoking pattern showed a weaker association between e-cigarette use and quantity of cigarette smoking.

CONCLUSION

Findings of this study suggest that the significant association between e-cigarette use and quantity of cigarette smoking may be driven by patterns of use among experimental or beginner smokers.

Association of Noncigarette Tobacco Product Use With Future Cigarette Smoking Among Youth in the Population Assessment of Tobacco and Health (PATH) Study, 2013-2015

IMPORTANCE

Approximately 90% of adult smokers first tried a cigarette by 18 years of age, and even infrequent smoking in adolescence is associated with established adult smoking. Noncigarette tobacco use is increasing and could stimulate subsequent conventional cigarette smoking in youths.

OBJECTIVE

To estimate the longitudinal association between noncigarette tobacco use and subsequent cigarette smoking initiation among US youth.

DESIGN, SETTING, AND PARTICIPANTS

In this prospective cohort study of the Population Assessment of Tobacco and Health (PATH) waves 1 (September 12, 2013, to December 14, 2014) and 2 (October 23, 2014, to October 30, 2015), a nationally representative sample of youths who never smoked a conventional cigarette at baseline and completed wave 2 follow-up (N = 10 384) was studied. PATH retention at follow-up was 87.9%.

EXPOSURES

Ever use and past 30-day use of electronic cigarettes (e-cigarettes), hookah, noncigarette combustible tobacco, or smokeless tobacco at baseline.

MAIN OUTCOMES AND MEASURES

Ever use and past 30-day use of cigarettes at follow-up.

RESULTS

The present analysis was based on the 10 384 PATH youth respondents who reported never having smoked a cigarette in wave 1 and whose cigarette ever or past 30-day use was reported in wave 2 (mean [SD] age, 14.3 [1.7] years; age range, 12-17 years; 5087 [49.1%] female; 4829 [52.5%] white). At 1-year follow-up, 469 (4.6%) of all baseline never-smoking youths had tried a cigarette and 219 (2.1%) had smoked a cigarette within the past 30 days. Cigarette ever use at follow-up was higher among youths who had ever used e-cigarettes (78 [19.1%]), hookah (60 [18.3%]), noncigarette combustible tobacco (45 [19.2%]), or smokeless tobacco (29 [18.8%]) at baseline. After adjusting for sociodemographic, environmental, and behavioral smoking risk factors and for baseline ever use of other tobacco products, the odds of past 30-day cigarette use at follow-up were approximately twice as high among baseline ever users of e-cigarettes (odds ratio [OR], 1.87; 95% CI, 1.15-3.05), hookah (OR, 1.92; 95% CI, 1.17-3.17), noncigarette combustible tobacco (OR, 1.78; 95% CI, 1.00-3.19), and smokeless tobacco (OR, 2.07; 95% CI, 1.10-3.87). Youths who had tried more than 1 type of tobacco product at baseline had 3.81 (95% CI, 2.22-6.54) greater adjusted odds of past 30-day cigarette smoking at follow-up than did baseline never tobacco users.

CONCLUSIONS AND RELEVANCE

Any use of e-cigarettes, hookah, noncigarette combustible tobacco, or smokeless tobacco was independently associated with cigarette smoking 1 year later. Use of more than 1 product increased the odds of progressing to cigarette use.

Exclusive e-cigarette use predicts cigarette initiation among college students

INTRODUCTION

An increasing body of research indicates that use of electronic nicotine delivery systems (ENDS) predicts cigarette initiation. However, no studies examine if risk for cigarette initiation varies for exclusive ENDS users versus users of ENDS and other tobacco products. This study examined if: a) cigarette-naïve young adults (i.e., never cigarette users) who ever used ENDS had a greater odds of initiating cigarettes than non-ENDS users over a 1.5year period and b) the odds of cigarette initiation was consistent across exclusive ENDS users and users of ENDS and at least one tobacco product.

METHODS

Participants were 2558 cigarette-naïve 18-25year old (M=19.71; SD=1.61) students from 24 Texas colleges who participated in a four-wave study, with six months between each wave.

RESULTS

Overall, 11% of students reported cigarette initiation by wave 4. Of those, 20.1% were wave 1 ENDS users and 8.4% were non-ENDS users. Multivariable, multilevel discrete-time hazard models indicated that wave 1 ENDS use predicted subsequent cigarette initiation, over and above the significant effects of cigarette use susceptibility, family-of-origin tobacco use, friend cigarette use, and other tobacco use. Additional findings indicated that exclusive ENDS users had a greater odds than non-users of subsequent cigarette initiation. Among users of alternative tobacco products, ENDS users did not have a greater odds of initiation than non-ENDS users.

