ArticleBMC nephrology2026
Geographical differences in the prevalence of diabetic kidney disease in middle-aged and elderly patients in China: an analysis based on the Bayesian conditional autoregressive model.
Article in BMC nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- The cholesterol, high-density lipoprotein, and glucose index and its derived indices predict diabetic kidney disease development and progression: evidence from two nationwide cohorts and a biopsy-proven clinical cohort.Cardiovascular diabetology · 2026Article
- Editorial: Exerscience: exploring physical activity's role in diabetes and its complications.Frontiers in endocrinology · 2026Article
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7 authors.
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Abstract
backgroundDiabetic kidney disease (DKD) has become the primary cause of end-stage kidney disease in patients in China. However, very little is known about the spatial correlation in the risk of DKD. This study aims to assess the burden of DKD among middle-aged and elderly individuals and maps the associated geographic differences.
methodsWe analyzed data from 14,079 participants aged 45 years or older of the China Health and Retirement Longitudinal Study (CHARLS). DKD is defined as the presence of chronic kidney disease in the context of diabetes. To improve representativeness and accuracy, population weights covering 28 provinces were applied, and a Bayesian conditional autoregressive model incorporating the spatial adjacency matrix effect was used to estimate DKD prevalence and the corresponding 95% Bayesian credible intervals. Risk factors potentially underpinning geographic variation were first screened with logistic regression, and their province-specific spatial effects were subsequently explored within the Bayesian framework.
resultsAmong the 28 provinces in mainland China, the prevalence of DKD in various provinces in 2015 ranged from 5.99% to 30.31%. The top three provinces were Guangxi (30.31%), Jilin (28.38%), and Sichuan (27.48%), while the bottom decile included Fujian, Shannxi, and Guizhou. The high prevalence of DKD is concentrated in the northwest region, showing the characteristic of ‘high–high clusters’, while the prevalence is low in the eastern coastal areas and southern provinces of China, characterized by a low–low cluster. Significant risk factors for DKD including age, very poor self-reported health, and cardiovascular disease. The risk effects of these factors showed heterogeneity across provinces.
conclusionOur findings reveal marked spatial heterogeneity in DKD burden among middle-aged and elderly adults in China, with high-high clusters in the northwest and low-low clusters along eastern and southern provinces. Region-specific strategies and sustained spatial surveillance are essential to promote equity in prevention and management.
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