Mortality, Cardiovascular Disease, and Their Associations With Risk Factors in Southeast Asia
Why this work is in the frame
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Bibliographic record
Abstract
Background: The drivers of cardiovascular disease (CVD) and all-cause mortality may differ around the world. Regional-level prospective data can help guide policies to reduce CVD and all-cause mortality. Objectives: This study examined the incidence of CVD and mortality in Malaysia and the Philippines and estimated the population-level risks attributable to common risk factors for each outcome. Methods: This prospective cohort study included 20,272 participants from Malaysia and the Philippines. The mean follow-up was 8.2 years. The incidences of CVD and mortality rates were calculated for the overall cohort and in key subgroups. For each outcome, population-attributable fractions (PAFs) were calculated to compare risks associated with 12 modifiable risk factors. Results: The mean age of the cohort was 51.8 years (59% women). Leading causes of mortality were CVD (37.9%) and cancer (12.4%). The incidence of CVD (per 1,000 person-years) was higher in the Philippines (11.0) than Malaysia (8.3), and CVD contributed to a higher proportion of deaths in the Philippines (58% vs 36%). By contrast, all-cause mortality rates were higher in Malaysia (14.1) than in the Philippines (10.9). Approximately 78% of the PAF for CVD and 68% of the PAF for all-cause mortality were attributable to 12 modifiable risk factors. For CVD, the largest PAF was from hypertension (24.2%), whereas for all-cause mortality, the largest PAF was from low education (18.4%). Conclusions: CVD and cancer account for one-half of adult mortality in Malaysia and the Philippines. Hypertension was the largest population driver of CVD, whereas low education was associated with the largest burden of overall mortality.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 it