Double Fortified Salt in India: Coverage, Efficacy and Way Forward
Bibliographic record
Abstract
Iron deficiency remains the world’s most widespread nutritional disorder and India is one of the countries very worst afflicted. India has successfully reduced the burden of iodine-deficiency disorders through mandatory iodization of salt for more than 20 years. This has resulted in a significant decrease in the prevalence of iodine deficiency diseases. Building on the success with iodization, double fortification of salt with iodine and iron is gaining ground and can be integrated with established iodization processes. DFS contemplates the creation and distribution of a powerful innovative product with demonstrated health effects, building on existing distribution platforms for salt through public distribution channels targeted to some of the most impoverished populations in the country at minimal expense and without requiring changes in cultural habits and compliance. Two formulations have been approved by Food Safety and Standard Authority of India (FSSAI) with iron either in the form of encapsulated ferrous fumarate or ferrous sulphate. A meta-analysis showed that DFS increased hemoglobin concentrations significantly. This intervention as part of a broader anemia strategy has the potential to effect large-scale anemia reduction across populations in India on a permanent and economically self-sustaining basis.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".