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Body Mass Index, Metabolic Syndrome, and Risk of Type 2 Diabetes or Cardiovascular Disease

General Medicine Division and Department of Medicine (J.B.M.) and Diabetes Unit and Department of Medicine (D.M.N.), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114; Department of Endocrinology, Diabetes, and Medical Genetics (P.W.F.W.), Medical University of South Carolina, Charleston, South Carolina 29403; The National Heart, Lung, and Blood Institute’s Framingham Heart Study and the Division of Endocrinology, Diabetes, and Hypertension (C.S.F.), Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts 02115; The National Heart, Lung, and Blood Institute’s Framingham Heart Study and the Evans Department of Medicine, Whitaker Cardiovascular Institute, and Preventive Medicine Section (R.S.V.), Boston University School of Medicine, Boston, Massachusetts 02215; and Department of Mathematics, Statistics, and Consulting Unit (L.M.S., R.B.D.), Boston University, Boston, Massachusetts 02118

Address all correspondence and requests for reprints to: James B. Meigs, M.D., M.P.H., General Medicine Division, Massachusetts General Hospital, 50 Staniford Street, 9th Floor, Boston, Massachusetts 02114. E-mail: jmeigs{at}partners.org.

Context: Metabolic risk conferred by adiposity may be due to associated risk factor clustering.

Objective: The objective of this study was to assess risk for diabetes or cardiovascular disease (CVD) stratified by body mass index (BMI) and the presence or absence of metabolic syndrome (MetS) or insulin resistance (IR).

Design, Setting, and Participants: This was a community-based, longitudinal study of 2902 people (55% women, mean age 53 yr) without diabetes or CVD in 1989–1992 followed for up to 11 yr. We categorized subjects by normal weight (BMI < 25 kg/m²), overweight (25–29.9 kg/m²), or obese (>30 kg/m²) and by the National Cholesterol Education Program’s Adult Treatment Panel MetS or the top quartile of homeostasis model IR. We used proportional hazard models to estimate risk relative to normal weight and no MetS or IR.

Main Outcome Measure: Incident type 2 diabetes (treatment or fasting glucose 7 mmol/liter, 141 events) or CVD (myocardial infarction, stroke, or claudication, 252 events) were measured.

Results: Among 1056 normal-weight subjects, 7% had MetS and a risk factor-adjusted relative risk for diabetes of 3.97 (95% confidence interval, 1.35–11.6) and for CVD of 3.01 (1.68–5.41). Among 638 obese subjects, 37% did not have MetS or significantly increased risk. Obese subjects with MetS had an adjusted relative risk for diabetes of 10.3 (5.44–19.5) and for CVD of 2.13 (1.43–3.18). Results were similar in analyses of BMI-IR categories.

Conclusions: People with normal weight and MetS or IR or with obesity but no MetS or IR were not uncommon in our sample. Risk factor clustering or IR appear to confer much of the risk for diabetes or CVD commonly associated with elevated BMI.

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