Neighborhood Walkability Influences Walking: Findings From A Longitudinal Residential Relocation Study
Bibliographic record
Abstract
PURPOSE: Cross-sectional evidence demonstrates that the neighborhood built environment (walkability) is associated with walking. Residential relocation studies offer rigorous longitudinal evidence that can inform urban design and public health. However, findings from residential relocation studies estimating associations between changes in walkability and walking are equivocal. Our aim was to estimate associations between changes in exposure to neighborhood walkability and changes in leisure, transportation, and total walking following residential relocation. METHODS: This secondary analysis included cohort data from the ‘Alberta’s Tomorrow Project’ (Alberta, Canada). The analysis included walking and walkability measures for two waves of survey data (baseline and follow-up; 2 year median follow-up time) collected from 5977 adults (age 35+ years). The International Physical Activity Questionnaire captured walking. Walkability included objectively-measured intersection, destination, and population counts within a 0.25 mile radius of participants’ homes. Using household address data at baseline and follow-up, we categorized participants into three residential relocation groups (non-movers: n = 5679; movers to less walkability: n = 164, and; movers to more walkability: n = 134). Using Inverse-Probability-Weighted Regression Adjustment, we estimated differences (average treatment effects in the treated; ATET) in weekly minutes of leisure (LW), transportation (TW), and total (TTW) walking at follow-up between the residential relocation groups, adjusting for baseline walking, walkability and sociodemographic characteristics. RESULTS: Most participants were female, married, employed, tertiary educated, and inhabiting single-dwelling homes. Adjusting for covariates, walkability was positively associated with baseline weekly minutes of TW (b = 3.17; 95CI 0.82, 5.53; p = 0.008), but not LW (b = -1.33; 95CI -3.59, 0.94; p = 0.251) or TTW (b = 1.89; 95CI -1.60, 5.38; p = 0.288). Compared to non-movers, weekly TW minutes at follow-up was lower among adults who relocated to less walkable neighborhoods (ATET:-41.34, 95CI:-68.30,-14.39; p < .01). CONCLUSION: Relocating to less walkable neighborhoods has detrimental effects on TW to the extent that may adversely affect health.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".