Neighbourhood walkability and mortality: Findings from a 15-year follow-up of a nationally representative cohort of Canadian adults in urban areas
Bibliographic record
Abstract
BACKGROUND: Using a nationally representative cohort of Canadian adults, we assessed associations between neighbourhood walkability and cause-specific mortality and investigated whether they differed by socioeconomic status. METHODS: The study population was drawn from the 2001 Canadian Census Health and Environment Cohort, which contains individual-level data from a random sample of 20% of Canadian households mandated to complete the long-form census. We included those aged ≥ 25 years at baseline who lived in urban and suburban areas. The national death registry was used to ascertain annual vital status. Linkages to annual income tax data provided place of residence. The Canadian Active Living Environments, a national index that summarizes walkability across Canadian neighbourhoods, was assigned to individuals' residential history. The Cox proportional hazards model was used to assess associations between walkability and cause-specific mortality. RESULTS: A total of 1.8 million participants (52.5% female) accrued 27.3 million person-years and 265 710 deaths during the 15-year follow-up. The adjusted hazard ratio (HR) for living in a highly walkable neighbourhood relative to living in the least walkable neighbourhoods was associated with a 9% (HR: 0.91 [0.88, 0.95]) and 3% (HR: 0.97 [0.94, 0.99]) reduced risk of cardiovascular and all non-accidental mortality, respectively. The strongest benefits of walkability were found among individuals within the lowest education and household income categories, and who lived in the most deprived neighbourhoods. There were no significant associations (most [class 5] versus least [class 1] walkable HR: 0.84 [0.61-1.16]) seen for accidental traffic mortality. CONCLUSIONS: Canadian adults who live in walkable neighbourhoods have lower rates of cardiovascular and non-accidental mortality, with the greatest benefits seen in those from the lowest socioeconomic groups.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".