Original Communication Wintertime vitamin D insufficiency is common in young Canadian women, and their vitamin D intake does not prevent it
Bibliographic record
Abstract
Objective: We asked whether women self-reporting the recommended consumption of vitamin D from milk and multivitamins would be less likely to have low wintertime 25-hydroxyvitamin D (25(OH)D) levels. Methods: This cross-sectional study enlisted at least 42 young women each month (age 18 – 35 y, 796 women total) through one year. We measured serum 25(OH)D and administered a lifestyle and diet questionnaire. Results: Over the whole year, prevalence of low 25(OH)D ( < 40 nmol=l) was higher in non-white, non-black subjects (25.6% of 82 women) than in the white women (14.8% of 702 white women, P < 0.05). Of the 435 women tested during the winter half of the year (November – April), prevalence of low 25(OH)D was not affected by vitamin D intake: low 25(OH)D occurred in 21% of the 146 consuming no vitamin D, in 26% of the 140 reporting some vitamin D intake, up to 5mg=day (median, 2.5mg=day), and in 20% of the 149 women reporting vitamin D consumption over 5mg=day (median, 10mg=day). Interpretation: The self-reported vitamin D intake from milk and=or multivitamins does not relate to prevention of low vitamin D nutritional status of young women in winter. Recommended vitamin D intakes are too small to prevent insufficiency. Vitamin D nutrition can only be assessed by measuring serum 25(OH)D concentration. Descriptors: cholecalciferol; dietary intake; RDA; AI; osteoporosis; deficiency
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".