Pesticide Dispersion in Texas Watersheds in Child Cancer

描述(由申请人提供)： 癌症是美国15岁以下儿童死亡的第二大原因。接触杀虫剂可能是儿童癌症的一个重要原因。受污染的饮用水被怀疑是这种接触的来源。然而，没有直接证据表明受农药污染的水是一个危险因素。该应用程序的目标是评估德克萨斯州每个分水岭的特定儿童癌症风险，以及“当地”种植做法在污染供水方面所起的作用。中心假设是，儿童癌症的发病模式与农业使用杀虫剂相对应，而且有一定比例的风险可归因于分水岭中介的农业杀虫剂暴露。这一假设将通过三个具体的目标进行检验，这三个目标得到了德克萨斯州癌症数据库初步分析的有力支持。1)估计可归因于种植做法的癌症风险。这一目标的产品将是基于县级作物生产的癌症风险地理信息系统层。2)估计德克萨斯州每个分水岭特定儿童癌症的风险。这里生成的癌症风险的地理信息系统层将基于对离散流域的风险估计。3)估计流域风险面与种植实践的相关程度。这一目标将利用正式的贝叶斯分析两个地理信息系统层的同源性。这种方法是创新的，因为它利用了最近开发的贝叶斯映射和分析技术。这项拟议的研究意义重大，因为我们预计将估计受污染的流域调解儿童接触农药农业致癌物的可能性。获得的数据将在进一步的研究设计中有用，以选择将优化环境和生物标志物测试的采样点。预计所产生的结果将提供在随后的R01资金支持下继续进行最终调查所需的初步数据。

DESCRIPTION (provided by applicant): Cancer is the second leading cause of fatalities among U.S. children under the age of fifteen. Exposure to pesticides is potentially an important cause of childhood cancer. Contaminated drinking water is suspected as a source of such exposure. However, there is no direct evidence that implicates pesticide-contaminated water as a risk factor. The objective of this application is to estimate the risk of specific childhood cancers with each watershed in Texas and the role that 'local' cropping practices have in contaminating water supplies. The central hypothesis is that childhood cancers have incidence patterns that correspond to the agricultural use of pesticides and that a proportion of the risk is attributable to watershed-mediated exposure to agricultural pesticides. This hypothesis will be tested by three specific aims, which are strongly supported by preliminary analysis of the Texas Cancer Database. 1) Estimate the cancer risks attributable to cropping practices. The product of this aim will be a GIS layer of cancer risk based on county-level crop production. 2) Estimate the risk for specific childhood cancers in each watershed in Texas. The GIS layer of cancer risk produced here will be based on risk estimates for discrete watersheds. 3) Estimate the extent that the risk surfaces for watersheds and cropping practice are correlated. This aim will utilize formal Bayesian analysis of homology of the two GIS layers. The approach is innovative, because it capitalizes on recently developed Bayesian mapping and analytical techniques. The proposed research is significant, because we expect to estimate the potential for contaminated watersheds to mediate childhood exposure to pesticide agricultural carcinogens. Data acquired will be useful in further study design to select sampling sites that will optimize environmental and biomarker testing. It is anticipated that the results produced will provide the preliminary data needed to continue definitive investigations under the auspices of subsequent R01 funding.