Minnesota Department of Health (MDH)
Environmental Health Tracking & Biomonitoring
Advisory Panel Meeting Summary
June 7, 2011
Advisory panel members – Present: Bruce Alexander, Al Bender, Greg Pratt,
David DeGroote, Tom Hawkinson, Cathi Lyman-Onkka, Geary Olsen, Cathy VillasHorns, Lisa Yost
Advisory panel members – Regrets:
Fred Anderson, Lisa Heins Nesvold, Pat McGovern
MDH officials and staff: Jeanne Ayers, MJ Levitt, B. Sevcik, J. Sample, P. Rode, J.
Nelson, J. Johnson, C. Stroebel, M. Manning, P. Swedenborg, C. Huset, B. Murdock
Welcome and Introductions
Bruce Alexander, chair, convened the meeting. Barbara Scott Murdock introduced David
DeGroote, a new member of the advisory panel.
New Content Areas for Tracking in Minnesota
MN EPHT staff presented two new content areas for environmental health tracking in
Minnesota:
Environmental tobacco smoke exposure (ETS), a content area selected through a
rigorous, multi-phase process: exploration, feasibility, recommendation, and
implementation.
Arsenic in private wells, a content area in the exploration phase.
ETS as a new content area
In the March 2011 Advisory Panel Meeting, EPHT staff Blair Sevcik and Jeannette
Sample presented details of a refined selection process for new Minnesota-specific
content areas, using ETS Exposure. Because the panel had no quorum that day, a motion
to adopt ETS as a new content area was postponed. The first item of business for the June
2011 meeting was thus to vote on recommending ETS as a new content area for the
tracking program.
Blair Sevcik briefly reviewed the rationale for choosing exposure to environmental
tobacco smoke (ETS), as measured by surveys of youths and adults, as a new content
area for environmental health tracking. The rationale for choosing this content area,
detailed in the June 7, 2011 Advisory Panel Meeting book, arises out of data-driven
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consideration of these factors:
Phase I: Exploration
Prevalence (significant proportion of population exposed)
Causality (evidence that exposure causes disease)
Actionability (prevention/control programs, policies, regulations, personal
actions, government public health objectives)
Public health impact (population attributable risk; costs of treatments)
Feasibility (data sources, legal authority, protection of private data)
Phase II: Feasibility
Detailed feasibility (data quality, continuity, timeliness, & comparability; ability
to aggregate data at different geographic areas; low cost to obtain data)
Phase III:
Recommendations
Emerging issues (exposure trends)
Potential for information building (unknown exposure level or health outcomes)
Interest from other MDH programs
Outside interest/public concern
Balance among content areas (hazard/exposure and disease)
Discussion of ETS as a new content area
Geary Olsen asked whether cigarette smoking was a content area for Minnesota tracking,
and why ETS exposure should precede cigarette smoking. Blair said that adult cigarette
smoking is well documented in other databases, such as the Behavioral Risk Factor
Surveillance Survey (BRFSS), and that we propose to use ETS exposure differently, as
ETS exposure among non-smokers. In short, Bruce said, ETS is an involuntary exposure,
rather than a voluntary behavioral risk factor. As no one raised other questions, Greg
Pratt moved that the panel recommend to the Commissioner that the ETS Exposure
content area be adopted and implemented as part of the Tracking program. Eight panel
members voted in favor, joining two panel members who had voted yes in absentia. One
panel member voted against, and one could not be reached for a vote. The motion
passed.
Arsenic as a new content area
Jeannette Sample reviewed the Phase I (Exploration) information collected for
considering arsenic in private wells in Minnesota as new content for environmental
tracking. She noted that, although it is unclear whether MDH will have the resources to
continue this content area after July 1, 2011, staff time is available for this work if normal
resources are available. The prevalence of potential exposure is high. One million
Minnesotans have private wells, and 10.5% of new wells tested for arsenic since August
2008 exceeded the 10µg/L standard; 56% showed no detectable arsenic (Level of
Detection = 2µg/L). Some groundwater in Minnesota has arsenic levels at high as
150µg/L.
Evidence for causality is clear. Arsenic’s health effects depend on its chemical form,
route of exposure, dose, half-life in the body, and on the exposed person’s health.
