FAQ, cont'd:
Q: I heard there were some studies more than a decade ago that looked at cancer and congenital diseases. What do you think about these studies?
A: I think these studies were promising first steps. But, like the Long Island Breast Cancer Study Project, ultimately they could have gone much deeper and both experienced frustrating complications. I’ve outlined a few of those complications here.
The study of cancer surrounding the lab done by the legislative task force in 1998 was complicated by the following facts:
--This was an ecological study, which is inherently limited, as discussed within the study itself. The paper described the study as being based primarily
on rates (as opposed to true counts or independent control groups). The decision to choose this type of study was explained in the paper as the
following: this type of study can be conducted relatively quickly and inexpensively because they are based on available data.
--The study used NY State cancer registry data from 1988-1992. In 1996, NY State changed the way that breast cancer cases are counted in order
to improve comparability with rates nationwide. Prior to 1996, NY State counted only one tumor per cancer site per person per lifetime. Therefore,
a woman who developed breast cancer in both breasts would still be counted as just one case. In order to be consistent with SEER coding rules,
beginning with 1996 data, NY State began counting a second tumor in the same person in the same primary cancer site (e.g., the breast) as an
additional “new” cancer case. As a result of these changes, cancer rates in NY State since 1996 can now be compared with rates based on SEER
data and most other states. Rates prior to 1996 are not directly comparable.
--The task force was charged with studying congenital malformations along with cancer. It could not complete this half of the study because,
as it notes, “The congenital malformations data is poor.” The 15-mile radius circle could not be used; the congenital malformations registry is not
equipped to geocode data to census tracts or to groups of census tracts. They can report zip codes for cases, but to do so for these data would have
repeatedly violated the “rule of six.” Therefore, the question of whether malformation rates in Suffolk County are higher in communities near BNL
than in communities away from it, cannot be answered.
--Within the discussion of unreported rates and unstable rates, the study talks about the issues of basing their findings on such small towns and areas
and the complications that arise in this type of study. “These circumstances have serious statistical consequences for small area with small populations,
especially if they have institutional housing and transient populations.” Shirley has an unusually large amount of both institutional housing and a
transient population (due to rentals).
--The high rate for breast cancer on the east end of Long Island found in this study was not observed in an earlier study of breast cancer rates for Long
Island communities, including a 1990 NY State Dept of Health Study. I believe the fact that this small study ended up with completely opposite
results goes to my point of the issue with imperfect studies—a cross-section of breast cancer studies on Long Island have all turned up differing
statistics and accounts. This is again one of my reasons for showing the human side of the debate with memoir rather than simply relying on numbers.
--The study did not include lung cancer, because as an ecological study it could not reach out to the people sick with the cancer and ask if they also
smoked, a detail that typically would be considered during the study. So instead, they simply didn’t look at it.
--The childhood cancer study was also incomplete. Due to the rare nature of the disease, this study was complicated by what is known as “The Rule of Six”:
the cancers must first be reported to the state, then if there are fewer than 6 in a region they are not counted due to a clause that “protects confidentiality
of cancer patients.” There were too few cancers within the geographic areas for the cancers to count—we can’t know if there was one case reported or 5.
We only know it was under 6, so the data was not counted. Randy Snell attempted to provide further information on families afflicted with the disease
that were not turning up in the registry, but this information was ultimately ignored as well because it did not come from a “scientific” source.
The BNL Worker Group study was complicated by the following facts:
--Dean Helms, then-executive manager of the Brookhaven National Laboratory Group, said himself that “this assessment is not a formal epidemiological
study.” Like the legislative task force study, this limits the depth and results.
--There is a phenomenon called the “Healthy Worker Effect” that should be considered when looking at this study. The majority of nuclear worker group
studies result in findings that report lower age-corrected cancer rates than average. The belief is that most of the scientists are selected and stay in this
work because they are in good health, and as a rule have good health care as an employee. The Japanese atomic bomb survivors also displayed the
“healthy worker effect,” and this is typically explained as a result that the more “health sensitive” people were less likely to survive the biological
effects of the bomb and had not survived. Many pro-nuclear groups point to this phenomenon as proof that radiation may actually be beneficial to
humans. Historically, the studies of the Hanford and Manhattan Project workers’ health was studied in the 1960s and these studies found that there
was no increase in cancers over expected incidence. Scientists have suggested that—especially in the Manhattan Project case—these individuals
were better educated and came from a higher socioeconomic status than the average blue collar worker in the United States and therefore knew
better how to protect themselves against excessive exposure, and were generally healthier as a consequence.
-- Similar to the legislative study, important information such as tobacco use, chemical exposure, and synergistic possibilities are never taken into
account. The way an epidemiological study would handle this would be to compare an exposed worker population to an unexposed worker
population doing similar work. Again, this was not an epidemiological study, and this was not done.
Ultimately, I used New York State incidence statistics for lung, thyroid and breast cancer statistics as well as a zip-code map from the Health Dept.
Here is an excerpt from that section:
A New York State Health Department map showing breast cancer incidence in New York state by zip code for the time period 1993–1997 highlights
Shirley in different shades of lavender and plum, showing the town’s breast cancer incidence as between 15 percent and 100 percent above the
expected rate. Shirley is also covered in diagonal lines on this map, as is the whole of Suffolk County, a marking that according to the key shows
“an area of elevated incidence not likely due to chance.” Lung cancer at the time was also 50–100 percent higher than expected, and thyroid
cancer was seen in women 20–29 percent above the state rate, and more than 30 percent the state rate in men.
I believe the fact that every study seems to show something different calls out for a profound renovation of the way we look at studies such as these
(and again goes to the heart of my reason for writing the book—no studies have been able to explain my experience in Shirley).