Interpretation of Serum Retinol Data From Latin America and the Caribbean
Bibliographic record
Abstract
BACKGROUND: In recent decades, the general socioeconomic situation in Latin America and the Caribbean countries has improved, and many vitamin A programs have been implemented in an attempt to reduce vitamin A deficiency in the region. OBJECTIVE: To examine vitamin A status in Latin America and the Caribbean based on serum retinol concentrations and to contrast available data published before and after 1998. METHODS: A systematic review was performed. National surveys or representative studies that reported vitamin A status were selected. RESULTS: Ten national surveys and six representative studies were identified. Data for children under 6 years of age indicate that Guatemala and Nicaragua have practically eradicated vitamin A deficiency (less than 2% prevalence of serum retinol < 20 μg/dL). In Costa Rica, Cuba, El Salvador, and Panama, the prevalence of vitamin A deficiency ranged from 2.8% to 9.4%. In Peru, Honduras, Argentina, Ecuador, and Brazil, vitamin A deficiency is a moderate public health problem (prevalence from 14.0% to 17.4%), while in Colombia, Mexico, and Haiti it is a severe public health problem (prevalence from 24.3% to 32.0%). Disadvantaged groups (indigenous people and those of Afro-Colombian descent) have the highest rates of deficiency. The prevalence of vitamin A deficiency is under 20% in school-children and adult women. When data published before and after 1998 for children under 6 years of age were compared, most Central American countries had a reduction in the prevalence of vitamin A deficiency (p < .05), whereas in South American countries, the prevalence of vitamin A deficiency increased over time (p < .05). CONCLUSIONS: The prevalence of vitamin A deficiency in children under 6 years of age has decreased in many Central American countries, but vitamin A deficiency still remains a public health problem in numerous Latin America and Caribbean countries, especially among disadvantaged and vulnerable groups. Because of issues with the accuracy of the serum retinol biomarker reflecting body stores, these results must be interpreted with caution.
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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) | 0.001 | 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".