A Nutrition Education Intervention Positively Affects the Diet–Health-Related Practices and Nutritional Status of Mothers and Children in a Pulse-Growing Community in Halaba, South Ethiopia
Bibliographic record
Abstract
OBJECTIVE: We conducted a six-month nutrition education intervention focused on the consumption of pulses and other foods to assess the effect on knowledge, attitude and practice (KAP) as well as the nutritional status of children and mothers from two pulse-growing communities in Halaba, south Ethiopia. METHODS: About 200 mother-child pairs in each of two purposively selected communities participated in this intervention study. A six-month nutrition education programme, involving interactive monthly community meetings and home visits, was offered to one of the two communities and the other served as a control/comparison. This study incorporated the use of Health Belief Model constructs to assess the KAP/perceptions of mothers surrounding pulse and other food consumptions, as well as nutrition-related issues before and after the intervention. Objective measures included dietary diversity scores (DDSs), one-day weighed dietary intakes and nutritional status measures based on anthropometric information. Demographics and socioeconomic information were also collected at baseline and endline. RESULTS: < 0.05) were found in the intervention group on the KAP and perceptions of pulse nutrition benefits among mothers, DDSs and pulse and animal source food consumption indexes for mothers and children and the mean body-mass-index-for-age Z-score and wasting among children. CONCLUSIONS: Community-based nutrition education interventions involving monthly interactive community meetings and home visits in pulse-growing communities from a resource-poor country like Ethiopia can be effective in improving mothers' knowledge of pulse nutrition and consumption frequency, leading to improvements in the DDSs of children and mothers while decreasing child underweight and wasting.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".