Prevalence of Anemia in Latin America and the Caribbean
Bibliographic record
Abstract
BACKGROUND: In Latin America and the Caribbean, anemia has been a public health problem that affects mainly women of childbearing age and children under 6 years of age. However, the current prevalence of anemia in this region is unknown. OBJECTIVE: To examine the latest available prevalence data on anemia in Latin America and the Caribbean. METHODS: A systematic review was conducted in 2011 and updated in 2014. Studies determining the prevalence of anemia conducted in apparently healthy populations with national or regional representativeness were included in the review. RESULTS: The lowest prevalence rates of anemia among children under 6 years of age were found in Chile (4.0%), Costa Rica (4.0%), Argentina (7.6%), and Mexico (19.9%). In Nicaragua, Brazil, Ecuador, El Panama, and Honduras, anemia was a moderate public health problem, with prevalence ranging Salvador, Cuba, Colombia, the Dominican Republic, Peru, from 20.1% to 37.3%. Anemia was a severe public health problem in Guatemala, Haiti, and Bolivia. The prevalence of anemia among women of childbearing age was lowest in Chile (5.1%). In Colombia, El Salvador, Costa Rica, Nicaragua, Ecuador, Mexico, Peru, Honduras, and Argentina, anemia was a mild public health problem, with prevalence ranging from 7.6% to 18.7%. In Guatemala, Brazil, the Dominican Republic, and Bolivia, anemia was a moderate public health problem, with prevalence ranging from 21.4% to 38.3%. Panama and Haiti had the highest reported prevalence rates (40.0% and 45.5%, respectively), and anemia was considered a severe public health problem in those countries. CONCLUSIONS: Anemia remains a public health problem in children under 6 years of age and women of childbearing age in most Latin America and Caribbean countries for which data are available.
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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".