Vitamin C from Foods, but Not Supplements, Is Associated with Increased Cognitive Function in Older Adults
Bibliographic record
Abstract
As adults age there is an increased risk for developing dementia or cognitive impairment. Evidence suggests that there may be a relationship between a healthful diet high in antioxidants and preservation of cognitive function. Common antioxidants obtained from the diet include vitamins C and E, beta‐carotene, and selenium. It is unclear as to whether this relationship exists with antioxidants from foods, supplements, or total intake from foods and supplements. Therefore, the purpose of the present study is to assess average intake of vitamins C and E, beta‐carotene and selenium, from foods, supplements and total intake from foods and supplements, and the relation to Montreal Cognitive Assessment score, total Digit Span score, and Digit Span scaled score. 128 men and women between the ages of 65–80 were involved in a cross‐sectional study. Dietary information was obtained through a Block food frequency questionnaire and cognitive tests were administered by a trained researcher. Bivariate Pearson correlations were run to assess associations among variables. There were no significant associations between intake of any form of beta‐carotene, vitamin E or selenium. Vitamin C intake from foods was positively associated with both total Digit Span score (r=.231; p=.009) and Digit Span scaled score (r=.217; p=.014). In conclusion, findings suggest vitamin C intake from foods, but not supplements or total intake, is associated with increased cognitive function. Further research is needed to investigate the possible protective effects of dietary vitamin C intake in cognitive function.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".