Acceptable Risk: The Discussion Continues

After the blog on “Acceptable Risk” I received an email and phone call from Harry Ettinger who, in addition to being a friend and colleague, is a Past President of the American Industrial Hygiene Association.  Harry has been around a long time and has a wealth of knowledge, wisdom and perspective.  Harry suggests that “Acceptable Risk” is an important subject that deserves additional attention.  He encouraged a panel discussion at a future AIHCE to air out the issues around this topic and the companion subjects:  “how safe is safe enough and how clean is clean enough”.    

If any readers of this blog are interested in participating on such a panel, please let me know (mjayjock@gmail.com) and I will put you on the list of potential participants.

Harry goes on to make the following points:

•        There is probably no definitive answer that will satisfy everyone (or perhaps anyone)
•         It depends on which side of the fence you are sitting on.
•         It needs

o    a balance so that the greatest good (whatever that means)       

o   to be is provided

§   to the greatest number of people who are most important (however that is measured)  

§  by ethical/unbiased/knowledgeable  decision makers (if these decision makers can be found or even exist)

§   in a long term time frame (rather than short term) 

Harry points out that, unfortunately, we typically define acceptable risk, to a large extent, on the basis of:

§  who has the most political clout

§  shouts the loudest

§  short term considerations

§  media influence

§  risk that has typically already been accepted

Harry advises that consideration should be added to any discussion of “acceptable risk” relative to the subjective perception and psychology regarding the source of the risk. 

He reminds us that we kill 38,000 people a year (approximately 100 deaths a day) in car incidents, and do not think very long about this death rate. We know that reducing the speed limit will reduce the death rate but when this restriction was introduced, many people objected.  Indeed,  New Mexico currently has a 75 mph speed limit on its Interstate.   If a rail car carrying chemicals such as Chlorine/Ammonia/shale oil/etc. derails, the subject is off the front page of the newspaper in 2-3 days (even if there are fatalities). If that same rail car was carrying protective clothing with minimal radioactive contamination (that is not readily released) the uproar would continue indefinitely.

Harry suggests that another topic to add to the discussion is that acceptable risk changes over time. What was unacceptable today was acceptable 10-20 years ago, and may or may not be acceptable in the future.  He believes that the definition of acceptable risk varies as a function of time and where it happens, and other relative risks extant at the time. This suggests that the 1/1000 definition in the benzene decision (which we still quote and use) probably needs to be updated.

I appreciate Harry providing his considerable insight on this subject and encourage you all to weigh in on this important topic.   As I get older I am beginning to appreciate more and more why some tribal folks highly value their elders. 

Dermal Exposure from the Air

We can get a significant dermal exposure to a toxicant from having exposed skin in contact with that toxicant in ambient air.   I am not talking about splashing or the settling of mist onto the skin, the mode of exposure discussed in this blog is pure vapor in air-to-skin-to-systemic absorption.  This manner of exposure can become very important when the respiratory route is reasonably well guarded via the use of a respirator.

The classic example of this type of exposure is phenol which has a relatively low exposure limit indicating that it is quite toxic via inhalation.   It is also quite irritating to the respiratory tract and thus may provide some good warning indications of exposure via that route.  Thus, folks who have to work in environments at greater than the OEL (ACGIH TLV and OSHA PEL = 5 ppm as an 8 hour time weighted average) would almost certainly be using respirators.

Phenol also readily penetrates the skin and, again, I believe dermal exposure to liquid phenol placed or splashed onto the skin surface would be very irritating or even corrosive. 

A more subtitle route of exposure is as vapor molecules going from the air above the skin, into the skin and then through the stratum corneum and dermis to be systemically absorbed.  This presents a real problem to the Industrial Hygienist trying to evaluate or estimate this exposure potential.  

One method would be to put absorbent patches on the skin to be subsequently desorbed and analyzed.   These could provide a measure of the weight per square centimeter to which the skin was exposed.   Multiply this weight by the total amount of exposed skin for at least some measure of what the exposure might be.

Other than involving a lot of logistics and laboratory development, the above method has the problem of being done AFTER the fact of exposure.   What we need is a method that is prospective; this is, before and predictive of the exposure.   

I have discussed Dr. Wil ten Berge’s work before here.  He developed SKINPERM which has been around for a long time and, working with Daniel Drolet, Rosalie Tibaldi  and Tom Armstrong, has produced the more recent, more user-friendly IHSkinperm model.  The basic modeling engine that Wil developed is the only one I know of that will take the airborne concentration of a chemical (along with other physical-chemical properties) and estimate the dermal exposure potential of that chemical to exposed skin.   

You can find SKINPERM on Wil’s website: http://home.wxs.nl/~wtberge/qsarperm.html   In addition to the model, Wil has a wealth of educational material on dermal exposure on this web site that has been around serving the risk assessment community for some time.   Put “IHSkinperm” into Google and the first two hits are the manual and the spreadsheet.

Unless someone is wearing well-fitted vapor barrier clothing, you might want to give some consideration to the possibility that even skin ostensibly covered with cloth clothing is at least somewhat “exposed” to vapors.   Considering the person naked (about 2 m² of skin) would represent a worst case or bounding condition for these estimates.

It is the Holiday Season and I would like to take this opportunity to wish everyone reading this, along with their loved-ones, according to their preference, a Merry Christmas, Happy Hanukah, or whatever holiday you observe including the Return of the Sun during this special time of year. 

What is ACCEPTABLE Risk?

In this week’s blog I go out on a limb, the topic is ACCEPTABLE RISK.

