Mixtures of multiple air pollutants from specific industrial or residential sources and mortality from ischemic heart disease, cardiovascular disease, and non-accidental causes: A large general population Canadian cohort study
Bibliographic record
Abstract
Abstract Background Previous studies on ambient air pollution and mortality typically focus on individual pollutants rather than their mixtures, and overall pollution rather than air pollution from specific sources. We aimed to assess the associations between ambient mixtures of fine particulate matter (PM 2.5 ), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), and ozone (O 3 ) from various industrial and residential sources, and deaths from ischemic heart disease (IHD), cardiovascular disease (CVD) and non-accidental causes. Methods We linked the 2006 Canadian Census Health and Environment Cohort (CanCHEC) with the Canadian Vital Statistics Database, identifying 56190, 98185, and 381050 deaths between 2006 and 2019 from IHD, CVD, and non-accidental causes, respectively. Annual average concentrations of PM 2.5 , SO 2 , NO 2 , and O 3 from upstream petroleum, downstream petroleum, non-ferrous smelting, chemical industry and residential fuel combustion were estimated using the Global Environmental Multiscale-Modelling Air Quality and Chemistry (GEM-MACH) model. These concentrations were assigned to CanCHEC participants based on their annual residential postal codes. Quantile g-computation models were used to calculate hazard ratios (HRs) for deaths from IHD, CVD, and non-accidental causes per quartile increase in all four air pollutants from each specific sector. Results We observed significant associations between the mixture of air pollutants and deaths from IHD, CVD, and non-accidental causes for emissions from upstream petroleum [HR: 1.18 (95% CI: 1.12-1.24), 1.12 (1.08-1.16), and 1.05 (1.04-1.05)], downstream petroleum [1.06 (1.05-, 1.04 (1.03-1.05), and 1.03 (1.02-1.03)], the chemical industry [1.10 (1.08-1.13), 1.07 (1.06-1.09), and 1.10 (1.08-1.13)], and residential fuel combustion [1.18 (1.12-1.23), 1.12 (1.08-1.16), and 1.07 (1.05-1.09)]. PM 2.5 and SO 2 contributed more to the increased risk of death than NO 2 and O 3 . Mortality from CVD or non-accidental causes was not associated with the mixtures of air pollutants from non-ferrous smelting. Conclusions Ambient PM 2.5 and SO 2 from certain sectors, but not all, greatly contribute to the increased risk of non-accidental, IHD, and CVD deaths.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 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".