CONCLUSION

Findings extend existing research by showing that ENDS use by young adults is a specific risk factor for later cigarette initiation and not an extension of a constellation of existing tobacco use behaviors.

A longitudinal study of electronic cigarette use and onset of conventional cigarette smoking and marijuana use among Mexican adolescents

PURPOSE

This study evaluated whether e-cigarette trial among Mexican adolescents increased the likelihood of trial and use of conventional cigarettes or marijuana use at follow-up.

METHOD

A school-based longitudinal survey was conducted in 60 public middle schools from the three largest cities in Mexico. Students (12-13years old) were surveyed in 2015 and followed up 20 months later (n=6574). Generalized estimating equations models were used to evaluate the association between e-cigarette trial at baseline and conventional cigarettes smoking and marijuana use at follow-up.

RESULT

Adolescents who had tried e-cigarettes (but not cigarettes) at baseline were more likely to have tried conventional cigarettes at followup compared to adolescents who had tried neither e-cigarettes nor cigarettes (43% vs. 24%, respectively; RR 1.41, 95% CI 1.18-1.70). We also found that adolescents who had tried both conventional cigarettes and e-cigarettes at baseline were more likely to have tried marijuana at follow-up compared to adolescents who had tried neither tobacco product (20% vs. 4%, respectively; RR 2.67, 95% CI 1.78-4.02). Trial of only e-cigarettes was not independently associated with marijuana use at followup.

CONCLUSIONS

Adolescents who had tried e-cigarettes were more likely to have tried conventional cigarettes and marijuana 20 months later. Although e-cigarettes have been banned in Mexico, it is likely that additional policies and public health campaigns are needed to reduce adolescent use of e-cigarettes and its consequences.

Do electronic cigarettes increase cigarette smoking in UK adolescents? Evidence from a 12-month prospective study

BACKGROUND

In cross-sectional surveys, increasing numbers of adolescents report using both electronic cigarettes (e-cigarettes) and cigarettes. This study assessed whether adolescent e-cigarette use was associated prospectively with initiation or escalation of cigarette use.

METHODS

Data were from 2836 adolescents (aged 13-14 years at baseline) in 20 schools in England. At baseline, breath carbon monoxide levels, self-reported e-cigarette and cigarette use, sex, age, friends and family smoking, beliefs about cigarette use and percentage receiving free school meals (measure of socioeconomic status) were assessed. At 12-month follow-up, self-reported cigarette use was assessed and validated by breath carbon monoxide levels.

RESULTS

At baseline, 34.2% of adolescents reported ever using e-cigarettes (16.0% used only e-cigarettes). Baseline ever use of e-cigarettes was strongly associated with subsequent initiation (n=1726; OR 5.38, 95% CI 4.02 to 7.22; controlling for covariates, OR 4.06, 95% CI 2.94 to 5.60) and escalation (n=318; OR 1.91, 95% CI 1.14 to 3.21; controlling for covariates, this effect became non-significant, OR 1.39, 95% CI 0.97 to 1.82) of cigarette use.

CONCLUSIONS

This is the first study to report prospective relationships between ever use of e-cigarettes and initiation and escalation of cigarette use among UK adolescents. Ever use of e-cigarettes was robustly associated with initiation but more modestly related to escalation of cigarette use. Further research with longer follow-up in a broader age range of adolescents is required.

Association Between Initial Use of e-Cigarettes and Subsequent Cigarette Smoking Among Adolescents and Young Adults: A Systematic Review and Meta-analysis

Importance

The public health implications of e-cigarettes depend, in part, on whether e-cigarette use affects the risk of cigarette smoking.

Objective

To perform a systematic review and meta-analysis of longitudinal studies that assessed initial use of e-cigarettes and subsequent cigarette smoking.

Data Sources

PubMed, EMBASE, Cochrane Library, Web of Science, the 2016 Society for Research on Nicotine and Tobacco 22nd Annual Meeting abstracts, the 2016 Society of Behavioral Medicine 37th Annual Meeting & Scientific Sessions abstracts, and the 2016 National Institutes of Health Tobacco Regulatory Science Program Conference were searched between February 7 and February 17, 2017. The search included indexed terms and text words to capture concepts associated with e-cigarettes and traditional cigarettes in articles published from database inception to the date of the search.

Study Selection

Longitudinal studies reporting odds ratios for cigarette smoking initiation associated with ever use of e-cigarettes or past 30-day cigarette smoking associated with past 30-day e-cigarette use. Searches yielded 6959 unique studies, of which 9 met inclusion criteria (comprising 17 389 adolescents and young adults).

