Bivariate Spatial Autocorrelation Analysis of Keshan Disease and Hair Selenium of Residents in Heilongjiang Province,...

Bivariate spatial autocorrelation between the prevalence of Keshan disease (KD) and hair selenium levels in residents of KD-endemic areas has not previously been reported. In this study, we investigated the types of spatial clusters between hair selenium levels and the prevalence of KD among residents of KD-endemic areas in Heilongjiang Province, using a bivariate spatial autocorrelation analysis. Population demographic information and hair samples were obtained using questionnaires and sample collection, respectively. Hair selenium levels were determined using hydride generation atomic fluorescence spectroscopy. Bivariate spatial autocorrelation analysis was performed using Geoda 1.22.0.2. The results revealed that the prevalence of individuals with chronic Keshan disease (CKD) with hair selenium levels in the high-low (HL) cluster was greatest in Shangzhi. Furthermore, the prevalences of KD-hair selenium levels, CKD-hair selenium levels, and latent Keshan disease (LKD)-hair selenium levels were classified into low-high (LH) clusters in Lindian, Saertu, Mashan, Dongning, Ningan, and Lanxi. Four high-selenium areas, centered on Lindian, Saertu, Mashan, and Ningan, and one low-selenium area, centered on Shangzhi, were located in Heilongjiang Province. Thus, the residents of KD-endemic areas in Heilongjiang Province remain at risk of selenium deficiency. Additionally, the geographical scope of HL clusters in terms of the number of counties was much smaller than that of LH clusters. This study provides a basis for the identification of KD-endemic areas with low selenium levels and the development of precise prevention and control strategies for KD in Heilongjiang Province.