Determinants of Stunting among Children Aged 6-23 Months of Age in Pastoral Community, Afar Region, Ethiopia: Unmatched Case-Control Study
Bibliographic record
Abstract
Background: Globally, stunting is a public health concern, more of in developing counties, including Ethiopia. Once occurred, in the first two years of life, it is irreversible and has long-lasting harmful consequences. Exploring the determinants has pivotal importance for evidence-based interventions. Therefore, the rationale of this study was to identify determinants of stunting among children aged 6-23 months in the pastoralist community, Afar region, Ethiopia. Method: A community-based unmatched case-control study was conducted among 381 (cases=126, controls 255) study participants from February 15/2017 to March 30/2017. Cases and controls were identified consecutively using the world health organization growth monitoring chart. Data was collected by interviewer-administered questionnaires and anthropometric measurements. Statistical significance was declared at p-value < 0.05 in the final multivariable logistic regression model. Result: Maternal education (AOR:0.34, 95% CI: 0.16, 0.77), maternal under-nutrition (AOR:2.91, 95% CI:1.51, 5.60), number of under-five children within the household (AOR:2.66, 95% CI: 1.38, 5.10), latrine ownership (AOR:0.28, 95% CI:0.15, 0.55), minimum Dietary Diversity score of children (AOR:0.41, 95% CI:0.22, 0.75), child age (AOR:1.76, 95% CI:1.01, 3.09), colostrum intake (AOR:3.03, 95%CI:1.62, 5.66), and exclusively breastfeed for the first six months (AOR:3.20, 95% CI:1.72,5.95) were found to be determinants of stunting. Conclusion: This study found that determinants of childhood stunting are multifactorial. Maternal, household and child-related characteristics are associated with childhood stunting. Therefore, to improve childhood nutritional status, inter-sectoral collaboration and commitment are vital.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".