Season, adiposity, and baseline 25‐hydroxyvitamin D are predictors of maternal change in vitamin D status from 1 to 4 months postpartum
Bibliographic record
Abstract
There is limited information on the vitamin D status of lactating women and the potential known predictors that contribute to vitamin D status during lactation. The objectives of this study were to determine vitamin D status of lactating women and identify key predictors of vitamin D status at 4 mo and change since 1 mo postpartum. Healthy, lactating mothers (n=44) in Montreal were recruited between May 2010 to April 2011. Fasted venous blood samples were collected at 1 and 4 mo postpartum for analyses of plasma 25‐hydroxyvitamin D (25(OH)D) by LIAISON® (Diasorin). Demographics, sun exposure, skin pigmentation, anthropometry, body composition, supplement use, and nutrition information were collected to identify predictors of 25(OH)D. From 1 to 4 mo postpartum, there was a significant decrease in 25(OH)D from 73.0 ± 21.6 nmol/L to 62.4 ± 18.3 nmol/L (p<0.001). At 1 mo, 7 (15.9%) mothers had 25(OH)D <50 nmol/L and 26 (59.1%) had 25(OH)D <75 nmol/L. At 4 mo, 9 (21.4%) mothers had 25(OH)D <50 nmol/L and 30 (71.4%) had 25(OH)D <75 nmol/L. Predictors of vitamin D status at 4 mo postpartum included weeks in the synthesizing period, vitamin D intake, and % change in body fat and predictors of change in 25(OH)D included baseline 25(OH)D, weeks in the synthesizing period, and % change in weight. These predictors are important to consider to prevent declines in vitamin D status during lactation. (Supported by CFDR).
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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 | 0.000 | 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) | 0.002 | 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".