Increased Effect of Obesity on Asthma in Adults with Low Household Income
Bibliographic record
Abstract
BACKGROUND: Both obesity and low income are risk factors of asthma and their joint effect on the disease has not been studied previously. OBJECTIVE: To examine the influence of obesity and household income and their joint effect on asthma. METHODS: The authors conducted an analysis based on data from 115,722 subjects 18+ years of age who participated in a national survey in 2005. Logistic regression analysis was used to adjust for covariates. The joint effect of household income and body mass index (BMI) on asthma was assessed on an additive scale. RESULTS: Obesity associated with an increased risk of asthma was significant in all income categories in women but was only significant in the low-income group in men. A stronger association between obesity and asthma was observed in low- than in high-income families. For men and women combined, the adjusted odds ratio for those with a BMI value of 35 kg/m(2) or more versus those with a BMI less than 25 kg/m(2) was 2.01 in the low-household income group compared with only 1.47 in the high-income group. The corresponding adjusted relative excess risk of interaction was 1.50 (95% confidence interval [CI]: 0.88, 1.65) for men and women combined and was 2.73 (95% CI: 1.50, 5.39) for women. CONCLUSION: These data suggested an interactive effect of obesity and low-household income on the prevalence of asthma.
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 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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".