Project description:ImportanceContinued cigarette smoking after cancer diagnosis has been shown to adversely alter the cancer survivor's health outcomes and quality of life. Although considerable progress has been made in reducing cigarette smoking in the United States over the last decades, trends in cigarette smoking cessation among cancer survivors have not yet been fully investigated.ObjectiveTo evaluate temporal trends in cigarette smoking cessation and their sociodemographic and behavioral correlates in the US population of adult cancer survivors.Design, setting, and participantsThis investigation was a serial cross-sectional study of the National Health Interview Survey (NHIS) from 2006 to 2018, a household survey of civilian US residents who were 18 years or older. Data analysis was performed from June to October 2019. The NHIS is population based and representative of the US population. Included in this study were 381 989 respondents to the NHIS in 2006 to 2018.Main outcomes and measuresThe primary outcome was the probability of quitting cigarette smoking after first cancer diagnosis. Secondary outcomes were factors associated with quitting cigarette smoking after cancer diagnosis.ResultsData on 381 989 adults (weighted N = 239 114 051; mean [SD] age, 48.96 [18.28] years; 211 508 [55.37%] female; 61.90% non-Hispanic White, 13.97% non-Hispanic Black, and 16.22% Hispanic individuals) 18 years or older were analyzed from the 2006 to 2018 NHIS, of whom 8.80% (n = 35 524; weighted n = 21 016 720) were diagnosed with cancer. Among cancer survivors diagnosed between 2000 and 2017, the age-adjusted prevalence of current cigarette smoking at the time of first cancer diagnosis was 24.45% (n = 4054; weighted n = 2 395 173). The probability of reporting a cigarette smoking cessation event after first cancer diagnosis statistically significantly increased with each year of cancer diagnosis (hazard ratio [HR], 1.05; 95% CI, 1.02-1.08), indicating upward trends in the prevalence of quitting cigarette smoking over time. Older individuals (HR, 1.02; 95% CI, 1.01-1.03), individuals diagnosed as having a smoking-related cancer (HR, 1.28; 95% CI, 1.06-1.54), individuals with an undergraduate degree (HR, 1.39; 95% CI, 1.08-1.79) or a postgraduate degree (HR, 1.61; 95% CI, 1.18-2.20), and individuals with obesity (HR, 1.32; 95% CI, 1.06-1.63) had a higher probability of reporting a cigarette smoking cessation event after cancer diagnosis, whereas individuals living below the poverty level (HR, 0.62; 95% CI, 0.48-0.81) had a lower probability of reporting a cigarette smoking cessation event after cancer diagnosis.Conclusions and relevanceIn this nationally representative survey of the US adult population, the likelihood of cigarette smoking cessation among cancer survivors increased with the year of cancer diagnosis from 2000 to 2017; however, the improvement is incremental, and the prevalence of smoking remained high among this population. Considering the projected increase in the population of cancer survivors in the United States, urgent action is needed to increase cigarette smoking cessation rates in this high-risk population.

Project description:IntroductionCigarette use is declining yet remains common among adults with mental health conditions. In contrast, e-cigarette use may be on the rise. This study investigated the relationship between serious psychological distress (SPD) and the exclusive and dual use of cigarettes and e-cigarettes among US adults from 2014 to 2017.Aims and methodsData came from 2014 to 2017 National Health Interview Survey, an annual, cross-sectional survey of nationally representative samples of US adults (total combined analytic sample n = 125 302). Past-month SPD was assessed using the Kessler Psychological Distress Scale (K6) and cigarette and e-cigarette use were assessed at each wave. Logistic regressions examined product use by SPD status in 2017 and trends in product use by SPD status from 2014 to 2017. Analyses adjusted for demographic covariates.ResultsThe prevalence of cigarette use, e-cigarette use, and dual use was higher among adults with SPD than without SPD in each year including the most recent data year 2017 (cigarette use, 39.50% vs. 13.40%, p < .001; e-cigarette use, 7.41% vs. 2.65%, p < .001; dual use, 5.30% vs. 1.26%, p < .001). Among adults with SPD, the prevalence of cigarette, e-cigarette, and dual product use did not change from 2014 to 2017 in contrast to a decreasing prevalence in cigarette, e-cigarette, and dual product use among individuals without SPD.ConclusionsUS adults with SPD report higher levels of cigarette, e-cigarette, and dual product use than adults without SPD. Use of these products has not declined over the past several years in contrast to decreasing trends among adults without SPD.ImplicationsThese data extend our knowledge of tobacco product use and mental health disparities by showing that in addition to higher levels of cigarette use, US adults with SPD also use e-cigarettes and dual products (cigarette and e-cigarette) more commonly than those without SPD. Furthermore, the use of these products has not declined over the past several years in contrast to continuing declines among adults without SPD. More research is needed to understand the potential positive and negative consequences of e-cigarette use among adults with SPD.

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:Background and aimsThe 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.DesignA 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.SettingUnited States.Participants and measurementsAdolescents 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).FindingsA 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).ConclusionsA 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.