Arsenic is not only a carcinogen, but can also cause non-carcinogenic problems. Fatal
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arsenic doses are around 60,000 µg—far higher than natural concentrations in the
environment. But over time, daily consumption of lower levels of arsenic in drinking
water, combined with the arsenic found in foods, can produce harmful effects. Someone
who primarily drinks water containing 100µg/L over a lifetime can develop nervous
system disorders, diabetes, and some circulatory diseases. Levels below 100µg/L may
cause nervous system problems, skin problems, high blood pressure, and reduced
intelligence in children.
Actionability. Community water supply systems must meet the EPA drinking water
standard for arsenic (10µg/L). Minnesota has no enforceable standard for arsenic in
private wells, but beginning in 2008, MDH’s Well Management Program requires that all
new wells be tested for arsenic, and advises private well owners to reduce arsenic
exposure by drilling a new well, connecting to a community water system, or adding
water treatment systems with arsenic removal media. Reducing toxic arsenic exposure in
drinking water is among the Healthy People 2020 Environmental Health Objectives.
Publishing and mapping data for this new content area will support the creation of public
outreach programs, drilling and well-construction recommendations, and identify special
well construction areas. The MDH database does not catch older wells, but one MDH
study has measured how much well water people were drinking, and counties also gather
data on what people are drinking. Larry Souther said that MDH would like to get county
data so we could add data for older wells to the MDH database. Tom Hawkinson
commented that it might be good to find funding to get those data.
Larry reviewed the estimated public health impact of private wells with water containing
3µg/L arsenic. The estimated cancer risk is 3-10 additional lung or bladder cancers in a
population of 10,000. Health impacts of arsenic are found at levels below the EPA
standard of 10 µg/L. MCLs, but this standard is not based only on health impact but also
on the technical feasibility of removing the chemical from water, the analytical detection
limit, and the economic impact of regulating the contaminant.
Obtaining reliable well and arsenic data is feasible because the Minnesota Geological
Survey’s County Well Index, containing data on local wells’ depth, stratigraphy/geology,
and other factors, is joined with MDH’s Well Management database, which contains
arsenic data on all new wells drilled since 2008, though not on older wells. All of these
data are public.
Discussion of arsenic as a content area - Jeannette Sample, MDH EHTB, and Larry
Souther, MDH Environmental Health
In answering questions from Tom Hawkinson and Greg Pratt about arsenic’s geographic
distribution and whether arsenic in wells occurs naturally, Larry Souther explained that
arsenic’s occurrence and distribution is the result of glacial activity. In Minnesota,
arsenic occurs primarily in the Des Moines lobe in central and western Minnesota. This
layer of glacial till overlies an aquifer with high arsenic content; some aquifers at the
edge and below have lower levels. Although arsenic typically occurs in central and
western Minnesota, the CDC has found it throughout the state. Arsenic distribution in the
state is analogous to radon, Larry noted: one house may have arsenic in the well, and the
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next may not. Jeannette added that Jim Lundy, in Environmental Health, said that the
arsenic content in well water depends both on geography and on the depth of the well.
When asked whether it would it make sense to have maps of the geographic areas, she
said that the tracking program plans to produce maps and graphs later during the
feasibility phase, and that arsenic in private wells is simply a hazard indicator, rather than
a measure of population exposure.
MDH tells well drillers where they are likely to find higher and lower arsenic levels. If a
well is intended to provide public water, MDH can rule out using a high arsenic aquifer.
For private wells, MDH informs citizens about choosing the best spots to drill a well and
advises them on ways to mitigate arsenic contamination. Arsenic mitigation is expensive,
Larry noted; ion exchange usually does not work well, but reverse osmosis removes
arsenic effectively.
The estimate of cancer cases from drinking arsenic in well water led to lively discussion.
