Prevalence and Determinants of Chronic Malnutrition Among Under-5 Children in Ethiopia
Bibliographic record
Abstract
Objectives: This paper studied the prevalence and determinants of chronic malnutrition in under-5 children from the 2011 Ethiopian Demographic and Health Survey dataset. Methods: The 2011 EDHS collected data on the nutritional status of children by measuring the height and weight of all children under age five in the sampled households, and calculated anthropometric indicators using the new WHO (2006) growth standards. Children whose height-for-age Z-score was below minus two standard deviations (−2 SD) from the median of the WHO reference population are considered stunted or chronically malnourished and if Z-scores are between −3 SD ≤ Z-score < −2 SD were identified as moderately stunted and if below −3 SD as severely stunted. Some variables were computed by combining information for original variables. The 2011 Ethiopian DHS dataset was obtained for further analysis from MEASURE DHS after permission. Complete anthropometric data for 9,611 children aged 0 to 59 months were analyzed. Results: The overall prevalence of stunting in children was 42.3%, with 20.4% severely stunted. Socio-demographic factors were significantly associated with both severe and moderate forms of stunting. Multivariate analysis showed that parents' education, household wealth index, age of household head, child's age, months of breast-feeding, place of delivery, media exposure, mother's BMI and residential differentials were the underlining determinants of stunting. Conclusions: Chronic malnutrition in children is a public health problem in Ethiopia specifically as children grow older to age three. To achieve the Millennium Development Goal target of 34% malnutrition prevalence by 2015, it is imperative to have specific interventions focusing on causes that directly influence stunting in children.
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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 | 0.001 |
| 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".