Shellfish-based dietary patterns and cognition in the Chinese senior population: A cross-sectional study in Qingdao, China.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: This study aims to investigate the association between dietary patterns and cognitive function among older adults with lower educational backgrounds living in China. METHODS AND STUDY DESIGN: We analyzed data from the 2018 Health Survey of individuals aged over 50 in Chengyang, Qingdao, China. Questionnaires were used to collect information on the behaviors and lifestyles of the elderly. The Montreal Cognitive Assessment (MoCA) was administered to evaluate cognition, with a total score of less than 19 indicating cognitive impairment for participants with low educational attainment. Using Principal Component Analysis, we identified three dietary patterns: Shellfish, Fruit, and Red Meat. Cross-sectional data regarding dietary intake, cognition, and demographics from 964 participants was analyzed using multivariate regression models to explore the relationship between dietary patterns and cognitive function. RESULTS: Our findings indicated that the 'Shellfish-based' dietary pattern ("Shellfish" DP) was significantly associated with cognitive function in both the third quartile (Q3: Odds Ratio = 0.58, 95% CI: 0.36-0.93, p <0.05) and the fourth quartile (Q4: OR = 0.54, 95% CI: 0.33-0.87, p <0.05). Furthermore, stratified analysis based on specific covariates revealed that significant results among individuals with a BMI of less than 25 kg/m² (OR = 0.57, 95% CI: 0.33-0.99, p <0.05). No significant interaction effects were observed between shellfish dietary intake and various subgroups (all interaction p >0.05). CONCLUSIONS: Our research demonstrates that "Shell-fish" DP is negatively correlated with cognitive decline among the elderly population. This correlation is particularly significant in individuals with BMI < 25kg/m2, as well as among women and under the age of 65. However, no interaction was observed between the shellfish DP and the various subgroups. These findings can effectively guide older adults in optimizing their dietary structures, thereby safeguarding their cognition.
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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 | 0.001 |
| 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".