Evaluating the mutual pathways among electronic cigarette use, conventional smoking and nicotine dependence

The "Gateway" hypothesis: evaluation of evidence and alternative explanations

BACKGROUND

Electronic nicotine delivery systems (ENDS) offer a substantial harm reduction opportunity for adults who smoke and are unlikely to quit. However, a major concern about ENDS is their use by non-smoking youth, and particularly whether ENDS are acting as a "gateway" that leads youth to later start smoking cigarettes. However, evidence for the gateway hypothesis can be interpreted in alternative ways, e.g. that youth who have certain characteristics were already predisposed to use both ENDS and cigarettes ("common liability" explanation).

AIMS

This commentary provides an evaluation of the gateway hypothesis that is accessible by a lay audience. This paper first reviews and evaluates the evidence interpreted as supporting the gateway hypothesis. Important alternative explanations (i.e., common liability) are discussed, as are different types of evidence (i.e., population-level trends) that can help differentiate between these competing explanations.

OVERVIEW

Evidence for the gateway hypothesis is based on the finding that youth who use ENDS are more likely to also smoke cigarettes. However, this evidence suffers from an important flaw: these studies fail to fully account for some youths' pre-existing tendency to use products containing nicotine, and inappropriately interpret the results as ENDS use causing some youth to smoke. Common liability studies suggest that ENDS use does not, in and of itself, directly cause youth to later smoke cigarettes, beyond their pre-existing tendency to use products containing nicotine. Population-level trends show that youth cigarette smoking declined faster after ENDS use became common, which contradicts the central prediction of the gateway hypothesis (i.e. that youth smoking would be more common following ENDS uptake, than otherwise be expected).

CONCLUSION

Evidence offered in support of the gateway hypothesis does not establish that ENDS use causes youth to also smoke cigarettes. Instead, this evidence is better interpreted as resulting from a common liability to use both ENDS and cigarettes. Population-level trends are inconsistent with the gateway hypothesis, and instead are consistent with (but do not prove) ENDS displacing cigarettes. Policies based on misinterpreting a causal gateway effect may be ineffective at best, and risk the negative unintended consequence of increased cigarette smoking.

Examining Predictors of Nicotine Dependence in Korean Adolescents : Comparing Ever Quitters and Never Quitters

Despite growing research on adolescent smokers, evidence for the differences between the two smoker groups who are ever quitters and never quitters is limited. The study aimed to examine predictors of nicotine dependence (ND) in Korean adolescents by comparing ever quitters and never quitters. Data from 349 adolescents were collected through an online survey. Among respondents, most of them were male, living with families, and were enrolled at schools. Data were analyzed by dividing participants into two groups - ever quitters and never quitters. The study found that adolescents' ND was commonly predicted by smoking peers and anxiety. However, schooling status was significantly associated with ever quitters' ND only. In the total sample, never-quitters were associated with higher ND compared to ever-quitters. This study did not control for differences among ever quitters in terms of the number of attempts to quit smoking and did not significantly control age effects in the sample. Based on study results, we suggest various policy implications. Cessation intervention should be designed keeping in mind the smokers' previous quit attempts and their motivation. It is also recommended that individually tailored smoking cessation programs be used to address the heterogenous nature of the adolescents.

Prevalence, lived experiences and user profiles in e-cigarette use: A mixed methods study among French college students

BACKGROUND

Little is known about e-cigarette use in French students. Our aims were to estimate the prevalence of e-cigarette experimentation and current e-cigarette use; describe the reasons for using e-cigarettes; explore the vaping experience and identify the profiles of e-cigarette users.

METHODS

We used a sequential, explanatory mixed methods design in a sample of French college students. Quantitative data was collected online for a cross-sectional analysis among 1698 students. Two separate analysis based on the thematic analysis and the Grounded Theory were also performed in 20 semi-structured interviews, focusing former and current smokers also current vapers.

RESULTS

The prevalence of e-cigarette experimentation was 39.3% (95% CI: 35.2-44.0) and 5.1% (95% CI: 3.2-8.0) of students were current e-cigarette users. Experimentation was opportunistic while current usage was rational, requiring to acquire a personal electronic device, getting used to its technicality, appreciating its availability, discretion, and learning the practice. In this context, three distinct groups of e-cigarette users were identified, based on assumed identity, tobacco and e-cigarette use, the functions assigned to e-cigarettes, and intentions with regards to vaping in the future.

