Vitamin D deficiency and whole-body and femur bone mass relative to weight in healthy newborns
Bibliographic record
Abstract
BACKGROUND: Vitamin D is required for normal bone growth and mineralization. We sought to determine whether vitamin D deficiency at birth is associated with bone mineral content (BMC) of Canadian infants. METHODS: We measured plasma 25-hydroxyvitamin D [25(OH)D] as an indicator of vitamin D status in 50 healthy mothers and their newborn term infants. In the infants, anthropometry and lumbar, femur and whole-body BMC were measured within 15 days of delivery. Mothers completed a 24-hour recall and 3-day food and supplement record. We categorized the vitamin D status of mothers and infants as deficient or adequate and then compared infant bone mass in these groups using nonpaired t tests. Maternal and infant variables known to be related to bone mass were tested for their relation to BMC using backward stepwise regression analysis. RESULTS: Twenty-three (46%) of the mothers and 18 (36%) of the infants had a plasma 25(OH)D concentration consistent with deficiency. Infants who were vitamin D deficient were larger at birth and follow-up. Absolute lumbar spine, femur and whole-body BMC were not different between infants with adequate vitamin D and those who were deficient, despite larger body size in the latter group. In the regression analysis, higher whole-body BMC was associated with greater gestational age and weight at birth as well as higher infant plasma 25(OH)D. CONCLUSION: A high rate of vitamin D deficiency was observed among women and their newborn infants. Among infants, vitamin D deficiency was associated with greater weight and length but lower bone mass relative to body weight. Whether a return to normal vitamin D status, achieved through supplements or fortified infant formula, can reset the trajectory for acquisition of BMC requires investigation.
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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 | 0.000 |
| 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) | 0.001 | 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".