1. Campania and cancer mortality: An inseparable pair? The role of environmental quality and socio-economic deprivation.
- Author
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Agovino, Massimiliano, Cerciello, Massimiliano, and Musella, Gaetano
- Subjects
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ENVIRONMENTAL health , *SOCIOECONOMIC factors , *TUMORS , *METROPOLITAN areas , *PROBABILITY theory - Abstract
The region of Campania in Southern Italy features high levels of socio-economic deprivation and low levels of environmental quality. A vast strand of the scientific literature has tried to verify whether poor environmental quality and widespread socio-economic deprivation might explain the high cancer mortality rates (CMRs) observed, especially in the municipalities – infamously labelled as the 'Land of Fires' – that were hit most severely by the crisis. While some studies managed to identify links between these two confounding factors and cancer mortality, the evidence is overall mixed. Interesting information may be drawn from the observation of municipal data: in spite of previous claims, some municipalities featuring high environmental quality and low socio-economic deprivation also display high CMRs, while other Campanian municipalities facing disastrous environmental and socio-economic conditions are characterised by low CMRs. These figures, in contrast to common sentiment and previous studies, need to be investigated thoroughly in order to assess the exact role of the confounding factors. In this work, we aim to identify the municipalities where confounding factors act as driving forces in the determination of high CMRs through an original multi-step analysis based on frequentist and Bayesian analysis. Pinpointing these municipalities could allow policymakers to design targeted and effective policy measures aimed at reducing cancer mortality. • This work studies Cancer Mortality Rates (CMRs) at the municipal level in Campania. • We identify environmental quality and socio-economic deprivation as confounding factors. • A multistep analysis is proposed to assess the role of the Confounding Factors (CFs). • Using Bayesian methods, we find that the CFs drive municipal differences in CMRs. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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