Association of vegetarian diet with inflammatory biomarkers: a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
OBJECTIVE: Vegetarian diets contain various anti-inflammatory components. We aimed to investigate the effects of vegetarianism on inflammatory biomarkers when compared with omnivores. DESIGN: Systematic review and meta-analysis. SETTING: Literature search was conducted in Science Direct, Proquest, MEDLINE and Google Scholar up to June 2016. Summary estimates and corresponding 95 % CI were derived via the DerSimonian and Laird method using random effects, subgroup analyses were run to find the source of heterogeneity and a fixed-effect model examined between-subgroup heterogeneity. SUBJECTS: Studies were included if they evaluated effects of any type of vegetarianism compared with omnivores on circulating levels of inflammatory biomarkers. No restriction was made in terms of language or the date of study publications. RESULTS: Eighteen articles were included. Pooled effect size showed no difference in high-sensitivity C-reactive protein (hs-CRP) levels in vegetarians v. omnivores (Hedges' g=-0·15; 95 % CI -0·35, 0·05), with high heterogeneity (I 2=75·6 %, P<0·01). A subgroup analysis by minimum duration of vegetarianism showed that a minimum duration of 2 years vegetarianism was associated with lower hs-CRP levels v. omnivores (Hedges' g=-0·29; 95 % CI -0·59, 0·01), with moderate heterogeneity (I 2=68·9 %, P<0·01). No significant effect was found in studies using a minimum duration of 6 months of vegetarianism, with low heterogeneity. Vegetarianism was associated with increased IL-6 concentrations (0·21 pg/ml; 95 % CI 0·18, 0·25), with no heterogeneity (I 2=0·0 %, P=0·60). CONCLUSIONS: The meta-analysis provides evidence that vegetarianism is associated with lower serum concentrations of hs-CRP when individuals follow a vegetarian diet for at least 2 years. Further research is necessary to draw appropriate conclusions regarding potential associations between vegetarianism and IL-6 levels. A vegetarian diet might be a useful approach to manage inflammaging in the long term.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.033 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".