The metabolic syndrome as a tool for predicting future diabetes : the AusDiab study Cameron, A. J., Magliano, D. J., Zimmet, P. Z., Welborn, T. A., Colagiuri, S., Tonkin, A. M. and Shaw, J. E. 2008, The metabolic syndrome as a tool for predicting future diabetes : the AusDiab study, Journal of internal medicine, vol. 264, no. 2, pp. 177-186, doi: 10.1111/j.1365-2796.2008.01935.x. Attached Files Name Description MIMEType Size Downloads Title The metabolic syndrome as a tool for predicting future diabetes : the AusDiab study Author(s) Cameron, A. J. orcid.org/0000-0002-0568-5497 Magliano, D. J. Zimmet, P. Z. Welborn, T. A. Colagiuri, S. Tonkin, A. M. Shaw, J. E. Journal name Journal of internal medicine Volume number 264 Issue number 2 Start page 177 End page 186 Total pages 10 Publisher Blackwell Scientific Publications Place of publication Oxford, England Publication date 2008 ISSN 0954-6820 1365-2796 Keyword(s) AusDiab diabetes epidemiology longitudinal cohort metabolic syndrome risk prediction Summary Objective. To compare the ability of the metabolic syndrome (MetS), a diabetes prediction model (DPM), a noninvasive risk questionnaire and individual glucose measurements to predict future diabetes. Design. Five-year longitudinal cohort study. Tools tested included MetS definitions [World Health Organization, International Diabetes Federation, ATPIII and European Group for the study of Insulin Resistance (EGIR)], the FINnish Diabetes RIsk SCore risk questionnaire, the DPM, fasting and 2-h post load plasma glucose. Setting. Adult Australian population. Subjects. A total of 5842 men and women without diabetes ≥25 years. Response 58%. A total of 224 incident cases of diabetes. Results. In receiver operating characteristic curve analysis, the MetS was not a better predictor of incident diabetes than the DPM or measurement of glucose. The risk for diabetes among those with prediabetes but not MetS was almost triple that of those with MetS but not prediabetes (9.0% vs. 3.4%). Adjusted for component parts, the MetS was not a significant predictor of incident diabetes, except for EGIR in men [OR 2.1 (95% CI 1.2–3.7)]. Conclusions. A single fasting glucose measurement may be more effective and efficient than published definitions of the MetS or other risk constructs in predicting incident diabetes. Diagnosis of the MetS did not confer increased risk for incident diabetes independent of its individual components, with an exception for EGIR in men. Given these results, debate surrounding the public health utility of a MetS diagnosis, at least for identification of incident diabetes, is required. Language eng DOI 10.1111/j.1365-2796.2008.01935.x Field of Research 111706 Epidemiology Socio Economic Objective 920104 Diabetes HERDC Research category C1.1 Refereed article in a scholarly journal Copyright notice ©2008, Blackwell Publishing Ltd. Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30021310 Document type: Journal Article Collections: Faculty of Health School of Exercise and Nutrition Sciences Institute for Physical Activity and Nutrition Open Access Collection Related Links Link Description Link to full-text (open access)   Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 11 Dec 2009, 10:02:16 EST Tue, 15 Dec 2009, 12:59:08 EST Tue, 15 Dec 2009, 13:00:57 EST Tue, 15 Dec 2009, 13:04:27 EST Mon, 20 Dec 2010, 09:50:56 EST Mon, 11 Apr 2011, 15:07:48 EST Mon, 16 Jun 2014, 13:39:26 EST Thu, 11 Dec 2014, 16:22:20 EST Thu, 01 Oct 2020, 21:36:17 EST Filtered Full Citation counts:   Cited 63 times in TR Web of Science Cited 64 times in Scopus Search Google Scholar Access Statistics: 799 Abstract Views, 1 File Downloads  -  Detailed Statistics Created: Fri, 11 Dec 2009, 10:02:13 EST by Adrian Cameron

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.