ERF of methylmercury

From Opasnet
Jump to navigation Jump to search



Question

What is the exposure-response function (ERF) of methyl mercury on several health endpoints such as intelligence quotient and lifetime risk of myocardial infarction after prenatal or long-term adult exposure, respectively?

Answer

Rationale

Data

Data updated successfully!

ERF of methylmercury(-)
ObsExposure agentResponseExposureExposure unitER functionScalingThresholdERFDescription
1MeHgLoss in child's IQ pointsThrough placenta as maternal MeHg concentration in hairµg /gERSNone0-130.7 (0 - 1.5)Cohen 2005
2MeHgLoss in child's IQ points2Maternal ingested intakeµg /kg /dERSBW09.8 (0 - 21.0)Converted from the row above assuming linearity and steady state
3MeHgMeHg TWIIngestionµg /kg /weekTWIBW01.3EFSA CONTAM panel, 2012
4HgHg TWIIngestionµg /kg /weekTWIBW04EFSA CONTAM panel, 2012

Study by Cohen et al[1] finds that prenatal MeHg exposure sufficient to increase the concentration of mercury in maternal hair at parturition by 1 µg/g decreases IQ by 0.7 points. The paper identifies important sources of uncertainty influencing this estimate, concluding that the plausible range of values for this loss is 0 to 1.5 IQ points, and they use triangular distribution. R↻

EFSA reviewed the tolerable weekly intakes for methylmercury and mercury and gave esimates 1.3 (previously 1.6) and 4 (unchanged) µg/kg/week, respectively.[2] The linear exposure-response from Cohen is more sensitive than EFSA TWI, as it predicts 9.8 IQp /(µg/kg/d) / 7 d/week * 1.3 µg/kg/week = 1.82 IQ point loss at the TWI exposure level (see conversion below). Both estimates are reasonably close to each other although the function shapes are different. Linear function is more realistic if exposure levels may be slightly smaller or a lot larger than the TWI. Also, when it is important to avoid false negative risk estimates, the linear ERF should be preferred over the EFSA TWI. However, the TWI approach assumes that there is no appreciable risk below TWI, and therefore we might want to give less weight to exposures below TWI. Thus, we assume a threshold for IQ effect but with large uncertainty from 0 to TWI = 1.3 ug/kg/week * 70 kg / 7 days/week = 13 ug/d. This enables value of information analyses about this uncertainty.

Based on the TWI from 2012, EFSA further concluded that infants, toddlers and pregnant women should avoid fish with high methylmercury (to prevent TWI exceedances) and eat plenty of fish with low methylmercury concentration (to ensure sufficient omega-3 fatty acid intake).[3]

Health Canada has produced a benefit-risk assessment on methylmercury and fish[4]. A risk assessment studied risks to children in Taiwan[5]. Another study was performed in five European countries[6]. Another benefit-risk assessment was done on pregnant women in Taiwan[7].

Methylmercury and cardiovascular disease

Virtanen et al [8][9] found that every microgram/gram of mercury (Hg) in adult men hair increases (on average) the risk of CVD death by 10% (95% CI: 2% to 19%) and the risk of CHD death by 13% (95% CI: 3% to 23%). D↷

In Beneris the output of interest is the CHD mortality due to MeHg intake from fish. Thus, first based on [8] the central estimate and the 95% CI for the change (in this case increase) in natural logarithm of relative risk (RR) of CHD mortality per unit change in Hg hair concentration were derived. In general, the relationship between the percent change in RR (%RR) associated with c-unit increase in hair Hg concentration and incremental change in lnRR (beta) per unit change in hair Hg concentration is beta = (1/c)*ln((%RR/100)+1). Since Virtanen et al. obtained their result using Cox regression normal distribution was chosen to represent the uncertainty in the parameter of the log-linear model for RR. The mean and the standard deviation of this distribution are respectively 0.1222 and 0.0473.

Exposure conversions

In order to derive the probability distribution of ERF for MeHg intake from fish a one-compartment model as well as the information on the proportion of dietary intake of MeHg that corresponds to fish was used. Assuming that the concentration of MeHg in blood is at a steady-state the daily dietary intake of MeHg from fish corresponding to a given hair Hg concentration or blood concentration can be estimated[10].

