Geospatial Association between Keshan Disease and Selenoprotein P in Heilongjiang Province: A Bivariate Spatial Autocorrelation Analysis.

Abstract

Keshan disease, a condition endemic to China, has been associated with selenium deficiency. However, spatial epidemiological research that integrates Keshan disease prevalence with selenium nutrition remains limited. This study aimed to explore the bivariate spatial autocorrelation between Keshan disease prevalence and serum selenoprotein P levels in Heilongjiang Province, in order to provide evidence for disease prevention and control. Prevalence data for all forms of Keshan disease were obtained through a national surveillance project and analyzed using spatial empirical Bayesian smoothing. Serum selenoprotein P levels were measured using enzyme-linked immunosorbent assay. Bivariate spatial autocorrelation analyses were conducted to assess the relationship between selenoprotein P levels and the prevalence of overall Keshan disease, chronic Keshan disease, and latent Keshan disease. Local spatial autocorrelation analysis of selenoprotein P levels revealed three low-low clusters, one low-high cluster, five high-low clusters, and one high-high cluster. No bivariate global spatial autocorrelation was observed between selenoprotein P levels and the prevalence of overall Keshan disease, chronic Keshan disease, or latent Keshan disease. In total, eight local clusters were identified, including three high-low and five low-high clusters. Nine clusters were identified as key regions for Keshan disease. The risk of Keshan disease among low-selenium nutrition groups was concentrated in three clusters. Residents living in or adjacent to these regions should be prioritized for prevention and control interventions.