Greg Pratt asked whether the public health impact estimate was based on someone
drinking well water all the time. Jeanette answered that the number came from the
National Research Council, which reviewed and revised EPA estimates, and was based
on a standard risk assessment assumption, in which someone drinks 2 liters/day for a
lifetime. Greg Pratt clarified the estimate, saying that the estimate calculation is based on
a population of 10,000 that is exposed at that concentration. Moreover, Greg added, from
a population perspective in Minnesota, this estimated number is not significant compared
to overall cancer risk, but for exposed individuals, it is important. Lisa Yost agreed,
adding that anyone who uses the estimate must make sure that people understand the
denominator [so they realize that the denominator population is all exposed at that level].
Al agreed, noting that because the extrapolation of a health risk statement to cancer in a
community is always difficult, we must be careful how we articulate statements of risk.
Lisa added, if you find many wells at the 100 level (50 to 100 range), and it seems that
you might, it would be important to include this content in Tracking.
Geary Olsen asked about how a private well owner would test for arsenic. Who pays for
it? And whose data is it? What disclosure must an owner do if the water contains more
than 10µg/L? In short, are the data public or private? Larry answered that land owners
who hire a well tester pay for the tests themselves and own the data. If MDH tests the
well, the data become public data coming from the well. If the Department of
Agriculture tests it under certain programs, then it’s private data. Real estate sales do not
require disclosure of the sample results, but if someone sells the land, the seller must
disclose that wells are on the property, whether they are open or sealed. Often, the sale is
contingent on the buyer having samples tested and making sure that local water is
available.
At the end of the discussion, Bruce Alexander suggested that the team spend more time
on actionability of arsenic information in the Phase II planning.
Tracking Updates
Chuck Stroebel enhanced the Tracking Update in the panel book with a short report of
the May 26 public launch of the Minnesota Public Health Data Access (MNPH Data
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Access), an electronic gateway to Minnesota health and environment data. MNPH Data
Access is part of a national initiative led by the Centers for Disease Control and
Prevention (CDC) to close the information gap in what is known about the impact of
environmental hazards on public health.
Local public health professionals, the public, and others can use MNPH Data Access to
gather information about health and environment trends over time, and to query state and
county-level data in Minnesota about diseases and illnesses, such as asthma, cancer and
heart attacks. MNPH Data Access currently includes data on ten topics: air quality,
asthma, heart attacks, childhood lead poisoning, carbon monoxide poisoning,
reproductive outcomes, cancer, birth defects, drinking water quality, and chronic
obstructive pulmonary disease. This summer, MNPH Data Access will add new data and
tools, including GIS maps.
Minnesota, along with 22 states and New York City, receives CDC grant funding to
improve what is known about the environment's impact on public health by building state
tracking networks.
CDC Biomonitoring Communications Evaluation Project
Jean Johnson introduced Claudia Vousden, a communications researcher from CDC.
Claudia joined the meeting by phone to present findings from a case study of the
communications efforts in the PFC pilot biomonitoring study in Minnesota. The section
overview and study abstract in the Panel book outline the study’s purpose, background,
methods, results, and conclusions. Jean showed the PowerPoint during the
teleconferenced presentation.
Key stakeholders in the study and intended audiences for the communications plan,
included:
State legislators
Other state and local government agencies
Industry
Environmental advocacy groups
Members of affected communities
Study participants
Health care providers
The study’s initial communication goals were to:
Increase awareness of the study plan
Increase understanding of the study’s purpose and limitations
Tell people how to find more information
To engage people to
 Collaborate or offer suggestions
 Encourage healthcare providers to participate in information sessions
 Encourage community members to take part in the study
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The key messages were:
 The study’s purpose is to characterize exposure to PFCs in the population.
 The study won’t provide information about relationships between PFCs and
current or future health effects.
Additional communication needs included:
Demonstrating to legislators how the PFC study would meet constituents’ needs
and how biomonitoring can be useful to future policy decisions.
Engaging healthcare providers in interpreting biomonitoring results, making
advice about reducing or avoiding exposure available to patients, and addressing
questions about health effects.
Explaining to community members and environmental advocates why the study
 Excluded children
 Limited the number of study participants
 Selected a random sample from the study population
With the release of the pilot biomonitoring results, the communication goals focused,
first, on telling individuals and their communities their PFC levels and emphasizing that
the health implications of these levels are neither known nor understood. Other major
goals were to fulfill the legislative mandate and demonstrate the value of PFC
biomonitoring to public health.
