Why We Often Get Risks Wrong

TERENCE HINES

Getting Risk Right: Understanding the Science of Elusive Health Risks. By Geoffrey C. Kabat. Columbia University Press, New York, 2016. ISBN 9 780231 166461. 272 pp. Hardcover, $35.00.

Geoffrey Kabat devoted his previous book, Hyping Health Risks: Environmental Hazards in Daily Life and the Science of Epidemiology (Columbia University Press 2008, reviewed in the July/August 2009 SI) to debunking overblown claims of risks of various environmental agents such as environmental causes of breast cancer on Long Island and radon and electromagnetic fields as causative agents in cancer. In his new book, Kabat goes beyond simple debunking and sets himself a much more ambitious task: “Two questions at the heart of this book are, first, how is it that extraordinary progress is made in solving certain problems, whereas in other areas little progress is made, and, second, why do instances of progress get so little attention, while those issues that gain attention often tend to be scientifically questionable?” (p. 27).

In the first three chapters, Kabat writes about how investigations of claimed risks sometimes get it right and uncover the actual causes of real risks versus investigations of non-risks that end up causing much unneeded anxiety and wasting large sums of research funds and researchers’ time and effort. The last four chapters are case studies of specific investigations. Two of these investigations resulted, through careful and arduous medical detective work, in uncovering the real causes of a very puzzling disease in one case and a type of cancer in the other. The other two case studies are of investigations of environmental agents—cell phones and endocrine disruptors—that went badly off the rails and continue to unduly alarm the public and consume research time and money that could be much better used studying actual risks.

The book starts with a brief introductory chapter, “The Illusion of Validity and the Power of ‘Negative Thinking.’” The second chapter, “The Splendors and Miseries of Associations,” begins with a discussion of basic concepts in epidemiology. It emphasizes the complexity of teasing apart causation when causation is a complex network of interacting variables. This could have been a bit clearer in places. For example, saying that “If two variables are correlated, as one increases, the other increases” (p. 14) ignores the existence of negative correlations. The chapter highlights the work of John Ioannidis, whose 2005 paper “Why Most Published Research Findings are False” (PLoS Medicine 2005, 2, e124) caused much controversy when it appeared. The paper applied to medical research, not to other areas of scientific studies. The paper was often thought to be an attack on biomedical research in general, arguing that medical research really couldn’t contribute to distinguishing between what was or was not risky or beneficial.