Neighborhood Walkability and Body Mass Index Trajectories: Longitudinal Study of Canadians
Bibliographic record
Abstract
OBJECTIVES: To assess the impact of neighborhood walkability on body mass index (BMI) trajectories of urban Canadians. METHODS: Data are from Canada's National Population Health Survey (n = 2935; biannual assessments 1994-2006). We measured walkability with the Walk Score. We modeled body mass index (BMI, defined as weight in kilograms divided by the square of height in meters [kg/m(2)]) trajectories as a function of Walk Score and sociodemographic and behavioral covariates with growth curve models and fixed-effects regression models. RESULTS: In men, BMI increased annually by an average of 0.13 kg/m(2) (95% confidence interval [CI] = 0.11, 0.14) over the 12 years of follow-up. Moving to a high-walkable neighborhood (2 or more Walk Score quartiles higher) decreased BMI trajectories for men by approximately 1 kg/m(2) (95% CI = -1.16, -0.17). Moving to a low-walkable neighborhood increased BMI for men by approximately 0.45 kg/m(2) (95% CI = 0.01, 0.89). There was no detectable influence of neighborhood walkability on body weight for women. CONCLUSIONS: Our study of a large sample of urban Canadians followed for 12 years confirms that neighborhood walkability influences BMI trajectories for men, and may be influential in curtailing male age-related weight gain.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.001 | 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".