scholarly journals Investigating gateway effects using the PATH study

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 264 ◽  
Author(s):  
Peter Lee ◽  
John Fry
Keyword(s):  
Cigarette Smoking ◽  
Odds Ratio ◽  
Meta Analysis ◽  
Smoking Initiation ◽  
Continuous Variable ◽  
Sensitivity Analyses ◽  
Health Study ◽  
Cigarette Use ◽  
Tobacco Products ◽  
Residual Confounding

Background: A recent meta-analysis of nine cohort studies in youths reported that baseline ever e-cigarette use strongly predicted cigarette smoking initiation in the next 6-18 months, with an adjusted odds ratio of 3.62 (95% confidence interval 2.42-5.41).  A recent review of e-cigarettes agreed there was substantial evidence for this “gateway effect”.  However, the number of confounders considered in the studies was limited, so we investigated whether the effect might have resulted from inadequate adjustment, using Waves 1 and 2 of the Population Assessment of Tobacco and Health study. Methods: Our main analyses considered Wave 1 never cigarette smokers who, at Wave 2, had information available on smoking initiation.  We constructed a propensity score for ever e-cigarette use from Wave 1 variables, using this to predict ever cigarette smoking.  Sensitivity analyses accounted for use of other tobacco products, linked current e-cigarette use to subsequent current smoking, or used propensity scores for ever smoking or ever tobacco product use as predictors.  We also considered predictors using data from both waves to attempt to control for residual confounding from misclassified responses. Results: Adjustment for propensity dramatically reduced the unadjusted odds ratio (OR) of 5.70 (4.33-7.50) to 2.48 (1.85-3.31), 2.47 (1.79-3.42) or 1.85 (1.35-2.53), whether adjustment was made as quintiles, as a continuous variable or for the individual variables.  Additional adjustment for other tobacco products reduced this last OR to 1.59 (1.14-2.20).  Sensitivity analyses confirmed adjustment removed most of the gateway effect.  Control for residual confounding also reduced the association. Conclusions: We found that confounding is a major factor, explaining most of the observed gateway effect.  However, our analyses are limited by small numbers of new smokers considered and the possibility of over-adjustment if taking up e-cigarettes affects some predictor variables.  Further analyses are intended using Wave 3 data which should avoid these problems.

scholarly journals Investigating gateway effects using the PATH study

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 264 ◽  
Author(s):  
Peter Lee ◽  
John Fry
Keyword(s):  
Cigarette Smoking ◽  
Propensity Scores ◽  
Meta Analysis ◽  
Smoking Initiation ◽  
Continuous Variable ◽  
Tobacco Product ◽  
Sensitivity Analyses ◽  
Cigarette Use ◽  
Product Use ◽  
Residual Confounding

Background: A recent meta-analysis of nine cohort studies in youths reported that baseline ever e-cigarette use strongly predicted cigarette smoking initiation in the next 6-18 months, with an adjusted odds ratio (OR) of 3.62 (95% confidence interval 2.42-5.41). A recent e-cigarette review agreed there was substantial evidence for this “gateway effect”. As the number of confounders considered in the studies was limited we investigated whether the effect might have resulted from inadequate adjustment, using Waves 1 and 2 of the US PATH study. Methods: Our main analyses considered Wave 1 never cigarette smokers who, at Wave 2, had data on smoking initiation.We constructed a propensity score for ever e-cigarette use from Wave 1 variables, using this to predict ever cigarette smoking. Sensitivity analyses accounted for other tobacco product use, linked current e-cigarette use to subsequent current smoking, or used propensity scores for ever smoking or ever tobacco product use as predictors. We also considered predictors using data from both waves, attempting to reduce residual confounding from misclassified responses. Results: Adjustment for propensity dramatically reduced the unadjusted OR of 5.70 (4.33-7.50) to 2.48 (1.85-3.31), 2.47 (1.79-3.42) or 1.85 (1.35-2.53), whether adjustment was made as quintiles, as a continuous variable or for the individual variables. Additional adjustment for other tobacco products reduced this last OR to 1.59 (1.14-2.20). Sensitivity analyses confirmed adjustment removed most of the gateway effect. Control for residual confounding also reduced the association. Conclusions: We found that confounding is a major factor, explaining most of the observed gateway effect. However, our analyses are limited by small numbers of new smokers considered and the possibility of over-adjustment if taking up e-cigarettes affects some predictor variables. Further analyses are intended using Wave 3 data to try to minimize these problems, and clarify the extent of any true gateway effect.

