Associations between neighbourhood street connectivity and sedentary behaviours in Canadian adults: Findings from Alberta’s Tomorrow Project
Bibliographic record
Abstract
Evidence suggests that neighbourhood street connectivity is positively associated with physical activity, yet few studies have estimated its associations with sedentary behaviour. We estimated the associations between space syntax derived street integration, a novel measure of street connectivity, and sedentary behaviours among Canadian adults. Data were sourced from a population-based study-Alberta's Tomorrow Project (n = 14,758). Items from the International Physical Activity Questionnaire captured sedentary behaviour, including sitting and motor vehicle travel time and walking. Street integration was measured within a 1600m radius of participants' homes. Covariate-adjusted linear regression models estimated the associations between street integration and sedentary behaviour. Street integration was significantly positively associated with daily minutes of sitting on week (b 6.44; 95CI 3.60, 9.29) and weekend (b 4.39; 95CI 1.81, 6.96) days, and for week and weekend days combined (b 5.86; 95CI 3.30, 8.41) and negatively associated with daily minutes of motor vehicle travel (b -3.72; 95CI -3.86, -1.55). These associations remained significant after further adjustment for daily walking participation and duration. More research is needed to understand the pathways by which street integration positively and or negatively affects sedentary behaviour.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.002 |
| 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".