Redundant causation from a sufficient cause perspective

Abstract

Sufficient causes of disease are redundant when an individual acquires the components of two or more sufficient causes. In this circumstance, the individual still would have become diseased even if one of the sufficient causes had not been acquired. In the context of a study, when any individuals acquire components of more than one sufficient cause over the observation period, the etiologic effect of the exposure (defined as the absolute or relative difference between the proportion of the exposed who develop the disease by the end of the study period and the proportion of those individuals who would have developed the disease at the moment they did even in the absence of the exposure) may be underestimated. Even in the absence of confounding and bias, the observed effect estimate represents only a subset of the etiologic effect. This underestimation occurs regardless of the measure of effect used.To some extent, redundancy of sufficient causes is always present, and under some circumstances, it may make a true cause of disease appear to be not causal. This problem is particularly relevant when the researcher's goal is to characterize the universe of sufficient causes of the disease, identify risk factors for targeted interventions, or construct causal diagrams. In this paper, we use the sufficient component cause model and the disease response type framework to show how redundant causation arises and the factors that determine the extent of its impact on epidemiologic effect measures.

Figure 1

Sufficient component causal (SCC) model with five sufficient causes of disease. Disease may result from: (1) the presence of both E and U₁; or (2) the presence of both U₂ and U₃; or (3) the presence of both U₁ and U₄; or (4) the presence of U₅; or (5) the absence of E (i.e. the complement of E, E^C) and the presence of U₆.

Figure 2

How redundancy arises from the perspective of the Sufficient Component Cause model (E is the exposure of interest).

Figure 3

Relationship among etiologic, excess, etiologic redundant cases and non-causal cases. Where, 'p' means proportion, 'n' means non-redundant, and 'r' means redundant.

Figure 4

Illustrative hypothetical example: two sufficient causes of liver cancer.

Figure 5

Acquisition of components and disease (Dz) status for liver cancer (based on the hypothetical causal model shown in Figure 4) in ten individuals over the course of a 12 year study.