Seafood Types and Age-Related Cognitive Decline in the Women’s Health Study
Bibliographic record
Abstract
BACKGROUND: Seafood consumption may prevent age-related cognitive decline. However, benefits may vary by nutrient contents in different seafood types. We examined associations between total seafood consumption and cognitive decline and whether these associations differ by seafood types. METHODS: We conducted a prospective cohort study of 5,988 women (mean age, 72 years) from the Women's Health Study who self-reported seafood intake at Women's Health Study baseline and also participated in telephone assessments of general cognition, verbal memory, and category fluency administered 5.6 years after Women's Health Study baseline and 2 and 4 years thereafter. Primary outcomes were standardized composite scores of global cognition and verbal memory. RESULTS: After adjusting for potential confounders, different amounts of total seafood consumption were not associated with changes in global cognition (p = .56) or verbal memory (p = .29). Considering seafood types, however, compared with women consuming less than once-weekly tuna or dark-meat finfish, those with once-weekly or higher consumption had significantly better verbal memory (0.079 standard units; p < .01) after 4 years-a difference comparable to that for women 2.1 years apart in age. There was also a statistically nonsignificant suggestion of better global cognition (p = .13) with once-weekly or higher tuna or dark-meat fish consumption. No significant associations were observed for light-meat finfish or shellfish. CONCLUSIONS: The relation of seafood to cognition may depend on the types consumed. Total consumption levels of seafood were unrelated to cognitive change. However, consumption of tuna and dark-meat fish once weekly or higher was associated with lower decline in verbal memory for a period of 4 years.
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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) | 0.001 | 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".