Re: Testimony of Steve Wing to US House of Representatives

["ruth_weiner" <ruth_weiner@email.msn.com>]

I believe Bruce is quite right.  The dose-to-risk conversion factor is, for
example, LCF/rem.  Has someone pointed this out to Wing?  To the House
Subcommittee?

Ruth Weiner
ruth_weiner@msn.com
-----Original Message-----
From: Heinmiller, Bruce <heinmillerb@aecl.ca>
To: Multiple recipients of list <radsafe@romulus.ehs.uiuc.edu>
Date: Friday, July 28, 2000 7:06 AM
Subject: RE: Testimony of Steve Wing to US House of Representatives


>Am I misreading the passages below?  Wing appears to be arguing that doses
>were underestimated and that this underestimates risk.  But any radiation
>risk coefficients that I've ever seen have dose on the denominator, and
that
>underestimating dose would thereby overestimate risk per unit dose.  Can
>someone help me out here?
>
>Bruce Heinmiller CHP
>heinmillerb@aecl.ca
>
>
>
>> Statement to the Subcommittee on Energy and Environment of the Committee
>> on
>>  Science, United States House of Representatives, July 18, 2000
>>
>>  Steve Wing, Associate Professor, Department of Epidemiology, School of
>> Public
>>  Health, University of North Carolina
>>
>>  Mr. Chairman and Members of the Committee, thank you for inviting me to
>> testify
>>  about health effects of low level radiation.  I am an epidemiologist on
>> the
>>  faculty at the University of North Carolina where I have studied
>> radiation
>>  health effects among workers at Oak Ridge, Los Alamos, Hanford and
>> Savannah
>>  River under funding from the Departments of Energy and Health and Human
>>  Services.  Epidemiology, the study of disease in human populations, is
>>  especially important in risk estimation and standard setting because
>> animal
>> and
>>  laboratory studies necessitate extrapolation from high to low doses,
from
>>
>>  molecules and cells to organisms, and from other species to humans
(1-3).
>>
>>
>>
><snip>
>>
>>  Detection of radiation risks depends upon the ability of an
>> epidemiological
>>  study to classify persons according to their exposure levels.  A-bomb
>> survivors
>>  were not wearing radiation badges, therefore their exposures had to be
>> estimated
>>  by asking survivors about their locations and shielding at the time of
>>  detonation.  In addition to the typical types of recall bias that occur
>> in
>>  surveys, stigmatization of survivors made some reluctant to admit their
>>  proximity (9).  Acute radiation injuries such as hair loss and burns
>> among
>>  survivors who reported they were at great distances from the blasts (10,
>> 11)
>>  suggests the magnitude of these errors, which would lead to under
>> estimation of
>>  radiation risks.
>>
>>  Another bias occurs because of the higher exposures of distant survivors
>> to
>>  residual radiation.  Fallout affected distant survivors in both cities
>> (8,
>> 12).
>>  In addition, survivors who were shielded or exposed at greater distances
>> were
>>  strong enough to enter the areas near the hypocenters of the blasts
>> within
>> hours
>>  of detonation, exposing themselves to residual radiation created by the
>> atomic
>>  weapons (8, 12-14).  Residual radiation exposures of lower dose
survivors
>>
>> leads
>>  to an underestimate of radiation risks.
>>
>>
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