Apples, Arsenic, and Risk - Part 6: Theory and Reality

My Mom likes to resend emails she receives.  This is the old-timers with computer's 21st century version of sending her kids and grand kids clippings from the newspaper or Reader's Digest.

Her latest email is titled "Here are some facts that of course you already knew...Of  Course..... :)." At the beginning of the email she writes:

If you find that any of these are wrong you don't have to email me back and tell me.

You see, my mom likes to live in a world where being told "that's not true" does not exist.  As you can probably tell from this blog, I and my two boys, tell her these "facts" are not true quite a bit.

However, there is a difference between believing as fact that "Chinese headbands are made from used condoms" and Water with 10 ppb of arsenic has an excess cancer risk of one in 500 as reported by Consumer Reports.

The problem with health related information is what someone will do with this information passed off as a fact.  Not buying hairbands does not impact health.  That's also the point the TCEQ was making in their response to the EPA over the use of this new cancer slope factor for arsenic.

[I]f erring on the side of conservatism significantly overestimates risk or hazard and is not  fully  justified, then harm to public health may result from diverting public, industry, and government attention and resources away from chemicals which may represent more of a public health risk at environmental levels.

A while back I wrote a number of posts on laundered shop towels and their risk of contamination to workers who use them.  I stated what I felt were a number of "rules" we public health professionals should abide by.  Rule number five was:

Always make sure the model and equations reflect reality.

For Consumer Reports to write "For water with 10 ppb of arsenic, the excess cancer risk is one in 500," and for the EPA to generate data showing a Risk for Male Bladder Cancer of three excess cancers in 1000 if exposed daily for a lifetime to 1 µg of arsenic per liter of drinking water, one must have confidence in the numbers used to calculate that risk value.

In other words, should we trust the value spat out by our model?

Models are what we use to predict an outcome.  So regarding the development of a model, here are some rules that I think we should consider:

1. Does the formula represent what is going on in the real world?
2. Can the parameters that make up the formula be derived from sound data?
3. Are the assumptions used to generate the values sound?
4. Does the model's prediction reflect what we see in the real world?

For example, lets say we want to estimate - or predict - how many days it will take to get from Los Angeles to New York City.  The more variables in the formula, the better the prediction.  So we could look at the number of rest stops, fuel stops, speed limits, road closures and work, etc.  In it's simplest form, the prediction of how long is dependent on how far you want to go divided by the top speed times the amount of time driving at that speed.

How long = Total Distance / (MPH x Hours Driving)

That formula is sound, it may not be the best we can do, but it does represent what is going on in the real world and the parameters can be derived from sound data.

We know how many miles it is from Los Angeles to New York City, we can estimate the MPH we will drive, and we can estimate the amount of hours we will drive each day.

How Long = 2790 miles / (70 x 8) = 5 days.

Does 5 days reflect reality?  Yeah, it does, but it is also based on the assumption that we can drive for 8 hours in a day at an average speed of 70 mph.  That's doable, so the model's prediction reflects a reality - a possibility of that outcome.

Now lets say I have never driven a car before, in fact no one has, but our data shows that our car could go as fast as 120 mph.  Since we have never driven before, we could also assume that a person could drive for 22 hours - allowing two hours for fuel and bathroom breaks.

How long = 2790 miles /(120 x 22) = 1.05 days.

Is the number 1.05 days correct?  Yes, based on the values used in the formula.  Would you accept it as representing what is possible in the real world?  No.  Is it possible to get from Los Angeles to New York in a car in about one day?  Yes...but only if you drive for 22 hours and average 120 MPH.  For 1 day to be a reasonable - or sound - prediction, all the variables used to calculate it must be sound. If the output of one day does not reflect the real world, then either the model is incorrect or the values used to calculate the prediction are not valid.

That's the fundamental problem with risk assessment models.  It uses complex formulas to estimate - predict - a risk.  And that prediction of risk is only possible if the data is correct and the formula is sound.  Look at the equation used to determine the chronic daily intake (CDI) of a chemical for a resident (person) eating fish from a contaminated water body:

Source

One or two incorrect values entered into the calculation will skew the results - too much - or - too little.  And with risk, we use values that are based on assumptions that are very conservative; such as 2 liters per day for 70 years.  Or in the case of shop towels, a worker touching their hand that handled a shop towel to their mouth 117,600 times over their lifetime.

