Relationship between insulin resistance and plasma vitamin D in adults
Bibliographic record
Abstract
Alaa Badawi,1 Suzan Sayegh,2 Eman Sadoun,3 Mohamed Al-Thani,2 Paul Arora,4 Pierre S Haddad51Office of Biotechnology, Genomics and Population Health, Public Health Agency of Canada, Toronto, ON, Canada; 2Department of Public Health, 3Clinical Research Division, Supreme Council of Health, Doha, Qatar; 4Dalla Lana School of Public Health, University of Toronto, ON, Canada; 5Department of Pharmacology, Faculty of Medicine, University of Montreal, Montreal, QC, CanadaAbstract: A recent relationship between vitamin D deficiency and the risk of type 2 diabetes mellitus (T2DM) and insulin resistance has been established through several studies. Research suggests a correlation between serum vitamin D and glycemic status measures. The aim of this study was to investigate the relationship between the plasma vitamin D levels (25[OH]D) and the factors linked to insulin resistance in a representative sample of Canadians ranging in age from 16–79 years. Data were used from the Canadian Health Measures Survey where direct measures of health and wellness were reported from 1,928 subjects. These data were gathered from March 2007–February 2009 at 15 sites selected through a multistage sampling strategy. An inverse relationship between insulin resistance and plasma vitamin D level in both men and women was observed. This study provides additional evidence for the role of vitamin D in T2DM. If causally associated, the supplementation of vitamin D may help in preventing insulin resistance and subsequent T2DM.Keywords: HOMA-IR, plasma 25(OH)D, diabetes
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".