The relationship between micronutrients and cognitive ability in an elderly population with mild cognitive impairment and Alzheimer’s disease: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Mild cognitive impairment (MCI) and Alzheimer's disease (AD) are significant neurodegenerative disorders with increasing prevalence worldwide. Lifestyle and dietary factors, including micronutrients, have been suggested as modifiable risk factors for disease development. This study aims to investigate the association between micronutrients and cognitive ability in these diseases. METHODS: A cross-sectional study involving 105 participants with MCI and AD was conducted. Dietary assessments were performed using a validated food frequency questionnaire (FFQ), and micronutrient intake was calculated based on nutrient content. Disease severity was evaluated using the Functional Assessment Staging Tool (FAST). Statistical analyses, including correlation coefficients and multiple regression models, were employed to examine the association between micronutrients and disease progression. RESULTS: The results revealed significant correlations between disease severity and several micronutrients, including omega-3 fatty acids (B = -0.2, P = 0.01), carotenoids (B = -0.19, P = 0.02), dietary antioxidant compounds, including vitamins A, C, D, E (B = -0.19, P = 0.02), selenium (B = -0.17, P = 0.03), alpha-carotene (B = -0.16, P = 0.04), beta-carotene (B = -0.17, P = 0.03), and lycopene (B = -0.16, P = 0.04). Multivariate regression analysis showed that higher intake of omega-3 fatty acids was associated with slower disease progression. Furthermore, the levels of these micronutrients declined in advanced stages of the disease. CONCLUSION: Omega-3 fatty acids and carotenoids may affect the cognitive ability and disease progression. Further longitudinal studies are warranted to establish causality and explore the therapeutic implications of these findings for the prevention and management of MCI and AD.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".