The Journal of Nutrition Nutrient Requirements and Optimal Nutrition Vitamin D Supplement Consumption Is Required to Achieve a Minimal Target 25-Hydroxyvitamin D Concentration of $75 nmol/L in Older People1,2
Bibliographic record
Abstract
Population level data on how older individuals living at high latitudes achieve optimal vitamin D status are not fully explored. Our objective was to examine the intake of vitamin D among healthy older individuals with 25-hydroxyvitamin D [25(OH)D] concentrations$75 nmol/L and to describe current sources of dietary vitamin D.We conducted a population-based, cross-sectional study of 404 healthy men and women aged 69 to 83 y randomly selected from the NuAge longitudinal study in Québec, Canada. Dietary intakes were assessed by 6 24-h recalls. We examined the contribution of foods and vitamin/ mineral supplements to vitamin D intake. Serum 25(OH)D was assessed by RIA. We assessed smoking status, season of 25(OH)D measurement, physical activity, and anthropometric and sociodemographic variables. Vitamin D status was distributed as follows: 7 % (,37.5 nmol/L), 48 % (37.5–74.9 nmol/L), and 45 % ($75 nmol/L). Vitamin D intake from supplements varied across the 3 vitamin D status groups: 0.5, 4.1, and 8.9 mg/d, respectively (P, 0.0001). Adding food sources, these total intakes were 4.6, 8.7, and 14.1 mg/d, respectively. In multivariate analysis, vitamin D from foods and supplements and by season was associated with vitamin D status. These healthy, community-dwelling older men and women with 25(OH)D concentrations.75 nmol/L had mean intakes of 14.1 mg/d from food and supplements. Supplement use is an important contributor to achieve a minimal target of 25(OH)D concentration $75 nmol/L. J. Nutr. 140: 551–556, 2010.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".