Neighbourhood street connectivity and injury in youth: a national study of built environments in Canada
Bibliographic record
Abstract
BACKGROUND: The influence of the built environment on health is of contemporary societal interest. The design of streets in neighbourhood settings may contribute positively to the health of populations through increased physical activity, but it may also have injury consequences. METHODS: We conducted a national cross-sectional study to describe the injury experiences of 9021 students from 180 Canadian schools that participated in the 2006 Health Behaviour in School-Aged Children survey. Street designs surrounding each school (5 km circular buffer) were estimated via geographic information systems for three established measures of connectivity (intersection density, average block length and connected node ratio). A composite scale of connectivity was derived using factor analysis. Multilevel logistic regression analyses were used to examine the associations between the composite connectivity measure and students' reports of physical activity injuries occurring in the street (street injuries). RESULTS: Students living in neighbourhoods with low versus high street connectivity reported possible increases in the occurrence of street injuries (OR, 1.38; 95% CI, 0.84 to 2.26). This relationship was mainly attributable to the occurrence of bicycle injuries (52% of all street injuries; OR, 2.33; 95% CI, 1.28 to 4.25). The population attributable risk was 20% for street injuries potentially caused by living in an area with low connectivity. CONCLUSION: The design of streets, as a measure of the built environment, is related to the occurrence of youth injury. Positive effects of poorly connected street designs that are likely in terms of physical activity were offset by negative injury outcomes, although the injuries observed were mostly minor in nature.
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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) | 0.000 | 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".