In the equation above, they assume the person will eat fish from the water body 350 days a year for 30 years.  Is C-fish the concentration in the whole fish or the part of the fish that is consumed?  Is that CDI possible? Yes.  Probable?  No.  Unfortunately the public will be told of the risk from eating fish from that area that is dependent on a possibility that is not probable.

It's the best we got...the people demand a number...and this is how we give it to them. And Consumer Reports will print that risk as if it will take place.

When it's all said and done, you must look at the prediction - the outcome - the value spat out by the formula - and ask:

Does the model's prediction reflect what we see in the real world?

That's what the TCEQ did when they looked at the cancer slope factor proposed by the EPA that was used for bladder cancer:

Drinking water in the US generally contains an average of 2 μg/L of arsenic (ATSDR 2007). Based on final draft SFo estimates, USEPA indicates that drinking water concentrations corresponding to 1 in 10,000 combined cancer risks for males and females are 0.21 and 0.14 μg/L, respectively. The implication is that on average all across the US, people’s drinking water contains arsenic levels that exceed the upper end of the USEPA acceptable risk range (1 in 10,000) by approximately 10-14 times. In other words, on average, the level of arsenic in the nation’s drinking water supply is unsafe. 

Why would the TCEQ doubt the cancer slope factor being used by the EPA?  Because the number it generated for the risk of bladder cancer does not reflect the reality of the world we live in:

For bladder cancer alone, the incidence risk calculated by USEPA based on final draft values for males/females is 3.1E-04 per μg/L. Therefore, based on 2 μg/L as an average drinking water concentration, the estimated bladder cancer risk for the US population would be 6.2 per 10,000 or 62 per 100,000. However, the actual occurrence of bladder cancer in the US is about 23 cases per 100,000 (males/females combined). It would take 3 times the actual bladder cancer incidence for US males/females combined to even make possible the 62 cases per 100,000 estimated due to arsenic exposure from drinking water alone. Thus, the incidence risk calculated by USEPA final draft values for bladder cancer appears to be inaccurate and overly conservative.

So what's the big deal if the potency being used is more protective?  Isn't less arsenic better?  Always, but in this case no...not if it is based on this model.  And here is why the TCEQ and I believe the EPA needs to discard this SFo:

Proceeding with this SFo will unnecessarily alarm the public by giving a greater perception of harm and risk than is actually taking place.

Speaking of harm....


Next Post: Apples, Arsenic, and Risk - Part 7: Who the heck is Sharyn Duffy of Geneseo, N.Y.?

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Apples, Arsenic, and Risk - Part 5: Calculating one in 500

I want to look at how Consumer Reports is able to claim that:

For water with 10 ppb of arsenic, the excess cancer risk is one in 500.

 How was that risk calculated, and most importantly, is it valid?

In my last couple of posts I have tried to explain how cancer risk is determined to answer the question of what amount of arsenic in my drinking water, apple juice, or grape juice is considered "safe?"  Ignoring less is better, how does the process work?

For chemicals that are known or suspected to be carcinogens, we use a potency factor which is the slope of the dose-response curve.  The EPA takes this potency and incorporates it into what they refer to as a "Unit Risk."

Unit Risk: The upper-bound excess lifetime cancer risk estimated to result from continuous exposure to an agent at a concentration of 1 µg/L in water, or 1 µg/m3 in air. The interpretation of unit risk would be as follows: if unit risk = 2 × 10-6 per µg/L, 2 excess cancer cases (upper bound estimate) are expected to develop per 1,000,000 people if exposed daily for a lifetime to 1 µg of the chemical per liter of drinking water. (1)

To calculate the Unit Risk, you need the cancer slope factor - potency - SFo.  Not to beat a dead horse here, but the  slope you calculate is going to be based on this hypothetical line you derive from the dose and the occurrence of cancer you have seen in your studies.

That hypothetical line is critical in determining the slope.  That slope represents the potency.  The potency will calculate the Unit Risk.  The Unit Risk will tell us the excess cancer cases (upper bound estimate) that are expected to develop per 1,000,000 people if exposed daily for a lifetime to 1 µg of the chemical per liter of drinking water.

