Causality, Causes, and Causal... Health Article

CAUSALITY, CAUSES, AND CAUSAL INFERENCE

Causality describes ideas about the nature of the relations of cause and effect. A cause is something that produces or occasions an effect. Causal inference is the thought process that tests whether a relationship of cause to effect exists.

CAUSALITY

Ideas about cause vary as culture and philosophical concepts generate their own momentum and logical requirements. In epidemiology, ideas of causality changed as societies, understanding of disease, and technical resources changed. In nineteenth-century England, William Farr, John Snow, John Simon, and others founded an ecologic epidemiology, imbued with the Sanitary Movement's concern about the wretched context of urbanization and industrialization and its attendant miasma theory.

Late in the century the advances of Louis Pasteur, Robert Koch, and others studying bacteria displaced the theory that miasma caused disease. In Germany, this specific-cause theory was challenged early in the twentieth century. Germ theory sought proximate, singular microbial causes of disease. For seventy-five years, however, it dominated an anglophone laboratory-based epidemiology and focused on infectious disease control.

By the mid–twentieth century, epidemic infectious disease was receding in the face of effective action and social change. Epidemic chronic diseases—cancer and respiratory or cardiac disorders—overrode other epidemiological concerns. A. Bradford Hill, Richard Doll, Jeremy Morris, and others led a search for causal factors in the new epidemics. The need became apparent for theory to accommodate multiple coexisting causes, now understood as risk factors.

Such shifts are inevitable for and epidemiology obliged, in a dynamic world, always to evolve new means and theory for coping. Unamended multiple cause theory too is unlikely to be enough to meet rising challenges. Despite its core in population level studies, epidemiology in the past half century concentrated on individual-level disease risk, but studies on several levels, including change over time, are increasingly frequent, however.

CAUSES

For contemporary epidemiologists, what elements constitute the idea of cause? This public health science is chiefly observational. Neither humans nor societies are readily manipulable as rigorous experiment requires, excepting circumstances such as permit and clinical trials, which can randomize groups to neutralize differences other than the experimental intervention.

In the observational sciences, inference about causes is well served by a pragmatic concept of determinants, here defined as something making a difference to outcome. Everyone would not accept so broad a sweep. Galileo's seventeenth-century formulation was that causes be "necessary and sufficient." In the experimental sciences this came to mean one to one relationships of specific causes to given effects. In 1840, Friedrich Henle developed a similar mode for the testing of his idea that infection, not miasma, was a cause for disease.

Later, Koch revised Henle in devising a set of postulates. These sealed Koch's work on bacteria as the proximate cause of tuberculosis. In the germ theory era, the postulates served to guide the search for specific organisms as one to one causes of given diseases. The postulates require laboratory-based experiment; they entail not only observation (does a singular bacterial distribution parallel disease-affected sites?) but intervention (do bacteria, cultured and then transmitted to animals, produce lesions analogous to human disease?).

Causality, thus defined by experiment with specified active agents producing change, excludes from consideration two other types. First, it excludes steady-state conditions, like sex or social position or climate or location. Being contextual, if not always passive, these cannot be actively structured to produce change, as is done in experiment. In the lexicon of determinants for noninterventionist science, such conditions are nonetheless determinants. Experiment cannot reproduce them; they are detected in controlled comparisons of different times and places.

Second, change upon rigorous experimental intervention cannot but exclude a panoply of determinants antecedent and subsequent to the change agent. A table of the possible combinations inherent in Galileo's causal requirements results in the following:

Here, determinants emerge as necessary and sufficient (row 1: both always present); necessary but not sufficient (row 2: always present but only with others); sufficient but not necessary (row 3: sometimes effective alone); and, probably most often, neither necessary nor sufficient but contributory (row 4). Thus, taken separately, Galileo's criteria encompass a multicausal theory that accommodates conditions and causal chains. Without multicausality, in truth, no theoretical legitimation exists for the chronic disease epidemiology of the twentieth century.