Dataset Information

Active, passive, and electronic cigarette smoking is associated with asthma in adolescents.

ABSTRACT: The present study investigated the associations of active, passive, and electronic cigarette (E-cigarette) smoking with asthma in Korean adolescents. We used the cross-sectional study of Korea Youth Risk Behavior Web-based Survey conducted in 2011, 2012 and 2013. Active smoking was classified into 4 groups (0 days, 1-5 days, 6-19 days, and ?20 days a month). Passive smoking was also categorized into 4 groups (0 days, 1-2 days, 3-4 days, and ?5 days a week). E-cigarette was defined as yes or no in the last 30 days. Age, sex, obesity, region of residence, economic level, and parental educational level were adjusted for as confounders. Smoking variables were adjusted for one another. Adjusted odd ratios (AORs) and 95% confidence intervals (CIs) were calculated using multiple logistic regression analysis with complex sampling. In total, 2.3% (4,890/216,056) of participants reported asthma in the past 12 months. Active smoking was significantly associated with asthma (AOR [95% CI] of smoking ?20 days/month?=?1.57 [1.38-1.77], P?

SUBMITTER: Kim SY

PROVIDER: S-EPMC5736689 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

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Active, passive, and electronic cigarette smoking is associated with asthma in adolescents.

Kim So Young SY Sim Songyong S Choi Hyo Geun HG

Scientific reports 20171219 1

The present study investigated the associations of active, passive, and electronic cigarette (E-cigarette) smoking with asthma in Korean adolescents. We used the cross-sectional study of Korea Youth Risk Behavior Web-based Survey conducted in 2011, 2012 and 2013. Active smoking was classified into 4 groups (0 days, 1-5 days, 6-19 days, and ≥20 days a month). Passive smoking was also categorized into 4 groups (0 days, 1-2 days, 3-4 days, and ≥5 days a week). E-cigarette was defined as yes or no i ...[more]

PMID: 29259221

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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.

Dataset Information

Active, passive, and electronic cigarette smoking is associated with asthma in adolescents.

Publications

Active, passive, and electronic cigarette smoking is associated with asthma in adolescents.

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