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Record W2318755469 · doi:10.3109/02770903.2011.570404

Smoking and Asthma in Men and Women with Normal Weight, Overweight, and Obesity

2011· article· en· W2318755469 on OpenAlexaffabout
Yue Chen, Xiao‐Mei Mai

Bibliographic record

VenueJournal of Asthma · 2011
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineAsthmaOverweightOdds ratioObesityBody mass indexConfidence intervalDemographyLogistic regressionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: There is a complex interrelationship among smoking, body weight, and asthma. It needs to be clarified whether smoking is related to an increased risk of asthma after taking into account for relative body weight. OBJECTIVE: To examine the association between cigarette smoking and the prevalence of asthma in Canadian men and women with normal weight, overweight, and obesity. METHODS: The analysis was based on data from 112,830 Canadians aged 18 years or more who participated in a national survey in 2007-2008. A questionnaire covered the information on prevalent asthma, smoking status, height, weight, and other factors. Logistic regression analysis was used to determine the association between smoking and the prevalence of asthma stratified by sex and body mass index (BMI). RESULTS: The crude prevalence of asthma was 6.6% for men and 9.3% for women. After adjustment for covariates, the odds ratios (ORs) for current smoking associated with asthma was 1.20 [95% confidence interval (CI): 1.01-1.43] for men with normal weight, 0.98 (95% CI: 0.81, 1.18) for overweight men, and 1.02 (95% CI: 0.80-1.30) for obese men. For women, the corresponding adjusted ORs were 1.41 (95% CI: 1.23-1.62), 1.27 (95% CI: 1.05-1.54), and 1.28 (95% CI: 1.03-1.59), respectively. CONCLUSION: Current smoking was significantly associated with prevalent asthma in all women regardless of their relative body weight. In men, however, the association was only observed in those with under- or normal weight.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.022
Threshold uncertainty score0.381

Codex and Gemma teacher scores by category

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

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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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 teacher head, 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

Citations8
Published2011
Admission routes2
Has abstractyes

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