Glycated Hemoglobin, Fasting Insulin and the Metabolic Syndrome in Males. Cross-Sectional Analyses of the Aragon Workers' Health Study Baseline

Abstract

Background and Aims Glycated hemoglobin (HbA1c) is currently used to diagnose diabetes mellitus, while insulin has been relegated to research. Both, however, may help understanding the metabolic syndrome and profiling patients. We examined the association of HbA1c and fasting insulin with clustering of metabolic syndrome criteria and insulin resistance as two essential characteristics of the metabolic syndrome. Methods We used baseline data from 3200 non-diabetic male participants in the Aragon Workers' Health Study. We conducted analysis to estimate age-adjusted odds ratios (ORs) across tertiles of HbA1c and insulin. Fasting glucose and Homeostatic model assessment - Insulin Resistance were used as reference. Here we report the uppermost-to-lowest tertile ORs (95\% CI). Results Mean age (SD) was 48.5 (8.8) years and 23\% of participants had metabolic syndrome. The ORs for metabolic syndrome criteria tended to be higher across HbA1c than across glucose, except for high blood pressure. Insulin was associated with the criteria more strongly than HbA1c and similarly to Homeostatic model assessment - Insulin Resistance (HOMA-IR). For metabolic syndrome, the OR of HbA1c was 2.68, of insulin, 11.36, of glucose, 7.03, and of HOMA-IR, 14.40. For the clustering of 2 or more non-glycemic criteria, the OR of HbA1c was 2.10, of insulin, 8.94, of glucose, 1.73, and of HOMA-IR, 7.83. All ORs were statistically significant. The areas under the receiver operating characteristics curves for metabolic syndrome were 0.670 (across HbA1c values) and 0.770 (across insulin values), and, for insulin resistance, 0.647 (HbA1c) and 0.995 (insulin). Among non-metabolic syndrome patients, a small insulin elevation identified risk factor clustering. Conclusions HbA1c and specially insulin levels were associated with metabolic syndrome criteria, their clustering, and insulin resistance. Insulin could provide early information in subjects prone to develop metabolic syndrome.