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2/10/2015 Advisory Panel Meeting Agenda
Environmental Health Tracking and Biomonitoring Program
1:00–4:00 pm at The Lung Association in Minnesota
490 Concordia Avenue, St. Paul, MN
Time
Agenda Items
Presenters
Description/expected outcome
1:00
Welcome & Introductions
Patricia McGovern,
Chair
Panel members & audience are invited to introduce
themselves.
1:05
Blood Spot Project Results
Update
Jessica Nelson and
Addis Teshome
Discussion item:
NCS
Jessica and Addis will present updates of MDH mercury
biomonitoring of newborns and pregnant women using
blood spots from the Riverside Newborn Mercury
Project, The Infant Development and Environment
Study, and the National Children’s Study in Minnesota.
Discussion
Question for the panel:
Riverside
TIDES
1:20
Does the panel have any recommendations for
additional analyses, data interpretation, or next steps?
1:35
Biomonitoring Updates
Carin Huset
Lab update
MDH Public Health Lab Research Scientist Carin Huset
will present an update on the laboratory analysis of
PFCs. Other updates are provided in written form. Panel
members are invited to ask questions and comment on
all updates.
PFCs in East Metro farms
Sustaining MN Biomonitoring
MN FEET
1:45
2:00
East Metro Community
Cancer Report
Discussion
Information item:
Kenneth Adams,
Minnesota Cancer
Surveillance
System
Discussion Item:
Kenneth will present the most recent update to the East
Metro Community Cancer Report and discuss challenges
of small area cancer analysis.
Questions for the panel:
Given the challenges of small area analyses, what
strategies would you suggest for describing the patterns
of cancer occurrence with community members?
In plain language, what key messages are most
important?
2:25
Refreshments
1
Time
Agenda Items
Presenters
Description/expected outcome
2:40
Tracking Updates
Matthew
Montesano
Information item:
New Interactive Asthma
Hospitalizations Map
New Reports
New Portal Content
Great Lakes Tribal Tracking
Project
Matthew will demonstrate the new interactive maps.
Other updates on new reports, new portal content,
Great Lakes Tribal Tracking Project, Health Impact
Assessment and Data Utilization, and Cancer Risk
Communications Toolkit are provided in written form.
Panel members are invited to ask questions and
comment on all updates.
Health Impact Assess-ment &
Data Utilization
Cancer Risk Communications
Toolkit
2:50
3:00
East Metro PFC3
Biomonitoring Project
Christina Rosebush
Discussion item:
Christina will present demographic data from the East
Metro PFC3 Biomonitoring Project and the analysis plan.
Discussion
Questions for the panel:
Given that we only have a small number of renters, how
should renters data be analyzed?
Does the panel have other comments/
recommendations for the analysis plan?
3:10
3:20
Ongoing PFC study in the East Jean Johnson
Metro
Discussion item:
Discussion
Questions for the panel:
Jean will present staff recommendations for the panel
for PFC biomonitoring in FY15-16.
Given that results of PFC3 are not available, does the
panel recommend any additional PFC biomonitoring in
the East Metro in the future?
In another community?
3:40
Future Meeting Topics
Pat McGovern
Discussion item:
Panel members are invited to recommend topics for
exploration and discussion at future meetings.
3:50
New Business
3:55
Audience Questions
4:00
Motion to adjourn
Note to audience: The panel asks that audience members hold comments and questions on discussion items
until the end of the meeting, when the chair will invite questions from the audience. Audience members are
asked to identify themselves when they speak, and to please record their names and affiliations on the list at
the sign-in table. Meetings are recorded on audiotape.
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Table of Contents
Section Overview: Blood Spot Project Results and Update .......................................................... 4
Section Overview: Biomonitoring Updates ....................................................................................... 7
Section Overview: East Metro Community Cancer Report........................................................ 12
Section Overview: Tracking Updates ............................................................................................... 36
Section Overview: East Metro PFC3 Biomonitoring Project ..................................................... 39
Section Overview: Ongoing PFC study in the East Metro .......................................................... 43
Section Overview: Other Information.............................................................................................. 47
3
Section Overview: Blood Spot Project Results Update
Jessica Nelson and Addis Teshome, epidemiologists with MN Biomonitoring, will present
updates on three MN Biomonitoring projects that are using available specimens from other
studies in Minnesota to investigate mercury levels in newborns and pregnant women.
Laboratory analysis of newborn blood spots and maternal specimens was conducted by the
MDH Public Health Laboratory. Addis will present her recent analysis and preliminary results of
newborn blood spot data collected as part of the Riverside Newborn Mercury Project (Riverside
Birth Study, Logan Spector, PI). Jessica will present an update on the most recent progress in
two other collaborative research projects: The Infant Development and Environment Study
(Ruby Nyugen, PI), and the National Children’s Study with Pat McGovern, PI.
Each of these projects use dried newborn blood spots collected for the purposes of research
with participant consent. These projects do not use specimens collected for the MDH newborn
screening program.
Question for the panel:
•
Does the panel have any recommendations for additional analyses, data interpretation,
or next steps?
4
Blood Spot Project Results Update
Riverside Newborn Mercury Project: Preliminary Results
Introduction. The Riverside Newborn Mercury Project is a collaboration with University of
Minnesota Investigator Dr. Logan Spector to analyze total mercury in newborn blood spots
collected from participants in the University of Minnesota’s Riverside Birth Study (RBS). The
project will help MN Biomonitoring to characterize newborn mercury exposures in different
Minnesota communities.
Methods. The Riverside Birth Study was conducted by the University of Minnesota in 2008-2010
at Fairview Riverside Hospital. The study was designed to measure the correlation between
specific analytes in neonatal infant specimens and maternal exposures during pregnancy. RBS
participants were pregnant women receiving prenatal care and planning to deliver at the
Fairview Riverside Hospital in Minneapolis. The hospital and clinic are centrally located in
Minneapolis-St. Paul and draw patients from a large and diverse urban area. Women completed
questionnaires and donated specimens, including a heel stick bloodspot collected at birth. In
total, 426 women participated, though not everyone gave all samples and data requested.
In 2013, MN Biomonitoring received permission to analyze total mercury in remaining RBS
bloodspots. The MDH Public Health Laboratory received 160 newborn bloodspot samples from
the RBS. Using the same method from previous MDH projects, two 3-mm punches were taken
from the bloodspot card, mercury was extracted from the punches during an overnight
digestion, and the resulting solution was analyzed via inductively coupled plasma mass
spectrometry (ICP-MS). The method detection limit (MDL) was 0.7 µg/L. Mercury was detected
in blanks taken from the bloodspot filter paper of 11 samples (7%). Results presented below are
adjusted for this mercury contamination of the filter paper.
Preliminary results. Table 1 shows the distribution of mercury concentrations in 160 RBS
newborn bloodspot samples. Mercury was detected in 61% of samples, and the geometric
mean was 0.9 µg/L. Only 2 samples (or 1.2%) had concentrations above 5.8 µg/L, the level
corresponding to the U.S. EPA’s Reference Dose for methyl mercury.
Table 1. Distribution of bloodspot mercury concentrations (µg/L), n=160
Total
Non-detects
GM
n (%)
(95% CI)*
63 (39%)
0.9
(0.8-1.0)
Median
95th
percentile
Minimum
Maximum
> 5.8 µg/L
n (%)
0.8
2.6
ND
9.1
2 (1.2%)
* For non-detect values, we substituted the MDL/sqrt2.
Next steps. RBS will provide MDH with de-identified demographic information on the mother
(race/ethnicity, income, age, birthplace) and responses to fish‐related diet questions from the
survey (frequency of consumption of canned tuna, fried fish/fish sticks, other fish). We will
determine whether mercury levels differ by these factors, along with babies’ birth season. We
will also explore whether it is appropriate to combine RBS bloodspot results with those from
the Pregnancy and Newborns Exposure Study, which was done in collaboration with the
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University of Minnesota’s TIDES study and drew women from the same clinic population. When
all analyses are complete, we will post results on the web site.
Pregnancy and Newborns Exposure Study (TIDES)
This project, a collaboration with the University of Minnesota’s The Infant Development and
Environment Study (TIDES), compared mercury levels in a small number of paired cord blood
and newborn bloodspot samples. Using results from the split cord blood/bloodspot
experiments that the MDH Public health Laboratory performed (presented at the October 2014
Advisory Panel meeting), we have revised our manuscript on the relationship between mercury
levels in paired newborn bloodspot and cord blood samples and will resubmit it soon. Cord
blood samples with mercury levels >1 µg/L will also be analyzed for speciated mercury. Once all
analyses are complete, we will summarize the results and post them on the web site.
NCS Newborn Mercury Biomarker Validation Supplemental Methodological Study
This project is measuring mercury and other metals in matched cord blood, newborn
bloodspot, and maternal blood samples from National Children’s Study (NCS) participants
enrolled by South Dakota State University’s Original Vanguard Center. This Center included
participants from Brookings, SD, and Yellow Medicine, Pipestone, and Lincoln Counties, MN.
The MDH Public Health Laboratory received 83 pairs of matched newborn bloodspot and cord
blood samples, and maternal blood samples at birth from 49 of these mothers.
Lab analyses on all samples are complete and data analysis and interpretation are underway.
Some of the mercury results appear to be aberrant, and we are concerned that there may have
been some type of contamination during the sample collection process. We are working to get
more detailed information on NCS protocols and investigate possible sources of contamination.
We are also waiting to receive data from the NCS on mothers’ demographic and other exposure
information.
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Section Overview: Biomonitoring Updates
Carin Huset will present an update on the MDH Public Health Laboratory processing of
specimens for measuring PFCs. Other updates are provided in written form. Panel members are
invited to ask questions and comment on all updates.
Information Item Updates:
•
•
•
PFCs in East Metro farms follow-up
Sustaining MN Biomonitoring
Minnesota Family Environmental Exposure Tracking (MN FEET)
7
Biomonitoring Updates
MDH Public Health Laboratory PFCs Processing
The sample preparation method used for the quantitative analysis of the perfluorinated
analytes PFBA, PFPeA, PFHxA, PFOA, PFNA, PFBS, PFHxS, and PFOS in human serum has been
modified from the method used in 2008 and 2010-11. Previously, the method employed solid
phase extraction (SPE) to prepare samples for LC/MS/MS analysis and was based on one
published by CDC (Kuklenyik, ES&T, 2004). During validation of this SPE method to include PFNA
(an analyte not measured by MDH PHL in previous studies), we had problems with blanks,
reproducibility, robustness, and chromatographic consistency. We attempted to troubleshoot
these problems with the SPE method, but eventually came to the conclusion that we could
rework the method and make improvements to throughput, use a smaller sample volume, and
solve the problems mentioned above. The new method uses acetonitrile to precipitate proteins
from the serum, followed by centrifugation and concentration steps to prepare samples for
analysis. The method is similar to one reported in Flaherty in 2005 in the Journal of
Chromatography B. Through this method, we use a smaller volume of serum (400 µL vs 1 mL)
and have faster throughput by using 96 well plates. In addition, we have validated this method
using quality control pools, which is more in line with how CDC performs their analysis, and is
how our Laboratory Response Network program quantifies agents in biospecimens.
Kuklenyik, Reich, Tully, Needham, Calafat, Automated Solid Phase Extraction and Measurement of
Perfluorinated Organic Acids and Amides in Human Serum and Milk, Environmental Science and
Technology, 2004, 38, 3698-3704.
Flaherty, Connolly, Decker, Kennedy, Ellefson, Reagen, Szostek, Quantitative Determination of Perfluorooctanoic Acid in Serum and Plasma by Liquid Chromatography Tandem Mass Spectrometry, Journal of
Chromatography B, Analytical Technologies in the Biomedical and Life Sciences, 2005, 819(2), 3329-338
PFCs in East Metro Farms
At the October Advisory Panel meeting, it was recommended that MDH staff follow-up with Dr.
Matt Simcik to determine how best to reach out to members of the Hmong community farmers
in the East Metro area. The purpose of the communication would be to listen to their concerns,
share what is known about health risks and the gaps in our knowledge, and, if appropriate, to
discuss protective strategies that would be acceptable to the community. Panel members also
wanted MDH to explore further the sources of PFCs in these agricultural soils, and the possible
role of biosolids.
Since the meeting, Jean Johnson has followed up with Matt by phone on his study progress with
the community and is planning a meeting to discuss a communication strategy for MDH. Jean
also spoke with Washington County epidemiologist and panel member, Fred Anderson. Fred
reported that they have had no communication from members of the Hmong farming
community expressing concerns about PFC exposure.
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Sustaining MN Biomonitoring
MN Biomonitoring staff continue to make progress with implementing portions of the Action
Plan for Sustaining Minnesota Biomonitoring that was developed in August 2014. Meetings
with the Minnesota Pollution Control Agency to discuss base funding levels for
MNFEET/mercury and PFC biomonitoring projects under the Environmental Risks Initiative in
state fiscal years 2016-17 were held in late fall. Funding levels will be determined in the months
ahead but are still subject to changes at this time. Staff have made progress in building
relationships with potential collaborators at the Health Partners Institute for Education and
Research and at the Great Lakes Intertribal Epidemiology Center. For building public awareness,
staff provided presentations or updates with community organizations, Healthy Legacy, and
Minnesota Conservation, and are scheduled to present to the MPCA Board in the spring. Jessica
Nelson was also interviewed by the MDH Commissioner for a taping of his television show, A
Public Health Journal, on the topic of biomonitoring at MDH. Plans are underway for developing
a Legislative Report or factsheet, and for sharing progress with Legislators.
Minnesota Family Environmental Exposure Tracking (MN FEET)
Background
Minnesota Family Environmental Exposure Tracking (MN FEET) will measure mercury, lead, and
cadmium in 600 pregnant women and newborns from diverse Minnesota populations. MN FEET
will investigate whether there are disparities in exposures in some Minnesota communities.
And, as an add-on study, we will continue our assessment of whether testing mercury in
newborn bloodspots is a good way to measure newborn exposures. The project will include
Hmong, Latina, Somali, and White women who are getting prenatal care at certain
HealthPartners and West Side Community Health Services clinics and plan to deliver their
babies at Regions Hospital (and possibly Abbott Northwestern Hospital, in the future). This
write-up provides an update since the October 2014 Advisory Panel meeting.
Current status
IRB submission and timeline. We submitted applications to the MDH and HealthPartners
Institutional Review Boards (IRB) in January. These included the protocol and project materials
(project overview, phone script, consent form, survey, results return letters, etc.). Researchers
from the SoLaHmo Partnership for Health and Wellness (part of West Side Community Health
Services) reviewed and gave feedback on materials for usability, effectiveness, and cultural
appropriateness. They also pilot tested the recruitment materials with Hmong, Latina, and
Somali women of childbearing age. We expect that the project will receive expedited review
from both IRBs and plan to launch recruitment in March.
Planning for recruitment and sample collection. Contracts are in place with SoLaHmo and nearly
in place with the HealthPartners Institute for Education and Research. These groups will recruit
women from their clinic patient lists via letter and phone and conduct a phone survey. They will
share participant information and survey responses with us once women have consented. We
are finalizing the logistics of sample collection (cord blood and maternal urine), storage, and
transport with Regions Hospital. We are in discussions with Abbott Northwestern Hospital
about their participation in the project.
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Current activities. Once IRB feedback is received and any changes made, we will have materials
translated into Hmong, Spanish, and Somali. We are now planning for the launch of the project,
including developing plans for outreach to communities and providers, and for interviewer
training.
Newborn bloodspot sub-study. We will submit the newborn bloodspot testing portion of the
project as a separate sub-study to the IRB. As discussed at the October 2014 Advisory Panel
meeting, the plan is now to ask for consent to test the leftover newborn screening bloodspot
after birth, and to do so only for a subset of participants (n=~300) with detectable levels of
mercury in their baby’s cord blood.
Study methods - communication of results to participants
The IRB submission included our protocol for reporting results to participants and ensuring that
follow-up is available for women or babies with elevated chemical levels. We will mail individual
results to all participants as soon as possible after receiving results from the MDH PHL, and
within two to three months of receipt of their samples. The letter participants receive will
depend on their results and how they compare with MDH action levels (Table 1), which are
based on the best available information for establishing safe levels of exposure in pregnant
women and newborns.
Women whose results do not exceed the action levels will receive a “not elevated” results
letter that includes their and their babies’ results. The letter will inform them that all results
were below action levels and they do not need to take steps to lower exposures. Participants
will also receive a set of brochures with information about ways to prevent exposure.
Women with at least one result above action levels will receive a different notification letter.
Women with lead results >5 µg/dL will be told they will be contacted for follow-up by their local
public health agency or MDH’s Blood Lead Program. MN FEET investigators will promptly report
the result with individual identifiers to the MDH Blood Lead Program in accordance with
Minnesota law. Follow-up will involve providing exposure reduction information, encouraging
her to get another lead test, and/or arranging a home visit from a public health professional
who will assess lead exposure sources.
For mercury and cadmium results above action levels, letters will inform women that their
results were above the action levels and they should take steps to reduce exposures. They will
be advised to share results with their medical provider. Women will also be told that they will
soon receive a phone call from the study physician. During this phone call (with translation
available if needed), the study physician will review results and information from the letter and
ask follow-up questions about possible sources of exposure. She will stress that it is important
to find and reduce the sources of exposure, and describe the resources available to help
women do this.
To use in prioritizing phone calls, MDH has set Tier 1 and Tier 2 action levels for mercury and
cadmium results (Table 1). Women with results above Tier 2 levels will be called first by the
study physician, who will tell them MDH is concerned that their or their baby’s health may be
affected.
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In collaboration with HealthPartners and West Side clinics, we will provide education and
information to providers to help in responding to patient concerns.
Table 1. MN FEET action levels
Tier 1 action level
Tier 2 action level
Blood lead
>5 µg/dL
N/A
Blood mercury
>5.8 µg/L
>20 µg/L
Blood cadmium
>1.7 µg/L
>5 µg/L
Urinary mercury
>20 µg/L
>20 µg/L
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Section Overview: East Metro Community Cancer Report
In this section, MDH presents two documents for review and discussion.
1. Issues in Interpreting Community Cancer Rates to Address Environmental Concerns
This excerpt is taken from the original report published in 2007, “Cancer Incidence in
Washington and Dakota County”. The report presented available cancer data at the
county and zipcode level in response to concerns heard from the community exposed to
PFC contamination in drinking water.
2. Draft MCSS Report: Cancer Incidence in Washington and Dakota County, 2015 Update
Kenneth Adams, Epidemiologist with the Minnesota Cancer Surveillance System, will present
the draft report results updating East Metro cancer incidence data analysis for Washington and
Dakota Counties, and specific zipcodes affected by PFC drinking water contamination. He will
also present some of the challenges of small area cancer analyses.
Some tables of zipcode level analyses have been omitted from the Panel materials for brevity,
but are included in the full report. Panel members are welcome to request the full report when
it is completed.
It will also be posted on the MDH website and be available to the public.
