Smart Mobility, Inc., Norwich, Vermont 05055, USA.
Int J Health Geogr. 2010 Feb 12;9:8. doi: 10.1186/1476-072X-9-8.
Studies involving the built environment have typically relied on US Census data to measure residential density. However, census geographic units are often unsuited to health-related research, especially in rural areas where development is clustered and discontinuous.
We evaluated the accuracy of both standard census methods and alternative GIS-based methods to measure rural density.
We compared residential density (units/acre) in 335 Vermont school neighborhoods using conventional census geographic units (tract, block group and block) with two GIS buffer measures: a 1-kilometer (km) circle around the school and a 1-km circle intersected with a 100-meter (m) road-network buffer. The accuracy of each method was validated against the actual residential density for each neighborhood based on the Vermont e911 database, which provides an exact geo-location for all residential structures in the state.
Standard census measures underestimate residential density in rural areas. In addition, the degree of error is inconsistent so even the relative rank of neighborhood densities varies across census measures. Census measures explain only 61% to 66% of the variation in actual residential density. In contrast, GIS buffer measures explain approximately 90% of the variation. Combining a 1-km circle with a road-network buffer provides the closest approximation of actual residential density.
Residential density based on census units can mask clusters of development in rural areas and distort associations between residential density and health-related behaviors and outcomes. GIS-defined buffers, including a 1-km circle and a road-network buffer, can be used in conjunction with census data to obtain a more accurate measure of residential density.
涉及建筑环境的研究通常依赖美国人口普查数据来衡量居民密度。然而，人口普查的地理单位通常不适合与健康相关的研究，尤其是在农村地区，那里的发展是集聚和不连续的。
我们评估了标准人口普查方法和替代 GIS 方法测量农村密度的准确性。
我们比较了 335 个佛蒙特州学校社区的住宅密度（单位/英亩），使用传统的人口普查地理单位（普查区、街区组和街区）与两种 GIS 缓冲区方法：学校周围 1 公里（km）的圆圈和与 100 米（m）道路网络缓冲区相交的 1 公里圆圈。每种方法的准确性都根据佛蒙特州 e911 数据库（为该州所有住宅结构提供精确地理位置）对每个社区的实际住宅密度进行了验证。
标准人口普查措施低估了农村地区的住宅密度。此外，误差程度不一致，因此即使是社区密度的相对等级也因人口普查措施而异。人口普查措施仅解释了实际住宅密度的 61%至 66%。相比之下，GIS 缓冲区措施解释了大约 90%的变化。结合 1 公里的圆圈和道路网络缓冲区可以最接近实际住宅密度。
基于普查单位的住宅密度可能掩盖农村地区的发展集群，并扭曲住宅密度与健康相关行为和结果之间的关联。GIS 定义的缓冲区，包括 1 公里的圆圈和道路网络缓冲区，可以与人口普查数据结合使用，以获得更准确的住宅密度测量值。
