Kinsey Eliza W, Neckerman Kathryn M, Quinn James W, Bader Michael D M, Mooney Stephen J, Lovasi Gina S, Kinsey Dirk, Rundle Andrew G
Department of Family Medicine and Community Health, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Columbia Population Research Center, Columbia University, New York, NY.
J Maps. 2024;20(1). doi: 10.1080/17445647.2024.2394505. Epub 2024 Sep 17.
Many cities have promoted nightlife or entertainment districts - concentrations of restaurants, bars, and other entertainment-related businesses - in order to revitalize declining neighborhoods. While entertainment districts can boost economic growth, they can also contribute to public health risks including violent crime, traffic accidents, and other harms. With data from the National Establishment Time Series (NETS) business database, we developed methods to use SaTScan cluster detection software to identify entertainment districts, and applied the method in a case-study of Philadelphia, Pennsylvania. Using SaTScan, we identified and mapped 101 spatial clusters of entertainment businesses in the city. Our approach is scalable and does not require prior local knowledge about entertainment areas. The results add to a small but growing literature about the use of SaTScan to map neighborhood features. Placing entertainment districts in spatial context can inform how the built environment might amplify or minimize the potential health risks of these districts.
许多城市都推出了夜生活或娱乐区，即餐厅、酒吧及其他与娱乐相关企业的集聚区，以振兴日渐衰败的社区。虽然娱乐区能够推动经济增长，但它们也可能带来包括暴力犯罪、交通事故及其他危害在内的公共健康风险。利用来自国家企业时间序列（NETS）商业数据库的数据，我们开发了一些方法，运用时空扫描聚类检测软件来识别娱乐区，并将该方法应用于宾夕法尼亚州费城的一个案例研究中。通过时空扫描，我们识别并绘制了该市101个娱乐企业的空间集群。我们的方法具有可扩展性，并且不需要事先了解当地的娱乐区域情况。这些结果丰富了关于使用时空扫描来绘制社区特征的少量但不断增加的文献。将娱乐区置于空间背景下，可以为建筑环境如何放大或最小化这些区域的潜在健康风险提供信息。
