Maternal vitamin D status during pregnancy is associated with infant anthropometry during the first year of life (267.1)
Bibliographic record
Abstract
Maternal vitamin D deficiency during pregnancy has been linked to fetal growth and may also impact child growth in infancy. We used data and blood samples from the 12‐site U.S. Collaborative Perinatal Project (1959‐65) to examine the association of maternal vitamin D status during pregnancy and infant anthropometry across the first year of life in singletons (n=2473 mother‐child pairs). Maternal serum 25‐hydroxyvitamin D (25(OH)D) was measured at 蠄26 weeks gestation using chromatography‐tandem mass spectrometry. Infant anthropometry was expressed as z‐scores for length (LAZ), head circumference (HC‐Z), weight (WAZ), and BMI (BMI‐Z) based on measures at birth and 4, 8 and 12 months of age. We controlled for study site, and important infant and maternal characteristics in linear mixed effects models. 25(OH)D <30 nmol/L (conventional definition of deficiency) vs. 蠅30 nmol/L was associated with LAZ and HC‐Z measures that were 0.13 (95% CI: 0.03‐0.23) and 0.20 (95% CI: 0.11‐0.28) lower, respectively, across the first year of life. Differences observed by 25(OH)D in WAZ and BMI‐Z at birth resolved by 4 months of age, potentially reflecting catch‐up growth. These findings suggest that maternal vitamin D deficiency has a sustained association with markers of linear or skeletal growth during the first year of life, while initial associations with measures of weight and body composition may resolve. Grant Funding Source : Supported by R01 HD 056999
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".