Maternal Vitamin D Status among Different Ethnic Groups and Its Potential Contribution to Adverse Pregnancy and Child Outcomes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Maternal vitamin D deficiency in pregnancy is a widespread public health concern. Race and ethnicity as biological and cultural factors, respectively, can affect vitamin D status through differences in skin color, sunlight exposure, and dietary intake. Low maternal vitamin D status in pregnancy may affect both mother and fetus adversely. Vitamin D deficiency and insufficiency are linked to a wide variety of adverse pregnancy outcomes such as gestational diabetes, preeclampsia, and preterm delivery. Furthermore, maternal vitamin D deficiency has been linked to several adverse health outcomes in infants and children. The examples include, but not limited to, impaired growth, skeletal problems, and autoimmune diseases such as type 1 diabetes and asthma. This chapter reviews the vitamin D status during pregnancy across different ethnic groups, looking into the adverse pregnancy and child outcomes, followed by a discussion on the association between maternal and child vitamin D status and successful interventions. Strong evidence exists about the association between vitamin D and some health outcomes during pregnancy, while more studies are needed to confirm the other claim. The existing body of evidence justifies the need for well-designed policies and systematic interventions to ensure optimal vitamin D status of pregnant women and their offsprings across different ethnic and racial groups.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it