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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Giorgia Stoppa & Carolina Mensi & Lucia Fazzo & Giada Minelli & Valerio Manno & Dario Consonni & Annibale Biggeri & Dolores Catelan, 2022. "Spatial Analysis of Shared Risk Factors between Pleural and Ovarian Cancer Mortality in Lombardy (Italy)," IJERPH, MDPI, vol. 19(6), pages 1-15, March.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:6:p:3467-:d:771635
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    References listed on IDEAS

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    1. D. J. Spiegelhalter & E. C. Marshall, 2006. "Strategies for inference robustness in focused modelling," Journal of Applied Statistics, Taylor & Francis Journals, vol. 33(2), pages 217-232.
    2. Leonhard Knorr‐Held & Nicola G. Best, 2001. "A shared component model for detecting joint and selective clustering of two diseases," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 164(1), pages 73-85.
    3. Diana Arachi & Sugio Furuya & Annette David & Alexander Mangwiro & Odgerel Chimed-Ochir & Kenneth Lee & Peter Tighe & Jukka Takala & Tim Driscoll & Ken Takahashi, 2021. "Development of the “National Asbestos Profile” to Eliminate Asbestos-Related Diseases in 195 Countries," IJERPH, MDPI, vol. 18(4), pages 1-20, February.
    4. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
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    Cited by:

    1. Getayeneh Antehunegn Tesema & Zemenu Tadesse Tessema & Stephane Heritier & Rob G. Stirling & Arul Earnest, 2023. "A Systematic Review of Joint Spatial and Spatiotemporal Models in Health Research," IJERPH, MDPI, vol. 20(7), pages 1-24, March.
    2. Cézar Akiyoshi Saito & Marco Antonio Bussacos & Leonardo Salvi & Carolina Mensi & Dario Consonni & Fernando Timoteo Fernandes & Felipe Campos & Franciana Cavalcante & Eduardo Algranti, 2022. "Sex-Specific Mortality from Asbestos-Related Diseases, Lung and Ovarian Cancer in Municipalities with High Asbestos Consumption, Brazil, 2000–2017," IJERPH, MDPI, vol. 19(6), pages 1-12, March.

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