Selenium deficiency is strongly associated with Keshan disease (KD). It is essential to investigate serum selenium levels from the perspective of etiological surveillance and evaluation of the populations at-risk. This research aims to identify areas at high risk of selenium deficiency using spatial epidemiological methods and to provide a scientific basis for targeted selenium supplementation. This cross-sectional study measured serum selenium levels using an atomic fluorescence spectrometer among 6,643 residents in KD endemic and non-endemic counties across China, applying spatial epidemiological methods, including global autocorrelation and local Moran's I analysis, to identify spatial clustering. Additionally, ordinary least squares regression was used to assess the correlation between serum selenium levels and per capita disposable income. The median serum selenium level among participants was 66.69 μg/L. Serum selenium levels of residents in KD endemic areas were significantly lower than those in non-endemic areas. A total of 72 counties were classified as selenium-deficient, 638 as selenium-marginal, and 967 as selenium-sufficient. Spatial clustering analysis identified 375 clusters of low selenium levels. Regression analysis revealed a positive correlation between serum selenium levels and per capita disposable income. The geographical distribution of serum selenium levels exhibits significant spatial clustering. The low-low clustering areas in provinces such as Sichuan, Shaanxi, Gansu and Yunnan should be prioritized for selenium nutrition interventions and surveillance. Furthermore, areas with low incomes may need enhanced strategies for selenium supplementation.
Keywords: Keshan disease; Selenium nutrition; Serum selenium; Spatial clustering; Spatial regression.
© 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.