The Association Between Dietary Fat Intake and Mild Cognitive Impairment in Japanese Men and Women: The Toon Health Study
Bibliographic record
Abstract
Previous studies have shown that dietary fatty acid intake is associated with the risk of developing dementia. However, its association with mild cognitive impairment (MCI) remains controversial. Therefore, we aimed to examine the association between dietary fatty acid intake and MCI in an older Japanese population. We included 1144 participants aged 60 or older who participated in the Toon Health Study in 2014–2018 in the analysis. Dietary fatty acid intake was estimated using food frequency questionnaires (FFQs). MCI was assessed using the Montreal Cognitive Assessment in Japanese (MoCA-J) and defined as an MoCA-J score below 26. The multivariable-adjusted odds ratio (OR) and 95% confidence interval (CI) were calculated using logistic regression. We determined that 430 of the participants had MCI. Intake levels of polyunsaturated fatty acids (PUFAs), n-3 and n-6, fatty acids, and saturated fatty acid/PUFA ratio (SFA/PUFA) were not significantly associated with MCI. The multivariable-adjusted ORs (95%CI) for MCI in the highest quartile of PUFA, n-3 and n-6 fatty acid, and SFA/PUFA intake were 0.79 (0.55, 1.14, p for trend = 0.29), 0.96 (0.59, 1.54, p for trend = 0.85), 0.81 (0.56, 1.16, p for trend = 0.34), and 0.85 (0.59 1.22, p for trend = 0.24) compared with the lowest quartiles, respectively. SFA was significantly associated with lower odds of developing MCI. The multivariable-adjusted OR (95%CI) for MCI in the highest quartile of SFA intake compared with the lowest quartile was 0.63 (0.43, 0.93, p for trend = 0.03). Conclusions: SFA intake was inversely associated with MCI, while intake of PUFAs, including n-3 and n-6 fatty acids, was not associated with MCI. Further investigation is required to clarify these associations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".