Gender and household structure factors associated with maternal and child undernutrition in rural communities in Ethiopia
Bibliographic record
Abstract
Addressing maternal and child undernutrition is a priority for the National Nutrition Program of Ethiopia. In a cross-sectional design, we selected mother-child pairs (n = 630) from Halaba, south Ethiopia (n = 413, two communities) and Zeway, Oromiya region (n = 217, one community). These communities were previously included in a project to improve agricultural practices. We aimed to estimate the level of maternal and child undernutrition in the two study sites and compare findings to regional/national reports. We also examined associations with gender, household-structure and nutrition/health related variables. Households were selected using simple random sampling based on list of households obtained from local health posts. Mothers were interviewed via questionnaire. Anthropometric measurements were taken from mothers-child pairs. Maternal undernutrition (% BMI<18.5) ranged from moderate (14% Zeway) to high (22% Halaba). In the children, stunting and underweight were very high (54% and 42% stunting, 36% and 21% underweight, in Halaba and Zeway, respectively). Up to 95% of Halaba and 85% of Zeway mothers reported "same as usual" or "less than usual" consumption patterns during their most recent pregnancy compared to periods of non-pregnancy. Mothers reported (61% in Halaba, 18% in Zeway) abstaining from consumption of certain nutritious foods for cultural reasons. Gender and socio-economic-demographic structure of the households, including imbalance of power, control of farm produce, physiological density, household size and dietary habits during pregnancy showed significant associations with maternal and child undernutrition (p<0.05). The levels of child and maternal undernutrition, particularly in children, were unexpected and of concern, given that a national nutrition program has been in place since 2008. The study provides insights for policy makers to improve women's education, reproductive health services for better family planning, and strengthen nutrition/health programs designed to target vulnerable segments of the population in these and other rural communities and districts with similar structure and demographics in Ethiopia.
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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 | 0.000 | 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) | 0.001 | 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".