May Measurement Month 2019: an analysis of blood pressure screening results from Ulaanbaatar, Mongolia
Bibliographic record
Abstract
Abstract Mortality from haemorrhagic stroke and ischaemic heart disease per 10 000 people in Mongolia ranks among the highest in the world. The main risk factor being hypertension. We aimed to screen hypertension for the working people in their workplace who rarely visit primary clinics. Two hundred health care volunteers were trained for blood pressure (BP) measuring technique and providing healthy lifestyle advice. Screening was performed at 80 sites, the majority were workplaces, over a period of 60 days when the May Measurement Month (MMM) campaign launched in May 2019. Hypertension was defined by the standard MMM guidance, as systolic BP ≥140 mmHg or diastolic BP ≥90 mmHg (based on the mean of the second and third measurement), or taking anti-hypertensive medication. Blood pressure measuring digital devices (Omron-M3, Microlife A6 PC) were all clinically verified and approved for clinical use. A total of 6522 individuals (majority 67.8% male and mean age 37.0 ± 10.4) were screened. The proportion of hypertensive adults was 32.5%, of whom, 62.2% were aware of their hypertension, and 50.1% were on medication. The control rate for those on treatment was 27.1%. Non-communicable disease risk factors were 51.2% (3342) overweight/obese (19.5% obese), 38.7% (2523) smoking, 64.4% (4200) alcohol consumption, 4.5% (294) previously diagnosed with diabetes, and 1.3% and 1.1% with a heart attack or stroke, respectively. We conclude that hypertension management needs to be prioritized and increased awareness is required in the population.
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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 | 0.000 | 0.000 |
| 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".