Messer Lynne C, Jagai Jyotsna S, Rappazzo Kristen M, Lobdell Danelle T
National Health and Environmental Effects Research Laboratory, U,S, Environmental Protection Agency, Chapel Hill, NC, USA.
Environ Health. 2014 May 22;13(1):39. doi: 10.1186/1476-069X-13-39.
A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.
The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.
Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).
The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.
对环境质量进行更全面的评估将增进我们对环境状况与人类健康之间关系的理解。为此开发了美国所有县的环境质量指数(EQI)。
EQI的开发分为四个部分:领域识别;数据源获取;变量构建;以及数据缩减。识别出五个环境领域(空气、水、土地、建成环境和社会人口统计学)。在每个领域内,确定数据源;每个数据源在时间上(2000 - 2005年)和地理上(县)都有限制。为每个领域构建变量,并评估其缺失值、共线性和正态性。使用主成分分析(PCA)完成特定领域的数据缩减,从而得到特定领域的指数。然后使用PCA将特定领域的指数合并为一个总体EQI。在每个PCA过程中,保留第一个主成分。特定领域的指数和总体EQI都按四个城乡连续体代码(RUCC)进行分层。每个指数的较高值对应于环境质量较差的地区。
纳入变量的浓度在城乡阶层之间存在差异,特定领域内的变量负荷以及EQI的领域指数负荷也存在差异。一般来说,在大都市区发现空气和社会人口统计学指数的值较高,而人口最稀少的地区每个领域指数的值最低。城市化程度较低的县(RUCC 3)表现出最大的异质性和EQI分数范围(-4.76, 3.57),而人口稀少的阶层(RUCC 4)包含得分最正的县(EQI分数范围为-5.86, 2.52)。
EQI有望改善我们对公共卫生总体环境的描述。EQI描述了居民所接触的县级非居住环境条件,特定领域的EQI负荷表明哪些环境领域在EQI环境的变异性中占最大比例。EQI是为美国所有县构建的,纳入了各种数据以提供环境状况的全面图景。我们采用了一种可重复的方法,主要利用公开可用的数据源。