Associated Factors for Adolescent Under Nutrition in Ethiopia: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction In Ethiopia, there are different pocket studies assessing the risk factors for adolescent under nutrition which comes up with inconsistent and inconclusive findings. Therefore, quantifying the risk factor using meta-analysis is crucial for evidence based intervention. Objective To assess the associated factors for adolescent under nutrition in Ethiopia Methods Systematic review of eligible articles was conducted using preferred reporting items for systemic reviews and meta-analysis (PRISMA) guidelines. A comprehensive search of literature was made in PubMed, Google and Google Scholar. Article quality was assessed using Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomized studies in meta-analyses. The odds ratio of the associated factors with its 95% confidence interval was computed using STATA version 14 software. Results Twenty two studies were included in the meta-analysis with a total of 17,854 adolescents. Random effects model was used for analysis. Rural residence, family size >=5, unprotected water source for drinking and household food insecurity were significant risk factors for adolescent stunting. Early adolescent age (10-14 years), family size >=5, food insecure household, lack of latrine, WHO diet diversity score<6, mother educational status were statistically significant risk factors for adolescent underweight. Conclusion Early adolescents’ age, low WHO diet score, family size>=5, illiteracy of mother, food insecure household, unsafe water source for drinking, lack of latrine and rural residence were statistical significant factors for adolescent under nutrition. Therefore, Adolescent nutritional interventions addressing the above risk factors should be designed and implemented in the country. Keywords: Adolescent, undernutrition, associated factors, Ethiopia.
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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 | 0.017 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.033 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".