A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease.
A multivariate analysis of CalEnviroScreen: comparing environmental and socioeconomic stressors versus chronic disease.
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DOI：
10.1186/s12940-017-0344-z
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发表时间：
2017-12-13
期刊：
影响因子：
--
通讯作者：
McKone TE
中科院分区：
文献类型：
--
作者：
Greenfield BK;Rajan J;McKone TE
健康风险评估范式正在从单一压力源评估转向多种压力源的累积评估。最近开发大规模公共健康危害数据集的努力为开发和评估多种接触危害提供了机会。我们对12个环境危害指标、5个社会经济困难指标和3个健康结果之间的空间关系进行了多变量研究。指标来自CalEnviroScreen（3.0版），这是一种由加州环境保护局开发的公开可用的环境正义筛选工具。将这些指标与邮政编码制表地区人口一级14种ICD-9疾病类别的总住院率（疾病负担的衡量标准）进行比较。我们进行了主成分分析，以可视化和减少CalEnviroScreen数据和空间自回归，以评估与疾病负担的关联。CalEnviroScreen与来自所有20个变量的主成分分析（PCA）的第一主成分（PC）强相关（斯皮尔曼ρ = 0.95）。在12个环境变量的PCA中，两个PC轴解释了43%的方差，第一个轴表示工业活动和空气污染，第二个轴与地面臭氧，饮用水污染和PM2.5相关。农业中使用的农药质量与所有其他环境指标以及CalEnviroScreen计算方法的相关性很差或呈负相关，表明该方法捕获农业暴露的能力有限。在5个社会经济变量的主成分分析中，第一个PC解释了66%的方差，代表了整体社会经济困难。在同步自回归模型中，第一个环境和社会经济PC都与疾病负担措施显着相关，但更多的模型变异解释了社会经济PC。本研究支持将CalEnviroScreen用于筛选加州地区高环境暴露和人群脆弱性区域的预期目的。研究结果进一步提出了一个假设，即与环境污染物暴露相比，社会经济地位对总体疾病负担的影响更大。本文的在线版本（10.1186/s12940-017-0344-z）包含补充材料，可供授权用户使用。
The health-risk assessment paradigm is shifting from single stressor evaluation towards cumulative assessments of multiple stressors. Recent efforts to develop broad-scale public health hazard datasets provide an opportunity to develop and evaluate multiple exposure hazards in combination. We performed a multivariate study of the spatial relationship between 12 indicators of environmental hazard, 5 indicators of socioeconomic hardship, and 3 health outcomes. Indicators were obtained from CalEnviroScreen (version 3.0), a publicly available environmental justice screening tool developed by the State of California Environmental Protection Agency. The indicators were compared to the total rate of hospitalization for 14 ICD-9 disease categories (a measure of disease burden) at the zip code tabulation area population level. We performed principal component analysis to visualize and reduce the CalEnviroScreen data and spatial autoregression to evaluate associations with disease burden. CalEnviroScreen was strongly associated with the first principal component (PC) from a principal component analysis (PCA) of all 20 variables (Spearman ρ = 0.95). In a PCA of the 12 environmental variables, two PC axes explained 43% of variance, with the first axis indicating industrial activity and air pollution, and the second associated with ground-level ozone, drinking water contamination and PM2.5. Mass of pesticides used in agriculture was poorly or negatively correlated with all other environmental indicators, and with the CalEnviroScreen calculation method, suggesting a limited ability of the method to capture agricultural exposures. In a PCA of the 5 socioeconomic variables, the first PC explained 66% of variance, representing overall socioeconomic hardship. In simultaneous autoregressive models, the first environmental and socioeconomic PCs were both significantly associated with the disease burden measure, but more model variation was explained by the socioeconomic PCs. This study supports the use of CalEnviroScreen for its intended purpose of screening California regions for areas with high environmental exposure and population vulnerability. Study results further suggest a hypothesis that, compared to environmental pollutant exposure, socioeconomic status has greater impact on overall burden of disease. The online version of this article (10.1186/s12940-017-0344-z) contains supplementary material, which is available to authorized users.
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作者：
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DOI：
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