Abstract MP55: Associations Between Traffic-Related Air Pollution and Cardiovascular Disease Risk Factors Were Stronger in More Walkable Neighborhoods: The Cardiovascular Health in Ambulatory Care Research Team Cohort
Bibliographic record
Abstract
Introduction: Studies suggest living in a more walkable neighborhood may protect against cardiovascular disease risk factors such as hypertension (HTN) and diabetes mellitus (DM) by encouraging physical activity. Walkable neighborhoods, however, often carry higher levels of traffic-related air pollution. Little is known regarding whether synergistic effects may exist between walkability and air pollution on these risk factors. Hypothesis: We hypothesized that the association between traffic-related air pollution, hypertension, and diabetes mellitus would be stronger in more walkable areas. Methods: We drew a cross-sectional sample of individuals ages 40-74 on January 1, 2008 from the CANHEART cohort. HTN and DM were ascertained using validated algorithms. Walkability (quintiles, Q5 highest, Q1 lowest) was measured using a validated index which has previously been shown to be inversely associated with obesity and diabetes. Exposure to nitrogen dioxide, a valid marker for traffic-related air pollution, was assessed using a land use regression models. The associations were tested using logistic regression with cluster-robust standard errors, adjusting for age, sex, area-level income, ethnicity, and comorbidities. Results: In total, 2,618,584 individuals were included in the analysis (mean (SD) age = 53.2 (9.2), 52% female). Walkability was inversely associated with odds for HTN (Q5 vs. Q1 OR = 0.80, 95% CI: 0.79, 0.82) and DM (Q5 vs. Q1 OR = 0.89, 95% CI: 0.87, 0.91), while NO 2 was positively associated with each (HTN: OR = 1.02 per 10 ppb (1.01, 1.03); DM: OR = 1.11 per 10 ppb (1.09, 1.13)). We observed significant interactions between walkability and NO 2 on odds for HTN and DM, with stronger NO 2 associations in the most walkable neighborhoods (Fig. 1). Conclusions: We observed significant interactions between traffic-related air pollution and walkability on odds for HTN and DM. This finding suggests that benefits from living in more walkable neighborhoods may be offset by stronger negative associations with air pollution.
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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) | 0.000 | 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 | 0.000 | 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".