From John Snow to omics: the long journey of environmental epidemiology

A major difference between infectious and non-communicable diseases is that infectious diseases typically have unique necessary causes whereas noncommunicable diseases have multiple causes which by themselves are usually neither necessary nor sufficient. Epidemiology seems to have reached a limit in disentangling the role of single components in causal complexes, particularly at low doses. To overcome limitations the discipline can take advantage of technical developments including the science of the exposome. By referring to the interpretation of the exposome as put forward in the work of Wild and Rappaport, I show examples of how the science of multi-causality can build upon the developments of omic technologies. Finally, I broaden the picture by advocating a more holistic approach to causality that also encompasses social sciences and the concept of embodiment. To tackle NCDs effectively on one side we can invest in various omic approaches, to identify new external causes of non-communicable diseases (that we can use to develop preventive strategies), and the corresponding mechanistic pathways. On the other side, we need to focus on the social and societal determinants which are suggested to be the root causes of many non-communicable diseases

Health co-benefits of climate change action in Italy

The climate breakdown is increasingly affecting the health of people around the world. As weather extremes intensify, the global health burden of unhealthy diets, sedentary lifestyles, and air pollution increases too. Against this backdrop, overstretched health systems can take stock of the co-benefits that a low carbon transition could deliver if health is prioritised in climate policies.1 Yet, as pointed out in a recent commentary,2 the UN Climate Change Conference (COP26) in Glasgow, UK, put little focus on health-related goals. Similarly, health is often disregarded in countries’ nationally determined contributions and in national climate policies. The dissociation between public health policy and climate action translates into millions of avoidable adverse health outcomes and deaths each year. For example, reducing greenhouse gas emissions also reduces the effect of air pollution, which is the largest environmental cause of disease and mortality in Europe in terms of measurable effect

Causality in cancer research: a journey through models in molecular epidemiology and their philosophical interpretation

In the last decades, Systems Biology (including cancer research) has been driven by technology, statistical modelling and bioinformatics. In this paper we try to bring biological and philosophical thinking back. We thus aim at making different traditions of thought compatible: (a) causality in epidemiology and in philosophical theorizing—notably, the “sufficient-component-cause framework” and the “mark transmission” approach; (b) new acquisitions about disease pathogenesis, e.g. the “branched model” in cancer, and the role of biomarkers in this process; (c) the burgeoning of omics research, with a large number of “signals” and of associations that need to be interpreted. In the paper we summarize first the current views on carcinogenesis, and then explore the relevance of current philosophical interpretations of “cancer causes”. We try to offer a unifying framework to incorporate biomarkers and omic data into causal models, referring to a position called “evidential pluralism”. According to this view, causal reasoning is based on both “evidence of difference-making” (e.g. associations) and on “evidence of underlying biological mechanisms”. We conceptualize the way scientists detect and trace signals in terms of information transmission, which is a generalization of the mark transmission theory developed by philosopher Wesley Salmon. Our approach is capable of helping us conceptualize how heterogeneous factors such as micro and macro-biological and psycho-social—are causally linked. This is important not only to understand cancer etiology, but also to design public health policies that target the right causal factors at the macro-level