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.
CHI Wen-xueWANG Jin-fengLI Xin-huZHENG Xiao-yingLIAO Yi-lan
By using digital satellite remote sensing data acquired in 1987―1989 and 1999―2000 and GIS combined with the natural and socio-economic data, this paper drew an integrated zonation of the cropland change and its driving forces in China. The results indicated that the cropland change in the study period was constrained by geographical factors and driven by cli-mate change as well as socio-economic system. Moreover, the regional differences of the drivers for cropland change were significant. In the midwest of China, natural condition changes and geographical background were the main constraints and drivers, while in Eastern China, social and economic changes and economic policies were the main driving forces. The cropland loss was nationwide. The dominant factors to cause this decrease included buildup of developing area to attract foreign capital and technologies, changes of industry structure due to urban in-fluence, the change of employment notions thanks to living standard improvement, rapid ur-banization due to the expansion of cities and towns, the diminished farming net income partly because of the global warming effects, and the rapid economic growth stimulated by the con-venient transportation system. These factors interact and interdepend with each other to cause the cropland loss in China recently. The reasons for the increase of cropland were primarily the cultivation and deforestation by the farmers who want to increase income. This study on the mechnism of LUCC relied on the cropland change integrated classification considering the natural or human factors both inside and outside the region, which provides a new approach to study the integrated regionalization and LUCC mechanism.
LIU Xuhua1,2, WANG Jinfeng1, LIU Mingliang4,1 & MENG Bin1,2,3 1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