CONCLUSION

Despite some limitations mainly related to the participants self-selection, this research showed that while many smokers and former smokers have tried e-cigarettes in this student population, few have continued to use them continuously. Moreover, these current e-cigarette users were a heterogeneous group. Longitudinal studies are needed in young adult smokers for a better understanding of how their tobacco and e-cigarette use affect each other and change over time.

A Decision-Theoretic Public Health Framework for Heated Tobacco and Nicotine Vaping Products

Markets for nicotine vaping products (NVPs) and heated tobacco products (HTPs) have grown as these products became positioned as harm-reduction alternatives to combusted tobacco products. Herein, we present a public health decision-theoretic framework incorporating different patterns of HTP, NVP, and cigarette use to examine their impacts on population health. Our framework demonstrates that, for individuals who would have otherwise smoked, HTP use may provide public health benefits by enabling cessation or by discouraging smoking initiation and relapse. However, the benefits are reduced if more harmful HTP use replaces less harmful NVP use. HTP use may also negatively impact public health by encouraging smoking by otherwise non-smokers or by encouraging initiation or relapse into smoking. These patterns are directly influenced by industry behavior as well as public policy towards HTPs, NVPs, and cigarettes. While substantial research has been devoted to NVPs, much less is known about HTPs. Better information is needed to more precisely define the health risks of HTPs compared to cigarettes and NVPs, the relative appeal of HTPs to consumers, and the likelihood of later transitioning to smoking or quitting all products. While our analysis provides a framework for gaining that information, it also illustrates the complexities in distinguishing key factors.

Experienced Effects on Well-Being following Smoking Cessation: Findings from the 2020 ITC Four Country Smoking and Vaping Survey

BACKGROUND AND AIMS

There has been limited research addressing changes in subjective well-being as a result of quitting smoking. This paper examines recent ex-smokers' well-being related experiences overall and as a function of (1) duration of cessation and (2) continued nicotine use from vaping.

METHODS

A sample of 1379 ever-daily smoking ex-smokers (quit for up to 5 years) from the 2020 ITC Four Country Smoking and Vaping Survey (Australia, Canada, the UK, and the US), of which 27.1% currently vaped daily. Well-being measures were perceived changes post-quitting in emotion coping (stress and negative emotions), enjoyment of life, and day-to-day functioning. We also assessed the level of persisting worry about past smoking leading to future health problems.

RESULTS

Overall, among those answering all four well-being measures, 51.8% of the ex-smokers reported positive effects and no negatives, but 27.3% reported at least one negative effect, with the remainder reporting no change in any measure. Positive effects were greater among those who had quit more than 1 year prior. The largest improvement (56.3%) was for daily functioning, which showed improvement over time since having quit. Current daily vapers reported similar well-being as those not vaping; however, fewer daily vapers reported worsening ability to cope with stress (10.2% vs. 20.7%). Overall, 84% reported being worried about future negative health effects of smoking, with no clear differences by quitting duration or vaping status.

CONCLUSIONS

Most ex-smokers reported changes in their well-being since quitting, with more reporting improvements than declines. Well-being improved with duration of time since quitting, but did not appear to be influenced by daily vaping use, but stress coping may be better among vapers. Persisting worries about possible future health effects from smoking may be reducing the experienced benefits of quitting smoking for some.

Age of e-cigarette initiation in USA young adults: Findings from the Population Assessment of Tobacco and Health (PATH) study (2013-2017)

INTRODUCTION

There is a lack of research prospectively estimating the age of e-cigarette initiation in U.S. young adults.

METHODS

Secondary analysis of PATH young adults across 2013-2017 (waves 1-4) were conducted. We prospectively estimated age of initiation of: ever, past 30-day, and fairly regular e-cigarette use using weighted interval-censoring survival analyses. Interval-censoring Cox proportional hazard models adjusting for sex, race/ethnicity, and previous use of six other tobacco products (cigarettes, traditional cigars, filtered cigars, cigarillos, hookah, and smokeless tobacco) were fitted for each of the three e-cigarette initiation outcomes.

