Obesity Is a Risk Factor for Dyspnea but Not for Airflow Obstruction
Bibliographic record
Abstract
BACKGROUND: Previous research suggests that obesity is an important risk factor for asthma. However, since obesity can cause dyspnea through mechanisms other than airflow obstruction, diagnostic misclassification of asthma could partially account for this association. OBJECTIVE: To determine whether there is a relationship between obesity and airflow obstruction. METHODS: A total of 16 171 participants (17 years or older) from the Third National Health and Nutrition Examination Survey (NHANES III) were divided into 5 quintiles based on their body mass index (BMI) to determine the association between BMI quintile and risk of self-reported asthma, bronchodilator use, exercise performance, and airflow obstruction. Significant airflow obstruction was defined as a ratio less than 80% the predicted value of forced expiratory volume in 1 second to forced vital capacity adjusted for age, sex, and race. RESULTS: The highest BMI quintile (ie, the most obese participants) had the greatest risk of self-reported asthma (odds ratio [OR], 1.50; 95% confidence interval [CI], 1.24-1.81), bronchodilator use (OR, 1.94; 95% CI, 1.38-2.72), and dyspnea with exertion (OR, 2.66; 95% CI, 2.35-3.00). Paradoxically, the highest BMI quintile had the lowest risk for significant airflow obstruction (P =.001). CONCLUSIONS: This study demonstrates that while obesity is a risk factor for self-reported asthma, obese participants are at a lower risk for (objective) airflow obstruction. Many more obese than nonobese participants were using bronchodilators despite a lack of objective evidence for airflow obstruction. These data suggest that mechanisms other than airflow obstruction are responsible for dyspnea genesis in obesity and that asthma might be overdiagnosed in the obese population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".