Effect of Nutrients, Dietary Supplements and Vitamins on Cognition: a Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Observational studies have suggested that various nutrients, dietary supplements, and vitamins may delay the onset of age-associated cognitive decline and dementia. We systematically reviewed recent randomized controlled trials investigating the effect of nutritional interventions on cognitive performance in older non-demented adults. METHODS: We searched MEDLINE, CINAHL, Embase, and the Cochrane Library for articles published between 2003 and 2013. We included randomized trials of ≥ 3 months' duration that examined the cognitive effects of a nutritional intervention in non-demented adults > 40 years of age. Meta-analyses were done when sufficient trials were available. RESULTS: Twenty-four trials met inclusion criteria (six omega-3 fatty acids, seven B vitamins, three vitamin E, eight other interventions). In the meta-analyses, omega-3 fatty acids showed no significant effect on Mini-Mental State Examination (MMSE) scores (four trials, mean difference 0.06, 95% CI -0.08 - 0.19) or digit span forward (three trials, mean difference -0.02, 95% CI -0.30 - 0.25), while B vitamins showed no significant effect on MMSE scores (three trials, mean difference 0.02, 95% CI -0.22 - 0.25). None of the vitamin E studies reported significant effects on cognitive outcomes. Among the other nutritional interventions, statistically significant differences between the intervention and control groups on at least one cognitive domain were found in single studies of green tea extract, Concord grape juice, chromium picolinate, beta-carotene, two different combinations of multiple vitamins, and a dietary approach developed for the control of hypertension. CONCLUSIONS: Omega-3 fatty acids, B vitamins, and vitamin E supplementation did not affect cognition in non-demented middle-aged and older adults. Other nutritional interventions require further evaluation before their use can be advocated for the prevention of age-associated cognitive decline and dementia.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".