Summary:March12,2013AdvisoryPanelMeeting
Advisory Panel: Bruce Alexander, Alan Bender, Jill Heins‐Nesvold, Pat McGovern, Geary Olsen, Greg Pratt Steering Committee: Jeanne Ayers, Aggie Leitheiser, and Joanne Bartkus MDH: Jean Johnson, Jessica Nelson, Mary Jeanne Levitt, Chuck Stroebel, Jeannette Sample, Matthew Montesano, Paula Lindgren, Blair Sevcik, Barbara Scott Murdock, Rita Messing, Carin Huset, Paul Swedenborg. Welcome and introductions Bruce Alexander, chair, welcomed panel members and attendees and invited them to introduce themselves. Legislative update Aggie Leitheiser gave the legislative update. Biomonitoring has garnered a great deal of interest in the legislature, and four bills have been introduced: 1) SF1170/HF097 would “address environmental health risks.” Part of the Omnibus environment bill includes the MPCA‐MDH initiative for biomonitoring, which is in the Governor’s budget. The legislature’s environmental fund, which has funded EHTB since 2007, would also fund this initiative. 2) A second bill introduced in the House (HF0961) would provide funding from clean water funds (the Legacy fund) “to establish a biomonitoring program that would focus on children and disadvantaged communities to provide data on disparities in pollutant exposure and other measures necessary to assist with water quality management and protection decisions.” 3) HF1402/SF785 would provide $313,000 per year to continue PFC biomonitoring in the East Metro, in accordance with the recommendations of the EHTB Advisory Panel. 4) HF994 would specify that “the MPCA may not issue or modify a permit to a facility without analyzing and considering all the cumulative levels and effects of past and current environmental pollution from all sources on the environment and population of the geographic area… within which the facility’s emissions are likely to be deposited.” The above bills provoked some lively discussion. Aggie reminded the panel members that both they and MDH had chosen mercury in children as the analyte of choice for further biomonitoring in Minnesota—because we can take action to prevent exposure to this chemical, which has known health effects. Greg Pratt noted that the language in House bill HF994 is already in law for the Phillips neighborhood. He observed that the requirements would create a lot of work for the MPCA, yet the bill does not appropriate any money to do the work. So far, Aggie said, the bill has not been heard and has no Senate companion. Pat McGovern asked, which analytes are mentioned in the HF0961 bill? Jean answered that this bill appears to be based on our report to the legislature, as it addresses some of the analytes we had listed. Both Aggie and Jeanne Ayers asked whether the panel would 1
recommend studying PFCs instead of mercury in the legislative initiative. The panel’s response was no. Aggie said that we hope to get some flexibility with funds [so we could add PFCs]. Geary reminded the panel that the original recommendation about PFCs in the report to the legislature had posited two studies: the first would create an update to the original East Metro project, and a second would recruit and biomonitor a larger population in the East Metro. He asked, can we prioritize one of these two? He added that, in his opinion, we have two studies that followed the same group of individuals, and it would be better to establish the trend in those people. If we have money for only one PFC study, EHTB should do the longitudinal study. Panel members agreed. Pat McGovern asked, would a PFC study trump the mercury study? Geary answered: No. Alan Bender added that, although a second longitudinal PFC study would be of interest, mercury is a much higher priority. Little is known about mercury’s distribution in the population, he said, and the mercury data could mean that something far more significant is going on that we don’t understand. Given the nature of that exposure, mercury trumps PFCs. Bruce reinforced the message by saying, mercury has known public health effects. Air Quality, Health, and Traffic Paula Lindgren and Greg Pratt presented a report on an MDH, MPCA, and Rochester Epidemiology Project (REP) Partnership study of asthma exacerbations and traffic in Olmsted County, Minnesota. The REP links medical records of Olmsted County residents with the sources of their medical care, and facilitates access to medical records from multiple institutions. The REP data, from 1.8 million medical records on nearly 1 million people, provide a complete picture of all health care delivered to each individual in that population. This study gathered data on all medical visits for asthma treatment from 2000 through 2010: inpatient hospitalizations, emergency department visits, and three or more outpatient visits for asthma. For each patient, the total number of asthma exacerbations was divided by the number of years in the REP during that 11‐
year period and recorded. Each patient’s address was geocoded to its exact location and the patient’s age and gender were also recorded. Altogether, 19,915 people with asthma were in this study (Table 1). These people with asthma exacerbations were then mapped to see whether asthma exacerbations were correlated with traffic, measured as vehicle kilometers traveled (VKT) within 250 and 500 meter buffers around the address or as traffic density. 2
