Risk factors for macrovascular disease in diabetes mellitus: the London follow-up to the WHO Multinational Study of Vascular Disease in Diabetics

Abstract

We have examined the relationship between baseline variables and the incidence of new macrovascular complications amongst the 497 members of the London cohort of the WHO Multinational Study of Vascular Disease in Diabetics over a mean 8.33-year follow-up. In univariate logistic regression analysis the incidence of new ischaemic electrocardiographic abnormality was significantly associated with systolic and diastolic blood pressure, diabetes duration and hypertension in patients with insulin-dependent diabetes, and with smoking in patients with non-insulin-dependent diabetes. New myocardial infarction was associated with systolic blood pressure, plasma cholesterol, proteinuria and smoking in patient with non-insulin-dependent diabetes; there were no significant associations among patients with insulin-dependent diabetes. All new ischaemic heart disease was associated with hypertension in patients with insulin-dependent diabetes, and plasma cholesterol and smoking in patients with non-insulin-dependent diabetes. New cerebrovascular disease was associated with systolic and diastolic blood pressure, ECG abnormality and hypertension. New peripheral vascular disease was associated with smoking. Multivariate analysis showed the following significant associations 1) in patients with insulin-dependent diabetes: ECG abnormality; hypertension, myocardial infarction; smoking, ischaemic heart disease; hypertension, diabetes duration and smoking, 2) in patients with non-insulin-dependent diabetes: ECG abnormality; smoking, myocardial infarction; serum cholesterol, proteinuria and smoking ischaemic heart disease; smoking. For new cerebrovascular disease, proteinuria and ECG abnormality were significant predictors in multivariate analysis. Patients with diabetes share many of the established risk factors for nondiabetic subjects, in addition proteinuria may be of significance in the prediction of macrovascular disease in diabetes.