RESULTS

Among never e-cigarette users, by age 21, 16.8% reported ever use, 7.2% reported past 30-day use, and 2.3% reported fairly regular e-cigarette use. Males had increased risk of initiating ever, past 30-day, and fairly regular e-cigarette use at earlier ages compared to females. Hispanic young adults had increased risk of initiating ever and past 30-day e-cigarette use at earlier ages compared to Non-Hispanic White young adults. Previous use of other tobacco products before e-cigarette initiation increased the risk of an earlier age of e-cigarette initiation.

CONCLUSION

Prevention and education campaigns should focus on young adults in order to alleviate the public health burden of initiating e-cigarette use at earlier ages.

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.

Characteristics of electronic cigarette user and traditional smokers: 2017 Youth risk behavior surveillance system

BACKGROUND

Although electronic cigarette (e-cigarette) use among adolescents rapidly has increased over the past decade, which has raised concerns over the corresponding behavioral health risks, the current literature presents limited data for understanding the characteristics of adolescent e-cigarette users.

OBJECTIVE

The purpose of this study was to (1) identify general characteristics that may be shared between e-cigarette users and traditional cigarette smokers and (2) examine the unique characteristics of e-cigarette users vis-à-vis traditional cigarette smokers.

DESIGN

Cross-sectional descriptive study.

SAMPLE AND DATA SOURCE

A total of 14,765 9th- to 12-grade students drawn from the CDC 2017 Youth Risk Behavior Surveillance System.

RESULTS

We observed that the prevalence of marijuana, alcohol, and other illicit drug use was higher among e-cigarette users and traditional tobacco users than non-users. Moreover, physically active adolescents were more likely to use e-cigarettes than those who were physically inactive, although the level of the activity did not predict smoking status.

CONCLUSION

We recommend that primary prevention strategies for e-cigarette use should be incorporated in physical education programs and target adolescents who engage in not only health risk behaviors, but also health promoting behaviors, such as physical activity.

Data Visualization Tools of Tobacco Product Use Patterns, Transitions and Sex Differences in the PATH Youth Data

INTRODUCTION

Evaluations of multiple tobacco product use and temporal changes in patterns of use are complicated by a large number of combinations and transitions. Visualization tools could easily identify most common patterns and transitions.

METHODS

Set intersection bar plots describe ever use of five tobacco products among 12-17 years old youth in wave 1 of the Population Assessment of Tobacco and Health (PATH) study (N = 11 497). Heat maps visualize unweighted frequencies of transitions from ever use at wave 1 (2013-2014) to past 12-month use at wave 2 (2014-2015). Weighted calibrated heat maps assess differences in relative frequencies of transitions by pattern at wave 1 and identify differences in transitions by sex.

RESULTS

The most common tobacco product ever use patterns in wave 1 were of cigarettes only, e-cigarettes only or hookah only, followed by ever use of both cigarettes and e-cigarettes. Initiation of use between waves was uncommon. The most frequent transition among those who reported use at wave 2 but not at wave 1 (N = 971) was to e-cigarette use (N = 301). However, among e-cigarette-only ever users at wave 1 (N = 260), about half did not report any product use at wave 2. Use of three or more products remained stable. Adolescent girls compared to boys appeared more likely to report hookah use at both waves.

CONCLUSION

Set intersection bar plots and heat maps are useful for visualizing tobacco product use patterns and transitions, especially for multiple products. Both techniques could identify common problematic tobacco use patterns across and within populations.

IMPLICATIONS

Given the growing complexity of the youth tobacco use landscape, approaches to efficiently communicate patterns of multiple tobacco product use should be used more often. This study introduces set intersection bar plots and modified versions of heat maps to the tobacco product literature and illustrates their use in the PATH youth sample. These techniques are useful for visualizing absolute and relative frequencies of multiple possible patterns and transitions. They also suggest targets for subsequent statistical inference such as sex differences in hookah use. The methods can be applied more generally for data visualization wherever large number of combinations occurs.

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-cigarettes: toxicological fiasco or better than not giving up smoking?]

E‑cigarettes are increasingly used to replace tobacco cigarettes and to stop smoking, but mainly in the sense of dual use. There is lively debate about the assessment of the health risks of e‑cigarettes, but so far there are no comprehensive data for direct comparison with tobacco cigarettes. Other points of controversy include the potential for smoking cessation and the risk of moving from e‑cigarettes to tobacco cigarettes (gateway hypothesis). The present overview comes to the conclusion that, in accordance with the health policy already largely implemented in Great Britain, e‑cigarettes represent a greatly reduced health risk compared with tobacco cigarettes and are certainly suitable for giving up smoking.