Association between e-cigarette use initiated after cigarette smoking and smoking abstinence: a cross-sectional study among adolescent established smokers in the USA

2021 ◽  
pp. tobaccocontrol-2020-055943
Author(s):  
Franziska S Saller ◽  
Israel T Agaku ◽  
Filippos T Filippidis
Keyword(s):  
High School Students ◽  
Cigarette Smoking ◽  
Electronic Cigarettes ◽  
Smoking Initiation ◽  
Sensitivity Analyses ◽  
Inverse Association ◽  
Cigarette Use ◽  
School Students ◽  
Cross Sectional ◽  
The Usa

BackgroundRecent years have seen a rapid increase in the popularity of electronic cigarettes (e-cigarettes) among adolescents in the USA. Evidence on their role in the continuation of or abstinence from cigarette smoking among young smokers remains scarce.ObjectiveTo examine the relationship between e-cigarette use initiated after cigarette smoking and abstinence from cigarette smoking among US adolescent established smokers.MethodsThe data were drawn from the 2015–2018 National Youth Tobacco Survey—a nationally representative survey of US middle and high school students. Multivariable logistic regression was used to assess the association between ever e-cigarette use and past 30-day abstinence from cigarette smoking. The analytical sample comprised ever established cigarette smokers with or without a history of e-cigarette use after smoking initiation.ResultsNeither experimental (adjusted OR 0.67, 95% CI 0.39–1.14) nor prior established (adjusted OR 1.56, 95% CI 0.96–2.56) nor current established (adjusted OR 0.65, 95% CI 0.41–1.03) e-cigarette use was statistically significantly associated with subsequent abstinence from cigarette smoking among adolescent ever established smokers. These findings were largely consistent across sensitivity analyses using alternative key definitions, although experimental and current established e-cigarette use was significantly negatively associated with past 6-month abstinence.ConclusionsWe found no evidence that e-cigarette use among US adolescents already smoking cigarettes is associated with subsequent abstinence from cigarette smoking; there was some evidence of an inverse association among experimental and current established e-cigarette users. These findings could inform future regulatory and public health efforts regarding youth e-cigarette use and the reduction of youth cigarette smoking in the USA.

scholarly journals Further investigations of gateway effects using the PATH study

2020 ◽  
Author(s):  
Peter N Lee ◽  
John S Fry
Keyword(s):  
Tobacco Use ◽  
Causal Effect ◽  
Smoking Initiation ◽  
Continuous Variable ◽  
Tobacco Product ◽  
Sensitivity Analyses ◽  
Health Study ◽  
Using Data ◽  
Confounder Adjustment ◽  
Confounding Adjustment

