Perspective: Weekly Iron and Folic Acid Supplementation (WIFAS): A Critical Review and Rationale for Inclusion in the Essential Medicines List to Accelerate Anemia and Neural Tube Defects Reduction
Bibliographic record
Abstract
Weekly iron and folic acid supplementation (WIFAS) is among the 8 key effective actions for improving adolescent nutrition included by the WHO in the 2018 guidelines. However, at present WIFAS in the WHO-recommended formulation is not included in the Model Essential Medicines List (MEML), limiting the potential for countries to import, produce, and prioritize this formulation as part of their national supply management and procurement plans for medicines. The WHO WIFAS guideline presents evidence that the formulation reduces anemia, but not that folic acid reduces neural tube defects (NTDs), because sufficient evidence was unavailable at the time of the last review. Recently, a 3-arm, parallel-group, randomized, double-blind, placebo-controlled folic acid efficacy trial on WIFAS was conducted to address this evidence gap. The study population included 331 women (18-45 y old), randomly assigned to 3 treatment groups, including a supplement with 60 mg Fe as ferrous fumarate and either 0 mg, 0.4 mg, or 2.8 mg of folic acid, to be consumed once weekly for 16 wk, followed by a 4-wk washout period. In this article we critically review how the outcomes of this folic acid efficacy trial, and how the evidence generated, could potentially be used to inform WHO WIFAS guidelines for the potential inclusion of this formulation on the MEML, and how this, in turn, may affect product availability. If the new evidence on weekly folic acid is assessed as adequately reducing the risk of NTDs, a guideline revision could be warranted and WIFAS could be presented to the MEML for the dual benefits of anemia reduction and NTD prevention. This inclusion could enable acceleration of implementing policies and programs to contribute to global anemia and NTD reduction efforts.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".