Panel members are asked to review and comment on the recent report findings shown here.
Communicating these results with affected communities presents unique challenges for MDH
staff that are described in these documents. Advice and recommendations are requested to
address the following questions.
Questions for the panel:
•
•
Given the challenges of small area analyses, what strategies would you suggest for
describing the patterns of cancer occurrence with community members?
In plain language, what key messages are most important?
12
East Metro Community Cancer Report
Issues in Interpreting Community Cancer Rates to Address Environmental Concerns
Excerpt from the original report: Cancer Incidence in Washington and Dakota County, 2007
The Minnesota Cancer Surveillance System (MCSS) is frequently asked to address concerns
about a known or perceived excess of cancer in a community, or to address concerns about
cancer risks from a known or suspected environmental exposure. These concerns often reflect
some common misunderstandings about the frequency and causes of cancer, as well as how
cancer risks are identified. Some of these issues are briefly discussed below.
Some Important Facts About Cancer
•
•
•
•
Cancer is not a single disease; it is a group of more than 100 different diseases. Different
types of cancer have differing rates of occurrence, causes, and chances for survival. The
development of cancer is a multi-step process, starting with genetic changes in cells,
followed by cell division and growth over time. The time from genetic change to the
development of cancer, known as the “latency period,” is usually decades long, often 30
years or longer. This means that many cancers diagnosed today are due to exposures
and genetic changes that occurred in cells a long time ago.
Cancer occurs in individuals of all ages and the risk of cancer at any particular age varies
greatly depending on the type of cancer. For example, the median age at diagnosis for
thyroid cancer is the mid-40s for both males and female, while the median age for
prostate cancer is 69. In general, however, overall cancer rates rise sharply with
increasing age and approximately 60% of cancers occur in individuals 65 years of age
and older. Because people are living longer, the risk of developing cancer is increasing.
Cancer is much more common than many people realize. Cancer can be viewed as either
a rare disease or a very common disease. If addressing the yearly rate of a specific
cancer in a young adult, it would be considered a rare disease. For example, the annual
rate of lung cancer among men aged 20-34 is less than one case per 100,000. However,
the risk of developing any form of cancer over an entire lifetime gives quite a different
perspective. Not including the most common forms of skin cancer, the current estimate
of the average lifetime risk of developing some form of cancer is approximately 47
percent. In other words, on average, between four and five people out of ten will be
diagnosed with some type of cancer during their lifetimes. Figure 21 shows the lifetime
risks for specific cancers for males and for females. An individual’s own personal risk of
cancer can of course be much higher or much lower than these averages, depending on
personal risk factors.
Since cancer is not a single disease, it does not have a single cause. There are a variety
of causes (better known as “risk factors”). These factors act over many years to increase
an individual’s chance of developing cancer. They can include such things as age, race,
gender, occupational exposures, diet, obesity, radiation, smoking, and reproductive
history. For many cancers, such as breast and colon cancer, genetics play a role. This
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means that a family history can be a risk factor for some types of cancers. It is not
unusual for several cases to occur within a family.
• While we have no control over risk factors such as age, race, and family history, much of
our cancer risk is related to factors that we can control. Such “lifestyle factors” include:
cigarette smoking; heavy drinking; and eating foods that have excess calories, high fat,
and low vegetable intake. It has been estimated that approximately 30% of total cancer
deaths in the U.S. are related to smoking, while another 30% are related to diet and
obesity. Other lifestyle factors that increase risk have to do with occupation,
reproductive patterns, sexual behavior, and sunlight exposure. However, even when no
modifiable risk factors are known that can reduce the risk of developing a cancer,
screening and early diagnosis may prevent or reduce the risk of death.
• It is often stated that most cancers are “environmental” in origin and thus potentially
avoidable. Environment in this context does not refer only to ambient environmental
exposures such as air and water pollutants, but also means everything that is not
genetically inherited. It includes all aspects of a person’s life and behavior, such as diet,
smoking, occupational history, exposure to sunlight, reproductive history, viruses,
medical history, alcohol use, and exposure to pollutants. Genetic factors, personal
behaviors, and life-style factors, as well as chemical and occupational exposures have
been identified as affecting our risk of developing cancer. It is very likely that a
combination of factors is important.
Limitations of Community Cancer Rates
Cancer risks are identified through epidemiologic studies of human populations or through
laboratory animal studies. Epidemiologic studies can provide the only direct evidence of cancer
risks in humans. However, with rare exceptions (such as mesothelioma in an asbestos exposed
population), community-level cancer statistics are not a useful tool for either confirming or
refuting the existence of a cancer risk from an environmental contaminant. A higher than
expected rate does not mean that some environmental pollutant is the cause of this higher rate
and a normal or lower than expected rate does not mean that there is no concern regarding
any particular pollutant. Some of the reasons are discussed below.
Cancer Latency and the Residential Mobility of the Population
Community cancer rates are defined by place of residence at the time of diagnosis. As
previously described, cancer is the end result of a long biological process in the body that takes
decades to develop. In assessing cancer risks, exposures that are of greatest interest are those
that occurred several decades prior to diagnosis of cancer. This leads to two problems. One
issue is that in communities with contaminants in drinking water, for example, it is frequently
not known when contamination first occurred. Thus, even for a life-long resident, it may not be
possible to determine exposures prior to the time of detection of the contamination. Another
issue is residential mobility. Due to the extreme mobility of our population, many members of a
community have not resided in the same house (and possibly in the same community) five
years ago. For example, based on 2000 census data for Washington County, over 40 percent of
the population was living in a different house than they lived in 1995. In Oakdale, 56.8% of the
residents over age 5 were living in the same house in both 1995 and 2000. For Woodbury only
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44.1% lived in the same house 5 years ago and approximately 83% of the residents of
Woodbury moved into their current (as of 2000) home between 1990 and 2000. Consequently,
present cancer rates in a particular community represent a vast array of personal histories at
various residences, many of which are outside their current community.
Occupational versus Community Settings
It was recognized over 200 years ago that workers in certain occupations experienced higher
risks of some cancers. Since then, a variety of occupations and workplace exposures have been
causally linked to certain cancers. Indeed, most known human carcinogens have been identified
through epidemiologic studies of occupational groups. Cancer risks are more likely to be
detected in occupational cohorts compared to community settings for at least three important
reasons: (1) occupational exposures are generally very much greater than community
exposures, making it easier to detect a risk; (2) it is frequently possible to estimate past
exposures in a workplace, using industrial hygiene data, job histories, and other data; and (3) it
is frequently possible in a workplace setting to identify a population of past or present
employees who were likely to have been exposed (or not exposed) to a particular agent.
Some of the specific chemicals known to increase the risk of cancer among exposed workers
include asbestos (lung cancer, mesothelioma), benzene (leukemia), arsenic compounds (lung,
skin cancer), aromatic amines (bladder cancer), bis[choloromethyl] ether (lung cancer),
chromium compounds (lung cancer), nickel dusts (cancer of lung, nasal sinuses), and vinyl
chloride (liver cancer). It has been estimated that past asbestos exposures account for about 5
percent of the lung cancer deaths in men in the U.S. A number of industrial processes are also
linked to increased cancer risks. It has been estimated that occupational exposures overall
account for about 5 percent of total cancer deaths.
Cancer Risks Detectable by Epidemiologic Studies vs. Regulatory Standards
Although epidemiologic studies of human populations provide the most direct evidence of
cancer risks, such studies cannot be relied upon exclusively to identify these risks. Even with the
best available methods, epidemiologic studies cannot usually identify excess cancer risks that
are less than about 10 percent above background (although a number of extremely large multicity studies of air pollution have been able to detect increases in adverse health effects of
several percent). Good epidemiologic data are not even available for the vast majority of
compounds, both man-made and naturally occurring.
Because many chemicals have been labeled and regulated as “carcinogens” based only on
extrapolation from animal studies, it is important to recognize the probable magnitude of the
risks from typical environmental exposures. Regulatory standards are commonly set at levels in
which lifetime exposure (70 years) to some agent is expected to result in a cancer risk of no
more than one in 100,000. Or in other words, there would be no more than one additional
cancer in 100,000 lifetimes of exposure. Such a level of risk, if real, would be approximately
10,000 times too small to be observed or verified by epidemiologic studies. If the entire
population of Minnesota had lifetime exposure to a chemical at the level of exposure
equivalent to this regulatory target there would be an expected 42 additional cancers due to
this exposure within the background of 1.9 million cancers occurring for other reasons. Another
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way of explaining this is that there would be, on average, less than one excess cancer per year,
out of the approximately 23,000 cancers due to all causes in Minnesota. Because cancer
ultimately affects so many people, almost everyone will have neighbors, friends, or relatives
with cancer. Epidemiologic or public health surveillance data such as that from the MCSS
cannot detect rates at these levels. Therefore, the finding of “normal” patterns of cancer
occurrence in a community conveys little information about specific cancer risks to the
community as defined by current regulatory standards.
Lack of Information on Other Known Cancer Risk Factors
When a situation occurs in which there is a confirmed cancer increase in a population, it is very
difficult to control for, or rule out, other risk factors that may have been the primary reason for
the cancer increase. For example, exposure to asbestos is a risk factor for lung cancer.
However, 85-90% of lung cancer occurrence is due to smoking. Consequently, smoking would
need to be accounted for in determining whether an elevated lung cancer rate is related to
asbestos exposure. In order to find what may have been the cause of the increased cancers, an
epidemiologic study is needed, involving detailed comparisons between hundreds of patients
recently diagnosed with a specific type of cancer and an equal number of individuals who have
worked in a particular occupation or industry (or who can otherwise be defined as having some
shared characteristic or exposure) over some time period. Typically, thousands of workers are
identified. The occurrence of various diseases over many years or decades in this group is then
compared to the occurrence in the general population. Even in such large-scale studies,
differences in exposure and other factors between the groups are often very modest, and it is
difficult to rule out random variation and various study biases. Consequently, no single
epidemiologic study provides definitive answers; multiple studies in different populations with
consistent findings are generally needed to establish causality.
Variability of Cancer Rates in Small Populations
Annual rates of specific cancers are generally low, and are subject to much variability. This is
true at the county level and the variability is even more pronounced when analyses are
attempted at the sub county (city or zip code) level. Interpretation of cancer incidence at the
county and community levels must take into account the statistical unreliability of rates from
year to year. An apparent excess during one period of time may be followed by an apparent
deficit the next time period. Geographic variations are also likely to occur from one population
(county or city) to another.
An example of this variability at the county-level is shown by the following analysis undertaken
for a previous MCSS report. Using county lines as geographic boundaries, an analysis was
conducted to identify excesses of cancer cases for each of 85 types of cancer, for either sex, for
any year between 1988 and 1994 in any of the 87 Minnesota counties. This analysis creates
more than 100,000 possibilities for identifying an unusual cancer rate. Nearly 10,000 of these
rates exceeded the statewide average by at least twofold. Roughly 1,500 of these rates reached
the usual criteria of statistical significance.
A typical cancer registry tracks 80 different kinds of cancer. Using these facts, statisticians at the
California Department of Health services have calculated that there is a 98% chance that a given
19
community will show a statistically significant but totally random elevation in the rate of at
least one type of cancer. Thus, even when a statistical test shows there is a “statistically
significant” difference between the observed and the expected number of cases, in many
instances the significant difference is due to chance and not to a real hazard in the community.
That is, unusual rates both high and low are to be expected when examining cancer rates
between communities or over time. High rates, low rates, and nominal rates moving
dynamically over time and region comprise the normal background of cancer incidence in our
community. The variability of cancer incidence over time and region requires that great care be
taken when attempting to conclude that any specific elevation or deficit is a result of a specific
factor.
20
MCSS Report: Cancer Incidence in Washington and Dakota
County, 2015 Update:
Background and Purpose of This Report
This report provides a data update of the information earlier presented in the 2007 MCSS
(MCSS) report, “Cancer Incidence in Dakota and Washington Counties, MCSS Epidemiology
Report 2007:1.”
The 2007 report presented information on cancer incidence (occurrence of newly diagnosed
cancer) among residents of Dakota and Washington Counties. The report was intended to
address cancer concerns in communities located east of the Minneapolis-St. Paul metropolitan
area (the East Metro). The 2007 report analyzed occurrence of new cancer in Washington and
Dakota counties diagnosed between the years 1988-2002, and cancer in eight east metro
communities diagnosed between the years 1996-2004. The eight east metro communities were
represented by zip code areas.
This update builds on the previous report by providing similar analyses for more recent years. It
repeats the analyses presented in Tables 2, 4, 7-15 of the 2007 report, using the same time
periods presented in the 2007 report (i.e., cancer diagnoses in the two counties from 19882002, and cancer diagnoses eight east metro communities [zip code areas] from 1996-2004).
Since the time of the 2007 report, the MCSS has collected information on additional persons
diagnosed with cancer during these time periods, so the results differ slightly from those
presented in the 2007 report. The report also includes analyses for more recent years; 20032012 for the county-level analyses and 2005-2012 for the community level analyses. This makes
it possible to compare results across time periods.
The methods used to analyze the information and interpret the results are similar to those
described in the 2007 report. This update supplements but does not replicate the entire 2007
report. Readers are referred to the earlier report for more detailed descriptions of the
motivation for the study, the methods used, and strengths and limitations of the analyses. The
strengths and limitations of the previous analysis apply equally to this report.
The main purpose of both the 2007 report and this data update is to quantify the extent of
cancer occurrence in the east metro area (i.e., the number of new cancers occurring over time)
and to compare these observed numbers with the numbers that would be expected based on
cancer rates in the state of Minnesota as a whole, and in the greater Twin Cities area. The term
“expected number of cancers” is described in the section below, “Methods in brief”.
This update adds to the earlier 2007 evaluation by comparing cancer occurrence over earlier
and more recent time periods. This is useful because the frequency of cancer occurrence (i.e.
cancer rate) tends to vary substantially over time within small geographic areas, especially for
cancer types that are relatively uncommon. Statistical evidence that cancer occurrence is
consistently higher or lower than expected over an extended period of time in a geographic
16
area adds weight to the evidence that the underlying incidence of cancer is actually higher or
lower, whether the reason is understood or not. By contrast, differences in cancer occurrence
that do not persist over time are considered likely to reflect random fluctuations. In this report,
MCSS staff evaluates the consistency with which cancer occurrence is higher or lower than
expected.
This reflects the unfortunate fact that cancer is very common in Minnesota and nationally.
Although the causes of most cancer are poorly understood, cancer risk can be reduced to some
extent by screening, weight control, exercise, and a healthy diet. More research into causes and
prevention of cancer, and stepped-up public health efforts to prevent cancer are urgently
needed.
Methods in brief
The methodology used in this report is standard public health surveillance practice. The
methodology allows assessment of whether the number of cancer cases occurring is unusually
high or low. Cancer case information was obtained from the MCSS (state cancer registry) for
two time periods, 1988-2002 and 2003-2012, for Washington and Dakota counties. Similar
information was obtained for the time periods 1996-2004 and 2005-2012 for eight east metro
communities (Tables 7-14) and for the eight communities combined. The 1988-2002 time
period for county-level analysis and 1994-2004 time period for community-level analysis were
used for consistency with the 2007 report. For the current update, MCSS staff evaluated similar
cancer types as analyzed in the 2007 report. Staff estimated cancer statistics for each
combination of geographic area, gender, and cancer type.
The statistics include the observed number of newly diagnosed cancers in each geographic area,
the number of cancers that would be expected based on comparison with larger reference
populations, the ratio of observed and expected numbers of cancers, and the 95th percent
confidence interval surrounding the ratio. These statistics are described briefly below, and are
discussed more completely in the 2007 report.
The observed number of cancers is a direct count of incident cases from the MCSS (Minnesota’s
central, population-based cancer registry). The expected number of cancer cases is a
statistically-modeled estimate or projection. The expected number of cases is an estimate
intended to represent the background cancer rate in the population, and is based on the cancer
rate in the reference population. Two reference populations were used in this study; the state
of Minnesota was used as the reference population for county-level analyses, and the seven
county metropolitan area of Minneapolis-Saint Paul was used as the reference population for
community-level analyses.
The initial step in evaluating whether the number of cancer cases occurring is unusually high or
low is to determine the statistical significance of the result (i.e., the observation or analysis).
Underlying the statistical methodology is an estimate of cancer rates, and these rates are
estimated with uncertainty. A test of statistical significance (assuming a 0.05 significance level)
identifies those results that would likely occur less than 5% of the time, if the underlying rate in
17
the community of interest were identical to that of the larger reference population. We used
statistical significance to identify instances in which the observed number of cancers differed
from the number expected. Statistically significant results are designated with an asterisk in the
results tables. However, a single statistical test of significance by itself cannot be used to judge
whether the observation is truly unusual or a result of the vagaries of statistical evaluation. This
is only one of several analyses and judgments are required to come to this conclusion, but it is a
widely used first screening test in this process.
Other statistics reported in the tables are the observed-to-expected ratio and the 95%
confidence intervals around this ratio. The observed-to-expected ratio is used to gauge the
proportional difference between the observed and expected numbers For example, a ratio of
1.5 suggests that 1.5 times as many cancer cases were observed than expected (50% more).
However, direct comparison of the magnitude of the observed and expected counts and their
difference provides a more concrete understanding of the results. Confidence intervals are
statistical estimates of the range of plausible values for the observed-to-expected ratio
Findings
The text of this section reports all positive findings; that is the combinations of sex, county or
community, and cancer type in which the observed number of cancers was either higher or
lower than expected, using statistical significance as the main criterion. The majority of findings
were null, but for the most part these are not called out in the text (see tables for complete
results). As noted in the “Methods in brief” an evaluation of whether cancer occurrence is
unusual begins with statistical significance but also considers of the number of cancer cases
involved (population size), effect size, consistency of results over time, and biological
plausibility.
County-level analyses
Washington County
Among males residing in Washington County from 1988-2002, the number of cancers observed
was lower than the number expected for all cancers combined and cancers of the lung and
larynx (Table 1a). From 2003-2012 the observed number of cancers was higher than expected
for melanoma, prostate cancer, leukemia, and mesothelioma; and lower than expected for oral,
pancreatic, and lung cancers. Observed numbers of lung cancers were lower than expected in
both time periods.
Among females residing in Washington County in 1988-2002, the number of cancer cases
observed was lower than expected for Hodgkin lymphoma and leukemia (Table 1b). From 20032012 the number of cancers observed was higher than expected for all cancers combined,
melanoma, and breast cancer; and lower than expected for cancer of the small intestine. The
number of cancers observed in Washington County females did not differ from expected in
both time periods for any of these cancers.
For the time period 2003-2012 the number of melanomas of the skin observed was higher than
expected in both genders.
18
Dakota County
Among males residing in Dakota County in 1998-2002, the observed number of cancers did not
differ from expected for any of the cancers evaluated (Table 2a). From 2003-2012, the numbers
of cancers observed for all types combined, esophagus, colorectal and pancreas were lower
than expected.
