Using Metabolic Syndrome Traits for Efficient Detection of Impaired Glucose Tolerance

  1. James B. Meigs, MD MPH12,
  2. Ken Williams, MS3,
  3. Lisa M. Sullivan, PHD4,
  4. Kelly J. Hunt, PHD3,
  5. Steven M. Haffner, MD3,
  6. Michael P. Stern, MD3,
  7. Clicerio González Villalpando, MD5,
  8. Jessica S. Perhanidis, MPH1,
  9. David M. Nathan, MD2,
  10. Ralph B. D’Agostino, Jr, PHD6,
  11. Ralph B. D’Agostino, Sr, PHD4 and
  12. Peter W.F. Wilson, MD7
  1. 1General Medicine Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
  2. 2Diabetes Center, Department of Medicine, Massachusetts Hospital and Harvard Medical School, Boston, Massachusetts
  3. 3Division of Clinical Epidemiology, Department of Medicine, University of Texas Health Science Center, San Antonio, Texas
  4. 4Statistics and Consulting Unit of the Mathematics and Statistics Department at Boston University, Boston, Massachusetts
  5. 5Centro de Estudios en Diabetes, The American British Coudray Hospital and Unidades de Investigación in Médica en Enfermedades Metabolicas y Epidemiología Clínica, Hospital Gabriel Mancera, Instituto Mexicano del Seguro Social, Mexico City, México
  6. 6Department of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
  7. 7Boston University School of Medicine and Framingham Heart Study, Framingham, Massachusetts
  1. Address correspondence and reprint requests to James B. Meigs, MD, MPH, General Internal Medicine Unit Massachusetts General Hospital, 50 Staniford St., 9th Floor, Boston, MA 02114. E-mail: jmeigs{at}


OBJECTIVE—Efficient detection of impaired glucose tolerance (IGT) is needed to implement type 2 diabetes prevention interventions.

RESEARCH DESIGN AND METHODS—We assessed the capacity of the metabolic syndrome (MetS) to identify IGT in a cross-sectional analysis of 3,326 Caucasian Framingham Offspring Study (FOS), 1,168 Caucasian and 1,812 Mexican-American San Antonio Heart Study (SAHS), 1,983 Mexico City Diabetes Study (MCDS), and 452 Caucasian, 407 Mexican-American, and 290 African-American Insulin Resistance Atherosclerosis Study (IRAS) men and women aged 30–79 years who had a clinical examination and an oral glucose tolerance test (OGTT) during 1987–1996. Those with diabetes treatment or fasting plasma glucose ≥7.0 mmol/l were excluded (MetS was defined by Third Report of the National Cholesterol Education Program’s Adult Treatment Panel criteria and IGT as 2-h postchallenge glucose [2hPG] ≥7.8 mmol/l). We calculated positive (PPV) and negative predictive values (NPV), population attributable risk percentages (PAR%), age- and sex-adjusted odds ratios (ORs), and areas under the receiver operating characteristic curve (AROCs) associated with MetS traits.

RESULTS—Among FOS, SAHS, and MCDS subjects, 24–43% had MetS and 15–23% had IGT (including 2–5% with 2hPG ≥11.1 mmol/l). Among those with MetS, OR for IGT were 3–4, PPV were 0.24–0.41, NPV were 0.84–0.91, and PAR% were 30–40%. Among subjects with MetS defined by impaired fasting glucose (IFG) and any two other traits, OR for IGT were 9–24, PPV were 0.62–0.89, NPV were 0.78–0.87, and PAR% were 3–12%. Among IRAS subjects, 24–34% had MetS and 37–41% had IGT. Among those with MetS, ORs for IGT were 3–6, PPVs were 0.57–0.73, and NPVs were 0.67–0.72. In logistic regression models, IFG, large waist, and high triglycerides were independently associated with IGT (AROC 0.71–0.83) in all study populations.

CONCLUSIONS—The MetS, especially defined by IFG, large waist, and high triglycerides, efficiently identifies subjects likely to have IGT on OGTT and thus be eligible for diabetes prevention interventions.


  • P.W.F.W. has received grant support from GlaxoSmithKline.

    A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances.

    • Accepted March 1, 2004.
    • Received November 10, 2003.
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