STATISTICAL METHODS TO ASSESS ENVIRONMENTAL JUSTICE

“环境正义”的概念越来越受到人们的重视。 在制定环境法规以保护 公众的健康。 这种形式的正义关系到所有阶层之间的公平 人口在暴露于环境危害和 健康成果。 特别关注的亚群包括妊娠 妇女、儿童、少数民族和种族以及其他历史上 弱势群体。 虽然数据可用性、存储和处理灵活性有所提高， 近年来，发展适当的统计 方法学没有跟上。 暴露和健康结果数据可以 通过地理信息系统（GIS）显示在引人注目的地图上，但 开发这些显示器的数字输入的最佳方法尚不清楚。 提出了一项为期四年的研究计划，以开发和评估 （1）利用空间结构稳定速率的方法 基于少数人的估计，从而维持 稳定比率的地理和人口分辨率;（2）统计 检测暴露于环境污染的区域的方法和模型 危害、发病率增加的地区和风险增加的地区 同时控制时间和空间上的已知混杂因素;（3） 指南和方法，以允许组合来自 多个来源（例如/暴露数据、结局数据和人口统计学数据） 一个令人信服的收集分析;和（4）一套软件例程 实施开发的方法，将作为原型系统 统计学家、流行病学家和地理学家的分析， 环境正义与GIS

DESCRIPTION: The concept of "environmental justice" plays an increasingly important role in developing environmental regulations to protect the public's health. This form of justice relates to equity among all segments of the population with respect to exposure to environmental hazard and to health outcomes. Subpopulations of particular interest include pregnant women, children, ethnic, and racial minorities, and other historically disadvantaged groups. While data availability, storage, and processing flexibility have increased enormously in recent years, development of appropriate statistical methodology has not kept pace. Exposure and health outcomes data can be displayed in striking maps via Geographic Information Systems (GIS), but the best way to develop numerical inputs for these displays is not yet clear. A four-year research program is proposed to develop and evaluate the following: (1) methods that exploit spatial structure to stabilize rate estimates based on small numbers of people and thereby to maintain geographic and demographic resolution of stabilized rates; (2) statistical methods and models to detect areas of elevated exposure to environmental hazards, areas of increased disease incidence, and areas of increased risk while controlling for known confounding factors in both time and space; (3) guidelines and methods to allow for the combining of misaligned data from several sources (e.g./ exposure data, outcome data, and demographic data) into a cogent collection for analysis; and (4) a suite of software routines implementing the developed methods that will serve as the prototype system of analysis for statisticians, epidemiologists and geographers investigating environmental justice with GIS.