RE: Risks of low level radiation - New Scientist Article

["Otto G. Raabe" <ograabe@UCDAVIS.EDU>]

At 09:22 PM 12/6/01 +0000, Jim Nelson wrote:

>As I told Dr. Cohen a few weeks ago, I agree with the papers by Smith et al. 

>that describe the limitations of Dr. Cohen's work.  The smoking data he uses 

>is so bad, it can only predict a little over 30% of the the lung cancers in 

>the counties. If there was no confounding, it should be able to predict 85% 

>or so.  I do not call that good control of confounding.

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December 6, 2001

Davis, CA



Dear Jim:



What do you mean "can only predict a little over 30% of the lung cancers"?

Do you mean that a regression R2=0.3? If so, that's only a description of

the fraction of the variability that is explained by the regression. The

important thing would be whether the trend is statistically significant,

not that there is considerable excess variability among the data. Such

variability is to be expected in such a study.



The key point that Prof. Cohen has shown so well is that the disagreement

between LNT and the observations is extremely robust. It is observed no

matter how you stratify the data. Just take Colorado as an example.

Residents of Colorado annually receive among the highest lung doses in the

U.S. from natural radon and its decay products in the air. Meanwhile,

Colorado enjoys one of the lowest lung cancer rates in the nation. In 1995

it was 49 the out of 51. Washington,DC, where radon concentrations are much

lower, had the highest lung cancer rate in 1995 (Am. Cancer Society, 1996).



Of course, it is always possible to say that some yet-to-be discovered

cross-level confounder could be causing the "apparent" disagreement with

LNT, but it does seem unlikely.



Otto



**********************************************

Prof. Otto G. Raabe, Ph.D., CHP

Center for Health & the Environment

(Street Address: Bldg. 3792, Old Davis Road) 

University of California, Davis, CA 95616

E-Mail: ograabe@ucdavis.edu

Phone: (530) 752-7754   FAX: (530) 758-6140

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