Now that you know that corporations have a nasty habit of manufacturing doubt about the harms caused by their products, I wanted to give you some background to help you understand how that game is played.
Unfortunately, doubt is a very easy product to create. As Dr. David Michaels (the current director of OSHA) says in his book, Doubt is Their Product, “Scientists do not have the truth; we seek the truth. We do not deal in absolute certainties but in the ‘weight of the evidence.’ We combine and evaluate information from many sources, and we apply both quantitative and qualitative methods in order to overcome real uncertainty and gaps in scientific knowledge.” This reality is true for science in general, but it applies in spades to the science of assessing whether chemicals cause disease.
Establishing that long-term exposure to a chemical can cause a chronic disease, like cancer, is a very difficult thing for even the best scientists in the world to do. Indeed, proof of chemical causation is almost always fraught with uncertainty. Scientists cannot ethically experiment on humans to confirm whether chemicals suspected of being harmful really cause that type of harm. Instead, scientists examining chemical causation must look primarily to two other types of evidence: epidemiology (human observational studies) and toxicology (laboratory experiments on animals and cells).
Although scientists can and do differ about whether evidence from epidemiology studies or toxicology studies are more important, most judges have decided that the most important evidence for proving causation in a courtroom must come from epidemiology studies. Epidemiological studies seek to determine whether there is a statistical association between exposure to particular chemicals and particular kinds of diseases or health outcomes. For example, a common type of epidemiological study will examine workers who have been exposed to a chemical occupationally, to determine whether those workers are suffering more cancers (or other diseases) than would be expected if those workers had not been exposed. The number of cancers among the group of chemically-exposed workers will be compared with the number of the same types of cancers in some control group. The control group might be the general population in the area where the workers live, or it might be a group of other workers who have not been exposed to the same chemical. If the exposed group has more cancers than the control group, then there is a “positive association” between exposure to the chemical and cancer. But such studies are subject to easy manipulation.
As Dr. Michaels explains:
By its nature, epidemiology is a sitting duck for uncertainty campaigns. Large epidemiological studies are complicated structures that require complex statistical analysis. … Judgment is called for all along the way, so disciplined integrity is mandatory. The nature of epidemiology and the ground rules epidemiologists use ensure that it is far more difficult to find a false positive result than a false negative one. It is relatively easy to design a study or reanalyze someone else’s data in a way that ensures that the new study will find no association between the exposure and the disease in question.
In other words, it is easy to manipulate the design of epidemiology studies to generate a “false negative” result – that is, a result that fails to find an association between the chemical and the disease, despite the fact that a true association exists. Unsurprisingly, this is one of the tried and true ways for corporations to generate doubt – they hire scientists to conduct epidemiology studies that are designed in such a way that they will probably not find a positive association. For example, most carcinogens only cause cancer many years (and often decades) after exposure. But corporate scientists might design studies to avoid finding any association by tracking a group of workers for a shorter period of time than might be necessary for the chemical to cause cancer in the exposed group. Effectively, a study designed in this way is akin to checking on the health of a patient who has just jumped off of the roof of a 40 story building when he has only fallen 20 floors — halfway to the street.
After designing and conducting studies to generate negative results, chemical producers will then point to those studies as proof that there is no causal connection between their chemicals and the cancer in question. But a failure to find an association in one or more epidemiological studies — even if, unlike most corporate-sponsored research, those studies are well-designed — is not the same as affirmative evidence of the absence of causal connection between the chemical and the disease. Just because you didn’t see evidence of the connection in that particular study does not demonstrate that no such connection exists. The disease being studied might be too rare to come up in the study group with sufficient frequency, there might be insufficient or inaccurate information about the extent of the chemical exposures suffered by the exposed workers, or the particular group of workers being studied might be particularly resilient. Just because you visit the North Pole for a few hours and don’t see a polar bear, you have not proven that there are no polar bears at the North Pole.
Next time I’ll continue this discussion and give you a few specific examples or corporate doubt production.