Effects of Industrial Emissions on Cardiovascular and Respiratory Markers of Asthmatic Children in Montreal, Canada
Bibliographic record
Abstract
ISEE-0793 Background and Objective: Air pollution can cause exacerbations of asthma and adversely affect lung function, however, relatively little is known about the effects of specific pollutants and emission sources, including industrial point sources. We are carrying out a study in Montreal, Canada, to determine the effects of living close to an oil refinery and other industrial sources of pollutants on pulmonary and cardiovascular function of asthmatic children. Methods: This panel study will enroll 120 asthmatic children living in close proximity to an oil refinery as well as other industrial sources of pollution. Over six separate 10-day periods, panels of up to 20 children will undergo daily tests of lung and cardiovascular markers: spirometry; exhaled nitric oxide (eNO); blood pressure and pulse oximetry. Exhaled breath condensate will also be measured using RTubeTM and analyzed for markers of inflammation and oxidative stress (specifically TBARS, 8-isoprostane, and interleukin-6). Exhaled nitric oxide will be measured by Portable NIOX MINO eNO analyzer from Aerocrine and spirometry will be measured by KoKo Spirometers. Daily concentrations of SO2, NO2, PM2.5, volatile organic compounds (VOC), polycyclic aromatic hydrocarbons (PAH), and ozone will be measured by means of outdoor monitoring at four locations surrounding the refinery. Participants will be asked to carry with them a small backpack that measures 24-hour integrated samples of SO2, NO2, PAH, and VOCs. Real-time PM2.5 will also be measured, as well as vanadium and nickel as markers for emissions from the oil refinery. Proximity of home and school to point sources will also be evaluated. Results: The effect of various air pollutants on lung and cardiovascular markers will be estimated using linear mixed-effects models, adjusted for salient risk factors. Conclusion: This is the first study among asthmatic children to provide detailed longitudinal information on variations in health arising from personal exposures to emissions from oil refineries, other industrial sources, and traffic. Data collection begins in summer 2009.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".