title: Metabolic Syndrome Derived from Principal Component Analysis and Incident Cardiovascular Events: The Multi Ethnic Study of Atherosclerosis (MESA) and Health, Aging, and Body Composition (Health ABC).
abstract: Background. The NCEP metabolic syndrome (MetS) is a combination of dichotomized interrelated risk factors from predominantly Caucasian populations. We propose a continuous MetS score based on principal component analysis (PCA) of the same risk factors in a multiethnic cohort and compare prediction of incident CVD events with NCEP MetS definition. Additionally, we replicated these analyses in the Health, Aging, and Body composition (Health ABC) study cohort. Methods and Results. We performed PCA of the MetS elements (waist circumference, HDL, TG, fasting blood glucose, SBP, and DBP) in 2610 Caucasian Americans, 801 Chinese Americans, 1875 African Americans, and 1494 Hispanic Americans in the multiethnic study of atherosclerosis (MESA) cohort. We selected the first principal component as a continuous MetS score (MetS-PC). Cox proportional hazards models were used to examine the association between MetS-PC and 5.5 years of CVD events (n = 377) adjusting for age, gender, race, smoking and LDL-C, overall and by ethnicity. To facilitate comparison of MetS-PC with the binary NCEP definition, a MetS-PC cut point was chosen to yield the same 37% prevalence of MetS as the NCEP definition (37%) in the MESA cohort. Hazard ratio (HR) for CVD events were estimated using the NCEP and Mets-PC-derived binary definitions. In Cox proportional models, the HR (95% CI) for CVD events for 1-SD (standard deviation) of MetS-PC was 1.71 (1.54-1.90) (P < 0.0001) overall after adjusting for potential confounders, and for each ethnicity, HRs were: Caucasian, 1.64 (1.39-1.94), Chinese, 1.39 (1.06-1.83), African, 1.67 (1.37-2.02), and Hispanic, 2.10 (1.66-2.65). Finally, when binary definitions were compared, HR for CVD events was 2.34 (1.91-2.87) for MetS-PC versus 1.79 (1.46-2.20) for NCEP MetS. In the Health ABC cohort, in a fully adjusted model, MetS-PC per 1-SD (Health ABC) remained associated with CVD events (HR = 1.21, 95%CI 1.12-1.32) overall, and for each ethnicity, Caucasian (HR = 1.24, 95%CI 1.12-1.39) and African Americans (HR = 1.16, 95%CI 1.01-1.32). Finally, when using a binary definition of MetS-PC (cut point 0.505) designed to match the NCEP definition in terms of prevalence in the Health ABC cohort (35%), the fully adjusted HR for CVD events was 1.39, 95%CI 1.17-1.64 compared with 1.46, 95%CI 1.23-1.72 using the NCEP definition. Conclusion. MetS-PC is a continuous measure of metabolic syndrome and was a better predictor of CVD events overall and in individual ethnicities. Additionally, a binary MetS-PC definition was better than the NCEP MetS definition in predicting incident CVD events in the MESA cohort, but this superiority was not evident in the Health ABC cohort.
authors.affiliation: Division of Cardiology, Department of Internal Medicine, Oakwood Hospital and Medical Center, Dearborn, MI 48124, USA.
authors.forename: Subhashish
authors.initials: S
authors.lastname: Agarwal
authors.forename: David R
authors.initials: DR
authors.lastname: Jacobs
authors.forename: Dhananjay
authors.initials: D
authors.lastname: Vaidya
authors.forename: Christopher T
authors.initials: CT
authors.lastname: Sibley
authors.forename: Neal W
authors.initials: NW
authors.lastname: Jorgensen
authors.forename: Jerome I
authors.initials: JI
authors.lastname: Rotter
authors.forename: Yii-Der Ida
authors.initials: YD
authors.lastname: Chen
authors.forename: Yongmei
authors.initials: Y
authors.lastname: Liu
authors.forename: Jeanette S
authors.initials: JS
authors.lastname: Andrews
authors.forename: Stephen
authors.initials: S
authors.lastname: Kritchevsky
authors.forename: Bret
authors.initials: B
authors.lastname: Goodpaster
authors.forename: Alka
authors.initials: A
authors.lastname: Kanaya
authors.forename: Anne B
authors.initials: AB
authors.lastname: Newman
authors.forename: Eleanor M
authors.initials: EM
authors.lastname: Simonsick
authors.forename: David M
authors.initials: DM
authors.lastname: Herrington