Project description:Importancee-Cigarette use among individuals who quit smoking more than 1 ago in England is highest among those with lower socioeconomic position and may affect smoking-related health inequalities, depending on whether the devices protect against relapse to tobacco smoking.ObjectivesTo assess trends in current e-cigarette use by socioeconomic position among individuals who have quit smoking for at least 1 year, to capture postcessation initiation among those who quit within the past year and did not use an e-cigarette in their most recent quit attempt (representing recent initiation), and to capture postcessation initiation among those who quit smoking before e-cigarettes became popular in 2011 (representing late initiation).Design, setting, and participantsThis cross-sectional study of 34 442 adults (≥16 years) who formerly smoked used data from the Smoking Toolkit Study (conducted 2014-2019), a nationally representative, monthly, repeated, cross-sectional, household survey of smoking and smoking cessation in England. Data analysis was conducted in December 2019.ExposuresSocioeconomic position based on occupation.Main outcomes and measuresCurrent self-reported e-cigarette use.ResultsWeighted samples consisted of 19 297 individuals who had quit smoking for at least 1 year (mean [SD] age, 59.2 [17.0] years; 9024 [46.8%] women), 904 who quit in the past year and did not use an e-cigarette in their most recent quit attempt (mean [SD] age, 41.6 [17.1] years; 445 [49.3%] women), and 14 241 who quit before 2011 (mean [SD] age, 63.6 [14.6] years; 6619 [46.5%] women). Among those who had quit smoking fot at least 1 year, e-cigarette use increased from 3.3% (95% CI, 2.7%-4.0%) in 2014 to 10.4% (95% CI, 9.2%-11.6%) in 2019 among all socioeconomic groups. Use was more common among those with lower socioeconomic position than those with higher socioeconomic position (odds ratio, 1.59; 95% CI, 1.05-2.40; P = .03). Regarding postcessation initiation of e-cigarettes, among those who quit smoking in the past year and did not use an e-cigarette in their most recent quit attempt, 7.1% (95% CI, 5.9%-9.3%) initiated e-cigarette use after smoking cessation, and there was no clear trend over time or any difference according to socioeconomic position. Among those who quit before 2011, there was an overall increase in use of e-cigarettes (0.8% [95% CI, 0.5%-1.2%] in 2014 to 2.1% [95% CI, 1.4%-2.8%] in 2019), but there were no apparent differences in use across socioeconomic position.Conclusions and relevanceIn this study, e-cigarette use increased among all participants from 2014 to 2019 but was highest among those with lower socioeconomic position. Continued monitoring of this socioeconomic patterning is important because if e-cigarettes do not confer the public health benefit of protection against relapse to smoking, then equity-negative disadvantages of long-term usage are more likely. Late, but not recent, postcessation initiation of e-cigarettes has increased over time but is not likely to affect smoking-related health inequalities because there were no differences by socioeconomic position.

Project description:IntroductionMany cancer patients who smoke report concurrent e-cigarette use. Using a mixed-methods approach, we aimed to (1) describe longitudinal e-cigarette use over 6 months after a cancer diagnosis and (2) assess the association between e-cigarette use and smoking cessation, among cancer patients in a smoking cessation trial.Aims and methodsData were from a 2-site randomized controlled trial of Standard (brief counseling) versus Intensive treatment (sustained counseling plus smoking cessation medication) in individuals who smoke recently diagnosed with cancer. Participants (n = 303) reported e-cigarette use at baseline, 3 months, and 6 months. Biochemically-verified past 7-day cigarette abstinence was collected at 6 months. Qualitative interviews at 6 months explored factors related to e-cigarette use.ResultsE-cigarette use prevalence was highest between baseline and 3 months (16%) and declined over time. Participants using e-cigarettes at follow-up had higher baseline cigarette dependence and smoked more heavily. Multivariable analyses found no significant association between follow-up e-cigarette use and 6-month cigarette abstinence. E-cigarette use at follow-up was higher in the Standard versus Intensive treatment group (p = .003 and .001 at 3 and 6 mo, respectively). Smoking cessation and health concerns were primary reasons for using e-cigarettes.ConclusionsAmong individuals who smoke recently diagnosed with cancer and enrolled in a smoking cessation intervention trial, e-cigarette use during trial participation was not associated with smoking abstinence. Individuals who chose to use e-cigarettes were less likely to be receiving intensive cessation support as part of the trial. Further studies are needed to evaluate the association between e-cigarette use and smoking cessation in cancer patients.ImplicationsE-cigarette use was not associated with cigarette abstinence at 6 months among adults who smoke recently diagnosed with cancer enrolled in a smoking cessation trial. Individuals with easier access to evidence-based smoking cessation treatment may be less likely to use e-cigarettes.

Dataset Information

Trends in Smoking and e-Cigarette Use Among US Patients With Cancer, 2014-2017.

Publications

Trends in Smoking and e-Cigarette Use Among US Patients With Cancer, 2014-2017.

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