Vitamin D Intakes of People Living in Canada: An Assessment Using Disaggregated Population Data from the 2015 Canadian Community Health Survey – Nutrition
Bibliographic record
Abstract
BACKGROUND: The dietary reference intakes for vitamin D were set in support of adequate vitamin D status. In Canada, the prevalence of inadequate vitamin D status is 19% based on biomarker data. OBJECTIVES: The objectives of this study are to assess the adequacy of total usual intakes (UIs) of vitamin D of people living in Canada and explore sociodemographic correlates. METHODS: Vitamin D intake data from the 2015 Canadian Community Health Survey - Nutrition (n = 19,567, ≥1 y) were used. The prevalence of inadequate UI was defined as the percent below the estimated average requirement (% UL). Intakes (% UL was <3%. Total UI of vitamin D in supplement nonusers and users did not vary widely according to sociodemographic factors. Overall, the top 4 food sources of vitamin D were cow's milk and fortified plant-based beverages (FPBBs) combined, margarine, fish, and eggs. CONCLUSIONS: In Canada, the population prevalence of inadequate vitamin D intake is high, although lower among supplement users. Since the time of this survey, dietary guidance advises vitamin D supplementation for people ≥2 y who do not consume a daily food source of vitamin D. Subsequently, the amount of vitamin D in milks, margarines, and FPBB was increased and its addition to yogurts and kefirs was permitted. These strategies may help people living in Canada to achieve adequate intakes of vitamin D.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".