Cancer Risk and Environmental Exposures to Nitrate, Pest

研究环境中农业暴露的癌症危险因素，以估计这些环境暴露对农村人口癌症的贡献。农业地区的农村人口在饮用水中接触杀虫剂和硝酸盐的程度介于职业接触群体和一般人口之间。对非霍奇金淋巴瘤和脑癌、膀胱癌、结肠癌、直肠癌、胃癌、食道癌、胰腺癌和肾癌进行了病例对照研究。在这些病例对照研究中，为例行监测目的收集的水污染物数据库被用来估计过去通过公共供水对个人的接触。爱荷华州公共供水中的硝酸盐水平与膀胱癌和胰腺癌的风险无关。然而，较高的饮食亚硝酸盐摄入量与胰腺癌的风险增加有关。总的来说，饮用水中的硝酸盐含量与结肠癌的风险无关；然而，亚硝化能力增加的特定亚组风险增加。内布拉斯加州公共饮用水中硝酸盐含量升高与非霍奇金淋巴瘤风险增加有关。一项对明尼苏达州和意大利撒丁岛饮用水中硝酸盐含量的分析发现，这两个地区的硝酸盐暴露水平较低。内布拉斯加州公共供水中硝酸盐含量升高与女性患神经胶质瘤的风险增加有关，而与男性无关。最近在爱荷华州、西雅图、洛杉矶和底特律地区四个中心完成的非霍奇金淋巴瘤病例对照调查正在进一步研究这一假设。在对内布拉斯加州和科罗拉多州普拉特河谷的人口普查群体进行的生态学研究中，硝酸盐作为癌症风险因素的问题正在得到进一步的探讨，那里的硝酸盐水平是全国最高的。利用土地覆盖、牲畜饲养场位置、土壤类型和其他信息来估计私人水井中的硝酸盐水平。我们还在开发新的方法，并改进现有的方法，在一般环境暴露研究中进行暴露评估，主要侧重于农药和硝酸盐。需要这些更好的方法来更好地估计风险，并发现在此类研究中经常遇到的相对较小的风险增加。目前正在利用地理信息系统开发新的方法来估计农药的间接接触和估计私人水井中硝酸盐的接触。利用遥感数据（卫星图像）和历史记录来估计内布拉斯加州和爱荷华州的人口，因为他们的家靠近农药处理过的农田，可能暴露于农业农药。首先，内布拉斯加州的一项可行性研究表明，可以利用现有数据和地理信息系统制作准确的历史作物地图，并将这些数据与农药使用数据联系起来，以估计间接接触农业农药的可能性。在一个农业区，共有24%的研究人口居住在可能已使用杀虫剂的农田500米范围内。这是第一项估计一般人群中潜在间接接触农业农药的流行程度的研究。在爱荷华州的NHL四中心病例对照研究中，采用了类似的方法。据确定，58%的研究人口居住在玉米或大豆田500米范围内，占作物面积的90%。为了验证这一方法，我们将房屋灰尘样本中测量的农业农药与农田附近的家庭进行了比较，发现在玉米或大豆田500米范围内的家庭中检测到除草剂的风险显着增加。我们的合作者在这一领域的进一步工作包括开发一种从卫星图像自动绘制作物地图的方法。在内布拉斯加州15个县的范围内，该方法被发现成功地将作物分为两类：玉米和其他作物类型。我们正在继续完善基于地理信息系统的方法，通过纳入农药漂移模型的信息来估计农业农药暴露。爱荷华州正在进行额外的分析，将地毯灰尘样本中的农业农药水平与几个基于gis的暴露指标进行比较，其中一个指标包含了风向和农药漂移的信息。

Risk factors for cancer from agricultural exposures in the ambient environment are studied to estimate the contribution of these environmental exposures to cancer in the rural population. Rural populations in agricultural areas have exposures to pesticides and nitrates in drinking water that are intermediate between occupationally-exposed groups and the general population. Case-control studies have been conducted on non-Hodgkin's lymphoma and cancers of the brain, bladder, colon, rectum, stomach, esophagus, pancreas, and kidney. Databases of water contaminants, gathered for routine monitoring purposes, are being used to estimate past exposures via public water supplies to individuals in these case-control studies. Nitrate levels in public water supplies in Iowa were not associated with risk of bladder and pancreas cancer. However, higher intakes of dietary nitrite were associated with an increased risk of pancreas cancer. Overall, drinking water nitrate levels were not associated with risk of colon cancer; however, specific subgroups with increased nitrosation ability were at increased risk. Elevated nitrate levels in public drinking water supplies were associated with an increased risk of non-Hodgkin's lymphoma in Nebraska. An analysis of nitrate in drinking water in Minnesota and Sardinia, Italy where exposure levels were lower found no association. Elevated nitrate in public water supplies in Nebraska was associated with an increased risk of glioma in women but not men. This hypothesis is being investigated further in a recently completed case-control investigation of non-Hodgkin's lymphoma in four centers: Iowa, Seattle, Los Angeles and the Detroit area. The issue of nitrate as a cancer risk factor is being pursued further in an ecologic study of census-block groups in the Platte River Valley of Nebraska and Colorado, where elevated nitrate levels are among the highest in the country. Nitrate levels in private wells are being estimated using data on land cover, livestock feedlot locations, soil type, and other information. We are also developing new approaches, and improving existing methods, of exposure assessment in studies of general environmental exposures, with a primary focus on pesticides and nitrate. These better methods are required to better estimate risk and to detect the relatively small increases in risk often encountered in such studies. Geographic information systems (GIS) are being utilized for developing new approaches to estimating indirect exposure to pesticides and for estimating exposure to nitrate in