More than a few years ago, a then newly minted PhD, friend and colleague; Jack Hamilton asked my opinion about rules one might use to set a level of exposure and risk as ACCEPTABLE.   Being older and a lot grayer than Jack, I got to render my opinions.  I decided to share these opinions with you in this week’s blog to hopefully stimulate some discussion.  I do not pretend to have all, or maybe any, of the answers but I am willing shared my opinions to shine a light into this somewhat dark area in the hopes of bringing out additional discourse from you, my intelligent readers.

Finding and declaring ACCEPTABLE Risk Levels are almost never easy.   If it were easy we would have a life that was more dull and more people could do our jobs.  The question of risk acceptability is political and social.  Acceptable to who?  When?  The answer(s) always has (have) been a mix of politically recognized and derived subjective VALUES.

I have heard some folks on the extreme political left declare that Risk Assessment is a “Tool of the Capitalist Devil”.   I believe that to the extent that anyone independently determines what is "acceptable"for OTHER stakeholders this harshly worded judgment may have a ring of truth.  

Perhaps my most important mentor as I was learning and developing in this field was Dr. Irv Rosenthal.  Irv was a wonderfully intelligent and wise person and a gifted teacher.  Irv reminded me that we often ask permission to pass someone in a narrow hallway.  We say “excuse me” or “peg your pardon”.  Why then, Irv asked, would we not seek their permission to render them at risk (however small) from exposure to compounds we introduce into their environment?  Why can't they participate in drawing the line relative to their own exposures and the putative consequences?

The situation with Human Health is such that we look for consensus among industrial colleagues, academics, regulators and judges as to what are historically "acceptable" levels of risk.  We get benchmarks like 1 in 1000 lifetime risk for carcinogens exposure to workers and 1 in 1,000,000 for non-workers.  This has been evolving somewhat in the courts (e.g., US Supreme Court Benzene decision) but I do not think it has ever been put directly to the ultimate stakeholders, those being exposed.  These folks personally deal with exposure and risk and my sense is that, properly educated and, much more important, properly empowered, I think they would come up with doable and workable limits.  

I mentioned this possibility at an American  Industrial Hygiene National Conference in a Forum on Risk Assessment in the 1990s and the reaction was somewhat predictable.  Very few expressed a willingness to open the process up to these type of potential complications and "problems."  I admit that it will not be easy - I just think it will be ultimately necessary to make the process more politically viable, legitimate and inherently ethical.

So to answer Jack’s question succinctly, I advised him to use his skill to determine the quantitative level of exposure and risk as best he could.  I suggest that, if pressed, he leave the issue of “acceptability” to the first viable choice from the following rough hierarchy.

    1. A "Gold Standard" or criteria you were given by the client or that the client agreed to.   Note:  This is also known as “Rendering unto Caesar those things belonging to Caesar”.

    2. A criteria that is acceptable to some standard-setting or regulatory authority AND seems to make sense to you.

    3. An unwritten but generally accepted "rule of thumb" or common practice that you can refer to and makes sense to you. 

    4. Your "gut feel" on what it should be. 

In every case above, it would be beneficial to identify which line of the above hierarchy was used and the reasoning for using it within the report.   Doing so is particularly important for #4.  Indeed, my advice to Jack was to avoid using #4 unless you are asked specifically to do so by the client OR you have an overwhelming personal need to make your opinion known.   We should always to keep in mind that the determination or declaration of ACCEPTABLE risk is a somewhat subjective risk management function and it is not strictly speaking risk assessment.

Finally, I believe that there should be a new line at the top of this hierarchy that does not exist yet:

Acceptable risk defined in quantitative terms by consensual agreement among all the principal stakeholders.   My sense is that this is a worthy goal.

Chemical exposure risk assessment – what might we be missing?

Over the last few weeks this blog has featured a discussion of dermal exposure and how we might accomplish it.  That series was enhanced and prolonged from an email I received last month from Chris Packham. Chris sent me a copy of a talk he was going to give at a Regional BOHS Meeting in the UK on November 18, 2014.

I thought there was a lot of good information and perspective in that piece and Chris granted permission to put it here after his talk.   We may not agree specifically on the approach but I think everyone will agree that dermal exposure is a very important route in many exposure scenarios and has been somewhat ignored.

Chemical exposure risk assessment – 

what might we be missing?

Chris Packham

It is well established that inhalation of toxic chemicals can result in systemic effects, i.e. damage to internal organs and systems. A great deal of research and development has been undertaken resulting in strategies and equipment to monitor inhalation exposure. As a result in many countries there are exposure limits for a wide range of chemicals. Far less attention has been paid to the potential for chemicals to penetrate the skin and either cause or contribute to systemic toxic effects. Yet there is considerable evidence showing the potential for skin exposure to do this, including with chemicals that are unlikely ever to be inhaled because of their physical properties.(1) There is also a view that inhalation exposure results in more serious damage to health than can occur from skin exposure, often regarded as “just a rash”. Yet the EU Classification, Labelling and Packaging Regulation (EU1272/2008) contains the Hazard Statement 'H310 – Fatal in contact with skin'. 

