Undernutrition, cognitive decline and dementia: The collaborative PROMED-COG pooled cohorts study
Bibliographic record
Abstract
BACKGROUND & AIMS: Undernutrition may negatively impact cognitive function, but evidence of this relationship is not yet consolidated. Under the "PROtein enriched MEDiterranean diet to combat undernutrition and promote healthy neuroCOGnitive ageing" (PROMED-COG) project, we evaluated the association between undernutrition, and cognitive decline and incident dementia in older adults. METHODS: Retrospective data harmonization was performed on three Italian population-based studies: the Italian Longitudinal Study of Ageing (ILSA), the Progetto Veneto Anziani (Pro.V.A.), and the Bollate Eye Study-Follow-Up (BEST-FU). The associations between undernutrition, operationalized using the Global Leadership Initiative on Malnutrition (GLIM) criteria, and decline on the Mini-Mental State Examination (MMSE) or dementia incidence follow-up were evaluated with Cox proportional hazard regression models. RESULTS: The pooled cohort comprised 9071 individuals (52% females) aged between 42 and 101 years. The prevalence of undernutrition at the baseline was 14.3%, significantly higher among females (15.4% vs 13%) and in older age, ranging from 3.5% in those aged <60 years to 28.8% in those 85+ years. Undernutrition was associated with both cognitive decline over a median 8.3-year follow-up (Hazard Ratio (HR) 1.20, 95% Confidence Interval (CI) 1.02-1.41, p = 0.028) and incidence of dementia over a median 8.6-year follow-up (HR = 1.57, 95%CI 1.01-2.43, p = 0.046). For cognitive decline, the association with undernutrition was more marked in males than females (HR = 1.36, 95%CI 1.05-1.77, p = 0.019 vs HR = 1.10, 95% CI 0.89-1.36, p = 0.375). CONCLUSION: Undernutrition is prevalent among older people and is associated with an increased risk of experiencing cognitive decline and dementia. The prevention and early identification of undernutrition could be an important nonpharmacologic strategy to counteract neurodegeneration.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".