Dataset Information

Electronic Cigarette Use and Progression From Experimentation to Established Smoking.

ABSTRACT: BACKGROUND:It has been shown that never-smoking adolescents who try electronic cigarettes (e-cigarettes) are at increased risk of subsequent conventional cigarette smoking. We evaluated associations between e-cigarette use and progression to established smoking among adolescents who had already tried cigarettes. METHODS:Among participants (age 12-17 years) in the nationally representative Population Assessment of Tobacco and Health survey who had smoked a cigarette (?1 puff) but not yet smoked 100 cigarettes (N = 1295), we examined 3 outcomes at 1-year follow-up as a function of baseline e-cigarette use: (1) having smoked ?100 cigarettes (established smoking), (2) smoking during the past 30 days, and (3) both having smoked ?100 cigarettes and past 30-day smoking (current established smoking). Survey-weighted multivariable logistic regression models were fitted to obtain odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for smoking risk factors. RESULTS:Versus e-cigarette never use, having ever used e-cigarettes was positively associated with progression to established cigarette smoking (19.3% vs 9.7%), past 30-day smoking (38.8% vs 26.6%), and current established smoking (15.6% vs 7.1%). In adjusted models, e-cigarette ever use positively predicted current established smoking (OR: 1.80; 95% CI: 1.04-3.12) but did not reach statistical significance (? = .05) for established smoking (OR: 1.57; 95% CI: 0.99-2.49) and past 30-day smoking (OR: 1.32; 95% CI: 0.99-1.76). CONCLUSIONS:Among adolescent cigarette experimenters, using e-cigarettes was positively and independently associated with progression to current established smoking, suggesting that e-cigarettes do not divert from, and may encourage, cigarette smoking in this population.

SUBMITTER: Chaffee BW

PROVIDER: S-EPMC5869336 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Electronic Cigarette Use and Progression From Experimentation to Established Smoking.

Chaffee Benjamin W BW Watkins Shannon Lea SL Glantz Stanton A SA

Pediatrics 20180305 4

<h4>Background</h4>It has been shown that never-smoking adolescents who try electronic cigarettes (e-cigarettes) are at increased risk of subsequent conventional cigarette smoking. We evaluated associations between e-cigarette use and progression to established smoking among adolescents who had already tried cigarettes.<h4>Methods</h4>Among participants (age 12-17 years) in the nationally representative Population Assessment of Tobacco and Health survey who had smoked a cigarette (≥1 puff) but n ...[more]

PMID: 29507167

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Project description:Background: The microbiome is increasingly being linked to cancer risk. Little is known about the lung and oral cavity microbiomes in healthy smokers (SM), and even less for electronic cigarette (EC) users, compared healthy never-smokers (NS). Methods: In a cross-sectional pilot study of SM (N=8), EC users (N=10) and NS (N=10) saliva and bronchoscopy-collected bronchoalveolar lavage samples were collected. Bacteria species were identified through metatranscriptome profiling by RNA-sequencing to study associations with the lung and oral microbiome. Pairwise comparisons and linear modeling was assessed with false discovery rates <0.1. Results: Total bacterial load was similar for the SM, EC users and NS, and there was no differences in the bacterial diversity across groups. In the lung, there were 44 bacterial species that were statistically significantly different for SM/NS, 80% of which were decreased in the SM. There were 12 bacterial species that were different for SM/EC users, all of which were decreased, 10 of which were also identified in the SM/NS comparison. The 2 bacterial species unique to SM/EC comparison were Neisseria sp. KEM232 and Curvibacter sp. AEP1-3. From the top 5 decreased species in SM/EC, 3 were also identified in the SM/NS comparison (Neisseria elongata, Neisseria sicca, and Haemophilus parainfluenzae) and 2 of these were unique to the SM/EC comparison (Neisseria zoodegmatis and Ottowia sp. oral taxon 894). There were 8 species increased in SM compared to NS, none of which are known to be clinically significant. In the oral microbiome, 152 bacteria species were differentially abundant for the SM/NS analysis, and only 17 for the EC/NS comparison, all which were also present in SM/NS comparisons. There were 21 bacteria that were differentially abundant in both the lung and oral cavity for SM and NS, 95% also were decreased in the SM. Conclusion: Smoking and EC use do not appear to materially affect the lung microbiome, although differences are noted of unclear clinical significance. Most differentially abundant bacteria decreased, which may be due to a toxic effect of cigarette smoke, including a change in humidity or heating. Given the low number of overlapping oral and lung microbes, the oral microbiome does not appear to be a good surrogate for smoking-related effects in the lung.

