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Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry
BACKGROUND: Previous ecological spatial studies of malignant mesothelioma cases, mostly based on mortality data, lack reliable data on individual exposure to asbestos, thus failing to assess the contribution of different occupational and environmental sources in the determination of risk excess in s...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404011/ https://www.ncbi.nlm.nih.gov/pubmed/25885893 http://dx.doi.org/10.1186/s12885-015-1301-2 |
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author | Corfiati, Marisa Scarselli, Alberto Binazzi, Alessandra Di Marzio, Davide Verardo, Marina Mirabelli, Dario Gennaro, Valerio Mensi, Carolina Schallemberg, Gert Merler, Enzo Negro, Corrado Romanelli, Antonio Chellini, Elisabetta Silvestri, Stefano Cocchioni, Mario Pascucci, Cristiana Stracci, Fabrizio Romeo, Elisa Trafficante, Luana Angelillo, Italo Menegozzo, Simona Musti, Marina Cavone, Domenica Cauzillo, Gabriella Tallarigo, Federico Tumino, Rosario Melis, Massimo Iavicoli, Sergio Marinaccio, Alessandro |
author_facet | Corfiati, Marisa Scarselli, Alberto Binazzi, Alessandra Di Marzio, Davide Verardo, Marina Mirabelli, Dario Gennaro, Valerio Mensi, Carolina Schallemberg, Gert Merler, Enzo Negro, Corrado Romanelli, Antonio Chellini, Elisabetta Silvestri, Stefano Cocchioni, Mario Pascucci, Cristiana Stracci, Fabrizio Romeo, Elisa Trafficante, Luana Angelillo, Italo Menegozzo, Simona Musti, Marina Cavone, Domenica Cauzillo, Gabriella Tallarigo, Federico Tumino, Rosario Melis, Massimo Iavicoli, Sergio Marinaccio, Alessandro |
author_sort | Corfiati, Marisa |
collection | PubMed |
description | BACKGROUND: Previous ecological spatial studies of malignant mesothelioma cases, mostly based on mortality data, lack reliable data on individual exposure to asbestos, thus failing to assess the contribution of different occupational and environmental sources in the determination of risk excess in specific areas. This study aims to identify territorial clusters of malignant mesothelioma through a Bayesian spatial analysis and to characterize them by the integrated use of asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM). METHODS: In the period 1993 to 2008, 15,322 incident cases of all-site malignant mesothelioma were recorded and 11,852 occupational, residential and familial histories were obtained by individual interviews. Observed cases were assigned to the municipality of residence at the time of diagnosis and compared to those expected based on the age-specific rates of the respective geographical area. A spatial cluster analysis was performed for each area applying a Bayesian hierarchical model. Information about modalities and economic sectors of asbestos exposure was analyzed for each cluster. RESULTS: Thirty-two clusters of malignant mesothelioma were identified and characterized using the exposure data. Asbestos cement manufacturing industries and shipbuilding and repair facilities represented the main sources of asbestos exposure, but a major contribution to asbestos exposure was also provided by sectors with no direct use of asbestos, such as non-asbestos textile industries, metal engineering and construction. A high proportion of cases with environmental exposure was found in clusters where asbestos cement plants were located or a natural source of asbestos (or asbestos-like) fibers was identifiable. Differences in type and sources of exposure can also explain the varying percentage of cases occurring in women among clusters. CONCLUSIONS: Our study demonstrates shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources, with major implications for public health policies, health surveillance, compensation procedures and site remediation programs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-015-1301-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4404011 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44040112015-04-21 Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry Corfiati, Marisa Scarselli, Alberto Binazzi, Alessandra Di Marzio, Davide Verardo, Marina Mirabelli, Dario Gennaro, Valerio Mensi, Carolina Schallemberg, Gert Merler, Enzo Negro, Corrado Romanelli, Antonio Chellini, Elisabetta Silvestri, Stefano Cocchioni, Mario Pascucci, Cristiana Stracci, Fabrizio Romeo, Elisa Trafficante, Luana Angelillo, Italo Menegozzo, Simona Musti, Marina Cavone, Domenica Cauzillo, Gabriella Tallarigo, Federico Tumino, Rosario Melis, Massimo Iavicoli, Sergio Marinaccio, Alessandro BMC Cancer Research Article BACKGROUND: Previous ecological spatial studies of malignant mesothelioma cases, mostly based on mortality data, lack reliable data on individual exposure to asbestos, thus failing to assess the contribution of different occupational and environmental sources in the determination of risk excess in specific areas. This study aims to identify territorial clusters of malignant mesothelioma through a Bayesian spatial analysis and to characterize them by the integrated use of asbestos exposure information retrieved from the Italian national mesothelioma registry (ReNaM). METHODS: In the period 1993 to 2008, 15,322 incident cases of all-site malignant mesothelioma were recorded and 11,852 occupational, residential and familial histories were obtained by individual interviews. Observed cases were assigned to the municipality of residence at the time of diagnosis and compared to those expected based on the age-specific rates of the respective geographical area. A spatial cluster analysis was performed for each area applying a Bayesian hierarchical model. Information about modalities and economic sectors of asbestos exposure was analyzed for each cluster. RESULTS: Thirty-two clusters of malignant mesothelioma were identified and characterized using the exposure data. Asbestos cement manufacturing industries and shipbuilding and repair facilities represented the main sources of asbestos exposure, but a major contribution to asbestos exposure was also provided by sectors with no direct use of asbestos, such as non-asbestos textile industries, metal engineering and construction. A high proportion of cases with environmental exposure was found in clusters where asbestos cement plants were located or a natural source of asbestos (or asbestos-like) fibers was identifiable. Differences in type and sources of exposure can also explain the varying percentage of cases occurring in women among clusters. CONCLUSIONS: Our study demonstrates shared exposure patterns in territorial clusters of malignant mesothelioma due to single or multiple industrial sources, with major implications for public health policies, health surveillance, compensation procedures and site remediation programs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12885-015-1301-2) contains supplementary material, which is available to authorized users. BioMed Central 2015-04-15 /pmc/articles/PMC4404011/ /pubmed/25885893 http://dx.doi.org/10.1186/s12885-015-1301-2 Text en © Corfiati et al.; licensee BioMed Central. 2015 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Corfiati, Marisa Scarselli, Alberto Binazzi, Alessandra Di Marzio, Davide Verardo, Marina Mirabelli, Dario Gennaro, Valerio Mensi, Carolina Schallemberg, Gert Merler, Enzo Negro, Corrado Romanelli, Antonio Chellini, Elisabetta Silvestri, Stefano Cocchioni, Mario Pascucci, Cristiana Stracci, Fabrizio Romeo, Elisa Trafficante, Luana Angelillo, Italo Menegozzo, Simona Musti, Marina Cavone, Domenica Cauzillo, Gabriella Tallarigo, Federico Tumino, Rosario Melis, Massimo Iavicoli, Sergio Marinaccio, Alessandro Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title | Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title_full | Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title_fullStr | Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title_full_unstemmed | Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title_short | Epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the Italian national registry |
title_sort | epidemiological patterns of asbestos exposure and spatial clusters of incident cases of malignant mesothelioma from the italian national registry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404011/ https://www.ncbi.nlm.nih.gov/pubmed/25885893 http://dx.doi.org/10.1186/s12885-015-1301-2 |
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