Data Extraction and Synthesis

Study quality and risk of bias were assessed using the Newcastle-Ottawa Scale and the Risk of Bias in Non-randomized Studies of Interventions tool, respectively. Data and estimates were pooled using random-effects meta-analysis.

Main Outcomes and Measures

Among baseline never cigarette smokers, cigarette smoking initiation between baseline and follow-up. Among baseline non-past 30-day cigarette smokers who were past 30-day e-cigarette users, past 30-day cigarette smoking at follow-up.

Results

Among 17 389 adolescents and young adults, the ages ranged between 14 and 30 years at baseline, and 56.0% were female. The pooled probabilities of cigarette smoking initiation were 30.4% for baseline ever e-cigarette users and 7.9% for baseline never e-cigarette users. The pooled probabilities of past 30-day cigarette smoking at follow-up were 21.5% for baseline past 30-day e-cigarette users and 4.6% for baseline non-past 30-day e-cigarette users. Adjusting for known demographic, psychosocial, and behavioral risk factors for cigarette smoking, the pooled odds ratio for subsequent cigarette smoking initiation was 3.62 (95% CI, 2.42-5.41) for ever vs never e-cigarette users, and the pooled odds ratio for past 30-day cigarette smoking at follow-up was 4.28 (95% CI, 2.52-7.27) for past 30-day e-cigarette vs non-past 30-day e-cigarette users at baseline. A moderate level of heterogeneity was observed among studies (I2 = 60.1%).

Conclusions and Relevance

e-Cigarette use was associated with greater risk for subsequent cigarette smoking initiation and past 30-day cigarette smoking. Strong e-cigarette regulation could potentially curb use among youth and possibly limit the future population-level burden of cigarette smoking.

Relationship between trying an electronic cigarette and subsequent cigarette experimentation in Scottish adolescents: a cohort study

BACKGROUND

This study examines whether young never smokers in Scotland, UK, who have tried an e-cigarette are more likely than those who have not, to try a cigarette during the following year.

METHODS

Prospective cohort survey conducted in four high schools in Scotland, UK during February/March 2015 (n=3807) with follow-up 1 year later. All pupils (age 11-18) were surveyed. Response rates were high in both years (87% in 2015) and 2680/3807 (70.4%) of the original cohort completed the follow-up survey. Analysis was restricted to baseline 'never smokers' (n=3001/3807), 2125 of whom were available to follow-up (70.8%).

RESULTS

At baseline, 183 of 2125 (8.6%) never smokers had tried an e-cigarette and 1942 had not. Of the young people who had not tried an e-cigarette at baseline, 249 (12.8%) went on to try smoking a cigarette by follow-up. This compares with 74 (40.4%) of those who had tried an e-cigarette at baseline. This effect remained significant in a logistic regression model adjusted for smoking susceptibility, having friends who smoke, family members' smoking status, age, sex, family affluence score, ethnic group and school (adjusted OR 2.42 (95% CI 1.63 to 3.60)). There was a significant interaction between e-cigarette use and smoking susceptibility and between e-cigarette use and smoking within the friendship group.

CONCLUSIONS

Young never smokers are more likely to experiment with cigarettes if they have tried an e-cigarette. Causality cannot be inferred, but continued close monitoring of e-cigarette use in young people is warranted.

E-cigarette use as a predictor of cigarette smoking: results from a 1-year follow-up of a national sample of 12th grade students

OBJECTIVE

To prospectively examine vaping as a predictor of future cigarette smoking among youth with and without previous cigarette smoking experience. A secondary aim is to investigate whether vaping may desensitise youth to the dangers of smoking.

METHODS

Analysis of prospective longitudinal panel data from the nationally representative Monitoring the Future study. The analysis is based on 347 12th grade students who were part of a randomly selected subsample that completed in-school surveys in 2014 and were resurveyed 1-year later.

RESULTS

Among youth who had never smoked a cigarette by 12th grade, baseline, recent vapers were more than 4 times (relative risk (RR)=4.78) more likely to report past-year cigarette smoking at follow-up, even among youth who reported the highest possible level of perceived risk for cigarette smoking at baseline. Among 12th grade students who had smoked in the past but had not recently smoked at baseline, recent vapers were twice (RR=2.15) as likely to report smoking in the past 12 months at the follow-up. Vaping did not predict cessation of smoking among recent smokers at baseline. Among never-smokers at baseline, recent vapers were more than 4 times (RR=4.73) more likely to move away from the perception of cigarettes as posing a 'great risk' of harm, a finding consistent with a desensitisation process.

CONCLUSIONS

These results contribute to the growing body of evidence supporting vaping as a one-way bridge to cigarette smoking among youth. Vaping as a risk factor for future smoking is a strong, scientifically-based rationale for restricting youth access to e-cigarettes.