Nori-Sarma Amruta, Spangler Keith R, Wang Biqi, Cesare Nina, Dukes Kimberly A, Lane Kevin J
Department of Environmental Health, Boston University School of Public Health, Boston, MA, USA.
Biostatistics and Epidemiology Data Analytics Center, Boston University School of Public Health, Boston, MA, USA.
J Expo Sci Environ Epidemiol. 2023 Mar;33(2):237-243. doi: 10.1038/s41370-022-00414-z. Epub 2022 Feb 10.
BACKGROUND/OBJECTIVE: Lack of access to resources such as medical facilities and grocery stores is related to poor health outcomes and inequities, particularly in an environmental justice framework. There can be substantial differences in quantifying "access" to such resources, depending on the geospatial method used to generate distance estimates.
We compared three methods for calculating distance to the nearest grocery store to illustrate differential access at the census block-group level in the Atlanta metropolitan area, including: Euclidean distance estimation, service areas incorporating roadways and other factors, and cost distance for every point on the map.
We found notable differences in access across the three estimation techniques, implying a high potential for exposure misclassification by estimation method. There was a lack of nuanced exposure in the highest- and lowest-access areas using the Euclidean distance method. We found an Intraclass Correlation Coefficient (ICC) of 0.69 (0.65, 0.73), indicating moderate agreement between estimation methods.
As compared with Euclidean distance, service areas and cost distance may represent a more meaningful characterization of "access" to resources. Each method has tradeoffs in computational resources required versus potential improvement in exposure classification. Careful consideration of the method used for determining "access" will reduce subsequent misclassifications.
背景/目的:缺乏获得医疗设施和杂货店等资源的机会与不良健康结果及不平等现象相关,尤其是在环境正义框架下。根据用于生成距离估计的地理空间方法,在量化获得此类资源的“机会”方面可能存在很大差异。
我们比较了三种计算到最近杂货店距离的方法,以说明亚特兰大大都市区人口普查街区组层面的不同获得机会,包括:欧几里得距离估计、纳入道路和其他因素的服务区,以及地图上每个点的成本距离。
我们发现三种估计技术在获得机会方面存在显著差异,这意味着估计方法导致暴露错误分类的可能性很高。使用欧几里得距离方法时,在获得机会最高和最低的区域缺乏细微的暴露差异。我们发现组内相关系数(ICC)为0.69(0.65,0.73),表明估计方法之间存在中等程度的一致性。
与欧几里得距离相比,服务区和成本距离可能更能有意义地描述获得资源的“机会”。每种方法在所需计算资源与暴露分类潜在改进之间都存在权衡。仔细考虑用于确定“机会”的方法将减少后续的错误分类。