May Measurement Month 2022: an analysis of blood pressure screening results from South Africa
Bibliographic record
Abstract
The May Measurement Month (MMM) campaign was carried out in South Africa in 2022 with the aim of raising awareness of raised blood pressure (BP). Here, we report on the findings of the campaign. Adults aged ≥18 years were recruited opportunistically at university campuses, community centres, schools, sport complexes, public parks, shopping centres, hospitals, and through household visits. Three seated BP readings were taken for each participant, along with completion of a questionnaire on demographics, lifestyle factors, and comorbidities. Hypertension was defined as a systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg or being on antihypertensive medication. Controlled BP was defined as being on antihypertensive medication with a BP < 140/90 mmHg. Multiple imputation was used to estimate any missing BP readings. In total, 4602 were screened, with a mean age of 31.9 years and 61.9% of whom were female. Of all participants, 1217 (26.5%) had hypertension, of whom 456 (37.5%) were aware, and 406 (33.4%) were on antihypertensive medication. Of those on antihypertensive medication, 205 (50.5%) had controlled BP, and of all participants with hypertension, 16.8% had controlled BP. The MMM campaign in South Africa identified significant numbers of participants with either untreated or inadequately treated hypertension. The high prevalence of hypertension, despite the young adult age, together with the high proportions of individuals unaware of their hypertension and with uncontrolled BP highlights the need for hypertension screening and awareness campaigns, and more rigorous management of hypertension.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".