Abstract Background: Considerable interest exists in whether e-cigarette use (“vaping”) by youths increases the risk of initiating cigarette smoking. Based on Waves 1 and 2 of the Population Assessment of Tobacco and Health study we reported that adjustment for propensity for vaping using Wave 1 variables explained about 80% of the unadjusted relationship. This analysis may be over-adjusted had vaping at Wave 1 affected some variables recorded then. Here we present analyses using Waves 1 to 3 to avoid this possibility. Methods: Our main analysis M1 concerned those who had never smoked by Wave 2 and never vaped by Wave 1. Wave 2 vaping was linked to smoking initiation by Wave 3, adjusting for Wave 1 predictors. Sensitivity analyses excluded other tobacco product users at Wave 1, included other tobacco product use as an additional predictor, or were based on propensity for ever smoking or ever any tobacco use, rather than ever vaping. Other analyses adjusted for propensity as derived originally, or ignored Wave 1 data. Other analyses used grouped age (only available originally) or exact age (available now) as a confounder variable, attempted residual confounding adjustment by modifying values of predictor variables using data later recorded, or considered interactions with age. Results: In M1, propensity adjustment removed about 50% of the excess odds ratio (i.e. OR–1), the unadjusted OR, 5.60 (95% CI 4.52-6.93) becoming 3.37 (2.65-4.28), 3.11 (2.47-3.92) or 3.27 (2.57-4.16) depending whether adjustment was for propensity as a continuous variable, as quintiles, or for the 16 variables making up the propensity score. Many factors studied hardly affected the results, including using grouped or exact age, consideration of other tobacco products, including interactions, or using predictors of smoking or tobacco use rather than vaping. The clearest conclusion was that analyses avoiding over-adjustment only explained about 50% of the excess OR whereas analyses subject to over-adjustment explained about 80%. Conclusions: Although much of the unadjusted gateway effect results from uncontrolled confounding, our current analysis provides stronger evidence of a causal effect of vaping than did our earlier analysis. However, some doubts remain about the completeness of confounder adjustment.

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

F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1915 ◽  
Author(s):  
Peter N. Lee ◽  
Katharine J. Coombs ◽  
Esther F. Afolalu
Keyword(s):  
Cigarette Smoking ◽  
Smoking Prevalence ◽  
Smoking Initiation ◽  
Health Impact ◽  
Cigarette Use ◽  
Peer Attitudes ◽  
National Surveys ◽  
Externalising Disorders ◽  
Analytical Review ◽  
Residual Confounding

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.

scholarly journals Sex Difference in the Association between Electronic Cigarette Use and Subsequent Cigarette Smoking among U.S. Adolescents: Findings from the PATH Study Waves 1–4

2021 ◽  
Vol 18 (4) ◽  
pp. 1695
Author(s):  
Zongshuan Duan ◽  
Yu Wang ◽  
Jidong Huang
Keyword(s):  
Mental Health ◽  
Cigarette Smoking ◽  
Tobacco Use ◽  
Mental Health Problems ◽  
Cigarette Use ◽  
Tobacco Products ◽  
Estimation Equations ◽  
Nationally Representative ◽  
Prospective Association

E-cigarettes are the most-used tobacco products among U.S. adolescents. Emerging evidence suggests that adolescents using e-cigarettes are at elevated risk for initiating cigarette smoking. However, whether this risk may differ by sex remains unknown. This study analyzed data from Wave 1 to 4 of the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative longitudinal survey. Generalized estimation equations (GEE) were performed to estimate the associations between baseline e-cigarette use and subsequent cigarette smoking, controlling for sociodemographic characteristics, mental health conditions, and other tobacco use. Effect modifications by sex were examined. Multivariate analyses showed that, among baseline never cigarette smokers, past-30-day e-cigarette use at baseline waves was significantly associated with past-30-day cigarette smoking at follow-up waves (aOR = 3.90, 95% CI: 2.51–6.08). This association was significantly stronger for boys (aOR = 6.17, 95% CI: 2.43–15.68) than for girls (aOR = 1.10, 95% CI: 0.14–8.33). Additionally, using other tobacco products, older age, and having severe externalizing mental health problems at baseline were significantly associated with an increased likelihood of cigarette smoking at follow-up. The prospective association between e-cigarette use and cigarette smoking differs by sex among U.S. adolescents. Sex-specific tobacco control interventions may be warranted to curb the youth tobacco use epidemic.

scholarly journals E-cigarette use and onset of first cigarette smoking among adolescents: An empirical test of the ‘common liability’ theory

