Self-reported asthma and allergies in top athletes compared to the general population - results of the German part of the GA2LEN-Olympic study 2008
Bibliographic record
Abstract
BACKGROUND: Prevalence of asthma and allergies in top athletes is high. However, most previous studies did not include a general population comparison group. We aimed to compare the prevalence of asthma, allergies and medical treatment in different groups of German top athletes to the general population. METHODS: Prior to the 2008 Summer Olympic Games, 291 German candidates for participation (65%) completed a questionnaire on respiratory and allergic symptoms. Results were compared to those of a general population study in Germany (n = 2425, response 68%). Furthermore, associations between types of sports and the self-reported outcomes were calculated. All models were adjusted for age, sex, level of education and smoking. RESULTS: Athletes reported significantly more doctors' diagnosed asthma (17% vs. 7%), more current use of asthma medication (10% vs. 4%) and allergic rhinitis (25% vs. 17%) compared to the general population. After adjustment, top athletes only had an increased Odds Ratio for doctor's diagnosed asthma (OR: 1.6; 95% CI 1.1-2.5). Compared to the general population, athletes in endurance sports had an increased OR for doctor's diagnosed asthma (2.4; 1.5-3.8) and current use of asthma medication (1.8; 1.0-3.4). In this group, current wheeze was increased when use of asthma medication was taken into account (1.8; 1.1-2.8). For other groups of athletes, no significantly increased ORs were observed. CONCLUSIONS: Compared to the general population, an increased risk of asthma diagnosis and treatment was shown for athletes involved in endurance sports. This might be due to a better medical surveillance and treatment of these 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".