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The Association Between Electronic Cigarette Smoking and Gastroesophageal Reflux Disease: A Population-Based Study

2018· article· en· W2921741607 on OpenAlexaboutno aff
Ahmad Fariz Malvi Zamzam Zein, Catur Setiya Sulistiyana, Murdani Abdullah

Bibliographic record

VenueThe American Journal of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsGERDMedicinePopulationDiseaseSmoking cessationCigarette smokingRefluxInternal medicineRegurgitation (circulation)Descriptive statisticsCross-sectional studyDemographyEnvironmental healthPathology

Abstract

fetched live from OpenAlex

Introduction: Gastroesophageal reflux disease (GERD) is associated with lifestyles. Electronic cigarette (e-cig) smoking is a new trend of lifestyle. Yet, the relationship between e-cig smoking and GERD among adult urban population. Methods: A cross-sectional study was conducted among 267 adult urban people in Cirebon, West Java, Indonesia. A self-administered questionnaire was given. It consisted demographic characteristics, e-cig smoking status, GERD-related symptom, and validated GERD questionnaire (GERDQ). Data were analyzed using descriptive statistics and chi-square test. This study has been approved by an ethical committee. Results: The median age of the subjects was 24.0 years old. E-cig smoking was frequent (74.2%) with the median duration 2.0 years. The median of its dose was 30.0 mL weekly. The prevalence of GERD in this study was 9.4%. The e-cig smoking was positively associated with regurgitation (PR= 1.388; 95%CI: 1.284-1.500; p=0.006), but it was negatively associated with GERD (PR= 0.334; 95%CI: 0.144-0.772; p=0.008). Conclusion: The prevalence of e-cig smoker in US is 15%, in UK 10%, in Canada 4%, and in Australia 2%.1-2 The prevalence of e-cig smoker in this study is high. The differences can be caused by different definition and scope of population used in the studies. E-cig smoking is still a controversial issue. Some in the community have embraced e-cig smoking as a safer alternative to conventional cigarettes, further as a smoking cessation method.1,3 Yet, the hazards of e-cig smoking are still unknown. S. A. Meo, et al.,4 reported that e-cig smoking can cause nausea and vomiting. Our study revealed that e-cig smoking was clinically associated with regurgitation. It was assumed that those effects are due to nicotine toxicity via inhalation delivery system. But, our study also showed that 2-year e-cig smoking is statistically negative association with GERD. There are limitations in this study. First, study design we used in this study was cross-sectional. We propose cohort study in the future studies evaluating the association between e-cig smoking and GERD. Second, relatively short duration of e-cig consuming might be less provoking the GERD. Third, we did not evaluate other variables enabling them as confounding factors. As a conclusion, this first population-based study showed that e-cig smoking is associated with regurgitation, but statistically it is negatively associated with GERD in adult urban population. Further studies are needed to evaluate this association.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.282
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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