Table 1. Exacerbations among REP Asthma Patients Exacerbations per Year N % None 16,218 81.44 1‐3 3,664 18.40 4‐6 28 0.14 7‐9 3 0.02 10‐12 1 0.01 > 12 1 0.01 Table from Lindgren/Pratt presentation. Because many components of traffic can affect human health, Greg Pratt explained, we don’t know which air pollutant, or other component of traffic, is responsible for adverse health effects. So this study took the perspective that traffic is harmful as a result of the integrated effect of multiple components. We looked at exposure to traffic itself, using methods for systematically generating a highly spatially resolved measure of traffic density. Once we have quantified exposure to traffic, Greg continued, we can use that metric to evaluate factors that may be associated with traffic, such as asthma, socio‐economic status, racial/ethnic composition, and measured or modeled pollutant concentrations. The metric can also be used in a land‐use regression model to estimate pollutant concentrations. This analysis is based on studies that showed that concentrations of many pollutants found along busy roads decrease to local urban background concentrations at about 300m from the roadway. The study then looked for associations between traffic exposure and the number of asthma exacerbations/year. Poisson models were used for average exacerbations and logistic models were used for binary outcomes (any exacerbation/no exacerbation). The data showed that the average number of asthma exacerbations per year increased as traffic density increased. Results from the logistic model showed that the odds of any exacerbation increased 8% for every unit increase in traffic density, after controlling for age, gender, and poverty. The odds also increased with each unit increase in vehicle kilometers traveled: 12% for people living within 250m of the roadway and 6% living within 500 m of the roadway. But another measure is also strongly associated with asthma: poverty. To measure this, staff constructed a block group for each geocoded address and examined the income to poverty ratio for each block group. (Note: The calculation uses the income levels defined as poverty thresholds by the federal government.) Families and individuals who are identified as having income below the poverty level have an income‐to‐poverty ratio of less than 1.00. In this study, the percentage below 1.0 in the block group was assigned to each person with asthma exacerbations in the block group. The analysis looked at any exacerbation or at the number of exacerbations with respect to age, sex, poverty, and traffic density and VKT. The data showed that the odds ratio for asthma exacerbations associated with poverty increased 600% (six‐fold) for every unit increase in poverty, after adjusting for age, sex, and traffic. 3
Discussion Much of the discussion revolved around other health and socioeconomic status (SES) indicators that might be added to the analysis. Pat McGovern commented that on the West Coast, studies looking at exposure to traffic have seen similar associations with preterm birth, which is also associated with poverty, especially for African‐Americans. Paula thought that would be a good idea, but explained that pre‐term birth data are available at the county level only. Bruce asked whether birth certificate data had location data, and Jeanne Ayers suggested that the REP might have vital records with fine geographic resolution. Jill asked, why not look at COPD as an outcome? Given that particulates from traffic affect people with COPD at the molecular level, we would expect a stronger COPD association with traffic pollution than with asthma. Traffic pollutants act more as irritants for asthma. Although staff had made the decision based partly on the fact that COPD is harder to document in medical records than asthma, Paula said she would be interested in looking at COPD. Aggie asked whether being poor means a higher risk of asthma, or whether it is a matter of where you live. Paula explained that it is a little of each. Jill asked about the estimate of 300m as the extent of bad air quality near highways, and Greg answered that earlier studies had shown that pollution levels decline to background between 200‐400m from the roadway. Bruce asked whether an urban/rural analysis would be possible, one that might compare Rochester to everywhere else in Olmsted County. He suggested that people in urban and rural environments might encounter very different exposures. Paula replied that an urban/rural indicator might be possible. In addition, Bruce noted, some significant changes in demography have taken place in Rochester over the last decade, as many more immigrant populations—
Hispanics and Somalis—have come to Rochester, according to 2010 data. Including race/ethnicity in the model could make it possible to identify disparities in exposure and target interventions to reduce exposures. This led Pat to ask whether staff had considered race as a covariate. Greg replied that staff could pull racial/ethnic data from the census, but that adding such data might cause the model to lose statistical power. The panel also suggested examining housing as another indicator of SES suggested for examination, but staff explained that, although the REP contains a housing index based on age and housing type, 50% of the data were missing. 4
