Literature DB >> 15446615

Spatial clusters of cancers in Illinois 1986-2000.

Fahui Wang1.   

Abstract

Elevated cancer rates in some areas may arise simply by chance. The pattern generally warrants a study only when it is statistically significant. This research uses a recently developed spatial statistic, implemented in a Geographic Information System (GIS) environment, to detect spatial clusters of diagnostically specific cancers in Illinois. On the basis of the cancer incidence data (the 1986-1990 and 1996-2000 data sets) from the Illinois Cancer Registry, the study examines different clustering patterns of four leading types of cancer in Illinois, namely breast, lung, colorectal, and prostate cancers. The first part of the study uses the data at the county level, and the second part uses the data in zip code areas. The analysis using the zip code area data directly may be problematic since the rate estimates for rare events like cancer in small populations are susceptible to data errors. The spatial order method is used to group zip code areas so that the new geographic areas have sufficiently large base populations for estimates of reliable cancer rates. Results from the spatial cluster analysis may be valuable for other researchers to design follow-up case-control and retrospective cohort studies.

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Year:  2004        PMID: 15446615     DOI: 10.1023/b:joms.0000032842.78643.38

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  11 in total

1.  Exploratory spatial analysis of birth defect rates in an urban population.

Authors:  G Rushton; P Lolonis
Journal:  Stat Med       Date:  1996 Apr 15-May 15       Impact factor: 2.373

2.  Geographic studies of pediatric cancer near hazardous waste sites.

Authors:  E White; T E Aldrich
Journal:  Arch Environ Health       Date:  1999 Nov-Dec

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Authors:  R C Grimson; R D Rose
Journal:  Methods Inf Med       Date:  1991-10       Impact factor: 2.176

4.  Geographic information system (GIS) studies of cancer around NPL sites.

Authors:  K R Krautheim; T E Aldrich
Journal:  Toxicol Ind Health       Date:  1997 Mar-Jun       Impact factor: 2.273

5.  Realistic power simulations compare point- and area-based disease cluster tests.

Authors:  N Oden; G Jacquez; R Grimson
Journal:  Stat Med       Date:  1996 Apr 15-May 15       Impact factor: 2.373

6.  Methods for investigating localized clustering of disease. Analysing the spatial distribution of disease using a method of constructing geographical areas of approximately equal population size.

Authors:  R J Black; L Sharp; J D Urquhart
Journal:  IARC Sci Publ       Date:  1996

7.  Monitoring for clusters of disease: application to leukemia incidence in upstate New York.

Authors:  B W Turnbull; E J Iwano; W S Burnett; H L Howe; L C Clark
Journal:  Am J Epidemiol       Date:  1990-07       Impact factor: 4.897

8.  Visual and statistical assessment of spatial clustering in mapped data.

Authors:  S D Walter
Journal:  Stat Med       Date:  1993-07-30       Impact factor: 2.373

9.  Adjusting Moran's I for population density.

Authors:  N Oden
Journal:  Stat Med       Date:  1995-01-15       Impact factor: 2.373

10.  Constructing regions for small area analysis: material deprivation and colorectal cancer.

Authors:  R Haining; S Wise; M Blake
Journal:  J Public Health Med       Date:  1994-12
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  2 in total

1.  On the use of ZIP codes and ZIP code tabulation areas (ZCTAs) for the spatial analysis of epidemiological data.

Authors:  Tony H Grubesic; Timothy C Matisziw
Journal:  Int J Health Geogr       Date:  2006-12-13       Impact factor: 3.918

2.  Application of geographic information systems and asset mapping to facilitate identification of colorectal cancer screening resources.

Authors:  Clement Kudzai Gwede; Beverly G Ward; John S Luque; Susan T Vadaparampil; Desiree Rivers; Dinorah Martinez-Tyson; Shalewa Noel-Thomas; Cathy D Meade
Journal:  Online J Public Health Inform       Date:  2010-04-09
  2 in total

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