Association of Air Pollution With Brain Health: A Cross-Sectional Analysis of Adults Living in Canada
Bibliographic record
Abstract
Abstract Background Air pollution is a risk factor for dementia but its role in early cognitive dysfunction is not clear. We aimed to investigate the association of air pollution with cognitive function, and the role of cardiovascular risk factors and greenspace in this association. Methods The Canadian Alliance for Healthy Hearts and Minds Cohort Study (CAHHM) is a cohort of Canadian adults recruited between 2014-2018, for whom averages of exposures to nitrogen dioxide (NO 2 ) and fine particulate matter (PM 2.5 ) were estimated for five years prior to recruitment. Outcomes included the Montréal Cognitive Assessment (MoCA) and Digit Symbol Substitution Test (DSST) for cognitive function, and magnetic resonance imaging-measured covert vascular brain injury. Generalized linear mixed models assessed pollutant associations with outcomes. Results A total of 6878 adults participated in the study with a mean age of 57.6 years (SD = 8.8) and 55.6% were women. Mean (SD; range) 5-year pollutant concentrations preceding enrolment (Figure S1) for PM 2.5 was 6.9 μg/m³ (2.0; 1.8-11.2), and for NO 2 was 12.9 ppb (5.9; 0.9-33.9). In adjusted models, a 5 μg/m 3 higher PM 2.5 concentration was associated with 0.44-points lower MoCA (95% confidence intervals (CI) −0.62, −0.25) and 1.31-points lower DSST (95% CI −2.41,-0.22) scores. A 5-ppb higher NO 2 concentration was associated with 0.12-points lower MoCA (95% CI −0.17, −0.07) and 0.38 lower DSST (95% CI −0.70, −0.05) scores. A 5-ppb higher NO 2 concentration was associated with higher odds of covert vascular brain injury (adjusted Odds Ratio (OR)=1.08; 95% CI 1.00, 1.17). Cardiovascular risk factors and greenspace did not change these associations. Conclusions PM 2.5 and NO 2 were associated with lower cognitive function scores in middle-aged adults living in Canada, independent of cardiovascular risk factors. This study suggests that air pollution mitigation efforts may help preserve cognitive function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 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".