The influence of farm production diversity on women’s dietary quality in Ethiopia
Bibliographic record
Abstract
Malnutrition remains a significant global challenge, particularly in low- and middle-income countries, such as Ethiopia, where the great majority of smallholder farm households rely on agriculture as a crucial source of both food and income. Diverse agricultural production has the potential to improve the quality of the diet and combat malnutrition. The linkage between agricultural production diversity and dietary quality, however, remains debated. In this study, we used three distinct techniques - food group production diversity, species count (crop and livestock), and Simpson Diversity Index - as measures of farm production diversity to assess the effect of production diversity on the women’s dietary quality, assessed in terms of dietary diversity score, minimum dietary diversity for women and nutrient mean adequacy ratio. Three different regression models, namely Poisson, logistic and OLS, were employed on a sample of 1,910 women of reproductive age from farming households selected using a multistage sampling technique in five regions of Ethiopia. The finding indicates that food group production diversity has a significant and positive association with all the dietary quality indicators, a one unit increase in food group production diversity increases dietary diversity by 0.013 at ( p < 0.05), increases the mean adequacy ratio by 3.1% at ( p < 0.01) and increases the odds of achieving minimum dietary diversity by 27.5% at ( p < 0.01). Furthermore, the species count has a significant and positive association with minimum dietary diversity for women. A one-unit increase in the species count increases the odds of achieving minimum dietary diversity by 1.5% at ( p < 0.05) but has significant influence on dietary diversity and mean adequacy ratio. The Simpson Diversity Index exhibits a significant and positive association with dietary diversity and minimum dietary diversity for women but shows no relationship with the mean adequacy ratio. Despite some variation between the measures, these findings suggest that a more diversified production system enhances the dietary diversity and nutrient adequacy of women within farm households, particularly minimum dietary diversity for women, supporting the potential of diversified agricultural systems to improve nutritional outcomes. This can be achieved by raising awareness and knowledge of the benefits of more diversified farming, and equipping farmers them with the skills to diversify their production systems, along with the provision of technical and financial support.
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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 | 0.002 |
| 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 | 0.001 | 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".