An epidemiologic view of causation: how it differs from the legal.

• Author: Dreyer, Nancy A.

THE PROCESS of determining causation and, in fact, the ultimate need to determine causation is different in law and science. In law, the goal of fairness seems to be paramount. Decisions are required, no matter whether the true causes are known or understood. In contrast, scientists have been described as "practitioners of a discipline that seeks, but never finds, absolute truth" and as people who use a "variety of criteria to evaluate data in conditions that provide less than total certainty."(1)

If lawyers and courts knew how epidemiologists look at causation and were aware of some of the methods used to provide scientific inferences, perhaps they would recognize the case for accepting the tentativeness of science and the scientific process. At a minimum, this knowledge would enhance their facility to make fair and equitable decisions.

WHAT IS EPIDEMILOGY?

Epidemiology is the science of the occurrence of human illness.(2) First and foremost, epidemiologists' work concerns human beings, not animals, which immediately relieves one of all the problems of extrapolating among species. Epidemiology is not the science of determining the cause of disease in an individual. No method in any science can determine the specific cause of a specific individual's disease.

Epidemiologists study groups and make causal inferences based on aggregate data. Their work is generally non-experimental. Much epidemiologic information comes from studies that utilize some facets of existing information to draw inferences about cause and effect. For example, to learn about the effects of residential exposure to commercial nuclear power, epidemiologists might compare the health of people who reside near a nuclear power plant with the health of those who live far from the plant. To learn about drug safety, they might compare users of a particular drug with users of other drugs approved for the same indication and compare side effects among the groups.

RELATIVE RISK

A commonly used epidemiologic measure of effect is the "relative risk," which is the ratio of the risks for exposed and unexposed people. If the relative risk is equal to one, indicating the same risk for exposed and unexposed people, then the exposure has no effect. A relative risk of two would indicate a doubling in risk for exposed individuals relative to unexposed individuals.

The emphasis in epidemiology is on the estimation of effects, and good studies include an assessment of the likelihood of measurement error and the potential for bias. Random error, often called "noise," reduces the precision of an effect estimate, or "signal." Epidemiologists account for this by creating a confidence interval around the point estimate of effect. Larger studies have less random error. Systematic errors, also known as non-random error and bias, also distort the effect estimates.(3) Good investigators must be self critical and examine how non-random error could influence their result.

In epidemiologic terms, a cause is an "act or event or state of nature"--for simplicity, it may be referred to as an exposure--"which initiates or permits, alone or in conjunction with other causes, a sequence of events, resulting in an effect."(4) In most instances, the exposure is neither necessary nor sufficient by itself to cause the disease. Rather, most causes are components of at least one sufficient cause.

Causes that inevitably produce the effect are sufficient. The disease may require some time to become evident, and during this induction period, the disease might actually be cured or the...