The Relationship of Urban Form on Children and Adolescent Health Outcomes: A Scoping Review of Canadian Evidence
Bibliographic record
Abstract
Urban form can have an impact on health outcomes in children, and the synthesis of findings can identify gaps in the literature and regional reviews may help guide policymakers. This study aims to complete a scoping review of the research relating urban form to health outcomes in children and adolescents from urban Canadian settings. Thirteen online databases were searched to identify studies that had objective measures of urban form and health outcomes. Two research assistants independently reviewed 27,444 titles and abstracts, and 176 full-text articles, returning 32 unique studies with youth-specific data. The majority of the included studies were cross-sectional or ecological (n = 26). Six studies used Canada-wide data and the rest were from Ontario (n = 11), Alberta (n = 6), and Quebec (n = 6). Urban form characteristics included neighbourhood food environment (n = 11), parks/natural space/greenness (n = 10), road or intersection characteristics (n = 7), and aggregated urban form measures (n = 7). Studies examined a variety of health outcomes: the majority considered weight status (n = 16) and injury (n = 10). Although there is over-reliance on mainly cross-sectional study designs, there is evidence suggesting that urban form is associated with health outcomes in Canadian youth, with parks/greenspace, road connectivity, and road characteristics most consistently associated with health outcomes in youth.
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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 | 0.019 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.023 | 0.039 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".