Whether you look on the community or the molecular scale, cancer is largely a matter of chance. Every second, millions of cells in a body are copying their DNA as they prepare to divide. It is an imperfect process, and errors occur at every turn. Some are corrected, some are not, and every once in a while the right combination causes a cell to begin multiplying indefinitely, bringing forth a malignant tumor.
Many chemicals, natural and synthetic, can damage DNA and increase the background mutation rate. But most cancers require several genetic hits—whether they are spontaneous, inherited, or induced from outside. Cancer clusters have been verified among workers who are exposed for years to high levels of carcinogens such as asbestos. The hits just keep on coming. But even occupational clusters are rare. One study after another has concluded that the relatively dilute exposures received by the public are probably not causing much cancer, even in places near toxic waste dumps, like Love Canal.
Toms River, like Woburn, appeared to be an exception. But was the difference caused by two federal Superfund sites that had been polluting the area for years? Or was it a statistical anomaly? Years earlier, the epidemiologist Seymour Grufferman coined the term “Texas sharpshooter effect.” Stand way back and blast the side of a barn with a shotgun and then find some holes that are crowded together. Draw a circle around them and you have what looks like a bull’s-eye.
When New Jersey officials concluded that there was probably nothing to worry about in Toms River, angry residents stormed the county health department. As the pressure continued, the state joined federal epidemiologists in a full-blown investigation. Interviews were conducted. Birth records were studied. Computer models were made of the water system and of the paths toxic emissions might have followed through the air. DNA was tested, and effluents were analyzed.
As epidemiologists worked through the data, they were struck by a pattern of evidence that appeared to implicate one of the town’s polluted well fields. But given the small number of cases, the uncertainty was overwhelming. In the end, two correlations seemed to rise above the rest—but only when boys were excluded from the statistics. That left eight girls whose mothers had drunk most often from the well field. Five of the girls had leukemia, a cancer of the blood, and three did not. The boys were apparently unaffected. A similar association was suggested for leukemia in girls with prenatal exposure to polluted air. For the other types of cancer a link to environmental contaminants couldn’t be established.
So what are we to make of this? As epidemiologists parsed the numbers this way and that—including one age group in their calculations and excluding another, or making different assumptions about when contamination reached the water taps—were they closing in on a deeply hidden truth or picking and choosing among the data? There was no biological explanation for why male and female fetuses would respond differently to the carcinogens. If limiting the analysis to girls hadn’t uncovered an association, would the next step have been to distinguish between those with brown hair and blond?
The study ultimately concluded with “considerable uncertainty” that water and air pollution might have been risk factors for leukemia in prenatally exposed girls. As with Woburn, the evidence was ambiguous and the litigation was settled out of court. The polluters paid off the plaintiffs while denying blame, and the families were left feeling robbed of vindication.
Given those kinds of subtleties and an anticlimactic ending, it takes a good writer to tell a compelling tale. With a talent for describing courtroom drama, Jonathan Harr turned the Woburn case into a best-selling book, A Civil Action. Where Fagin excels is in vividly recounting the science of carcinogenicity and the remarkable history of how the international chemical and pharmaceutical industry arose from a few Swiss dye makers—along with the problem of pollution and the ever inexact science of epidemiology. He brings the complexities of Toms River to life. The result is an honest, thoroughly researched, intelligently written book. It closes with the warning that there may be more to Toms River than what could be confidently concluded from the data—and other towns where industrial pollution is causing a barely noticeable but deadly rise in cancer.
That may be, but no matter how hard I squinted at the numbers, I found it hard to be convinced that there had been a cancer problem in Toms River. The tools of statistics, so powerful when applied to large populations, break down with small numbers. As so often in life, we’re left wondering how to distinguish between randomness and patterns too subtle to see.
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