On Sun, 06 Feb 2005 06:30:52 GMT, wrote:

On Fri, 04 Feb 2005 20:23:28 -0700, Mark & Juanita
wrote:

On Fri, 4 Feb 2005 19:15:27 -0700, "David Hakala"
wrote:

Well, I'll go with the experts on this:


WOODD-DUST-EXPOSURE
NASAL-CANCER

WOOD DUST AND SINO-NASAL CANCER: POOLED REANALYSIS OF TWELVE CASE-CONTROL
STUDIES
Data from 12 case control studies conducted in seven countries were pooled
and reanalyzed in an effort to examine the relationship between wood dust
and sino/nasal cancer. There was a high risk of adenocarcinoma among male
employees in wood related occupations, with the greatest risk found for
those in jobs with the highest wood dust exposure and increased duration of
exposure. The risk of adenocarcinoma was also greater among women employed
in wood related jobs. An excess of squamous cell carcinoma appeared in women
in dust exposed jobs, which increased with the duration of exposure, but
only men employed for 30 or more years showed an increased risk of squamous
cell carcinoma. The authors conclude that the study provides strong support
to the link between wood dust exposure with various occupations and the risk
of sino/nasal adenocarcinoma, but the evidence with regard to squamous cell
carcinomas is ambiguous.

American Journal of Industrial Medicine, 28(2):151-166, 1995. (36
references)

http://infoventures.com/osh/abs/wood0002.html

Not very helpful. "high", "... also greater", "an excess of .."
"increased risk" are all very fuzzy assertions. What is the definition of
higher risk? Twice as likely? 4 times? These are important questions
since epidemiological studies generally consider anything less than 2 times
as great to be down in the noise and inconclusive -- especially when
dealing with cause and effect kind of numbers over the lifetimes of
individuals. Often there are many confounding factors.

Note, I'm not recommending that people ignore the hazards of wood dust --
just the annoyance should be enough to make one wear a dusk mask. However,
the "moon-suited" woodworker is probably going overboard.

.... snip
I'm sure all those questions are answered in the study itself. It
wouldn't get into a peer-reviewed journal without a lot of hard
numbers and methodology.

--RC

I'm sure numbers are in the study, but citing the study abstract as proof
does not help. There are cases where some researchers have treated small
correlations as "statistically significant" only to be refuted by other
researchers in the future. It would helpful to know what the numbers are
and what this set of researchers and peer reviewers consider to be
"significant".

Beyond that is the problem with many of these studies is that there are
just so many confounding factors that can obliterate true cause-effect
conclusions. Think about your own life, how many different things have you
done vis a vis life style, eating habits, and living conditions over the
past 30 years? Now, assume some researcher attempts to use your life as a
case study for some particular element of the life you are leading and an
element that may have been one of the constants over the past 30 years of
your life. Should something that happens be linked to that one event in
your life, or could it be a result of something else you did in the past?
The real question is whether various cause/effect conclusions are valid
based upon a single element pulled from a diverse set of lifestyles. The
conclusions based upon a sampling of people in, for example, a certain
industry is also only a starting point -- those people may have a certain
malady, but it may also be due to them having come from similar
backgrounds.

What many researchers will say is that these statistical studies are
useful in identifying areas of further research, not as conclusive on their
own. More detailed research would then identify root-cause mechanisms for
postulated problems or refute the findings by not finding any root-cause
mechanism that would support the statistical findings.





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The absence of accidents does not mean the presence of safety

Army General Richard Cody

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