CMAJ • March 17, 2009; 180 (6). doi:10.1503/cmaj.080972.
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Research

Metabolic syndrome and its components as predictors of incident type 2 diabetes mellitus in an Aboriginal community

Sylvia H. Ley, RD MSc, Stewart B. Harris, MD, Mary Mamakeesick, RPN, Tina Noon, Edith Fiddler, Joel Gittelsohn, PhD, Thomas M.S. Wolever, MD PhD, Philip W. Connelly, PhD, Robert A. Hegele, MD, Bernard Zinman, MD and Anthony J.G. Hanley, PhD

From the Department of Nutritional Sciences (Ley, Wolever, Hanley), University of Toronto, Toronto, Ont.; the Center for Studies in Family Medicine (Harris), Schulich School of Medicine and Dentistry, University of Western Ontario, London, Ont.; the Sandy Lake Health and Diabetes Project (Mamakeesick, Noon, Fiddler), Sandy Lake, Ont.; the Center for Human Nutrition (Gittelsohn), Johns Hopkins Bloomberg School of Public Health, Baltimore, USA; the Department of Laboratory Medicine and Pathobiology (Connelly), University of Toronto, Toronto, Ont.; the Keenan Research Centre of the Li Ka Shing Knowledge Institute (Connelly); St. Michael's Hospital, Toronto, Ont.; the Robarts Research Institute and University of Western Ontario (Hegele), London, Ont.; the Division of Endocrinology (Zinman, Hanley), University of Toronto, Toronto, Ont.; the Leadership Sinai Centre for Diabetes (Zinman, Hanley), Mount Sinai Hospital, Toronto, Ont.; and the Samuel Lunenfeld Research Institute (Zinman), Mount Sinai Hospital, Toronto, Ont.

Correspondence to: Dr. Anthony J.G. Hanley, Department of Nutritional Sciences, University of Toronto, FitzGerald Building, 150 College St., Rm. 341, Toronto ON M5S 3E2; fax 416 978-5882; anthony.hanley{at}utoronto.ca

Background: Risk factors for type 2 diabetes remain poorly characterized among Aboriginal Canadians. We aimed to determine the incidence of type 2 diabetes in an Aboriginal community and to evaluate prospective associations with metabolic syndrome and its components.

Methods: Of 606 participants in the Sandy Lake Health and Diabetes Project from 1993 to 1995 who were free of diabetes at baseline, 540 (89.1%) participated in 10-year follow-up assessments. Baseline anthropometry, blood pressure, fasting insulin and serum lipid levels were measured. Fasting and 2-hour postload glucose levels were obtained at follow-up to determine incident cases of type 2 diabetes.

Results: The 10-year cumulative incidence of diabetes was 17.5%. High adiposity, dyslipidemia, hyperglycemia, hyperinsulinemia and hypertension at baseline were associated with an increased risk of diabetes after adjustment for age and sex (all p ≤ 0.03). Metabolic syndrome had high specificity (75%–88%) and high negative predictive value (85%–87%) to correctly detect diabetes-free individuals at follow-up. It had low sensitivity (26%–48%) and low positive predictive value (29%–32%) to detect future diabetes. Metabolic syndrome at baseline was associated with incident diabetes after adjustment for age and sex, regardless of whether the syndrome was defined using the National Cholesterol Education Program criteria (odds ratio [OR] 2.03, 95% confidence interval [CI] 1.10–3.75) or the International Diabetes Federation criteria (OR 2.14, 95% CI 1.29–3.55). The association was to the same degree as that for impaired glucose tolerance assessed using the oral glucose tolerance test (OR 2.87, 95% CI 1.52–5.40; p > 0.05 for comparison of C statistics).

Interpretation: Metabolic syndrome and its components can be identified with readily available clinical measures. As such, the syndrome may be useful for identifying individuals at risk of type 2 diabetes in remote Aboriginal communities.


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