Physical activity vital sign assessment and associated health outcomes in an underserved South African community
Bibliographic record
Abstract
Abstract Background Physical activity is particularly low in South Africa and contributes to chronic conditions. This study aimed to determine physical activity levels in a South African community, using the physical activity vital sign (PAVS), and identify associations between physical activity and key health outcomes. Methods A cross-sectional study used community health workers to collect PAVS data, blood pressure and self-reported medical history from 2282 participants living in Soweto, Johannesburg. Physical activity was defined as meeting or not meeting WHO guidelines of ≥ 150 min/week. Hypertension was defined according to the International Society of Hypertension guidelines. Results The study population included 1161 women and 1121 men. Administering the PAVS was quick (29.5 ± 43.4 s). Only 19.8% of the total population reported meeting the guidelines, and it was significantly lower in women (17.6%) compared with men (22.1%). The logistic regression models demonstrated significant association between not meeting physical activity guidelines and hypertension (adjusted odd ratio [AOR] 0.77, 95% CI 0.61–0.97, p = 0.032), current smoking (AOR 0.73, 95% CI 0.55–0.97, p = 0.030) and past smoking (AOR 0.61, 95% CI 0.44–0.83, p = 0.002). Conclusions This study demonstrates the validity of using the PAVS in an underserved community. The observed associations highlight the potential of advocating physical activity as a feasible intervention for improving the health of urban-dwelling Black South Africans.
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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 | 0.001 |
| 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".