Nutritional Status among Children under Five Years in Amman, Jordan
Bibliographic record
Abstract
Objectives: There is scarcity of data on malnutrition among children in Jordan. Therefore, this study was conducted to assess the nutritional status and estimate the prevalence rates of stunting, underweight, and wasting and their associated factors among children under five. Subjects and Methods: A cross-sectional study was conducted between January and April 2017 among children under five years in Amman, Jordan. All Jordanian children under five years who visited the selected health centers for vaccination or accompanied their mothers during the study period were included in this study. Mothers or caregivers of children were interviewed face-to face using the study questionnaire. Weight in kilograms and height in centimeters were measured for all children. Anthropometric indices were calculated using reference medians recommended by the World Health Organization. Results: This study included a total of 923 (463 boys and 460 girls) children. The prevalence rates of stunting, underweight, and wasting were 6.2%, 3.8%, and 2.8%, respectively. Multivariate analysis showed that low birth weight was significantly associated with stunting (OR = 2.9, 95% CI: 1.4,6.0; p-value=0.003) and underweight (OR =5.6, 95% CI: 2.5,12.3, p-value <0.001). Compared to exclusive breastfeeding, mixed feeding was associated with increased odds of stunting (OR =2, 95% CI: 1.1-3.9, p-value =0.029) and underweight (OR = 2.2, 95% CI: 1.002, 5.0; p = 0.049). None of the variables were significantly associated with wasting. Conclusions: The prevalence rates of stunting, wasting and undernutrition among children under five years in Jordan are low. Low birth weight and mixed feeding were associated with higher rates of malnutrition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".