Epidemiological status, development trends, and risk factors of disability-adjusted life years due to diabetic kidney disease: A systematic analysis of Global Burden of Disease Study 2021

Abstract

Background: Approximately 40% of individuals with diabetes worldwide are at risk of developing diabetic kidney disease (DKD), which is not only the leading cause of kidney failure, but also significantly increases the risk of cardiovascular disease, causing significant societal health and financial burdens. This study aimed to describe the burden of DKD and explore its cross-country epidemiological status, predict development trends, and assess its risk factors and sociodemographic transitions.

Methods: Based on the Global Burden of Diseases (GBD) Study 2021, data on DKD due to type 1 diabetes (DKD-T1DM) and type 2 diabetes (DKD-T2DM) were analyzed by sex, age, year, and location. Numbers and age-standardized rates were used to compare the disease burden between DKD-T1DM and DKD-T2DM among locations. Decomposition analysis was used to assess the potential drivers. Locally weighted scatter plot smoothing and Frontier analysis were used to estimate sociodemographic transitions of DKD disability-adjusted life years (DALYs).

Results: The DALYs due to DKD increased markedly from 1990 to 2021, with a 74.0% (from 2,227,518 to 3,875,628) and 173.6% (from 4,122,919 to 11,278,935) increase for DKD-T1DM and DKD-T2DM, respectively. In 2030, the estimated DALYs for DKD-T1DM surpassed 4.4 million, with that of DKD-T2DM exceeding 14.6 million. Notably, middle-sociodemographic index (SDI) quintile was responsible for the most significant DALYs. Decomposition analysis revealed that population growth and aging were major drivers for the increased DKD DALYs in most regions. Interestingly, the most pronounced effect of positive DALYs change from 1990 to 2021 was presented in high-SDI quintile, while in low-SDI quintile, DALYs for DKD-T1DM and DKD-T2DM presented a decreasing trend over the past years. Frontiers analysis revealed that there was a negative association between SDI quintiles and age-standardized DALY rates (ASDRs) in DKD-T1DM and DKD-T2DM. Countries with middle-SDI shouldered disproportionately high DKD burden. Kidney dysfunction (nearly 100.0% for DKD-T1DM and DKD-T2DM), high fasting plasma glucose (70.8% for DKD-T1DM and 87.4% for DKD-T2DM), and non-optimal temperatures (low and high, 5.0% for DKD-T1DM and 5.1% for DKD-T2DM) were common risk factors for age-standardized DALYs in T1DM-DKD and T2DM-DKD. There were other specific risk factors for DKD-T2DM such as high body mass index (38.2%), high systolic blood pressure (10.2%), dietary risks (17.8%), low physical activity (6.2%), lead exposure (1.2%), and other environmental risks.

Conclusions: DKD markedly increased and varied significantly across regions, contributing to a substantial disease burden, especially in middle-SDI countries. The rise in DKD is primarily driven by population growth, aging, and key risk factors such as high fasting plasma glucose and kidney dysfunction, with projections suggesting continued escalation of the burden by 2030.

Keywords: Diabetic kidney disease; Disability-adjusted life years; Disease burden; Type 1 diabetes; Type 2 diabetes.

Figure 1

Time trend of global DKD prevalence and DALYs from 1990 to 2030. (A) The global prevalence of DKD-T1DM; (B) The global prevalence of DKD-T2DM; (C) The number of DALYs of DKD-T1DM; (D) The number of DALYs of DKD-T2DM. The dashed line indicates the year 2021. The data prior to the dashed line represent the actual statistics from GBD, while the data following the dashed line correspond to the predicted values for the period 2021–2030 (excluding 2021), derived using the nordpred R package (https://rdrr.io/github/haraldwf/nordpred/man/nordpred). DALYs: Disability-adjusted life years; DKD: Diabetic kidney disease; DKD-T1DM: DKD due to type 1 diabetes; DKD-T2DM: DKD due to type 2 diabetes.

Figure 2

Changes in DKD DALYs according to population-level determinants of population growth, aging, and epidemiological change from 1990 to 2021 at the global level and by quintiles of SDI. (A) Changes in DKD-T1DM DALYs; (B) Changes in DKD-T2DM DALYs. The black dot represents the overall value of change contributed by all three components. For each component, the magnitude of a positive value indicates a corresponding increase in DKD DALYs attributed to the component; The magnitude of a negative value indicates a corresponding decrease in DKD DALYs attributed to the related component. DALYs: Disability-adjusted life years; DKD: Diabetic kidney disease; DKD-T1DM: DKD due to type 1 diabetes; DKD-T2DM: DKD due to type 2 diabetes; SDI: Sociodemographic index.

Figure 3

Frontier analysis exploring the relationship between SDI and age-standardized DALYs rate (ASDR) for DKD-T1DM (A and B) and DKD-T2DM (C and D). The frontier line is shown in solid black, which represented the countries or territories with exemplary performance, achieving the lowest DKD burden relative to their SDI. Each point represents a specific country or region in 2021. In (A) and (C), the color scale represents the years from 1990 (depicted in light blue/green) to 2021 (depicted in deep blue/green). In (B) and (D), the top 15 countries and territories with the largest effective difference (largest DKD DALYs gap from the frontier) are labeled in black. The direction of ASDR change from 1990 to 2021 is indicated by the color of the dots, with red dots indicate a decrease and blue dots indicate an increase. DALYs: Disability-adjusted life years; DKD: Diabetic kidney disease; DKD-T1DM: DKD due to type 1 diabetes; DKD-T2DM: DKD due to type 2 diabetes; SDI: Sociodemographic index.