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.

Dual Users Compared to Smokers: Demographics, Dependence, and Biomarkers

INTRODUCTION

The availability of electronic cigarettes (e-cigarettes) has profoundly changed the tobacco product landscape. In the United States, almost 6 million adults use both combustible and e-cigarettes (ie, dual users). The goal of this study was to understand how smokers and dual users differ in terms of demographics, cigarette dependence, and exposure to carcinogens.

METHODS

An observational cohort (smokers, n = 166, ≥5 cigarettes/day for 6 months and no e-cigarette use in 3 months; dual users, n = 256, smoked daily for 3 months and used e-cigarettes at least once/week for the past 3 months) completed baseline assessments of demographics, tobacco use, and dependence. They also provided breath samples for carbon monoxide (CO) assay and urine samples for cotinine, 3-hydroxycotinine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) assays.

RESULTS

Compared to smokers, dual users (mean e-cigarette use = 5.5 days/week [SD = 1.9]) were significantly younger and more likely to be white, have more education, report a history of psychiatric co-morbidity, and smoke fewer cigarettes per day. There were no differences in CO, cotinine, or 3-hydroxycotinine levels; however, dual users had significantly lower levels of NNAL than did smokers. Most smokers and dual users had no plans to quit smoking within the next year; 91% of dual users planned to continue using e-cigarettes for at least the next year.

CONCLUSIONS

In this community sample, dual users are supplementing their smoking with e-cigarette use. Dual users, versus smokers, smoked fewer cigarettes per day and delayed their first cigarette of the day, but did not differ in quitting intentions.

IMPLICATIONS

This comparison of a community sample of established dual users and exclusive smokers addresses key questions of dependence and health risks of dual use in real-world settings. Dual users were more likely to be white, younger, have more than a high school education and have a psychiatric history. Dual users also smoked significantly fewer cigarettes and had lower levels of NNAL (a carcinogen), but they did not differ from exclusive smokers in CO or cotinine levels, suggesting that they supplemented their nicotine intake via e-cigarettes.

Is dual use of nicotine products and cigarettes associated with smoking reduction and cessation behaviours? A prospective study in England

OBJECTIVES

To investigate associations of dual use of e-cigarettes and cigarettes with subsequent quitting activity (smoking reduction, quit attempts and use of evidence-based cessation aids). To overcome potential confounding by factors associated with use of pharmacological support, we selected dual use of over-the-counter nicotine replacement therapy (OTC NRT) and cigarettes as a behavioural control.

DESIGN

Prospective cohort study with 6-month follow-up.

SETTING

England, 2014-2016.

PARTICIPANTS

413 current smokers participating in the Smoking Toolkit Study, a representative survey of adults in England, who reported current use of e-cigarettes or OTC NRT and provided data at 6-month follow-up.

MAIN OUTCOME MEASURES

The exposure was dual use of e-cigarettes or OTC NRT at baseline. Outcomes were change in cigarette consumption, quit attempts and use of evidence-based cessation aids during quit attempts over 6-month follow-up. Relevant sociodemographic and smoking characteristics were included as covariates.

RESULTS

After adjustment for covariates, dual e-cigarette users smoked two fewer cigarettes per day at follow-up than at baseline compared with dual OTC NRT users (B=2.01, 95% CI -3.62; -0.39, p=0.015). While dual e-cigarette users had 18% lower odds than dual OTC NRT users to make a quit attempt at follow-up (risk ratio (RR) 0.82, 95% CI 0.67 to 1.00, p=0.049), the groups did not differ in use of cessation aids (RR 1.06, 95% CI 0.93 to 1.21, p=0.388).

CONCLUSIONS

Dual use of e-cigarettes is associated with a greater reduction in cigarette consumption than dual use of OTC NRT. It may discourage a small proportion of users from making a quit attempt compared with dual OTC NRT use but it does not appear to undermine use of evidence-based cessation aids.

