Assessing community-level exposure to social vulnerability and isolation: spatial patterning and urban-rural differences.
Assessing community-level exposure to social vulnerability and isolation: spatial patterning and urban-rural differences.
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DOI：
10.1038/s41370-022-00435-8
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发表时间：
2023-03
影响因子：
4.5
通讯作者：
Bell, Michelle L.
中科院分区：
文献类型：
--
作者：
Deziel, Nicole C.;Warren, Joshua L.;Bravo, Mercedes A.;Macalintal, Franchesca;Kimbro, Rachel T.;Bell, Michelle L.
环境卫生差距研究涉及使用指标来评估对社区一级脆弱性或不平等的暴露程度。虽然已经制定了许多脆弱性指数，但没有就标准化或适当使用达成协议，它们主要应用于城市地区，其解释和用途可能因地区而异。我们评估了城市和农村环境中不同社会脆弱性和隔离指标之间的空间分布、变异性和关系，为环境差异研究的指标解释和选择提供信息。对于北卡罗莱纳州的所有人口普查区，我们使用来自2010年美国人口普查和美国社区调查的23个社会经济/人口变量进行了主成分分析。计算得到了社区剥夺指数（NDI）、居住种族隔离指数（RI）、教育隔离指数（EI）、基尼系数（Gini）和社会脆弱性指数（SVI）。统计分析包括Moran 's I（空间聚类）、城乡差异的t检验、Pearson相关系数和各指标间的区域排名变化。社会脆弱性指标表现出明显的空间格局（Moran’s I≥0.30,p<0.01）。农村地区存在更大的教育隔离和更严重的邻里剥夺，城市地区存在更大的种族隔离。单域指标之间相关性不高（rho≤0.36），而复合指标（即NDI、SVI、主成分分析）之间相关性高（rho>0.80）。与农村地区（rho: 0.36-0.48）相比，城市地区（rho: 0.54-0.64）的综合指标与种族隔离指标的相关性更高。人口普查区的排名根据所采用的衡量标准而有很大的变化。城市和农村地区的综合指标之间的高度相关性表明它们可以互换使用；单域度量不能。复合指标反映了城市和农村环境脆弱性的不同方面，研究人员应将这些复杂性应用于不同的城市和农村形式。
Environmental health disparity research involves the use of metrics to assess exposure to community-level vulnerabilities or inequities. While numerous vulnerability indices have been developed, there is no agreement on standardization or appropriate use, they have largely been applied in urban areas, and their interpretation and utility likely vary across different geographies. We evaluated the spatial distribution, variability, and relationships among different metrics of social vulnerability and isolation across urban and rural settings to inform interpretation and selection of metrics for environmental disparity research. For all census tracts in North Carolina, we conducted a principal components analysis using 23 socioeconomic/demographic variables from the 2010 United States Census and American Community Survey. We calculated or obtained the neighborhood deprivation index (NDI), residential racial isolation index (RI), educational isolation index (EI), Gini coefficient, and social vulnerability index (SVI). Statistical analyses included Moran’s I for spatial clustering, t-tests for urban-rural differences, Pearson correlation coefficients, and changes in ranking of tracts across metrics. Social vulnerability metrics exhibited clear spatial patterning (Moran’s I ≥0.30, p<0.01). Greater educational isolation and more intense neighborhood deprivation was observed in rural areas and greater racial isolation in urban areas. Single-domain metrics were not highly correlated with each other (rho≤0.36), while composite metrics (i.e., NDI, SVI, principal components analysis) were highly correlated (rho>0.80). Composite metrics were more highly correlated with the racial isolation metric in urban (rho: 0.54–0.64) versus rural tracts (rho: 0.36–0.48). Census tract rankings changed considerably based on which metric was being applied. High correlations between composite metrics within urban and rural tracts suggests they could be used interchangeably; single domain metrics cannot. Composite metrics capture different facets of vulnerabilities in urban and rural settings, and these complexities should be examined by researchers applying metrics to areas of diverse urban and rural forms.
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影响因子：
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