Vitamin D3 Supplementation in Overweight/Obese Pregnant Women: No Effects on the Maternal or Fetal Lipid Profile and Body Fat Distribution—A Secondary Analysis of the Multicentric, Randomized, Controlled Vitamin D and Lifestyle for Gestational Diabetes Prevention Trial (DALI)
Bibliographic record
Abstract
Vitamin D deficiency is a common finding in overweight/obese pregnant women and is associated with increased risk for adverse pregnancy outcome. Both maternal vitamin D deficiency and maternal obesity contribute to metabolic derangements in pregnancy. We aimed to assess the effects of vitamin D3 supplementation in pregnancy versus placebo on maternal and fetal lipids. Main inclusion criteria were: women <20 weeks’ gestation, BMI ≥ 29 kg/m2. Eligible women (n = 154) were randomized to receive vitamin D3 (1600 IU/day) or placebo. Assessments were performed <20, 24−28 and 35−37 weeks and at birth. Linear regression models were used to assess effects of vitamin D on maternal and cord blood lipids. In the vitamin D group significantly higher total 25-OHD and 25-OHD3 levels were found in maternal and cord blood compared with placebo. Adjusted regression models did not reveal any differences in triglycerides, LDL-C, HDL-C, free fatty acids, ketone bodies or leptin between groups. Neonatal sum of skinfolds was comparable between the two groups, but correlated positively with cord blood 25-OH-D3 (r = 0.34, p = 0.012). Vitamin D supplementation in pregnancy increases maternal and cord blood vitamin D significantly resulting in high rates of vitamin D sufficiency. Maternal and cord blood lipid parameters were unaffected by Vitamin D3 supplementation.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".