Waist circumference independently associates with the risk of insulin resistance and type 2 diabetes in mexican american families

Abstract

Objective: In spite of the growing recognition of the specific association of waist circumference (WC) with type 2 diabetes (T2D) and insulin resistance (IR), current guidelines still use body mass index (BMI) as a tool of choice. Our objective was to determine whether WC is a better T2D predictor than BMI in family-based settings.

Research design and methods: Using prospectively collected data on 808 individuals from 42 extended Mexican American families representing 7617.92 person-years follow-up, we examined the performance of WC and BMI as predictors of cumulative and incident risk of T2D. We used robust statistical methods that accounted for the kinships and included polygenic models, discrete trait modeling, Akaike information criterion, odds ratio (OR), relative risk (RR) and Kullback-Leibler R(2). SOLAR software was used to conduct all the data analyses.

Results: We found that in multivariate polygenic models, WC was an independent predictor of cumulative (OR = 2.76, p = 0.0002) and future risk of T2D (RR = 2.15, p = 3.56×10(-9)) and outperformed BMI when compared in a head-to-head fashion. High WC (≥94.65 cm after adjusting for age and sex) was also associated with high fasting glucose, insulin and triglyceride levels and low high-density lipoprotein levels indicating a potential association with IR. Moreover, WC was specifically and significantly associated with insulin resistant T2D (OR = 4.83, p = 1.01×10(-13)).

Conclusions: Our results demonstrate the value of using WC as a screening tool of choice for future risk of T2D in Mexican American families. Also, WC is specifically associated with insulin resistant T2D.

Figure 1. Determination of the optimal cut-point for waist circumference as a predictor of cumulative T2D risk.

Figure shows Akaike information criterion (left y-axis) and odds ratio (right y-axis) for a cut-point of waist circumference indicated on the x-axis. Dashed vertical line indicates the optimal cut-point.

Figure 2. Association of dichotomized WC with T2D-related traits.

The bars represent regression coefficients estimated using polygenic regression models.

Figure 3. Association of dichotomized WC with IR and insulin resistant T2D.

The bars represent regression coefficients estimated using polygenic regression models. Results are shown before (purple bars) and after (red bars) adjusting for the use of antidiabetic medication which includes the oral antidiabetic drugs as well as insulin. Statistical significance of a regression coefficient is shown in color-coded fashion at the top of the graph.