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土壤性质在出生缺陷环境风险中的指示作用
引用本文:李新虎,王劲峰,郑晓瑛,廖一兰,张科利,张 霆,陈 功.土壤性质在出生缺陷环境风险中的指示作用[J].环境科学研究,2007,20(6):21-26.
作者姓名:李新虎  王劲峰  郑晓瑛  廖一兰  张科利  张 霆  陈 功
作者单位:1.中国科学院 城市环境研究所,福建 厦门 361003
基金项目:国家重点基础研究发展计划(973计划)
摘    要:为研究土壤性质在出生缺陷环境风险中的指示作用,考虑了区域人口分布和疾病空间结构,使用Bayesian方法,对山西省和顺县连续4年的神经管畸形发生的数据进行了处理,并使用非参数统计的方法,结合土壤环境过程机理,对土壤的理化性质和出生缺陷的环境风险做了系统分析. 结果表明:土壤的机械组成,阳离子交换量(CEC),pH,有机质含量及碳酸钙含量都与神经管畸形发生率显著相关. 土壤砂粒含量高的地区,神经管畸形发生的风险会显著增加;土壤粘粒含量高的地区,神经管畸形发生的风险会显著降低. 土壤阳离子交换量高的地区,神经管畸形发生的风险会显著降低. 在偏碱性土壤且pH较高的地区,神经管畸形发生的风险会显著降低.在有利于土壤提供有效形态重金属及稀土元素的环境条件下,神经管畸形发生率会显著提高.在影响神经管畸形发生的环境因素中,土壤介质中各形态元素的有效含量比其总量具有更强的指示作用. 

关 键 词:Bayesian方法    非参数统计    出生缺陷    土壤性质
文章编号:1001-6929(2007)06-0021-06
收稿时间:2007-03-18
修稿时间:2007-06-21

The Indication Effect of Soil in Environmental Risk Assessment of Birth Defects
LI Xin-hu,WANG Jin-feng,ZHENG Xiao-ying,LIAO Yi-lan,ZHANG Ke-li,ZHANG Ting and CHEN Gong.The Indication Effect of Soil in Environmental Risk Assessment of Birth Defects[J].Research of Environmental Sciences,2007,20(6):21-26.
Authors:LI Xin-hu  WANG Jin-feng  ZHENG Xiao-ying  LIAO Yi-lan  ZHANG Ke-li  ZHANG Ting and CHEN Gong
Institution:1.Institute of Urban Environment, Chinese Acadamy of Sciences, Xiamen 361003, China2.Institute of Geographical Sciences and Nature Resources Research, Chinese Acadamy of Sciences, Beijing 100101, China3.Institute of Population Research, Peking University, Beijing 100871, China4.Department of Resource and Environment Science, Beijing Normal University, Beijing 100875, China5.Capital Institute of Pediatrics, Beijing 100020, China
Abstract:In order to study the indication effect of soil in environmental risk of birth defects, the data on neural tube defect (NTD) in Heshun County, Shanxi Province for 4 consecutive years were analyzed. The population distribution and disease spatial structure were considered, and Bayesian method was used to adjust the prevalence ratio of NTDs. The nonparametric statistic method was also usedto systematically analyze the soil physiochemical properties and the environmental risk of birth defects, combined with analysis of process mechanisms of soil environment. The results show that mechanical composition, pH and cation exchange capacity (CEC), organic matter content and lime carbonate content insoils have significant correlation with the prevalence ratio of NTDs. The risk of NTDs significantly increases in areas with high content of sand grains in the soil, while it significantly decreases in areas with high content of clay particlesor high CEC in the soil. In alkaline soils, the risk of NTDs significantly decreases in areas with high pH. Under the soil conditions favorable to the soil''s providing effective forms of heavy metals and rare earth elements, prevalence ratio of NTDs will significantly increase. The existing state and activity ofchemicals in soils are more indicative than the total content of those chemicals.
Keywords:Bayesian method  nonparametric statistic  birth defects  soil properties
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