Neglected micronutrients—considering a broader set of vitamins and minerals in public health nutrition programs worldwide: a narrative review
Bibliographic record
Abstract
Several essential vitamins and minerals whose deficiencies are associated with metabolic and functional disorders, including increased morbidity and mortality from both communicable and noncommunicable diseases, are not being adequately addressed by large-scale, public health nutrition programs worldwide. These neglected micronutrients include thiamine, riboflavin, niacin, pyridoxine, vitamin B-12, vitamin D, vitamin K, calcium, selenium, and possibly others. In this narrative review, our objectives are to describe briefly the health implications of each of these deficiencies, summarize the limited available information on their epidemiology, and suggest possible approaches to address them. We conclude that more information, based on dietary assessments, nutritional biomarker surveys, and systematic surveillance of associated health conditions, is needed. Appropriate intervention programs, including changes in food systems to provide wider access to nutrient-rich foods, food fortification and targeted supplementation, should be implemented in settings where these deficiencies are confirmed.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".