Supplemental Use of Antioxidant Vitamins and Subsequent Risk of Cognitive Decline and Dementia
Bibliographic record
Abstract
There are conflicting reports about the potential role of vitamin antioxidants in preventing and/or slowing the progression of various forms of cognitive impairment including Alzheimer's disease (AD). We examined longitudinal data from the Canadian Study of Health and Aging, a population-based, prospective 5-year investigation of the epidemiology of dementia among Canadians aged 65+ years. Our primary objective was to examine the association between supplemental use of antioxidant vitamins and subsequent risk of significant cognitive decline (decrease in 3MS score of 10 points or more) among subjects with no evidence of dementia at baseline (n=894). We also explored the relationship between vitamin supplement use and incident vascular cognitive impairment (VCI; including a diagnosis of vascular dementia, possible AD with vascular components and VCI but not dementia), dementia (all cases) and AD. After adjusting for potential confounding factors assessed at baseline, subjects reporting a combined use of vitamin E and C supplements and/or multivitamin consumption at baseline were significantly less likely (adjusted OR 0.51; 95% CI 0.29-0.90) to experience significant cognitive decline during a 5-year follow-up period. Subjects reporting any antioxidant vitamin use at baseline also showed a significantly lower risk for incident VCI (adjusted OR 0.34, 95% CI 0.13-0.89). A reduced risk for incident dementia or AD was not observed. Our findings suggest a possible protective effect for antioxidant vitamins in relation to cognitive decline but randomized controlled trials are required for confirmation.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".