The Malaysian Burden of Disease Study: Protocol for Mortality, Morbidity, and Risk Factor Evaluation
Bibliographic record
Abstract
BACKGROUND: Knowledge of the burden of disease at the national level is crucial for understanding regional health patterns and epidemiological trends. Regular updates and methodological enhancements are essential to produce accurate estimates that effectively represent the current health landscape, thereby assisting policymakers in resource allocation and strategic planning. OBJECTIVE: The objective of this study protocol is to revise the list of diseases and injuries; estimate years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) in phase 1; and identify the list of risk factors and determine risk-attributable burdens in phase 2. METHODS: The Malaysian Burden of Disease (MBOD) Study adopts the Global Burden of Disease Study approach, using various metrics to quantify health loss related to specific diseases, injuries, and risk factors. These metrics include deaths, YLLs, YLDs, and DALYs, which are calculated in terms of counts, age-specific rates, and all-age rates. In addition, this MBOD Study calculates risk-attributable deaths, YLLs, YLDs, and DALYs for all relevant risk factors. This study also conducts focus group discussions to develop the lists of diseases and injuries as well as risk factors. RESULTS: By December 2024, we had successfully completed the focus group discussions, which led to the development of an updated and comprehensive list of diseases and injuries. Furthermore, mortality data collection is complete, and the calculation of YLLs is currently in progress. The YLD calculation is expected to conclude by the end of 2025. While phase 1 is underway, phase 2, which addresses risk factor estimation, is scheduled for completion in mid-2026. CONCLUSIONS: This MBOD Study offers a comprehensive and current framework for assessing the burden of disease in Malaysia, with continuous improvement initiatives to enhance the list of diseases and injuries and refine the methodology for more accurate estimation and risk factor analysis. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/71583.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 | 0.054 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.066 | 0.016 |
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".