{"title":"2000-2018 年伦巴第大区(意大利)因接触石棉而导致的卵巢癌死亡人数。","authors":"Giorgia Stoppa, Carolina Mensi, Lucia Fazzo, Giada Minelli, Valerio Manno, Alessandro Marinaccio, Dario Consonni, Annibale Biggeri, Dolores Catelan","doi":"10.1136/oemed-2023-109342","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>We aimed to estimate the fraction of deaths from ovarian cancer attributable to asbestos exposure in Lombardy Region, Italy, using a novel approach that exploits the fact that ovarian cancer asbestos exposure is associated with pleural cancer and other risk factors for breast cancer.</p><p><strong>Methods: </strong>This ecological study is based on the Italian National Institute of Statistics mortality data. We formulate a trivariate Bayesian joint disease model to estimate the attributable fraction (AF) and the number of ovarian cancer deaths attributable to asbestos exposure from the geographic distribution of ovarian, pleural and breast cancer mortality at the municipality level from 2000 to 2018. Expected deaths and standardised mortality ratios were calculated using regional rates.</p><p><strong>Results: </strong>We found shared dependencies between ovarian and pleural cancer, which capture risk factors common to the two diseases (asbestos exposure), and a spatially structured clustering component shared between ovarian and breast cancer, capturing other risk factors. Based on 10 462 ovarian cancer deaths, we estimated that 574 (95% credibility interval 388-819) were attributable to asbestos (AF 5.5%; 95% credibility interval 3.7-7.8). AF reaches 34%-47% in some municipalities with known heavy asbestos pollution.</p><p><strong>Conclusions: </strong>The impact of asbestos on ovarian cancer occurrence can be relevant, particularly in areas with high asbestos exposure. Estimating attributable cases was possible only by using advanced Bayesian modelling to consider other risk factors for ovarian cancer. These findings are instrumental in tailoring public health surveillance programmes and implementing compensation and prevention policies.</p>","PeriodicalId":19459,"journal":{"name":"Occupational and Environmental Medicine","volume":" ","pages":"359-365"},"PeriodicalIF":3.9000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11347218/pdf/","citationCount":"0","resultStr":"{\"title\":\"Ovarian cancer deaths attributable to asbestos exposure in Lombardy (Italy) in 2000-2018.\",\"authors\":\"Giorgia Stoppa, Carolina Mensi, Lucia Fazzo, Giada Minelli, Valerio Manno, Alessandro Marinaccio, Dario Consonni, Annibale Biggeri, Dolores Catelan\",\"doi\":\"10.1136/oemed-2023-109342\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>We aimed to estimate the fraction of deaths from ovarian cancer attributable to asbestos exposure in Lombardy Region, Italy, using a novel approach that exploits the fact that ovarian cancer asbestos exposure is associated with pleural cancer and other risk factors for breast cancer.</p><p><strong>Methods: </strong>This ecological study is based on the Italian National Institute of Statistics mortality data. We formulate a trivariate Bayesian joint disease model to estimate the attributable fraction (AF) and the number of ovarian cancer deaths attributable to asbestos exposure from the geographic distribution of ovarian, pleural and breast cancer mortality at the municipality level from 2000 to 2018. Expected deaths and standardised mortality ratios were calculated using regional rates.</p><p><strong>Results: </strong>We found shared dependencies between ovarian and pleural cancer, which capture risk factors common to the two diseases (asbestos exposure), and a spatially structured clustering component shared between ovarian and breast cancer, capturing other risk factors. Based on 10 462 ovarian cancer deaths, we estimated that 574 (95% credibility interval 388-819) were attributable to asbestos (AF 5.5%; 95% credibility interval 3.7-7.8). AF reaches 34%-47% in some municipalities with known heavy asbestos pollution.</p><p><strong>Conclusions: </strong>The impact of asbestos on ovarian cancer occurrence can be relevant, particularly in areas with high asbestos exposure. Estimating attributable cases was possible only by using advanced Bayesian modelling to consider other risk factors for ovarian cancer. These findings are instrumental in tailoring public health surveillance programmes and implementing compensation and prevention policies.</p>\",\"PeriodicalId\":19459,\"journal\":{\"name\":\"Occupational and Environmental Medicine\",\"volume\":\" \",\"pages\":\"359-365\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-08-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11347218/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Occupational and Environmental Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1136/oemed-2023-109342\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Occupational and Environmental Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1136/oemed-2023-109342","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
Ovarian cancer deaths attributable to asbestos exposure in Lombardy (Italy) in 2000-2018.
Objectives: We aimed to estimate the fraction of deaths from ovarian cancer attributable to asbestos exposure in Lombardy Region, Italy, using a novel approach that exploits the fact that ovarian cancer asbestos exposure is associated with pleural cancer and other risk factors for breast cancer.
Methods: This ecological study is based on the Italian National Institute of Statistics mortality data. We formulate a trivariate Bayesian joint disease model to estimate the attributable fraction (AF) and the number of ovarian cancer deaths attributable to asbestos exposure from the geographic distribution of ovarian, pleural and breast cancer mortality at the municipality level from 2000 to 2018. Expected deaths and standardised mortality ratios were calculated using regional rates.
Results: We found shared dependencies between ovarian and pleural cancer, which capture risk factors common to the two diseases (asbestos exposure), and a spatially structured clustering component shared between ovarian and breast cancer, capturing other risk factors. Based on 10 462 ovarian cancer deaths, we estimated that 574 (95% credibility interval 388-819) were attributable to asbestos (AF 5.5%; 95% credibility interval 3.7-7.8). AF reaches 34%-47% in some municipalities with known heavy asbestos pollution.
Conclusions: The impact of asbestos on ovarian cancer occurrence can be relevant, particularly in areas with high asbestos exposure. Estimating attributable cases was possible only by using advanced Bayesian modelling to consider other risk factors for ovarian cancer. These findings are instrumental in tailoring public health surveillance programmes and implementing compensation and prevention policies.
期刊介绍:
Occupational and Environmental Medicine is an international peer reviewed journal covering current developments in occupational and environmental health worldwide. Occupational and Environmental Medicine publishes high-quality research relating to the full range of chemical, physical, ergonomic, biological and psychosocial hazards in the workplace and to environmental contaminants and their health effects. The journal welcomes research aimed at improving the evidence-based practice of occupational and environmental research; including the development and application of novel biological and statistical techniques in addition to evaluation of interventions in controlling occupational and environmental risks.