Determinants of child anthropometric indicators in Ethiopia
Bibliographic record
Abstract
BACKGROUND: Malnutrition is one of the major contributors to child mortality in Ethiopia. Currently established, child nutrition status is assessed by four anthropometric indicators. However, there are other factors affecting children's anthropometric statuses. Thus, the main objective of this paper is to explore some of the determinants of child anthropometric indicators in Ethiopia. METHODS: Data from GROW (the Growing Nutrition for Mothers and Children), a survey including 1261 mothers and 1261 children was carried out in Ethiopia in 2016. Based on the data gathered, the goal of GROW is to improve the nutritional status of women of reproductive age (15-49), as well as boys and girls under 5 years of age in Ethiopia. In order to investigate the association between different factors and child anthropometric indicators, this study employs various statistical methods, such as ANOVA, T-test, and linear regressions. RESULTS: Child's sex (confidence intervals for (wasting = - 0.782, - 0.151; stunting = - 0.936,-0.243) (underweight = - 0.530, - 0.008), child's age (confidence intervals for (wasting = - 0.020, 0.007; stunting = - 0.042,-0.011) (underweight = - 0.025, - 0.002), maternal MUAC (confidence intervals for (wasting = 0.189, 0.985; BMI-for-age = 0.077, 0.895), maternal education (stunting = 0.095, 0.897; underweight = 0.120, 0.729), and open defecation (stunting = 0.055, 0.332; underweight = 0.042, 0.257) were found to be significantly associated with anthropometric indicators. Contrary to some findings, maternal dietary diversity does not present significance in aforementioned child anthropometric indicators. CONCLUSION: Depending on the choice of children anthropometric indicator, different conclusions were drawn demonstrating the association between each factor to child nutritional status. Results showed child's sex, age, region, open defecation, and maternal MUAC significantly increases the risk of child anthropometric indicators. Highlighting the factors influencing child undernutrition will help inform future policies and programs designed to approach this major problem in Ethiopia.
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 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 | 0.001 | 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) | 0.002 | 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".