Population Characteristics In a related presentation, Blair Sevcik reviewed new Minnesota‐specific Tracking indicators of population characteristics that describe… 
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People in Poverty Median Household Income People without Health Insurance She used data from the U.S. Census Bureau’s Small Area Estimates Program, including the 2005‐
2009 Small Area Health Insurance Estimates (SAHIE) and the 2000‐2010 Small Area Income and Poverty Estimates (SAIPE) and determined poverty by comparing household income to federal household poverty thresholds. These thresholds are determined by the U.S. Census Bureau and calculated using a family's household size and composition. If a household’s income (the sum of incomes from everyone living at the address) is less than a poverty threshold, then every person living in that household is considered to be in poverty. People without health insurance have neither private nor public (government) insurance. In demonstrating the data, Blair pointed out the increase in poverty in Minnesota. She noted that the poverty rate in 2010 was 12%, 4% higher than in 2000, but also explained that the method for calculating poverty had changed substantially between 2004 and 2005. Thus, this rising trend should be interpreted carefully. Moreover, although 12% of Minnesotans of all ages were impoverished in 2010, 15% of all Minnesota children under age 18 and 17% of those under age 5 lived in poverty. Overall, childhood poverty in Minnesota has trended upward since the year 2000. In the same time frame, median household income in Minnesota had been trending upward until 2008, when it began to decline. Nevertheless, median household income in Minnesota has been consistently above the national average since the year 2000. Health insurance coverage in Minnesota has been relatively stable since 2005, with a small increase in the percentage of people without health insurance in 2009‐10. Again, Blair cautioned, this trend must be interpreted with caution because of a substantial change in methodology between 2007 and 2008. In 2010, about 10% of Minnesotans under 65 years of age and about 7% of children (18 years and younger) had no health insurance. Analyzed by race/ethnicity from 2005 through 2010, the health insurance data show that non‐Hispanic whites without health insurance were consistently around 8% of the population compared to about 15% for non‐Hispanic blacks until 2009‐2010, when the uninsured rate rose to about 16%. Minnesota’s uninsured Hispanic population, however, has hovered around 27‐28% throughout the entire period. Questions to the panel requested recommendations for: 
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Other measures to link Other data users Other indicators 5
Discussion Pat McGovern suggested looking at employment (yes/no) to see how it correlated with poverty and income. She suggested contacting the Minnesota Department of Employment and Economic Development (DEED) for data. Greg asked whether the median income was in constant dollars, and Blair explained that the SAIPE database uses only unadjusted income numbers. Noting that the race/ethnicity slide for lack of health insurance may reflect a big change in demography in Minnesota, Bruce commented that it would be good to show the number of people in each racial/ethnic category together with the percentage of uninsured in each group. Are we seeing changes in the numbers of uninsured people with a rising Hispanic population? Hispanic immigration is changing age distribution in Minnesota, especially in rural areas. Alan asked whether the public would understand why we consider poverty, income, and health insurance to be environmental. Traffic is an environmental issue that people can understand, but while the professional world would understand why we looked at traffic, the public might not understand why we’re looking at poverty. Greg replied that people in the Phillips neighborhood—a disadvantaged neighborhood—are surprisingly sophisticated about the many things that affect health, adding that the language in one of the House bills described above (HF994) illustrates this. He also commented that it’s not good for society to have young kids growing up in poverty. In response to the discussion of other variables, Pat suggested, first, that education level may affect people’s ability to get access to healthcare and, also, that the Tracking program might consider health insurance’s association with emergency department (ED) visits. Jill added that public programs have found that uninsured people have the highest rates of ED visits. Pat asked whether Tracking had any data on homelessness. When Blair asked about sources, Jill suggested Wilder Foundation, which has done regular surveys of homelessness statewide. Using housing age came up as a possible measure of poverty, and Greg Pratt noted that the cities have categorized housing, denoting some as distressed housing. He suggested contacting Cecelia Martinez at the Center for Earth, Energy, and Democracy (CEED) and also noted that housing built in 1950 is more likely to contain lead paint. Bruce suggested that it would be interesting to look at asthma rates over time in Olmsted County, especially as demographic changes take place in the population and as asthma definitions change. Tracking Updates Jean Johnson reviewed the update about the CDC Tracking Network’s solicitation of “data use” project proposals. CDC has asked Tracking grantees to submit proposals for short‐term projects that explore data presentation and impact analysis, apply innovative informatics techniques, and publicize highly relevant results or products. The agency’s areas of interest include the use of: 
