Dairy Product Consumption and Changes in Cognitive Performance: Two‐Year Analysis of the PREDIMED‐Plus Cohort
Bibliographic record
Abstract
SCOPE: Dairy consumption has been suggested to impact cognition; however, evidence is limited and inconsistent. This study aims to longitudinally assess the association between dairy consumption with cognitive changes in an older Spanish population at high cardiovascular disease risk. METHODS AND RESULTS: Four thousand six hundred sixty eight participants aged 55-75 years, completed a validated food frequency questionnaire at baseline and a neuropsychological battery of tests at baseline and 2-year follow-up. Multivariable linear regression models are used, scaled by 100 (i.e., the units of β correspond to 1 SD/100), to assess associations between baseline tertile daily consumption and 2-year changes in cognitive performance. Participants in the highest tertile of total milk and whole-fat milk consumption have a greater decline in global cognitive function (β: -4.71, 95% CI: -8.74 to -0.69, p-trend = 0.020 and β: -6.64, 95% CI: -10.81 to -2.47, p-trend = 0.002, respectively) compared to those in the lowest tertile. No associations are observed between low fat milk, yogurt, cheese or fermented dairy consumption, and changes in cognitive performance. CONCLUSION: Results suggest there are no clear prospective associations between consumption of most commonly consumed dairy products and cognition, although there may be an association with a greater rate of cognitive decline over a 2-year period in older adults at high cardiovascular disease risk for whole-fat milk.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".