Smoking and Asthma in Men and Women with Normal Weight, Overweight, and Obesity
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".