For conversion from methylmercury intake to methylmercury concentration in hair, WHO suggests the use of a single-compartment model. Blood mercury was converted to total hair mercury using a 1:250 ratio (New Zealand and Seychilles Island studies) and an assumption of equivalent maternal and cord blood levels[11][12]. R↻

Conversion from MeHg hair concentration into dietary MeHg intake is proposed by the U.S.EPA [13]. This conversion was used in the Bayesian Belief Network (BBN) model developed for the fish case study in Beneris project. Assuming that the concentration of MeHg in blood is at a steady-state the daily dietary intake of MeHg from fish corresponding to a given hair MeHg concentration can be estimated as

I = (a*Ch*b*V) / (R*A*f*BW)

where:

  • I is the intake of MeHg from fish (µg/kg bw-day)
  • Ch is the hair Hg concentration (assuming [Hg]=[MeHg]) (µg/g hair),
  • b is the elimination rate from blood (assumed 0.014 /day,[13]),
  • V is the blood volume (assumed 5 l[13]),
  • f is the fraction of absorbed MeHg that is distributed to the blood (assumed 0.059[13]),
  • A is the fraction of ingested MeHg that is absorbed from GI tract (assumed 0.95[13]),
  • BW is the body weight of adult (kg bw),
  • a is the proportion of daily dietary intake of MeHg that comes from fish (assumed 1, i.e.100%),
  • R is the hair-to-blood Hg concentration ratio (0.25 L blood/g hair)[13].

When using default values, this becomes

I = Ch * 1 * 0.014 /d * 5 l / (0.25 l/g * 0.95 * 0.059 * 70 kg) = 0.0714 g/kg/d * Ch,

where Ch is in units µg/g hair and I in µg/kg/d. Respectively, blood concentration can be converted to intake by

I = Cb * 1 * 0.014 /d * 5 l / (0.95 * 0.059 * 70 kg) = 0.0178 1/kg/d * Cb,

where Cb is in units µg/l.

The resulting ERF of MeHg exposure can be scaled from either concentration to intake and vice versa by using the equation. For example, the ERF from Cohen becomes

0.7 IQp/(1 µg/g * 0.0714 g/kg/d) = 9.8 IQp/(µg/kg/d)

The corresponding confidence intervals 0 and 1.5 IQp/(µg/kg) convert to 0 and 21.0 IQp/(µg/kg/d). According to Leino[14], Health Canada assumes that 14 ppm in the hair corresponds to 1.5 µg/kg/d intake of methylmercury. This is close to the estimate derived above.

We can also look at the intake that is not scaled by body weight I' = I * BW. Because f is the fraction of MeHG that is in the blood and thus (1 - f) is the fraction elsewhere in the body, we can say that the distribution volume Vd = V / f. Then we can write

I' = (a*Ch*b*Vd) / (R*A),

and, as we often know the intake, we can solve

Ch = I' * R * A / (a * b * Vd) = I' (ug/d) * 0.25 l/g * 0.95 / (1 * 0.014 1/d * 5 l / 0.059) = I' (ug/d) * 0.200 d/g,

which is analogous to the equation at Infant's dioxin exposure except that here we look at transport from mother's diet to mother's hair rather than to child.

Methylmercury and omega-3 interaction

Stern and Korn discuss challenges of separating methylmercury effects from omega-3 fatty acid effects, because they partly have the same endpoints, namely fetal and infant neurodevelopment[15]. They this especially important for benefit-risk assessments and dietary recommendations based on them. See also ERF of omega-3 fatty acids.

The Seychell Study found that omega-3 fatty acids may overcome or even prevent the harmful effects of methylmercury.[16] However, this if not easy to quantify in an ERF, so it is not included in the answer. This potentially causes bias exaggerating risk, which is - in a typical assessment - a better situation than false omission of risk.