Among Dakota County females in 1998-2002, the observed number of cancers was higher than
expected for all cancers combined, liver cancer, and breast cancer (Table 2b). In 2013-2012, the
observed number of breast cancer cases was again higher than expected, was higher for
mesothelioma, and was lower for bladder cancer. The number of observed cancers did not
differ from expected in both genders in either time period (Tables 2a, 2b).
Summary of county-level analyses
Combining all cancers, the analyses found small differences between the numbers of cancers
observed and the numbers expected; but no clear pattern was evident across county, gender,
and time period. (For the 1988-2002 time period, all cancer types combined; the number of
cancers observed was slightly lower than expected in Washington County males and slightly
higher than expected in Dakota County females. For the 2013 time period combining all time
periods the number of cancers observed was slightly higher than expected in Washington
County females, and slightly lower than expected in Dakota County males.)
Of the 96 analyses in males (2 counties, 2 time periods, 24 cancer types), the number of cancers
observed was lower than expected in 10, higher than expected in 4, and did not differ from
expected in 82. Of the 104 analyses in females (2 counties, 2 time periods, 26 cancer types), the
number of cancers observed was lower than expected in 5, higher than expected in 8, and did
not differ from expected in 91.
The most consistent relationship in the county-level analyses was higher than expected
numbers of breast cancers in females (Washington County 2013-2012, Dakota County 19882002 and 2013-2012). Differences between observed and expected numbers of three other
cancers were also observed with some consistency: In 2003-2012, the number of melanomas of
the skin observed was higher than expected in both genders in Washington County. Also in
2003-2012, observed numbers of mesothelioma, a rare cancer, were higher than expected in
Washington County males and Dakota County females. Finally, in Washington County males,
observed numbers of lung cancer were lower than expected in both 1988-2002 and 2003-2012.
Community-level analyses
MCSS staff compared observed numbers of cancers with the numbers expected within each of
eight east metro communities (defined by zip codes, Tables 3-10), and the eight communities
combined (Table 11). As noted in the 2007 report, analyses within the east metro communities
should be interpreted cautiously because the statistical methodology used by MCSS
epidemiologists provides less valid and reliable results when applied to small populations. For
perspective, in 2010 the eight communities ranged in population from 3,418 to 43,281,
compared with Washington and Dakota County populations of 238,136 and 398,552
respectively, according to the US Census. Validity here refers to the ability to correctly
19
determine whether the number of cancer cases observed is truly unusual. Validity issues are
compounded for cancers that are rare, and when multiple comparisons are made (i.e., when
many cancers and geographic areas are evaluated). Both situations are present in this report.
The section “Cancer Incidence for Geographic Regions within Dakota and Washington Counties”
from the 2007 report provides useful background for understanding these issues.
Zip code 55128 (Oakdale)
Among males residing in Oakdale in 1996-2004, the number of colorectal cancers observed was
higher than expected (Table 3a). In 2005-2012, the number of all cancers combined was higher
than expected, and the observed-to-expected ratio for colorectal cancer appeared higher than
expected but did not reach statistical significance. In combination, these results suggest
persistently elevated colorectal cancer incidence among men in Oakdale.
Among females in Oakdale in 1996-2004, the number of lung cancers observed was higher than
expected (Table 3b). In 2005-2012 the number of observed cancers was higher than expected
for all cancers combined, breast cancer, and thyroid cancer.
Zip code 55042 (Lake Elmo)
Among male residents of Lake Elmo in 1996-2004, the number of oral cancers observed was
higher than expected (Table 4a). In 2005-2012, the number of prostate cancers was higher than
expected; and the number of lung cancers was lower than expected.
Among Lake Elmo females, the number of observed cancers did not differ from the number
expected for any of the cancers evaluated in either 1996-2004 or 2005-2012 (Table 4b).
Zip code 55016 (Cottage Grove)
Among Cottage Grove residents, the number of observed cancers did not differ from the
number expected in either gender in either 1996-2004 or 2005-2012 (Table 5a, 5b).
Zip code 55125 and 55129 (Woodbury)
Among male residents residing in Woodbury in 1996-2004, the number of lung cancers
observed was lower than expected (Table 6a). The observed number of oral cancer cases
appeared lower than expected, but the result missed statistical significance. In 2005-2012, the
number of prostate cancers observed was higher than expected and the numbers of observed
oral-, colorectal-, pancreatic-, lung cancer, and lymphoma were lower than expected. These
results in combination suggest that incidence of oral and lung cancers among Woodbury men
are persistently lower than expected.
Among female Woodbury residents in 1996-2004, the number of observed cancers did not
differ from the number expected for any of the cancers evaluated (Table 6b). In 2005-2102, the
number of lymphomas was higher than expected.
Zip code 55055 (Newport)
Among male residents of Newport in 1996-2004, the number of observed cancers did not differ
from the number expected for any of the cancers evaluated (Table 7a). In 2005-2012, the
number of lymphomas was higher than expected.
20
Among female residents of Newport in 1996-2004, the number of observed cancers did not
differ from the number expected for any of the cancers evaluated (Table 7b). In 2005-2012, the
numbers of all cancers combined and kidney cancer were higher than expected.
Zip code 55071 (Saint Paul Park)
Among male residents of Saint Paul Park in 1996-2004, the number of observed all cancer types
combined was higher than expected (Table 8a). In 2005-2012, the number of cancers did not
differ from the number expected for any of the cancers evaluated.
Among female residents of Saint Paul Park in 1996-2004, the number of observed cancers was
higher than expected for liver cancer (Table 8b). In 2005-2012, the number of lung cancers
observed was higher than expected.
Zip code 55033 (Hastings)
Among male residents of Hastings in 1996-2004, the number of cancers observed did not differ
from the number expected for any of the cancers evaluated (Table 9a). In 2005-2012, the
number of prostate cancers was lower than expected.
Among female residents of Hastings in 1996-2004, the number of breast cancers observed was
lower than the number expected (Table 9b). In 2005-2012, the number of pancreatic and
ovarian cancers was lower than expected.
Zip code 55075 (South Saint Paul)
Among male residents of South Saint Paul, the observed numbers of all cancer types combined
and lung cancer appeared higher than expected in 1996-2004, although neither result reached
statistical significance (Table 10a). In 2005-2012, the number observed for all cancer types
combined and for lung cancer were higher than expected.
Among female residents of South Saint Paul, the observed numbers of all cancer types
combined and lung cancer were higher than expected in both time periods (Table 10b). In
combination, these results suggest persistently high incidence of cancers of all types and lung
cancer in both males and females.
Eight east metro communities combined
Among male residents of the eight east metro communities combined in 1996-2004, the
number of observed cancers did not differ from the number expected for any of the cancers
evaluated (Table 11a). In 2005-2012, the numbers of oral and pancreatic cancers were lower
than expected.
Among female residents of the eight east metro communities combined in 1996-2004, the
number of observed colorectal cancers was lower than expected in1996-2004 (Table 11b). In
2005-2012, the observed number of uterine cancers was higher than expected.
Summary of community-level analyses
MCSS staff performed a total of 234 community-level analyses in males (13 cancer types, 9
geographic areas, and 2 time periods). In 19 (8.1%) of these analyses, the observed number of
cancers was either lower than or higher than expected, based on a statistically significant p21
value. A total of 270 community-level analyses were performed in females (15 cancer types, 9
geographic areas, and 2 time periods). The observed number of cancers was either lower than
or higher than expected in 19 (7.0%) of the analyses.
The results of tables 3-11 were distilled into a single table presenting only positive results; that
is the combinations of sex, community, and cancer type in which the observed number of
cancers was either higher or lower than expected in at least one of the two time periods (Table
12).
In most instances, (evaluating a combination of cancer type and geographic area) differences in
observed and expected numbers of cancers in one time period were not evident in the other
time period (Table 13). For example, in St. Paul Park females 1996-2004, the observed-toexpected ratio for liver cancer was 7.0 (based on 3 cases), whereas in 2012 there were no liver
cancer cases.
However, there were also exceptions in which an observed numbers of cancers were
consistently high (or low) in both 1994-2004 and 2005-2012, or the result was statistically
significant in one time period and borderline significant in the other. The most notable was for
lung cancer in South Saint Paul, where the observed numbers of lung cancer and cancer of all
types was higher than expected (statistically significant or borderline significant) in both men
and women, in both the 1996-2004 and 2005-2012 time periods.
22
Table 1a. Observed and Expected New Cancers and Standardized Incidence Ratios for Male Residents of Washington County
Cancer type
1988-2002
Cases
Observed
Cases
Expected
2003-2012
Cases
Observed
Cases
Expected
all types
4339
5368
child
1.2
0.8
0.9
78
18
colorectal
Lower
95% CI
Upper
95% CI
4553
Observed/
Expected
Ratio
1.0
Lower
95% CI
Upper
95% CI
5322
Observed/
Expected
Ratio
1.0
0.9
1.0
1.0
1.0
73
78
0.9
0.7
73
65
1.1
0.9
1.4
oral
156
160
1.0
1.1
137
177
0.8
0.6
0.9
esophagus
51
59
0.6
1.1
84
83
1.0
0.8
1.2
stomach
65
0.8
0.6
1.1
64
76
0.8
0.7
1.1
small intestine
21
0.8
0.5
1.3
23
28
0.8
0.5
1.2
473
505
0.9
0.9
1.0
473
483
1.0
0.9
1.1
liver
35
38
0.9
0.6
1.3
59
74
0.8
0.6
1.0
pancreas
86
82
1.1
0.8
1.3
93
120
0.8
0.6
0.9
larynx
43
61
0.7
0.5
0.9
*
46
56
0.8
0.6
1.1
lung
546
601
0.9
0.8
1.0
*
510
611
0.8
0.8
0.9
soft tissue
39
36
1.1
0.8
1.5
49
39
1.3
0.9
1.7
melanoma
187
175
1.1
0.9
1.2
321
282
1.1
1.0
1.3
*
prostate
1314
1372
1.0
0.9
1.0
1783
1660
1.1
1.0
1.1
*
testes
96
88
1.1
0.9
1.3
69
76
0.9
0.7
1.2
bladder
272
281
1.0
0.9
1.1
363
343
1.1
1.0
1.2
kidney
154
151
1.0
0.9
1.2
226
223
1.0
0.9
1.2
brain
90
87
1.0
0.8
1.3
84
81
1.0
0.8
1.3
thyroid
35
40
0.9
0.6
1.2
61
64
0.9
0.7
1.2
Hodgkin lymphoma
47
43
1.1
0.8
1.4
28
38
0.7
0.5
1.1
non-Hodgkin lymphoma
196
218
0.9
0.8
1.0
281
266
1.1
0.9
1.2
multiple myeloma
46
51
0.9
0.7
1.2
84
72
1.2
0.9
1.4
leukemia
163
160
1.0
0.9
1.2
240
202
1.2
1.0
1.3
*
mesothelioma
23
17
1.3
0.8
2.0
29
18
1.6
1.1
2.3
*
*
*
*
*
23
Table 1b. Observed and Expected New Cancers and Standardized Incidence Ratios for Female Residents of Washington County
1988-2002
2003-2012
Cancer type
Cases
Observed
Cases
Expected
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
4241
Observed/
Expected
Ratio
1.0
Lower
95% CI
Upper
95% CI
4899
Observed/
Expected
Ratio
1.0
all types
4205
1.0
1.0
5076
1.0
1.1
child
55
65
0.9
0.6
1.1
46
54
0.9
0.6
1.1
oral
64
72
0.9
0.7
1.1
72
84
0.9
0.7
1.1
esophagus
11
16
0.7
0.3
1.2
24
24
1.0
0.7
1.5
stomach
34
40
0.9
0.6
1.2
34
40
0.8
0.6
1.2
small intestine
14
16
0.9
0.5
1.4
12
24
0.5
0.3
0.9
colorectal
425
450
0.9
0.9
1.0
419
437
1.0
0.9
1.1
liver
15
17
0.9
0.5
1.5
31
31
1.0
0.7
1.4
pancreas
61
67
0.9
0.7
1.2
104
100
1.0
0.9
1.3
larynx
10
13
0.7
0.4
1.4
10
14
0.7
0.3
1.3
lung
413
415
1.0
0.9
1.1
570
553
1.0
0.9
1.1
soft tissue
32
29
1.1
0.8
1.6
30
33
0.9
0.6
1.3
melanoma
157
162
1.0
0.8
1.1
322
254
1.3
1.1
1.4
*
breast
1527
1466
1.0
1.0
1.1
1704
1552
1.1
1.0
1.2
*
cervix
112
106
1.1
0.9
1.3
71
73
1.0
0.8
1.2
uterus
273
277
1.0
0.9
1.1
349
346
1.0
0.9
1.1
ovary
155
161
1.0
0.8
1.1
144
144
1.0
0.8
1.2
bladder
100
93
1.1
0.9
1.3
111
110
1.0
0.8
1.2
kidney
75
81
0.9
0.7
1.2
117
123
1.0
0.8
1.1
brain
60
62
1.0
0.7
1.2
53
59
0.9
0.7
1.2
thyroid
100
110
0.9
0.7
1.1
220
194
1.1
1.0
1.3
Hodgkin lymphoma
22
33
0.7
0.4
1.0
36
29
1.3
0.9
1.7
non-Hodgkin lymphoma
187
172
1.1
0.9
1.3
206
209
1.0
0.9
1.1
multiple myeloma
44
39
1.1
0.8
1.5
43
51
0.8
0.6
1.1
leukemia
85
111
0.8
0.6
0.9
145
130
1.1
0.9
1.3
mesothelioma
3
5
0.7
0.1
1.9
2
6
0.3
0.0
1.2
*
*
*
*
24
Table 2a. Observed and Expected New Cancers and Standardized Incidence Ratios for Male Residents of Dakota County
1988-2002
2003-2012
Cancer type
Cases
Observed
Cases
Expected
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
7701
Observed/
Expected
Ratio
1.0
Lower
95% CI
Upper
95% CI
8408
Observed/
Expected
Ratio
1.0
all types
7628
1.0
1.0
8227
1.0
1.0
child
149
139
1.1
0.9
1.3
107
110
1.0
0.8
1.2
oral
269
267
1.0
0.9
1.1
292
281
1.0
0.9
1.2
esophagus
98
98
1.0
0.8
1.2
98
131
0.7
0.6
0.9
stomach
116
131
0.9
0.7
1.1
115
120
1.0
0.8
1.2
small intestine
36
36
1.0
0.7
1.4
46
44
1.0
0.8
1.4
colorectal
836
849
1.0
0.9
1.1
710
765
0.9
0.9
1.0
liver
57
64
0.9
0.7
1.2
126
116
1.1
0.9
1.3
pancreas
123
136
0.9
0.8
1.1
158
189
0.8
0.7
1.0
larynx
83
101
0.8
0.7
1.0
85
88
1.0
0.8
1.2
lung
950
1005
0.9
0.9
1.0
920
958
1.0
0.9
1.0
soft tissue
62
63
1.0
0.8
1.3
63
63
1.0
0.8
1.3
melanoma
329
297
1.1
1.0
1.2
436
451
1.0
0.9
1.1
prostate
2305
2311
1.0
1.0
1.0
2511
2582
1.0
0.9
1.0
testes
183
165
1.1
1.0
1.3
147
134
1.1
0.9
1.3
bladder
479
475
1.0
0.9
1.1
554
541
1.0
0.9
1.1
kidney
237
252
0.9
0.8
1.1
385
353
1.1
1.0
1.2
brain
153
151
1.0
0.9
1.2
119
133
0.9
0.7
1.1
thyroid
76
70
1.1
0.9
1.4
107
105
1.0
0.8
1.2
Hodgkin lymphoma
87
78
1.1
0.9
1.4
69
64
1.1
0.8
1.4
non-Hodgkin lymphoma
374
369
1.0
0.9
1.1
420
424
1.0
0.9
1.1
multiple myeloma
97
86
1.1
0.9
1.4
102
113
0.9
0.7
1.1
leukemia
287
275
1.0
0.9
1.2
330
324
1.0
0.9
1.1
mesothelioma
36
29
1.2
0.9
1.7
32
29
1.1
0.8
1.6
*
*
*
*
25
Table 2b. Observed and Expected New Cancers and Standardized Incidence Ratios for Female Residents of Dakota County
Cancer type
1988-2002
Cases
Observed
Cases
Expected
all types
7597
child
Lower
95% CI
Upper
95% CI
7395
Observed/
Expected
Ratio
1.0
1.0
1.1
130