Project description:ImportanceThe prevalence of electronic nicotine delivery systems (ENDS) use, including e-cigarettes, among US young adults (YAs) has raised questions about how these products may affect future tobacco and nicotine use among YAs. Given this prevalence and that young adulthood is a critical period for the establishment of tobacco and nicotine use, it is important to consider the association between ENDS use and cigarette smoking specifically in this age group.ObjectiveTo examine whether ENDS use frequency or intensity is associated with changes in cigarette smoking among US YA ever smokers during 1 year.Design, setting, and participantsThis cohort study used 3 waves of data (2013-2014, 2014-2015, and 2015-2016) from the Population Assessment of Tobacco and Health (PATH) Study, an ongoing longitudinal cohort study of adults and youth. Unweighted 1:6 propensity score matching was used to match participants on wave 1 risk factors for ENDS use at wave 2. The changes in smoking between wave 2 and wave 3 were assessed using the matched sample. In total, 1096 ENDS-naive, ever cigarette-smoking YAs (18-24 years of age) at wave 1 who participated in wave 2 and wave 3 and who had complete data in the PATH Study were included in the analyses, which were conducted from August 2018 to October 2019.ExposuresNever ENDS use (n = 987), any previous 30-day ENDS use (n = 109), 1 to 5 days of ENDS use in the previous 30 days (n = 75), and 6 or more days ENDS use in the previous 30 days at wave 2 (n = 34).Main outcomes and measuresThe analytic sample was selected using multiple variables based on peer-reviewed literature supporting associations with ENDS use. The main outcomes-changes in cigarette smoking behavior between wave 2 and wave 3-were defined using 2 measures: (1) change in smoking frequency, defined as the number of smoking days in the previous 30 days at wave 3 vs wave 2, and (2) change in smoking intensity, defined as the number smoking days in the previous 30 days multiplied by the mean number of cigarettes consumed on smoking days at wave 3 vs wave 2.ResultsThe present cohort analyses included 1096 YA ever smokers who were ENDS naive at wave 1. The majority of the sample were women (609 [55.6%]) and White individuals (698 [63.7%]), and the mean (SD) age was 21.4 (1.9) years. In wave 1, 161 YAs (14.7%) were daily smokers in the previous 30 days. After propensity score matching, no statistically significant associations were observed between any definition of wave 2 ENDS use and changes in either the frequency or intensity of smoking at wave 3.Conclusions and relevanceIn this cohort study of US YA ever smokers, ENDS use was not associated with either decreased or increased cigarette smoking during a 1-year period. However, it is possible that the rapidly evolving marketplace of vaping products may lead to different trajectories of YA cigarette and ENDS use in the future.

Project description:ImportanceThe electronic cigarette (EC) has become popular among smokers who wish to reduce their tobacco use levels or quit smoking, but its effectiveness as a cessation aid is uncertain.ObjectiveTo examine the association of regular EC use with the number of cigarettes smoked per day, smoking cessation among current smokers, and smoking relapse among former smokers.Design, setting, and participantsThe CONSTANCES (Consultants des Centres d'Examens de Santé) cohort study, based in France, began recruiting participants January 6, 2012, and is currently ongoing. Participants were enrolled in CONSTANCES through 2015, and included 5400 smokers (mean [SD] follow-up of 23.4 [9.3] months) and 2025 former smokers (mean [SD] follow-up of 22.1 [8.6] months) at baseline who quit smoking in 2010, the year in which ECs were introduced in France, or afterward. Analyses were performed from February 8, 2017, to October 15, 2018.Main outcomes and measuresThe association between EC use and the number of cigarettes smoked during follow-up was studied using mixed regression models. The likelihood of smoking cessation was studied using Poisson regression models with robust sandwich variance estimators. The association between EC use and smoking relapse among former smokers was studied using Cox proportional hazards regression models. All statistical analyses were adjusted for sociodemographic characteristics, duration of follow-up, and smoking characteristics.ResultsAmong the 5400 daily smokers (2906 women and 2494 men; mean [SD] age, 44.9 [12.4] years), regular EC use was associated with a significantly higher decrease in the number of cigarettes smoked per day compared with daily smokers who did not use ECs (-4.4 [95% CI, -4.8 to -3.9] vs -2.7 [95% CI, -3.1 to -2.4]), as well as a higher adjusted relative risk of smoking cessation (1.67; 95% CI, 1.51-1.84]). At the same time, among the 2025 former smokers (1004 women and 1021 men; mean [SD] age, 43.6 [12.1] years), EC use was associated with an increase in the rate of smoking relapse among former smokers (adjusted hazard ratio, 1.70; 95% CI, 1.25-2.30).Conclusions and relevanceThis study's findings suggest that, among adult smokers, EC use appears to be associated with a decrease in smoking level and an increase in smoking cessation attempts but also with an increase in the level of smoking relapse in the general population after approximately 2 years of follow-up.

Project description:IntroductionThe 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.MethodsCross-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.ResultsAfter 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.ConclusionsE-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.ImplicationsThis 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.

