Abstract
This study examines spatial accessibility of primary care in the Baton Rouge Metropolitan Statistical Area, Louisiana. Two popular accessibility measures are used: the proximity method focuses on the travel time from the nearest facility and the two-step floating catchment area (2SFCA) method considers the match ratio between providers and population as well as the complex spatial interaction between them. The two methods capture different elements of spatial accessibility: one being physically close to a facility and another adding availability of service. Both properties can be valuable for residents. In the study area, residents in urban areas generally enjoy shorter travel time from their nearest service providers as well as higher accessibility scores measured by the 2SFCA method (i.e., physicians per 1000 residents) than rural residents. Overall, disproportionally higher percentages of African Americans are in areas with shorter travel time to the nearest primary care providers and higher accessibility scores; so are residents in areas of higher poverty rates. This “reversed racial advantage” in spatial accessibility does not capture nonspatial obstacles related to financial and other socioeconomic factors for African Americans (and population in poverty) and nevertheless represents one fewer battle to fight in reducing healthcare disparities for various disadvantaged population groups. Such an advantage disappears or is even reversed in remote rural areas with high concentration of African Americans, who suffer from double disadvantages in both spatial and nonspatial access to primary care.
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Notes
- 1.
Dissimilarity between two neighboring areas i and j is measured by their attribute distance Dij such as Dij = (xi − xj)2, where xi and xj are standardized attribute values (here African American percentage) for i and j, respectively.
- 2.
The total sum of squared deviations (SSD) measures overall heterogeneity in derived regions such as \( \mathrm{SSD}=\sum \limits_{r=1}^k\sum \limits_{i=1}^{nr}{\left({x}_i-\overline{x}\right)}^2 \), where k is the number of regions, nr is the number of small areas in region r; xi is the standardized attribute value, and \( \overline{x_t} \) is the regional mean.
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Acknowledgement
We are grateful for the supports by the National Institutes of Health (Grant No. R21CA212687, Wang) and the ASPIRE undergraduate research program in the College of Humanities and Social Sciences at Louisiana State University (Vingiello).
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Wang, F., Vingiello, M., Xierali, I.M. (2020). Serving a Segregated Metropolitan Area: Disparities in Spatial Access to Primary Care Physicians in Baton Rouge, Louisiana. In: Lu, Y., Delmelle, E. (eds) Geospatial Technologies for Urban Health. Global Perspectives on Health Geography. Springer, Cham. https://doi.org/10.1007/978-3-030-19573-1_5
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