Risk factors for stunting among under-fives in Libya
Bibliographic record
Abstract
OBJECTIVE: Stunting is a chronic condition reflecting poor nutrition and health. Our aim was to ascertain major predictors of stunting in children <5 years old in Libya. POPULATION AND METHODS: A nationally representative, cross-sectional, two-stage stratified cluster sample survey enrolled 4549 under-fives from 6707 households. Logistic regression was used to determine individual risk factors in bivariate and multivariate analyses. RESULTS: Anthropometric measurements were available for 4498 children. Among the 929 stunted children (20.7 %), 495 were boys (53.3 %) and 434 were girls (46.5 %). In multivariate analysis, risk factors were young age (1-2 years: OR = 2.32, 95 % CI 1.67, 3.22; 2-3 years: OR = 1.64, 95 % CI 1.22, 2.21), resident of Al-Akhdar (OR = 1.67, 95 % CI 1.08, 2.58), being a boy (OR = 1.28, 95 % CI 1.05, 1.55), having a less educated father (illiterate: OR = 2.10, 95 % CI 1.17, 3.77; preparatory school: OR = 1.71, 95 % CI 1.11, 2.65), poor psychosocial stimulation (no family visits or trips: OR = 1.52, 95 % CI 1.07, 2.16; father rarely/never plays with child: OR = 2.24, 95 % CI 1.20, 4.16), filtered water (OR = 8.45, 95 % CI 2.31, 30.95), throwing garbage in the street (OR = 13.81, 95 % CI 2.33, 81.72), diarrhoea (OR = 1.58, 95 % CI 1.09, 2.29) and low birth weight (OR = 1.8, 95 % CI 1.17, 2.40). Protective factors were older age of father (OR = 0.53, 95 % CI 0.32, 0.90) and water storage (OR = 0.70, 95 % CI 0.54, 0.90). These variables only explained 20 % of cases of stunting. CONCLUSION: Various multilevel actions are needed to improve nutritional status of under-fives in Libya. At risk-groups include those with young age (1-3 years), resident of Al-Akhdar region, boys, father's low educational level, poor psychosocial stimulation, poor housing environment, diarrhoea and low birth weight.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".