The EPA is proposing to change the IRIS Toxicological Review of Inorganic Arsenic (Cancer) by increasing the slope factor - potency - by 17 fold.  Here is an example of how this cancer potency affects the cancer risk described.

Let's look at how the EPA looks at arsenic and bladder cancer in males.  This information comes from an Excel spreadsheet that can be downloaded from the IRIS web site.

The oral cancer slope factor (CSF or SFo) the EPA uses for its "Male Bladder Cancer Model Outputs" is:

11.2 mg/kg-day

If the average male weighs 70 kg and drinks 2 liters of water per day, the liters per kg drinking water intake will be calculated as follows:

2.0 L / 70 kg = 0.029 L/kg-day

To calculate the Unit Risk per ug/L, the cancer slope factor (CSF or SFo) is multiplied by 0.001 to go from mg to ug.

0.001 x 11.2 mg/kg-day = 0.0112 ug/kg-day.

...it is then multiplied by the L/kg-day:

0.0112 ug/kg-day x 0.029 L/kg-day = 0.00032 ug/L or 3.2E-04 = Unit Risk

The Unit Risk for Male Bladder Cancer for arsenic is 3.2E-04 ug/L

So how do we use that Unit Risk?

Well, for starters, we can use it to calculate the Lifetime Risk of arsenic in drinking water at 10 ug/L:
10 ug x 0.00032 ug/L = 0.0032 or 3.2E-3 Lifetime Incidence.

What's that mean?

If the cancer slope factor is correct, we will see 3 excess cancers in 1000 if exposed daily for a lifetime to 10 µg of arsenic per liter of drinking water.

So how much arsenic in drinking water would not present a significant risk for cancer?  What amount could we live with and still consider the water to be "safe?"

For that, the EPA has to decide what is significant.  Is it one in a million?  One in 100,000?  One in 10,000?  For a significant risk, the calculations used in the proposed IRIS document for arsenic use a "water concentration for a 10-4 incidence risk" - or one in 10,000.  The amount of arsenic in drinking water that is considered "safe" is the amount that will estimate a one in 10,000 lifetime risk.

To calculate the amount of arsenic in drinking water that will see a one in 10,000 lifetime risk, the EPA multiplies the cancer slope factor (CSF or SFo) by 0.0001 (1 in 10,000)

0.00032 x 0.0001 = 0.32 ug/L

There you have it.  To reduce the risk of male bladder cancer we need to consume no more than 0.32 ug/L of arsenic based on a 70 kg males drinking 2 liters per day for 70 years.  At that concentration, 0.32 ug/L, we should see no more than one additional male bladder cancers per 10,000.

Using the CalEPA method, we would come up with the same risk.  Using their formula, ([mg/day] * SFo) / 70 kg = risk, and the amount consumed, 0.32 ug/L = 0.00032 mg/L in a 70kg adult who drinks two liters of water per day (0.00032 x 2 = 0.00064 mg/L....we get:

([0.0064] x 11.2) / 70 = 0.000102 = 1.02E-04 or one in 10,000

And what does the proposed SFo model predict for excess male bladder cancers at the current MCL of 10 ug/L?  Three additional male bladder cancers per 1000, or about one in 330.

For those "lifetime risks" to me valid, the cancer slope factor (CSF or SFo) must be valid.  You saw in my last post that the TCEQ thinks the EPA has erred in how they calculated the slope factor.  You may also remember that the proposed cancer slope factor they want to use is 17 times higher than the one they use now.  They want to take it from a potency of 1.5 mg/kg-day to 25.7 per mg/kg-day.  The CSF used for male bladder cancer was 11.2 mg/kg-day and that gave use a male bladder cancer incidence of one per 300!

The question now becomes: how representative is that upper bound limit of risk that has been calculated?

Should we accept Consumer Reports excess cancer risk is one in 500 for 10 ug/L of arsenic in drinking water?

I bet the TCEQ has something to say about that as well.


Next post: Apples, Arsenic, and Risk - Part 6: Theory and Reality


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Apples, Arsenic, and Risk - Part 4: The TCEQ tells the EPA, Phooey!

