Dietary Antioxidant Intake and Its Association With Cognitive Function in an Ethnically Diverse Sample of US Adults
Bibliographic record
Abstract
BACKGROUND: Dietary antioxidants can inhibit reactions accompanying neurodegeneration and thus prevent cognitive impairment. We describe associations of dietary antioxidants with cognitive function in a large biracial population, while testing moderation by sex, race, and age and mediation by depressive symptoms. METHODS: This was a cross-sectional analysis of 1274 adults (541 men and 733 women) aged 30 to 64 years at baseline (mean [standard deviation] = 47.5 [9.3]) in the Healthy Aging in Neighborhoods of Diversity Across the Lifespan Study, Baltimore city, MD. Cognitive performance in the domains of memory, language/verbal, attention, spatial, psychomotor speed, executive function, and global mental status were assessed. The 20-item Center for Epidemiologic Studies Depression Scale was used to measure depressive symptoms. Dietary intake was assessed with two 24-hour recalls, estimating daily consumption of total carotenoids and vitamins A, C, and E per 1000 kcal. RESULTS: Among key findings, 1 standard deviation (∼ 2.02 mg/1000 kcal) higher vitamin E was associated with a higher score on verbal memory, immediate recall (β = +0.64 [0.19], p = .001), and better language/verbal fluency performance (β = +0.53 [0.16], p = .001), particularly among the younger age group. Women with higher vitamin E intake (β = +0.68 [0.21], p = .001) had better performance on a psychomotor speed test. The vitamin E-verbal memory association was partially mediated by depressive symptoms (proportion mediated = 13%-16%). CONCLUSIONS: In sum, future cohort studies and dietary interventions should focus on associations of dietary vitamin E with cognitive decline, specifically for domains of verbal memory, verbal fluency, and psychomotor speed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".