Impaired renal function in a rural Ugandan population cohort

Abstract

Background: Kidney disease is an important cause of morbidity and mortality globally. However, there are limited data on the prevalence of impaired kidney function in sub-Saharan Africa. We aimed to determine the prevalence of reduced kidney function and associated factors in a rural Ugandan population. Methods: We undertook a study of a representative sample of the General Population Cohort in South-western Uganda. We systematically collected data on cardiovascular disease risk factors, anthropometric measurements and blood tests including haemoglobin, HIV, HbA1c and serum creatinine. The estimated glomerular filtration rate (eGFR) was calculated using the CKD-Epi equation, without the race component of the equation. Results: A total of 5,979/6,397 (93.5%) participants had valid creatinine results. The mean age was 39 years (Range:16-103 years) and 3,627 (60.7%) were female. HIV prevalence was 9.7% and about 40% of the population were pre-hypertensive or hypertensive. The mean serum creatinine level was 0.75 mg/dl (95% CI 0.74–0.75), and the average eGFR was 109.3 ml/min/1.73 m 2 (95% CI 108.8–109.9). The overall prevalence of eGFR <60 ml/min/1.73 m2 was 1.64% (98/5,979) (95% CI 1.34–1.99). Additionally, 4,792(80.2%) were classified as normal eGFR (≥90 ml/min/1.73 m2), 1,089(18.2%) as low eGFR (60–89 ml/min/1.73 m2), 91(1.52%) as moderately reduced eGFR (30–59 ml/min/1.73 m2), 4(0.07%) as severely reduced eGFR (15-29 ml/min/1.73 m2), and 3(0.05%) classified as having kidney failure (eGFR<15 ml/min/1.73 m2). When age-standardised to the WHO Standard Population the prevalence of eGFR<60 ml/min/1.73 m2 was 1.79%. Age above 35 years and the presence of hypertension (OR 2.86, 95% CI 1.15-7.08) and anaemia (OR 2.14, 95% CI 1.12-4.09) were associated with eGFR<60 ml/min/1.73 m2. Conclusion: In a systematic survey of people in rural Uganda, we found a substantial proportion had eGFR<60 ml/min/1.73 m2. More population based studies are needed to further characterize kidney disease in sub-Saharan Africa.

Association of impaired kidney function with mortality in rural Uganda: results of a general population cohort study

“…Those including participants from urban areas in South Africa and Nairobi found similar risk factors for those well established in high-income countries: age, hypertension, diabetes, HIV and female sex 22. However, in cohorts in Malawi and Uganda, where the populations are younger, often living in rural areas and with low levels of smoking, obesity and diabetes showed low prevalence of impaired kidney function and an association with diabetes was found, possibly due to hyperfiltration 14 23. These findings suggest that the aetiology of kidney disease in rural SSA is unclear and highlight the possibility that the mechanism by which kidney function is associated with increased mortality may differ from that in high-income countries.…”

“…For this study we selected a subset of the GPC using information from the 2011–2012 and 2014–2015 rounds of the GPC in which a major disease of interest was CKD and thus baseline information on kidney function was available 14. The outcome was total mortality among participants who had a baseline creatinine measured in either 2011–2012 or 2014–2015.…”

“…We used participants’ height and weight to determine their body mass index (BMI) using weight (kg)/height 2 (m 2 ). We tested for creatinine level using a Cobas e 601 auto analyser (Roche Diagnostics, North America), using the enzymatic method traceable to an isotope dilution mass spectrometry method 14 16. We calculated estimated glomerular filtration rate (eGFR) based on the CKD-Epi creatinine equation without adjustment for ethnicity17 and classified impaired kidney function in categories analogous to those used to define CKD stages 18.…”

“…We calculated estimated glomerular filtration rate (eGFR) based on the CKD-Epi creatinine equation without adjustment for ethnicity17 and classified impaired kidney function in categories analogous to those used to define CKD stages 18. Detailed descriptions of these measurements have been previously published 14…”

“…Thus, we present models adjusted for age and sex, and then additionally for baseline HIV status, hypertension, diabetes mellitus, BMI, smoking, alcohol and marital status. These potential confounders were defined a priori based on existing literature showing their association with low eGFR and mortality in this population14 20 and were included after investigation of collinearity and data sparsity.…”