Swansea University, College of Medicine, Grove Building, Singleton Park, Swansea SA2 8PP, UK.
Health Place. 2012 Mar;18(2):209-17. doi: 10.1016/j.healthplace.2011.09.006. Epub 2011 Sep 28.
Spatial analyses of environment and health data are often made using point address data, despite the risk of identity disclosure. We describe how geospatial environment and non-spatial health data can be linked anonymously, thereby maintaining geoprivacy. High resolution environment data and population density were calculated specific to each residence. Population density and environment data were anonymously linked to individual-level demographic data using a split file method and residential anonymous linking fields. Access to the nearest park or playground was calculated for each residence; children in deprived areas have increased access compared to those in affluent areas. This method has the potential to be used to evaluate natural experiments and complex environmental health interventions.
空间分析环境与健康数据通常使用点地址数据进行，尽管存在身份泄露的风险。我们描述了如何匿名链接地理空间环境和非空间健康数据，从而维护地理隐私。针对每个住所，我们专门计算了高分辨率环境数据和人口密度。人口密度和环境数据通过拆分文件方法和住所匿名链接字段匿名链接到个人层面的人口统计数据。为每个住所计算了到最近公园或游乐场的距离；贫困地区的儿童比富裕地区的儿童有更多的机会接近公园或游乐场。这种方法有可能用于评估自然实验和复杂的环境健康干预措施。
