doi: 10.1161/CIRCULATIONAHA.105.559633
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(Circulation. 2005;112:3713-3721.)
© 2005 American Heart Association, Inc.
Epidemiology |
Prediction of Type 2 Diabetes Mellitus With Alternative Definitions of the Metabolic Syndrome
The Insulin Resistance Atherosclerosis Study
From the Division of Clinical Epidemiology (A.J.G.H., K.W., A.F., S.M.H.), University of Texas Health Sciences Center, San Antonio, Tex; Leadership Sinai Centre for Diabetes (A.J.G.H.), Mt. Sinai, Hospital, Toronto, Ontario, Canada; Division of Research (A.J.K.), Kaiser Permanente, Oakland, Calif; and Department of Public Health Sciences (R.B.D., L.E.W.), Wake Forest University School of Medicine, Winston Salem, NC.
Reprint requests to Dr Steven Haffner, Division of Clinical Epidemiology, University of Texas Health Science Center at San Antonio, Mail Code 7873, 7703 Floyd Curl Dr, San Antonio, TX 78229-3900. E-mail haffner{at}uthscsa.edu
Received May 2, 2005; revision received August 8, 2005; accepted August 10, 2005.
Background— In addition to predicting cardiovascular disease (CVD) morbidity and mortality, the metabolic syndrome is strongly associated with the development of type 2 diabetes mellitus (DM), itself an important risk factor for CVD. Our objective was to compare the ability of various metabolic syndrome criteria (including those recently proposed by the International Diabetes Federation), markers of insulin resistance (IR) and inflammation, and impaired glucose tolerance (IGT) in the prediction of DM and to determine whether various proposed modifications to the National Cholesterol Education program (NCEP) metabolic syndrome definition improved predictive ability.
Methods and Results— We examined 822 subjects in the Insulin Resistance Atherosclerosis Study aged 40 to 69 years who were nondiabetic at baseline. After 5.2 years, 148 individuals had developed DM. IGT, metabolic syndrome definitions, and IR markers all significantly predicted DM, with odds ratios ranging from 3.4 to 5.4 (all P<0.001), although there were no significant differences in the areas under the receiver operator characteristic (AROC) curves between the definitions. Modifying or requiring obesity, glucose, or IR components in NCEP-defined metabolic syndrome did not significantly alter the predictive ability of the definition under AROC curve criteria (all P>0.05). Similarly, although IR and inflammation variables were significantly associated with incident DM when included in multivariate models with NCEP-defined metabolic syndrome (all P<0.01), expanding the definition by adding these variables as components did not significantly alter the predictive ability of the definition under AROC curve criteria (all P>0.05).
Conclusions— The International Diabetes Federation and NCEP metabolic syndrome definitions predicted DM at least as well as the World Health Organization definition, despite not requiring the use of oral glucose tolerance testing or measures of IR or microalbuminuria. Modifications or additions to the NCEP metabolic syndrome definition had limited impact on the prediction of DM.
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