South Asian individuals at high risk of type 2 diabetes have lower plasma vitamin C levels than white Europeans
Bibliographic record
Abstract
Individuals of South Asian origin are at high risk of developing type 2 diabetes; the relationship between this risk and diet remains to be investigated fully. Furthermore, fruit and vegetable intake remains low throughout the world and previous data suggest that intake is associated with risk of diabetes. The aim of this research study was to compare plasma vitamin C concentrations, measured as a biomarker for fruit and vegetable intake, in South Asian and white European individuals. Participants recruited as part of the Let's Prevent Diabetes Study provided samples for the quantification of plasma vitamin C. We compared vitamin C levels by ethnicity using multiple regression, both unadjusted and adjusted for confounders, including glycaemic status. Mean plasma vitamin C was significantly lower in the South Asian participants compared with white European participants (34.5 (sd 19·8) v. 39·9 (sd 22·1) µmol/l, respectively; P ≤ 0·0001). Significantly fewer South Asian individuals consumed five portions of fruit and vegetables per d, as determined by a plasma vitamin C concentration of ≥ 50 µmol/l (23·2 % (n 58) v. 31·4 % (n 558); P = 0·01). Vitamin C reflects habitual fruit and vegetable consumption; thus results suggest that South Asians have lower fruit and vegetable intake. However, it cannot be excluded that vitamin C is utilised differently. Dietary advice specifically targeting the South Asian population should be developed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".