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

doi:10.1007/s10552-017-0941-8

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

Geography and Geographic Information Science

Research output: Contribution to journal › Article › peer-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 language	English (US)
Pages (from-to)	1095-1104
Number of pages	10
Journal	Cancer Causes and Control
Volume	28
Issue number	10
DOIs	https://doi.org/10.1007/s10552-017-0941-8
State	Published - Oct 1 2017

Keywords

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

ASJC Scopus subject areas

Oncology
Cancer Research

Access to Document

10.1007/s10552-017-0941-8

Fingerprint Dive into the research topics of 'A geographic information system-based method for estimating cancer rates in non-census defined geographical areas'. Together they form a unique fingerprint.

Cite this

A geographic information system-based method for estimating cancer rates in non-census defined geographical areas. / Freeman, Vincent L.; Boylan, Emma E.; Pugach, Oksana; Mclafferty, Sara L.; Tossas-Milligan, Katherine Y.; Watson, Karriem S.; Winn, Robert A.

In: Cancer Causes and Control, Vol. 28, No. 10, 01.10.2017, p. 1095-1104.

Research output: Contribution to journal › Article › peer-review

@article{ba32f8bad69045d9b2da8fd8768234a1,

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

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{\textquoteright}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{\textquoteright}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.",

keywords = "Areal interpolation through dasymetric mapping, Local cancer health information, Precision public health",

author = "Freeman, {Vincent L.} and Boylan, {Emma E.} and Oksana Pugach and Mclafferty, {Sara L.} and Tossas-Milligan, {Katherine Y.} and Watson, {Karriem S.} and Winn, {Robert A.}",

note = "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).",

year = "2017",

month = oct,

day = "1",

doi = "10.1007/s10552-017-0941-8",

language = "English (US)",

volume = "28",

pages = "1095--1104",

journal = "Cancer Causes and Control",

issn = "0957-5243",

publisher = "Springer Netherlands",

number = "10",

}

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).

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

UR - http://www.scopus.com/inward/record.url?scp=85027845802&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85027845802&partnerID=8YFLogxK

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 -