Effect of multiple micronutrient fortified milk consumption on vitamin D status among school-aged children in rural region of Morocco
Bibliographic record
Abstract
Vitamin D deficiency is a health problem in both developed and developing countries. The aim of this study was to determine the effect of multi-vitamin fortified milk consumption on vitamin D status among children living in the mountainous region of Morocco. Children aged 7 to 9 years (n = 239; 49% of girls vs 51% of boys) participated in a double-blind longitudinal study, where they were divided in 2 groups: a fortified group that received daily 200 mL of fortified ultra-high-temperature (UHT) milk enriched with 3 μg of vitamin D3 and a nonfortified group that received 200 mL of nonfortified UHT milk with a natural abundance of vitamin D3 (about 1.5 μg). Blood samples were collected 3 times (at baseline, then at the fourth and ninth months). The average weight, height, and z score of body mass index for age of participants were 22.8 ± 2.6 kg, 121.5 ± 5.2 cm, and –0.2 ± 0.6 kg/m2, respectively. At baseline, 47.5% of children had a concentration of 25-hydroxyvitamin D below 50 nmol/L. At the end of the study the prevalence of vitamin D <50 nmol/L decreased significantly by 37.6% in the fortified group. These results reveal prevalent vitamin D insufficiency (<50 nmol/L) during winter among rural Moroccan school-aged children, which seems to be better improved by consuming the fortified milk instead of the nonfortified one.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".