Folic Acid Fortification through Existing Fortified Foods: Iodized Salt and Vitamin A—Fortified Sugar
Bibliographic record
Abstract
BACKGROUND: Folic acid fortification of cereal-grain products has markedly improved folate status and reduced the risks of neural tube defects and other chronic diseases in the populations participating in fortification programs. To more broadly extend its benefit to affected populations in developing countries, it would seem logical to incorporate folic acid fortification into existing or planned programs to minimize the incremental cost of this intervention. OBJECTIVE: To examine the feasibility of providing folic acid through ongoing programs for salt iodization and vitamin A fortification of sugar. METHODS: Folic acid was added to iodized salt and vitamin A-fortified sugar by various methods--direct blending as a powder, spraying onto the carriers as aqueous solution or suspension, or blending as a microencapsulated premix. The multiple fortified samples were subjected to a prolonged storage stability test, and the retentions of the added micronutrients were followed. RESULTS: Folic acid was generally stable when incorporated into Guatemalan iodized salt and vitamin A-fortified sugar. Even in the presence of encapsulated ferrous fumarate as an iron fortificant, samples retained > 80% in salt and approximately 70% in sugar samples respectively, after 9 months of storage at 40 degrees C and 60% relative humidity. The addition of folic acid as a dry premix made by extrusion was most effective in retaining both folic acid and the other added micronutrients. CONCLUSIONS: The fortification method had a pronounced impact on the stability of both folic acid and the other added micronutrients. Proper encapsulation may be required to ensure the stability of multiple fortified foods.
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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 | 0.000 |
| 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 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".