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.

Jiaqi Li, Keyu Guo, Junlin Qiu, Song Xue, Linhua Pi, Xia Li, Gan Huang, Zhiguo Xie, Zhiguang Zhou
Author Information
  1. Jiaqi Li: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  2. Keyu Guo: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  3. Junlin Qiu: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  4. Song Xue: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  5. Linhua Pi: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  6. Xia Li: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  7. Gan Huang: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  8. Zhiguo Xie: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.
  9. Zhiguang Zhou: Department of Metabolism and Endocrinology, National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China.

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 2,228,000 to 3,876,000) and 173.6% (from 4,123,000 to 11,279,000) 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 GBD 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% 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.

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Word Cloud

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