The Air Quality Health Index and Emergency Department Visits for Urticaria in Windsor, Canada
Bibliographic record
Abstract
Ambient air pollution exposure has been associated with several health conditions, limited not only to respiratory and cardiovascular systems but also to cutaneous tissues. However, few epidemiological studies examined pollution exposure on skin problems. Basically, the common mechanism by which pollution may affect skin physiology is by induction of oxidative stress and inflammation. Urticaria is among the skin pathologies that have been associated with pollution. Based on the combined effects of three ambient air pollutants, ozone (O₃), nitrogen dioxide (NO₂), and fine particulate matter (PM) with a median aerodynamic diameter of less than 2.5 μm (PM(2.5)), on mortality, the Air Quality Health Index (AQHI) in Canada was developed. The aim of this study was to examine the associations of short-term changes in AQHI with emergency department (ED) visits for urticaria in Windsor-area hospitals in Canada. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). A time-stratified case-crossover design was applied to 2905 ED visits (males = 1215; females = 1690) for urticaria from April 2004 through December 2010. Odds ratios (OR) and their corresponding 95% confidence intervals (95%CI) for ED visits associated with increase by one unit of risk index were calculated employing conditional logistic regression. Positive and significant results were observed between AQHI levels and OR for ED visits for urticaria in Windsor for lags 2 and 3 days. A distributed lag nonlinear model technique was applied to daily counts of ED visits for lags 0 to 10 and significant results were obtained from lag 2 to lag 5 and for lag 9. These findings demonstrated associations between ambient air pollution and urticarial confirming that air pollution affects skin conditions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".