Long-term effect of asthma on the development of obesity among adults: an international cohort study, ECRHS
Bibliographic record
Abstract
Introduction Obesity is a known risk factor for asthma. Although some evidence showed asthma causing obesity in children, the link between asthma and obesity has not been investigated in adults. Methods We used data from the European Community Respiratory Health Survey (ECRHS), a cohort study in 11 European countries and Australia in 3 waves between 1990 and 2014, at intervals of approximately 10 years. We considered two study periods: from ECRHS I (t) to ECRHS II (t+1), and from ECRHS II (t) to ECRHS III (t+1). We excluded obese (body mass index≥30 kg/m2) individuals at visitt. The relative risk (RR) of obesity att+1associated with asthma attwas estimated by multivariable modified Poisson regression (lag) with repeated measurements. Additionally, we examined the association of atopy and asthma medication on the development of obesity. Results We included 7576 participants in the period ECRHS I-II (51.5% female, mean (SD) age of 34 (7) years) and 4976 in ECRHS II-III (51.3% female, 42 (8) years). 9% of participants became obese in ECRHS I-II and 15% in ECRHS II—III. The risk of developing obesity was higher among asthmatics than non-asthmatics (RR 1.22, 95% CI 1.07 to 1.38), and particularly higher among non-atopic than atopic (1.47; 1.17 to 1.86 vs 1.04; 0.86 to 1.27), those with longer disease duration (1.32; 1.10 to 1.59 in >20 years vs 1.12; 0.87 to 1.43 in ≤20 years) and those on oral corticosteroids (1.99; 1.26 to 3.15 vs 1.15; 1.03 to 1.28). Physical activity was not a mediator of this association. Conclusion This is the first study showing that adult asthmatics have a higher risk of developing obesity than non-asthmatics, particularly those non-atopic, of longer disease duration or on oral corticosteroids.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".