Socioeconomic Disparities and Spatiotemporal Dynamics of Kidney Cancer Burden: A Global Analysis of Modifiable Risk Factors and Disease Epidemiology, 2017-2021

Background: The worldwide burden of kidney cancer is characterized by vast variability by societal and geographical context; however, systematic assessments of modifiable risk factors within the developmental stratum are scarce. In this analysis, we quantify the distribution of kidney cancer burden across space and time, by socioeconomic factors, and for the known risk factors that contribute to kidney cancer burden globally using the GBD 2015 estimates. Methods: Using Global Burden of Disease (GBD) 2021 data covering 204 countries, we examined age-standardized incidence rate (ASR), mortality rate and years of life lost (YLLs) from 2017–2021. Multilevel regression, Joinpoint trend, and Bayesian spatiotemporal analyses were used to investigate correlations with the Socio-demographic Index (SDI). Attribution was made using population-attributable fractions (PAFs) for smoking, obesity, and hypertension. Spatial clustering and age-sex differences were calculated using Moran’s I, Getis-Ord Gi, and multivariable Poisson regression. Results: Global occurrence of kidney cancer slightly declined (−3.0%), but increased in low-SDI areas (+1.2%), indicating the emergence of risk concentration. High SDI countries experienced a J shaped relationship between SDI and mortality (threshold: SDI=0.65), whereas low-middle SDI regions were associated with a linear reduction in mortality (β=−1.21 per 0.1 SDI,p<0.001). Metabolic risks were the leading cause for DALYs in high-SDI countries (22.9% [22.6–23.3]), but smoking was highest in emerging economies (high-middle SDI:12.0% [11.7–12.4]). Spatial hotspots included parts of Eastern Europe (DALYs:100.14/100,000) and Latin America, largely due to obesity and health services gaps. Male-to-female mortality ratios increased with age (1.8–3.3-times), worse in low-SDI regions due to delayed diagnosis (PAF:33.7% for healthcare access). Bayesian predictions flagged rising East Asian hotspots (China:8.5 DALYs/100k by 2030) coalescing with urbanization-borne metabolic risks. Concusions: Kidney cancer burden is a prototype of divergent epidemiologic transitions requiring SDI-stratified interventions: metabolic risk mitigation in high socio-demographic regions and tobacco control combined with strengthening health care access in low-SDI areas. Furthermore, the spatial-temporal mapping of risk factor gradients yields health policy recommendations to precision public health responses.