Modeling preclinical cardiovascular risk for use in epidemiologic studies: Miami community health study

Rita Z. Goldstein, Barry E. Hurwitz, Maria M. Llabre, Neil Schneiderman, Miriam Gutt, Jay S. Skyler, Ronald J. Prineas, Richard P. Donahue

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

To develop a method for assessing preclinical cardiovascular disease risk, models of resting cardiovascular regulation and of insulin metabolic syndrome were derived from information collected from 1991 to 1996 in a culturally heterogeneous sample of 319 healthy men and women (aged 25-44 years) from Miami-Dade County, Florida. The model of resting cardiovascular regulation used 8 noninvasive measures of autonomic and cardiovascular function. Three factors were derived: 1) parasympathetic, 2) inotropy, and 3) systemic vascular resistance. The model of insulin metabolic syndrome used 12 measures assessing body mass, insulin, glucose, and lipid metabolism. Four factors were derived: 1) body mass and fat distribution, 2) glucose level and regulation, 3) insulin level and regulation, and 4) plasma lipid levels. Analyses of the association of the two models revealed that subjects with lower cardiac contractility had greater body mass, higher fasting and postload insulin and glucose levels, and lower insulin sensitivity. Subjects with greater vascular resistance had greater body mass, higher total cholesterol and triglyceride levels, and lower high density lipoprotein cholesterol levels. These findings indicate that preclinical cardiovascular disease risk may involve pathophysiologic processes in which cardiac inotropic and vasodilatory functions are linked to specific aspects of insulin metabolic syndrome.

Original languageEnglish (US)
Pages (from-to)765-776
Number of pages12
JournalAmerican journal of epidemiology
Volume154
Issue number8
DOIs
StatePublished - Oct 15 2001

Keywords

  • Blacks
  • Cardiovascular
  • Cardiovascular system
  • Factor analysis
  • Hispanic Americans
  • Insulin resistance
  • Models
  • Sex
  • Statistical
  • Whites

ASJC Scopus subject areas

  • Epidemiology

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