The relationship between objectively-measured attributes of the built environment and selected cardiovascular risk factors in a South African urban setting
Bibliographic record
Abstract
BACKGROUND: Evidence concerning the relationship between objectively-measured attributes of the built environment with cardio-metabolic risk in populations from lower- and middle-income countries is lacking. In this paper, we describe the association between the objectively-measured built environment with body mass index, blood pressure and physical activity in adult South Africans. METHODS: This cross-sectional study included 341 adults aged ≥35 years drawn from the Cape Town arm of the Prospective Urban Rural Epidemiology (PURE) cohort study. All Cape Town PURE participants were invited to take part in the study. Actigraph GT3X accelerometer and Geographic Information Systems were used to measure physical activity and built environment attributes (community center, shopping center and taxi rank). RESULTS: In age and sex adjusted models (reference 500 m), access to community centers (1000 m) was positively related to body mass index [beta 4.70 (95%CI: 2.06 to 7.34)] and diastolic blood pressure [4.97 (0.00 to 9.95)]. Distance from a community center (1600 m) was positively related to diastolic blood pressure [6.58 (1.57 to 11.58)] and inversely with moderate-to-vigorous physical activity [- 69.30 (- 134.92 to - 3.70)]. Distance to a shopping center (1600 m) was positively related to body mass index [4.78 (1.11 to 8.45)] and shopping center (1000 m) was positively related to systolic blood pressure respectively [76.99 (0.03 to 83.95)]. CONCLUSION: Distance to community and shopping centers were significantly associated with BMI, systolic, diastolic blood pressure and moderate-to-vigorous physical activity. Future research should include multiple aspects of built environment variables in order to provide for a broader understanding of their effect on cardiovascular risk profile of African populations.
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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 | 0.002 |
| 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 | 0.000 |
| 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".