116
1.1
0.9
1.3
oral
133
126
1.1
0.9
esophagus
29
29
1.0
stomach
69
70
small intestine
35
colorectal
2003-2012
Cases
Observed
Cases
Expected
8155
Lower
95% CI
Upper
95% CI
8090
Observed/
Expected
Ratio
1.0
1.0
1.0
103
91
1.1
0.9
1.4
1.3
125
139
0.9
0.8
1.1
0.7
1.5
32
39
0.8
0.6
1.2
1.0
0.8
1.2
61
67
0.9
0.7
1.2
28
1.2
0.9
1.7
45
39
1.2
0.8
1.5
737
788
0.9
0.9
1.0
750
722
1.0
1.0
1.1
liver
43
30
1.4
1.0
1.9
46
51
0.9
0.7
1.2
pancreas
120
117
1.0
0.9
1.2
149
164
0.9
0.8
1.1
larynx
29
23
1.3
0.8
1.8
17
23
0.7
0.4
1.2
lung
758
718
1.1
1.0
1.1
901
906
1.0
0.9
1.1
soft tissue
42
51
0.8
0.6
1.1
52
56
0.9
0.7
1.2
melanoma
303
290
1.0
0.9
1.2
417
427
1.0
0.9
1.1
breast
2659
2528
1.1
1.0
1.1
2698
2550
1.1
1.0
1.1
cervix
168
190
0.9
0.8
1.0
111
123
0.9
0.7
1.1
uterus
454
476
1.0
0.9
1.0
570
565
1.0
0.9
1.1
ovary
298
279
1.1
1.0
1.2
235
238
1.0
0.9
1.1
bladder
156
162
1.0
0.8
1.1
153
180
0.8
0.7
1.0
kidney
159
141
1.1
1.0
1.3
185
202
0.9
0.8
1.1
brain
114
110
1.0
0.9
1.2
100
99
1.0
0.8
1.2
thyroid
218
201
1.1
0.9
1.2
316
330
1.0
0.9
1.1
Hodgkin lymphoma
74
63
1.2
0.9
1.5
41
50
0.8
0.6
1.1
Non-Hodgkin lymphoma
313
302
1.0
0.9
1.2
373
346
1.1
1.0
1.2
multiple myeloma
72
68
1.1
0.8
1.3
78
84
0.9
0.7
1.2
leukemia
197
196
1.0
0.9
1.2
240
217
1.1
1.0
1.3
mesothelioma
7
8
0.9
0.4
1.8
18
10
1.7
1.0
2.8
*
*
*
*
*
*
26
Table 3a. Observed/Expected Cancer Incidence, Males, Zip 55128 (Oakdale)
1996-2004
2005-2012
Cancer type
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
all types
481
459
1.0
1.0
1.1
591
531
1.1
1.0
1.2
oral
9
14
0.6
0.3
1.2
14
17
0.8
0.4
1.4
colorectal
57
43
1.3
1.0
1.7
55
43
1.3
1.0
1.7
liver
8
5
1.6
0.7
3.1
8
9
0.9
0.4
1.8
pancreas
6
9
0.7
0.3
1.5
8
12
0.7
0.3
1.3
lung
59
56
1.0
0.8
1.3
57
57
1.0
0.8
1.3
prostate
135
140
1.0
0.8
1.1
182
158
1.2
1.0
1.3
bladder
28
29
1.0
0.6
1.4
39
33
1.2
0.8
1.6
kidney
20
16
1.3
0.8
2.0
23
21
1.1
0.7
1.6
brain
9
7
1.2
0.6
2.3
11
7
1.5
0.7
2.6
thyroid
5
4
1.2
0.4
2.8
5
6
0.8
0.3
1.9
lymphoma
28
31
0.9
0.6
1.3
44
36
1.2
0.9
1.6
leukemia
18
16
1.1
0.6
1.7
24
21
1.1
0.7
1.7
*
*
27
Table 3b. Observed/Expected Cancer Incidence, Females, Zip 55128 (Oakdale)
1996-2004
Cancer type
all types
oral
colorectal
liver
pancreas
lung
breast
uterus
ovary
bladder
kidney
brain
thyroid
lymphoma
leukemia
2005-2012
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
484
482
1.0
0.9
1.1
625
559
1.1
1.0
1.2
7
8
0.9
0.3
1.8
9
9
1.0
0.4
1.8
34
44
0.8
0.5
1.1
48
46
1.0
0.8
1.4
1
2
0.5
0.0
2.5
8
4
1.9
0.8
3.8
7
8
0.8
0.3
1.7
11
11
1.0
0.5
1.7
73
55
1.3
1.0
1.7
73
64
1.1
0.9
1.4
163
162
1.0
0.9
1.2
208
172
1.2
1.1
1.4
28
30
0.9
0.6
1.4
34
36
0.9
0.6
1.3
18
16
1.1
0.7
1.8
13
16
0.8
0.4
1.4
13
11
1.2
0.6
2.0
18
12
1.5
0.9
2.3
5
9
0.5
0.2
1.3
12
12
1.0
0.5
1.7
6
5
1.1
0.4
2.4
5
6
0.9
0.3
2.0
16
13
1.3
0.7
2.0
31
20
1.5
1.0
2.2
25
27
0.9
0.6
1.3
30
32
1.0
0.6
1.4
12
11
1.1
0.6
1.9
19
15
1.3
0.8
2.0
*
*
*
*
28
Table 10a. Observed/Expected Cancer Incidence, Males, Zip 55075 (South St Paul)
1996-2004
Cancer type
Cases
Observed
2005-2012
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
468
433
1.1
1.0
1.2
451
396
1.1
1.0
1.2 *
oral
10
12
0.8
0.4
1.5
11
13
0.9
0.4
1.6
colorectal
43
42
1.0
0.7
1.4
30
33
0.9
0.6
1.3
liver
5
5
1.1
0.4
2.6
12
6
1.9
1.0
3.4
pancreas
8
8
1.0
0.4
1.9
10
9
1.1
0.5
2.0
70
55
1.3
1.0
1.6
70
44
1.6
1.3
2.0 *
146
135
1.1
0.9
1.3
112
115
1.0
0.8
1.2
bladder
26
30
0.9
0.6
1.3
32
26
1.2
0.8
1.7
kidney
17
14
1.2
0.7
2.0
15
15
1.0
0.5
1.6
brain
11
6
1.8
0.9
3.2
7
5
1.3
0.5
2.7
7
3
2.1
0.8
4.4
3
5
0.7
0.1
1.9
lymphoma
34
29
1.2
0.8
1.7
29
28
1.1
0.7
1.5
leukemia
17
15
1.1
0.6
1.8
17
16
1.1
0.6
1.7
all types
lung
prostate
thyroid
29
Table 10b. Observed/Expected Cancer Incidence, Females, Zip 55075 (South St Paul)
1996-2004
Cancer type
all types
oral
colorectal
liver
pancreas
lung
breast
uterus
ovary
bladder
kidney
brain
thyroid
lymphoma
leukemia
2005-2012
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
487
432
1.1
1.0
1.2
463
403
1.1
1.0
1.3
7
7
1.0
0.4
2.0
4
7
0.6
0.2
1.5
41
44
0.9
0.7
1.3
38
34
1.1
0.8
1.5
3
2
1.4
0.3
4.2
2
3
0.7
0.1
2.4
10
8
1.2
0.6
2.2
6
9
0.7
0.3
1.5
70
52
1.3
1.0
1.7
73
47
1.6
1.2
2.0
149
137
1.1
0.9
1.3
125
120
1.0
0.9
1.2
28
25
1.1
0.7
1.6
28
25
1.1
0.7
1.6
13
14
1.0
0.5
1.6
9
11
0.8
0.4
1.5
12
11
1.1
0.6
1.9
6
9
0.6
0.2
1.4
13
9
1.5
0.8
2.6
18
9
2.0
1.2
3.2
9
5
1.9
0.9
3.6
2
4
0.5
0.1
1.7
13
10
1.3
0.7
2.3
12
14
0.9
0.4
1.5
25
26
1.0
0.6
1.4
27
23
1.2
0.8
1.7
9
11
0.8
0.4
1.5
15
12
1.3
0.7
2.1
*
*
*
*
*
30
Table 11a. Observed/Expected Cancer Incidence, Males, Combined zip codes for Eight Communities
1996-2004
Cancer type
all types
oral
colorectal
liver
pancreas
lung
prostate
bladder
kidney
brain
thyroid
lymphoma
leukemia
2005-2012
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
2841
2842
1.0
1.0
1.0
3535
3540
1.0
1.0
1.0
71
89
0.8
0.6
1.0
81
114
0.7
0.6
0.9
281
265
1.1
0.9
1.2
269
288
0.9
0.8
1.1
30
32
0.9
0.6
1.3
53
57
0.9
0.7
1.2
59
53
1.1
0.8
1.4
57
80
0.7
0.5
0.9
339
348
1.0
0.9
1.1
381
380
1.0
0.9
1.1
841
870
1.0
0.9
1.0
1063
1044
1.0
1.0
1.1
189
180
1.1
0.9
1.2
234
219
1.1
0.9
1.2
105
97
1.1
0.9
1.3
157
143
1.1
0.9
1.3
52
46
1.1
0.8
1.5
57
53
1.1
0.8
1.4
24
26
0.9
0.6
1.4
43
43
1.0
0.7
1.3
196
193
1.0
0.9
1.2
233
246
0.9
0.8
1.1
101
101
1.0
0.8
1.2
156
143
1.1
0.9
1.3
*
*
31
Table 11b. Observed/Expected Cancer Incidence, Females, Combined zip codes for Eight Communities
1996-2004
2005-2012
Cancer type
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
Cases
Observed
Cases
Expected
Observed/
Expected
Ratio
Lower
95% CI
Upper
95% CI
all types
2737
2781
1.0
0.9
1.0
3574
3471
1.0
1.0
1.1
oral
40
47
0.9
0.6
1.2
46
58
0.8
0.6
1.1
colorectal
218
250
0.9
0.8
1.0
279
278
1.0
0.9
1.1
liver
10
12
0.8
0.4
1.5
23
25
0.9
0.6
1.4
pancreas
38
47
0.8
0.6
1.1
55
68
0.8
0.6
1.0
lung
328
305
1.1
1.0
1.2
415
386
1.1
1.0
1.2
breast
900
929
1.0
0.9
1.0
1107
1071
1.0
1.0
1.1
uterus
160
168
0.9
0.8
1.1
259
226
1.1
1.0
1.3
ovary
86
91
0.9
0.8
1.2
88
98
0.9
0.7
1.1
bladder
71
62
1.1
0.9
1.4
71
73
1.0
0.8
1.2
kidney
57
54
1.1
0.8
1.4
84
76
1.1
0.9
1.4
brain
43
35
1.2
0.9
1.7
36
39
0.9
0.6
1.3
thyroid
84
78
1.1
0.9
1.3
150
133
1.1
1.0
1.3
lymphoma
153
159
1.0
0.8
1.1
212
193
1.1
1.0
1.3
leukemia
60
71
0.9
0.6
1.1
109
96
1.1
0.9
1.4
*
*
32
Table 12a. Distillation of positive results from tables 3-11, males
1996-2004
2005-2012
Community
Cancer type
Cases Obs
Cases Exp.
Obs/Exp
95%
Conf.
Interval
Cases Obs
Cases Exp.
Obs/Exp
95%
Cont.
Interval
Zip 55128 (Oakdale)
all types
481
459
1.0
1.0
1.1
591
531
1.1
1.0
1.2
Zip 55128 (Oakdale)
colorectal
57
43
1.3
1.0
1.7
*
55
43
1.3
1.0
1.7
Zip 55042 (Lake Elmo)
oral
11
5
2.3
1.2
4.2
*
2
6
0.3
0.0
1.1
Zip 55042 (Lake Elmo)
lung
15
18
0.9
0.5
1.4
10
21
0.5
0.2
0.9
*
Zip 55042 (Lake Elmo)
prostate
43
45
1.0
0.7
1.3
79
60
1.3
1.0
1.6
*
Zip 55125-29 (Woodbury)
oral
13
22
0.6
0.3
1.0
16
33
0.5
0.3
0.8
*
Zip 55125-29 (Woodbury)
colorectal
62
62
1.0
0.8
1.3
54
82
0.7
0.5
0.9
*
Zip 55125-29 (Woodbury)
pancreas
16
13
1.3
0.7
2.1
13
23
0.6
0.3
1.0
*
Zip 55125-29 (Woodbury)
lung
47
80
0.6
0.4
0.8
84
106
0.8
0.6
1.0
*
Zip 55125-29 (Woodbury)
prostate
185
199
0.9
0.8
1.1
332
292
1.1
1.0
1.3
*
Zip 55125-29 (Woodbury)
lymphoma
44
47
0.9
0.7
1.3
51
71
0.7
0.5
0.9
*
Zip 55055 (Newport)
lymphoma
5
4
1.2
0.4
2.9
10
4
2.2
1.1
4.1
*
Zip 55071 (St. Paul Park)
all types
128
103
1.2
1.0
1.5
94
105
0.9
0.7
1.1
Zip 55033 (Hastings)
prostate
153
168
0.9
0.8
1.1
156
195
0.8
0.7
0.9
*
Zip 55075 (South St Paul)
all types
468
433
1.1
1.0
1.2
451
396
1.1
1.0
1.2
*
Zip 55075 (South St Paul)
lung
70
55
1.3
1.0
1.6
70
44
1.6
1.3
2.0
*
Eight Communities
oral
71
89
0.8
0.6
1.0
81
114
0.7
0.6
0.9
*
Eight Communities
pancreas
59
53
1.1
0.8
1.4
57
80
0.7
0.5
0.9
*
*
55016 (Cottage Grove)
*
*
33
Table 12b. Distillation of positive results from tables 3-11, females
1996-2004
2005-2012
Community
Cancer type
Cases Obs.
Cases Exp.
Obs/Exp
95%
Conf.
Interval
Cases Obs.
Cases Exp.
Obs/Exp
95%
Conf.
Interval
Zip 55128 (Oakdale)
all types
484
482
1.0
0.9
1.1
625
559
1.1
1.0
1.2
Zip 55128 (Oakdale)
lung
73
55
1.3
1.0
1.7
73
64
1.1
0.9
1.4
Zip 55128 (Oakdale)
breast
163
162
1.0
0.9
1.2
208
172
1.2
1.1
1.4
*
Zip 55128 (Oakdale)
thyroid
16
13
1.3
0.7
2.0
31
20
1.5
1.0
2.2
*
Zip 55016 (Cottage
Grove)
Zip 55125-29
(Woodbury)
Zip 55055 (Newport)
lymphoma
39
39
1.0
0.7
1.4
72
56
1.3
1.0
1.6
*
all types
70
73
1.0
0.7
1.2
75
59
1.3
1.0
1.6
*
Zip 55055 (Newport)
kidney
2
1
1.4
0.2
5.0
5
1
3.9
1.3
9.0
*
Zip 55071 (St Paul Park)
liver
3
0
7.0
1.4
20.4
0
1
0.0
0.0
5.2
Zip 55071 (St Paul Park)
lung
17
11
1.5
0.9
2.4
20
11
1.8
1.1
2.8
*
Zip 55033 (Hastings)
pancreas
4
9
0.5
0.1
1.2
5
13
0.4
0.1
0.9
*
Zip 55033 (Hastings)
breast
132
161
0.8
0.7
1.0
193
184
1.1
0.9
1.2
Zip 55033 (Hastings)
ovary
17
16
1.1
0.6
1.7
8
17
0.5
0.2
0.9
*
Zip 55075 (South St Paul)
all types
487
432
1.1
1.0
1.2
*
463
403
1.1
1.0
1.3
*
Zip 55075 (South St Paul)
lung
70
52
1.3
1.0
1.7
*
73
47
1.6
1.2
2.0
*
Zip 55075 (South St Paul)
kidney
13
9
1.5
0.8
2.6
18
9
2.0
1.2
3.2
*
Eight Communities
colorectal
218
250
0.9
0.8
1.0
279
278
1.0
0.9
1.1
Eight Communities
uterus
160
168
0.9
0.8
1.1
259
226
1.1
1.0
1.3
*
*
Zip 55042 (Lake Elmo)
*
*
*
*
34
Table 13. Comparison of results according to time period; 1996-2004 vs. 2005-2012
Males
2005-2012
Fewer cancers
than expected
Number cancers does
not differ from expected
More cancers than
expected
Total
1996-2004
Fewer cancers than
expected
1
0
0
1
1996-2004
Number of cancers does
not differ from
expected
8
99
6
113
1996-2004
More cancers than
expected
0
3
0
3
Total
9
102
6
117
Fewer cancers
than expected
Number cancers does
not differ from expected
More cancers than
expected
total
Females
2005-2012
1996-2004
Fewer cancers than
expected
0
2
0
2
1996-2004
Number of cancers does
not differ from
expected
2
108
9
129
1996-2004
More cancers than
expected
0
2
2
4
Total
2
122
11
135
35
Section Overview: Tracking Updates
Matthew Montesano, MN Tracking Data Portal Coordinator, will demonstrate the New
Interactive Asthma Hospitalizations Map. Other updates are provided in written form. Panel
members are invited to comment and ask questions on any of the updates in this section.
Information Item Updates:
•
•
•
•
•
New reports
New portal content
Great Lakes Tribal Tracking Project
Health Impact Assessment and Data Utilization
Cancer Risk Communications Toolkit
36
Tracking Updates
New Interactive Asthma Hospitalizations Map
In January 2015 MN Tracking implemented a new mapping system for the Data Access Portal,
with new map views for asthma hospitalizations (county and ZIP code). This mapping system is
mobile-friendly and includes several enhancements for usability and design. View asthma maps
at (https://apps.health.state.mn.us/mndata/asthma).
MN Tracking is working to update the other maps on the Data Access portal in 2015.
New Reports
In December 2014, MN Tracking released a new report, The Economic Burden of the
Environment on Two Childhood Diseases: Asthma and Lead Poisoning in Minnesota. This report
focuses on the economic costs of both conditions and estimates the fraction that is attributable
to environmental causes. MN Tracking worked together with CDC and other state Tracking
partners to develop methods and this report to help inform policy discussions.
Also, in December MN Tracking published a new report, The Scope of Lung Cancer in
Minnesota. This report was a joint project with the American Lung Association in Minnesota.
Access these reports under “Special Projects” on the MN Tracking web site:
(http://www.health.state.mn.us/tracking).
New Portal Content
MN Tracking currently is developing three new content areas for the Data Access Portal:
•
•
•
Childhood obesity
Diabetes
Oral Health (non-Tracking data and measures; added with supplemental funding)
Check the Data Access portal in late spring to access these data. To receive updates as new
content is released, please sign up for our email subscription service on the Data Access portal
home page: (https://apps.health.state.mn.us/mndata/).
Great Lakes Tribal Tracking Project
MN Tracking’s cooperative agreement with CDC provides funding for an exciting new
opportunity to work with the Great Lakes Inter-Tribal Epidemiology Center (GLITEC), and
Tracking Programs and Tribal Communities in WI, MI, and MN. The goal of this project is to
assess and plan how disparate data sources can be brought together to track environmental
and health outcomes at a Tribal level, and to strengthen environmental epidemiology capacity
within GLITEC.
GLITEC will help prioritize environmental and health surveillance data content priorities from a
Bemidji Tribal Territory data needs assessment, working with input from at least one Tribal
community in each state. In addition, they will help select at least one content area relevant to
the needs of tribes for conducting a data source inventory.
37
In addition, GLITEC will explore and recommend options for indicator development and display
of outcomes, including potential for data sharing as reports, mapping, or inclusion as part of a
community (Tribal) health profile. This project does not include the collection of any new data.
GLITEC and MN Tracking currently are working with the Fond du Lac Tribe, who expressed
interest in working collaboratively on this project. Please stay tuned as we work with GLITEC,
CDC, and other tracking partners.
Note: The CDC National Tracking Network provided initial funding for this project through July
31, 2015. We are hopeful that CDC will continue to support GLITEC and project activities
beyond the current budget cycle.
For questions or more information about this project, please contact Jean Johnson,
[email protected], 651-201-5902.
Health Impact Assessment and Data Utilization
In April 2014, the CDC National Tracking Network launched new web content for Health Impact
Assessment (HIA). This content included a data user guide and diagrams that illustrate how
Tracking Data can be used to inform HIAs (e.g., HIAs for land use planning, climate change
adaptation, and transportation policy). MN Tracking launched similar content on MDH’s web
site to promote use of local Tracking Data in HIAs in Minnesota.
Tracking grantees in Massachusetts, New York City, and Minnesota currently are using Tracking
Data in HIA projects. In addition, a new national Tracking project team has been proposed to
CDC to further promote and expand use of Tracking Data in HIAs at the national, state, and local
levels.
In Minnesota, MN Tracking serves as a member of the MN HIA Coalition, which is a diverse
group of partners working to champion HIA in MN. MN Tracking also is working in partnership
with the MDH Health Impact Assessment Program to identify data needs, and where feasible,
fulfill data requests.
For more information and links to resources, visit the MN Tracking Program web site, Using
Tracking Data in HIAs: (http://www.health.state.mn.us/divs/hpcd/tracking/hia/hia.html).
