TY - JOUR
T1 - A geographic information system-based method for estimating cancer rates in non-census defined geographical areas
AU - Freeman, Vincent L.
AU - Boylan, Emma E.
AU - Pugach, Oksana
AU - Mclafferty, Sara L.
AU - Tossas-Milligan, Katherine Y.
AU - Watson, Karriem S.
AU - Winn, Robert A.
N1 - Funding Information:
Acknowledgments We thank Richard E. Barrett, PhD of the Department of Sociology at the University of Illinois at Chicago for his substantive knowledge, and Tiefu Shen, PhD of the Division of Epidemiologic study, Illinois Department of Public Health, for his comments and technical assistance.
Funding Information:
Funding This research was supported by a research project grant from the American Cancer Society (117534-RSGT-09-286-01-CPHPS) (VLF) to the University of Illinois at Chicago and the University of Illinois at Chicago Cancer Center and (VLF).
Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017/10/1
Y1 - 2017/10/1
N2 - 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.
AB - 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.
KW - Areal interpolation through dasymetric mapping
KW - Local cancer health information
KW - Precision public health
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U2 - 10.1007/s10552-017-0941-8
DO - 10.1007/s10552-017-0941-8
M3 - Article
C2 - 28825153
AN - SCOPUS:85027845802
VL - 28
SP - 1095
EP - 1104
JO - Cancer Causes and Control
JF - Cancer Causes and Control
SN - 0957-5243
IS - 10
ER -