A geographic information system-based method for estimating cancer rates in non-census defined geographical areas

Vincent L. Freeman, Emma E. Boylan, Oksana Pugach, Sara L. Mclafferty, Katherine Y. Tossas-Milligan, Karriem S. Watson, Robert A. Winn

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: 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. Methods: 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. Results: 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. Conclusions: 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.

Original languageEnglish (US)
Pages (from-to)1095-1104
Number of pages10
JournalCancer Causes and Control
Volume28
Issue number10
DOIs
StatePublished - Oct 1 2017

Keywords

  • Areal interpolation through dasymetric mapping
  • Local cancer health information
  • Precision public health

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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