In this article the authors will review the evidence showing why, in considering risks of damage to health due to the use of chemicals, the potential for skin exposure to cause systemic damage must be an integral part of any chemical exposure risk assessment. Firstly we need to recognise that the skin is not an impermeable barrier. The outermost layer, the stratum corneum, which forms 90% of the barrier, is, over most of our body, only as thick as the cling film that we use to wrap sandwiches. The way in which our skin interacts with the (working) environment is extremely complex and by no means scientifically fully understood. It is certainly beyond the scope of this article to attempt an in-depth explanation. (emphasis added)

Indeed, the complexity is such that the European Agency for Safety and Health at Work has stated: “However, there is no scientific method of measuring the results of the body’s exposure to risk through dermal contact. Consequently no dermal exposure standards have been set.” - from “Occupational skin diseases and dermal exposure in the European Union (EU-25):policy and practice overview - European Agency for Safety and Health at Work 

So where does this leave the health and safety practitioner attempting to establish the risks to the health of the workforce due to the presence of chemicals in their workplace? In the U.K. those chemicals that have been assigned a limit for airborne presence (Workplace Exposure Limit or WEL) and that are known to be able to penetrate the skin will be listed in the official hazard classification documentation(2) with an sk notation. However, this is far from a comprehensive list. Not only are there many chemicals that do not appear in this list that are able to penetrate the skin on their own and could then cause systemic damage. There are others that have systemic toxic properties but due to their form are on their own unlikely to be able to penetrate the skin. However, should these be mixed with a skin penetrant the potential for them then to able to cause systemic damage can be considerable. So establishing and assessing the hazard of a chemical in the workplace may not be as simple as many might assume. 

So what is the evidence that this is something that needs to be considered as significant when chemicals are being used in a workplace? The following statements and case studies should serve to illustrate why. 

1. Systemic uptake of 5-Hydroxy-N-methylpyrolidone

In this study(3) a comparison was made between the concentration of this chemical in urine arising from inhalation at 10mg/m3 over an 8 hour period with just 15 minutes exposure of one hand to a 15% solution in water. Despite the fact that skin exposure stopped after just 15 minutes, the concentration in urine continued to increase for several hours and matched that of the full 8 hour
respiratory exposure. The implications of this when conducting risk assessment are important as the assumption that the skin exposure is only for a very short period and therefore not of significance may not be correct. 

2. Systemic uptake of methylene diamine 

In a factory using this chemical in the manufacture of helicopter rotor blades this study (4) identified 14.7 μg/l of this chemical in urine under the actual working conditions initially observed. These did not include any effective control measures. By eliminating respiratory exposure the concentration was reduced to 12.1 μg/l. By allowing respiratory exposure but eliminating skin exposure the concentration was reduced to 2.6 μg/l. The conclusion that has to be drawn is that the major route of uptake was via the skin. 

3. Systemic effects in the rubber industry 

In his doctoral thesis (5) on genotoxic effects of dermal exposure in the rubber industry, Vermeulen comments: “Little attention has been paid to dermal exposure in this particular industry. Falck et al and Kilpikari already suggested in the early eighties that dermal absorption of chemical compounds could play an important part in the rubber industry. Direct evidence for this hypothesis was found in a study by Bros et al in an aircraft tire retreading company where a direct relation was found between dermal exposure to cyclohexane soluble matter and urinary mutagenicity while no relation was found between urinary mutagenicity and rubber particulates and fumes in air.” 

What should be clear from the above is that if we do not include the potential for skin uptake and the consequences we may well be missing a significant risk of serious damage to health. We need also to include the potential for ingestion as a route of uptake. 

The fact is that for systemic damage what is important is the total dose reaching the target organ, irrespective of the route of uptake. So what we need to identify is the combined uptake of all three routes: inhalation, dermal and ingestion. One of the immediate consequences of this is that with many chemicals the concept that ensuring airborne exposure is below the prescribed regulatory level represents adequate control may not be valid in terms of the true risk of damage to health. It may be necessary for regulatory compliance, but should the combination of the uptake of the three routes be sufficient to cause systemic damage, worker health can be severely, possibly permanently and potentially fatally, compromised. A consequence of this is that considering each of the three routes in isolation is no longer an acceptable approach. 

The problem now arises as to how we can develop a comprehensive risk assessment approach, combining the data on all three routes. Unfortunately very little seems to exist in terms of scientific studies or guidance on this. At the present time our only reliable technique appears to be that of biological monitoring of workers to establish their level of exposure, such as was carried out in the case study of exposure to methylene diamine described earlier in this article. Obviously it would be impracticable to do this for every chemical exposure risk assessment, but perhaps where there is evidence that the chemical which forms the subject of the risk assessment has properties that can cause systemic damage and that, under the particular circumstances prevailing in the work environment, there is potential for more than one form of exposure, biological monitoring should at least be considered. 

Ideally a database of results would be set up by a suitable organisation to build an evidence based overview of the true significance of this issue so that effective guidelines can be produced and perhaps new techniques developed. Until then the risk remains that we will continue to expose workers to situations that are putting their health in jeopardy.

References
(1) OSHA Technical Manual, Section II, Chapter 2 
(2) EH40/2005 Workplace exposure limits 
(3) Akrill et al (2002). Toxicol. Lett. 265 – 269 
(4) Weiss T, Schuster H, et al.; Dermal uptake and excretion of 4,4’-Methylenedianiline during rotor blade production in helicopter industry – an intervention study; Ann.Occup.Hyg, 2011, 55, 8, 886-892 
(5) Vermeulen R, genotoxic exposure and biological effects in the rubber manufacturing industry – relevance of the dermal route – doctoral thesis (2001)

In Defense of Dermal Exposure Modeling

A couple of weeks ago this blog had an Argument Against Dermal Exposure Modeling from Chris Packham which I thought made some good points.   However, being an advocate of modeling myself, I thought I would open the discussion to others for their input and publish some of the counter arguments. 

Before I get to this, one of my colleagues asked for specific clarification.  She was not sure from the discussion exactly what the purpose of estimating dermal exposure might be in our discourse.  My sense is that we are looking for quantitative estimates of systemic and local tissue exposure and dose estimation to use in comparison with dose-response information to determine or estimate the potential risk to human health from dermal exposure.  This determination of risk would be used like any other risk assessment to make decisions about potential risk management.

