Obesity is a risk marker for progressive renal function loss in patients with known renal disease. There is, however, increasing evidence that obesity may also damage the kidney in otherwise healthy subjects. There appears to be an intriguing parallel between the renal effects of obesity and those of diabetes. First, an increased renal blood flow and glomerular filtration rate has been described in obesity and, second, microalbuminuria is found to be related to obesity. These two events are known to predict future loss of renal function in diabetes. The mechanism responsible for the renal damage in obesity has not been established but there is evidence suggesting that this might be related to both hormonal changes as well as low-grade inflammation.
Microalbuminuria is associated with both an increased prevalence of cardiovascular risk factors and greater renal and cardiovascular morbidity. We questioned whether in the general population such associations can be found at lower levels of urinary albumin excretion than that of classically defined microalbuminuria. To that purpose urinary albumin concentration was measured in 40619 subjects aged 28 to 75 years. The subjects filled in a questionnaire on cardiovascular risk factors and events and were divided in deciles according to their urinary albumin concentration. Smoking was associated with albuminuria in the fifth or higher decile of urinary albumin concentration, that is with an albumin concentration of 5.1 mg/l and higher. The lower cut-off point for a positive association with hypertension was 8.8 mg/l, and for diabetes 11.2 mg/l. Family history for cardiovascular disease and hyperlipidaemia were not associated with albuminuria. We conclude that urinary albumin concentrations far below the microalbuminuric range are associated with increased prevalence of established cardiovascular risk factors. Family history for cardiovascular disease and hyperlipidaemia seems to behave differently. These data emphasize the need for more studies on the impact of albuminuria on the prediction of cardiovascular and renal disease in the general population.
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