Associations between dairy intake and metabolic risk parameters in a healthy French-Canadian population
Bibliographic record
Abstract
Observational studies support that dairy product intake is associated with a reduced risk of developing type 2 diabetes; however, several clinical studies report conflicting results on the association between dairy product consumption and metabolic parameters. The aim of this study was to determine associations between dairy product consumption and metabolic profile. Dietary data, using a validated food frequency questionnaire, and fasting blood samples were collected from 233 French Canadians. Plasma phospholipid (PL) fatty acids (FA) concentrations were determined by gas chromatography. Subjects consumed 2.5 ± 1.4 portions of dairy products daily, including 1.6 ± 1.3 portions of low-fat (LF) and 0.90 ± 0.70 portions of high-fat (HF) dairy products. Trans-palmitoleic acid level in plasma PL was related to HF dairy consumption (r = 0.15; p = 0.04). Total (r = -0.21; p = 0.001) and LF dairy (r = -0.20; p = 0.003) intakes were inversely correlated with fasting plasma glucose level. Total dairy intake was inversely associated to systolic blood pressure (r = -0.17; p = 0.008) and diastolic blood pressure (r = -0.14; p = 0.03). LF dairy intake was also inversely correlated with systolic blood pressure (r = -0.17; p = 0.009). Total dairy intake was correlated with plasma C-reactive protein (CRP) (r = 0.15; p = 0.03). No association was found between HF dairy consumption and the risk factors studied. In conclusion, dairy intake is inversely associated with glycaemia and blood pressure; yet, it may modify CRP levels. Moreover, trans-palmitoleic FA levels in plasma PL may be potentially used to assess full-fat dairy consumption.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".