Re: Ecological studies and population shifts

[Bernard L Cohen <blc+@pitt.edu>]

	Can you propose a specific model on which I can do calculations?
For example, how do I model the movement of x% of populations (I can vary
x with little trouble). I can easily rank counties by radon exposure, and
say y% move to counties whose distribution in rank is characterized by
any standard type distribution you choose and z% move to counties with
some different distribution, etc. For the $2500 award (if this explains my
data plausibly), someone should suggest details and ranges of plausible
parameters for the above calculation.The assumption made in my paper is
that people move to areas of U.S. average radon exposure (but if they move
to FL, CA, or AZ, they are excluded).
	Note that my studies have shown that, on average, people spend 70%
of their lives within 25 miles of where they reside at death.
Bernard L. Cohen
Physics Dept.
University of Pittsburgh
Pittsburgh, PA 15260
Tel: (412)624-9245
Fax: (412)624-9163
e-mail: blc+@pitt.edu


On Tue, 28 Jan 1997, David Scherer wrote:

> Wade Patterson wrote, in part:
> Dr. Kaurin and others:
> I'd like an explanation of why the Japanese survivor data is not an
> "ecological" study. No Japanese wore a dosimeter. Doses are assigned solely
> on the basis of "entire" radial increments. How are radial increments
> different than counties? By the way, the errors in doses so assigned are
> 30%-50% due to potential inverse quare law differences. 
> <end quote>
> 
> With the A-bomb survivors, we are at least sure that all the subjects were
> in fact exposed to some radiation, approximated by their distance from
> ground zero.  In the radon study there is no individual verification that
> the subjects were actually exposed to the radon levels suggested by the
> county in which they died.
> 
> It could be that people from high-Rn counties moved to low-Rn counties
> after their cancers had been initiated but before they were diagnosed.  It
> is also possible that people spent most of their life in low-Rn counties
> and moved to high-Rn counties later in life, thus avoiding the Rn exposures
> assumed by using the county average.  I know of no way to numerically model
> this effect.  Perhaps one could look at bulk changes in population or age
> distributions over time, but they are only suggestive.
> 
> Perhaps because of the large database involved in Dr. Cohen's study this
> effect is not significant.  For example, one could presume thia happened
> with some fraction of the population (N percent) and see if this changes
> the inverse dose-reponse relationship.  If you need a 25 percent population
> shift to overcome the result, it seems pretty unlikely that this is
> important.  On the otherhand, if a 2 percent population shift is sufficient
> to alter the result, then ....
> 
> Regards,
> Dave Scherer
> scherer@uiuc.edu
>