Epidemiological analysis of chronic kidney disease from 1990 to 2019 and predictions to 2030 by Bayesian age-period-cohort analysis

BackgroundChronic Kidney Disease (CKD) has emerged as a significant global health issue. This study aimed to reveal and predict the epidemiological characteristics of CKD.MethodsData from the Global Burden of Disease Study spanning the years 1990 to 2019 were employed to analyze the incidence, prevalence, death, and disability-adjusted life year (DALY) of CKD. Joinpoint analysis assessed epidemiological trends of CKD from 1990 to 2019. An age-period-cohort model evaluated risk variations. Risk factor analysis uncovered their influences on DALYs and deaths of CKD. Decomposition analysis explored the drivers to CKD. Frontier analysis evaluated the correlations between CKD burden and the sociodemographic index (SDI). A Bayesian Age-Period-Cohort model was employed to predict future incidence and death of CKD.ResultsIn 2019, there were 18,986,903 incident cases, 697,294,307 prevalent cases, 1,427,232 deaths, and 41,538,592 DALYs of CKD globally. Joinpoint analysis showed increasing age-standardized rates of CKD incidence, prevalence, mortality, and DALY from 1990 to 2019. High systolic blood pressure significantly contributed to CKD-related deaths and DALYs, particularly in the high SDI region. Decomposition analysis identified population growth as the primary driver of CKD incident cases and DALYs globally. Countries like Nicaragua showed the highest effective differences, indicating room for improvement in CKD management. By 2030, while incident cases of CKD were predicted to rise, the global deaths might decrease.ConclusionsThe study revealed a concerning upward trend in the global burden of CKD, emphasizing the need for targeted management strategies across different causes, regions, age groups, and genders.