Plasma Vitamin D and Biomarkers of Cardiometabolic Disease Risk in Adult Canadians, 2007–2009
Bibliographic record
Abstract
INTRODUCTION: Vitamin D may modulate cardiometabolic disease risk, although the relationship has not been investigated in the general Canadian population. Understanding this relationship may inform public health strategies to curb the incidence of cardiometabolic disease in Canada and elsewhere. The objectives of this study were to examine the association between vitamin D and traditional and novel biomarkers of cardiometabolic disease and to describe the extent of the month-to-month fluctuations of vitamin D in the Canadian population. METHODS: We examined the association between plasma 25-hydroxyvitamin D and a range of cardiometabolic risk biomarkers in participants (n = 1,928; age range, 16-79 years) from the Canadian Health Measures Survey. We conducted linear regressions analyses (adjusted for sex, waist circumference, physical activity, hormone use, and season) to assess the relationship between 25-hydroxyvitamin D and biomarkers of dysglycemia, dyslipidemia, and inflammation in the study population. We repeated analyses stratified by sex, and we evaluated monthly fluctuations in 25-hydroxyvitamin D in men and women. RESULTS: We observed wide month-to-month variations in 25-hydroxyvitamin D; fluctuations were more pronounced in men. Plasma 25-hydroxyvitamin D was inversely associated with insulin, insulin resistance, triglycerides, total cholesterol, low-density lipoprotein cholesterol, and the ratio of total to high-density lipoprotein cholesterol but not with fasting glucose, apolipoprotein A1, apolipoprotein B, C-reactive protein, fibrinogen, or homocysteine. This pattern varied between men and women. CONCLUSION: Vitamin D may modulate various metabolic processes and may influence cardiometabolic disease risk in Canadians. These findings may have public health implications when recommending vitamin D for the prevention of cardiometabolic disease and related conditions.
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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 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".