Cancer Risk Communication Toolkit
To inform the public about cancer risks and the role of the environment, MN Tracking, working
in collaboration with the Minnesota Cancer Surveillance System, proposed to develop, test, and
promote two new tools as part of a “toolkit”. These tools include new web content using plain
language and best practices for risk communication. Topics will address what is known about
the causes of cancer, resources, and links to more information, and how communities can
access cancer data from MDH via the data portal or special data requests. In addition, MN
Tracking proposed to develop and conduct usability testing (internal and external to MDH) of a
template for providing sub-county level cancer data to communities. To date, communications
staff have conducted key informant interviews with local public health officials about the
documents used to communicate information in Fridley and Como communities.
38
Section Overview: East Metro PFC3 Biomonitoring Project
The PFC3 Biomonitoring Project is the third in a series of projects designed to track blood levels
of PFCs in residents of the East Metro area following public health interventions to improve the
community’s water systems. PFC3 will check that these interventions are continuing to reduce
PFC exposures in East Metro residents. Recruitment for the project was completed by January
2015. Specimen collection will be complete in February 2015.
At the February 2015 Advisory Panel meeting, Christina Rosebush will report preliminary
demographic data for three groups of participants: the Original Cohort, New Residents, and
New Renters. The PFC analysis plan will also be presented. Panel members are invited to ask
questions and provide comment on the analysis plan.
Background: Differences between the New Residents group identified through the Oakdale
water billing records and the New Renters group identified through the Washington County
HRA were seen in the preliminary demographic analysis. The sample size for the New Renters
group is very small (N=19).
In the next phase of analysis, we will test whether serum PFC levels are different between New
Residents and New Renters. If no significant differences are observed, New Residents and New
Renters could be grouped together to provide an inclusive picture of PFC levels in individuals
who began their residence in Oakdale after October 2006.
Alternatively, PFC results for New Residents and New Renters could be presented separately
due to the important demographic differences between the two groups.
Questions to the panel:
•
•
Given that we only have a small number of renters, how should renters data be
analyzed?
Does the panel have other comments/recommendations for the analysis plan?
39
East Metro PFC3 Biomonitoring Project
Project Summary
The East Metro PFC3 Biomonitoring Project will measure six-year change in blood levels of
perfluorochemicals (PFCs) in long-term East Metro residents as a check that measures put into
place to reduce PFC exposures in drinking water are working. Additionally, the project will
measure PFCs in newer Oakdale residents– people who moved to the city after the intervention
and who didn’t have known PFC drinking water exposures – to see if they are similar to U.S.
general population.
Recruitment and sample collection
Recruitment for PFC3 was completed in January 2014, and sample collection is expected to end
in February 2015.
All participants of the 2008 and 2010 PFC Biomonitoring Projects who agreed to future contact
(175 East Metro residents) were asked to participate via mail and follow-up calls starting in
February 2014. One hundred fifty-six of these Original Cohort members consented to
participate in PFC3.
The pool of eligible adults for the New Residents group was determined using City of Oakdale
water billing records. Two hundred twenty-five individuals from unique Oakdale households
were selected and invited to participate. For those who refused participation, a replacement
from the same household was selected. One hundred forty-one New Residents consented to
participate.
In the New Renters group, 43 Oakdale renters identified through the Washington County
Housing and Redevelopment Authority (HRA) were invited to participate. All eligible renters
were invited, including multiple people per household, due to the small recruitment pool.
Nineteen New Renters consented. The difficult process of identifying an eligible pool of renters
and challenges in individual participant recruitment resulted in this small final sample size.
Preliminary Demographic Analysis
Table 1 presents population characteristics for the three study groups: Original Cohort, New
Residents, and New Renters. Additionally, characteristics are presented for a combined group
of New Residents and Renters, as individuals for both of these groups were selected based on
beginning their Oakdale residency after the East Metro public health interventions (after
October 2006).
As expected, members of the Original Cohort are older and have lived in the East Metro for
more years than New Residents and New Renters. These differences are largely due to
differing residency eligibility requirements for participation in the PFC Pilot Project and PFC3.
The Original Cohort includes a greater proportion of White, non-Hispanic individuals compared
to New Residents and New Renters. Nearly half of the New Renters group is in the “Other”
race/ethnicity category. The Original Cohort and New Residents groups have similar household
income profiles. Comparatively, the New Renters group includes a larger proportion of
individuals whose annual household income is less than $45,000. When the New Residents and
40
New Renters groups are combined, some of these important differences in race/ethnicity and
income are less apparent.
Table 1. Population characteristics of PFC3 participants, 2014
Original Cohort New Residents New Renters
(n=156)
(n=141)*
(n=19)**
All New
Residents and
Renters (n=160)
Age (mean yrs)
59.1
44.8
48.9
45.2
Gender
Male
45%
41%
21%
39%
Female
55%
59%
79%
61%
Length of residence (mean
yrs)
24.8
3.8
2.4
3.7
Race/ethnicity
White, non-Hispanic
98%
86%
58%
85%
Other
2%
14%
42%
15%
Income
<$45,000
19%
15%
79%
23%
$45,000-$74,999
25%
36%
11%
33%
≥ $75,000
56%
49%
11%
44%
* The New Residents population was recruited from City of Oakdale water billing
records. It includes six renters.
** The New Renters population was recruited from Washington County HRA records. It
includes only renters who meet income requirements for HRA properties.
41
Analysis Plan
The next phase of the analysis will begin when serum PFC results are available and will consist
of the following.
•
•
•
For the Original Cohort, 2014 PFC levels will be compared to levels found in 2008 and
2010, and an overall percent change will be calculated for PFOS, PFOA, and PFHxS. This
group will also be compared to U.S. background levels (NHANES 2011-2012).
PFC levels in the New Residents group will be compared to U.S. background levels. The
association between length of residence in Oakdale since November 1, 2006 and PFC
blood levels will also be analyzed to determine if longer residence results in elevated
PFC blood levels. Although PFC levels in Oakdale city water are below health-based
limits, low levels of PFCs are still present in some water samples.
For all groups, differences in serum PFC levels by demographic characteristics and
questionnaire responses (e.g. occupational history, diet, product use) will be examined.
42
Section Overview: Ongoing PFC Study in the East Metro
Minnesota Statutes, 144.997 Subd. 2 (b) (1) describes the Advisory Panel’s role in advising the
Commissioner on the usefulness of continuing biomonitoring as follows:
(b) Following the conclusion of the pilot program, the commissioner shall:
(1) work with the advisory panel to assess the usefulness of continuing biomonitoring among
members of communities assessed during the pilot program and to identify other communities
and other designated chemicals to be assessed via biomonitoring;
Following the completion of the PFC Biomonitoring pilot in 2010 and again in 2013, the
Advisory Panel recommended continued biomonitoring in the East Metro Community in order
to track changes in PFCS blood levels, an indicator of the progress of public health
interventions. In addition, the panel has recommended communication of findings with
participants, the public, and with scientific peers. MDH has made a commitment to the
community to monitor the evolving scientific literature regarding the health effects of PFCs and
keep community leaders apprised as new information is learned.
Giving consideration to these recommendations, a review of recent literature, and consistent
with MDH’s commitment to the community, staff are recommending continued work in the
next biennium (2016-17) as described in this section.
Panel members are asked to review these staff recommendations and consider whether any
additional recommendations for continued biomonitoring in the East Metro community, or in
another community, are needed at this time.
Questions for the panel members:
•
•
Given that results of PFC3 are not available, does the panel recommend any additional
PFC biomonitoring in the East Metro in the future?
In another community?
43
Ongoing PFC Study in the East Metro
Staff Recommendation for State Fiscal Years 2016-17
Completion of East Metro PFC3 Biomonitoring Project
•
•
•
•
•
•
•
•
•
•
•
Conduct aggregate epidemiological analysis of questionnaire and blood PFC data for
three sampled groups: original cohort, new residents, and renters.
Analyze changes in population PFC levels over time among exposed cohort.
Provide individual results communication to over 300 study participants.
Develop and share a Community Biomonitoring Report (public results presentation).
Develop and share a data brief or website post in plain language for communication of
Cancer Occurrence in Washington and Dakota Counties: 2000-2012 Data Update.
Presentation results to EHTB Advisory Panel: Develop recommendations on the need
and direction for further PFC biomonitoring in the East Metro.
Maintain Advisory Panel in accordance with state law (3 meetings per year). Respond to
results and emerging health concerns, and plan for possible future projects.
Manuscript preparation for peer-reviewed publication of PFC2 and PFC3 results for
scientific audiences.
Monitor scientific/epidemiologic literature and evaluate/update PFC health effects
messages for the community.
Engage with community members, including local public health and elected officials,
through web announcements, legislative factsheets, media, and public meetings as
needed.
Work to improve communications about biomonitoring results and health effects. This
could include convening a community advisory group to assist MDH in reviewing the
effectiveness of communications about health impacts of PFCs and the interpretation of
biomonitoring data, and identify data needs for understanding community health
impacts.
44
Recent PFC Health Study Publications Abstracts
These abstracts are presented as examples of recent literature published on the health effect of
PFCs, including two systematic review papers of birth outcomes and one analysis of NHANES
data for liver effect markers, and is not a comprehensive list of all new publications. Staff
continue to track and monitor this growing body of literature.
Johnson, P. I., et al. (2014). "The Navigation Guide - evidence-based medicine meets
environmental health: systematic review of human evidence for PFOA effects on fetal growth."
Environ Health Perspect 122(10): 1028-1039.
Abstract. BACKGROUND: The Navigation Guide methodology was developed to meet the need
for a robust method of systematic and transparent research synthesis in environmental health
science. We conducted a case study systematic review to support proof of concept of the
method. OBJECTIVE: We applied the Navigation Guide systematic review methodology to
determine whether developmental exposure to perfluorooctanoic acid (PFOA) affects fetal
growth in humans. METHODS: We applied the first 3 steps of the Navigation Guide
methodology to human epidemiological data: 1) specify the study question, 2) select the
evidence, and 3) rate the quality and strength of the evidence. We developed a protocol,
conducted a comprehensive search of the literature, and identified relevant studies using
prespecified criteria. We evaluated each study for risk of bias and conducted meta-analyses on
a subset of studies. We rated quality and strength of the entire body of human evidence.
RESULTS: We identified 18 human studies that met our inclusion criteria, and 9 of these were
combined through meta-analysis. Through meta-analysis, we estimated that a 1-ng/mL increase
in serum or plasma PFOA was associated with a -18.9 g (95% CI: -29.8, -7.9) difference in birth
weight. We concluded that the risk of bias across studies was low, and we assigned a
"moderate" quality rating to the overall body of human evidence. CONCLUSION: On the basis of
this first application of the Navigation Guide systematic review methodology, we concluded
that there is "sufficient" human evidence that developmental exposure to PFOA reduces fetal
growth.
Bach, C. C., et al. (2014). "Perfluoroalkyl and polyfluoroalkyl substances and human fetal
growth: A systematic review."Crit Rev Toxicol: 1-15.
Abstract. BACKGROUND: Exposure to perfluoroalkyl and polyfluoroalkyl substances (PFASs) is
ubiquitous in most regions of the world. The most commonly studied PFASs are
perfluorooctane sulfonate (PFOS) and perfluorooctanoate (PFOA). Animal studies indicate that
maternal PFAS exposure is associated with reduced fetal growth. However, the results of
human studies are inconsistent. Objectives: To summarize the evidence of an association
between exposure to PFASs, particularly PFOS and PFOA, and human fetal growth. Methods:
Systematic literature searches were performed in MEDLINE and EMBASE. We included original
studies on pregnant women with measurements of PFOA or PFOS in maternal blood during
pregnancy or the umbilical cord and associations with birth weight or related outcomes
according to the PFAS level. Citations and references from the included articles were
investigated to locate more relevant articles. Study characteristics and results were extracted to
45
structured tables. The completeness of reporting as well as the risk of bias and confounding
were assessed. Results: Fourteen studies were eligible. In utero PFOA exposure was associated
with decreased measures of continuous birth weight in all studies, even though the magnitude
of the association differed and many results were statistically insignificant. PFOS exposure and
birth weight were associated in some studies, while others found no association. Conclusions:
Higher PFOS and PFOA concentrations were associated with decreased average birth weight in
most studies, but only some results were statistically significant. The impact on public health is
unclear, but the global exposure to PFASs warrants further investigation.
Gleason, J. A., et al. (2015). "Associations of perfluorinated chemical serum concentrations and
biomarkers of liver function and uric acid in the US population (NHANES), 2007-2010." Environ
Res 136: 8-14.
Abstract. BACKGROUND: Perfluorinated chemicals (PFCs) are a group of manmade compounds
that are not broken down in the body. Four PFCs (PFHxS, PFOS, PFOA, and PFNA) have been
found in the blood of more than 98% of the United States population. OBJECTIVES: Our goal
was to assess associations between PFHxS, PFOS, PFOA, and PFNA and uric acid, alanine
transferase (ALT), gamma-glutamyl transferase (GGT), asparate aminotransferase (AST),
alkaline phosphate (ALP), and total bilirubin in 2007-2008 and 2009-2010 combined National
Health and Nutrition Examination Survey (NHANES). METHODS: We used multivariate linear
regression and logistic regression adjusted for age, gender, race/ethnicity and BMI group,
poverty, smoking, and/or alcohol consumption to estimate associations. Trend analysis was
performed. RESULTS: PFHxS was associated with ALT. Each quartile of PFOS was statistically
associated with total bilirubin [(Q2: OR=1.44, 95% CI 1.12-1.84), (Q3: OR=1.65, 95% CI 1.252.18), and (Q4: OR=1.51, 95% CI 1.06-2.15)], with evidence of an increasing trend (pvalue=0.028). PFOA was associated with uric acid, ALT, GGT, and total bilirubin. PFNA was
linearly associated with ALT (p-value <0.001), and there was statistically significant increasing
trend (p-value=0.042). CONCLUSIONS: Our analysis found evidence of associations of
biomarkers of liver function and uric acid with PFHxS, PFOS, PFOA, and PFNA at levels found in
the general U.S. population.
46
Section Overview: Other Information
This section contains documents that may be of interest to panel members.
•
•
•
•
•
•
2015 Upcoming Advisory Panel Meeting dates
Summary: October 14, 2014 Advisory Panel Meeting
Advisory Panel Roster
Biographical Sketches of Advisory Panel Members
Biographical Sketches of Staff
Environmental Health Tracking and Biomonitoring Legislation
47
2015 Advisory Panel Meetings
Tuesday, February 10, 2015
1-4 pm
Tuesday, June 9, 2015
1-4 pm
Tuesday, October 13, 2015
1-4 pm
All meetings for 2015 will take place at
The American Lung Association of Minnesota
490 Concordia Avenue
St. Paul, Minnesota
48
October 14, 2014 Advisory Panel Meeting Summary:
Environmental Health Tracking & Biomonitoring
1:00–4:00 p.m., American Lung Association
Advisory Panel Members: Bruce Alexander, Alan Bender, David De Groote, Melanie Ferris,
Thomas Hawkinson, Patricia McGovern, Geary Olsen, Steven Pedersen, Cathy Villas-Horns, and
Lisa Yost
Advisory Panel Regrets: Fred Anderson, Jill Heins Nesvold, and Gregory Pratt,
MDH staff: Betsy Edhlund, Melissa Finnegan, Carin Huset, Jim Kelly, Jean Johnson, Aggie
Leitheiser, Mary Manning, Pat McCann, Jessica Nelson, Christina Rosebush, Deanna Scher,
Chuck Stroebel, Lisa Strong, Janis Taramelli, Addis Teshome
Others: Matt Simcik, University of Minnesota
Welcome and introductions
Chair Pat McGovern welcomed the attendees and invited the panel members and audience to introduce
themselves.
Sustaining Minnesota Biomonitoring: Workgroup Progress Report
In Kris Van Amber’s absence, Jean Johnson updated the panel members on the Sustaining MN
Biomonitoring Workgroup meetings. The background material for this and the Legislative Presentation
can be found on pages 4-8 of the October 14, 2014 Advisory Panel Meeting book.
Discussion was delayed until Melissa Finnegan, Legislative Liaison for the Minnesota Department of
Health, completed her presentation on the following:
Legislative Process and the Role of the Advisory Panel
The following questions were asked of the panel to consider:
•
•
What is the role of the panel in the legislative process?
What additional support and resources do they need?
Discussion
David DeGroote expressed his understanding that as advisory panel members, we have to be careful to
note that we are speaking as citizens, when there is no Advisory Panel position, and not as advisory
panel members. Melissa Finnegan agreed, pointing out that the advisory panel bylaws state that you
have to refrain from sending letters or representing the committee without the approval of the
committee. You have to make it clear that this is your opinion and you are giving this information as a
citizen and not as a member of the EHTB Advisory Panel. As long as you make that clear, then you can be
a citizen advocate. Melissa added that as a panel, if you all want to put things forward that is amongst
you to decide.
Lisa Yost asked about the opportunity for input from interested entities during the process when bills
are going through committees. Melissa Finnegan responded that there was a lot of input from outside
allowed in that process. She suggested that you attend the hearings on a bill that you really care about.
She added that if they are changing the bill in ways you do not like, every amendment is discussed, just
49
like every bill, and is voted on. People who are for and against it get to weigh in, so that would be your
chance to step in and speak either for or against it. If the bill is changed and goes to the next committee,
you can talk to the author and give your opinion again. So it is a continually malleable process to go
through. Every time a bill is in a committee, this is your opportunity to weigh in and talk about concerns,
ideas, and support, right up until it gets to the floor. There were no further questions.
PFCs in soil and produce: Recent Findings
Deanna Scher, Exposure Consultation Staff with Environmental Public Health, and Carin Huset, Research
Scientist in the MDH Public Health Lab, presented the MDH Perfluorochemicals in Homes and Gardens
Study (PIHGS). Background materials can be found on pages 9-11 of the October 14, 2014 Advisory Panel
Meeting book.
Matt Simcik, Associate Professor at the University of Minnesota’s School of Public Health, Division of
Environmental Health Sciences, presented recent findings from analyses of farm and garden soils in the
East Metro for Perfluorochemicals (PFCs), and discussed his upcoming “food basket study”, which is
awaiting University of Minnesota IRB approval. The background materials are on page 12 of the October
14, 2014 Advisory Panel Meeting book.
The following questions were asked of the panel:
•
•
•
How should MDH respond to legislators’ questions about potential exposure to East Metro
farmers? Is it likely to be a health concern?
What additional investigation is recommended?
Is additional biomonitoring for PFCs recommended for the East Metro?
The speakers then took questions. Tom Hawkinson asked if there had been any biomonitoring done in
Matt Simcik’s population or whether he had just looked at potential exposure sources. Matt replied that
residents of the area may have been eligible for the MDH PFC biomonitoring projects, but the Hmong
farmers who worked in the area were not necessarily residents. Jean Johnson added that the question
being asked by a legislator was, “Should we be testing this unique population because of this exposure.”
Matt thought that biggest exposure source in the Hmong Community was fish. He also expressed his
surprise that PFOS levels in soil were so high, since he understood that it was not in the Washington
County landfill. So, he did not know the source of PFOS contamination in this particular field.
