|
Ruth,
You are correct that we cannot make conclusions by
simply looking at the map. There are too many variables. We can use it, however,
to test our models. If you have an equation:
a = b + c + d + e, you obviously don't know what b
is if you are only given a. However, if a is your observable and you know what
b, c, d, e are, you can test to see if your equation was correct.
We have certain theories of what causes cancer, how
long the latency is and we know the demographic data and general migration
patterns of the population. If we put all of that together, we should be able to
reproduce the map. Otherwise, our theories or demographic data are wrong. The
map has clear distinguishable features and doesn't seem to be just statistical
noise.
WARNING! PHILOSOPHICAL RAMBLING
FOLLOWS:
Recently, I have simply been amazed at our
unwillingness to test our theories. This seems to be true for society in general
and not just in our profession. After September 11, 2001, politicians debated
(along party lines and using outdated and irrelevant political philosophy) if
airport screeners should work for the feds or for private contractors. Neither
side came up with the suggestion of hiring an independent agency to test the
system and continually report back to the people.
Marx, Locke and Hobbs are not relevant to these
situations. We have modern management tools available (such as ISO 9000), which
are applicable. These all rely heavily on continual testing and
evaluation.
Kai
It was a little hard to read, but you are right. However: 1. A map of cancer mortality by itself is meaningless. With latency periods of ten years or more, where a person dies of cancer may be totally unrelated to where he or she was exposed to a carcinogen (my personal experience is that basal cell skin cancers -- almost never fatal -- emerge about 15 years after the exposure to intense sunlight for long periods of time). 2. What is the ratio of cancer deaths to total deaths? How are total deaths distributed? 3. nothing about the map indicates "excess" vs/. "expected" cancer deaths. Ruth Weiner, Ph. D. ruthweiner@aol.com |