Association between long-term exposure to ambient PM2.5 and NO2 and cognitive function in the CARTaGENE cohort
Bibliographic record
Abstract
Ambient air pollution is a recognized risk factor for cardiopulmonary disease, but its effects on cognition remain unclear, particularly at low exposure levels. This cross-sectional study assessed whether long-term exposure to fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) was associated with cognitive measures in the CARtaGENE cohort. The analysis included 6,659 participants aged 40-69 years from four urban areas in Quebec, Canada. Cognitive function was assessed from computerized tests of processing speed, working memory, and reasoning. Average exposures over the past 11 and 6 years were estimated by linking residential postal codes to PM 2.5 and NO 2 concentrations from satellite-based and land-use regression models, respectively. Associations with standardized cognitive scores were examined using mixed-effect models adjusted for potential confounders. Effect modification by sex, education, and smoking status was explored in subgroup analyses. Each interquartile range increase in 11-year PM 2.5 exposure was associated with slower processing speed (β = -0.079;95% CI: -0.121, -0.037). NO 2 exposure was associated with a poorer working memory (β = -0.053;95% CI: -0.11, 0.004). Both pollutants were associated with better reasoning scores (β for PM 2.5 = 0.059; 95% CI: 0.031, 0.087 and β for NO 2 = 0.108; 95% CI: 0.053, 0.164). Results were similar for the 6-year exposure window. Associations between NO 2 and working memory were modified by the smoking status and education level. Long-term exposure to low levels of ambient PM 2.5 was associated with slower reaction times and NO 2 to poorer visual working memory. Highlights : • Low-level air pollution is associated with cognitive scores in adults aged 40–69. • Long-term PM 2.5 exposure was associated with slower processing speed. • Long-term NO 2 exposure was associated with poorer visual working memory. • Both pollutants were associated with better performance in reasoning. • Smoking and education appeared to modify NO 2 effects on memory.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".