Assessment of Serum Calcium, Serum Iron and Nutritional Status among Under-Five Children in Six Municipalities of Abidjan District, Côte d’Ivoire
Bibliographic record
Abstract
Malnutrition occurs in various forms in the world, especially in African countries. It affects two-thirds of the children in sub-Saharan Africa. In addition to the protein-energy malnutrition (PEM), micronutrient deficiencies also affect many children. The aim of this study was to evaluate the nutritional status, serum iron and serum calcium among under-five children. This study was conducted on a cohort from 480 children in six municipalities of Abidjan: Abobo, Cocody, Koumassi, Marcory, Treichville and Yopougon. A blood sample and anthropometric measurements (weight, height) were performed to determine the hematological profile and nutritional status of children. The results showed that stunting was the most widespread form of malnutrition among children surveyed. Depending on age, children from 0 to 6 months have a low prevalence of PEM than those from 7 to 59 months: wasting (1.2% vs 3.5%), stunting (8.6% vs 25.2%) and underweight (3.4% vs 10.7%). Also, the results reveal a lowest serum iron (µmol/l) among children from low households income (9.77 ± 2.4), illiterate mothers (8.92 ± 1.3) compared to those from mothers with a high level of education (21.75 ± 4.1) and high living standard (21.28 ± 2.1). There was no notable difference (p>0.05) between serum calcium whatever socio-demographic parameters considered. The parameters under study such as nutritional status, serum calcium and serum iron have shown a variation of malnutrition in Abidjan.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".