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ISSN: 2155-6156

Journal of Diabetes & Metabolism
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Review Article

Surrogate Measures of Adiposity and Cardiometabolic Risk – Why the Uncertainty? A Review of Recent Meta-Analytic Studies

Seán R Millar*, Ivan J Perry and Catherine M Phillips

HRB Centre for Health and Diet Research, Department of Epidemiology and Public Health, University College Cork, Ireland

Corresponding Author:
Seán R. Millar
Department of Epidemiology & Public Health
University College Cork.4th Floor
Western Gateway Building
Western Road, Cork, Ireland
Tel: 353(0)214205520
Fax: 353(0)214205469
E-mail: [email protected]

Received Date: June 12, 2013; Accepted Date: July 27, 2013; Published Date: August 04, 2013

Citation: Millar SR, Perry IJ, Phillips CM (2013) Surrogate Measures of Adiposity and Cardiometabolic Risk – Why the Uncertainty? A Review of Recent Meta- Analytic Studies. J Diabetes Metab S11:004. doi:10.4172/2155-6156.S11-004

Copyright: © 2013 Millar SR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

The increasing obesity epidemic has become a significant public health concern worldwide, as excess body fat has been shown to be strongly related to cardiometabolic risk. Measurement of adiposity is commonly used as an indicator of health and various anthropometric measurement procedures have been proposed to characterise individual susceptibility to cardiometabolic conditions. Although extensive research has attempted to quantify relationships between different adiposity measures and morbidity, results have been conflicting and inconclusive, and considerable controversy still exists as to which anthropometric measurement most accurately defines nonoptimal body fat distribution.In this review we describe the most commonly used indices of general and central adiposity and review the most recently completed meta-analytic studies to determine which adiposity measure is most strongly associated with, and the best discriminator of, type 2 diabetes, cardiovascular disease and mortality.

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