The Relationship between Inflammation, Metabolic Syndrome and Markers of Cardiometabolic Disease among Canadian Adults
Bibliographic record
Abstract
Background: The metabolic syndrome (MetS) is a well-established risk factor for cardiometabolic disease. However, the association between MetS, and its components, with the metabolic phenotypes and inflammatory markers that are risk factor for cardiometabolic disease has not been explored in the general population. The present study examines this association among Canadian adults and explores the changes in the profile of a number of metabolic and inflammatory markers associated with cardiometabolic disease at various MetS stages. Methods: Serum levels of apolipoprotein A1 and B (Apo-A1, -B), total:HDL-cholesterol (HDL-C) ratio, C-reactive protein (CRP), fibrinogen, glycosylated haemoglobin (HbA1c) and homocysteine were determined in 1,818 non-diabetic adults (16-79 years of age) from the Canadian Health Measures Survey (CHMS). The definition of MetS components was based on the National Cholesterol Education Program, Adult Treatment Panel III criteria. Taylor-series expansion methods for complex survey data were used to estimate variances. Generalized linear models adjusted for age, sex, physical activity, smoking status, use of medications and ethnicity were used to quantify the relationship between the metabolic phenotypes and inflammatory markers associated with risk to cardiometabolic disease and the number of MetS components. Results: The prevalence of the MetS (i.e., with three or more MetS components) among the study subjects was 8.9%, with 31.8% having at least one component. As expected, metabolic markers such as total: HDL-C, Apo-B and HbA1c were all significantly increased as the number of MetS components increased whereas Apo-A was decreased. We also observed a significant association between the number of MetS components and the serum levels of inflammatory biomarkers such as CRP and fibrinogen, but not homocysteine. Mean serum levels of these markers were significantly elevated as the numbers of MetS components increased. Strong correlations were noted between CRP, fibrinogen, and homocysteine and the individual components of the MetS. Conclusions: There is an apparent profile of metabolic phenotypes and inflammatory biomarkers, known to be related to the cardiometabolic disease risk, that emerges as MetS manifests with increasing the number of its components. These findings may permit proposing a metabolic trait that predisposes to MetS and may permit developing an effective approach for early risk prediction and intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".