Utility of the metabolic syndrome and its components in the prediction of incident cardiovascular disease: a prospective cohort study.
BACKGROUND
To investigate the prognostic importance of the metabolic syndrome (MetS) on incident cardiovascular disease (CVD).


METHODS
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).


CONCLUSIONS
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.
Knuiman
Matthew W
MW
School of Population Health, University of Western Australia, Nedlands, Western Australia, Australia. Matthew.Knuiman@uwa.edu.au
Hung
Joseph
J
Divitini
Mark L
ML
Davis
Timothy M
TM
Beilby
John P
JP
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002318:Cardiovascular Diseases / Q000453:epidemiology / Q000209:etiology*; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D015994:Incidence; D008297:Male; D024821:Metabolic Syndrome / Q000150:complications* / Q000453:epidemiology; D008875:Middle Aged; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D014904:Western Australia / Q000453:epidemiology