Obesity and <scp>C</scp>‐reactive protein in various populations: a systematic review and meta‐analysis
Bibliographic record
Abstract
Obesity has been associated with elevated levels of C-reactive protein (CRP), a marker of inflammation and predictor of cardiovascular risk. The objective of this systematic review and meta-analysis was to estimate the associations between obesity and CRP according to sex, ethnicity and age. MEDLINE and EMBASE databases were searched through October 2011. Data from 51 cross-sectional studies that used body mass index (BMI), waist circumference (WC) or waist-to-hip ratio (WHR) as measure of obesity were independently extracted by two reviewers and aggregated using random-effects models. The Pearson correlation (r) for BMI and ln(CRP) was 0.36 (95% confidence interval [CI], 0.30-0.42) in adults and 0.37 (CI, 0.31-0.43) in children. In adults, r for BMI and ln(CRP) was greater in women than men by 0.24 (CI, 0.09-0.37), and greater in North Americans/Europeans than Asians by 0.15 (CI, 0-0.28), on average. In North American/European children, the sex difference in r for BMI and ln(CRP) was 0.01 (CI, -0.08 to 0.06). Although limited to anthropometric measures, we found similar results when WC and WHR were used in the analyses. Obesity is associated with elevated levels of CRP and the association is stronger in women and North Americans/Europeans. The sex difference only emerges in adulthood.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".