Bruce Alexander asked where the vegetable concentrations came from in Matt Simcik’s data. Matt
replied that he had applied ratio transfer factors for soil to vegetables from another study. He added
that he would be analyzing the vegetables as soon as they received IRB approval.
Pat McGovern wondered how large the Hmong population was in the location of concern and whether it
was a stable population or a migrant work force. Matt Simcik responded that they were not a migrant
work force and some had farmed in the area for 20 years, but the folks that had been farming the
specific plot with the high levels of PFCs were no longer farming that same spot. He was not sure if they
were completely done with farming or whether they were farming elsewhere. The field is now being
used for beets. Pat McGovern asked if we had any sense how many Hmong families of concern lived and
farmed in this area. Matt replied that there were probably 30 families on that field, all farming for
personal consumption; but some of the crops were also for the farmers’ markets. Pat McGovern asked
whether these families would have had the highest doses. Matt Simcik said that he did not know, but he
guessed that would be true. What he had really wanted to do was look at an area that had not been
disturbed by farming.
50
Lisa Yost commented that Matt Simcik’s earlier slides showed the distribution being closer to the roads
and that would lead to a different conclusion about the source. Then Matt had discussed bio solids
deposition. She wondered whether Matt had a sense, in that later slide, if the source had been road
related. Matt responded that he did not believe it was.
Thomas Hawkinson commented that it could have been a permeability issue. Matt agreed with him, that
PFCs could be coming from the top. He mentioned that Lake Jane, nearby, was contaminated. He also
did not know the water source, as there was currently no irrigation for this field, so whether it was rain
fed agriculture or whether this was public access water brought to the field was unknown. He hoped to
interview the people who used to farm there to find this out.
Bruce Alexander questioned whether the concentrations were related to the roads; Matt Simcik
responded that he was not saying that. What he had been trying to determine at first was whether he
could look at traffic patterns and road congestion to find areas with higher contamination. All of these
concentrations were higher than the median they had found for the gardens in the PIHGS study,
indicating that soil in close proximity to roads is elevated over background concentrations. Bruce
clarified that near roads means near a point source. Matt replied that there were no manufacturing
storage disposal sources near Big Lake, yet the levels are higher than any other reporting background
concentrations, so that would indicate that roads have some sort of source. Although, Matt pointed out,
we do not know what Minnesota background soil is; we have so many different soil types in Minnesota.
He thought it would be interesting to look at whether soil type has an effect on concentrations. PFCs are
ubiquitous; they have been found in lakes in Voyageur’s National Park. PFC levels could have to do with
soil type, organic matter, or some kind of point source.
Pat McGovern asked whether Matt Simcik had thought of biomonitoring in the East Metro when he did
his soil project or what he thought about it now. Matt answered that he would like to see biomonitoring
in the Hmong community--but how you go about doing that and whether the community would be
receptive to it are important questions.
Jean Johnson asked how many people were in Matt Simcik’s food basket study. Matt replied that he was
trying to recruit 200 total people, so anywhere from 50-75 families. Jean Johnson clarified that the
population being discussed—they rent the farm fields for farming; they may or may not actually live in
the area, because if they lived in the area, they would have been eligible for our biomonitoring to be
done. So they may not have the drinking water exposure component. Matt Simcik replied that he
agreed, although some folks had moved into the area, they had not traditionally lived in the East
Metro—maybe Oakdale.
Pat McCann, MDH Fish Consumption Advisory Program Manager, asked about the recruitment process
for the study. Matt Simcik responded that he had been working with the Hmong community, and he had
a list-serve from the cultural work that had been conducted, such as Right-to-Know workshops. They
would be invited to come to the Cultural Center. He would also use in person as well as ads in the native
media.
Cathy Villas-Horns wondered whether this was the only farm that used bio solids, to which Matt Simcik
responded that he did not know if bio solids had even been put on this farm. He added that from a
national perspective, bio solids are important when you are thinking about PFC contamination.
Cathy Villas-Horns wondered about concerns around bio solids and Hmong farmers in particular. Matt
replied that it was because the farm he happened to sample was a Hmong farm and it was elevated. So
he was concerned for them because they eat different foods, they were farming in a different area, and
they were renting the farms. They were not captured by the MDH PFC studies if they did not live where
51
they farmed, and they were fishing in the area and eating fish, so he guessed they would have a higher
exposure than the general population.
Pat McGovern asked what the three speakers would recommend, if they had to make a
recommendation for further studies to this group, specifically for biomonitoring and exposure
assessment. Matt Simcik stated that he was going to begin addressing exposure assessment as soon as
his food basket study had IRB approval. Deanna Scher added that one unfortunate aspect of the
biomonitoring done so far was that it had not been done during the growing season, when they were
eating their own homegrown produce, so it likely did not capture many of these shorter-chain
compounds that are not persistent in the body. She wondered whether PFC3 spanned more of the
summer months; if so, that may capture some new information.
Lisa Yost questioned Deanna Scher about the higher concentrations that she had found and how they
compared to the existing screening levels for soil. Deanna answered that the PCA screening levels were
well in the thousands for PFOS, PFOA, and one other. Lisa Yost commented that presumably, even Matt
Simcik’s higher numbers were much below that, but she realized that that was different than bio
concentration into plants; she was just trying to get a gauge on how high the levels were. Deanna
answered that they were much lower than the level of where the state would come in and clean up.
Cathy Villas-Horns wondered how the house dust levels compared to the produce levels. Deanna Scher
commented that when looking at the entryway detects and concentrations compared to the interior
part of the home, it was really the living areas, the interior areas, that they had found the higher
detections and concentrations. This led them to the conclusion that it was really the consumer products
that were in the home—the carpet and the textiles—that were contributing the most to house dust,
rather than any tracking from outside. She noted that she had found a relationship between PFOA in soil
and PFOA in entryway dust. Beyond this relationship, the interior sources overwhelmed any potential
connection between soil and dust in the home.
Pat McGovern asked if she were the legislator of concern here, what would the speakers say to her
about the potential exposures and health concerns for the Hmong community. Deanna Scher stated that
they had done a comprehensive assessment. When they looked across all the PFCs that they had
reference doses for and across exposure pathways, (dust, soil, produce, drinking water), and even with
the worst case assumptions that they put into the assessment, they still ended up with a hazard index of
0.4, and >1.0 is the level of concern. There were some limitations to the assessment, in that she did not
include commercial foods, but based on 0.4; she did not think it was a level of concern.
Matt Simcik’s concern was a cultural concern; the Hmong did not fit the same model because of what
they were eating and how they were obtaining their food. Deanna Scher added that there was more fish
in the diet and that was something that needed attention.
Carin Huset noted that we really do not have a lot of information about PFC exposure to the general
population of Minnesota. We know about the east metro and drinking water exposures, but we do not
really know much more than that. Hmong farmers, whether that’s people in urban inner city areas or
people in outstate Minnesota, we don’t really know a whole lot about those populations either, so I
think there is reason to study a lot more than just the people with the drinking water exposure and get
more information about background levels across the state.
Lisa Yost asked Matt Simcik when he anticipated he might have data on the vegetables that he had
collected. He thought he would have the data within a year; unfortunately, the chemical analysis was
being held up by the IRB approval. He would be looking at the whole suite of PFCs, including PFBA,
which is common in produce. Lisa Yost asked how many data points he would have. Matt replied that he
52
had many vegetables in the freezer; he would have as many as he could get his student to do; there are
the six in the materials. Carin asked whether Matt was only going to look at the edible components.
Matt responded that in the common produce they were only going to look at the edible components.
However, the edible portion is different culturally for certain produce (such as making tea).
Deanna Scher asked her study partners for their thoughts. Jim Kelly cautioned that these were all good
questions, but the goal of the study they [Deanna] had done was to answer the community’s questions
about what they had felt was a particularly exposed community. To the extent that there are other
unknown exposure sources, he agreed that those are concerns, but suggested thoughtfulness in tackling
these concerns. He cautioned against using ‘random biomonitoring’ as the way to address them. He did
not think enough was known about potential sources of exposure in order to do large-scale
biomonitoring around them.
Matt Simcik would not suggest any random biomonitoring either; he would concentrate on the Hmong
community, because it would seem that they have a different exposure scenario than the general
population.
Pat McGovern wondered whether any of this group had experience with biomonitoring in the Hmong
community, and what their experience had been. Deanna Scher suggested that Pat McCann, MDH FISH
Consumption Advisory Program Manager, had done work on fish consumption. Pat McCann responded
that she had not done any biomonitoring, but she had done a lot of outreach to the Hmong community
about fish consumption. Pat McGovern wondered if there had been receptivity. Pat McCann answered
that they had worked with the DNR, who had an established relationship with the Hmong community
and Hmong speaking staff; and then they also had established relationships with Hmong community
leaders; particularly with people in the community who were leaders in fishing. They were receptive to
interactions at community events through these established avenues. But she cautioned that the Hmong
community had been studied in a number of different ways, and she didn’t think that they were all that
receptive to us studying them.
Pat McCann would also feel uncomfortable trying to pinpoint fishing and fish consumption as a bad
thing. She did not think that PFCs were a big exposure for the Hmong community in general, because of
all the different locations that they fished, and PFCs were not high in fish throughout the metro. They
were only high in particular in sites; therefore, she did not think it was a widespread issue within the
Hmong community. She continued that other studies of fish consumption have not shown that fish
consumption was a big exposure source for PFCs. That was not to say that people who fished in
particular locations that had high PFCs were not exposed. It depended on where they were fishing and
which fish they were eating.
David DeGroote stated that the ultimate question was whether it was likely a health concern. Deanna
Scher noted that what they saw across all the studies was that it was really the shorter-chain
compounds that were getting up into the vegetative plants, and those were the ones that were much
less toxic than PFOS and PFOA. Matt Simcik said that PFOS and PFOA were still getting into these plants
to a lesser extent.
Lisa Yost commented that she thought that the write up was good, but one thing she wished she had
was a little table with the screening values, the RFDs, because her presumption was that the shorterchain PFCs were probably less toxic. She continued that it would have been helpful to have that piece:
reduced toxicity with that shorter-chain is a very important part of the puzzle. Matt Simcik explained
that the shorter chains were much less bio accumulative in people as well.
53
Alan Bender stated that there were two quick points to remember in summarizing this when trying to
address the legislator. The first is that the sampling of another community was outside the scope of the
original projects. We were looking for a stable community that we could measure over time and assess if
remediation was working, so this would become another protocol, another entire hypothesis. Secondly,
one has to be very careful in a general public health setting not to discredit the consumption of
vegetables or other parts of one’s diet; so we should always be cautious that we are not doing more
harm than good.
Aggie Leitheiser commented that in other conversations, one challenge was that there had been an
issue with the Hmong population being very reluctant to have their blood drawn. Aggie continued that
there were some cultural or historical beliefs involving blood in the older population, not so much in the
younger.
Jessica Nelson reminded panel members that in the MN FEET update, which would be discussed after
the break, the Hmong population was one of the four groups that she was hoping to recruit, so she
would need to work on that as well, irrespective of the PFC project.
Pat McGovern recommended taking a break, and then they would come back with a couple
recommendations for the group to consider. She also thanked the three presenters for their informative
presentations.
After the break, Pat McGovern announced that she and Jean Johnson had worked with a couple people
on a recommendation for the group, so she turned it over to Jean Johnson to articulate that. Jean said
that they thought the place to start was to have a conversation with the Hmong community to see what
their concern was and if they had an interest in biomonitoring. If biomonitoring was truly going to be
community based, it really should come from the Hmong community, so the proposal was that the
Minnesota Department of Health would work with either Matt’s connections in the community, or with
SoLaHmo, another community group, to have a conversation and understand this issue from the Hmong
community’s perspective.
Pat McGovern added that if the Hmong community is interested and would like to be tested, then there
is an opportunity for the MDH staff to collaborate with Matt Simcik and explore how to connect it with
the food basket assessment. She thought that would be a good place to start. Pat asked if anyone
wanted to second that. Alan Bender seconded.
Steven Pedersen questioned how narrow the focus was going to be. He cautioned against approaching
the community with, “The Minnesota Department of Health thinks there’s a problem and wants you to
help figure out if that’s true.” He continued that not much is known about PFCs and the environment or
PFCs and human health. He wondered how a question about those topics would be answered. He
cautioned against asking people to be part of something unless the gaps in knowledge and how the
community could help address the research questions were stated. Pat McGovern said that she
appreciated what Steven Pedersen was saying. She added that part of the context for this
recommendation was that the health department has a long history in health education, reaching out to
groups to communicate health risks and protective strategies, so she thought they would be well
positioned. She suggested starting with the community that Matt Simcik already has a relationship with,
or starting with a known group, with an established researcher, who was already taking the group’s diet
history with a food basket.
Steven Pedersen assured that he was not against this. He cautioned that the health department needs
to be very up front with what is not known and where gaps would need to be filled. Steven wanted to
54
state in the motion very, very clearly what would be done. Pat McGovern said she appreciated all those
good points.
Melanie Ferris wondered if a second part of this was also seeing if there was a way to do some work to
look into sources of higher concentrations in that field. It seemed like there was a focus on the Hmong
community, but it may be broader or expand depending on what is learned about why that particular
field is a potential hotspot. Pat McGovern asked Matt Simcik if that was part of his study; he answered
that it was not, but he absolutely agreed.
Cathy Villas-Horns asked Matt Simcik to describe the food basket study. Matt explained that the food
basket study involved asking the community where they farmed, where they got their vegetables, how
much of it did they eat, where they fished; what fish were they taking; how much of each species did
they eat; to try to determine what their exposure might be.
Matt continued that he absolutely agreed that this might not be a Hmong community problem. There
could be other fields that were contaminated, whether from bio solids application or pesticides use.
Matt suggested that Geary Olsen might know if PFCs were used with surfactants for agricultural fields or
if there was a pesticide, herbicide or insecticide, or carrier of solvents and surface-active molecules.
Geary Olsen said that pesticides would not have been a source of PFCs. Geary added that if something
was used, it was bio solids that would have been a source of exposure for an agricultural field. Matt
continued that if that was the source for this field, then there were other fields that were certainly an
issue, so it may not be a Hmong issue at all.
Lisa Yost thought that the reason to talk to the Hmong community was because that question had been
brought to us and rather than treating the Hmong community like a group of people who have no
agency of their own, to find out what concerns they have. They had already been studied, so instead of
coming from the outside, come from the inside just to see how they felt about it and get their opinion.
They may not want anybody to look at their vegetables—that was their product. So to start with them,
to see what their concerns and their issues are. Matt agreed that in talking with farmers, some have
agreed to participate; some have not.
Pat McGovern added that she’d heard Melanie’s concern that we should put the question about looking
at PFC sources on the agenda for next time and then focus today on the concern related to the Hmong
community, because that was like another level of investment.
David DeGroote asked if we had any data about levels in various sources of bio waste materials, bio
solids came from somewhere. Matt Simcik responded that we knew the PCA put a limit on wastewater
treatments; they just have not figured out what to do about it. He was also told, from his investigation,
that none of the bio solids had come from metro plants or any that are under the Metropolitan Council.
He added that he would be following up with farmers on this issue.
Lisa Yost thought we also got some perspective today that although the concentrations are well above
background, they are far below the screening levels for soil, so she cautioned that we should be careful
about how we talk about it, because people can become concerned very quickly about something that
maybe isn’t as high a priority.
Pat McGovern wondered if it made sense to focus on this issue with the Hmong, and then if people want
to bring up the issue of looking at bio solids and their distribution in relationship to farming, to put that
on the agenda for the next meeting. David DeGroote interjected that we should take Alan Bender’s
point of not letting this group or this work end up in the middle of something that they should not be
involved with. Geary Olsen shared David’s opinion. He added that he did not feel comfortable voting on
this. Pat McGovern explained that she thought it was due to it being a first step towards doing
55
biomonitoring with that community in response to a request from the legislature. Geary 0lsen clarified
that he thought that the request was to the Minnesota Department of Health by a state legislator and
that it was up to the Health Department’s prerogative on how to deal with this request or any other
from a state legislator.
Pat McGovern asked Jean whether her group could move forward in the absence of a vote on this and
Jean responded that she thought so. Matt Simcik clarified that his data was part of a Center for
Transportation Studies study and the report had been submitted to the State Department of
Transportation a year and a half ago; yesterday the peer review publication was accepted.
Pat McGovern asked whether the rest of the group felt comfortable not voting on it, knowing that Jean
was going to move forward with her staff to see about this community concern with an identified
Hmong group on this land where Matt was doing his work in response to a legislative concern. Geary
Olsen wondered if this was in Washington County and whether Fred Anderson [Washington County
panel member} was knowledgeable about it? He suggested that the Washington County Public Health
Department could engage in this—and that he would go to them before he would go anywhere. Jean
Johnson offered to talk to Fred Anderson and then report back to this group in February what we have
learned. Geary Olsen thought that was reasonable.
Cathy Villas-Horns noted that the materials did not mention the Hmong farm or bio solids. The materials
said east metro farmers, not east metro Hmong farmers, so. . . Jean Johnson added that at the time, she
wasn’t drawing the distinction, but now that she’d listened to Matt Simcik, she understood that there
was something unique about the Hmong pathway, that was the cultural theory. Matt interjected ‘there
may be—we don’t know’.
Tracking Updates
Matthew Montesano announced that the tracking program had received CDC grant renewal. He also
demonstrated the portal updates, including county profiles, interactive maps of asthma and COPD,
cancer data, and air quality index. The Urban Air Quality and Health Initiative and the Economic Burden
of the Environment on Childhood Disease in Minnesota were described on pages 13-15 of the October
14, 2014 Advisory Panel Meeting book.
Biomonitoring Updates
Biomonitoring updates on the MDH Public Health Lab and East Metro PFC3 Biomonitoring Project were
provided on pages 16-18 of the October 14, 2014 Advisory Panel Meeting book.
Steven Pedersen wondered about the various materials that had been included in the CDC
Biomonitoring grant application. He added that there had been several articles that had come out on
micro beads or micro particles in cosmetics that were flat going through treatment and into our water
systems. He would just like to see that considered in any future grant, since that could separate us from
what other people were looking at and maybe get us that grant next time.
Cord Blood v. Newborn Bloodspot Experiment Results, Other Mercury Project Updates
Betsy Edhlund, Research Scientist in the Environmental Section of the MDH Public Health Laboratory,
reviewed results from The Pregnancy and Newborns Exposure Study. Background materials can be
found on pages 19-21of the October 14, 2014 Advisory Panel Meeting book. Updates on The Pregnancy
and Newborns Exposure Study, the National Children’s Study Newborn Mercury Biomarker Validation
56
Supplemental Methodological Study, and the Riverside Newborn Mercury Project were included in
written form on page 22 of the October 14, 2014 Advisory Panel Meeting book.
Pat McCann wondered, since there were good recoveries with the standard reference materials (SRMs),
whether there was a difference between the SRM blood and the cord blood. Betsy Edhlund replied that
there could be. She did not know how the chemistry of SRM blood compared to the chemistry of cord
blood.