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Sub‐county data, such as zip code level data; Environmental health profiles (multiple exposures and impacts, making effective policies); 6
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Place‐based decision making; Social vulnerability indices; Private well data. Minnesota is interested in proposing a place‐based analysis project and a private wells project focused on arsenic. In choosing projects, CDC aims to highlight and promote the use and relevance of Tracking work by demonstrating how Tracking is a unique, valuable resource. Discussion Bruce asked for some clarification on the review process for the proposals, and Jean explained that these proposals do not provide extra funding for the grantees. The money for the projects comes from existing grant money, which is currently from the Affordable Care Act, and the projects are a redirection of existing resources, rather than new resources. Greg suggested that staff get in touch with Cecelia Martinez, who works on similar multiple variable issues using EPA tools, such as EJ (Environmental Justice) View and EJ Screen, at the Center for Earth, Energy, and Democracy (CEED). He also suggested Jeff Matson at the University of Minnesota’s Center for Urban and Regional Affairs (CURA). Bruce commented that pulling together multiple indicators sounds similar to network analysis projects happening at the U. Chuck Stroebel then highlighted updates on the MN EPHT website and called attention to two recent successes: 
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Collaboration with MN Cancer Alliance to develop a press release about ways to prevent melanoma. The press release used MN EPHT data to illustrate the rise in melanoma among adults aged 20‐49 years. Collaboration with the American Lung Association‐Minnesota to produce a joint publication, The Scope of COPD, which lists various ways people can prevent chronic obstructive pulmonary disease and uses MN EPHT data to illustrate facts about COPD. The East Metro PFC Biomonitoring Follow‐up Project: Results from Survey Data Analysis Jessica Nelson and Christy Rosebush presented the preliminary results of the questionnaire analysis portion of the East Metro Follow‐up Project. Jessica began by briefly describing the scope of the project, which in 2010 measured the concentration of perfluorochemicals (PFCs) in 164 East Metro residents who had participated in MDH’s 2008 pilot project. The Phase 1 analysis of the follow‐up, now complete, measured the 2‐year change in PFC concentrations among project participants. The Phase 2 analysis is studying participants’ survey responses to investigate sources of exposure to PFCs. The 2008 project had gathered limited information on participants. Thus, Jessica said, the 2010 project questionnaire was designed to gather more detailed information on residential and water consumption history. This enables staff to construct a better measure of each participant’s exposure to PFC‐contaminated water and―poten ally―a range of other sources of PFC exposure reported in earlier studies. 7
She then described how staff derived four variables related to residential history and water consumption based on questionnaire responses: 
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Total time lived in the three communities1 Total time in which participants drank unfiltered water Type of water treatment at the 2008 address Tap water consumption Jessica then reviewed the data (tables and graphs in March 2013 Advisory Panel book) and summed up the findings for water consumption and residence in the community. Overall, the longer participants had lived in the community and the more years they had spent drinking unfiltered water, the higher their PFC levels. Analyses of total years residing in the community and total years drinking unfiltered water showed a clear rising trend in PFC levels, which was somewhat stronger for the years of drinking unfiltered water. People who used reverse osmosis or granulated activated charcoal filters had the lowest geometric mean PFC levels. People who did not treat their water at home had the highest, while people who used bottled water or pitcher/refrigerator/kitchen filters had levels in between. But because the survey question asked about only one point in time, these results are difficult to interpret. Finally, Jessica said, the analysis had also shown a strong positive association between serum PFCs and current tap water