I had a few folks write to me defending the “no need to quantitatively model dermal exposure” approach but I also found two good examples of a cogent defense of dermal exposure modeling.    The first comes from Paul Schlosser (an Environmental Health Scientist  at the US EPA).   Paul has been working on a chemical where a significant amount of vapor uptake is via the skin. An abstract is available online :

http://link.springer.com/article/10.1007/s00204-007-0230-5#page-1 

As such, he had some very recent experience with these models.  The second set of comments comes from friend and colleague Wil tenBerge from the Netherlands who has been a thought leader in this area for many years.   Their comments are presented below:

“Something I'd said in my previous posts is that doing the experiments to quantify skin absorption will certainly be costly and time-consuming, and folding that into a PBPK model will take even more time, though simpler modeling approaches should also be useful. I would agree that if it constituted 10% or less of total absorption, that it's not important, not worth counting. But for NMP the absorption of *vapor* through the skin was measured as 40% of what's absorbed when inhalation also occurs, not insignificant, and any liquid contact increases that considerably. The fact that it's difficult doesn't mean it's not worth doing.

The EASH [European Agency for Safety and Health] statement is a bit odd. We generally don't do dose-response experiments on humans, going high enough to cause toxicity, so we typically don't have *measurements* of risk from dermal contact in humans. But the same is true for inhalation or oral ingestion of many chemicals. We *do* have scientific means of *estimating* risk in humans for all these routes of exposure, though. For systemic effects it doesn't matter how it gets into the circulation, just the concentration (peak, AUC, or perhaps other), and with the appropriate PK data we can estimate that about as well for dermal as for other routes. So the statement is simply incorrect.

Figuring or estimating the surface area of skin exposed, especially to incidental liquid contact, may be a bit subjective. But the alternative, which is to ignore the risk, seems a lot worse than a bit of subjectivity.

-Paul Schlosser “

“Dear Mike, Your blogs are always very interesting. I would like to give my opinion on the statement that modelling dermal exposure and dermal absorption is not very productive. Modelling dermal exposure and absorption is certainly not straight forward. One of the problems is to define the type of exposure. There is a need to define type and conditions of dermal exposure to: - gas, vapour - spilling liquid or solids - aerosol of liquid via air - aerosol of solid via air and further: - exposure to bare skin - exposure to skin protected by clothes and further: - exposure to pure substance - exposure to a mixture - exposure to aqueous solution and finally the fraction absorbed - which amount in mg/cm2 is deposited on the skin? - which part adheres to the skin and for what time? - which part evaporates? - which part is permeating the skin (minutes to weeks)? - which parts resides in the stratum corneum? - which part is removed by desquamation (weeks) from the stratum corneum? The IH-SkinPerm is able to quantify: - dermal absorption by whole body exposure to vapour. - dermal absorption by spill of liquid or of solid on the bare skin during a limited period of time. - dermal absorption of aerosol of liquid or of solid, deposited on the bare skin during a limited period of the working day. The deposited amount per day on the skin in relation to the type of work can be read off from so-called guidance documents for risk assessment, based on experimental observations. The real absorption of the dermal deposited dose is assessed by IH-SkinPerm. The accuracy of dermal absorption estimates by IH-SkinPerm for the few dermal exposure scenarios has been assessed by experimental exposures in volunteers. The simulated and experimentally measured absorption fractions were in fair agreement. IH-SkinPerm covers only a few but not all possible types of dermal exposure. The developed theoretical background for IH-SkinPerm is still able to simulate exposure for other exposure conditions and also for mixtures. I would highly appreciate receiving the note of Chris Packham. Best regards, Wil 

-Wil tenBerge

___________________________________

This subject remains open to anyone who wants to respond to this blog or send me an email at mjayjock@gmail.com; however, I remain strong in my opinion of the positive value of Dermal Exposure Modeling for risk assessment in the context I outlined above.

We do NOT spend enough on Risk Assessment

  

I think I mentioned in previous blogs that my friend and colleague, Gurumurthy Ramachandran or “Ram” is a brilliant teacher and researcher.   A few years ago he and J.Y. Choi conducted a survey of technical experts on the occupational oversight framework in this country.  They used nanotechnology as the example.

The mathematical techniques they used were quite sophisticated in their analysis of the survey.   That is not my primary area of expertise but it appears to be very well done.  Indeed, as he always does, it is a very careful piece of research and its conclusions are properly couched in terms of the uncertainty and limitations of the study. Notwithstanding these caveats, I was struck by the following excerpts from the paper:

Despite the large investments in nanotechnology, corresponding investments in studying the health and safety aspects of this technology and its products have been minimal.

The most striking finding is that experts in our sample tend to believe that the current oversight system for chemicals in the workplace is not adequate and effective. About 17 (or 70 percent) of the 25 criteria were scored below 50 out of 100. The mean score of the 25 criteria across all experts is 42.4 and median is 41.3 out of 100.

This reference is:

Choi, J.Y, Ramachandran, G. Review of the OSHA Framework for Oversight of Occupational Environments. Journal of Law, Environment, and Ethics, 37(4):633-650, 2009.

If Ram gives me the OK I will send this to anyone who asks me for it: mjayjock@gmail.com.

Indeed, this has been my general experience during a long career doing product safety risk assessment for the chemical industry.   About 12 years ago I did a calculation of the amount of money being spent by the chemical industry on health and safety research of chemicals by the chemical industry.   This included the 15-20 million USD being spent every year at that time by the Industry sponsored Chemical Industry Institute of Toxicology (CIIT). Compared to the industry’s profits it came out to be in the parts per million range.   This is not to say that other money was not being spent on health and safety research by individual companies but, like the CIIT efforts, they were primarily reactive in nature in that they were responding to obvious problems that were either easily anticipated or brought to them.  

