DARTMOUTH COL COBRE: P5: ENVIRONMENTAL EPIDEMIOLOGY OF LUNG CANCER IN NH

达特茅斯 COL COBRE：P5：新罕布什尔州肺癌的环境流行病学

• 批准号: 7720660
• 负责人: ERIC J DUELL
• 金额: $ 35.98万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-11 至 2009-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7720660
• 关键词: Adopted; Age; Air Pollution; Arsenic; Burn injury; Clip; Computer Retrieval of Information on Scientific Projects Database; DNA; DNA Repair; Data; Databases; Dietary Factors; Disease regression; Education; Environment; Environmental Epidemiology; Environmental Health; Environmental Risk Factor; Epidemiologic Methods; Epidemiology; Exposure to; Funding; Future; Gender; Genetic Predisposition to Disease; Genotype; Geographic Information Systems; Germ Lines; Grant; Health; Health Information System; Incidence; Individual; Institution; Lung diseases; Malignant neoplasm of lung; Maps; Methods; Modeling; Modification; New Hampshire; Occupations; Outcome; Particulate; Pattern; Phase; Policy Maker; Population; Questionnaires; Relative Risks; Research; Research Personnel; Resources; Risk; Risk Assessment; Risk Factors; Scientist; Serum; Smoking; Smoking Status; Source; Staging; Structure of nail of toe; Techniques; Testing; United States National Institutes of Health; Water; Wood material; analog; base; cancer risk; case control; disorder prevention; drinking water; improved; multilevel analysis; water sampling

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This project integrates spatial analytic techniques and traditional case-control methods in epidemiology to study environmental risk factors for lung cancer in New Hampshire. We will adopt a three-phase approach. First, a geographic information system (GIS), which is the technical environment in which spatial analyses are performed, will be used to reveal spatial patterns and relationships between environmental factors (such as fine particulate air pollution) and lung cancer in New Hampshire. Second, traditional population-based, case-control methods of epidemiology will be used to study individual-level risk factor information (collected from questionnaires, drinking water samples, toenails clippings, sera, and germ-line DNA). This will permit us to model causal relations between environmental factors and risk of incident lung cancer in New Hampshire. As part of this approach, we will explore potential modifications in relative risk due to synergy between exposures (arsenic and smoking), host genetic susceptibility, dietary factors, and gender. We also will employ multilevel modeling (hierarchical regression) of individual lung cancer risk using group-level (ecologic-geographic) exposure information (e.g., fine particulate air pollution) and individual-level exposure information (e.g., smoking status, age, gender, education, occupation, use of wood burning stoves, water arsenic concentration, toenail arsenic concentration, DNA repair genotype, and other variables). Multilevel modeling will allow us to improve estimates of individual lung cancer risk by including group-level data that have no individual-level analogue (e.g., exposure to fine particulate air pollution). Third, using spatial environmental data and risk models built in phase 2, we will create a risk map of lung cancer in New Hampshire. We will test the validity of our environmental models and our risk map of lung cancer using newly collected lung cancer incidence data from New Hampshire. Through this three-phase approach, we expect that new etiologic factors for lung cancer will be uncovered and that this information will aid scientists and policy makers regarding risk assessment and disease prevention. This project will also set the stage for a comprehensive regional environmental health information system that will serve as a database and knowledgebase for future environmental health studies of lung diseases and other health outcomes in New Hampshire.

该副本是利用众多研究子项目之一 由NIH/NCRR资助的中心赠款提供的资源。子弹和 调查员（PI）可能已经从其他NIH来源获得了主要资金， 因此可以在其他清晰的条目中代表。列出的机构是 对于中心，这不一定是调查员的机构。 该项目将流行病学中的空间分析技术和传统病例对照方法整合在一起，以研究新罕布什尔州肺癌的环境风险因素。我们将采用三相方法。首先，将使用空间分析的技术环境（GIS）来揭示新罕布什尔州的环境因素（例如细颗粒空气污染）和肺癌之间的空间模式和关系。其次，传统的基于人群的病例对照方法将使用流行病学方法来研究个体级别的危险因素信息（从问卷，饮用水样品，脚趾甲剪剪，血清和种系DNA收集）。这将使我们能够在新罕布什尔州的环境因素和发生肺癌发生风险之间建模因果关系。作为这种方法的一部分，我们将探索由于暴露（砷和吸烟），宿主遗传易感性，饮食因素和性别之间的协同作用而导致的相对风险的潜在修改。我们还将使用小组级（生态地理）暴露信息（例如，颗粒颗粒空气污染）和个体水平的暴露信息（例如吸烟状态，年龄，性别，性别，教育，教育，使用木材燃烧stoves，燃烧木材，以及其他维修浓度，浓缩，de na ssenic conseniac andication and de na conseniac incenication，ding nikation，使用群体状态，年龄，性别，教育，使用良好的颗粒状态（例如，颗粒状空气污染）和个人水平的暴露信息（例如，吸烟状态，年龄，性别，教育，使用，颗粒状空气污染）和个体水平的暴露信息（例如，颗粒状空气污染）和个体水平的暴露信息，变量）。多级建模将使我们能够通过包括没有个体级类似物的组级数据来改善单个肺癌风险的估计（例如，暴露于细节颗粒空气污染）。第三，使用第2阶段建立的空间环境数据和风险模型，我们将在新罕布什尔州创建肺癌的风险图。我们将使用来自新罕布什尔州的新收集的肺癌发病率数据来测试环境模型和肺癌风险图的有效性。通过这种三相方法，我们预计将发现有关肺癌的新病因因素，并且该信息将帮助科学家和决策者了解风险评估和预防疾病。该项目还将为全面的区域环境健康信息系统奠定基础，该系统将作为新罕布什尔州肺部疾病和其他健康状况的未来环境健康研究的数据库和知识基础。