Objectives While increasing attention is paid to the rising prevalence of chronic diseases in Africa, there is little focus on chronic kidney disease (CKD). This systematic review assesses CKD burden… Click to show full abstract
Objectives While increasing attention is paid to the rising prevalence of chronic diseases in Africa, there is little focus on chronic kidney disease (CKD). This systematic review assesses CKD burden among the general population and high-risk groups on the entire African continent. Design, setting and participants We searched Medline and PubMed databases for articles published between 1 January 1995 and 7 April 2017 by sensitive search strategies focusing on CKD surveys at the community level and high-risk groups. In total, 7918 references were evaluated, of which 7766 articles were excluded because they did not meet the inclusion criteria. Thus, 152 studies were included in the final analysis. Outcome measurement The prevalence of CKD in each study group was expressed as a range and pooled prevalence rate of CKD was calculated as a point estimate and 95% CI. No meta-analysis was done. Data were presented for different populations. Results In the community-level studies, based on available medium-quality and high-quality studies, the prevalence of CKD ranged from 2% to 41% (pooled prevalence: 10.1%; 95% CI 9.8% to 10.5%). The prevalence of CKD in the high-risk groups ranged from 1% to 46% (pooled prevalence: 5.6%; 95% CI 5.4% to 5.8%) in patients with HIV (based on available medium-quality and high-quality studies), 11%–90% (pooled prevalence: 24.7%; 95% CI 23.6% to 25.7%) in patients with diabetes (based on all available studies which are of low quality except four of medium quality) and 13%–51% (pooled prevalence: 34.5%; 95 % CI 34.04% to 36%) in patients with hypertension (based on all available studies which are of low quality except two of medium quality). Conclusion In Africa, CKD is a public health problem, mainly attributed to high-risk conditions as hypertension and diabetes. The poor data quality restricts the validity of the findings and draws the attention to the importance of designing future robust studies.
               
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