Yogurt intake is associated with a healthier dietary pattern and is a lower contributor of energy intake in obese individuals (1018.6)
Bibliographic record
Abstract
Objectives: To examine whether yogurt consumption is associated with Prudent or Western dietary patterns and to study associations between total, fat‐free, low‐fat (2% M.F.) yogurt intake and obesity. Methods: A 91‐items food frequency questionnaire was administered to 664 subjects from the INFOGENE study. Obesity was defined as having a body mass index > 30kg/m². A total of 564 subjects (160 obese and 404 non‐obese individuals) consumed yogurt and were then classified as “consumers”. Results: Yogurt consumption (daily servings) was positively associated to the Prudent dietary pattern (r=0.15, p=0.0001) and inversely associated to the Western dietary pattern (r=‐0.22, p<0.0001). In yogurt consumers, yogurt contributed to a lesser extent to daily energy intake in obese than in non‐obese individuals (% of total energy, 2.92±2.53% vs. 3.54±2.49% respectively, p=0.02). In addition, non‐obese subjects reported more daily servings of high‐fat yogurt compared to obese individuals (0.18±0.40 vs. 0.10±0.23, p=0.03). Conclusions: This study shows that yogurt consumption is associated with a healthier dietary pattern. Moreover, the contribution of yogurt to daily energy intake is more pronounced in non‐obese individuals. Grant Funding Source : Danone Nutricia Research, Centre Daniel Carasso
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".