Utility of the metabolic syndrome and its components in the prediction of incident cardiovascular disease: a prospective cohort study
Received 2 October 2008; accepted 14 January 2009.
Background
To investigate the prognostic importance of the metabolic syndrome (MetS) on incident cardiovascular disease (CVD).
Design
Prospective cohort study.
Methods
The study was based on 10-year follow-up of 3041 men and women aged 25–84 years without CVD or diabetes who participated in the 1994/1995 Busselton Health Survey. Hazards ratio (HRs) from Cox regression models were used to describe the effect of the MetS as a dichotomous classification and as the number of risk components on incident coronary heart disease (CHD), stroke and all CVD events.
Results
All cardiovascular and metabolic risk factors studied showed a strong association with the number of MetS risk components. The age-adjusted and sex-adjusted HR for the MetS was 1.70 (95% confidence interval: 1.15–2.51) for incident CHD but this was reduced to almost unity after adjustment for cardiovascular risk factors or the homoeostasis model assessment measure of insulin resistance. However, the number of MetS risk components remained significant (P<0.01) with those having 3+ risk components with a three-fold increase in risk compared with those with no risk components (adjusted HR: 3.59, 95% confidence interval: 1.43–8.99).
Conclusion
Consideration of the number of MetS risk components seems to be more informative than the (dichotomous) MetS classification when determining risk in clinical practice. Identification of people without any MetS risk components is clinically valuable, as these people seem to have a substantially reduced risk of developing CHD.
bSchool of Medicine and Pharmacology, Sir Charles Gairdner Hospital Unit
cSchool of Medicine and Pharmacology, Fremantle Hospital Unit
dClinical Biochemistry PathWest and School of Surgery and Pathology, University of Western Australia, Nedlands, Western Australia, Australia
Correspondence to Professor Matthew Knuiman, PhD, School of Population Health (M431), University of Western Australia, Nedlands, WA 6009, Australia Tel: +61 8 6488 1250; fax: +61 8 6488 1188;
ABSTRACT