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

University of Illinois at Chicago School of Public Health
University of Illinois at Urbana-Champaign
University of Illinois Cancer Center, Chicago. IL

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

2 Scopus citations

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
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 2017
Externally published	Yes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Adolescent
Adult
Aged
Censuses
Chicago/epidemiology
Child
Child, Preschool
Female
Geographic Information Systems
Humans
Male
Middle Aged
Neoplasms/epidemiology
Registries
Young Adult

Access to Document

10.1007/s10552-017-0941-8

Cite this

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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'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.",

keywords = "Adolescent, Adult, Aged, Censuses, Chicago/epidemiology, Child, Child, Preschool, Female, Geographic Information Systems, Humans, Male, Middle Aged, Neoplasms/epidemiology, Registries, Young Adult",

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\}",

year = "2017",

month = oct,

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

language = "English",

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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

PY - 2017/10

Y1 - 2017/10

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.

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KW - Child, Preschool

KW - Female

KW - Geographic Information Systems

KW - Humans

KW - Male

KW - Middle Aged

KW - Neoplasms/epidemiology

KW - Registries

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U2 - 10.1007/s10552-017-0941-8

DO - 10.1007/s10552-017-0941-8

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SN - 0957-5243

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