Practical way to assess metabolic syndrome using a continuous score obtained from principal components analysis

We devised a practical continuous score to assess the metabolic syndrome, and assessed whether this syndrome score predicts incident diabetes and cardiovascular disease.

Among 5,024 participants of the Data from an Epidemiological Study on the Insulin Resistance Syndrome (D.E.S.I.R.) cohort, we defined a metabolic syndrome score by the first principal component (PC1), using only the correlations between continuous metabolic syndrome measures (glucose, waist circumference, triglycerides, and systolic blood pressure). This metabolic syndrome score was highly correlated with a similar score also including insulin and HDL cholesterol (r ( s )=0.94). Over 9 years of follow-up, incident diabetes and cardiovascular disease (CVD) were predicted by logistic regression using the simpler metabolic syndrome score.

The means of the metabolic syndrome measures differed between men and women. Nevertheless, as the degree of variance explained and the PC1 coefficients were remarkably similar, we used a common metabolic syndrome score. The metabolic syndrome score explained 50% of the variance of the metabolic syndrome measures, and waist circumference had the highest correlation (0.59) with this score. Each standard deviation increase in the metabolic syndrome score was associated with a markedly increased age-adjusted risk of developing diabetes (odds ratios: men 3.4 [95% CI 2.6-4.4]; women 5.1 [3.6-7.2]) and with increased incident CVD of 1.7 (1.4-2.1) in men and 1.7 (1.0-2.7) in women.

Our results, which should be confirmed in other populations, suggest that it is possible to evaluate the risk of the metabolic syndrome in a pragmatic fashion with a continuous score, obtained from principal components analysis of the basic, continuous syndrome measures.