Dietary Inflammatory Index, Erythrocyte Membrane Fatty Acids and Cognitive Function in Obese Chinese Population from 45 to 75 Years: Cross-Sectional and Mediation Analysis
Bibliographic record
Abstract
Abstract Few studies have focused on the connection between dietary inflammatory index (DII) and cognitive function in obese people, despite the fact proved that both obesity and cognitive dysfunction are associated with chronic inflammation. Since DII can reflect the anti-inflammatory or pro-inflammatory potential of the diet, using the normal population as a reference we conducted a study in obese individuals to examine the relationship between DII and several cognitive functions in this population. Additionally, we investigate the mediating elements of this association. Higher DII scores were linked to lower Montreal cognitive assessment (MoCA) total scores, MoCA visuospatial function, MoCA naming, MoCA attention, and MoCA memory in the obese group, according to adjusted linear regression. Taking the tertile of DII score as a categorical variable substituted into a binary linear regression, the negative correlation between DII score and cognitive function score remains, as shown by the increasing incidence of mild cognitive impairment (MCI) as DII increases by one tertile. We discovered chained mediation effects in the mediation analysis between the DII score, erythrocyte membrane fatty acids and the overall MoCA score. We propose that in obese individuals, higher DII scores are linked to a deterioration in cognitive performance. Furthermore, the fatty acids in the erythrocyte membrane may mediate this action.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".