Consumer Reports writes:

As our investigation found, when scientists and doctors do look, the connections they’ve found underscore the need to protect public health by reducing Americans’ exposure to this potent toxin.

But it's not that simple as the EPA points out:

The behavior of arsenic in the body is very complex. After absorption, inorganic arsenic can undergo a complicated series of enzymatic and non-enzymatic oxidation, reduction, and conjugation reactions. Although all these reactions may occur throughout the body, the rate at which they occur varies greatly from organ to organ. In addition, there are important differences in arsenic metabolism across animal species, and these variations make it difficult to identify suitable animal models for predicting human metabolic patterns. (1)

So with that in mind, the EPA has moved forward to significantly change the estimated carcinogenic potency of arsenic, which the Texas Commission on Environmental Quality (TCEQ) believes "already has a relatively high SFo." (2)

What's the EPA using to support this change?  The TCEQ points out:

USEPA used lung and bladder mortality data from Morales et al. (2000) for the dose-response assessment for the final draft SFo. 

And that "Morales et al. uses these mortality data to calculate standardized mortality ratios (SMRs) and notes:"

“Although the computed SMRs display a large amount of noise, there appear to be higher SMRs at high exposure levels compared to exposures in the lower range, especially for bladder and lung cancer.”

Wait just a dang minute, TCEQ exclaims:

To say that there is “noise” in the SMRs over the eight exposure categories is an understatement. 

What is the TCEQ basing this on?  Well back to square one, it's all about the dose-response curve and the SFo derived from it.  If we are going to except the 17 fold increase in potency then we must accept the dose response curve used to determine the slope.  The TCEQ notes this, stating:

Dose-response is the cornerstone of toxicology, but the lung and bladder mortality data (SMRs) from Morales et al. (2000) provide a poor basis for dose-response assessment as a dose-response is not apparent and not monotonic.

If you recall, the slope is derived from the line representing the dose and response and is based on the assumption that every dose poses a risk.  It is all predicated on a dose-response where the higher the dose the greater the risk.  With that in place you can get a line and a slope:

That line though, is dependent on a linear progression - higher the dose, higher the risk or occurrence.  But that's not apparent in the Morales et al. data the EPA is using according to the TCEQ:

For bladder cancer, the dose-response data from Morales et al. (2000) and used by USEPA do a poor job of characterizing the shape of the dose-response curve, as can be seen from the figure below (line added for emphasis).

What does the dose-response curve look like for bladder cancer?  Take a gander at this:

Page 13

With that shape seen, the TCEQ informs the EPA:

The ability to fit a line through data points does not necessarily mean that the underlying data adequately define the shape of the dose-response curve, including the critical low dose region. Based on the above considerations, the underlying data modeled by USEPA provide a poor basis for dose-response assessment.

The 17 fold increase is based on the Morales et al. data.  The SFo the EPA proposes is based off of a line that used a dose response curve that looks the one above.  How much confidence in that SFo should we have?

So why does Keeve Nachman, the Johns Hopkins scientist, tell Consumer Reports:

The [EPA] proposal "suggests that arsenic's carcinogenic properties have been underestimated for a long time and that the federal drinking-water standard is underprotective based on current science."

You'll have to ask him that.  I suspect he, like a lot of others, just accepts what others professionals have to say as long as it follows their established way of thinking.  Arsenic is toxic ergo any amount in the water is unhealthy.

But "current science" has not brought forth anything that can support lowering the current 10 ppb in drinking water.  So what's the problem?  Well the damage has already been done.  When Consumer Reports writes:

For known human carcinogens such as inorganic arsenic, the EPA assumes there's actually no "safe" level of exposure, so it normally sets exposure limits that include a margin of safety to ideally allow for only one additional case of cancer in a million people, or at worst, no more than one in 10,000. For water with 10 ppb of arsenic, the excess cancer risk is one in 500.

...it has drawn a line in the sand for the public.  The risk of cancer now becomes one in 500 for water the EPA claims has been telling us is "safe."

But that risk of one in 500 is based on a slope generated from a squiggly line akin to a path from the Family Circus.




That Morales et al. dose-response curve is what helped generate a SFo that is 17 times more potent than what we currently accept.

Next post: Apples, Arsenic, and Risk - Part 5: Calculating one in 500