Postwar dietary diversity among children aged 6-23 months in northern Ethiopia
Bibliographic record
Abstract
Introduction: Conflict exacerbates poor complementary feeding and reduces dietary diversity. Before the 2020–2022 war in northern Ethiopia, around 74% of children aged 6–23 months failed to meet minimum dietary diversity (MDD) and post-war prevalence was unknown. This study aims to assess MDD prevalence and associated factors among children aged 6–23 months in a town in northern Ethiopia two years after the ceasefire. Methodology: A health facility-based cross-sectional study of 584 participants was conducted in a town in northern Ethiopia. Sociodemographic and dietary data were collected using a 24-hour dietary recall questionnaire and analyzed in STATA ® version 15. Pre-war dietary diversity was estimated using data from the 2016 and 2019 Ethiopian Demographic and Health Surveys. Results: MDD declined from 33.2% pre-war period to 25.2% (95% CI: 21.6-28.7) in the post-war period. Children aged 18–23 months were 3.2 times more likely to achieve MDD than those aged 6–11 months (p = 0.001). Middle- and high-income households had 6.13-fold and 13.58-fold higher odds of meeting MDD, respectively (both p < 0.001). Households with 5–8 members had 3.6-fold higher odds of providing MDD compared to those with 1–3 members (p = 0.017). Children of mothers aged 26–35 years (AOR = 0.48, p = 0.026) and 36–42 years (AOR = 0.29, p = 0.017) had lower odds of meeting MDD. Higher paternal education (AOR = 2.58, p = 0.031) and paternal occupation as a merchant (AOR = 3.17, p = 0.001) were positively associated with MDD. Post-war, grain (77.5% to 92.1%) and legume (33.9% to 69.3%) consumption increased significantly, while flesh foods (20.9% to 7.2%) and vitamin A-rich foods 46.8% to 26%) declined. Conclusion: Post-war dietary diversity in remains low, influenced by socioeconomic and demographic factors. Significant reductions in nutrient-dense foods highlight critical gaps in child nutrition. Targeted nutrition education for caregivers and interventions promoting dietary diversity are essential in conflict-affected settings.
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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 | 0.001 |
| 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) | 0.002 | 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".