Towards a realistic and relevant public health: the challenges of useful simplification.

Ian McDowell discusses many of the limitations of the risk factor paradigm in public health and epidemiology, building and amplifying on prior work. As discussed by McDowell, an important and perhaps unintended consequence of the focus on risk factors is that it has shifted epidemiologic inquiry from understanding causes to estimating ‘independent’ associations. This has impoverished epidemiology and has constrained not only the methods that we use but also the way in which we formulate research questions and even the research questions that we ask. For example, many epidemiologic investigations routinely formulate research questions in terms of identifying the presence of an ‘independent association’ of a given factor with an outcome, rather than on understanding the causes of an outcome or explaining (in McDowell’s sense) differences in health between people or between groups. In many ways, the methods that we use (in terms of both study designs and analytical approaches) which largely focus on enhancing our ability to estimate ‘independent effects’ constrain the questions that we ask and the answers that we obtain. The task is to develop an alternative approach that is rigorous, feasible and informative for public health. Unfortunately, as is often the case, this is easier to say than do. Three challenges that I will briefly discuss in turn are the challenge of multiple levels, the challenge of systems and the tension between full explanation and identification of intervention points. McDowell notes that ‘explaining public health matters involves many levels’. The need to consider multiple level of organization, from genes to society, when studying the causes of ill health, has been repeatedly noted by epidemiologists and public health researchers in recent years. But, of course, it would be impossible to study all possible levels all the time. The art of research is the ability to determine which levels are likely to be the most relevant in answering a particular research question. And then features of these levels need to be operationalized so that they can be studied empirically. This means that grandiose multilevel conceptual schemes need to be simplified so that they are tractable. The trick is to make them simple enough so that they can be studied empirically but not so simple that we get the wrong answer. Ultimately, this is what scientific inquiry is all about. An important aspect is understanding the connections between levels, or more specifically, how factors at one level may affect variations at another level. For example, even when investigating the causes of ill-health in individuals, factors defined at higher levels of organization may need to be considered. This is because higher level factors may be causally related to the health of individuals or may interact with individual-level factors. For example, living in an unequal society may operate as a stressor for a given individual that may in turn cause health problems, or inequality may interact with genes causing disease in susceptible individuals. Similarly, the group-level health outcome, or the disease rate, results from the joint and interacting effects of both individual and higher level factors. For this reason, I would quibble with McDowell’s statement that ‘causes of cases are typically drawn from lower levels of investigation while causes of patterns of incidence typically invoke higher level phenomena’. Both lower and higher level factors may be important for understanding the causes of disease in individuals and the causes of higher rates of disease in a particular population. Geoffrey Rose is often cited to support the notion that ‘the causes of cases’ may be