Adiposity indices in the prediction of metabolic abnormalities associated with cardiovascular disease in non-diabetic adults NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES Liu, A., Abbasi, F., Reaven, G. M. 2011; 21 (8): 553-560

Abstract

The prevalence of insulin resistance and cardiovascular disease (CVD) increases with degree of obesity. Whether measurements of generalized and abdominal obesity differ in the ability to predict changes associated with increased CVD risk is widely debated. We compared the prevalence of metabolic abnormalities in 275 women and 204 men stratified by categories of body mass index (BMI) and waist circumference (WC), and assessed the ability of these adiposity indices in combination with metabolic risk variables to predict insulin resistance.Healthy, non-diabetic volunteers underwent measurements of BMI, WC, blood pressure, fasting plasma glucose (FPG), lipoprotein concentrations, and direct quantification of insulin-mediated glucose uptake. Insulin resistance was defined as the top tertile of steady-state plasma glucose (SSPG) concentrations. BMI and WC were highly correlated (P < 0.001) in both women and men. Abnormal SSPG and triglyceride concentrations were associated with increasing adiposity by either index in both genders. Among women, abnormal FPG and high density lipoprotein cholesterol (HDL-C) concentrations were associated with increasing BMI and WC. In men, abnormal HDL-C was associated with increasing BMI only. Elevated systolic blood pressure (SBP) was associated with increasing BMI in both genders. The odds of insulin resistance were greatest in women with elevated FPG and triglycerides (4.5-fold). In men, the best predictors were BMI and SBP, and WC and HDL-C (3-fold).BMI is at least comparable to WC in stratifying individuals for prevalence of metabolic abnormalities associated with increased CVD risk and predicting insulin resistance.

View details for DOI 10.1016/j.numecd.2009.12.009

View details for Web of Science ID 000293596800003

View details for PubMedID 20304617