Bayesian mapping of neural tube defects prevalence in Heshun County, Shanxi Province, China during 1998～2001  

作　　者：CHI Wen-xue WANG Jin-feng LI Xin-hu ZHENG Xiao-ying LIAO Yi-lan 

机构地区：[1]China University of Geosciences, Beijing 100083, China [2]Institute of Geographical Sciences and Nature Resources Research, Chinese Academy of Sciences, Beo＇ing 100101, China [3]Institute of Population Research, Peking University, Beijing 100871, China

出　　处：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2007年第6期921-925,共5页浙江大学学报（英文版）A辑（应用物理与工程）

基　　金：Project supported by the National Natural Science Foundation of China (Nos. 40471111 and 70571076);the Ministry of Science and Technology of China (No. 2001CB5103)

摘　　要：Objective: To estimate the prevalence rates of neural tube defects (NTDs) in Heshun County, Shanxi Province, China by Bayesian smoothing technique. Methods: A total of 80 infants in the study area who were diagnosed with NTDs were analyzed. Two mapping techniques were then used. Firstly, the GIS software ArcGIS was used to map the crude prevalence rates. Secondly, the data were smoothed by the method of empirical Bayes estimation. Results: The classical statistical approach produced an extremely dishomogeneous map, while the Bayesian map was much smoother and more interpretable. The maps produced by the Bayesian technique indicate the tendency of villages in the southeastern region to produce higher prevalence or risk values. Conclusions: The Bayesian smoothing technique addresses the issue of heterogeneity in the population at risk and it is therefore recommended for use in explorative mapping of birth defects. This approach provides procedures to identify spatial health risk levels and assists in generating hypothesis that will be investigated in further detail.Objective： To estimate the prevalence rates of neural tube defects （NTDs） in Heshun County, Shanxi Province, China by Bayesian smoothing technique. Methods： A total of 80 infants in the study area who were diagnosed with NTDs were analyzed. Two mapping techniques were then used. Firstly, the GIS software ArcGIS was used to map the crude prevalence rates. Secondly, the data were smoothed by the method of empirical Bayes estimation. Results： The classical statistical approach produced an extremely dishomogeneous map, while the Bayesian map was much smoother and more interpretable. The maps produced by the Bayesian technique indicate the tendency of villages in the southeastern region to produce higher prevalence or risk values. Conclusions： The Bayesian smoothing technique addresses the issue of heterogeneity in the population at risk and it is therefore recommended for use in explorative mapping of birth defects. This approach provides procedures to identify spatial health risk levels and assists in generating hypothesis that will be investigated in further detail.

关 键 词：Birth defects Neural tube defects （NTDs） Disease map Spatial analysis Bayesian smoothing China 

分 类 号：R726.2[医药卫生—儿科] TP317[医药卫生—临床医学]