The association between the Canadian active living environments index and glucose metabolism in a Canadian national population study
Bibliographic record
Abstract
Biomarkers of glucose metabolism may reflect insulin resistance, a risk factor for diabetes and cardiovascular disease (CVD). Neighborhoods conducive to a physically active lifestyle have the potential to improve these biomarkers. We examined cross-sectional associations between walkability and blood biomarkers of glucose metabolism in 29,649 Canadian Health Measures Survey (CHMS) participants. We used generalized linear mixed models with sampling weights adjusted for province, participants’ age, sex, annual household income and educational attainment, cigarette smoking, environmental tobacco smoke, alcohol consumption, and exposure to ambient fine particulate air pollution (PM2.5). A higher value of the Canadian Active Living Environments Index, a measure of neighborhood walkability, equivalent to the magnitude of its interquartile range (IQR) of 2.4 was significantly associated with percentage differences of −0.48 (95% confidence interval (CI): 0.63, −0.32), −3.17 (95%CI: 5.27, −1.08), −3.88 (95%CI: 6.38, −1.38), and −3.36 (95%CI: 5.25, −1.47) in HbA1C, fasting insulin, HOMA-IR, and HOMA-β, respectively, for all CHMS participants. No significant effects were observed in those ≤16 years old. Canadians living in neighborhoods that facilitate active living have more favorable biomarkers of glucose metabolism, suggesting that the built environment has the potential to improve risk factors for diabetes and CVD in adults.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".