Calculations

+ Show code

See also

  • Code with separate ERF and threshold archived

References

  1. Cohen JT, Bellinger DC, Shaywitz BA. A quantitative analysis of prenatal methyl mercury exposure and cognitive development. Am J Prev Med. 2005 Nov;29(4):353-65. [1]
  2. EFSA Panel on Contaminants in the Food Chain (CONTAM). Scientific Opinion on the risk for public health related to the presence of mercury and methylmercury in food. (2012) EFSA Journal 2012;10(12):2985. https://doi.org/10.2903/j.efsa.2012.2985
  3. EFSA Scientific Committee. (2015) Statement on the benefits of fish/seafood consumption compared to the risks of methylmercury in fish/seafood. EFSA Journal 2015;13(1):3982. doi:10.2903/j.efsa.2015.3982. press release
  4. Health Canada. (2008) Human Health Risk Assessment of Mercury in Fish and Health Benefits of Fish Consumption. [2] Accessed 13 Sept 2019
  5. Shu Han You, Shu Li Wang, Wen Han Pan, Wan Ching Chan, Anna M.Fan, Pinpin Lin. (2018) Risk assessment of methylmercury based on internal exposure and fish and seafood consumption estimates in Taiwanese children. International Journal of Hygiene and Environmental Health 221;4;697-703. https://doi.org/10.1016/j.ijheh.2018.03.002
  6. Silke Jacobs, Isabelle Sioen, Liesbeth Jacxsens, José L.Domingo, Jens J.Sloth, António Marques, Wim Verbek (2017) Risk assessment of methylmercury in five European countries considering the national seafood consumption patterns. Food and Chemical Toxicology 104;26-34. https://doi.org/10.1016/j.fct.2016.10.026
  7. Hsing-Cheng Hsi, You-Wen Hsu, Tien-Chin Chang, Ling-Chu Chien. (2016) Methylmercury Concentration in Fish and Risk-Benefit Assessment of Fish Intake among Pregnant versus Infertile Women in Taiwan. Plos One May 17, 2016. https://doi.org/10.1371/journal.pone.0155704
  8. 8.0 8.1 Jyrki K. Virtanen, Sari Voutilainen, Tiina H. Rissanen, Jaakko Mursu, Tomi-Pekka Tuomainen, Maarit J. Korhonen, Veli-Pekka Valkonen, Kari Seppanen, Jari A. Laukkanen, Jukka T. Salonen. Mercury, fish oils, and risk of acute coronary events and cardiovascular disease, coronary heart disease, and all-cause mortality in men in Eastern Finland. Arterioscler. Thromb. Vasc. Biol. 25 (2005), p.228-233.
  9. Jyrki K. Virtanen, Tiina H. Rissanen, Sari Voutilainen, Tomi-Pekka Tuomainen. Mercury as a risk factor for cardiovascular diseases. Journal of Nutritional Biochemistry 18 (2007) 75–85. Beneris:media:Virtanen_JNutrBiochem_2007_HgandCVD.pdf
  10. National Research Council. Toxicological effects of methylmercury. National Academy Press, 2000.
  11. WHO (World Health Organization). (1990) Environmental Health Criteria 101: Methylmercury. Geneva
  12. Methyl mercury: Bidone et al. (2004)
  13. 13.0 13.1 13.2 13.3 13.4 13.5 Integrated Risk Information System (IRIS). Chemical Assessment Summary, 2001. [3] [4] Accessed 13.9.2019
  14. Olli Leino: Fish consumption: human health effects and decision making. National Institute for Health and Welfare, Research 120/2014. Dissertation.
  15. Alan H. Stern and Leo R. Korn. An Approach for Quantitatively Balancing Methylmercury Risk and Omega-3 Benefit in Fish Consumption Advisories. Environ Health Perspect 2011: 119 (8) https://doi.org/10.1289/ehp.1002824
  16. Strain JJ, Yeates AJ, van Wijngaarden E, Thurston SW, Mulhern MS, McSorley EM, Watson GE, Love TM, Smith TH, Yost K, Harrington D, Shamlaye CF, Henderson J, Myers GJ, Davidson PW. (2015) Prenatal exposure to methyl mercury from fish consumption and polyunsaturated fatty acids: associations with child development at 20 mo of age in an observational study in the Republic of Seychelles. Am J Clin Nutr. 101(3):530-7. doi: 10.3945/ajcn.114.100503.