{"title":"Deconstructing rurality to better \"place\" health data.","authors":"Daniel Beene, Yan Lin, Joseph H Hoover, Xun Shi","doi":"10.1080/13658816.2025.2482718","DOIUrl":null,"url":null,"abstract":"<p><p>Rural-urban classification schemes are frequently used in ecological studies of population health. However, the algorithms used to produce these classifications as well as their underlying assumptions may not match their intended use in health research. Here, we focus on the spatial distribution of features of the physical environment that are related to health - such as healthcare - to examine the extent to which eight classification schemes capture the heterogeneous context of rural places. We further explore how well rural-urban classifications distinguish between different types of rural places by comparing rural Tribal reservations with other rural areas in the American southwest. Because health services and infrastructure are often distributed through state and federal programs to underserved populations in rural areas, this approach speaks to the broader political implications in how rural communities are defined and represented. Results indicate that rural-urban classifications do not adequately reflect heterogeneous contexts within and across rural places. We advocate for more appropriate population health models that explain contextual differences in the relationship between health and place.</p>","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":" ","pages":""},"PeriodicalIF":5.1000,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12435940/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geographical Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/13658816.2025.2482718","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Rural-urban classification schemes are frequently used in ecological studies of population health. However, the algorithms used to produce these classifications as well as their underlying assumptions may not match their intended use in health research. Here, we focus on the spatial distribution of features of the physical environment that are related to health - such as healthcare - to examine the extent to which eight classification schemes capture the heterogeneous context of rural places. We further explore how well rural-urban classifications distinguish between different types of rural places by comparing rural Tribal reservations with other rural areas in the American southwest. Because health services and infrastructure are often distributed through state and federal programs to underserved populations in rural areas, this approach speaks to the broader political implications in how rural communities are defined and represented. Results indicate that rural-urban classifications do not adequately reflect heterogeneous contexts within and across rural places. We advocate for more appropriate population health models that explain contextual differences in the relationship between health and place.
期刊介绍:
International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.