Dietary patterns: a novel approach to examine the link between nutrition and cognitive function in older individuals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cognitive decline may lead to dementia whose most frequent cause is Alzheimer's disease (AD). Among the many potential risk factors of cognitive decline and AD, diet raises increasing interest. Most studies considered diet in the frame of a single nutrient approach with inconsistent results. A novel approach to examine the link between nutrition and cognitive function is the use of dietary patterns. The aim of the present review was to update and complete the body of knowledge about dietary patterns in relationship with various cognitive outcomes in the elderly. Two approaches can be used: a priori and a posteriori patterns. A priori patterns are defined by the adhesion to a pre-defined healthy diet using a score such as the Mediterranean diet (MeDi) score, the Healthy Eating Index, the Canadian Healthy Eating Index, the French National Nutrition and Health Programme (Programme National Nutrition Santé) Guideline Score (PNNS-GS), the Recommended Food Score (RFS) and Dietary Approaches to Stop Hypertension (DASH). MeDi score, RFS, PNNS-GS and DASH have been associated with lower risks of cognitive impairment, cognitive decline, and dementia or AD. Principal components analysis, reduced rank regression and clustering methods allow the identification of 'healthy' patterns associated with lower risk of cognitive decline. However, some studies did not report any associations with cognitive outcomes and results are discordant especially regarding MeDi and the risk of dementia. Several methodological challenges should be overcome to provide a higher level of evidence supporting the development of nutritional policies to prevent cognitive decline and AD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it