private wells. Remote sensing data (satellite imagery) and historical records were used to estimate the population in Nebraska and Iowa potentially exposed to agricultural pesticides through the proximity of their homes to agricultural land treated with pesticides. First, a feasibility study in Nebraska demonstrated that using available data and a GIS accurate historical crop maps could be produced and that these could be linked to pesticide use data to estimate probabilities of indirect exposure to agricultural pesticides. A total of 24% of the study population in an agricultural area were determined to live within 500 meters of crop fields likely to have been treated with pesticides. This was the first study to estimate the prevalence of potential indirect exposure to agricultural pesticides in the general population. A similar approach was used for Iowa participants in the four center case control study of NHL. It was determined that 58% of the study population lived within 500 meters of corn or soybeans fields, which account for >90% of crop acreage. To validate this method, we compared agricultural pesticides measured in house dust samples to the proximity of homes from crop fields and found a significantly increased risk of herbicide detections in homes within 500 meters of corn or soybean fields. Further work in this area by our collaborators included the development of a method to automate crop mapping from satellite imagery. The method was found to be successful at classifying crops into two categories: corn and other crop types, over a 15 county area of Nebraska. We are continuing to refine the GIS-based approach to estimating agricultural pesticide exposure by incorporating information from a pesticide drift model. Additional analyses are underway in Iowa to compare agricultural pesticide levels in carpet dust samples with several GIS-based exposure metrics including one that incorporates information on wind direction and pesticide drift. With collaborators in California, we are planning to evaluate agricultural pesticide use near residences as a risk factor for childhood leukemia in an ongoing study. Carpet dust samples will be analyzed for pesticides, and information about the current and historical location of crops near residences will be determined. In a pilot study in the Central Valley of California, we compared a metric based solely on California's pesticide use reporting (PUR) database with a metric that incorporates information on the location of crops grown. A comparison of pesticide use within 500 meters of homes based on these two metrics indicates that the PUR metric classifies a substantially greater number of homes as "exposed" compared with a crop-based metric. Using a GIS, residential proximity to specific industries, hazardous waste sites, and specific chemical releases as reported by the Environmental Protection Agency's Toxic Release Inventory will be evaluated in an ongoing case control study of bladder cancer in New England. As a first step, we evaluated the feasibility of geocoding past residential histories from a pilot study in New Hampshire to determine the historical locations of specific industries associated with bladder cancer risk. The location of residences and industries is usually determined by geocoding (estimating the latitude and longitude) of addresses, but the accuracy of this method has not been systematically evaluated. We evaluated the accuracy of geocoding methods for determining residential location in rural and urban areas of Iowa by comparing geocoded residential addresses to the global positioning system measurements of latitude and longitude taken at Iowa homes in the four-center NHL study. Overall, the median error of geocoded residential locations was approximately 50 meters; however, the median error increased to about 200 meters for rural addresses.