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.

意大利南部的坎帕尼亚地区社会经济贫困程度高，环境质量低。大量科学文献试图验证恶劣的环境质量和广泛的社会经济剥夺是否可以解释所观察到的高癌症死亡率 (CMR)，尤其是在被称为“火之国”的城市受危机影响最严重。虽然一些研究设法确定了这两个混杂因素之间的联系和癌症死亡率，证据总体上喜忧参半。从市政数据的观察中可以得出有趣的信息：尽管之前有过这样的说法，但一些环境质量高、社会经济贫困程度低的城市也表现出较高的 CMR，而其他面临灾难性环境和社会经济条件的坎帕尼亚城市的特点是低 CMR。与普遍情绪和以前的研究相比，这些数字需要彻底调查，以评估混杂因素的确切作用。在这项工作中，我们的目标是通过基于频率论和贝叶斯分析的原始多步分析，确定混杂因素在确定高 CMR 时充当驱动力的城市。