Responses to the communication efforts were largely favorable: constituent calls to
legislators dropped significantly, and most study participants said they understood that
the results could not predict current or future health effects. But they—and their
legislators—were still unhappy with the lack of information about health effects.
Nevertheless, study participants valued the follow-up biomonitoring study and
communication.
The lessons for public health
Transparency, openness, and availability are key to facilitating communication, but
public health staff must reinforce the message that measurement of exposure is not a
health study at every step. Moreover, they must realize that communities expect follow
up and continuing communication beyond the study. One person said, ―I look forward to
communications from the State of Minnesota on any updates on the facts of what they
find. I feel some level of comfort knowing that the State has an eye on what’s
happening… and that level of concern…‖
Nevertheless, study participants still wonder whether exposure will affect their future
health, and struggled to understand the fact sheets and letters that accompanied their
results. As a study participant said about the letter, ―It’s very informative, but it doesn’t
tell me anything… it strikes me that these… are written by very well meaning people
who talk about this every day with other people who understand it… When they try to
write for the general public, they write like they are writing to their co-workers… and
that’s the problem.‖
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Biomonitoring Updates
PFCs and Lake Superior Mercury
The East Metro PFC Biomonitoring Follow up (PCF2) Project Update and the Lake
Superior Mercury in Newborns Project are described in the Panel book. In a further
update to the PFC2 study, Jessica Nelson explained that the current plan is to send
individual results in a letter to study participants this summer, before the next Advisory
Panel meeting. Participants will also receive their 2008 result and the NHANES results.
The other option is to wait until the next meeting, but people are anxious to know their
results. Al Bender asked whether the participants’ exposures are falling. Jean Johnson
replied that we don’t have the results from the lab yet. Jessica added that we can’t send
out the results until we are sure we have the right numbers. Panel members discussed
whether it would be good to use a study group geometric mean or median to give
participants a sense of where they stood in relation to the other participants. Geary Olsen
questioned what the MDH response might be if the press asked for more information.
The panel agreed that it would be best if the individual findings could be sent to the
participants with geometric means or other measures that would enable participants to
compare their results with the rest of the group, not just with NHANES.
Riverside Prenatal Biomonitoring Pilot Project
Jessica Nelson introduced Logan Spector, associate professor in Pediatric Epidemiology,
University of Minnesota, and then presented an overview of this pilot project, which was
ancillary to Logan’s larger research study. She briefly reviewed the rationale for the
study (measurement of cotinine, a biomarker for tobacco exposure, and environmental
phenols, used in plastics and personal care products), methods, and data collection, and
then presented preliminary summary results for cotinine, bisphenol A (BPA), and four
parabens.
Jessica reviewed the data in Tables 1-3 in the panel book. Table 1 describes the
characteristics of the pilot project population. The 66 participants were spread relatively
similarly across the income spectrum from 10 people (15%) with incomes below
$10,000/year, through 11 people in the $80,000 to $100,000/year income range and 16
participants in the highest range, >$100,000. Most participants were white (70%), while
the rest of the participants self-identified as non-white: black/African American (12%),
Hispanic/Latina (6%), Asian (6%), and Other (Eastern European, South African, Russian
Jewish, 5%).
Limits of detection (LOD) in cotinine. In reviewing the cotinine data, Jessica raised a
concern. The LOD for urinary cotinine in this group was 20 ng/ml, but other studies have
shown that non-smokers who live with a smoker have a lower geometric mean: 11.4
ng/mL. The pilot study results thus could identify 9 women who were active smokers,
using the MedTox definition (cotinine + nicotine > 200ng/mL), and one as either a light
smoker or as exposed to ETS. The other 56 women (85% of the group) had no detectable
urinary cotinine, but because the LOD was above mean ETS exposure levels, it is
possible that some non-smoking Riverside women were exposed to ETS.
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Overall, the percentage of the women who were classified as active smokers (14%) was
similar to the percentage found in other studies, the 1999-2006 NHANES (13%) and the
MN PRAMS survey (13.8%). Women with lower household incomes were more likely
to have detectable cotinine.
