Neighborhood walkability: Differential associations with self-reported transport walking and leisure-time physical activity in Canadian towns and cities of all sizes
Bibliographic record
Abstract
OBJECTIVE: To estimate associations between walkability and physical activity during transportation and leisure in a national-level population. METHODS: Walkability was measured by Walk Score® (2012-2014) and physical activity by the Canadian Community Health Survey (2007-2012) for urban participants who worked or attended school. Multiple linear regression was done on the total study population, four age subgroups (12-17, 18-29, 30-64, 65+) and three population center subgroups (1000-29,999, 30,000-99,999, 100,000+). RESULTS: 151,318 respondents were examined. Comparing highest to lowest Walk Score® quintiles, covariate-adjusted energy expenditure on transport walking [95% confidence interval] was 0.17 [0.15, 0.18] kcal/kg/day higher in the total study population, and significantly higher in all age and population center subgroups. Leisure physical activity was lower in the age 18-29 subgroup (-0.28 [-0.43, -0.12]) and population centers 100,000+ subgroup (-0.10 [-0.18, -0.03]), but higher in the population centers 1000-29,999 subgroup (0.30 [0.12, 0.48]). Total physical activity was higher in the following subgroups: age 30-64 (0.19 [0.12, 0.26]), population centers 100,000+ (0.12 [0.04, 0.19]) and population centers 1000-29,999 (0.40 [0.20, 0.59]). CONCLUSIONS: Walkability is associated with transport walking in all age groups and towns and cities of all sizes. Walkability's inverse associations with leisure physical activity among young adults and in large population centers may offset energy expenditure gains, while positive associations with leisure physical activity in small centers may add to energy expenditure.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".