Plasma vitamin D levels and risk of metabolic syndrome in Canadians
Bibliographic record
Abstract
PURPOSE: Vitamin D deficiency has been implicated in susceptibility to the development of metabolic syndrome, obesity and type 2 diabetes mellitus. The present study aimed to quantify the association between vitamin D plasma level, the number of metabolic syndrome components and insulin resistance in Canadians. METHODS: Vitamin D plasma level and clinical data were determined from 1,818 subjects from the Canadian Health Measures Survey; a representative health survey of the general population of Canada conducted from 2007 to 2009. The definition of metabolic syndrome was based on the National Cholesterol Education Program, Adult Treatment Panel III criteria. Adjusted general linear models were used to estimate the association between vitamin D level and probability of having metabolic syndrome, as well as the association between plasma vitamin D and insulin resistance (homeostasis model assessment for insulin resistance, or HOMA-IR). RESULTS: The prevalence of metabolic syndrome in the study population was 8.9%. The number of metabolic syndrome components was inversely correlated with plasma vitamin D level (ρ= -0.1, p < 0.0001). Subjects in the highest vitamin D quartile had lower odds ratio of metabolic syndrome compared with their counterparts in the lowest vitamin D quartile (0.50, 95% CI= 0.24-1.06). Increasing plasma vitamin D level (by 10 nmol/L) was inversely associated with HOMA-IR score (β= -0.08, p=0.006) in a model adjusted for physical activity, smoking status, month of interview, age, sex and ethnicity. CONCLUSION: Vitamin D plasma levels are associated with the occurrence of metabolic syndrome components and insulin resistance among Canadians and are linked to increased level of insulin resistance.
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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 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".