Clustering of dyslipidemia, hyperuricemia, diabetes, and hypertension and its association with fasting insulin and central and overall obesity in a general population

Schmidt, Maria Inês; Watson, Robert L.; Duncan, Bruce B.; Metcalf, Patricia; Brancati, Frederick L.; Richey Sharrett, A.; Davis, C.E.; Heiss, Gerardo; for the Atherosclerosis Risk in Communities Study Investigators,

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Volume 45, Issue 6 , Pages 699-706, June 1996

Clustering of dyslipidemia, hyperuricemia, diabetes, and hypertension and its association with fasting insulin and central and overall obesity in a general population☆

Maria Inês Schmidt
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
Robert L. Watson
- Address reprint requests to Robert L. Watson, DVM, PhD, Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, 2500 N State St, Jackson, MS 39216-4505
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
Bruce B. Duncan
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
Patricia Metcalf
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
Frederick L. Brancati
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
A. Richey Sharrett
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
C.E. Davis
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
Gerardo Heiss
- From the Departmento de Medicina Social Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
- Departments of Epidemiology and Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC USA
- Division of Epidemiology, Department of Preventive Medicine, University of Mississippi Medical Center, Jackson, MS USA
- Welch Center for Prevention, Epidemiology and Clinical Research, The Johns Hopkins Medical Institutions, Baltimore, USA
- National Heart, Lung, and Blood Institute, Bethesda, MD USA
for the Atherosclerosis Risk in Communities Study Investigators

Received 18 July 1994; accepted 13 November 1995.

Abstract

Clustering of elevated triglycerides, decreased high-density lipoprotein cholesterol (HDL-C), hyperuricemia, diabetes, and hypertension has been related to insulin resistance/high insulin levels and central and/or overall obesity. The extent to which these abnormalities cluster and whether hyperinsulinemia, central adiposity, and overall obesity each independently associate with this clustering were evaluated in 14,481 US whites and African-Americans 45 to 64 years of age. With the exception of hypertension, abnormalities rarely existed in isolated form. Clustering greatly exceeded chance association (P < .001). Although this clustering was greater in relative terms (ratio of observed to expected cluster frequency) in the lean and less centrally obese, it was greater in absolute terms (observed minus expected cluster frequency as a percent of total population) in the more centrally and more generally obese. The greatest excesses were found for clusters that included both hypertriglyceridemia and low HDL-C. Multiple logistic regression models showed strong and independent graded relationships of clusters with quintiles of fasting insulin (fifth quintile odds ratio, 10 to 54, P < .001) and to a lesser degree with quintiles of the waist to hip ratio (2.2 to 5.4, P < .001 for most) and of body mass index (1.6 to 4.5, P < .05 for most). In conclusion, all abnormalities cluster in excess of that predicted by chance, with clusters showing remarkable and graded independent associations with fasting hyperinsulinemia and to a lesser extent with central and overall obesity. Thus, a metabolic syndrome occurs in both lean and obese middle-aged US adults.

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☆ Supported by National Heart, Lung, and Blood Institute Contracts No. N01-HC-55015, N01-HC-55016, N01-HC-55018, N01-HC-55019, N01-HC-55020, N01-HC-55021, and N01-HC-55022, and in part by a fellowship from the Brazilian Conselho Nacional de Desenvolvimento Cientifico e Technológico (M.I.S.), a fellowship from the Brazilian Ministry of Education (B.B.D.), an Overseas Research Fellowship from the Health Research Council of New Zealand (P.M.), and a Career Development Award from the American Diabetes Association (F.L.B.).

PII: S0026-0495(96)90134-1

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Volume 45, Issue 6 , Pages 699-706, June 1996

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