Is E-cigarette use a gateway to marijuana use? Longitudinal examinations of initiation, reinitiation, and persistence of e-cigarette and marijuana use

BACKGROUND

Concerns have been raised regarding e-cigarette use as a potential stepping-stone to marijuana use. Based on Kandel's gateway hypothesis, this study investigated if e-cigarette use could lead to marijuana use by testing two hypotheses with a longitudinal national U.S. adult sample, including (1) primary hypothesis: e-cigarette use is a gateway to marijuana use; and (2) falsification hypothesis: marijuana use is not a gateway to e-cigarette use.

METHODS

Adults were extracted from the Population Assessment of Tobacco and Health Study Waves 1-3 (2013-2016). For primary hypotheses, based on baseline e-cigarette use statuses, three study groups were defined, and three logistic regressions were conducted to examine associations between baseline e-cigarette use and follow-up marijuana use initiation, reinitiation, and persistence, respectively. Similarly, for falsification hypotheses, three additional study groups were defined, and three logistic regressions were conducted to examine associations between baseline marijuana use and follow-up e-cigarette use behaviors.

RESULTS

Baseline e-cigarette use was associated with marijuana use initiation and reinitiation (ORs = 2.08, 1.37, respectively, both ps < .05) but not persistence at follow-up. Additionally, baseline marijuana use was associated with only e-cigarette use initiation (OR = 2.23, p < .01) but not reinitiation or persistence at follow-up.

CONCLUSIONS

Findings partially support the gateway hypothesis that e-cigarette use could be a steppingstone to marijuana use reinitiation among the U.S. adults. The mechanisms and behavioral characteristics, such as etiological and psychosocial factors, that may pertain to the progression from e-cigarette use to reinitiation of other substance use should be further investigated to inform effective behavioral, educational, and policy interventions.

Youth smoking and anti-smoking policies in North Dakota: a system dynamics simulation study

BACKGROUND

The current study utilizes system dynamics to model the determinants of youth smoking and simulate effects of anti-smoking policies in the context of North Dakota, a state with one of the lowest cigarette tax rates in the USA.

METHODS

An explanatory model was built to replicate historical trends in the youth smoking rate. Three different policies were simulated: 1) an increase in cigarette excise taxes; 2) increased funding for CDC-recommended comprehensive tobacco control programs; and 3) enforcement of increased retailer compliance with age restrictions on cigarette sales.

RESULTS

The explanatory model successfully replicated historical trends in adolescent smoking behavior in North Dakota from 1992 to 2014. The policy model showed that increasing taxes to $2.20 per pack starting in 2015 was the most effective of the three policies, producing a 32.6% reduction in youth smoking rate by 2032. Other policies reduced smoking by a much lesser degree (7.0 and 3.2% for comprehensive tobacco control program funding and retailer compliance, respectively). The effects of each policy were additive.

CONCLUSIONS

System dynamics modeling suggests that increasing cigarette excise taxes are particularly effective at reducing adolescent smoking rates. More generally, system dynamics offers an important complement to conventional analysis of observational data.

Dependence motives of young adult users of electronic nicotine delivery systems

INTRODUCTION

Nicotine dependence contributes to changes in tobacco use among young adults. However, research examining salient dependence motives in young adult users of electronic nicotine delivery systems (ENDS) is limited. This study examined the association of dependence motives with ENDS use or lifetime quit attempt, and tests sex moderation in these relationships.

METHODS

Young adults (N = 304; age 18-24) self-identifying as regular ENDS users and self-reporting vaping within a week of data collection completed an online survey. They reported demographics, past 30-day vaping and smoking days and frequency, and lifetime quit attempt. Dependence motives were measured with the 14-item Wisconsin Inventory for Smoking Dependency Motives. Backward-stepwise models regressed ENDS use behaviors or lifetime quit attempt onto dependence motives, and separately onto the interactions between motives and sex.

RESULTS

Tolerance was positively associated with daily ENDS use frequency (b = 0.34, p < .001) past 30-day vaping days (b = 1.50, p < .001), and negatively associated with lifetime quit attempt (OR = 0.58, p = .005). Loss of control was negatively associated with daily ENDS use frequency (b = -0.24, p < .001) and past 30-day vaping days (b = -1.48, p < .001), and positively associated with lifetime quit attempt (OR = 1.56, p = .002). Craving was positively associated with lifetime quit attempt among males (OR = 1.83, p = .006) but not females (OR = 0.84, p = .51).

