Cardiovascular risk and the neighbourhood built environment in urban settings
Bibliographic record
Abstract
Cardiovascular disease (CVD) is a leading cause of death, and the greatest contributor to health care costs in Canada. Primary prevention is an important strategy for limiting both disease and costs. Cardiovascular disease incidence and mortality are causally related to physical activity in an inverse, dose-response trend. Physically inactive lifestyles increase and hasten the incidence of CVD. Features of the built environment have been shown to moderate physical activity levels in neighbourhood residents and thus could also be contributing to CVD risk. However, investigation into the association between the built environment and modifiable CVD risk factors is rather limited. The purpose of this investigation is to compare levels of CVD risk factors affected by physical activity in neighbourhoods varying on walkability and number of leisure-time physical activity correlates. Objective measures of several cardiovascular risk factors: BMI, waist girth, systolic blood pressure and HDL-C concentration were collected on participants across British Columbia, Canada. Geographical information system software was used to score a 750m network buffer around each participant’s residence on the Neighbourhood Walkability Index and number of leisure-time physical activity correlates. Participants were also grouped based on their neighbourhood-level median after-tax income. A total of 2999 individuals were included in statistical analyses. Findings revealed significantly lower BMI, waist girth and systolic blood pressure values amongst residents of high (compared to low) walkable neighbourhoods. Individuals living in environments with more leisure-time physical activity correlates also exhibited significantly lower BMI and waist girth values. Higher income groups were associated with significantly less risk for BMI and waist girth. These results contribute to a growing body of research on the effect of the urban built environment at the neighbourhood level on cardiovascular health. This investigation is unique in its analysis of several CVD risk factors which are influenced by physical activity, beyond BMI. Findings of lower waist girths among residents of high walkability neighbourhoods are novel and speak to potential cardiometabolic effects of living in areas which support active transportation and leisure-time physical activity. Furthermore, our data identify low income neighbourhoods with the least physical activity correlates as relatively high risk areas.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".