consumption, reported as number of cups/day. People who reported drinking 0 to 2 cups of tap water/day had about half the geometric mean for PFOA compared to those who drank 3‐6 cups/day and those who drank 7 or more cups/day. She said that this likely indicates that current consumption reflects a person’s past consumption. We do not want to convey the message that current tap water is a significant source of exposure to PFCs, she added, so we need to think carefully about how to present this. All analyses were adjusted for age, gender, and blood donation. Jessica then discussed blood donation, product use, and home garden variables. The survey had asked whether participants had donated blood in the last 2 years and how frequently they donated blood each year. Despite the small numbers, the analysis showed that the people who had donated blood in the last 2 years had significantly lower PFC levels compared to those who had not, and that people who donated frequently (3+/year) had lower levels than those who donated only 1‐2 times/year. The results from questions about product use and home gardens were mostly null for the three PFCs of interest: PFOS, PFOA, and PFHxS. Participants who reported having new carpets installed in the last year before the follow up project (2009) had higher blood levels for these three PFCs, but the results were not statistically significant for PFOA and PFHxS. Participants who reported using waterproof spray had statistically significant lower levels of PFOS and PFOA. PFC levels did not differ between people who had home gardens and ate homegrown produce, and those who didn’t. 1
People in the study area were fairly mobile within the three communities. Thirty‐nine percent of participants had two different addresses in Oakdale, Lake Elmo, or Cottage Grove, 15% had three addresses, and 7% had four or more addresses. 8
Christy Rosebush reported the results from the survey’s food frequency questions. The literature on PFCs had suggested that certain foods, fast food, and fast food or snack packaging contributed to PFC levels, so the survey contained many questions about diet. The questions emphasized products with food contact packaging. The analysis, however, did not find any associations between PFC levels and eating fast foods frequently or eating microwave popcorn and other foods that come into contact with packaging, nor did it find associations with eating foods such as red meat and potatoes, which are suspected as sources of exposure to PFCs. Jessica then handed out two supplemental tables of preliminary results and presented a slide of the first, the 2010 results for exposure to PFBA, a PFC detected in only 21% of participants. PFBA is widely detected in water sampling in the East Metro, and has a much shorter half‐life (several days) than the other PFCs discussed. •
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Likelihood of PFBA detection increases with age Groups less likely to have PFBA detected included females (OR=0.48) and people who donated blood (OR=0.31) There was no association with whether or not a person had a home garden, but frequent eaters of home garden produce were more likely than never eaters to have PFBA detected (though this was not statistically significant) People whose carpet and furniture were treated for stain resistance prior to 2002 were more likely to have detectable PFBA The results were not different by community She next presented a slide of the second supplementary table, which summarized the data from people whose PFC levels did not decline from 2008 to 2010. People who had lower PFC levels in 2008 were more likely to be in this group, and people who donated blood were less likely to be in this group. There was no evidence of any associations with home garden produce, years drinking unfiltered water, sex, or age. There were some positive associations with product use, but these were not statistically significant. Jessica then summarized the preliminary conclusions: •
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Total years drinking unfiltered water best predicts serum PFCs Current tap water consumption reflects past consumption habits This evidence supports the conclusion that drinking water was a major source of exposure in the community and that efforts to reduce this exposure were key in reducing serum levels Serum PFCs are lower in people who donate blood A positive association may exist between PFOS, PFOA, PFHxS, and new carpet Lack of positive results with other products or diet variables could be due to the small sample size and the fact that this population was highly exposed to PFCs in their drinking water in the past. PFBA was more likely to be found in people who were: o male, older, frequent home garden produce eaters, not blood donators, and/or had pre‐2002 stain resistant carpet treatment 9
