In the last blog I
discussed the inherent uncertainty around measured or model estimated exposure. This week it is time to talk about the
uncertainty in any exposure limit.
We have all seen changes in
the exposure limits we have used over time.
The changes are almost invariably downward toward lower limits. Does this mean that the chemical became more
toxic? Of course not, it just means
that the uncertainty inherent in that particular exposure limit was not very
well handled. To guard against these surprises, I believe that uncertainty should be explicitly addressed during the
documentation process.
The current definition of
the risk present at the exposure limits that most of us use is that exposures
controlled to these limits will protect “nearly all”. Although the intent is clearly to protect
the vast majority of folks exposed at the limit, there is currently no attempt
to quantify what is meant by “nearly all”.
For a long time I have thought that the level of risk present at any
exposure limit worthy of documentation should be quantified to the extent
possible and, more important, the uncertainty around that estimated quantitative
level of risk should also be provided.
In truth, the risk of an
adverse health effect occurring is a distribution of values which is low at low exposure levels and high at high exposures. The exposure limit is but one value on that
distribution. We (Jerry Lynch, Phil
Lewis and I) wrote a paper in 2001 about how one could estimate the risk at any
exposure limit and how the uncertainty might be estimated. I would be happy to send a copy of that paper
to anyone who asked me at mjayjock@gmail.com. A more definitive scientific treatment of this subject was put forth in 2009 by in the
National Academy of Sciences – Science and Decisions: Advancing Risk
Assessment, also known as the “Silver Book”. The hard copy of the book will set you back
about $55 but the NAS offers it for FREE as a PDF Download!
The meat of this subject is in Chapter 5.
So in the final analysis,
risk is a combination of uncertain (a distribution of) exposure and (a
distribution of) hazard (or toxicological response). Combining both distributions presents an
output distribution of risk at any particular nominal or median exposure. If the following conditions are met then the
risk will be shown to be relatively low or “safe”:
·
An exposure limit that
is relatively high versus the median estimated exposure.
·
The distributions for exposure
and exposure limit are relatively narrow such that they do not have a
lot of overlap.
Please
note there will still be some finite level of predicted risk – it will never be
zero.
When
the exposure goes up relative to the exposure limit and/or the
distributions for exposure or exposure limit are relatively wide
then the predicted potential risk goes up as well.
I believe that this is
how we might start to get our arms around “How safe is safe?”
Describing uncertainty in this or a similar manner will keep us from being surprised like we have been in the past. It is also important to understand that much (perhaps most) of the uncertainty in the estimated hazard (exposure limit) is a result of our lack of knowledge around the actual mechanisms of toxicology. Some modeled exposure estimates are also fraught with this uncertainty born of a lack of knowledge. Thus, this type of analysis will also show us where we need to sharpen up our tools to narrow either the exposure limit or exposure distributions and allow much more confident estimates of risk for our clients.
Describing uncertainty in this or a similar manner will keep us from being surprised like we have been in the past. It is also important to understand that much (perhaps most) of the uncertainty in the estimated hazard (exposure limit) is a result of our lack of knowledge around the actual mechanisms of toxicology. Some modeled exposure estimates are also fraught with this uncertainty born of a lack of knowledge. Thus, this type of analysis will also show us where we need to sharpen up our tools to narrow either the exposure limit or exposure distributions and allow much more confident estimates of risk for our clients.
If one is interested in estimating the exposure limit - it is suggested to consult the ProUCL 5.0 Tech Guide for a detailed discussion of statistics which can be used to estimate EPC based upon for full uncensored as well as data sets with nondetects. Methods in ProUCL 5.0 adjust for skewness to compute the exposure limits.
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