Amount of Zinc Transferred in Breast Milk to Breastfed Moroccan Babies with Normal or Low Birth Weight at 1, 3 and 6 Months After Birth
Bibliographic record
Abstract
The amount of zinc in breast milk is generally regarded as sufficient to cover the increasing zinc demands of most infants. However, this is not well investigated where stores zinc may be compromised in babies with low birth weight (LBW) who are born with low stores of zinc. In Morocco, this is the first time that the amount of zinc transferred in breast milk has been estimated. This study included 32 mother-baby pairs. In our case study, we aimed to measure The quantity of zinc in mothers’ breast milk with normal birth weight (NBW) and LBW babies who were exclusively or not exclusively breast fed at 1,3 and 6 month after birth. The results showed that the majority of mothers have a BMI ≥25 kg/m2 this means that all mothers are overweight during 6 months after birth. Zinc concentration (mg/l) in mothers’ breast milk decreased from first month to six month. p- value showed that for mothers with NBW babies, there is a significant difference between the 1 and 6 month (p=0.0003) and between 3 and 6 month after birth (p=0.0007). For mothers with LBW babies, p-value showed a significant difference between the zinc concentration in breast milk in the 1st and 3rd month (p=0.0007), 1 and 6 month (p< 0.0001) and between 3rd and 6th month after birth (p=0.0056). The rate of NBW babies who were exclusively breastfed was 36.67%, 30.25% and 10% successively in 1st, 3rd and 6th month after birth. For LBW babies, the rate of exclusively breastfed was 15.38%, 7.69% and 2.69% successively in 1st, 3rd and 6th month after birth. Based on the K. Brown study in 2009, we can develop a mathematical equation to our own population using our data: Ln [Zinc] = 0.960 – 0.161*Ln(âge) – 0.187*Ln(âge)2. In conclusion the zinc concentration in milk is within normal range and decreases with the age of the babies. The predicted model of zinc concentration in breast milk was developed and tested.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".