Reducing the Burden of Anemia and Neural Tube Defects in Low- and Middle-Income Countries: An Analysis to Identify Countries with an Immediate Potential to Benefit from Large-Scale Mandatory Fortification of Wheat Flour and Rice
Bibliographic record
Abstract
Using a predetermined set of criteria, including burden of anemia and neural tube defects (NTDs) and an enabling environment for large-scale fortification, this paper identifies 18 low- and middle-income countries with the highest and most immediate potential for large-scale wheat flour and/or rice fortification in terms of health impact and economic benefit. Adequately fortified staples, delivered at estimated coverage rates in these countries, have the potential to avert 72.1 million cases of anemia among non-pregnant women of reproductive age; 51,636 live births associated with folic acid-preventable NTDs (i.e., spina bifida, anencephaly); and 46,378 child deaths associated with NTDs annually. This equates to a 34% reduction in the number of cases of anemia and 38% reduction in the number of NTDs in the 18 countries identified. An estimated 5.4 million disability-adjusted life years (DALYs) could be averted annually, and an economic value of 31.8 billion United States dollars (USD) generated from 1 year of fortification at scale in women and children beneficiaries. This paper presents a missed opportunity and warrants an urgent call to action for the countries identified to potentially avert a significant number of preventable birth defects, anemia, and under-five child mortality and move closer to achieving health equity by 2030 for the Sustainable Development Goals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 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".