The Relationship between Asthma and Obesity in Urban Early Adolescents
Bibliographic record
Abstract
Asthma and obesity, which have reached epidemic proportions, impact urban youth to a great extent. Findings are inconsistent regarding their relationship; no studies have considered asthma management. We explored the association of obesity and asthma-related morbidity, asthma-related health care utilization, and asthma management in urban adolescents with uncontrolled asthma. We classified 373 early adolescents (mean age=12.8 years; 82% Hispanic or Black) from New York City public middle schools into 4 weight categories: normal (body mass index [BMI]<85th percentile); overweight (85th percentile≤BMI<95th percentile); obese (95th percentile≤BMI<97th percentile); and very obese (BMI≥97th percentile). We compared sample obesity prevalence to national estimates, and tested whether weight categories predicted caregiver reported asthma outcomes, adjusting for age and race/ethnicity. Obesity prevalence was 37%, with 28% of the sample being very obese; both rates were significantly higher than national estimates. We found no significant differences in asthma-related health care utilization or asthma management between weight categories, and a few differences in asthma-related morbidity. Relative to normal weight and obese youth, overweight youth had higher odds of never having any days with asthma-related activity limitations. They also had higher odds of never having asthma-related school absences compared with obese youth. Overweight youth with asthma-related activity limitations had more days with limitations compared with normal weight youth. Overweight, but not obese youth, missed more school due to asthma than normal weight youth. Overweight and obesity prevalence was very high in urban, Hispanic, and Black adolescents with uncontrolled asthma, but not strongly associated with asthma-related morbidity, asthma-related health care utilization, or asthma management practices.
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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 | 0.001 |
| 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".