MN FEET Update
Jessica Nelson presented an update on study design, methods, and current planning activities for the
Minnesota Family Environmental Exposure Tracking (MN FEET) project. Background materials can be
found on pages 23-26 of the October 14, 2014 Advisory Panel Meeting book.
Discussion: The following questions were asked of the panel members:
•
•
Given that we relationship between mercury levels in cord blood v. newborn bloodspots as part
of MN FEET, that consent and lab analysis will now come at a later time for bloodspots (see
updates, below), and that participants will receive their individual cord and urine results, staff
recommend that we do not return individual results for newborn bloodspot mercury levels. Do
you agree with this recommendation?
Do you agree with possibly limiting the number of bloodspots analyzed to a subset of
participants?
Melanie Ferris indicated she had mixed feelings about not returning the bloodspot results. She
appreciated that the results would have to be sent back differently and framed in a different way, but
felt that some sort of follow up would be more transparent. Pat McGovern asked how others felt about
that. David DeGroote stated that, since we are talking about a bloodspot methodology that is still a little
experimental and since we plan to return the results for cord blood and urine, he was not sure what
value the somewhat questionable bloodspot data might have. Melanie agreed that the results would
not have the same impact as cord blood and urine, but pointed out that people are sensitive about
bloodspots and the testing that’s done after birth, and that it could be a lingering question for a parent.
Pat McGovern offered an alternative. Typically when results don’t have clinical implications, they aren’t
released to participants, but she said her bias is to release information for the reasons Melanie stated. In
this situation, she suggested a blend: release the cord blood and urine results, but, because of all the
scientific questions about the bloodspot results, say that participants can have their results if they
request them but do not send them routinely. Sending the bloodspot results will involve a lot of
conversation about what they mean relative to the other results. Jean Johnson concurred that
bloodspot results would not be returned routinely, for the reasons we described, but participants can
have them if they really want them. We would have to offer some additional explanation and could
provide counseling or have a physician talk to them and explain why the numbers might be different.
Pat McGovern wondered if that addressed Melanie’s concern. She replied that it did feel better because
there was a place where participants could request results.
Geary assumed that the IRB would be reviewing this. Jessica confirmed this, and added that it will also
be reviewed by SoLaHmo, a community-based research arm of West Side Community Health Services.
SoLaHmo is made up of Somali, Latina, and Hmong researchers. In addition to doing recruitment, they
will also be reviewing the materials. If we discuss this issue and they have concerns about it, we will
have to rethink our strategy.
57
Steven Pedersen asked about bullet two; what is your definition of a subset of participants? Jessica
responded that we have not yet run power calculations, but are thinking around 300 people. In the
Pregnancy and Newborns Exposure Study, mercury was detected in around 60% of cord blood samples.
If the same is true for this population, it would be around half of the 600 total population, or in the 300
range. The plan would be to only ask women with mercury detected in cord blood to participate in the
bloodspot testing. This would allow us to be most efficient in making the cord blood v. bloodspot
comparison because we should have fewer non-detects in bloodspots. Jessica asked if anyone had a
problem or objection to this subset approach. David DeGroote agreed and said to let the past results
guide what the subset looks like. Jessica noted that we will need SoLaHmo and others’ input on the
wording about it in the consent form, as some participants will not be offered this chance and additional
gift card.
New Business
There was no new business.
Audience Questions
There were no audience questions.
Adjournment
Pat McGovern thanked everyone for their attention and patience. The meeting was adjourned
at 4:00 pm. The next Advisory Panel meeting will be held on February 10, 2015 from 1:00–4:00
p.m. at the American Lung Association in Minnesota.
58
Environmental Health Tracking and Biomonitoring Advisory Panel Roster
As of January 1, 2015
Bruce Alexander, PhD
School of Public Health
University of Minnesota
Environmental Health Sciences Division
MMC 807 Mayo
420 Delaware Street SE
Minneapolis, Minnesota 55455
612-625-7934
[email protected]
At-large representative
Fred Anderson, MPH
Washington County
Dept. of Public Health & Environment
14949 62nd St N
Stillwater MN 55082
651-430-6655
[email protected]
At-large representative
Alan Bender, DVM, PhD
Minnesota Department of Health
Health Promotion & Chronic Disease Division
85 East 7th Place
PO Box 64882
Saint Paul, MN 55164-0882
651-201-5882
[email protected]
MDH appointee
Melanie Ferris
Wilder Foundation
451 Lexington Parkway N
St. Paul, MN 55104
651-280-2660
[email protected]
Nongovernmental organization
representative
Thomas Hawkinson, MS, CIH, CSP
Toro Company
8111 Lyndale Avenue S
Bloomington, MN 55420
[email protected]
952-887-8080
Statewide business org representative
Jill Heins Nesvold, MS
American Lung Association of Minnesota
490 Concordia Avenue
St. Paul, Minnesota 55103
651-223-9578
[email protected]
Nongovernmental organization
representative
Pat McGovern, PhD, MPH
School of Public Health
University of Minnesota
Environmental Health Sciences Division
MMC Mayo 807
420 Delaware St SE
Minneapolis MN 55455
612-625-7429
[email protected]
University of Minnesota representative
Geary Olsen, DVM, PhD
3M Medical Department
Corporate Occupational Medicine
MS 220-6W-08
St. Paul, Minnesota 55144-1000
651-737-8569
[email protected]
Statewide business organization
representative
Steven Pedersen, MPH
8403 Mississippi Boulevard NW
Coon Rapids, MN 55433
612-850-1058
[email protected]
Minnesota Senate appointee
59
Gregory Pratt, PhD
Minnesota Pollution Control Agency
Environmental Analysis & Outcomes Division
520 Lafayette Road
St. Paul, MN 55155-4194
651-757-2655
[email protected]
MPCA appointee
Cathy Villas-Horns, MS, PG
Minnesota Dept. of Agriculture
Pesticide & Fertilizer Management Division
625 Robert Street North
St. Paul, Minnesota 55155-2538
651-201-6697
[email protected]
MDA appointee
Lisa Yost, MPH, DABT
ENVIRON International Corporation
333 West Wacker Drive, Suite 2700
Chicago, IL 60606
Local office
479 Iglehart
St. Paul, Minnesota 55103
Phone: 651-225-1592
Cell: 651-470-9284
[email protected]
At-large representative
Vacant
Minnesota House of Representatives
appointee
60
Biographical sketches of advisory panel members
Bruce H. Alexander is a Professor in the Division of Environmental Health Sciences at the
University of Minnesota’s School of Public Health. Dr. Alexander is an environmental and
occupational epidemiologist with expertise in cancer, reproductive health, respiratory disease,
injury, exposure assessment, and use of biological markers in public health applications.
Fred Anderson is an epidemiologist at the Washington County Department of Public Health and
Environment and has over 30 years of public health experience. He holds a Master’s of Public
Health (MPH) in environmental and infectious disease epidemiology from the University of
Minnesota and is a registered environmental health specialist. For over 20 years, he has led
countywide disease surveillance and intervention programs, including numerous
multidisciplinary epidemiologic investigations.
Alan Bender is the Section Chief of Chronic Disease and Environmental Epidemiology at the
Minnesota Department of Health. He holds a Doctor of Veterinary Medicine degree from the
University of Minnesota and a PhD in Epidemiology from Ohio State University. His work has
focused on developing statewide surveillance systems, including cancer and occupational
health, and exploring the links between occupational and environmental exposures and chronic
disease and mortality.
Melanie Ferris, MPH, is a Research Scientist at Wilder Research, a nonprofit research
organization based in St. Paul, Minnesota. She conducts a variety of program evaluation and
applied research projects focused primarily in the areas of public health and mental health. She
has worked on a number of recent projects that focus on identifying disparities across
populations and using existing data sources to develop meaningful indicators of health and
wellness. Examples of these projects include a study of health inequities in the Twin Cities
region related to income, race, and place, development of a dashboard of mental health and
wellness indicators for youth living in Hennepin County, and work on local community health
needs assessments. She has a Master’s of Public Health degree in Community Health Education
from the University of Minnesota’s School of Public Health.
Tom Hawkinson is the Corporate Environmental, Health, and Safety Manager for the Toro
Company in Bloomington, MN. He completed his MS in Public Health at the University of
Minnesota, with a specialization in industrial hygiene. He is certified in the comprehensive
practice of industrial hygiene and a certified safety professional. He has worked in EHS
management at a number of Twin Cities based companies, conducting industrial hygiene
investigations of workplace contaminants and done environmental investigations of subsurface
contamination both in the United States and Europe. He has taught statistics and mathematics
at both graduate and undergraduate levels as an adjunct, and is on the faculty at the Midwest
Center for Occupational Health and Safety A NIOSH-Sponsored Education and Research Center
School of Public Health, University of Minnesota.
61
Jill Heins Nesvold serves as the Director of the Respiratory Health Division for the American
Lung Association in Iowa, Minnesota, North Dakota, and South Dakota. Her responsibilities
include program oversight and evaluation related to asthma, chronic obstructive lung disease
(COPD), lung cancer, and influenza. Jill holds a master’s degree in health management and a
short-course master’s degree in business administration. Jill has published extensively in a
variety of public health areas.
Pat McGovern is a Professor in the Division of Environmental Health Sciences at the University
of Minnesota’s School of Public Health. Dr. McGovern is a health services researcher and nurse
with expertise in environmental and occupational health policy and health outcomes research.
She serves as the Principal Investigator for the National Children’s Study (NCS) Center serving
Ramsey County, one of 105 study locations nationwide. The NCS is the largest, long-term study
of children’s health and development in the US and the assessment of environmental exposures
will include data collection from surveys, biological specimens, and environmental samples.
Geary Olsen is a corporate scientist in the Medical Department of the 3M Company. He
obtained a Doctor of Veterinary Medicine (DVM) degree from the University of Illinois and a
Master of Public Health (MPH) in veterinary public health and PhD in epidemiology from the
University of Minnesota. For 27 years, he has been engaged in a variety of occupational and
environmental epidemiology research studies while employed at Dow Chemical and, since
1995, at 3M. His primary research activities at 3M have involved the epidemiology,
biomonitoring (occupational and general population), and pharmacokinetics of
perfluorochemicals.
Steven Pedersen is a retired Environment, Health, and Safety (EHS) scientist who worked for
BAE Systems in Fridley, MN. He completed his Masters in Public Health at the University of
Minnesota, with a specialization in environmental health. He has thirty-five years’ experience
working on EHS issues; focusing on environmental compliance and the development and
implementation of a management system compliant with the requirements of the international
standards. He has worked in EHS project management at a number of aerospace companies in
Minnesota, Washington, and California. He worked on environmental legislative and regulatory
issues and is an expert on the requirements of the Toxic Substances Control Act as it affects
article-manufacturing companies. He was the project manager implementing an enterprisewide Occupational Safety, Health, and Environment (OSHENs) illness & injury data-management
system. Recently he was a Governor-appointed member, representing the business community,
of the State's Clean Water Council.
Gregory Pratt is a research scientist at the Minnesota Pollution Control Agency. He holds a
Ph.D. in Plant Physiology from the University of Minnesota, where he worked on the effects of
air pollution on vegetation. Since 1984, he has worked for the MPCA on a wide variety of issues
including acid deposition, stratospheric ozone depletion, climate change, atmospheric fate, and
dispersion of air pollution, monitoring, and occurrence of air pollution, statewide modeling of
air pollution risks, and personal exposure to air pollution. He is presently cooperating with the
Minnesota Department of Health on a research project on the Development of Environmental
Health Outcome Indicators: Air Quality Improvements and Community Health Impacts.
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Cathy Villas Horns is the Hydrologist Supervisor of the Incident Response Unit (IRU) within the
Pesticide and Fertilizer Management Unit of the Minnesota Department of Agriculture. Cathy
holds a Master of Science in Geology from the University of Delaware and a Bachelor of Science
in Geology from Carleton College and is a licensed Professional Geologist in MN. The IRU
oversees or conducts the investigation and cleanup of point source releases of agricultural
chemicals (fertilizers and pesticides including herbicides, insecticides, fungicides, etc. as well as
wood treatment chemicals) through several different programs. Cathy has worked on complex
sites with Minnesota Department of Health and MPCA staff, and continues to work with
interagency committees on contaminant issues. She previously worked as a senior
hydrogeologist within the IRU, and as a hydrogeologist at the Minnesota Pollution Control
Agency and an environmental consulting firm.
Lisa Yost is a Principal Consultant at ENVIRON, an international consulting firm. She is in
their Health Sciences Group, and is based in Saint Paul, Minnesota. Ms. Yost completed her
training at the University of Michigan’s School of Public Health and is a board-certified
toxicologist with expertise in evaluating human health risks associated with substances in soil,
water, and the food chain. She has conducted or supervised risk assessments under CERCLA,
RCRA, or state-led regulatory contexts involving a wide range of chemicals and exposure
situations. Her areas of specialization include exposure and risk assessment, risk
communication, and the toxicology of such chemicals as PCDDs and PCDFs, PCBs,
pentachlorophenol (PCP), trichloroethylene (TCE), mercury, and arsenic. Ms. Yost is a
recognized expert in risk assessment and has collaborated in original research on exposure
issues, including background dietary intake of inorganic arsenic. She is currently assisting in a
number of projects including a complex multi-pathway risk assessment for PDDD/Fs that will
integrate extensive biomonitoring data collected by the University of Michigan. Ms. Yost is also
an Adjunct Instructor at the University of Minnesota’s School of Public Health.
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Staff Biosketches
Kenneth F Adams, PhD, is an epidemiologist with the Minnesota Cancer Surveillance System
(MCSS), Minnesota’s central cancer registry. His day-to-day work includes estimation of cancer
rates, performance of record linkages between MCSS and other data, responding to citizen
cancer concerns, and data collection for a screening colonoscopy research study. He was
formerly a postdoctoral fellow in the US National Cancer Institute Division of Cancer
Epidemiology and Genetics, and a research investigator at HealthPartners Institute. He received
a PhD in epidemiology from the University of Washington in 2003.
Wendy Brunner, PhD, serves as surveillance epidemiologist for the MDH Asthma Program since
2002, and joined Minnesota’s Environmental Public Health Tracking and Biomonitoring Program
(MN Tracking) program on a part-time basis in fall 2009. Previously, she worked on occupation-al respiratory disease studies for MDH. She has a master’s degree in Science and Technology
Studies from Rensselaer Polytechnic Institute and a master’s degree in Environmental and
Occupational Health from the University of Minnesota. She received her doctorate in the
Division of Epidemiology and Community Health at the University of Minnesota.
Betsy Edhlund, PhD, is a research scientist in the Environmental Section of the Public Health
Laboratory at the Minnesota Department of Health. She works in the metals laboratory
developing methods and analyzing samples for both biomonitoring programs and emergency
response. Betsy received her PhD in chemistry from the University of Minnesota where her
research focused on the photochemistry of natural waters.
Carin Huset, PhD, has been a research scientist in the Environmental Laboratory section of the
MDH Public Health Laboratory since 2007. Carin received her PhD in Chemistry from Oregon
State University in 2006 where she studied the fate and transport of perfluorochemicals in
aqueous waste systems. In the MDH PHL, Carin provides and coordinates laboratory expertise
and information to program partners within MDH and other government entities where studies
require measuring biomonitoring specimens or environmental contaminants of emerging
concern. In conjunction with these studies, Carin provides biomonitoring and environmental
analytical method development in support of multiple analyses.
Jean Johnson, PhD, MS, is Program Director/Principal Investigator for MN Tracking. Dr. Johnson
received her Ph.D. and M.S. degrees from the University of Minnesota, School of Public Health
in Environmental Health and has 25 years of experience working with the State of Minnesota in
the environmental health field. As an environmental epidemiologist at MDH, her work has
focused on special investigations of population exposure and health, including studies of
chronic diseases related to air pollution and asbestos exposure, and exposure to drinking water
contaminants. She is currently an adjunct faculty member at the University of Minnesota School
of Public Health.
Tess Konen, MPH, graduated from the University of Michigan’s School of Public Health with a
master’s in Occupational Environmental Epidemiology. She completed her thesis on the effects
of heat on hospitalizations in Michigan. She worked with MN Tracking for 2 years as a CSTE
Epidemiology Fellow where she was project coordinator for a follow-up study of the Northeast
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Minneapolis Community Vermiculite Investigation cohort. She currently is an epidemiologist
working on birth defects, pesticides, and climate change, and is developing new Disaster
Epidemiology tools for MDH-HPCD.
Mary Jeanne Levitt, MBC, is the communications coordinator with MN Tracking. She has a
Master’s in Business Communications and has worked for over 20 years in both the public and
non-profit sector in project management of research and training grants, communications and
marketing strategies, focus groups and evaluations of educational needs of public health
professionals. She serves on three institutional review boards, which specialize in academic
research, oncology research, and overall clinical research.
Paula Lindgren, MS, received her Masters of Science degree in Biostatistics from the University
of Minnesota. She works for the Minnesota Department of Health as a biostatistician, and
provides statistical and technical support MN Tracking for data reports, publications, webbased portal dissemination, and presentations in the Chronic Disease and Environmental
Epidemiology section. Ms. Lindgren has also received training in the area of GIS for chronic
disease mapping and analysis. In addition to her work for MN Tracking, she works for various
programs within Chronic Disease and Environmental Epidemiology including the Asthma
program, Center for Occupation Health and Safety, Minnesota Cancer Surveillance System, and
Cancer Control section.
Matthew Montesano, the Data Portal Coordinator with the Minnesota Tracking Program, is
responsible for the Data Portal’s content strategy, ensuring that its utility is maximized through
evidence-based health and science communications practices. He has expertise in
communicating health and science to lay audiences and developing strategic web-based public
health material. He is an advocate for the use of plain language and data visualization
techniques that increase users’ understanding of complex information. He has over 8 years of
nonprofit and public health experience with community programming, research, and
evaluation.
Jessica Nelson, PhD, is an epidemiologist with MN Tracking, working primarily on design,
coordination, and analysis of biomonitoring projects. Jessica received her PhD and MPH in
Environmental Health from the Boston University School of Public Health where her research
involved the epidemiologic analysis of biomonitoring data on perfluorochemicals. Jessica was
the coordinator of the Boston Consensus Conference on Biomonitoring, a project that gathered
input and recommendations on the practice and uses of biomonitoring from a group of Bostonarea lay people.
Christina Rosebush, MPH, is an epidemiologist with MN Tracking. Her work includes the
development and coordination of biomonitoring projects that assess perfluorochemicals (PFCs)
and mercury in Minnesota communities. She also works on collection and statistical analysis of
public health surveillance data for MN Tracking, with a focus on behavioral risk factors.
Christina received her Master’s degree in epidemiology from the University of Minnesota’s
School of Public Health, completing research in PFC biomonitoring for the Minnesota
Department of Health in partial fulfillment of her degree.
