Uncertainty is the Bane of the Risk Assessment Process

Almost 20 years ago I had the privilege of presenting testimony before the President’s Commission on Risk Assessment.  I used that opportunity to describe and bemoan the relative nascent state-of-the-science and how uncertainties in both the toxicology and exposure assessment of risk assessment were really limiting the utility and ultimately the credibility of the process.   A measure of our progress might be seen in fact that the title of that talk and the title of this week’s blog are identical.   That talk from almost 20 years ago goes into the subject in a lot more detail.   If any of you reading this ask me for it I will send you the PowerPoint slides from that presentation (mjayjock@gmail.com).

This is not to say that no progress have been made; indeed, a lot has happened in twenty years on the exposure side of things.   Some really great tools have been developed by the volunteers within the American Industrial Hygiene Association which have been made generally available as books and freeware.    Go to:

 http://www.aiha.org/get-involved/VolunteerGroups/Pages/Exposure-Assessment-Strategies-Committee.aspx 

to get some of these models and go to the AIHA Press:  https://webportal.aiha.org/Purchase/SearchCatalog.aspx

to see the books on Exposure Assessment Strategies, Risk Assessment Principles and Mathematical Modeling.   Even with these tools a ton of work still needs to happen on the exposure side of risk to reduce the uncertainty; however, I must say that we have come a long way.

From my perspective, even more work needs to happen in toxicology.   Clearly, advanced techniques have been developed but from my perspective, available data that provides confident information on what is happening in human tissue at environmentally relevant concentrations of chemical exposure has not happened.   Most of the current occupational exposure limits (OELs) are based on the current toxicity base which uses the responses of animals at high doses in order to estimate relatively “safe” or allowable levels of exposure to humans at relatively low exposure.     See previous blogs for a more detailed discussion of this subject.

So what might be done with all this uncertainty?   Is the risk assessment process so laden with uncertainty as to be worthless?  I think not.  Indeed, at almost any level, a rational assessment of the health risk posed by chemical exposure is better than not doing it.   For me, the challenge is appropriately describing that uncertainty for the various stakeholders in the process.    Indeed, the suitable description of uncertainty would hopefully point the way to its reduction.   

Properly handed using the upper end of the uncertainty – for example, the 95^th upper bound percentile -as the measure of risk will reasonably bias the analysis toward overestimating and not underestimating the risk.   Thus, if one is able to shrink the range of uncertainty (with more data) the 95^th percentile upper bound will come down as well which means we are properly trading data for conservatism in the spirit of a precautionary approach.

For many years I used Monte Carlo uncertainty analysis for the assessment of risk which allows for everyone to see the specific uncertainty that exists and feeds the various parts of the assessment.   It gives the stakeholders a good view of where the uncertainties exist and how additional information might truly help the evaluation and the subsequent decisions.   This and a simpler form of uncertainty analysis will the subject of a future blog.

Given the level of uncertainty in our current set of OELs, my suggestion is that we quantitative describe the uncertainty within these values as part of the documentation of any OEL.    Doing so will typically reveal a relatively large range of uncertainty which some may find disconcerting; however, I believe that disclosing it is a critical part of the integrity of the process.   More about this critical issue of documenting OELs will happen in a future blog as well.   

WE ALLOW WORKERS TO BEAR MUCH MORE CHEMICAL RISK THAN THE GENERAL PUBLIC

Last week I discussed the fact that for most chemicals (i.e., those NOT identified as carcinogens) quantitative risk at any exposure including the exposure limit is NOT estimated as part of any documentation describing the toxicity of those chemicals. In the case of identified carcinogens, however, a quantitative level of risk IS estimated such that some finite risk is assigned for every exposure down to zero. The “allowable” exposure for members of the general public is often set at around 1 in 100,000 or 1 in 1,000,000 extra or additional risk of getting cancer during a lifetime of exposure at this level.   The “acceptable” level set for occupational exposures to carcinogens is typically set at exposure limits which render an estimated risk around 1 in 1,000 extra or additional risk of cancer.  The natural questions are:  Where did the one in 1,000 come from?  Why is there such a large difference between workers and the general public?  Shouldn't we be just as protective of workers as we are members of the general public?   The answers are interesting and the subject of this week’s blog.

The conventional wisdom is that the 1 in 1,000 number came out of the US Supreme Court decision on the carcinogenic risk assessment and statutory (OSHA) exposure limit for benzene.  Considering a 1 in a billion risk Justice Steven’s wrote that it “clearly could not be considered significant”.   One the other hand, he offered that a one in a thousand risk of dying from inhaling vapors containing benzene “might well” be considered significant (emphasis added).   

Hence the 1 in a 1,000 level of putative risk became the de facto standard for occupational carcinogens.   It turns out that the level of actuarial risk of death from occupational or on-the-job injury in the United States is somewhat higher.   See the table below which is perhaps 10 year old data from the US Bureau of Labor Statistics.  These are the actuarial working lifetime risk of death per thousand in various job classifications:

• All private industry                             --              2.1
• Manufacturing                                    --              1.6
• Mining                                                 --            10.8
• Construction                                       --               5.9
• Finance                                               --               0.6
• Commercial Fishing                            --             61

Readers who have watched "The Deadliest Catch" on TV will appreciate the last entry.

From my perspective, a putative risk at 1 in 1,000 for cancer using a linear dose response model described in my previous blogs fits in reasonably well with these actuarial risks. Other reason that folks have given to rationalize a higher risk for workers than the general public includes the fact that workers are normally healthier than individuals in the general populations which includes very old, very young and some critically and chronically ill individuals.   Another factor that is not typically stated but perhaps implied is that workers are deriving some financial benefit from their exposure and should thus bear some higher level risk.    Whatever the reason, the difference appears to be well inculcated as a societal norm at least in the US.  

The "gut check" for me is whether I would allow or advise my son or daughter to be occupationally exposed at any such an exposure limit - that is, an exposure that would present a putative risk of 1 in 1,000.    The answer to that question depends on the data and model used to make that determination.   Given a reasonable data set, model and a clear toxicological rationale by the experts, I would.   The problem is that these elements are often not present - which will be a topic included in next week's blog.

Next week's blog will be "Uncertainty is the Bane of the Risk Assessment Process".