F1000Research ◽  
2020 ◽  
Vol 8 ◽  
pp. 2099
Author(s):  
Hui G. Cheng ◽  
Edward G. Largo ◽  
Maria Gogova
Keyword(s):  
Structural Equation Modeling ◽  
Cigarette Smoking ◽  
Structural Equation ◽  
Equation Modeling ◽  
Cigarette Use ◽  
Tobacco Products ◽  
Latent Construct ◽  
The Us ◽  
The Common ◽  
The Relationship

Background: E-cigarettes have become the most commonly used tobacco products among youth in the United States (US) recently. It is not clear whether there is a causal relationship between e-cigarette use and the onset of cigarette smoking. The “common liability” theory postulates that the association between e-cigarette use and cigarette smoking can be attributed to a common risk construct of using tobacco products. This study aims to investigate the relationship between ever e-cigarette use and cigarette smoking onset in the US using a structural equation modeling approach guided by the “common liability” theory. Methods: The study population is non-institutionalized civilian adolescents living in the US, sampled in the longitudinal Population Assessment of Tobacco and Health study. Information about tobacco product use was obtained via confidential self-report. A structural equation modeling approach was used to estimate the relationship between e-cigarette use at wave 1 and the onset of cigarette smoking at wave 2 after controlling for a latent construct representing a “common liability to use tobacco products.” Results:  After controlling for a latent construct representing a “common liability to use tobacco products”, ever e-cigarette use does not predict the onset of cigarette smoking (β=0.13, 95% CI= -0.07, 0.32, p=0.204). The latent “common liability to use tobacco products” is a robust predictor for the onset of cigarette smoking (β=0.38; 95% CI=0.07, 0.69; p=0.015). Conclusions: Findings from this study provide supportive evidence for the ‘common liability’ underlying observed associations between e-cigarette use and smoking onset.

scholarly journals Developmental Changes in Genetic and Shared Environmental Contributions to Smoking Initiation and Subsequent Smoking Quantity in Adolescence and Young Adulthood

2015 ◽  
Vol 18 (5) ◽  
pp. 497-506 ◽  
Author(s):  
Cristina B. Bares ◽  
Kenneth S. Kendler ◽  
Hermine H. Maes
Keyword(s):  
Cigarette Smoking ◽  
Young Adulthood ◽  
Environmental Influences ◽  
Smoking Initiation ◽  
Developmental Changes ◽  
Adolescent And Young Adult ◽  
Shared Environment ◽  
Adult Health ◽  
Cigarette Use ◽  
Smoking Quantity

Background: Few studies examining the genetic architecture of cigarette smoking have focused on adolescents or examined developmental changes in additive genetic, shared environment, and unique environmental influences on liability to initiate cigarette smoking and quantity of cigarettes smoked. The aim of this study was to add to the literature on liability to initiate and use cigarettes during adolescence using a nationally representative sample. Method: Data for this study came from adolescent and young adult twin pairs (aged 14–33 years) from the National Longitudinal Study of Adolescent to Adult Health. We ran a series of developmental causal–contingent–common pathway models to examine whether additive genetic, shared, and unique environmental influences on liability to the initiation of cigarette use are shared with those on smoking quantity, and whether their contributions change across development. Results: We found evidence for a developmental shift in genetic and shared environmental contributions to cigarette use. Early in adolescence, genetic and environmental influences work independently on liability to cigarette smoking initiation and quantity of cigarettes smoked, but liability to these behaviors becomes correlated as individuals age into young adulthood. Conclusions: These findings provide insight into the causal processes underlying the liability to smoke cigarettes. With age, there is greater overlap in the genetic and environmental factors that influence the initiation of cigarette smoking and quantity of cigarettes smoked.

scholarly journals Tobacco price and use following California Proposition 56 tobacco tax increase

