Glucose intolerance is predicted by the high Fasting Insulin-to-Glucose ratio

Diabetes Metab. 2001 Apr;27(2 Pt 1):117-21.

Abstract

Objective: To determine whether impaired glucose tolerance (IGT) is predicted by high Fasting Insulin-to-Glucose (FIG) ratio and to establish its correlation with insulin resistance and fasting insulin.

Material and methods: A population-based three-year follow-up study was performed. The target population consisted of healthy volunteers, men and non-pregnant women aged 30 years or over. Participants were required to have normal referenced ranges of OGTT and blood pressure. Previous diagnosis of chronic diseases was an exclusion criterion. At baseline and at the 3-yr of follow-up, an OGTT was performed. The ratio of serum Fasting Insulin (microUI/ml)/Fasting Glucose (mg/dl) was used to calculate the FIG ratio. Insulin action and secretion were estimated by HOMA and Insulinogenic index, respectively.

Results: The FIG ratio was directly correlated with the HOMA index (r=0.83, p<0.01) and fasting insulin (r=0.95, p<0.001). Multivariate logistic regression analysis showed that IGT was more likely to develop in subjects with high FIG ratio (RR 5.01; CI(95%) 1.9-12.2, p=0.02), high HOMA index (RR 6.1; CI(95%) 2.1-11.1, p=0.01), and fasting hyperinsulinemia (RR 4.7 CI(95%) 2.7-13.2, p<0.05). The cutoff point of FIG ratio for determining the risk of developing IGT was 0.25 +/- 0.05.

Conclusions: The FIG ratio could be a reliable alternative for the screening of apparently healthy subjects in high risk groups.

Publication types

  • Multicenter Study

MeSH terms

  • Adult
  • Blood Glucose / metabolism*
  • Blood Pressure*
  • Body Mass Index
  • Cohort Studies
  • Female
  • Follow-Up Studies
  • Glucose Intolerance / blood*
  • Glucose Intolerance / diagnosis*
  • Glucose Tolerance Test*
  • Humans
  • Insulin / blood*
  • Longitudinal Studies
  • Male
  • Mexico
  • Multivariate Analysis
  • Patient Selection
  • Predictive Value of Tests
  • Reference Values
  • Regression Analysis
  • Time Factors

Substances

  • Blood Glucose
  • Insulin