Abstract

Spatiotemporal disparities exist in the disease burden of non-communicable diseases (NCDs) attributable to kidney dysfunction, which has been poorly assessed. The present study aimed to evaluate the spatiotemporal trends of the global burden of NCDs attributable to kidney dysfunction and to predict future trends. Data on NCDs attributable to kidney dysfunction, quantified using deaths and disability-adjusted life-years (DALYs), were extracted from the Global Burden of Diseases Injuries, and Risk Factors (GBD) Study in 2019. Estimated annual percentage change (EAPC) of age-standardized rate (ASR) was calculated with linear regression to assess the changing trend. Pearson's correlation analysis was used to determine the association between ASR and Sociodemographic Index (SDI) for 21 GBD regions. A Bayesian age-period-cohort (BAPC) model was used to predict future trends up to 2040. Between 1990 and 2019, the absolute number of deaths and DALYs from NCDs attributable to kidney dysfunction increased globally. The death cases increased from 1,571,720 (95% uncertainty interval [UI]: 1,344,420-1,805,598) in 1990 to 3,161,552 (95% UI: 2,723,363-3,623,814) in 2019 for both sexes combined. Both the ASR of death and DALYs increased in Andean Latin America, the Caribbean, Central Latin America, Southeast Asia, Oceania, and Southern Sub-Saharan Africa. In contrast, the age-standardized metrics decreased in the high-income Asia Pacific region. The relationship between SDI and ASR of death and DALYs was negatively correlated. The BAPC model indicated that there would be approximately 5,806,780 death cases and 119,013,659 DALY cases in 2040 that could be attributed to kidney dysfunction. Age-standardized death of cardiovascular diseases (CVDs) and CKD attributable to kidney dysfunction were predicted to decrease and increase from 2020 to 2040, respectively. NCDs attributable to kidney dysfunction remain a major public health concern worldwide. Efforts are required to attenuate the death and disability burden, particularly in low and low-to-middle SDI regions.

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