Spatially Filtered Multilevel Analysis on Spatial Inequality of Tuberculosis in Gyeongsangbuk-do, Korea

Abstract

Objectives: This study aims to identify the spatial inequality of tuberculosis (TB) and related socio-environmental factors in Gyeongsangbuk-do, Korea. Methods: This study explains TB incidences in a spatial perspective. A spatial multilevel regression model was applied to account for the spatial inequality of TB and related factors. Applied socio-environmental factors were average age, population density, Normalized Difference Built-up Index (NDBI), particulate matter (PM10), medical insurance, financial independence rate, and medical doctors per 1,000 people. Results: This study finds evident spatial inequality of TB in Gyeongsangbuk-do. Most TB hotspots are identified around Yeongyang-gun, the area with the lowest socio-economic status in Korea. The regression result shows that level 1 factors (Average age, NDBI, PM10) and level 2 factors (medical insurance, financial independence rate) were statistically significant related to TB incidences. Furthermore, spatial filtering applied to multilevel regression accounts for spatial autocorrelation of TB incidence. Conclusions: Regional socio-economic and demographic conditions in Gyeongsangbuk-do influence TB incidences. Given low expectations on Gyeongsangbuk-do’s socio-economic and demographic growth, reducing the spatial inequality of TB would be challenging.