Chemcials that were clearly toxic, like pesticides or proven carcinogens or endocrine disruptors (all most often initially discovered in academia) received the focus of attention.

For many years almost all of the risk assessments I did for my company were focused on these types of products (e.g., recognized sensitizers, carcinogens, etc).   During my tenure, the vast majority of products produced by most companies never really received any proactive attention relative to the risk of their use in commerce. I believe it is the same today.

It would seem that the Europeans have been trying to reverse that trend with the REACh regulations.  There are also noises being made in this country to reauthorize TSCA to be more REACh-like and do proactive assessment of chemical risk as well.

My read of all this here or in Europe is that unless or until proper resources are allocated to do this research, we will continue to flounder in a sea of uncertainty in which we really do not understand the risk of the chemicals we use.   This is not to say that all or even many of the chemicals we are exposed to are harmful at the exposure we encounter them.   I am quite sure, however, that there are unacceptable risks from the chemicals we use out their today that we have not discovered and we will not find them without these resources.  

That is my read but I would very much like to hear other opinions.   After all, this is a discussion group.   The discussion will appear at the bottom of this blog or in the LinkedIn Group in which it is posted.  However, if you write a good and compelled argument or treatise relevant to this issue, I will publish it, along with my comments, here in a future blog.

Relative to last week’s blog (Argument AGAINST Dermal Exposure Modeling), I got very few folks defending the use of dermal modeling.  I was somewhat surprised in that I made sure that the people I know that are or were doing dermal modeling got the blog.  Perhaps it is because everyone is so busy with the holidays and work.   I will leave the question open for a few more weeks in case folks wanted to comment but just did not have the time. 

An Argument AGAINST Modeling Dermal Exposure

After last week’s last blog:  Lost Keys Under Street Lamp Part II – Dermal Exposure,   I received an email from Chris Packham.   An excerpt from Chris’ email is reproduced below:

“Mike

In response to your latest blog, perhaps the attached document may be of interest. I think it explains some of the complexities and why my approach to skin exposure risk assessment is that, with the exception of perhaps specific research projects, attempting to measure or model the significance of skin exposure will be time consuming and not for most of us a productive use of our time. I know that hygienists tend to feel that unless one can measure then they are not perhaps achieving a reliable result. However, as I keep saying, we should keep in mind Einstein’s saying: “Not everything that can be measured counts, and not everything that counts can be measured”.”

 

He attached a PDF file to this email:  

About skin measurement.pdf  in which he outlines, in some detail, the complications associated with the measurement of dermal exposure, let alone any modeling of the exposure potential.  Chris has granted me permission to send anyone who requests it the full text of this file (it is about one page in length).  Just email me at mjayjock@gmail.com.  I have cut and pasted an excerpt from it below that I would like to make the basis for future discussion:

“As this document suggests, measurements of skin exposure are fraught with complications, particularly when it comes to interpreting the significance of the measurements themselves. My view is that assessing the effects of skin exposure, except in very specific situations, will be by its nature subjective and likely to remain so in the real world for some considerable time.

As a final word, consider the view of the European Agency for Safety and Health at Work:

“However, there is no scientific method of measuring the results of the body’s exposure to risk through dermal contact. Consequently no dermal exposure standards have been set.” - from “Occupational skin diseases and dermal exposure in the European Union (EU-25):policy and practice overview - European Agency for Safety and Health at Work””

I must say that I was aware that regulatory bodies have been slow to accept dermal exposure modeling but I thought that some progress had been made on this front in recent years especially in Europe with REACh. 

Clearly, Chris paints a somewhat dismal picture of the current state-of-the-science around quantitative dermal exposure measurement and modeling.  I have expressed my opinion on this in recent blogs but I would really prefer to hear from others on this topic.  I am especially interested in hearing from folks who are much more expert than I in the realm of dermal exposure measurement and exposure estimation via modeling.  This will include those who might incidentally read this blog and those who I am going to send it to directly. 

You can either reply to this blog or send me an email.  I will publish the best of them in a subsequent blog or blogs.

On an administrative manner, I have been in the habit of “Sharing” this blog with LinkedIn Groups of which I am a member.  This utility automatically posts the blog to the identified LinkedIn Group page.    When I attempted to do so for last week’s blog most of my groups  (e.g., American Industrial Hygiene Association) did not show up for sharing access.  If this continues I will post directly to the selected LinkedIn Group with a link to the blog.

Lost Keys Under Street Lamp Part II – Dermal Exposure

Chris Packham is a colleague from the UK who I met many years ago over there.  For as long as I have known him, and I am sure before that,  he has worked tirelessly trying to raise awareness of dermal exposure as an important source of risk to workers.  He is presenting a talk on the subject at a regional British Occupational Health Society (BOHS) meeting on November 18^th and he has graciously allowed me to publish that talk in this blog afterwards.   

Before then he sent me an email which I am reproducing below on the general subject in which, I believe, he makes some very good points.

I continue to be frustrated at the apparent insistence by hygienists on concentrating on inhalation exposure and ignoring skin exposure, particularly when statistics show otherwise.

==

“Both the number of cases and the rate of skin diseases in the U.S. exceed recordable respiratory illnesses.

In 2006, 41,400 recordable skin diseases were reported by the Bureau of Labor Statistics at a rate of 4.5 injuries per 10,000 employees, compared to 17,700 respiratory illnesses with a rate of 1.9 illnesses per 10,000 employees.” - OSHA Technical Manual, Section II, Chapter 2

==

“Occupational skin diseases are among the three most frequent groups of occupational diseases. ... However, occupational skin diseases have attracted relatively little attention in the global and national agendas for prevention of occupational and work-related diseases. – World Health Organisation Global Workshop, Geneva, February, 2011

==

At a skin conference in Amsterdam in 2013 German statistics were presented showing that occupational skin disease represented 35% of all recognised cases of occupational ill health!

