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Welcome to PSR's Environmental Health Policy Institute, where we ask questions -- then we ask the experts to answer them. Join us as physicians, health professionals, and environmental health experts share their ideas, inspiration, and analysis about toxic chemicals and environmental health policy.


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Uncertainty should not delay public health protections

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By Steven G. Gilbert, PhD DABT

This essay is in response to: How can we set science-based policies in the face of scientific uncertainty?

All scientific work is incomplete -- whether it be observational or experimental. All scientific work is liable to be upset or modified by advancing knowledge. That does not confer upon us a freedom to ignore the knowledge we already have or postpone the action that it appears to demand at a given time.

Sir Austin Bradford Hill (1965)

As Bradford Hill noted, there is no escape from uncertainty, and scientific advances modify our understanding of any issue. We need to acknowledge and address uncertainty without letting it paralyze our decision-making process as we strive to protect human and environmental health. Doing this requires that when we establish public policy, we take a precautionary approach that acknowledges an ethical responsibility to protect human and environmental health. Following tragic lessons, such as the fetal effects of thalidomide, we have adopted a very precautionary approach to putting new drugs on the market. The FDA requires the pharmaceutical industry to provide data demonstrating efficacy and safety of their products. However, despite numerous tragic incidents, such as mercury poisoning in Minamata, Japan, and then again in Iraq, and asbestos exposure causing cancer, we have yet to adopt a similar approach to preventing harmful exposure to industrial chemicals.

Uncertainty has been emphasized to delay or forestall regulations to protect public health. The classic example is how the tobacco industry denied and refuted that their products caused cancer or other health effects. Much of the discussion centered around proving causation, with industry arguing that causation could not be proven because there was always some uncertainty--some weakness in a study design or results. Denial of causation has been used repeatedly and to such an extent that a case can be made that uncertainty is manufactured expressly to delay and frustrate the regulatory process. David Michaels documents numerous cases of manufactured uncertainty in his excellent book Doubt Is Their Product: How Industry’s Assault on Science Threatens Your Health (2008). The title refers to a quote from a tobacco executive who emphasized that creating doubt in the science evidence was critical to their campaign to curtail health warnings about cigarettes. Another good example is lead: despite strong scientific evidence of its harmful effects on the nervous system, the U.S. allowed the use of lead paint to continue until 1978, while most of Europe banned it in the 1920s. Regulation in the U.S. took so long in part because the lead industry claimed that lead could not be definitively linked to health problems, and because policymakers accepted that claim.

Uncertainty can also be dissected and to some extent reduced. First, there is the fundamental uncertainty of not knowing what questions to ask. This can manifest itself in not knowing the most sensitive end point or health effect to study. For example, at high levels of exposure, lead in children can cause swelling of the brain and death in children, while even very low levels of exposure result in intellectual impairment. Having the right data and study design are essential.

Second is model or system uncertainty, where the relationship between variables is not understood, such as not knowing the mechanism of action or differences in dose response. For example, endocrine disruptors have different effects depending on low or high doses, and this profoundly affects policy and regulation of exposure.

Finally, there is statistical uncertainty or effects of study design. Variability in a measure is often related to sample size. Increasing the sample size reduces variability, allowing more definitive, statistically based results that support causation. Proper study design that accounts for variation within and between subjects is critical in controlling variability and, in essence, the certainty of the effects reported. In some ways this is the easiest to address, assuming there are ample resources and time.

More recently, the issues of decision making and uncertainty have been addressed by the precautionary principle, which states: “When an activity raises threats of harm to human health or the environment, precautionary measures should be take even if some cause and effect relationships are not fully established scientifically” (Wingspread Conference, 1998). This statement neatly brings together the ethical and scientific justifications for decision-making that prioritizes and protects human and environmental health. While some aspects of uncertainty can be systematically addressed through science, the fundamental change must be one of prioritizing our ethical responsibility to protect the biotic community. We must acknowledge that the externalization of costs causes unacceptable harm to the health of individuals and of society, and establish precautionary policies that acknowledge and prioritize our ethical responsibilities.

In conclusion, we have a tremendous amount of scientific knowledge that is underutilized while we pursue absolute proof of causation. Implementation of appropriate policy and regulation to protect the biotic community and future generations requires less focus on uncertainty and more emphasis on ethically based decision-making. 

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