Anemia among Primary School Children (5-12 years) in Riyadh Region, Saudi Arabia: A Community-Based Study
Bibliographic record
Abstract
Background: Anemia among school aged children is known to be an important global public health problem in both developing and developed countries. It affects the physical and intellectual functions of the affected children. School years are ideal opportune time to intervene to prevent and control anemia. Objectives: The objective of the study is to investigate the frequency of anemia and the associated dietary and medical risk factors in school aged children in Riyadh region. Subject and Methods: A cross sectional survey was carried out in Riyadh region. The study sample was selected using the two stages of cluster sampling technique. Standardized Arabic questionnaire was completed by parents of school aged children by two well trained nurses. Dietary frequency was requested for the last week prior to the interview. A venous blood sample was taken for hemoglobin estimation. Anemia in school aged children was defined according to the WHO definition. Results: The total sample was 1117 children, 49.9% males and 50.1% females. Prevalence of anemia was 22.3% (22.4% in males & 22.2% in females). Frequent eating of red meat reduced the risk of anemia (OR=0.8). Frequent drinking of cola or sour milk (Laban) with lunch meal significantly increased the risk of anemia (OR=1.52, 1.06-2.16 and OR=1.55, 1.07-2.25 respectively). Family history of hereditary blood disorders or iron deficiency anemia increased the risk of anemia in school aged children (OR=5.48, 1.02-31.21 and OR= 3.38, 1.74-6.54 respectively). Conclusions: Anemia in school children is a moderate public health problem in Riyadh region. Drinking sour milk with lunch and positive family history increases the risk of anemia in school children.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".