Project description:Importance:There is an ongoing debate about whether electronic cigarettes (e-cigarettes) are the solution to the tobacco epidemic or a new public health threat. Large representative studies are needed to study e-cigarette use in the general population, but hardly any have been published. Objectives:To estimate the prevalence of e-cigarette use and to investigate the association of e-cigarette use with smoking habits, demographic factors, and respiratory symptoms. Design, Setting, and Participants:Cross-sectional, population-based study of random samples of the population, performed within the Obstructive Lung Disease in Northern Sweden (OLIN) study and West Sweden Asthma Study (WSAS). The same validated questionnaire including identical questions was used in OLIN and WSAS. In 2016, OLIN and WSAS conducted postal questionnaire surveys in random samples of adults aged 20 to 75 years. In OLIN, 6519 participated (response rate, 56.4%); in WSAS, 23?753 participated (response rate, 50.1%). Main Outcomes and Measures:Electronic cigarette use, smoking habits, and respiratory symptoms. Results:Of 30?272 participants (16?325 women [53.9%]), 3897 (12.9%) were aged 20 to 29 years; 4242 (14.0%), 30 to 39 years; 5082 (16.8%), 40 to 49 years; 6052 (20.0%), 50 to 59 years; 6628 (21.9%), 60 to 69 years; and 4371 (14.4%), 70 to 75 years. The number of current smokers was 3694 (12.3%), and 7305 (24.4%) were former smokers. The number of e-cigarette users was 529 (2.0%), and e-cigarette use was more common among men (275 of 12?347 [2.2%; 95% CI, 2.0%-2.5%]) than women (254 of 14?022 [1.8%; 95% CI, 1.6%-2.0%]). Among current smokers, 350 of 3566 (9.8%; 95% CI, 8.8%-10.8%) used e-cigarettes compared with 79 of 6875 (1.1%; 95% CI, 0.9%-1.3%) in former smokers and 96 of 15?832 (0.6%; 95% CI, 0.5%-0.7%) in nonsmokers (P?<?.001). Among e-cigarette users who answered the survey question about cigarette-smoking habits (n?=?525), 350 (66.7%; 95% CI, 62.7%-70.7%) were current smokers, 79 (15.0%; 95% CI, 11.9%-18.1%) were former smokers, and 96 (18.3%; 95% CI, 15.0%-21.6%) were nonsmokers (P?<?.001 for trend). In a regression analysis, e-cigarette use was associated with male sex (odds ratio [OR], 1.35; 95% CI, 1.12-1.62); age groups 20 to 29 years (OR, 2.77; 95% CI, 1.90-4.05), 30 to 39 years (OR, 2.27; 95% CI, 1.53-3.36), 40 to 49 years (OR, 1.65; 95% CI, 1.11-2.44), and 50 to 59 years (OR, 1.47; 95% CI, 1.01-2.12); educational level at primary school (OR, 1.99; 95% CI, 1.51-2.64) and upper secondary school (OR, 1.57; 95% CI, 1.25-1.96); former smoking (OR, 2.37; 95% CI, 1.73-3.24); and current smoking (OR, 18.10; 95% CI, 14.19-23.09). All respiratory symptoms were most common among dual users and former smokers and nonsmokers who used e-cigarettes. Conclusions and Relevance:Use of e-cigarettes was most common among smokers, and dual users had the highest prevalence of respiratory symptoms. On a population level, this study indicates that the present use of e-cigarettes does not adequately serve as a smoking cessation tool.

Project description:The first goal of this study was to identify the most appropriate measure of cigarette smoking for identifying unique smoking trajectories among adolescents; the second goal was to describe the resulting trajectories and their characteristics. Using 15 annual waves of smoking data in the National Longitudinal Survey of Youth 1997 (NLSY97), we conducted an exploratory latent class growth analysis to determine the best of four outcome variables for yearly smoking (cigarettes per day on days smoked, days smoked per month, mean cigarettes per day, and total cigarettes per month) among individuals aged 12 to 30 (n = 8,791). Days smoked per month was the best outcome variable for identifying unique longitudinal trajectories of smoking and characteristics of these trajectories that could be used to target different types of smokers for prevention and cessation. Objective statistics were used to identify four trajectories in addition to never smokers (34.1%): experimenters (13.6%), quitters (8.1%), early established smokers (39.0%), and late escalators (5.2%). We identified a quitter and late escalator class not identified in the only other comparable latent class growth analysis. Logistic regressions were used to identify the characteristics of individuals in each trajectory. Compared with never smokers, all trajectories except late escalators were less likely to be black; experimenters were more likely to be out of school and unemployed and drink alcohol in adolescence; quitters were more likely to have a mother with a high school degree/GED or higher (versus none) and to use substances in adolescence and less likely to have ever married as a young adult; early established smokers were more likely to have a mother with a high school diploma or GED, be out of school and unemployed, not live with both parents, have used substances, be depressed, and have peers who smoked in adolescence and to have children as young adults and less likely to be Hispanic and to have ever married as young adults; and late escalators were more likely to be Hispanic, drink alcohol, and break rules in adolescence and less likely to have ever married as young adults. Because of the number of waves of data analyzed, this analysis provided a clearer temporal depiction of smoking behavior and more easily distinguishable smoking trajectories than previous analyses. Tobacco control interventions need to move beyond youth-focused approaches to reach all smokers.

Dataset Information

Electronic Cigarette Use and Progression From Experimentation to Established Smoking.

Publications

Electronic Cigarette Use and Progression From Experimentation to Established Smoking.

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