The Inflammatory Bowel Diseases and Ambient Air Pollution: A Novel Association
Bibliographic record
Abstract
OBJECTIVES: The inflammatory bowel diseases (IBDs) emerged after industrialization. We studied whether ambient air pollution levels were associated with the incidence of IBD. METHODS: The health improvement network (THIN) database in the United Kingdom was used to identify incident cases of Crohn's disease (n=367) or ulcerative colitis (n=591), and age- and sex-matched controls. Conditional logistic regression analyses assessed whether IBD patients were more likely to live in areas of higher ambient concentrations of nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), and particulate matter <10 μm (PM(10)), as determined by using quintiles of concentrations, after adjusting for smoking, socioeconomic status, non-steroidal anti-inflammatory drugs (NSAIDs), and appendectomy. Stratified analyses investigated effects by age. RESULTS: Overall, NO(2), SO(2), and PM(10) were not associated with the risk of IBD. However, individuals ≤23 years were more likely to be diagnosed with Crohn's disease if they lived in regions with NO(2) concentrations within the upper three quintiles (odds ratio (OR)=2.31; 95% confidence interval (CI)=1.25-4.28), after adjusting for confounders. Among these Crohn's disease patients, the adjusted OR increased linearly across quintile levels for NO(2) (P=0.02). Crohn's disease patients aged 44-57 years were less likely to live in regions of higher NO(2) (OR=0.56; 95% CI=0.33-0.95) and PM(10) (OR=0.48; 95% CI=0.29-0.80). Ulcerative colitis patients ≤25 years (OR=2.00; 95% CI=1.08-3.72) were more likely to live in regions of higher SO(2); however, a dose-response effect was not observed. CONCLUSIONS: On the whole, air pollution exposure was not associated with the incidence of IBD. However, residential exposures to SO(2) and NO(2) may increase the risk of early-onset ulcerative colitis and Crohn's disease, respectively. Future studies are needed to explore the age-specific effects of air pollution exposure on IBD risk.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".