Deconstructing rurality to better "place" health data.

IF 5.1 1区 地球科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Daniel Beene, Yan Lin, Joseph H Hoover, Xun Shi
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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.

解构农村以更好地“放置”健康数据。
农村-城市分类方案经常用于人口健康的生态学研究。然而,用于产生这些分类的算法及其基本假设可能与它们在卫生研究中的预期用途不匹配。在这里,我们将重点放在与健康相关的物理环境特征的空间分布上,例如医疗保健,以检查八种分类方案在多大程度上反映了农村地区的异质背景。通过比较美国西南部的农村部落保留地和其他农村地区,我们进一步探讨了城乡分类如何区分不同类型的农村地区。由于卫生服务和基础设施通常是通过州和联邦计划分配给农村地区服务不足的人口,这种方法说明了如何定义和代表农村社区的更广泛的政治含义。结果表明,城乡分类不能充分反映农村地区内部和之间的异质背景。我们主张建立更适当的人口健康模型,以解释健康与地点之间关系的背景差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
11.00
自引率
7.00%
发文量
81
审稿时长
9 months
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.
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