BACKGROUND: Although screening programs for chronic kidney disease (CKD) may be of great value, these programs are not yet implemented in the Democratic Republic of Congo. This study focused on proteinuria and examined its prevalence in terms of the number needed to screen for the different risk factors of CKD. Such knowledge would guide the utility of population screening to prevent end-stage renal disease. METHODS: A cross-sectional survey was conducted in Kinshasa on the Second World Kidney Day. A sample of 3,018 subjects was interviewed and the following measurements were performed: blood pressure, body mass index, glycemia and urine protein. Logistic regression analysis was used to identify determinants of proteinuria. RESULTS: The prevalence of proteinuria was 17.1% (95% CI 15.8-18.6). Other CKD risk factors identified were: hypertension, diabetes mellitus, obesity and metabolic syndrome. To identify 1 case of proteinuria, one would need to screen 4 persons with diabetes, 5 persons with hypertension, 4 subjects having metabolic syndrome, 5 persons aged >or=72 years and 9 persons without any of the conditions mentioned above. Age, overweight and diabetes were the strongest factors associated with proteinuria. CONCLUSIONS: This study indicates that proteinuria and traditional risk factors for CKD are very prevalent in Kinshasa. Realistic policies to stem these conditions should be a public health priority. (c) 2008 S. Karger AG, Basel.
BACKGROUND: Although screening programs for chronic kidney disease (CKD) may be of great value, these programs are not yet implemented in the Democratic Republic of Congo. This study focused on proteinuria and examined its prevalence in terms of the number needed to screen for the different risk factors of CKD. Such knowledge would guide the utility of population screening to prevent end-stage renal disease. METHODS: A cross-sectional survey was conducted in Kinshasa on the Second World Kidney Day. A sample of 3,018 subjects was interviewed and the following measurements were performed: blood pressure, body mass index, glycemia and urine protein. Logistic regression analysis was used to identify determinants of proteinuria. RESULTS: The prevalence of proteinuria was 17.1% (95% CI 15.8-18.6). Other CKD risk factors identified were: hypertension, diabetes mellitus, obesity and metabolic syndrome. To identify 1 case of proteinuria, one would need to screen 4 persons with diabetes, 5 persons with hypertension, 4 subjects having metabolic syndrome, 5 persons aged >or=72 years and 9 persons without any of the conditions mentioned above. Age, overweight and diabetes were the strongest factors associated with proteinuria. CONCLUSIONS: This study indicates that proteinuria and traditional risk factors for CKD are very prevalent in Kinshasa. Realistic policies to stem these conditions should be a public health priority. (c) 2008 S. Karger AG, Basel.
Authors: Ernest K Sumaili; Eric P Cohen; Chantal V Zinga; Jean-Marie Krzesinski; Nestor M Pakasa; Nazaire M Nseka Journal: BMC Nephrol Date: 2009-07-21 Impact factor: 2.388
Authors: John W Stanifer; Venance Maro; Joseph Egger; Francis Karia; Nathan Thielman; Elizabeth L Turner; Dionis Shimbi; Humphrey Kilaweh; Oliver Matemu; Uptal D Patel Journal: PLoS One Date: 2015-04-17 Impact factor: 3.240
Authors: Sophie P Maule; Danielle C Ashworth; Hannah Blakey; Charlotte Osafo; Morara Moturi; Lucy C Chappell; Kate Bramham; Jack Milln Journal: Kidney Int Rep Date: 2020-05-26