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0257553
Author(s):  
Christian Gunadi ◽  
Tarik Benmarhnia ◽  
Martha White ◽  
John P. Pierce ◽  
Sara B. McMenamin ◽  
...  
Keyword(s):  
Smokeless Tobacco ◽  
Control Method ◽  
Cigarette Consumption ◽  
Sensitivity Analyses ◽  
Synthetic Control ◽  
Cigarette Use ◽  
Cigarette Price ◽  
Cigarette Tobacco ◽  
Tobacco Products ◽  
Tobacco Tax

Background California Proposition 56 increased cigarette excise tax by $2 per pack with equivalent increases on non-cigarette tobacco products. We estimated the changes in cigarette price, cigarette use, and non-cigarette use following the implementation of Proposition 56 in California in 2017. Methods Seven waves of Tobacco Use Supplements to the Current Population Survey (TUS-CPS) 2011–2019 data were used to obtain state-level aggregate self-reported outcomes, including cigarette price per pack, current and daily cigarette use, cigarette consumption per day, and current and daily use of non-cigarette tobacco products (hookah, pipe, cigar, and smokeless tobacco). A modified version of a synthetic control method was used to create a “synthetic” California that best resembled pre-policy sociodemographic characteristics and outcome trends in California while correcting time-invariant pre-policy differences. Various sensitivity analyses were also conducted. Results The implementation of Proposition 56 was associated with an increase in self-reported cigarette price per pack in California ($1.844, 95%CI: $0.153, $3.534; p = 0.032). No evidence suggested that Proposition 56 was associated with the changes in the prevalence of current or daily cigarette use, cigarette consumption per day, or the prevalence of current or daily use of non-cigarette tobacco products. Conclusion Most of the cigarette tax increase following Proposition 56 in California was passed on to consumers. There is a lack of evidence that the implementation of Proposition 56 was associated with the changes in the use of cigarettes and other tobacco products such as hookah, pipe, cigar, and smokeless tobacco.

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

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1915
Author(s):  
Peter N. Lee ◽  
Katharine J. Coombs ◽  
Esther F. Afolalu
Keyword(s):  
Cigarette Smoking ◽  
Smoking Prevalence ◽  
Smoking Initiation ◽  
Health Impact ◽  
Discussion Paper ◽  
National Surveys ◽  
Precise Adjustment ◽  
Confounding Variables ◽  
Analytical Review ◽  
Residual Confounding

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.

Cigarette smoking and schizophrenia: Mendelian randomisation study

2020 ◽  
pp. 1-6
Author(s):  
Jianhua Chen ◽  
Ruirui Chen ◽  
Siying Xiang ◽  
Ningning Li ◽  
Chengwen Gao ◽  
...  
Keyword(s):  
Cigarette Smoking ◽  
Association Studies ◽  
Smoking Initiation ◽  
Sensitivity Analyses ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Complex Behaviour ◽  
Asian Populations ◽  
Smoking Behaviours

Background The link between schizophrenia and cigarette smoking has been well established through observational studies. However, the cause–effect relationship remains unclear. Aims We conducted Mendelian randomisation analyses to assess any causal relationship between genetic variants related to four smoking-related traits and the risk of schizophrenia. Method We performed a two-sample Mendelian randomisation using summary statistics from genome-wide association studies (GWAS) of smoking-related traits and schizophrenia (7711 cases, 18 327 controls) in East Asian populations. Single nucleotide polymorphisms (SNPs) correlated with smoking behaviours (smoking initiation, smoking cessation, age at smoking initiation and quantity of smoking) were investigated in relation to schizophrenia using the inverse-variance weighted (IVW) method. Further sensitivity analyses, including Mendelian randomisation-Egger (MR-Egger), weighted median estimates and leave-one-out analysis, were used to test the consistency of the results. Results The associated SNPs for the four smoking behaviours were not significantly associated with schizophrenia status. Pleiotropy did not inappropriately affect the results. Conclusions Cigarette smoking is a complex behaviour in people with schizophrenia. Understanding factors underlying the observed association remains important; however, our findings do not support a causal role of smoking in influencing risk of schizophrenia.

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