Effect of outdoor air pollution on respiratory deseases in the District of Tunis
Bibliographic record
Abstract
Abstract Background Asthma and Chronic Obstructive Pulmonary Disease (COPD) are the two most common chronic obstructive pulmonary diseases worldwide. The objective of this study was to analyze the relation between the daily levels of air pollution indicators and the number of emergency department visits (EDV) for asthma and COPD exacerbation in the District of Tunis. Methods We conducted a retrospective ecological study. We collected daily morbidity data from the emergency register of Ariana Mami Hospital from 1 January 2007 to 31 December 2014. We investigated the association between daily EDV for asthma or COPD exacerbation and daily concentrations levels of air pollutants by simple Pearson correlation and by binomial negative regression using generalized linear models (GLM). Results For morbidity data, we recorded 19127 EDV for asthma (10771, 56.3%) and COPD exacerbation (8356, 43.7%) between 2007 and 2014. We observed a rising trend in the number of EDV for COPD since 2007 with winter seasonality. Regarding the profile of air pollution in the study region, we have exceeded the thresholds of all standards for PM10, exceeding the Canadian standard for O3. However, no threshold exceeded for NO2 and SO2. In the univariate analysis, there was a positive correlation between the daily number of EDV for asthma and COPD exacerbation and NO2 ambient concentration (r = 0.121, p < 10-3) and O3 level (r = 0.066, P < 10-3). Multivariate analysis showed a significant positive association between the daily number of EDV for asthma and COPD exacerbation and NO2 daily concentration (Adjusted OR = 1.033, CI = [1.011 - 1.055], P < 10-3) with a delayed effect of 10 days for NO2 and 12 days for O3. Conclusions The exacerbation of asthma and COPD was correlated to the NO2 outdoor air concentration level, with an immediate and other delayed effect of 10 days, also with the 12-day lag from the elevation of O3. Key messages Ambient air pollution is a major risk factor for respiratory health. Reducing NO2 emissions could decrease morbidity and direct health care costs of respiratory diseases.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".