Association Between Neighborhood Walkability and Predicted 10‐Year Cardiovascular Disease Risk: The CANHEART (Cardiovascular Health in Ambulatory Care Research Team) Cohort
Bibliographic record
Abstract
Background Individuals living in unwalkable neighborhoods appear to be less physically active and more likely to develop obesity, diabetes mellitus, and hypertension. It is unclear whether neighborhood walkability is a risk factor for future cardiovascular disease. Methods and Results We studied residents living in major urban centers in Ontario, Canada on January 1, 2008, using linked electronic medical record and administrative health data from the CANHEART (Cardiovascular Health in Ambulatory Care Research Team) cohort. Walkability was assessed using a validated index based on population and residential density, street connectivity, and the number of walkable destinations in each neighborhood, divided into quintiles (Q). The primary outcome was a predicted 10-year cardiovascular disease risk of ≥7.5% (recommended threshold for statin use) assessed by the American College of Cardiology/American Heart Association Pooled Cohort Equation. Adjusted associations were estimated using logistic regression models. Secondary outcomes included measured systolic blood pressure, total and high-density lipoprotein cholesterol levels, prior diabetes mellitus diagnosis, and current smoking status. In total, 44 448 individuals were included in our analyses. Fully adjusted analyses found a nonlinear relationship between walkability and predicted 10-year cardiovascular disease risk (least [Q1] versus most [Q5] walkable neighborhood: odds ratio =1.09, 95% CI: 0.98, 1.22), with the greatest difference between Q3 and Q5 (odds ratio=1.33, 95% CI: 1.23, 1.45). Dose-response associations were observed for systolic blood pressure, high-density lipoprotein cholesterol, and diabetes mellitus risk, while an inverse association was observed with smoking status. Conclusions In our setting, adults living in less walkable neighborhoods had a higher predicted 10-year cardiovascular disease risk than those living in highly walkable areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".