SUN-192 EPIDEMIOLOGY OF CHRONIC KIDNEY DISEASE IN EAST AND SOUTHERN SUB-SAHARAN AFRICA - A MULTI-CENTER STUDY FROM UGANDA, MALAWI AND SOUTH AFRICA (THE ARK STUDY)

Abstract

Little is understood about the epidemiology of chronic kidney disease (CKD) in sub-Saharan Africa (SSA). Prevalence data from our region may overestimate CKD because studies are relatively small and convenience samples with those at high risk for CKD. This study comprises a collaboration between three Health and Demographic Surveillance sites in Uganda (rural), Malawi (one rural , one urban) and South Africa (rural). Our aim was to determine a country-specific CKD population prevalence and additionally, after pooling data, to jointly determine CKD prevalence for eastern and southern SSA. We harmonized protocols across study sites and randomly selected a population-based sample of Africans aged 15-103 years who were screened for risk factors for CKD. KDIGO criteria were used to diagnose CKD based on serum creatinine, estimating glomerular filtration rate using the CKD-EPI equation and albuminuria (ACR>3.0mg/mmol). We are currently rescreening those with eGFR <60ml/min/1.73m2 and/or albuminuria to confirm CKD at a minimum follow up period of 3 months. We assessed sociodemographic and phenotypic risk using assets-based household scores, CKD risk questionnaires, height, weight, BMI, hip/waist circumference, blood glucose, cholesterol, haemoglobin, creatinine, urine dipstick analysis and urine microscopy for urinary schistosomiasis. Table 1Results across all three sites (Malawi sample was age–stratified so weighted towards older people)Variable N (%)UgandaMalawi RuralMalawi UrbanSouth AfricaSample size5979290623582023Median age (IQR) years39 (16-103)41 (39-52)37 (27-47)35 (27-47)Male2771 (39.3%)1325 (45.6%)969 (41.1%)853 (42.2%)BMI (kg/m2) Median and IQR22.6 (16.3-39.8)21.9 (20.1-24.2)23.9 (21.2-27.8)26.0 (22.0-30.0)Hypertension*617 (14.8%)457/2903 (15.7%)522/2358 (22.1%)Diabetes Mellitus#89 (2.1%)106/2906 (3.7%)127/2356(5.4%)151 (7.5%)HIV prevalence578 (9.7%)241/1719 (14.0%)212/2163 (9.8%)399/2317(17.0%)eGFR<60ml/min/1.73m2 Age-standardised98 (1.6%)50/2906 (1.7%) (1.8%)22/2358 (0.9%) (1.5%)32 (1.6%)ACR>3.0mg/mmolN/AN/AN/A239 (11.8%)Mean eGFR (SD) ml/min/1.73m2109.3105.5 (21.6)108.0 (19.1)112.07 (18.74)∗hypertension: SBP>=140 and/or DBP>=90 or history of hypertension, currently taking treatment;.#diabetes mellitus: South Africa - random glucose >11.0mmol/l, or history of diabetes mellitus and taking medication, Malawi- fasting glucose >=7.0mmol/L or history of diabetes Open table in a new tab ∗hypertension: SBP>=140 and/or DBP>=90 or history of hypertension, currently taking treatment;. #diabetes mellitus: South Africa - random glucose >11.0mmol/l, or history of diabetes mellitus and taking medication, Malawi- fasting glucose >=7.0mmol/L or history of diabetes The observed population prevalences for CKD may be lower than expected because data are not all age adjusted, end stage kidney disease is terminal and those who cannot access treatment will inevitably die and eGFR may be overestimated using the CKD-EPI equation, whose performance is known to be sub-optimal in African populations. In this study we will determine true population prevalence of CKD in countries from Eastern and Southern Africa. At present, we await results from the repeat at screening to confirm CKD, using KDIGO criteria. This data will make a critical contribution to the region for SSA to direct future science, promote informed decision-making for health policy in relation to screening, prevention and management of CKD, which is particularly relevant as those who progress to ESKD have very few treatment options.