Association of Maternal Vitamin D Deficiency with Early Childhood Caries
Bibliographic record
Abstract
Alaska Native (AN) children experience one of the highest reported rates of severe early childhood caries (S-ECC). Serum vitamin D concentrations in AN childbearing women in the Yukon Kuskokwim Delta (YKD) region have decreased since the 1960s to currently low levels, related to a decrease in traditional marine diet. Recent studies suggest an association between prenatal vitamin D (25(OH)D) concentrations in mothers and S-ECC in their infants. We used independent t tests to analyze the influence of prenatal 25(OH)D levels in YKD AN mothers on S-ECC in their children using data collected in the Maternal Organics Monitoring Study (MOMS). Maternal 25(OH)D levels were assessed at prenatal visits and in cord blood. We queried electronic dental records to assess early childhood caries (ECC) status using highest decayed, missing, filled, primary teeth (dmft) scores at 12 to 59 mo of age. We examined prenatal and cord blood for 76 and 57 mother/infant pairs, respectively. Children 12 to 35 mo of age with "deficient" cord blood (25(OH)D <30 nmol/L) had a mean dmft score twice as high as children who were "nondeficient" at birth (9.3 vs. 4.7; P = 0.002). There was no significant difference in mean dmft scores for children aged 36 to 59 mo with deficient versus nondeficient cord blood 25(OH)D (10.9 vs. 8.7 P = 0.14). There was no significant difference in mean dmft scores for children aged 12 to 35 mo whose mothers had "sufficient" versus "insufficient" 25(OH)D during prenatal visits (9.0 vs. 7.4; P = 0.48). In this small sample, children with deficient vitamin D levels in cord blood had a dmft score at 12 to 35 mo 2-fold higher than children with nondeficient cord blood. Maternal 25(OH)D may influence the primary dentition, and improving vitamin D status in pregnant women might affect ECC rates in their infants.
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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 | 0.000 | 0.002 |
| 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".