Congestive heart failure predicts the development of non-insulin-dependent diabetes mellitus in the elderly. The Osservatorio Geriatrico Regione Campania Group

Diabetes Metab. 1997 Jun;23(3):213-8.


Congestive heart failure (CHF) is an insulin-resistant state which constitutes the main risk factor for the development of non-insulin-dependent diabetes mellitus (NIDDM). Our study investigated the predictive role of CHF on the development of NIDDM in 1,339 elderly subjects with a mean ( +/- SD) age of 74.2 +/- 6.4 years. CHF had a 9.5% prevalence, and 14.7% of the subjects had NIDDM. After stratification by age, subjects between 80 and 84 years had the highest prevalence of CHF and a total of 29.6% of CHF patients had NIDDM. In multiple logistic regression analysis, CHF was associated with NIDDM [odds ration (OR) = 2.0, 95% confidence interval (CI) - 1.6-2.5] independent of age, sex, family history of diabetes, body mass index, (BMI), waist/hip ratio, and diastolic blood pressure. When only untreated CHF patients were taken into account, the association between CHF and NIDDM was even stronger (OR = 4.0, 95% CI = 3.4-5.8). When untreated CHF patients were grouped into those with low (I and II) and high (III and IV) New York Heart Association (NYHA) classes, the association of CHF and NIDDM was stronger with the worsening of CHF. In a longitudinal study, CHF predicted NIDDM independently of age, sex, family history of diabetes, BMI, waist/hip ratio, systolic and diastolic blood pressure, and therapy for CHF (OR = 1.4, 95% CI = 1.1-1.8). CHF was associated with a higher prevalence of NIDDM and was a risk factor for its development. Elevated FFA concentrations may play a pivotal role.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / diagnosis*
  • Diabetes Mellitus, Type 2 / epidemiology
  • Diabetes Mellitus, Type 2 / etiology
  • Female
  • Heart Failure / complications*
  • Heart Failure / epidemiology
  • Humans
  • Incidence
  • Insulin Resistance*
  • Logistic Models
  • Longitudinal Studies
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prevalence
  • Risk Factors