Statistical Methods to Account for Exposure Uncertainty in Environmental Epidemiology

解释环境流行病学中暴露不确定性的统计方法

• 批准号: 9788454
• 负责人: DONNA L SPIEGELMAN
• 金额: $ 60.99万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-19 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9788454
• 关键词: Address; Adult; Age; Air Pollution; Area; Attention; Biological; Biological Markers; Body Weight; Buffers; Carbon Black; Cardiovascular Diseases; Cardiovascular system; Chemicals; Complex; Computer software; Data; Data Analyses; Development; Disease Marker; Elderly; Environment; Environmental Epidemiology; Environmental Exposure; Environmental Health; Environmental Risk Factor; Epidemiologist; Event; Exposure to; Goals; Grant; Hand; Health; Health Food; Health Policy; Impaired cognition; Incidence; Individual; Internet; Libraries; Life Cycle Stages; Longevity; Measurement; Measures; Methodology; Methods; Modeling; National Institute of Environmental Health Sciences; Nature; Neighborhoods; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Outcome; Population; Principal Investigator; Recording of previous events; Relative Risks; Research; Risk; Source; Statistical Methods; Time; Toxic effect; Uncertainty; Validation; Work; cardiovascular disorder risk; coarse particles; disorder prevention; high dimensionality; improved; innovation; middle age; mortality; multidisciplinary; novel; obesity development; obesity in children; older women; pollutant; public health relevance; tool; toxicant; user friendly software; user-friendly; validation studies; walkability; web site

 DESCRIPTION (provided by applicant): Exposure measurement error is a likely source of bias in nearly all environmental health studies, typically leading to an under-estimation of relative risks and a loss of statistical power to detect effects. In this proposed research, we wil take a life course approach, as consistent with NIEHS strategic priorities, focusing on methodological needs in several critical areas of environmental health, including the effects of constituents of air pollution and of aspects of the neighborhood environment on cardiovascular disease and its precursors and consequences, including all-cause mortality, obesity, type 2 diabetes and subclinical cardiovascular biomarkers. Having assembled a strong multi-disciplinary team of leading theoretical and applied statisticians, environmental epidemiologists and environmental exposure assessment experts, consistent with another NIEHS strategic objective, we will make significant contributions to novel areas of pressing environmental health policy importance, with a major focus on developing methods to accurately quantify the effects of complex single and multiple, simultaneous exposure effects across space and time, responding to another NIEHS strategic priority, reducing if not eliminating the bias and loss of efficiency otherwise present due to the presence of substantial exposure measurement error. In this work, careful attention will be paid to removing bias due to spatial and temporal confounding as well as to adjusting for confounding by indoor sources of air pollution. Currently available validation data on air pollution constituents and on features of the neighborhood environment will be assembled and used to develop measurement error models relating personal exposure to measured ambient exposure as suitable for the data at hand. Mixed longitudinal and Cox survival data regression models will underlie the analytic framework. User-friendly software implementing the methods will be posted on the web, facilitating wide-scale application of the new methods to a broad range of environmental health problems.

 描述（由适用提供）：几乎所有环境健康研究中的暴露测量误差可能是偏见的来源，通常导致相对风险的估计低估和统计能力丧失以检测效应。在这项拟议的研究中，我们将采取一种与NIEHS战略重点相一致的生活课程方法，重点关注环境健康的多个关键领域的方法论需求，包括空气污染成分以及邻里环境方面对心血管疾病的影响及其对先前的疾病及其先兆和后果，包括死亡率，肥胖者，2型糖尿病和2型糖尿病。组成了一个由领先的理论和应用统计学家，环境流行病学家和环境暴露评估专家组成的强大多学科团队，与另一个NIEHS战略目标一致，我们将对新颖的领域做出重大贡献，对环境健康政策的新颖领域进行重要的贡献，并重点介绍了一种对跨越跨越的效果的效果，以范围内的效果，并将其构成复杂的效应，并构成复杂的效应，并构成复杂的效应，并将其产生效应，并构成复杂的效应，并将其效应效应，并将其效应效应，并将其效应效应，并将其产生效果，并逐渐构成效应，并将其效应，并构成型号的效应，并将其产生效果减少由于存在实质性暴露测量误差而导致的效率偏差和效率损失，否则会降低效率。在这项工作中，由于空间和暂时的混淆以及调整空气污染的混淆，将仔细注意消除偏见。目前，将组装有关空气污染一致性和邻里环境特征的可用验证数据，并用于开发有关个人暴露与测量环境暴露的测量误差模型，以适合手头数据。混合的纵向和COX生存数据回归模型将是分析框架的基础。实施该方法的用户友好软件将发布在网络上，支持新方法在各种环境健康问题上的广泛应用。