Residential moves, neighbourhood walkability, and physical activity: a longitudinal pilot study in Ontario Canada
Bibliographic record
Abstract
BACKGROUND: Numerous cross-sectional studies have consistently demonstrated an association between attributes of urban form or 'walkability' and individual- and population-level physical activity (PA) patterns. However, in the absence of longitudinal research, the self-selection problem undermines the claim that a walkable built form produces more physically active people. Through a longitudinal pilot study of 'imminent movers' in Ontario using a quasi-experimental approach, we sought to examine the feasibility of longitudinal methods that would produce stronger evidence for a causal relationship between the built environment and PA levels. METHODS: Participants were recruited using publicly available real estate listings. Successful recruits were sent a PA diary to track their activity for a week, and were also scheduled for a 45-min phone interview that collected demographic details, neighbourhood perceptions and self-efficacy for walking, and verified the PA diary. Following their move, participants were given the same tasks and then sorted into groups based on changes in their neighbourhood walkability (measured with Walk Score) from baseline to follow-up. RESULTS: There were challenges in recruiting a sufficient number of participants and counter-factuals to examine the relationship between changes in walkability and PA. Our limited sample showed a substantial decrease in Walk Score over the entire sample, from an average of 45.8 to 30.6, with most participants moving to less walkable areas. From baseline to follow-up, the largest declines in reported self-efficacy for walking were to grocery stores, banks, and for entertainment. For the entire sample, utilitarian PA decreased, while recreational and job-related PA increased. CONCLUSIONS: This pilot study highlighted the methodological challenges involved in collecting quasi-experimental evidence on the effect of walkable environments on PA. Additionally, the low sample size and the tendency for most participants to move to less walkable areas meant there were insufficient counter-factuals for study of the effect of walkability on PA. Despite these challenges, we saw important changes in self-efficacy for walking that were commensurate with changes to the built environment. In sum, while longitudinal research on health and the built environment is urgently needed, recruiting an adequate sample size for a quasi-experimental study such as this is extremely challenging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".