Response: FACEing reality: productive tensions between our epidemiological questions, methods and mission

Educational note: types of causes

We explore the different types of causes that are commonly investigated by epidemiologists. We first distinguish between causes which are events (including actions) and causes which are states. Second, we distinguish between modifiable and non-modifiable states. This yields three types of causes: fixed states (non-modifiable), dynamic states (modifiable) and events (including actions). Different causes may have different characteristics: the methods available to study them, the types of possible biases, and therefore the types of evidence needed to infer causality, may differ according to the specific cause-effect relationship under study. Nevertheless, there are also substantial commonalities. This paper is intended to improve understanding of the different types of causes, and the different types of causality, that underpin epidemiological practice.

Post-Modern Epidemiology: When Methods Meet Matter

In the last third of the 20th century, etiological epidemiology within academia in high-income countries shifted its primary concern from attempting to tackle the apparent epidemic of noncommunicable diseases to an increasing focus on developing statistical and causal inference methodologies. This move was mutually constitutive with the failure of applied epidemiology to make major progress, with many of the advances in understanding the causes of noncommunicable diseases coming from outside the discipline, while ironically revealing the infectious origins of several major conditions. Conversely, there were many examples of epidemiologic studies promoting ineffective interventions and little evident attempt to account for such failure. Major advances in concrete understanding of disease etiology have been driven by a willingness to learn about and incorporate into epidemiology developments in biology and cognate data science disciplines. If fundamental epidemiologic principles regarding the rooting of disease risk within populations are retained, recent methodological developments combined with increased biological understanding and data sciences capability should herald a fruitful post-Modern Epidemiology world.

Causal criteria: time has come for a revision

Epidemiologists study associations but they are usually interested in causation that could lead to disease prevention. Experience show, however, that many of the associations we identify are not the causes we take an interest in (correlation is not causation). In order to proper translate association into causes, a set of causal criteria was developed 50-60 years ago and they became important tools guiding this translational process (sometimes correlation is causation). Best known of these are the Bradford Hill 'criteria'. In these last 50 years, epidemiologic theory and infrastructure have advanced rapidly without changes in these causal criteria. We think time has come to revisit the 'old' criteria to see which ones we should keep and which ones should be taken out or be replaced by new measures of association. Robustness of these criteria in attempts to make the association go away should have high priority. A group of renowned internationally recognized researchers should have this task. Since classifying associations as causes is often done in order to reduce or eliminate the exposures of concern results from conditional outcome research should also be used. We therefore suggest to add a 'consequence' criterion. We argue that a consequence criterion that provides a framework for assessing or prescribing action worthy or right in social contexts is needed. A consequence criterion will also influence how strict our causal criteria need to be before leading to action and will help in separating the 'causal discussion' and the discussion on what to do about it. A consequence criterion will be a tool in handling dilemmas over values (as social solidarity, fairness, autonomy). It will have implications for the interpretation and use of the procedural criteria of causality. Establishing interconnected procedural and consequence criteria should be a task for institutions representing and being recognized by experts, civil society and the state.