Objective: The aim was to determine the prevalence, distribution, concordance and associations of chronic kidney disease (CKD) assessed by five glomerular filtration rate (GFR) formulae in urban black residents of Cape Town. Design and method: In this population-based cross-sectional study, stratified for age and gender, data collection included administered questionnaires, clinical measurements and biochemical analyses, including serum creatinine and cystatin C levels. GFR was based on the CKD Epidemiology Collaboration (CKD-EPI) equations (CKD-EPI creatinine (CKD-EPIcr), CKD-EPI cystatin C (CKD-EPIcys), CKD-EPI creatinine-cystatins (CKD-EPIcr-cys)), Modification of Diet in Renal Disease (MDRD) and Cockcroft-Gault formula (CGF). GFR <60 mL/min/1.73 m2 defined CKD. Results: Mean estimated GFR, among 392 men and 700 women, was between 114.0 (CKD-EPIcr) and 135.4 mL/min/1.73 m2 (CGF) in men, and between 107.5 (CKD-EPIcr-cys) and 173.4 mL/min/1.73 m2 (CGF) in women. CKD prevalence ranged from 2.3% (CKD-EPIcr and MDRD) to 5.1% (CKD-EPIcys) in men and 1.6% (CGF) to 6.7% (CKD-EPIcr-cys) in women. Correlations between different estimates of GFR were positive and significant, and there were no significant differences between any two coefficients. The kappa statistic was high between CKD-EPIcr and MDRD (0.934), and CKD-EPIcys and CKD-EPIcr-cys (0.815), but fair-to-moderate between the other equations (0.353–0.565). In the basic regressions, older age and body mass index >30 kg/m2, but not gender, were significantly associated with CKD-EPIcr-defined CKD. In the presence of these three variables, but in separate models, hypertension, heart rate >90 beats/minute, diabetes and increasing low-density lipoprotein cholesterol were significant predictors of prevalent CKD by CKD-EPIcr and MDRD (except for diabetes). Metabolic syndrome, in the model with age and gender only, was significantly associated with CKD-EPIcr- and MDRD-defined CKD. No cardio-metabolic variable was associated with CKD determined by CKD-EPIcys, CKD-EPIcr-cys or CGF. Conclusions: The varying CKD prevalence estimates, on account of different GFR equations used, underscores the need to improve accuracy of CKD diagnoses. Moreover, considering the significant associations of cardio-metabolic diseases with CKD-EPIcr- and MDRD-defined CKD, screening for CKD should be incorporated into the routine assessment of high-risk patients such as those with hypertension or diabetes.
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