To determine the prevalence of microalbuminuria in a mixed, thnic population and to find the extent that ethnic variation in microalbuminuria can be explained by abnormal glucose metabolism, obesity, hypertension, hypertriglyceridemia, and life-style factors.
Urinary albumin concentrations were measured in 5467 middle-aged Maori, Pacific Islander, and European workers who participated in a health-screening survey of 46 New Zealand companies. Participants provided a first-voided, morning urine sample; had a 75-g oral glucose tolerance test; had weight, height, and blood pressure measured; and completed a self-administered questionnaire about past medical history and sociodemographic status.
A significantly higher prevalence of microalbuminuria was found in individuals with new cases of diabetes mellitus (24.1%), in cases of diabetes mellitus previously diagnosed (20.6%), and in those with impaired glucose tolerance (16.1%) compared with nondiabetic individuals (4.0%). Moreover, in the general population, a piecewise linear relationship was detected between albuminuria and plasma glucose with significant changes of slope corresponding with 2 h plasma glucose concentrations (95% confidence interval) of 6.7 (6.4–7.0) and 9.2 (8.6–9.8) mM, respectively. After adjusting for sex, obesity, hypertension, hypertriglyceridemia, cigarette smoking, and heavy alcohol consumption in a multivariate model, glycemia was the most significant determinant of urinary albumin concentrations in all three ethnic groups. However, blood glucose concentrations did not completely explain the higher relative risk (95% confidence interval) of microalbuminuria in Maori (5.97; 4.48–7.78) and Pacific Islander (5.33; 4.13–6.87) workers compared with European workers.
Of the variables investigated, hyperglycemia was the most important factor explaining the high prevalence of microalbuminuria in Maori and Pacific Islander workers compared with the European workers. However, only 14.9% of the variation in urinary albumin concentrations was found in our multivariate model, and we have speculated on the contribution of other factors such as diet and coexisting renal diseases.