And that is just skin disease, ignoring the contribution that skin uptake  makes to systemic toxic effects.

Is it because hygienists believe that they can measure inhalation exposure and confirm compliance with the exposure limits?  As this is not possible with skin they do not feel comfortable with skin exposure assessments? Perhaps they should consider what Einstein once said: “Not everything that can be measured counts, and not everything that counts can be measured”!

My take on this is that while it is certainly more difficult to measure or estimate dermal exposure (compared to inhalation), I believe that some attempt at quantification of dermal exposure is possible.  Dermal penetration modeling, which has been around for some time, is one way of getting a handle on dermal skin exposure potential.    Wil tenBerge has been a pioneer in putting together and sharing useful tools for the assessment of dermal exposure from skin contact with liquids and from skin contact with airborne vapors.   The latest has been his collaboration with Danial Drolet and Rosalie Tibaldi to fashion IH SkinPerm  (see https://www.aiha.org/get-involved/volunteergroups/documents/expassvg-ihskinperm.pdf).   

Dr. ten Berges previous work on this subject has been freely available for many years on his web site: http://home.wxs.nl/~wtberge/

Theses tools allow for the estimation (albeit currently unrefined) of how much of a dermally available substance might be absorbed into the body.   A previous blog here highlights the work of Dr. Deborah Lander in evaluating the uncertainty around these models.   Check it out at as the July 7 2014 blog: jayjock-associates.blogspot.com/2014/07/evaluation-of-ihskinperm-with-in-vitro.html.   Dr. Langer reports  “ that 27% of the model predictions were within a factor of 2,  73% where within a factor of 10 and all of them were within a factor of 30 fold. “  Clearly, 30 is a relatively large factor but my sense is that it can be significantly, if not dramatically, brought down by future experimental data  sets in which the consistency of the quality of the experimental data are carefully monitored and assured.  

The point of all this is that some quantification of dermal exposure is possible today given the details of the exposed skin area and duration of exposure.   If we are dealing with systemic toxic effect then we can estimate systemic dose.   Inhalation OELs can be converted to dermal OELs to make the comparison. If we are dealing with irritation or Type IV contact allergy as the primary response of concern then we are focused on determining the worst case amount per cm2 of exposure.  In my previous work we establish working mg/cm2/day exposure limits for contact allergens.  Thus, both primary types of dermal exposure are subject to quantitative estimates.  We should not fail to look for our “lost keys” in this area that is not “under the street lamp” of inhalation exposure assessment.

Looking for lost keys under a street-light

This statement sums up what a lot of us fall prey to; namely, seeking solutions where the looking is easy rather than striking off into the darkness for the true answers.

A real-world example in the world of Industrial Hygiene might be the situation where there is a continual occurrence of workers with symptoms of chemical overexposure.   The “street-light” approach here would be to determine what chemicals are present within the workplace and then monitor the breathing zone of the workers for the chemical.   In many, perhaps most, cases an overexposure is detected and then controlled and the problem solved.   The “easy” and obvious approached worked.

To stretch the analogy further, street-lights are positioned with a purpose.   They are designed to illuminate spaces that we need to see.  Thus, looking under street-lights for solutions is a good place to start.

In some cases, however, the solution does not reveal itself so readily.   You monitor and monitor, compare the results to all your OELs and nothing presents itself as (to steal another phrase) a “smoking gun.”   In this situation, the easy “street-light” approach has failed you and you need to strike out into the dark.   What to do?

It is now time to bring out the scientific method

1.        State the problem
2.        Form a hypothesis as to cause
3.        Experiment and Observe
4.        Interpret the Data
5.        Draw Conclusions and Make Predictions

IF 5 does not work out, THEN you need to go back to step 2.

You can do this on a number of levels.   Perhaps the simplest level you can do it is as a thought experiment.   That is, form a hypothesis and run it through the Hill Criteria of Causation that was the subject of a previous blog.  Just go to:  http://jayjock-associates.blogspot.com/2014/  and expand the “September” link to the right and then click on “The Hill Criteria of Causation” to see a detailed discussion of this important tool.   When you do this consider all of the available data and circumstance to see how good the fit is of your hypothesis to reality.   If it does not fit very well go to step 2 and form another hypothesis.    Just “rinse and repeat” until a coherent picture starts to emerge.

Giving the above problem a number of hypotheses are possible.  Here are a few that I thought of but there are almost certainly others:

   1.   You are measuring the wrong agent:
Perhaps a chemical you did not consider or perhaps it is a biological agent that is causing the problem.  It could be an agent, not directly associated with the operations, occurring in the ambient environment of the workers.

2    You are measuring air and dermal is the primary route of exposure:

    High MW, high Kow compounds will not be in the air as much as they might enter the body unmeasured through the skin.

3.  You are measuring to an 8 hour time-weighted average exposure and very short acute exposures are causing the problem which are not showing up as an over-exposure to an 8 hour OEL.

4.  The workers are lying or "faking it" to get out of work

5.  The effected workers are extremely sensitive; that is, “hypersusceptible” and will react to very low concentrations of chemicals in their workplace environment

On the face of it and without data, any of these could be true, it is up to you to figure out which one is the best fit to the facts at hand and then get as much data as you can or do some experiments to prove it.   Indeed, it is incumbent upon you as the IH to sort through the various hypotheses in a concerted effort to really nail down the cause of the adverse health effects of workers in your charge. 

