Abstract P105: Less Walkable Neighborhoods Are Associated With Worse Cardiovascular Risk Profile
Bibliographic record
Abstract
Introduction: There is mounting evidence that neighborhoods that have low levels of walkability have higher burdens of cardiovascular disease (CVD) risk factors such as obesity and hypertension. However, few studies have examined the impact of walkability on overall cardiovascular risk. Hypothesis: We hypothesized that residents living in less walkable communities have a higher burden of cardiovascular risk factors and a greater predicted risk for future CVD events. Methods: We assembled a cross-sectional sample of community dwelling adults aged 40-74 on January 1, 2008 from the CANHEART cohort. We ascertained systolic blood pressure, HDL and total cholesterol, smoking status, and diabetes status using a combination of EMR, clinical laboratory databases, and health administrative databases. The primary outcome was an estimated total 10-year cardiovascular disease risk of ≥ 7.5% using the ACC/AHA Pooled Cohort risk score. Walkability was measured using a validated index and divided into quintiles from lowest (Q1) to highest (Q5). The associations were tested using linear and logistic regression with cluster-robust standard errors, adjusting for confounders. Results: In total, 44,448 individuals were included in the analysis. Individuals living in less walkable areas had a higher predicted 10-year CVD risk than those living in highly walkable areas. The association was non-linear, as individuals living in neighborhoods of mid-range walkability (Q3) were even more likely to have an estimated 10-year CVD risk exceeding 7.5% in comparison to those in Q5 (OR = 1.33, (1.23, 1.45)). Conversely, we observed monotonic associations between decreasing walkability and higher mean systolic blood pressure (Q1 vs. Q5: +2.73 mmHg, 95% CI: +2.11, + 3.35) and odds of diabetes (Q1 vs. Q5: OR = 1.29, 95% CI: 1.13, 1.47). Dose-response associations were also observed between decreasing walkability and lower HDL cholesterol (Q1 vs. Q5: -1.93 mg/dl, 95% CI: -2.32, -1.16) and likelihood of being a current smoker (Q1 vs. Q5: OR = 0.76, 95% CI: 0.67, 0.85). Conclusions: Residents living in less walkable neighborhoods had a higher burden of CVD risk factors and a higher estimated risk of future CVD. Conversely, the likelihood of smoking was higher in more walkable neighborhoods, suggesting this may be an area to focus smoking cessation efforts.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".