Ambient Air Pollution and Subclinical Cardiovascular Disease Measured by Magnetic Resonance Imaging in the Canadian Alliance for Healthy Hearts and Minds Study
Bibliographic record
Abstract
Abstract Background Long-term exposure to air pollution, even at levels below regulatory standards, has been associated with higher risk of cardiovascular-related mortality. Less is known about the association of air pollution and initial development of CVD in low-exposure settings in generally healthy human populations. Objective In the Canadian Alliance for Healthy Hearts and Minds Cohort Study (CAHHM), we aimed to investigate the association between low-level exposure to key air pollutants and subclinical carotid atherosclerosis in adults without known clinical CVD. To date, the association of ambient air pollution and atherosclerosis measured by magnetic resonance imaging (MRI) has not been studied. Methods We studied 6,645 Canadian adults recruited between 2014-2018 from the provinces of British Columbia, Alberta, Ontario, Quebec, and Nova Scotia, for whom average long-term exposures to nitrogen dioxide (NO 2 ), ozone (O 3 ), and fine particulate matter (PM 2.5 ) were estimated for five years prior to the start of CAHHM recruitment, and who underwent MRI to assess carotid vessel wall volume (CWV). Linear mixed models were used to quantify associations between each air pollutant and CWV adjusting for individual-level and community-level risk factors for CVD. Secondary analyses included region-specific stratification and modeling the effect of one pollutant on CWV within low, medium, and high levels of a second pollutant to test for interactions. Results Higher PM 2.5 was nominally associated with lower CWV (quintile 5: 893.3 mm 3 , quintile 1: 908.8 mm 3 ; p-trend =0.05), but this was not robust in region-stratified analysis. Higher NO 2 was associated with lower CWV (quintile 5: 889.5 mm 3 , quintile 1: 918.6 mm 3 ; p-trend <.0001). Higher O 3 was associated with higher CWV (quintile 5: 925.4 mm 3 , quintile 1: 899.7 mm 3 ; p-trend =0.02). NO 2 emerged as a consistent effect modifier of both PM 2.5 and O 3. Conclusion In a cohort of generally healthy adults living in Canada, a country with relatively low levels of air pollution, exposure to NO 2 was negatively associated, and O 3 was positively associated with CWV as a measure of subclinical atherosclerosis by MRI, while associations to PM 2.5 were inconsistent. The reasons for these associations warrant further study.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".