Higher Maternal and Child Undernutrition in Pulse than Cereal Growing Rural Communities of Ethiopia: A comparative Cross-sectional Study
Bibliographic record
Abstract
Background: Whether growing pulses (low fat legumes rich in protein and micronutrients) translates to nutritional health benefits has not been well documented in Ethiopia. In pulse- and cereal-based agricultural communities, we compared the nutrition of mothers and children (<5y) through anthropometric and dietary assessment to document evidence of pulse agriculture translating to nutritional health benefits. We also explored contextual factors influencing nutritional status. Methods: Comparative study was conducted in purposively selected pulse- and cereal-growing Ethiopian communities, from rural Halaba and Zeway, with randomly selected individual participants of 413 and 217 mother-child dyads, respectively. Dietary diversity scores (DDS) and consumption indexes for selected food groups were assessed; median intakes of energy, protein, Fe, Zn, Ca were determined from a single-day weighed food records (in a subsample). Mother-child undernutrition was estimated using anthropometric assessments of weight, length/height and mid-upper-arm-circumference, MUAC. Results: Median energy and nutrient intakes for pulse-mothers, but not children, were significantly higher than cereal-mothers (p<0.01); Median DDS for mothers-children were three, out of nine food groups, in both communities; consumption index of pulses, although higher in the pulse-community (p<0.001), was generally low amounting to consumption of only 1-2/week; consumption from animal sources was minimal. Undernutrition in mothers was 22% in pulse and 14% in cereal. Child stunting, wasting and underweight were 53.5%, 10.4% and 36.5% in pulse and 41.8%, 4.1% and 21.6% in the cereal group, respectively. Gender-sensitive factors, such as access to own-land and work-burden predicted maternal-MUAC. Stunting, household size, land size, antenatal-clinic visits and frequency of dairy consumption also predicted maternal-MUAC. Child age, community (i.e., pulse- or cereal-growing), household size and land size predicted chid height-for-age z-score (HAZ). Pulses were mostly sold and women had limited control; mothers’ knowledge of the nutrition benefits of pulses was lower in pulse community (p<0.01). Conclusions: Poor DDS, pulse or animal-source food consumption and high levels of maternal and child undernutrition were found in both communities. The unexpected finding of greater undernutrition in the pulse-growing Halaba communities was of concern needing further investigation. The pulse-community could benefit from educational nutrition-intervention focusing on nutrition and other benefits of pulses.
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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 | 0.000 |
| 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".