Components of the metabolic syndrome and incidence of diabetes in elderly Italians: the Italian Longitudinal Study on Aging

Atherosclerosis. 2006 Aug;187(2):385-92. doi: 10.1016/j.atherosclerosis.2005.09.018. Epub 2005 Oct 20.

Abstract

The aim of this study was to explore the relationship among components of the metabolic syndrome and their role in the development of diabetes. We included 2295 subjects, aged 65-84 years, participating in the Italian Longitudinal Study on Aging, a population-based study conducted in 1992 and with a follow-up in 1996. Factor analysis was conducted, separately for diabetic and non-diabetic men and women, using the principle components method and varimax rotations. Factor scores for the baseline were used as independent variables in logistic regressions models to determine risk factors predicting the development of diabetes. Factor analysis among non-diabetic elderly showed two factors for men (body size/insulin resistance, blood pressure/lipids) and three for women (body size, lipids, blood pressure). Among diabetic subjects, three factors emerged for men (body size/lipids/insulin resistance, body size/blood pressure, glucose) and four for women (body size/lipids/insulin resistance, lipids, body size/glucose/insulin resistance, lipids/blood pressure). For non-diabetic men and women, the body size factor (body size/insulin resistance factor for men) was strongly associated with diabetes incidence (OR=2.30, 95% CI 1.41-3.74 and OR=2.06, 95% CI 1.33-3.17, respectively). This study confirms that the metabolic syndrome (MetS) does not recognize one single underlying factor in an elderly cohort and that the obesity factor is a strong predictor of development of new onset diabetes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aged, 80 and over
  • Aging*
  • Cohort Studies
  • Diabetes Mellitus, Type 2 / epidemiology*
  • Female
  • Humans
  • Incidence
  • Italy / epidemiology
  • Longitudinal Studies
  • Male
  • Metabolic Syndrome / epidemiology*
  • Predictive Value of Tests
  • Prevalence
  • Risk Factors
  • Sex Distribution