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Metabolic syndrome and inflammatory biomarkers: a community-based cross-sectional study at the Framingham Heart Study

Dhayana Dallmeier12, Martin G Larson258, Ramachandran S Vasan234, John F Keaney9, Joao D Fontes23, James B Meigs7, Caroline S Fox102 and Emelia J Benjamin236*

Author Affiliations

1 General Internal Medicine Division, Boston University School of Medicine, Boston, USA

2 National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, USA

3 Cardiology, Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, USA

4 Preventive Medicine Divisions, Whitaker Cardiovascular Institute, Boston University School of Medicine, Boston, USA

5 Biostatistics Department, Boston University School of Public Health, Boston, USA

6 Epidemiology Department, Boston University School of Public Health, Boston, USA

7 Department of Medicine, Harvard Medical School, Boston, USA

8 Department of Mathematics and Statistics, Boston University, Boston, USA

9 Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, USA

10 Department of Endocrinology, Diabetes, and Metabolism, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA

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Diabetology & Metabolic Syndrome 2012, 4:28  doi:10.1186/1758-5996-4-28

Published: 20 June 2012

Abstract

Background

Prior studies reported conflicting findings on the association between metabolic syndrome and inflammatory biomarkers. We tested the cross-sectional associations between metabolic syndrome and nine inflammatory markers.

Methods

We measured C-reactive protein, CD40 ligand, interleukin-6, intercellular adhesion molecule-1, monocyte chemoattractant protein-1, osteoprotegerin, P-selectin, tumor necrosis factor-alpha, and tumor necrosis factor receptor-2 in 2570 Framingham Offspring Study participants free of diabetes and cardiovascular disease at examination 7. Metabolic syndrome was defined by National Cholesterol Education Program criteria. We performed multivariable linear regressions for each biomarker with metabolic syndrome as the exposure adjusting for age, sex, smoking, aspirin use, and hormone replacement. We subsequently added to the models components of the metabolic syndrome as continuous traits plus lipid lowering and hypertension treatments. We considered P < 0.05 as statistically significant.

Results

Metabolic syndrome was present in 984 (38%) participants and was statistically significantly associated with each biomarker (all P < 0.02) except osteoprotegerin. After adjusting for its component variables, the metabolic syndrome was associated only with P-selectin (1.06 fold higher in metabolic syndrome, 95% CI 1.02, 1.10, p = 0.005).

Conclusions

Metabolic syndrome was associated with multiple inflammatory biomarkers. However, adjusting for each of its components eliminated the association with most inflammatory markers, except P-selectin. Our results suggest that the relation between metabolic syndrome and inflammation is largely accounted for by its components.

Keywords:
Metabolic syndrome; Inflammatory biomarkers; Body mass index; Insulin resistance