Determinants of nutrition security status of women in rural households in Northwest Ethiopia
Bibliographic record
Abstract
The nutrition security of women is critically important for society’s well-being. Therefore, this study was conducted to determine the determinants of the nutrition security status of rural women in Northwest Ethiopia. Data collected from rural women in 197 randomly selected households were analyzed using a binary logit regression model. The results show that 72.6% of the women are nutritionally insecure. The determinants that significantly affect nutrition security status are family size (a negative effect), women’s daily feed frequency, milk consumption, feeding habits of fruits and vegetables, feeding habits of animal products, and women empowerment (all positive effects). The weight, height, and BMI of nutritionally insecure women were significantly lower than those of nutritionally secure women. These findings reveal the need for government and other stakeholders’ interventions to increase access to nutritious food products and to provide training on feeding culture and dietary diversity to women. The findings of this study can help the Government of Ethiopia to focus on the significant determinants to achieve its National Development Priorities focusing on the Sustainable Development Goals (SDGs) of the UN, particularly Goals 2, 3, and 5.
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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 | 0.000 | 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 | 0.000 | 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".