Prevalence of Asthma among Norwegian Elite Athletes
Bibliographic record
Abstract
Objective. Asthma is a common problem among elite athletes and represents a health risk interfering with the athlete’s performance status. This study aimed to evaluate the asthma prevalence among Norwegian summer and winter elite athletes and asthma prevalence across sport categories. We also aimed to examine whether bronchial hyperresponsiveness (BHR), lung function, fraction of exhaled nitric oxide (FENO), and allergy status differed between asthmatic and non-asthmatic elite athletes. Methods. Norwegian athletes qualifying for the Beijing Olympic Summer Games 2008 (n = 80) and the Vancouver Olympic Winter Games 2010 (n = 55) were included. The athletes underwent clinical respiratory examination including lung function measurement, methacholine bronchial challenge for assessment of BHR, FENO, and skin prick testing. Asthma was diagnosed based on respiratory symptoms and clinical examination including objective measurements. Results. Asthma was more prevalent among winter athletes (50%) than summer athletes (20%). Thirty-three (52%) endurance athletes, 3 (6%) team sport athletes, and 7 (33%) technical sport athletes had medically diagnosed asthma. Significantly lower lung function ( <a:math xmlns:a="http://www.w3.org/1998/Math/MathML" id="M1"> <a:mi>p</a:mi> <a:mo><</a:mo> <a:mn>0.001</a:mn> </a:math> ) and higher prevalence of severe BHR ( <c:math xmlns:c="http://www.w3.org/1998/Math/MathML" id="M2"> <c:mi>p</c:mi> <c:mo><</c:mo> <c:mn>0.001</c:mn> </c:math> ) were found in asthmatic athletes compared with non-asthmatic athletes. Conclusion. Asthma is common among Norwegian elite athletes, with winter and endurance athletes showing the highest prevalence. Asthmatic athletes were characterized by lower lung function and more severe BHR compared with non-asthmatic counterparts. The high prevalence among winter and endurance athletes demonstrates a need for increased attention to prevent and reduce the prevalence of asthma among those athletes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 teacher head, 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".