What you do not want to do is “fall in love” with any particular paradigm designed to evaluate the risk of chemical exposures in the workplace.   You do not want to insist that you have done everything you can to find the answer and that there really is no problem because you cannot find it.  You owe it to your workers and yourself to really look into what they say is happening to them relative to adverse health effects at work.  I have found most workers to be honest witnesses to what is happening to them and their coworkers.   You need to listen carefully to what they are telling you and, unless you are sure that #4 is occurring in this situation, you need to give credence to their accounts.

 If you fail to do the above, if you continue to turn the handle on a paradigm that is not showing you what is happening, you may be guilty of futilely “looking for your lost keys under a street-light”.

Confession : The math I should have learned in school

Let’s face it; a lot of us in the IH profession are at some level intimidated by math.  I confess to the syndrome and I believe that  this fear is one of the reasons that modeling is still not generally done or even attempted by everyone.   Poor teachers, poor classes, and poor motivation as a teenager are all possible reasons.   I have experienced all of them, but significantly later in my professional life, well after the age of 30, I recognized the need.   I saw that math was the real basis of physical science and a tool I had to have if I was going to understand and work as a technologist.  At that point, I decided to back-fill my education and was fortunate to find some very good teachers in night school.

I have pushed modeling in the IH profession for many years and have seen a steady increase in its use as dedicated professional colleagues in the AIHA have picked up the banner and have written books and articles and given excellent courses.    I continue to believe, however, that there is only a relatively small percentage of IH professionals who might benefit from this tool are actually engaged.  My new hypothesis is that math intimidation is the reason.

The overarching purpose of this blog is as an “ An educational blog designed to introduce and facilitate industrial hygienists' involvement in quantitative risk assessment - especially exposure assessment and the specific area of exposure modeling.”   If foggy math concepts are keeping folks from engaging then I want to try and help.   I would like to help and back-fill your education relative to some basic mathematical concepts that will provide you with very useful tools.

At the end of this blog I am going to cut and paste some stuff from last week’s blog in which I tried to explain two-dimensional acute inhalation toxicity (both concentration and time).    To provide a good explanation of the subject I needed to explain PROBITS.   If your understanding of probits is a bit foggy, I think this explanation below could help.   If it doesn't explain it clearly please let me know where I lost you.   You can reply anonymously and, believe me, if you have the issue others will as well.  Indeed, please send me math topics that remain foggy to you.  Send me math topics that you just quit thinking about because you thought they were too hard.

Other areas I could try and provide some simple explanations as to how they work and why they are useful include:

• Logarithms (done in a previous blog but it could be repeated and improved)
• Calculus:  Area under the curve
• Statistics:   correlation, curve fitting, standard deviation, linear regression
• Mathematical definitions of inhalable, thoracic and respirable airborne concentrations and mass

PROBITS (and their use in acute toxicity – lethal dose-response example):

You may or may not remember what a “probit” is but it is a very useful mathematical construct.  It is directly related to the standard Gaussian bell-shaped curve with the area-under-the-curve (AUC) describing the portion of a population included on any part of that curve.  I know what some of you are thinking:  YIKES!  What is this guy talking about?  All I ask is that you Please stay with me on this for a few more paragraphs!  Like a professor of mine once said, “If it’s foggy you’re learning something!”   A few minutes of concentration can pay off in a lifetime of understanding. 

Here is an illustration of a Gaussian or bell-shaped curved:

The peak of the bell-shaped Gaussian curve is right at 50%.   That is, half the folks are in the area-under- the-curve (AUC) below (to the left of) the peak and half are in the AUC above (to the right) of the peak.   This is the average or mean value.   It is also Probit = 5.   Now I am going to ask you to remember a statistical construct you learned called the standard deviation .   The AUC from one standard deviation (or sigma on the above illustration) above the mean on the Gaussian curve is approximately 84%; that is, 84% of the population is in the AUC to the left of one standard deviation above the mean.   One standard deviation above the mean is also Probit = 6.   So 1 sigma above the mean  = probit = 6.   Because it symmetrical, Probit = 4 is one standard deviation below the mean and only 16% of the population are in the AUC to the left of this value.  

Still foggy?  Let’s put this in terms we all might understand:  SAT scores.    The average or mean SAT test score is a Probit multiplied by 100; that is, Probit 5 x 100 = 500.  Half the folks taking the test got a higher SAT score than 500 and half lower.   If you got an SAT of 600 you did better than 84% of the folks taking the test.    If you got a 733 on the SAT you were better than 99% of the folks who took that test.   The computer stops at 800 because you are getting so close to 100% that it does not matter any more.  How did I figure that a 733 SAT score beat 99% of the folks tested, it is a simple function in Excel.  Just put in (=NORMSINV(0.99)  + 5) and you will get 7.33, multiply by 100 to get the SAT score.

We all probably remember living and dying with “the curve” in college.  The raw tests score were converted to probits and, depending on the teacher, the grades assigned such that there was something like 10% “A”s, 25% “B”s, 55% “C”s and perhaps 10% “D”s or lower.   This is how you could get 40 out of 100 correct on a physics test and still get a “B”!    This is also why we all hated the person or persons who “killed the curve” by scoring very high and dragging the mean upward and everyone else's grade downward.

So let’s shift our thinking over to toxic or lethal dose-response which also follows this curve.   Probit = 7.33 (5 + 2.33) means that 99% of the population will respond with the toxic effect being measured, in this case death.   Since it is symmetrical, Probit = 2.67 (or 5 – 2.33) means that 1% of the population will be predicted to die and 99% predicted to live.    You can never get there but you can get as close to 0% deaths as you like with smaller and smaller Probit values.

Please let me know what you want to see and whether I am just talking to myself. 

