Risk Factors for Undernutrition among Children in South Central Somalia
Bibliographic record
Abstract
Objectives: Undernutrition is a global public health challenge, especially in countries that experience extreme climate conditions and armed conflict. In Somalia, undernutrition is chronic, often graded for emergency response. The purpose of this study was to provide evidence on immediate, proximate, and distal risk factors for undernutrition in the most affected region of Somalia. Setting: Data for the study was from cross-sectional nutritional surveys implemented by the Somalia Food Security and Nutrition Analysis Unit. Sampling for the surveys followed a multistage cluster sampling methodology where in the first stage, 30 clusters were randomly assigned to villages, and then 30 households were randomly selected from each cluster. Generalized Estimation Equations were used to determine risk factors for undernutrition. Data analysis followed survey analysis procedures. Participants: 60,856 children aged 6-59 months from cross-sectional nutritional surveys implemented in South-Central Somalia from 2007 to 2012. Results: When factors at the individual, household, and society level were considered simultaneously, diarrhea diseases and geographical region were the main risk factors for underweight, child gender, meal frequency, and livelihood zone were risk factors for stunting, while diarrhea and livelihood zone were the risk factors for wasting. Geographical region and livelihood system were significant factors for undernutrition. Conclusions: Interventions to address undernutrition in Somalia should be tailored to the region and livelihood zone while prioritizing innovative climate-smart food production and addressing childhood illnesses. The study findings provide evidence to inform nutrition policy and programs that could eliminate nutrition disparities and the burden of childhood undernutrition in Somalia and other countries with similar contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".