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Record W6910876029 · doi:10.5061/dryad.djh9w0w9p

Postwar dietary diversity among children aged 6-23 months in northern Ethiopia

2025· dataset· en· W6910876029 on OpenAlexaboutno aff

Bibliographic record

VenueDRYAD · 2025
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsOddsDietary diversityOdds ratioDiversity (politics)Public healthQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.535
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.003

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.

Opus teacher head0.010
GPT teacher head0.238
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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