Cardiology Research and Practice CVD event was deﬁned as incident myocardial infarction, resuscitated cardiac arrest, deﬁnite angina, probable angina if followed by revascularization, stroke, stroke death, coronary heart disease (CHD) death, other atherosclerotic death, and other CVD death as deﬁned by the MESA protocol. 2.4. Statistical Analysis. Descriptive analyses of all the vari- ables utilized in the data analysis were conducted. The baseline features were compared, using ANOVA or Kruskal- Wallis tests for continuous variables and the chi-square or the Fisher exact tests for categorical variables, into four columns: Neither CKD/MetS; CKD only; MetS only; both CKD and MetS. A Cox proportional hazards regression with and without adjustment for age, ethnicity, gender, study site, education, income, smoking, alcohol use, physical activity, total, and LDL cholesterol was performed to assess the independent association of CKD and MetS with incident CVD events with CKD and MetS in the same model. We next divided the participants into four groups according to the presence/absence of CKD and/or MetS. Survival analysis was performed using cumulative event- free Kaplan-Meier curves according to the presence/absence of CKD or MetS, and the groups were compared by log- rank test for trend. A similar Cox proportional hazards regression was performed to investigate the relationship of the four groups (neither CKD/MetS, CKD only, MetS only, nor both CKD and MetS) with incident CVD events using two sets of models: unadjusted models and models adjusted (Table 2) for established cardiovascular risk factors (age, ethnicity, gender, study site, education, income, smoking, alcohol use, physical activity, and total and LDL cholesterol) using CKD−/MetS− as the reference category. The potential confounders were selected based on their relationship with cardiovascular disease and the prior literature. Additionally, a similar analysis was performed after excluding participants with prevalent diabetes. Formal tests for additive and multiplicative interactions between CKD and MetS and prediction of incident CVD were also performed. We tested additive and multiplicative interactions in the proportional hazards model. A formal interaction term CKD × MetS was introduced in the model with all covariates to test for multiplicative interaction. Formal tests for indices of additive interaction such as relative excess risk due to interaction (RERI), attributable portion (AP), and synergy index (SI) were performed as described by Li and Chambless [28]. RERI is calculated as ((HR (both CKD and MetS) − HR (CKD alone) − HR (MetS alone) + 1)). AP is calculated as RERI divided by HR (both CKD and MetS). SI is ratio of increase in hazard due to both exposures (CKD and MetS) to the sum of the increases due to one exposure alone. Please see The appendix for formal calculations. All statistical analyses were performed using JMP Version 8 (SAS Institute Inc., Cary, NC/USA). 3. Results 3.1. Participant Characteristics. The sociodemographic char- acteristics of the study sample are depicted in Table 1. The 3 mean age of the sample was 61.6 years with the mean age being much higher at 69.7 years for participants with both CKD and MetS. A larger proportion of Chinese-Americans had no CKD/MetS (81%) compared to other ethnicities, and only 1% of Chinese-Americans had both the conditions compared to 3% for all other ethnicities. Among women, 31% had MetS as compared to 26% of men. Diabetes was more prevalent in the groups with MetS and both CKD/MetS compared to those without MetS or CKD/MetS. Smoking rates were not much diﬀerent between the groups, whereas alcohol consumption was signiﬁcantly higher in healthy participants. Additionally, the healthy participants were signiﬁcantly more physically active as compared to participants with either or both conditions. 3.2. Cardiovascular Events. During 5.5 years of followup, 283 CVD events were identiﬁed (118, CKD−/MetS− group; 10, CKD+/MetS− group; 120, CKD−/MetS+ group; 35, CKD+/MetS+ group). A Kaplan-Meier survival curve shows decreased survival free of CVD events across the four groups of CKD and MetS with a log test for trend which is statistically signiﬁcant (P < 0.0001) (Figure 1). These curves show signiﬁcantly poorer survival in the CKD+/MetS+ group. When CKD and MetS were entered into the same model, the results of multivariate Cox regression analysis including age, sex, ethnicity, smoking habit, cholesterol both total and LDL-C, alcohol consumption, and physical activity found that CKD (HR 2.02, 95% CI 1.43–2.79, P < 0.0001) and MetS (HR 2.55, 95% CI 2.01–3.25, P < 0.0001) were both signiﬁcantly associated with incident CVD events. Table 2 shows the results from a series of crude and multivariate regression analysis, showing how the association of CKD and MetS with CVD risk changed as groups of CVD risk factors were added to the regression model. In the crude model, the risk for CVD was signiﬁcantly higher in the CKD+/MetS+ group compared with the MetS−/CKD− group (HR 8.46). The hazard in the CKD+/MetS+ group remained highly signiﬁcant in the multivariate model (HR 5.56). It remained signiﬁcant even after further adjustment for antihypertensive medications and systolic blood pressure (HR 4.55, 95% CI 3.01–6.73). Furthermore, when compared with the CKD+/MetS− group or with the CKD−/MetS+ group, the risk of CVD events was signiﬁcantly higher in the CKD+/MetS+ group in univariate Cox regression analysis (versus CKD+/MetS− group: HR 3.14, 95% CI 1.61–6.69, P < 0.001; versus CKD−/MetS+ group: HR 3.38, 95% CI 2.28–4.87, P = 0.0001) and in multivariate Cox regression analysis (versus CKD+/MetS− group: HR 3.89, 95% CI 1.99– 8.31; versus CKD−/MetS+ group: HR 2.32, 95% CI 1.56– 3.37, P < 0.0001, resp.). We performed several additional analyses to address the robustness of these ﬁndings. Because patients with diabetes were more frequent in the CKD+/MetS+ group, we repeated our analysis for the 4,591 participants without previous diabetes. In this study, 210 CVD events occurred during the follow-up period. The independent predictive value of CKD+/MetS+ for CVD events was also conﬁrmed by the Kaplan-Meier method (log rank test for trend chi-square = 60; P < 0.0001) and by multivariate Cox regression analysis.