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People whose PFC levels did not decrease from 2008‐1010 more likely to: o have had lower 2008 levels, not donate blood Jessica ended by summarizing the next steps for the project:  Finish the data analysis and interpretation;  Report results to the participants by letter;  Hold meetings with the community and with healthcare providers in the community;  Submit manuscript of the results to a journal. Discussion Greg Pratt asked whether we know how effective different water filtration methods are. Jessica answered that MDH has studied the effectiveness of water filtration methods in removing PFCs. All of the types mentioned can filter PFCs. The results presented categorized the type of water treatment at participants’ 2008 address based on the likelihood of consistent, effective filtration. Jessica asked the panel: Would the panel recommend a combined variable using years of drinking unfiltered water and current tap water consumption (as a surrogate for past consumption)? Bruce’s question was: What are you trying to answer? Jessica said that the intent is to create a predictor variable that best reflects past exposure to PFCs through drinking water. This combined variable would incorporate both length of time of exposure and quantity of exposure. Geary Olsen said that the survey question should have asked about tap water drinking habits in the past. Earlier, he had commented that the three tap water consumption categories presented really appeared to be two groups—people who don’t really drink tap water and people who do—and suggested that Jessica analyze a binary classification, with 0 to 2 cups per day compared to 3 cups or more per day. Bruce, on the other hand, thought that displaying the water consumption data in finer categories would be instructive. But he did not think the suggested combined variable (i.e., combining years of drinking unfiltered water and current tap water consumption as a surrogate for past consumption) would be helpful either for analysis or for conveying a clear message to the community. Greg commented that he didn’t see why we shouldn’t combine these variables, but he, too, was unsure that the new metric would be more useful. If current water consumption is linked to PFC levels, he said, and if no PFCs are in the drinking water anymore, then current consumption of water does relate to past exposure. But Jessica quickly pointed out that the filtered drinking water still has some low PFC levels, although nothing like the PFC levels in the past. Alan’s comment on the discussion was that, in considering how to present these data, it is important to determine whether the message is aimed at the community or at publication in a peer‐reviewed journal. 10
Jessica asked: Do panel members recommend additional analyses for the phase 2 analysis? Geary Olsen suggested that Jessica should be very cautious in interpreting any relationship between PFBA laboratory data and any possible sources of exposure identified by questionnaire. Saying that it is a widespread, poorly understood contaminant, he explained that low levels of PFBA are found in many different sources, not just in water, and it’s unclear what they are. Pat asked, are you saying that PFBA is ubiquitous in the environment? Yes, he answered, in numerous ways. In addition, it has a very short half‐life—about three days—so it leaves the body quickly. For this reason, he advised against the logistic regression (detection vs. non‐detection) analysis, but instead recommended showing actual values for PFBA. Overall, because of the number of sources and the short half‐life of the chemical, Geary believes that the analysis presented is uninterpretable. He suggested talking to Bill Reagan of 3M about the difficulties in analyzing PFBA. The panel recommended no additional analyses for this project, and Jessica asked: How should MDH interpret these results for participants and the community? In reviewing the preliminary conclusions, Bruce said that the current tap water consumption reflects past consumption is an assumption, not a finding. Geary commented that Jessica should anticipate the question, is it safe for me to get a blood transfusion? This prompted Greg to ask whether nursing mothers transfer their PFCs to their offspring, and Geary said yes, we know that they do. But it’s only a slight transfer—not much. Pat asked, what message should we recommend in answer to the question about blood donation? Geary said the reduction in PFCs in blood donation is just a few ng/ml, but that the finding is important for the people who give blood. Alan said that blood donation is of tremendous social value, so we need to be very careful in giving that message. Geary recommended talking with David Mair, the medical director at the Red Cross, and to use their message, rather than giving an MDH message. Bruce asked for a clarification on the conclusion that people whose PFC levels did not decline from 2008 to 2010 were more likely to have had lower levels in 2008 and did not donate blood. What does “lower” mean? You need to think about magnitude and come up with some sort of explanation—analytical variance or individual variation. Carin Huset, from the Public Health Laboratory, replied, saying that, for people who had low levels in 2008, even though the PFC levels rose a little in 2010, the changes were statistically insignificant, given lab variability. We’re talking about people who were at low levels before and were a little higher in 2010, but still well below the rest of the population. Jessica added, we think that particular population is basically at background levels. In short, Greg suggested, if you had low PFC levels in 2008 and did not donate blood, your results in 2010 will be about the same. Alan asked, Geary, do you expect this population to continue to have their levels decline? There has to be a bottom somewhere. Geary answered, what you’ll see is that the levels will get to a point where the half‐life gets muddy. This, he argued, is why it’s a good idea to repeat the PFC study in these participants now, before the PFC levels get down to the background levels in the population. 11