Do you think I have it right about math intimidation in the IH ranks or do you think that I am all wet on this?

Modeling Acute Toxicity Dose-Response

By definition, things happen quickly during acute toxic responses to chemical exposure.  Indeed, adverse health effects from inhaling an acute toxicant can happen in the time-frame of seconds to tens of minutes.   Haber’s Rule advises that the toxic effect should be a linearly combined function of both concentration and time.  The classic expression of Haber’s Rule is: 

  Toxic Response = f ((Concentration)(time)).   

This mathematical expression says that when the breathing zone concentration is twice as high (e.g., 200 ppm versus 100 ppm) the time of exposure needs only be half (50%) as long to get the same toxic response.

The majority of acute toxicity dose-response modeling that has been done to date deals with lethality from inhalation.  Here acute lethality inhalation testing is done with rats in a time frame of tens of minutes extending to hours in duration.  These data are then modeled with the intention that these models will be useful for predicting human risk.

Relative to acute inhalation toxicity, Haber’s rule needs some adjustment.  The modified relationship that fit reality better is:

  Lethality = f ((Concentration)ⁿ(time))    n > 1   (but typically < 4)

In this relationship, the inhaled concentration has a non-linear effect on lethality.  For example, at n = 2, when the concentration is twice as high the time of exposure only needs to be 25% as long to render the same response.

Some of the earliest work on this was done in the Netherlands and, I believe, that much of the modeling tools were developed by Dr. Wil tenBerge.    The current standard equation used to fit animal data is:

  Probit = a + b ln (Cⁿt)

a, b and n are coefficients.   C is expressed either as mg/m³ or ppmv.

You may or may not remember what a “probit” is but it is a very useful mathematical construct.    It is directly related to the standard Gaussian bell-shaped curve with the area-under-the-curve (AUC) describing the portion of a population included on any part of that curve.  I know what some of you are thinking but please stay with me on this!  Like a professor of mine once said, “If it’s foggy you’re definitely learning something!”    

The peak of the bell-shaped Gaussian curve is right at 50%.   That is, half the folks are in the area-under- the-curve (AUC) below (to the left of) the peak and half are in the AUC above (to the right) of the peak.   This is the average or mean value.   It is also Probit = 5.   Now I am going to ask you to remember a statistical construct you learned called the standard deviation.   The AUC from the value of one  standard deviation above the mean on the Gaussian curve is approximately 84%; that is, 84% of the population is in the AUC to the left of one standard deviation above the mean.   One standard deviation above the mean is also Probit = 6.    Because it symmetrical, Probit = 4 is one standard deviation below the mean and only 16% of the population are in the AUC to the left of this value.  

Still foggy?  Let’s put this in terms we all understand:  SAT scores.    The average or mean SAT test score is a Probit multiplied by 100; that is, Probit 5 x 100 = 500.  Half the folks taking the test got a higher SAT score than 500 and half lower.   If you got an SAT of 600 you did better than 84% of the folks taking the test.    If you got a 733 on the SAT you were better than 99% of the folks who took that test.   The computer stops at 800 because you are getting so close to 100% that it does not matter any more. How did I figure that a 733 SAT score beat 99% of the folks tested?  Ans: It is a simple function in Excel, just put in (=NORMSINV(0.99)  + 5) into a cell and you will get 7.33, multiply by 100 to get the SAT score.

We all probably remember living and dying with “the curve” in college.  The raw tests scores were converted to probits and, depending on the teacher, the grades assigned such that there was something like 10% “A”s, 20% “B”s, 50% “C”s and perhaps 10% “D”s or lower.   This is how you could get 40 out of 100 correct on a physics test and still get a “B”!  This is also why we all hated the person who “killed the curve” by scoring very high and dragging the mean upward and everyone with lower scores downward.

So let’s shift our thinking back to dose-response.   Probit = 7.33 (5 + 2.33) means that 99% of the population will respond with the toxic effect being measured, in this case death.   Since it is symmetrical, Probit = 2.67 (or 5 – 2.33) means that 1% of the exposed population will be predicted to die.  You can never get there but you can get as close to 0% as you like with smaller and smaller probit values.  So let reproduce the above equation here:

Probit = a + b ln (Cⁿt)

Given any value of breathing zone concentration (C) over any time interval (t) and the fitted values for a, b and n (from animal studies) we get a predicted percentage response expressed as a probit.   At Probit = 9 everyone is predicted to respond.  At Probit = 1 essentially no one is predicted to respond or be adversely effected by this concentration over this time interval.  Using another function in Excel (NORMSDIST()) we can easily convert the probits to percentages predicted to respond.

A previous blog here discussed bolus exposures to acute toxicants.  Exposures that occur in a time frame of seconds to minutes.   In most cases we are not dealing with lethality but we could be encountering serious respiratory irritation from this short term exposures.   If we had good toxicological data on these responses at various C,t points we could model the percentage of the exposed population predicted to have a respiratory irritation response.   

As I mentioned in a previous blog, Dr. Wil tenBerge is an incredibly generous colleague who shares all of his models and software on his web site.  Just put in “home page Wil tenBerge” into Google.   http://home.wxs.nl/~wtberge/   He also has a considerable amount of very good educational material explaining this further as well as quite a few data sets of C,t rat lethality for chemicals like ammonia.

Questions for Discussion:

In a previous blog I discussed that potent chronic carcinogens like nitrosamines can have serious acute inhalation irritation potential. Do you have “chronic” toxicants in your work place that you are controling to 8 hour OELs than might also be acute irritants?   How would you evaluate and control this acute risk?

Is anyone out there aware of some available in-vivo or in-vitro toxicological testing protocols that could evaluate acute C,t irritation potential?   If so please share.