Ku-Sheng Wu1, Xia Huo, Guang-Hui Zhu. 1. Department of Preventive Medicine, Shantou University Medical College, Shantou, Guangdong, PR China. kswu@stu.edu.cn
Abstract
OBJECTIVES: The purpose of this study is to explore the relationship between esophageal cancer (EC) and soil, vegetation types as well as soil organic carbon densities (SOCD) at depths of 100cm and 20cm in China. METHODS: Database of EC mortality surveyed in 1990-1992 in China was established in Excel. Digital polygon maps of study areas were created in Arc/Info 9.0 software and linked with the database. Soil and vegetation types of sampling areas were extracted from digital maps of soil types, vegetation types and distribution map of EC mortality by using overlay analysis. Mean SOCD at depths of 100cm and 20cm of these areas were calculated, and spearman correlation analysis was used to evaluate the relationship between EC mortality and SOCD. RESULTS: Soil and vegetation types of high and low-risk areas of EC in China were different. There were both negative correlations between EC mortality and SOCD at depths of 100cm and 20cm. The correlation coefficient for men is -0.504 and -0.575 (p< 0.01 respectively), for women is -0.487 and -0.526 (p<0.01 respectively). CONCLUSIONS: EC may correlate to SOCD, soil and vegetation types, which needs further studies. GIS-based spatial techniques can provide an opportunity to connect diseases with ambient environment, and lay a foundation to pursue further investigation into the environmental factors responsible for disease risk.
OBJECTIVES: The purpose of this study is to explore the relationship between esophageal cancer (EC) and soil, vegetation types as well as soil organic carbon densities (SOCD) at depths of 100cm and 20cm in China. METHODS: Database of EC mortality surveyed in 1990-1992 in China was established in Excel. Digital polygon maps of study areas were created in Arc/Info 9.0 software and linked with the database. Soil and vegetation types of sampling areas were extracted from digital maps of soil types, vegetation types and distribution map of EC mortality by using overlay analysis. Mean SOCD at depths of 100cm and 20cm of these areas were calculated, and spearman correlation analysis was used to evaluate the relationship between EC mortality and SOCD. RESULTS: Soil and vegetation types of high and low-risk areas of EC in China were different. There were both negative correlations between EC mortality and SOCD at depths of 100cm and 20cm. The correlation coefficient for men is -0.504 and -0.575 (p< 0.01 respectively), for women is -0.487 and -0.526 (p<0.01 respectively). CONCLUSIONS: EC may correlate to SOCD, soil and vegetation types, which needs further studies. GIS-based spatial techniques can provide an opportunity to connect diseases with ambient environment, and lay a foundation to pursue further investigation into the environmental factors responsible for disease risk.