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Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data

BACKGROUND: In 1988, elevated cancer incidence in upper Cape Cod, Massachusetts prompted a large epidemiological study of nine cancers to investigate possible environmental risk factors. Positive associations were observed, but explained only a portion of the excess cancer incidence. This case-contr...

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Autores principales: Vieira, Verónica, Webster, Thomas, Weinberg, Janice, Aschengrau, Ann
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652449/
https://www.ncbi.nlm.nih.gov/pubmed/19208254
http://dx.doi.org/10.1186/1476-069X-8-3
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author Vieira, Verónica
Webster, Thomas
Weinberg, Janice
Aschengrau, Ann
author_facet Vieira, Verónica
Webster, Thomas
Weinberg, Janice
Aschengrau, Ann
author_sort Vieira, Verónica
collection PubMed
description BACKGROUND: In 1988, elevated cancer incidence in upper Cape Cod, Massachusetts prompted a large epidemiological study of nine cancers to investigate possible environmental risk factors. Positive associations were observed, but explained only a portion of the excess cancer incidence. This case-control study provided detailed information on individual-level covariates and residential history that can be spatially analyzed using generalized additive models (GAMs) and geographical information systems (GIS). METHODS: We investigated the association between residence and bladder, kidney, and pancreatic cancer on upper Cape Cod. We estimated adjusted odds ratios using GAMs, smoothing on location. A 40-year residential history allowed for latency restrictions. We mapped spatially continuous odds ratios using GIS and identified statistically significant clusters using permutation tests. RESULTS: Maps of bladder cancer are essentially flat ignoring latency, but show a statistically significant hot spot near known Massachusetts Military Reservation (MMR) groundwater plumes when 15 years latency is assumed. The kidney cancer map shows significantly increased ORs in the south of the study area and decreased ORs in the north. CONCLUSION: Spatial epidemiology using individual level data from population-based studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of bladder cancer near MMR plumes that suggest further investigation using detailed exposure modeling.
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spelling pubmed-26524492009-03-07 Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data Vieira, Verónica Webster, Thomas Weinberg, Janice Aschengrau, Ann Environ Health Research BACKGROUND: In 1988, elevated cancer incidence in upper Cape Cod, Massachusetts prompted a large epidemiological study of nine cancers to investigate possible environmental risk factors. Positive associations were observed, but explained only a portion of the excess cancer incidence. This case-control study provided detailed information on individual-level covariates and residential history that can be spatially analyzed using generalized additive models (GAMs) and geographical information systems (GIS). METHODS: We investigated the association between residence and bladder, kidney, and pancreatic cancer on upper Cape Cod. We estimated adjusted odds ratios using GAMs, smoothing on location. A 40-year residential history allowed for latency restrictions. We mapped spatially continuous odds ratios using GIS and identified statistically significant clusters using permutation tests. RESULTS: Maps of bladder cancer are essentially flat ignoring latency, but show a statistically significant hot spot near known Massachusetts Military Reservation (MMR) groundwater plumes when 15 years latency is assumed. The kidney cancer map shows significantly increased ORs in the south of the study area and decreased ORs in the north. CONCLUSION: Spatial epidemiology using individual level data from population-based studies addresses many methodological criticisms of cluster studies and generates new exposure hypotheses. Our results provide evidence for spatial clustering of bladder cancer near MMR plumes that suggest further investigation using detailed exposure modeling. BioMed Central 2009-02-10 /pmc/articles/PMC2652449/ /pubmed/19208254 http://dx.doi.org/10.1186/1476-069X-8-3 Text en Copyright ©2009 Vieira et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Vieira, Verónica
Webster, Thomas
Weinberg, Janice
Aschengrau, Ann
Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title_full Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title_fullStr Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title_full_unstemmed Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title_short Spatial analysis of bladder, kidney, and pancreatic cancer on upper Cape Cod: an application of generalized additive models to case-control data
title_sort spatial analysis of bladder, kidney, and pancreatic cancer on upper cape cod: an application of generalized additive models to case-control data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2652449/
https://www.ncbi.nlm.nih.gov/pubmed/19208254
http://dx.doi.org/10.1186/1476-069X-8-3
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