Breast cancer (BC) had the highest incidence of all cancers in Chinese women. However, studies on spatial pattern and environmental drivers of BC were still lacked as they were either limited in a small area or few considered the comprehensive impact of multiple risk factors. In this study, we firstly performed spatial visualization and the spatial autocorrelation analysis based on Chinese women breast cancer incidence (BCI) data of 2012-2016. Then, we explored the environmental drivers related to BC by applying univariate correlation analysis and geographical detector model. We found that the BC high-high clusters were mainly distributed in the eastern and central regions, such as Liaoning, Hebei, Shandong, Henan, and Anhui Provinces. The BCI in Shenzhen was significantly higher than other prefectures. Urbanization rate (UR), per capita GDP (PGDP), average years of school attainment (AYSA), and average annual wind speed (WIND) had higher explanatory power on spatial variability of the BCI. PM10, NO2, and PGDP had significant nonlinear enhanced effect on other factors. Besides, normalized difference vegetation index (NDVI) was negatively associated with BCI. Therefore, high socioeconomic status, serious air pollution, high wind speed, and low vegetation cover were the risk factors for BC. Our study may able to provide evidence for BC etiology research and precise identification of areas requiring focused screening.
Keywords: Breast cancer incidence (BCI); China; Environmental factors; Geographical detector; Spatial pattern.
© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.