In this ethnically diverse population of 6,780 individuals aged 45–84, the first principal component derived from elements of the MetS explains 33% of the variance of the metabolic measures. This continuous metabolic syndrome score (MetS-PC) is a significant predictor of 5.5-year incident clinical cardiovascular events in the total population, and in each of the four major race/ethnicity subgroups separately. Additionally, a binary definition of the MetS based on this continuous measure was a better predictor of clinical cardiovascular events compared to the NCEP definition.
It should be acknowledged that MetS is not an absolute risk indicator, because it does not contain many of the factors that determine absolute risk, for example, age, sex, cigarette smoking, and low-density lipoprotein cholesterol levels [6
]. Risk predictors such as the Framingham risk score are much superior if risk prediction is the goal; however, the primary goal of this analysis was not risk prediction per se, but rather improving upon the current NCEP definition of MetS, using the same components that make the MetS and comparing the two definitions using incident CVD events as a criteria measure.
The current binary definitions of the metabolic syndrome, including the NCEP definition, were developed by expert committees as a clinically useful means of identifying high-risk individuals [1
]. However, dichotomization of the continuous variables leads to loss of information [7
]. A minor improvement in one component could result in an individual no longer being classified as having MetS, despite no meaningful change of actual cardiovascular risk [11
]. Additionally, the NCEP MetS may not predict risk of CVD events in all ethnicities equally as the data for constructing the NCEP definition were derived from predominantly Caucasian populations [12
]. The evaluation of the MetS as a continuous score derived from a multiethnic population is potentially a more informative and generalizable approach to defining the syndrome and determining its clinical correlates. Additionally, a continuous measure may also improve the ability to identify lifestyle, environmental, molecular, and genetic etiologic factors that are specific for the MetS, and in future, these etiological factors could be incorporated in the definition of the continuous measure providing a stronger CVD predictive value [7
Principal component analysis is a mathematical technique that transforms a number of correlated variables into a reduced number of uncorrelated variables called principal components, of which the first principal component captures the maximal variance [17
]. Since the MetS is a metabolic condition characterized by the co-occurrence of multiple metabolic abnormalities, it follows that the first principal component of the measures for these traits would be an efficient way to quantify the presence of the syndrome. In our data, MetS-PC correlated well with all the components of the MetS (correlation coefficients 0.44–0.61, ), consistent with a definition of a syndrome.
The metabolic syndrome is a known risk factor for cardiovascular disease, and MetS-PC predicts clinical cardiovascular events extremely well in this multiethnic cohort. MetS-PC was significantly associated with a more than twofold, fully adjusted increased risk of incident CVD in this cohort. We choose to show the analysis in the entire cohort including also diabetics as the analysis after excluding diabetics was qualitatively similar to the results obtained with the entire cohort. In analyses stratified by ethnicity, MetS-PC is a significant predictor of CVD across the four ethnic groups with similar point estimates for the hazard ratios. Additionally, there are suggestions that perhaps for better risk prediction; the definition of metabolic syndrome should be broadened to incorporate other elements such as high-sensitivity C-reactive protein (hsCRP) in the MetS definition [7
]. We performed an analysis wherein we added hsCRP in the MetS-PC, but the addition did not lead to any substantial improvement in risk prediction of incident CVD events. Our findings parallel similar results where addition of hsCRP to MetS did not lead to improvement in prediction of incident CVD events [29
] or atherogenesis [30
Further, we compared the MetS-PC definition of MetS with the NCEP definition in predicting CVD events in the MESA cohort. To facilitate comparison of MetS-PC with the dichotomous NCEP definition, a MetS-PC cut point (0.475) was chosen to yield the same 37% prevalence of MetS as when using the NCEP definition (37%) in the MESA cohort. The strength of association with incident cardiovascular events was compared using the NCEP and the derived binary MetS-PC definitions, in a fully adjusted model. The binary MetS-PC has a stronger association with incident cardiovascular events compared to the NCEP MetS as the point estimate for hazard using the binary MetS-PC definition is not included in the confidence interval of the NCEP hazard ratio. Additionally, the chi-square values were much higher when using the binary MetS-PC definition compared to the NCEP MetS definition. However, when an independent validation of a similar strategy was applied in the Health ABC cohort, the association of MetS-PC with CVD events remained, but the superiority of the MetS-PC definition versus NCEP MetS definition was no longer evident. This could be the result of the inherent differences between the two cohorts such as differences in age. The mean age of the MESA cohort is 62 years versus 74 for the Health ABC cohort. Additionally, the overall mean age and gender-adjusted systolic and diastolic blood pressures are much lower in the MESA cohort as compared to the Health ABC cohort. This is reflected in the loading for the first principal component. Both the systolic and diastolic blood pressures are well represented in the first principal component in the MESA cohort (loading factors: systolic BP = 0.61, diastolic BP = 0.56). In contrast, the systolic and diastolic BP were less heavily represented in the PC analysis for the Health ABC cohort (loading factors: systolic BP = 0.13, diastolic BP = 0.05), perhaps secondary to the greater prevalence of essential hypertension uncorrelated with the other metabolic derangements of the Met syndrome. In a previous Health ABC study evaluating CVD risk in older adults with MetS without past history of coronary heart disease and heart failure, the proportion of MI (6.1% versus 4.8%, P
= 0.18) and HF hospital stay (5.6% versus 4.3%, P
= 0.17), although higher among those with MetS compared to those without MetS, did not reach statistical significance [31
]. This finding perhaps explains the lower hazards for CVD events in the Health ABC cohort compared to the MESA cohort findings.
A few studies have applied PCA to identify factors and their relationship to incident diabetes and cardiovascular disease (CVD) using the elements of the MetS, measures of obesity, and insulin resistance [19
]. Hillier et al., [22
] found increased odds of cardiovascular events in 5,024 middle-aged French cohort; men, 1.7 (1.4, 2.1), and women 1.7 (1.0, 2.7), which is similar to our findings of 1.71 (1.54, 1.90). Lempiainen et al., [19
] applied factor analysis to 1069 subjects 65 to 74 years old from Finland followed for a period of 7 years and found similar hazards of coronary events. Similarly, Pyörälä et al., [23
] applied factor analysis to 970 healthy men aged 34 to 64 years in the Helsinki Policemen Study and found that the insulin resistance factor increased the hazard for coronary heart disease to 1.28 (95% CI 1.10–1.50) during 22 years of followup. The current study builds on these earlier efforts by applying similar methods to a larger and much more ethnically diverse cohort. The strength of the association between the continuous MetS-PC score and CVD events, its utility for predicting CVD events in multiple ethnicities, and its improved performance relative to the NCEP definition provide compelling evidence that this approach may be a superior strategy for defining the metabolic syndrome.
The strength of this study is the inclusion of four different ethnicities from six different recruitment sites in the United States, and stringent quality control procedures, as well as an average 5.5-year followup for identification of incident cardiovascular events. Additionally, we performed a replication of the strategy using an independent cohort and found results to be qualitatively similar. Among its limitations, the exclusion of individuals with known cardiovascular disease calls for caution in generalizing results to the total population. It should also be emphasized that acculturation to diet and environment plays a role in the development of the cardiovascular disease, and therefore, our findings may not apply to the same ethnicities in other parts of the world. Additionally, the sample size for Chinese Americans was small, and the event rate was low, making the estimates of risk less certain in the Chinese American participants compared with other groups. Further, this continuous score will need to be validated in larger cohorts before finding general applicability.