Cord Blood Vitamin D Status Is Associated With Cord Blood Insulin and C-Peptide in Two Cohorts of Mother-Newborn Pairs
Bibliographic record
Abstract
CONTEXT: Vitamin D may be important for prenatal programming of insulin and glucose regulation, but maternal vitamin D deficiency during pregnancy is common. OBJECTIVE: We examined associations of early vitamin D status with markers of fetal insulin secretion: cord blood insulin and c-peptide. We hypothesized that maternal 25-hydroxyvitamin D (25(OH)D) during pregnancy and cord blood 25(OH)D would both be positively associated with cord blood insulin and c-peptide. METHODS: We studied mother-newborn pairs from two cohorts: Project Viva (n = 862 pairs included) and Genetics of Glucose Regulation in Gestation and Growth (Gen3G; n = 660 pairs included). We analyzed associations of the cord blood hormones with maternal 25(OH)D using generalized additive models with nonlinear spline terms, and with cord blood 25(OH)D using multivariable linear regression models. RESULTS: The 25(OH)D levels were <75 nmol/L in >70% of mothers and 85% of newborns. Maternal and cord blood 25(OH)D levels were correlated (Project Viva, r = 0.58; Gen3G, r = 0.37). Maternal 25(OH)D had an inverted-U-shaped relationship with cord blood insulin and c-peptide in both cohorts. Cord blood 25(OH)D had a linear relationship with the cord blood hormones. In fully adjusted models, each 10-nmol/L increase in cord blood 25(OH)D was associated with higher cord blood insulin and c-peptide concentrations: 3.7% (95% CI, 0.09 to 7.5) and 3.2% (95% CI, 0.8 to 5.6), respectively, in Project Viva; 2.2% (95% CI, -0.1 to 4.6) and 3.6% (95% CI, 1.0 to 6.3), respectively, in Gen3G. CONCLUSION: Vitamin D may play a role in regulating fetal insulin secretion, potentially affecting glucose regulation and growth.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".