Longitudinal changes in calcium and vitamin D intakes and relationship to bone mineral density in a prospective population-based study: the Canadian Multicentre Osteoporosis Study (CaMos).
Bibliographic record
Abstract
OBJECTIVES: Our objective was to study changes in calcium and vitamin D intakes over time, and their cross-sectional and longitudinal associations with bone mineral density (BMD). METHODS: We followed 9382 women and men aged ≥25 and 899 aged 16-24, for 10 and 2 years respectively. RESULTS: Calcium and vitamin D intakes increased over time in adults, but decreased in women aged 16-18. The increased intakes in adults were largely attributable to the increased use of calcium and/or vitamin D supplements. Both the percentage of supplement users and average dose among users increased over time. There was nevertheless a high prevalence of calcium and vitamin D intake below the estimated average requirement. At baseline, higher calcium and vitamin D intakes were associated with higher total hip and femoral neck BMD in young men, and cumulatively high levels of calcium and vitamin D intakes over time contributed to better BMD maintenance at lumbar spine and hip sites in adult women. CONCLUSIONS: Although total intakes, particularly of vitamin D, frequently fell below the Institute of Medicine recommendations despite an increase over time in supplement use, we found some positive associations between total calcium and vitamin D intake and bone health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".