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The strategy of the “Belt and Road” initiative aims not only to promote the cooperation and the development of economic trade, but also to boost the integration and development in multiple fields—especially in the field of health. This paper explores the health levels of member-states in the Belt and Road initiative from the perspective of regional differences and spatial patterns. Data from the 68 member-states in the Belt and Road initiative were selected from the statistical data on disease and socioeconomics in all countries from the 2015 publication by the World Bank and the World Health Organization. Health indicators that can reflect health levels of member states were selected. Moran’s I and Getis-Ord Gi* were used to analyze the spatial clustering and hot/cold spots of the health status. After that a novel spatial statistical method “geographical detector” was used to analysis the spatial stratified heterogeneity of the selected health indicators. The result showed that the health level of the member states fluctuated around the world average and varied greatly within the member states. The health status of the member states showed spatial clustering, and the q-statistics of the geographical detector confirmed that the health status demonstrated statistically significant spatial heterogeneity for different continent the member states reside. In general, member states in Europe and Oceania demonstrated higher health status, while those in South Asia, Southeast Asia, Africa and part of Middle East have lower health status. In particular, special attention should be paid to control communicable diseases in African member states. Different regions and member states face different kinds of health threats in various degrees. Member states should strengthen health cooperation between themselves and work closely with other countries to make the “belt and road” a healthy road. [ABSTRACT FROM AUTHOR]

Understanding the relationship between urbanization and pollutant emissions in China is of great significance to realizing sustainable development. Previous studies focused on the relationship between urbanization and air pollutants in China. However, the relationship between urbanization and industrial or domestic pollutants remains unclear. In this paper, we used the stochastic impacts by regression on population, affluence, and technology (STIRPAT) model to examine whether an environmental Kuznets curve (EKC) relationship exists between urbanization and pollutant emissions, including industrial wastewater, industrial SO 2 , industrial soot (dust), and domestic garbage based on panel data for 277 prefecture-level cities in China from 2003 to 2015. We found that industrial soot (dust) emissions and domestic garbage increased by 83.0% and 43.5%, respectively, whereas industrial wastewater discharge and SO 2 emissions decreased by 7.4% and 10.5%, respectively. The identified inverted U-shaped relationship between the urbanization ratio (i.e., percentage of the population living in urban areas) and industrial pollutants supports the EKC hypothesis. However, the domestic garbage volume increased with increasing urbanization ratio. In the future, more attention should be paid to the prevention and control of domestic pollution. In addition, small and medium-sized cities should reduce pollutant emissions and determine effective ways to achieve sustainable development. • The EKC hypothesis for industrial/domestic pollution in China was tested. • An inverted U-shaped relation was identified between urbanization and industrial pollution. • Domestic pollution increased along urbanization ratio in China. • Large cities started to experience declines in pollution after 2010. [ABSTRACT FROM AUTHOR]