Geary added, given the data, what does this mean in terms of health risk limits and drinking water standards? Rita Messing answered that the relative source contribution for drinking water is currently 0.2 (20% of a person’s daily PFC consumption compared to other sources of exposure), and the Environmental Health division has no plans to change it, because we don’t have any information that would lead us to raise it. Biomonitoring Updates These reported on the current status of the 
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Pregnancy and Newborns Exposure Study Fond du Lac Community Biomonitoring Study As time was short, panel members moved on to the next item on the agenda. Minnesota National Children’s Study Newborn Mercury Project Proposal In light of the limited time, Jessica quickly reviewed a few slides for this proposal. The impetus, she said, was the response to findings that 10% of the newborns tested in MDH’s Mercury in Newborns in the Lake Superior Basin2 study had blood mercury levels that might harm cognitive development. The EHTB Advisory Panel had recommended looking at mercury in newborns in other regions of Minnesota. The goal of this recommendation is to learn whether babies in other areas of the state are being exposed to potentially harmful mercury levels during prenatal development. This project proposes that MDH’s EHTB Program would obtain matched cord blood, cord blood spot, maternal blood, and newborn blood spot samples that were collected from participants in the former National Children’s Study (NCS ) South Dakota State University (SDSU) Vanguard pilot study. It covers Brookings, SD, and three counties in western Minnesota. The MDH Public Health Laboratory would analyze all of the samples for total mercury content and analyze cord blood for lead, cadmium, and several forms of mercury. The project would address two Advisory Panel recommendations: 1. Because the lab method used in the Mercury in Newborns study is novel, do mercury levels in newborn blood spots accurately reflect those in more common measures of prenatal exposure to mercury, including cord blood, the basis for the EPA reference dose? 2. Is the observation that 10% of newborns tested had been exposed to potentially harmful levels of mercury unique to babies in the Lake Superior, or are these exposures also occurring in other parts of Minnesota? 2
Mercury in Newborns in the Lake Superior Basin, conducted by MDH’s Fish Consumption Advisory Program and funded by the Environmental Protection Agency (EPA), with additional support from MDH’s Environmental Health Tracking and Biomonitoring (EHTB) Program. 12
The aims of the project are to… 1. Measure and compare total mercury levels in specimens of maternal blood, cord blood, and newborn blood spots from mother‐baby pairs to see if these different measures of prenatal exposure to mercury give comparable results. 2. Measure and compare paired whole cord blood and cord blood spot mercury levels to learn whether levels measured in the blood spot accurately reflect those in the blood sample, to verify that the process of spotting the blood onto filter paper and extracting the sample does not introduce error into the measurement. This would validate the use of blood spots as a surrogate for whole blood. 3. Explore the extent of newborn exposure to mercury in Minnesota outside of the Lake Superior Basin to learn whether and where newborns in other regions of the state also have elevated mercury levels at birth. In addition, because the MDH Pregnancy and Newborns Exposure Study is also measuring lead and cadmium in cord blood, the SDSU NCS samples can serve as a comparison population from a very different area of Minnesota. She cautioned that the Vanguard cord blood collection method may have compromised the quality of the cord blood samples. If so, MDH may decide not to submit this proposal. Given that time was limited, panel members posed no questions, and the meeting moved on to new business. New business Bruce asked for panel members’ ideas or thoughts for new business. Geary asked whether the biomonitoring summit idea was still in the planning. Jean answered that, yes, it is in our plan, but it has been pushed farther out on the calendar. Aggie noted that a number of bills had been introduced in the legislature that would ban certain products or contaminants, such as triclosan, used in antibacterial soaps, or BPA (Bisphenol A), used in some plastics. Others have proposed an expansion of the Toxic Free Kids Act. Motion to adjourn Bruce requested a motion to adjourn. Pat McGovern offered the motion, Jill Heins‐Nesvold seconded the motion, and the meeting adjourned. 13