Table 2 shows results for the environmental phenols (BPA, methyl paraben (MePb),
propyl paraben (PrPb), and ethyl and butyl parabens), adjusted and not adjusted for
creatinine, a measure of urine dilution. Jessica also showed the panel a graphical way of
displaying the biomonitoring data based on research done at UC Berkeley and the Silent
Spring Institute on how to communicate results most effectively to participants in
community studies. Overall, despite the limitations of a small pilot study, BPA levels in
these women were similar to those found in NHANES and other studies that measured
BPA in pregnant women. Levels of MePb and PrPb found in this project were lower than
those found in NHANES. Table 4 in the Panel book lists findings from NHANES and
other studies.
Jessica then discussed differences in phenol levels by income and race/ethnicity. Table 3
displays the geometric means for BPA, MePb, and PrPb in three income ranges
(<$20,000/year, $20-80,000/year, >$80,000/year) and for non-white vs. white ethnicity.
She also showed bar graphs with these results.
These graphs illustrate higher BPA and MePb levels in low income women compared to
middle and higher income women, though the sample size was small and the results not
statistically significant. For MePb and PrPb, and particularly for MePb, levels were
higher in non-white women compared to white women. Jessica showed results from a
paper on parabens in NHANES 2003-2004 that found similar differences by
race/ethnicity, with Non-Hispanic Blacks having markedly higher levels than NonHispanic Whites. Mexican Americans also had higher levels than Non-Hispanic Whites.
Limitations of the study
Small size (66 pregnant women out of 122 who were told about the study)
Study did not meet its goal to recruit three racial/ethnic groups equally (initial
goal was to recruit 30 women in three ethnicities: African American, white,
Hispanic)
Women identified as ―non-white‖ in analysis by income and race/ethnicity
represented several different ethnic/racial backgrounds
Urine samples were self-collected at home (each woman provided one spot urine
sample), which increased the variability among women
Limits of detection (LOD) limited some conclusions that could be drawn, both for
cotinine and environmental phenols
Because of the chemicals’ short half-lives in the body, these analytes show
substantial variability
Questions for Advisory Panel Discussion
Do Panel members agree with the data analysis and interpretation presented? Are
additional analyses recommended?
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For the community factsheet, staff propose to present results for environmental
phenols by income and race/ethnicity, with appropriate caveats about the small
sample size. Given that the data are consistent with NHANES findings, do Panel
members consider this acceptable?
Do Panel members agree with the following approaches to data analysis?
1. For measurements <LOD, assign a value of LOD/2
2. Include participants with creatinine <20 mg/dL
Based on these pilot project findings, is further biomonitoring for environmental
phenols and cotinine recommended in this community (pregnant women)?
Should MDH continue biomonitoring work with this target population for a
different set of chemicals or a different specimen type?
Analysis of non-detect values. Jessica asked panel members for advice in handling non-
detection values in the environmental phenols data. Different studies use different
approaches in assigning a value to biomonitoring measurements below the limit of
detection (LOD). The most common approach, used by NHANES, is to use LOD/sqrt21;
other investigators use LOD/2. Because the LODs for BPA, propyl paraben, and butyl
paraben in this project are higher than in NHANES, the non-detect values assigned are
different. An example is BPA: the LOD in this project is 1µg/L; the LOD in NHANES is
0.4µg/L. The BPA geometric mean (GM) presented in Table 2 differs according to
which non-detect value is used: with LOD/sqrt2, GM = 2.5µg/g; with LOD/2, GM =
2.2µg/g; with the NHANES non-detect value, GM = 1.7µg/g. These preliminary analyses
used LOD/2.
Greg Pratt strongly recommended against censoring the data. Instead, he advocated using
all of the data, including data below LOD. He recommended a software program
(ProUCL) designed for low detect data and suggested using statistical tests and methods
for calculating central tendencies and best fit. He also suggested displaying the data with
box charts, which can indicate confidence limits, medians, quartiles, and other measures.
Al Bender suggested non-parametric tests for analyzing <LOD data (Kolmogorov–
Smirnov, Wilcoxon). Lisa Yost commented that the Minnesota Department of
Agriculture often has to use data that are < LOD. In this case, laboratory chemist Carin
Huset said, the lab did not report data below LOD for the phenols because the urine
samples were complex and difficult, and the signal-to-noise ratio in the samples was too
high.
