Mediterranean diet and plasma concentration of inflammatory markers in old and very old subjects in the ZINCAGE population study
Bibliographic record
Abstract
BACKGROUND: Aging is associated with low-grade elevation of circulating inflammatory markers, leading to increased risk of morbidity and mortality. The Mediterranean diet has been suggested as a determinant of longevity. In the current study, we investigated the impact of the Mediterranean diet on inflammatory status in old subjects. METHODS: Within the ZINCAGE study, 957 healthy old subjects (>or=60 years old) from five European countries were recruited. Plasma interleukin (IL)-6, IL-8, monocyte chemoattractant protein, tumor necrosis factor-alpha, high-density lipoprotein cholesterol (HDL-C) and erythrocyte sedimentation rate (ESR) were measured. Dietary data were collected applying a food frequency questionnaire and were used to estimate adherence to the Mediterranean diet. RESULTS: The Italians presented the greatest adherence to the Mediterranean diet, while the Polish the poorest. In females, higher diet score was significantly associated with lower body mass index and ESR and higher HDL-C levels (beta=-0.127, p=0.003; beta=-0.144, p=0.001; beta=0.144, p=0.029, respectively). In males, diet score was negatively associated with IL-8 levels (beta=-0.101, p=0.044). The Mediterranean diet was associated with reduced IL-8 concentrations in Greeks (beta=-0.213, p=0.007). CONCLUSIONS: There were significant effects of the components of the Mediterranean diet on inflammation markers. The Mediterranean diet score is useful in assessing nutritional influence on immune status.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".