Interacting effects of obesity, race, ethnicity and sex on the incidence and control of adult-onset asthma
Bibliographic record
Abstract
BACKGROUND: To improve care and control for patients with adult-onset asthma, a better understanding of determinants of their risk and outcomes is important. We investigated how associations between asthma, asthma control and obesity may be modified by patient demographic characteristics. METHODS: This retrospective study of adults enrolled in several health plans across the U.S. (n = 2,860,305) examined the interacting effects of obesity, age, race, and sex on adult-onset asthma and asthma control. Multivariable adjusted Cox and logistic regression models estimated hazard ratios (HR), and 95 % confidence intervals (CI) for the associations between body mass index (BMI) and study outcomes, and interactions of BMI with demographic characteristics. RESULTS: (HR 2.49, 95 % CI 2.38, 2.60). The magnitude of the association between obesity and asthma risk was greater for women (compared with men) and lower for Blacks (compared with non-Hispanic Whites). Among individuals with asthma, obesity was associated with poorly controlled and high-risk asthma. CONCLUSIONS: The present study demonstrates that the magnitude of the associations between obesity and adult-onset asthma incidence and control are modified by race, age, and sex. Understanding the role of obesity in the development of adult-onset asthma will help to improve asthma treatment algorithms and to develop targeted interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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".