Geary Olsen commented that the approach (LOD/2 or LOD/sqrt2) does not matter as
long as the difference is less than the LOD. Both simply use a constant.
Exclusion based on creatinine values. Because urine varies in concentration, laboratories
typically report the creatinine concentration in urine to allow analysts to adjust for
dilution. Creatinine, a normal constituent in urine, is a metabolic product of muscle
tissue. Some analyses exclude samples with creatinine values below a certain level, such
as 20mg/dL.2 The reasoning is that low creatinine values may inflate results because the
analyte is divided by creatinine for the creatinine-adjusted concentration. Results from
1
Square root of 2.
Wolff et al. Prenatal phenol and phthalate exposures and birth outcomes. Environ Health Perspect. 2008
Aug;116(8):1092-7.
2
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two participants, for example, have BPA <LOD, but have very different creatinineadjusted concentrations: Participant A (creatinine=10) = 5.0µg/g; participant B
(creatinine=116) = 0.43µg/g. Low creatinine values inflate the adjusted results.
The preliminary analyses did not exclude the five participants with creatinine <20 mg/dL,
and panel members agreed with that decision.
Presentation of results by income and race/ethnicity. The panel raised no objections to
reporting these results. Lisa and Bruce recommended that appropriate caveats be made
clear about the study’s small size, and about such factors as variations in the samples as a
result of the chemicals’ short half-life in the body.
Further biomonitoring for these or other compounds in this population. Given the high LOD
for cotinine, Bruce commented that he couldn’t see the point of testing for cotinine if the
lab can’t get a lower LOD; [with this LOD] it isn’t possible to detect exposure to ETS.
Greg said it is hard to draw conclusions because of the pilot study’s small sample size.
One would need to look at a larger sample size and lower LOD.
Geary Olsen said that one reason the project chose Riverside was to get minority
populations, yet the pilot project had trouble recruiting them. He asked whether a
different method might get better recruitment in that population. Logan Spector, PI of
the larger University of Minnesota Riverside Birth Study (RBS), explained that the pilot
was a sub-set of the main study population, and only women who were willing to have to
have future contact were sent information about the pilot project. He believes that if the
project had only asked women in a clinic for a spot urine sample, participation would
have been better.
Logan also addressed specific barriers to recruiting Somali women, one of the aims of the
larger RBS. These included a lack of adequate recruiting staff, the patriarchal culture, and
functional illiteracy (oral tradition).
Phase II Strategic Planning for an MDH Biomonitoring Program
Barbara reviewed current strategic planning for an MDH biomonitoring program. Phase
II builds on earlier Phase I planning that established the vision, framework, long-term
goal, and approach to biomonitoring. Phase II asks stakeholders to identify priorities for
study. Ultimately, it will lead to a plan for an ongoing biomonitoring program at MDH
that includes several specific and potentially fundable initial projects. Using a standard
set of questions, the biomonitoring planning team began meeting with key stakeholders in
April. Stakeholder meetings will continue this summer, depending on resources.
To date, the staff have met with faculty members at the University of Minnesota, local
advocacy groups, and environmental directors in the LPHA (Local Public Health
Association) and the LPHA’s Committee on Policy and Practice (Table 1). These
stakeholders have suggested target populations, priority chemical classes, sources for
funding, and health outcomes of interest (Table 2). Suggested potential funders,
collaborations, and partnerships are in Table 3.
