Spatiotemporal Distribution and Evolution of Digestive Tract Cancer Cases in Hefei, China Since 2012

Abstract Background: Cancer has become the major killer of deaths among Chinese urban and rural residents, and about 50% of new cases are from liver cancer, gastric cancer, and esophageal cancer. Digestive tract cancer(DTC) has received widespread attention due to its poor treatment effect and high mortality rate, as well as severe physical, psychological, mental, and economic trauma to patients and their families. Methods: The data on DTC cases in Lujiang County in Hefei, China, were downloaded from the Data Center of the Center for Disease Control and Prevention in Hefei, Anhui Province, China, while the demographic data were sourced from the demographic department in China. Systematic statistical analyses, including the spatial empirical Bayes smoothing, spatial autocorrelation, hotspot statistics, and Kulldorff's retrospective space-time scan, were used to identify the spatial and spatiotemporal clusters of DTC. GM(1,1) and standard deviation ellipses were then applied to predict the future evolution of the spatial pattern of the DTC cases in Lujiang County. Results: DTC in Lujiang County had obvious spatiotemporal clustering. The spatial distribution of DTC cases increases gradually from east to west in the county in a stepwise pattern. The peak of DTC cases occurred in 2012-2013, and the high-case spatial clusters were located mainly in the northwest of Lujiang County. At the 1% significance level, two spatiotemporal clusters were identified. From 2012 to 2017, the cases of DTC in Lujiang County gradually shifted to the high-incidence area in the northwest, and the spatial distribution range experienced a process of “dispersion-clustering”. The cases of DTC in Lujiang County will continue to move to the northwest from 2018 to 2025, and the predicted spatial clustering tends to be more obvious. Conclusions: High-incidence time of DTC was 2012-2013, and the number of cases increased from east to west in Lujiang County. High clusters were mostly located in the northwestern area and agglomerated from southeast to northwestern especially after 2014.