Freeman Vincent L, Boylan Emma E, Pugach Oksana, Mclafferty Sara L, Tossas-Milligan Katherine Y, Watson Karriem S, Winn Robert A
Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, 1603 W. Taylor St., Chicago, IL, 60612, USA.
University of Illinois at Chicago Cancer Center, University of Illinois Hospital and Health Sciences System, 914 S. Wood St., Chicago, IL, 60612, USA.
Cancer Causes Control. 2017 Oct;28(10):1095-1104. doi: 10.1007/s10552-017-0941-8. Epub 2017 Aug 20.
To address locally relevant cancer-related health issues, health departments frequently need data beyond that contained in standard census area-based statistics. We describe a geographic information system-based method for calculating age-standardized cancer incidence rates in non-census defined geographical areas using publically available data.
Aggregated records of cancer cases diagnosed from 2009 through 2013 in each of Chicago's 77 census-defined community areas were obtained from the Illinois State Cancer Registry. Areal interpolation through dasymetric mapping of census blocks was used to redistribute populations and case counts from community areas to Chicago's 50 politically defined aldermanic wards, and ward-level age-standardized 5-year cumulative incidence rates were calculated.
Potential errors in redistributing populations between geographies were limited to <1.5% of the total population, and agreement between our ward population estimates and those from a frequently cited reference set of estimates was high (Pearson correlation r = 0.99, mean difference = -4 persons). A map overlay of safety-net primary care clinic locations and ward-level incidence rates for advanced-staged cancers revealed potential pathways for prevention.
Areal interpolation through dasymetric mapping can estimate cancer rates in non-census defined geographies. This can address gaps in local cancer-related health data, inform health resource advocacy, and guide community-centered cancer prevention and control.
为解决与当地相关的癌症相关健康问题,卫生部门经常需要标准普查区域统计数据之外的数据。我们描述了一种基于地理信息系统的方法,该方法使用公开可用的数据来计算非普查定义地理区域的年龄标准化癌症发病率。
从伊利诺伊州癌症登记处获取了2009年至2013年在芝加哥77个普查定义社区区域中每个区域诊断出的癌症病例汇总记录。通过普查街区的密度制图进行面积插值,用于将人口和病例数从社区区域重新分配到芝加哥50个政治定义的市议员选区,并计算选区层面的年龄标准化5年累积发病率。
地理区域间人口重新分配中的潜在误差限制在总人口的<1.5%以内,我们的选区人口估计数与经常引用的一组估计数之间的一致性很高(皮尔逊相关系数r = 0.99,平均差异 = -4人)。安全网初级保健诊所位置与晚期癌症选区层面发病率的地图叠加显示了潜在的预防途径。
通过密度制图进行面积插值可以估计非普查定义地理区域的癌症发病率。这可以填补当地癌症相关健康数据的空白,为卫生资源宣传提供信息,并指导以社区为中心的癌症预防和控制。