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Global health inequalities of chronic kidney disease: a meta-analysis
Rachael Duff1, Omodolapo Awofala1, Muhammad Tahir Arshad1
1Division of Population Health and Genomics, School of Medicine, University of Dundee, Dundee, UK.
Background:
Chronic kidney disease (CKD) is a significant contributor to global morbidity and mortality. This study investigated disparities in age, sex and socio-economic status in CKD and updated global prevalence estimates through systematic review and meta-analysis.
Methods:
Five databases were searched from 2014 to 2022, with 14 871 articles screened, 119 papers included and data analysed on 29 159 948 participants. Random effects meta-analyses were conducted to determine overall prevalence, prevalence of stages 3-5 and prevalence in males and females. Influences of age, sex and socio-economic status were assessed in subgroup analyses and risk of bias assessment and meta-regressions were conducted to explore heterogeneity.
Results:
The overall prevalence of CKD was 13.0% [95% confidence interval (CI) 11.3-14.8] and 6.6% (95% CI 5.6-7.8) for stages 3-5. The prevalence was higher in studies of older populations (19.3% for stages 1-5, 15.0% for stages 3-5) and meta-regression demonstrated an association of age, body mass index, diabetes and hypertension with prevalence of stages 3-5. The prevalence of CKD stages 1-5 was similar in males and females (13.1% versus 13.2%), but the prevalence of stages 3-5 was higher in females (6.4% versus 7.5%). Overall prevalence was 11.4%, 15.0% and 10.8% in low-, middle- and high-income countries, respectively; for stages 3-5, prevalence was 4.0%, 6.7% and 6.8%, respectively. Included studies were at moderate-high risk of bias in the majority of cases (92%) and heterogeneity was high.
Conclusion:
This study provides a comprehensive assessment of CKD prevalence, highlighting important disparities related to age, sex and socio-economic status. Future research should focus on targeted screening and treatment approaches, improving access to care and more effective data monitoring, particularly in low- and middle-income countries.
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