Prevalence of Iron Deficiency and Iron Deficiency Anemia in the Northern and Southern Provinces of Rwanda
Bibliographic record
Abstract
BACKGROUND: Anemia remains a public health problem in Rwanda, affecting 38% of young children and 17% of reproductive-aged women (Demographic and Health Survey [DHS] 2010). The importance of iron deficiency (ID) as a cause of anemia in Rwanda is not known. OBJECTIVE: We aimed to estimate the prevalence of ID and iron deficiency anemia (IDA) among young children and women in 2 provinces of Rwanda. METHODS: We conducted a cluster randomized survey, selecting 408 rural households each in the Northern and Southern Provinces of Rwanda in 2010. Anemia was defined as hemoglobin <110 g/L in children and <120 g/L in nonpregnant women after correction for altitude. We defined ID as (1) serum transferrin receptor (TfR) >8.3 mg/L or (2) serum ferritin (SF) <12 μg/L in children and <15 μg/L in nonpregnant women after correction for inflammation. RESULTS: The prevalence of anemia was 30.9% (95% confidence interval [CI], 26.4-35.8) in children (n = 577) and 11.2% (95% CI, 8.4-14.7) in women (n = 595). The prevalence of ID in children was 3.1% (95% CI, 1.8-5.1) as defined by high TfR and 5.9% (95% CI, 4.0-8.4) as defined by low SF. Similarly, 3.0% (95% CI, 1.8-4.8) of women had high TfR and 4.8% (95% CI, 3.2-7.2) had low SF. The prevalence of IDA (low SF with concurrent anemia) ranged from 1.4% (95% CI, 0.5-3.6) among women in the North to 5.6% (95% CI, 3.1-10.0) among children in the South. CONCLUSIONS: ID is likely not an important contributor to anemia in the Northern and Southern Provinces of Rwanda. This finding warrants further investigation into other causes of anemia.
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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".