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Table 1. Stakeholder Meetings
UMN Academic Stakeholders
Health & Environmental Advocacy Groups
LPHA
Environmental Health Sciences
Bruce Alexander
Pat McGovern
UMN Epidemiology
David Jacobs
Jose Suarez
Ruby Nguyen
Pediatric Epidemiology
Logan Spector
Healthy Legacy
Kathleen Schuler, IATP; Healthy Legacy
co-leader
Kim LaBo, Clean Water Action; Healthy
Legacy organizer
Julia Earl, Preventing Harm Minnesota;
Healthy Legacy member
Minnesota Center for Environmental Advocacy
Scott Strand, director
Allison Wolf, legislative liaison
Staff
Environmental health
directors
Committee on Policy &
Practice
Table 2. Stakeholder Suggestions
Target populations
Pregnant women, infants,
& children
Disadvantaged populations
Fish-eating populations
Rural/agricultural
populations
Men
Priority chemicals & data needs
Health outcomes
MN Chemicals
Endocrine disrupting chemicals
Pesticides
Heavy metals
MN reference data
NHANES-like data specific to MN
Assessment of exposure-reducing policies
Other data needs
MN data should be published in peerreviewed journals
Reproductive health
Developmental
disabilities
Neurobehavioral
disabilities (e.g.,
autism)
Allergies
Table 3. Potential Funders, Collaborations, and Partnerships
Potential funders
NIEHS (Partnerships for Environmental
Public Health, if available)
Foundations interested in health (e.g.,
Robert Wood Johnson Foundation)
CDC (if grants available)
Potential Collaborators or Partners
Research projects at UMN
Follow up or collaboration on existing studies
NCS (National Children’s Study sub-programs)
Food Safety Act (focuses on microbial contaminants;
could address pesticides)
TIDES (The Infant Development & Environment Study)
Health plans/foundations (BCBS, Health Partners Fdn)
Discussion
Criteria for identifying specific target populations
Greg Pratt suggested that the biomonitoring program focus on vulnerable & at risk
populations. To resolve the question of how to set vulnerability or risk factor criteria, he
suggested using cumulative levels and effects analysis, which attempts to take account of
all exposures and effects analysis of known hazards, plus the health status of the
community. The MPCA developed ways to assess the cumulative levels of
environmental hazards and their effects on communities at Representative Karen Clark’s
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behest. [The MPCA link to ―Cumulative Impacts Air Permitting in South Minneapolis
is:‖ http://www.pca.state.mn.us/index.php/air/air-permits-and-rules/air-permits-andforms/air-permits/cumulative-impacts-air-permitting-in-south-minneapolis.html. A
background document reviews hazard/exposure/health indicators for the community and
includes demographics and data sources at http://www.pca.state.mn.us/index.php/viewdocument.html?gid=14030 ].
Lisa Yost suggested that the criteria used in selecting new content areas for tracking offer
a good model, as they ask for data on such factors as prevalence, causality, actionability,
and detectability. Cathi Lyman-Onkka cautioned that the program should not decide to
investigate an area simply because it’s easy to obtain the data.
Geary Olsen raised a concern that people interested in biomonitoring may not appreciate
the relationship between absorption and clearance of chemicals in the body, particularly
clearance of chemicals at low-level concentrations in the body. He pointed out that an
individual or a specific population may have physiological characteristics
(pharmacokinetics, toxicokinetics) that affect clearance of certain chemicals. He
recommended looking at Matthew Longnecker’s work for a discussion of
pharmacokinetics. [Longnecker is in the biomarker epidemiology group at NIEHS].
Bruce noted that the choice of target populations will drive which partnerships and
collaborations are possible. Cathi advised MDH to look at questions that we identify as
being important to ask and to take available funding into account.
David DeGroote asked whether the Advisory Panel can take a more proactive approach
to choosing a population, rather than waiting for a community to push for it. Noting that
MDH identified three biomonitoring approaches (statewide population exposure tracking,
targeted population exposure tracking, and special investigations in response to public
concerns), he asked what the special investigations involved. Barbara said that the PFC
and arsenic pilot studies were examples, as legislators in those communities were very
aware of public concern about the exposures. David asked, which communities would
we choose in such situations? In the case of concern over pregnant mothers who eat fish
that contain high mercury levels, is there enough interest in the community to drive the
study, or do the Advisory Panel and MDH decide? Al commented that we have
significant areas of concern other than the fears of specific communities, but
acknowledged that, often, sociology drives the decision.
Legislative Update
Jean Johnson gave the legislative update. Although funding cuts and a government
shutdown loom, she said that the EHTB program is still planning for the future. One
possibility is that the legislature will fund the biomonitoring program only to finish the
PFC pilot, although we all recognize that there are other significant areas of concern.
The tracking program currently has CDC funding.
The meeting adjourned at 4:00 PM.
Finalized August 22, 2011
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