Impacts of the choice of distance measurement method on estimates of access to point-based resources

• Published in: Journal of exposure science & environmental epidemiology Vol. 33; no. 2; pp. 237 - 243
• Main Authors: Nori-Sarma, Amruta, Spangler, Keith R., Wang, Biqi, Cesare, Nina, Dukes, Kimberly A., Lane, Kevin J.
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.03.2023; Nature Publishing Group
• Subjects: Account aggregation; Censuses; Computer applications; Correlation coefficient; Correlation coefficients; Datasets; Distance measurement; Environmental health; Environmental justice; Epidemiology; Estimates; Euclidean geometry; Exposure; Food; Geography, Medical; Georgia; Grocery stores; Health care; Health Status Disparities; Humans; Mathematical analysis; Measurement methods; Medicine; Medicine & Public Health; Methods; Metropolitan areas; Neighborhood Characteristics; Neighborhoods; Public health; Roads & highways; Service areas; Social Determinants of Health; Topography; Georgia; Disparities; Geospatial analysis; Resource access; Exposure differences
• ISSN: 1559-0631; 1559-064X; 1559-064X
• DOI: 10.1038/s41370-022-00414-z

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. Methods 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. Results 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. Significance 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.