Associations between the built environment and physical activity among adults with low socio-economic status in Canada: a systematic review
Bibliographic record
Abstract
OBJECTIVE: To synthesize literature on the associations between the built environment and physical activity among adults with low socio-economic status (SES) in Canada. METHODS: Using a pre-specified study protocol (PROSPERO ID: CRD42019117894), we searched seven databases from inception to November 2018, for peer-reviewed quantitative studies that (1) included adults with low SES living in Canada and (2) estimated the association between self-reported or objectively measured built characteristics and self-reported or objectively measured physical activity. Study quality was assessed using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Findings were synthesized using a narrative approach. SYNTHESIS: Of the 8338 citations identified by our search, seven studies met the inclusion criteria. Most studies included adults living in one province (Alberta, British Columbia, Ontario, or Quebec), with one study including a national sample. All studies were cross-sectional, and none controlled for residential self-selection. Sampling designs and data collection strategies were heterogeneous. Sample sizes ranged between 78 and 37,241 participants. Most studies measured SES using household income. Street connectivity, greenness, destination density, and walkability were positively associated with physical activity. Relative to the objectively measured built environment, associations between the self-reported built environment and physical activity were less consistent. Studies were of fair to good quality. CONCLUSION: Findings suggest that the neighbourhood built environment is associated with physical activity among adults with low SES in Canada. More rigorous study designs are needed to determine whether or not the built environment and physical activity are causally related within this vulnerable population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.018 | 0.026 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".