CONCLUSION

Tolerance and loss of control were uniquely associated with ENDS use behaviors across all analytic models, although effects for loss of control were counter-intuitive. Understanding the relationship between dependence motives and ENDS use behaviors or attempts to quit may provide targets for preventive interventions against increased or continued ENDS use.

Adolescent Dual Use Classification and Its Association With Nicotine Dependence and Quit Intentions

PURPOSE

Electronic cigarettes (e-cigarette) use is rapidly increasing in the U.S., especially among adolescents. A significant number of adolescents use both cigarettes and e-cigarettes, often referred to as dual use. We used a new classification of dual use, taking into account the frequency of use of both products. In addition, we examined the association between dual use with time to first cigarette after waking (a nicotine dependence measure) and quit intention.

METHODS

Data were drawn from the 2015-2018 National Youth Tobacco Survey. We grouped participants by dual use frequency. Multivariable logistic regression was used to examine the association of dual use frequency with nicotine dependence and quit intention.

RESULTS

Different categories of dual users varied in demographic characteristics and beliefs on the harms of cigarette smoking and e-cigarette use. Compared with cigarette-only smokers, significantly higher odds of nicotine dependence were found for high-frequency e-cigarette dual users (within 5 minutes of awakening, odds ratio [OR]: 1.67, 95% confidence interval [CI], 1.07-2.62; within 30 minutes, OR: 1.61, 95% CI, 1.15-2.27), high-frequency cigarette dual users (5 minutes, OR: 2.85, 95% CI, 1.76-4.63; within 30 minutes, OR: 4.14, 95% CI, 2.96-5.80), and high-frequency dual users (5 minutes, OR: 4.46, 95% CI, 2.88-6.91; 30 minutes, OR: 3.94, 95% CI, 2.43-6.42). In addition, high-frequency e-cigarette dual users had significantly lower quit intention compared with both cigarette-only smokers and low-frequency dual users.

CONCLUSIONS

Findings highlight the need for a standard, granulated classification of dual user, as important characteristics may vary between different categories. Future studies on dual use should consider categorizing dual use into the four classifications described in this study.

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

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

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

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

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

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

Role of Poor Oral Hygiene in Causation of Oral Cancer-a Review of Literature

Oral squamous cell carcinomas (OSCC) are among the commonest cancers in South East Asia and more so in the Indian subcontinent. The role of tobacco and alcohol in the causation of these cancers is well-documented. Poor oral hygiene (POH) is often seen to co-exist in patients with OSCC. However, the role of poor oral hygiene in the etio-pathogenesis of these cancers is controversial. We decided to evaluate the available literature for evaluating the association of POH with OSCC. A thorough literature search of English-language articles in MEDLINE, PubMed, Cochrane Database of Systematic Reviews, and Web of Science databases was conducted, and 93 relevant articles were short-listed. We found that POH was strongly associated with oral cancers. It aids the carcinogenic potential of other known carcinogens like tobacco and alcohol. Even on adjusting for known confounding factors like tobacco, alcohol use, education, and socio-economic strata, presence of POH exhibits higher odds of developing oral cancer.

Examining the relationship of vaping to smoking initiation among US youth and young adults: a reality check

Background

The 2018 National Academies of Sciences, Engineering, and Medicine Report found substantial evidence that electronic cigarette use (vaping) by youth is strongly associated with an increased risk of ever using cigarettes (smoking) and moderately associated with progressing to more established smoking. However, the Report also noted that recent increases in vaping have been associated with declining rates of youth smoking. This paper examines the temporal relationship between vaping and youth smoking using multiple data sets to explore the question of whether vaping promotes smoking initiation in the USA.

Methods

Using publicly available, nationally representative data on smoking and vaping among youth and young adults, we conducted a trend line analysis of deviations from long-term trends in smoking starting from when vaping became more prevalent.

Results

There was a substantial increase in youth vaping prevalence beginning in about 2014. Time trend analyses showed that the decline in past 30-day smoking prevalence accelerated by two to four times after 2014. Indicators of more established smoking rates, including the proportion of daily smokers among past 30-day smokers, also decreased more rapidly as vaping became more prevalent.

Conclusions

The inverse relationship between vaping and smoking was robust across different data sets for both youth and young adults and for current and more established smoking. While trying electronic cigarettes may causally increase smoking among some youth, the aggregate effect at the population level appears to be negligible given the reduction in smoking initiation during the period of vaping’s ascendance.