Re: Risks of low level radiation - New Scientist Article

[Muckerheide <muckerheide@MEDIAONE.NET>]

 From: "Jim Nelson" <nelsonjima@HOTMAIL.COM>



> PLEASE REPLY OFF LIST>



Too embarrassing? :-)  You get the last word?  Or "plausible deniability"

when you use the same errors/disinformation next time? to the next audience

you can get to believe the LNT is valid? Not even NCRP and EPA say that!

They're now saying (misstating):  "We don't have low-dose data, so we have

to project from high doses, which is not sufficient, but the possibility

that the LNT is true isn't eliminated (even if for only some small

highly-rad-sensitive group)." Of course, if true radiologists would be mass

murderers.



And this isn't just Bernie, such strong correlations are evident in dozens

of other studies, esp. Bogen's correlation of women lung cancer deaths

1950-1954 by county and EPA's radon data by county from environmental

mesurements. Only 4% of women 60-80 yrs old had smoked; 11% 40-80 yrs old.



Results equivalent to Bernie's!



> From: BERNARD L COHEN <blc+@pitt.edu>



>> On Fri, 7 Dec 2001, Jim Nelson wrote:

>> 

>>> I diasagree totally with what you wrote below.



So? Your lack of knowledge of the subject?



>>> What you are saying below is that smoking is not an important factor for

>>> lung cancer.

>> 

>> --I said nothing of the kind. I said that if all counties studied

>> had very nearly the same smoking prevalence, the variations in the data

>> due to these very small differences in smoking would be very small.

>> 

>>> You really think "ethnic variations, medical services, reporting variations,

>>> chemicals in the environment and in the food,respiratory illness, etc, and

>>> just plain statistical variations" cause prclude a good correlation between

>>> smoking and lung cancer for the counties?

>> 

>> --No. They do not interfere with the correlation. But they still

>> cause variations in cancer rates which are larger than those caused by

>> smoking differences because the smoking differences are very small. Hence,

>> they lead to a very small R-squared

>> 

>>> The number of standard deviations are not important.



!? :-)  Don't know epi/statistics?  Just trying to regurgitate the Lubin,

Samet et al. mantra? But they wouldn't say this.



>> --They are a direct measure of how lung cancer rates depend on

>> smoking. What else is important?



>>> What is important is that the smoking rates for counties are

>>> actually predictive of the lung cancer rates for those counties.

>> 

>> --If the smoking prevalence for all counties is nearly the same,

>> other small factors that differ much more would dominate the variations in

>> lung cancer.

>> 

>>> I also note there is a huge unexplained inverse relationship between your

>>> radon measurments and the smoking rates for the counties.  While I would

>>> like to know the reason for this inverse relation, it is obvious that by not

>>> using good smoking exposure data, you are left wwith residual condfounding

>>> from smoking to explain your finding.

 

>> --The inverse correlation between smoking and radon is easily

>> explainable, but that is irrelevant. That inverse correlation reduces the

>> discrepancy between my data and LNT predictions. If there were no

>> correlation between radon and smoking, the discrepancy I found would be

>> still larger.





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