Spatial Analysis of Shared Risk Factors between Pleural and Ovarian Cancer Mortality in Lombardy (Italy)

Giorgia Stoppa, Carolina Mensi, Lucia Fazzo, Giada Minelli, Valerio Manno, Dario Consonni, Annibale Biggeri and Dolores Catelan
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Giorgia Stoppa: Unit of Biostatistics, Epidemiology and Public Health, DCTVPH, University of Padova, 35131 Padova, Italy
Carolina Mensi: Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
Lucia Fazzo: Department of Environment and Health, Istituto Superiore di Sanità, 00100 Rome, Italy
Giada Minelli: Statistical Service, Istituto Superiore di Sanità, 00100 Roma, Italy
Valerio Manno: Statistical Service, Istituto Superiore di Sanità, 00100 Roma, Italy
Dario Consonni: Occupational Health Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
Annibale Biggeri: Unit of Biostatistics, Epidemiology and Public Health, DCTVPH, University of Padova, 35131 Padova, Italy
Dolores Catelan: Unit of Biostatistics, Epidemiology and Public Health, DCTVPH, University of Padova, 35131 Padova, Italy

IJERPH, 2022, vol. 19, issue 6, 1-15

Abstract: Background: Asbestos exposure is a recognized risk factor for ovarian cancer and malignant mesothelioma. There are reports in the literature of geographical ecological associations between the occurrence of these two diseases. Our aim was to further explore this association by applying advanced Bayesian techniques to a large population (10 million people). Methods: We specified a series of Bayesian hierarchical shared models to the bivariate spatial distribution of ovarian and pleural cancer mortality by municipality in the Lombardy Region (Italy) in 2000–2018. Results: Pleural cancer showed a strongly clustered spatial distribution, while ovarian cancer showed a less structured spatial pattern. The most supported Bayesian models by predictive accuracy (widely applicable or Watanabe–Akaike information criterion, WAIC ) provided evidence of a shared component between the two diseases. Among five municipalities with significant high standardized mortality ratios of ovarian cancer, three also had high pleural cancer rates. Wide uncertainty was present when addressing the risk of ovarian cancer associated with pleural cancer in areas at low background risk of ovarian cancer. Conclusions: We found evidence of a shared risk factor between ovarian and pleural cancer at the small geographical level. The impact of the shared risk factor can be relevant and can go unnoticed when the prevalence of other risk factors for ovarian cancer is low. Bayesian modelling provides useful information to tailor epidemiological surveillance.

Keywords: asbestos-related diseases; ovarian cancer; pleural cancer; Bayesian shared spatial models; mortality; surveillance; epidemiology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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