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Jeannette M. Sample, MPH, is an epidemiologist with MN Tracking at the Minnesota
Department of Health, working primarily with the collection and statistical analysis of public
health surveillance data for MN Tracking. She also works on research collaborations with
academic partners relating to reproductive outcomes and birth defects. Prior to joining MN
Tracking, she was a CSTE/CDC Applied Epidemiology Fellow with the MDH Birth Defect
Information System. Jeannette received her Master’s degree in epidemiology and biostatistics
from The George Washington University in Washington, DC.
Blair Sevcik, MPH, is an epidemiologist with MN Tracking at the Minnesota Department of
Health, where she works on the collection and statistical analysis of public health surveillance
data for .MN Tracking. Prior to joining MN Tracking in January 2009, she was a student worker
with the MDH Asthma Program. She received her Master of Public Health degree in
epidemiology from University of Minnesota School of Public Health in December 2010.
Chuck Stroebel, MSPH, is the MN Tracking Program Manager. He provides day-to-day direction
for program activities, including: 1) development and implementation of the state network, 2)
development and transport of NCDMs and metadata for the national network, and 3)
collaboration and communication with key EPHT partners and stakeholders. Chuck received a
Masters of Public Health in Environmental Health Sciences from the University of North
Carolina (Chapel Hill). He has over 15 years of expertise in environmental health, including
areas of air quality, pesticides, climate change, risk assessment, and toxicology. Chuck also
played a key role in early initiatives to build tracking capacity at the Minnesota Department of
Health. Currently, he is a member of the IBIS Steering Committee (state network), the MDH
ASTHO Grant Steering Committee (climate change), and the Northland Society of Toxicology. He
also serves on the Minnesota EPHT Technical and Communications Teams.
Janis Taramelli, TTS, is the Community Outreach Coordinator for MN Biomonitoring,
responsible for communications with the MN Tracking Advisory Panel and study participants. A
tobacco treatment specialist, she has 20 years of experience working on research studies,
surveys, group facilitation, and one-on-one counseling in both the public and private sectors.
Her background includes development and coordination of statewide QUITPLAN at Work
programs, metro area QUITPLAN centers, and piloting tobacco cessation and heart healthy
programs for Minnesota’s Sage (Breast and Cervical Cancer Screening) and SagePlus (Heart
Health Screening) programs, funded by the Centers for Disease Control.
Addis Teshome has been an epidemiologist with MN Tracking since September 2014. Her work
involves populating a database of the scientific literature on perflurochemicals (PFCs),
performing statistical analysis of public health data, and developing various elements of the MN
Family Environmental Exposure Tracking project. Prior to joining MN Tracking as a student
worker in June 2014, she held similar positions at MDH’s Center for Occupational Health and on
the Safety and the Autism Spectrum Disorders Public Health Surveillance Report. Addis is
analyzing trends in predictors and outcomes of alcohol consumption among racial/ethnic
subgroups in partial fulfilment of her master’s degree in epidemiology at the University of
Minnesota’s School of Public Health.
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Allan N. Williams, MPH, PhD, is an environmental and occupational epidemiologist in the
Chronic Disease and Environmental Epidemiology Section at the Minnesota Department of
Health. He is the supervisor for the MDH Center for Occupational Health and Safety. For over 25
years, he has worked on issues relating to environmental and occupational cancer, cancer
clusters, work-related respiratory diseases, and the surveillance and prevention of work-related
injuries among adolescents. He has served as the PI on two NIOSH R01 grants, as a coinvestigator on four other federally-funded studies in environmental or occupational health,
and is an adjunct faculty member in the University of Minnesota’s School of Public Health. He
received an MA in Biology from Indiana University, an MPH in Environmental Health and
Epidemiology from the University of Minnesota, and a PhD in Environmental and Occupational
Health from the University of Minnesota.
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Environmental Health Tracking and Biomonitoring Statute
$1,000,000 each year is for environmental health tracking and biomonitoring. Of this amount, $900,000
each year is for transfer to the Minnesota Department of Health. The base appropriation for this
program for fiscal year 2010 and later is $500,000.
144.995 DEFINITIONS; ENVIRONMENTAL HEALTH TRACKING AND BIOMONITORING
given.
(a) For purposes of sections 144.995 to 144.998, the terms in this section have the meanings
(b) "Advisory panel" means the Environmental Health Tracking and Biomonitoring Advisory
Panel established under section 144.998.
(c) "Biomonitoring" means the process by which chemicals and their metabolites are identified
and measured within a biospecimen.
(d) "Biospecimen" means a sample of human fluid, serum, or tissue that is reasonably available
as a medium to measure the presence and concentration of chemicals or their metabolites in a human
body.
(e) "Commissioner" means the commissioner of the Department of Health.
(f) "Community" means geographically or nongeographically based populations that may
participate in the biomonitoring program. A "nongeographical community" includes, but is not limited
to, populations that may share a common chemical exposure through similar occupations, populations
experiencing a common health outcome that may be linked to chemical exposures, populations that
may experience similar chemical exposures because of comparable consumption, lifestyle, product use,
and subpopulations that share ethnicity, age, or gender.
(g) "Department" means the Department of Health.
(h) "Designated chemicals" means those chemicals that are known to, or strongly suspected of,
adversely impacting human health or development, based upon scientific, peer-reviewed animal,
human, or in vitro studies, and baseline human exposure data, and consists of chemical families or
metabolites that are included in the federal Centers for Disease Control and Prevention studies that are
known collectively as the National Reports on Human Exposure to Environmental Chemicals Program
and any substances specified by the commissioner after receiving recommendations under section
144.998, subdivision 3, clause (6).
(i) "Environmental hazard" means a chemical or other substance for which scientific, peerreviewed studies of humans, animals, or cells have demonstrated that the chemical is known or
reasonably anticipated to adversely impact human health.
(j) "Environmental health tracking" means collection, integration, analysis, and dissemination of
data on human exposures to chemicals in the environment and on diseases potentially caused or
aggravated by those chemicals.
144.996 ENVIRONMENTAL HEALTH TRACKING; BIOMONITORING.
Subdivision 1. Environmental health tracking. In cooperation with the commissioner of the
Pollution Control Agency, the commissioner shall establish an environmental health tracking program
to:
(1) coordinate data collection with the Pollution Control Agency, Department of Agriculture,
University of Minnesota, and any other relevant state agency and work to promote the sharing of and
access to health and environmental databases to develop an environmental health tracking system for
Minnesota, consistent with applicable data practices laws;
(2) facilitate the dissemination of aggregate public health tracking data to the public and
researchers in accessible format;
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(3) develop a strategic plan that includes a mission statement, the identification of core
priorities for research and epidemiologic surveillance, and the identification of internal and external
stakeholders, and a work plan describing future program development and addressing issues having to
do with compatibility with the Centers for Disease Control and Prevention's National Environmental
Public Health Tracking Program;
(4) develop written data sharing agreements as needed with the Pollution Control Agency,
Department of Agriculture, and other relevant state agencies and organizations, and develop additional
procedures as needed to protect individual privacy;
(5) organize, analyze, and interpret available data, in order to:
(i) characterize statewide and localized trends and geographic patterns of population-based
measures of chronic diseases including, but not limited to, cancer, respiratory diseases, reproductive
problems, birth defects, neurologic diseases, and developmental disorders;
(ii) characterize statewide and localized trends and geographic patterns in the occurrence of
environmental hazards and exposures;
(iii) assess the feasibility of integrating disease rate data with indicators of exposure to the
selected environmental hazards such as biomonitoring data, and other health and environmental data;
(iv) incorporate newly collected and existing health tracking and biomonitoring data into efforts
to identify communities with elevated rates of chronic disease, higher likelihood of exposure to
environmental hazards, or both;
(v) analyze occurrence of environmental hazards, exposures, and diseases with relation to
socioeconomic status, race, and ethnicity;
(vi) develop and implement targeted plans to conduct more intensive health tracking and
biomonitoring among communities; and
(vii) work with the Pollution Control Agency, the Department of Agriculture, and other relevant
state agency personnel and organizations to develop, implement, and evaluate preventive measures to
reduce elevated rates of diseases and exposures identified through activities performed under sections
144.995 to 144.998; and
(6) submit a biennial report to the chairs and ranking members of the committees with
jurisdiction over environment and health by January 15, beginning January 15, 2009, on the status of
environmental health tracking activities and related research programs, with recommendations for a
comprehensive environmental public health tracking program.
Subd. 2. Biomonitoring. The commissioner shall:
(1) conduct biomonitoring of communities on a voluntary basis by collecting and analyzing
biospecimens, as appropriate, to assess environmental exposures to designated chemicals;
(2) conduct biomonitoring of pregnant women and minors on a voluntary basis, when
scientifically appropriate;
(3) communicate findings to the public, and plan ensuing stages of biomonitoring and disease
tracking work to further develop and refine the integrated analysis;
(4) share analytical results with the advisory panel and work with the panel to interpret results,
communicate findings to the public, and plan ensuing stages of biomonitoring work; and
(5) submit a biennial report to the chairs and ranking members of the committees with
jurisdiction over environment and health by January 15, beginning January 15, 2009, on the status of the
biomonitoring program and any recommendations for improvement.
Subd. 3. Health data. Data collected under the biomonitoring program are health data under
section 13.3805.
144.997 BIOMONITORING PILOT PROGRAM.
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Subdivision 1. Pilot program. With advice from the advisory panel, and after the program
guidelines in subdivision 4 are developed, the commissioner shall implement a biomonitoring pilot
program. The program shall collect one biospecimen from each of the voluntary participants. The
biospecimen selected must be the biospecimen that most accurately represents body concentration of
the chemical of interest. Each biospecimen from the voluntary participants must be analyzed for one
type or class of related chemicals. The commissioner shall determine the chemical or class of chemicals
to which community members were most likely exposed. The program shall collect and assess
biospecimens in accordance with the following:
(1) 30 voluntary participants from each of three communities that the commissioner identifies
as likely to have been exposed to a designated chemical;
(2) 100 voluntary participants from each of two communities:
(i) that the commissioner identifies as likely to have been exposed to arsenic; and (ii) that the
commissioner identifies as likely to have been exposed to mercury; and
(3) 100 voluntary participants from each of two communities that the commissioner identifies as
likely to have been exposed to perfluorinated chemicals, including perfluorobutanoic acid.
Subd. 2. Base program. (a) By January 15, 2008, the commissioner shall submit a report on the
results of the biomonitoring pilot program to the chairs and ranking members of the committees with
jurisdiction over health and environment.
(b) Following the conclusion of the pilot program, the commissioner shall:
(1) work with the advisory panel to assess the usefulness of continuing biomonitoring among
members of communities assessed during the pilot program and to identify other communities and
other designated chemicals to be assessed via biomonitoring;
(2) work with the advisory panel to assess the pilot program, including but not limited to the
validity and accuracy of the analytical measurements and adequacy of the guidelines and protocols;
(3) communicate the results of the pilot program to the public; and
(4) after consideration of the findings and recommendations in clauses (1) and (2), and within
the appropriations available, develop and implement a base program.
Subd. 3. Participation. (a) Participation in the biomonitoring program by providing biospecimens
is voluntary and requires written, informed consent. Minors may participate in the program if a written
consent is signed by the minor's parent or legal guardian. The written consent must include the
information required to be provided under this subdivision to all voluntary participants.
(b) All participants shall be evaluated for the presence of the designated chemical of interest as
a component of the biomonitoring process. Participants shall be provided with information and fact
sheets about the program's activities and its findings. Individual participants shall, if requested, receive
their complete results. Any results provided to participants shall be subject to the Department of Health
Institutional Review Board protocols and guidelines. When either physiological or chemical data
obtained from a participant indicate a significant known health risk, program staff experienced in
communicating biomonitoring results shall consult with the individual and recommend follow-up steps,
as appropriate. Program administrators shall receive training in administering the program in an ethical,
culturally sensitive, participatory, and community-based manner.
Subd. 4. Program guidelines. (a) The commissioner, in consultation with the advisory panel,
shall develop:
(1) protocols or program guidelines that address the science and practice of biomonitoring to be
utilized and procedures for changing those protocols to incorporate new and more accurate or efficient
technologies as they become available. The commissioner and the advisory panel shall be guided by
protocols and guidelines developed by the Centers for Disease Control and Prevention and the National
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Biomonitoring Program;
(2) guidelines for ensuring the privacy of information; informed consent; follow-up counseling
and support; and communicating findings to participants, communities, and the general public. The
informed consent used for the program must meet the informed consent protocols developed by the
National Institutes of Health;
(3) educational and outreach materials that are culturally appropriate for dissemination to
program participants and communities. Priority shall be given to the development of materials
specifically designed to ensure that parents are informed about all of the benefits of breastfeeding so
that the program does not result in an unjustified fear of toxins in breast milk, which might inadvertently
lead parents to avoid breastfeeding. The materials shall communicate relevant scientific findings; data
on the accumulation of pollutants to community health; and the required responses by local, state, and
other governmental entities in regulating toxicant exposures;
(4) a training program that is culturally sensitive specifically for health care providers, health
educators, and other program administrators;
(5) a designation process for state and private laboratories that are qualified to analyze
biospecimens and report the findings; and
(6) a method for informing affected communities and local governments representing those
communities concerning biomonitoring activities and for receiving comments from citizens concerning
those activities.
(b) The commissioner may enter into contractual agreements with health clinics, communitybased organizations, or experts in a particular field to perform any of the activities described under this
section.
144.998 ENVIRONMENTAL HEALTH TRACKING AND BIOMONITORING ADVISORY PANEL.
Subdivision 1. Creation. The commissioner shall establish the Environmental Health Tracking
and Biomonitoring Advisory Panel. The commissioner shall appoint, from the panel's membership, a
chair. The panel shall meet as often as it deems necessary but, at a minimum, on a quarterly basis.
Members of the panel shall serve without compensation but shall be reimbursed for travel and other
necessary expenses incurred through performance of their duties. Members appointed by the
commissioner are appointed for a three-year term and may be reappointed. Legislative appointees
serve at the pleasure of the appointing authority.
Subd. 2. Members. (a) The commissioner shall appoint eight members, none of whom may be
lobbyists registered under chapter 10A, who have backgrounds or training in designing, implementing,
and interpreting health tracking and biomonitoring studies or in related fields of science, including
epidemiology, biostatistics, environmental health, laboratory sciences, occupational health, industrial
hygiene, toxicology, and public health, including:
(1) at least two scientists representative of each of the following:
(i) nongovernmental organizations with a focus on environmental health, environmental justice,
children's health, or on specific chronic diseases; and
(ii) statewide business organizations; and
(2) at least one scientist who is a representative of the University of Minnesota.
(b) Two citizen panel members meeting the scientific qualifications in paragraph (a) shall be
appointed, one by the speaker of the house and one by the senate majority leader.
(c) In addition, one representative each shall be appointed by the commissioners of the
Pollution Control Agency and the Department of Agriculture, and by the commissioner of health to
represent the department's Health Promotion and Chronic Disease Division.
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Subd. 3. Duties. The advisory panel shall make recommendations to the commissioner and the
legislature on:
(1) priorities for health tracking;
(2) priorities for biomonitoring that are based on sound science and practice, and that will
advance the state of public health in Minnesota;
(3) specific chronic diseases to study under the environmental health tracking system;
(4) specific environmental hazard exposures to study under the environmental health tracking
system, with the agreement of at least nine of the advisory panel members;
(5) specific communities and geographic areas on which to focus environmental health tracking
and biomonitoring efforts;
(6) specific chemicals to study under the biomonitoring program, with the agreement of at least
nine of the advisory panel members; in making these recommendations, the panel may consider the
following criteria:
(i) the degree of potential exposure to the public or specific subgroups, including, but not
limited to, occupational;
(ii) the likelihood of a chemical being a carcinogen or toxicant based on peer-reviewed health
data, the chemical structure, or the toxicology of chemically related compounds;
(iii) the limits of laboratory detection for the chemical, including the ability to detect the
chemical at low enough levels that could be expected in the general population;
(iv) exposure or potential exposure to the public or specific subgroups;
(v) the known or suspected health effects resulting from the same level of exposure based on
peer-reviewed scientific studies;
(vi) the need to assess the efficacy of public health actions to reduce exposure to a chemical;
(vii) the availability of a biomonitoring analytical method with adequate accuracy, precision,
sensitivity, specificity, and speed;
(viii) the availability of adequate biospecimen samples; or
(ix) other criteria that the panel may agree to; and
(7) other aspects of the design, implementation, and evaluation of the environmental health
tracking and biomonitoring system, including, but not limited to:
(i) identifying possible community partners and sources of additional public or private funding;
(ii) developing outreach and educational methods and materials; and
(iii) disseminating environmental health tracking and biomonitoring findings to the public.
Subd. 4. Liability. No member of the panel shall be held civilly or criminally liable for an act or
omission by that person if the act or omission was in good faith and within the scope of the member's
responsibilities under sections 144.995 to 144.998.
INFORMATION SHARING.
On or before August 1, 2007, the commissioner of health, the Pollution Control Agency,
and the University of Minnesota are requested to jointly develop and sign a memorandum of
understanding declaring their intent to share new and existing environmental hazard, exposure,
and health outcome data, within applicable data privacy laws, and to cooperate and
communicate effectively to ensure sufficient clarity and understanding of the data by divisions
and offices within both departments. The signed memorandum of understanding shall be
reported to the chairs and ranking members of the senate and house of representatives
committees having jurisdiction over judiciary, environment, and health and human services.
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Effective date: July 1, 2007
This document contains Minnesota Statutes, sections 144.995 to 144.998, as these sections were
adopted in Minnesota Session Laws 2007, chapter 57, article 1, sections 143 to 146. The appropriation
related to these statutes is in chapter 57, article 1, section 3, subdivision 4. The paragraph about
information sharing is in chapter 57, article 1, section 169.
Current Appropriation for EHTB
Office of the Revisor of Statutes
88th Legislature, 2013, Regular Session,
Chapter 114 Minnesota Session Laws
Subd. 2. Water
25,453,000
25,454,000
General
3,737,000
3,737,000
State Government Special Revenue
75,000
75,000
Environmental
21,641,000
21,642,000
Appropriations by Fund
$913,000 the first year and $913,000 the second year are from the environmental fund to continue
perfluorochemical biomonitoring in eastern metropolitan communities, as recommended by the
Environmental Health Tracking and Biomonitoring Advisory Panel, and address other environmental
health risks, including air quality. Of this amount, $812,000 the first year and $812,000 the second year
are for transfer to the Department of Health.
NEW 2014 Legislation
20.28 Sec. 13. CLARIFICATION OF CONTINUED EXISTENCE.
20.29 This section clarifies that the groups listed in this section did not expire June 30,
20.30 2009. Actions taken by the groups listed in this section and public funds spent on behalf
20.31 of these groups since June 30, 2009, are valid:
21.1
(1) Medical Assistance Drug Formulary Committee, created in Minnesota Statutes,
21.2
section 256B.0625, subdivision 13c:
21.3
(2) Environmental Health Tracking & Biomonitoring Advisory Panel, created
21.4
in Minnesota Statutes, section 144.998:
21.5
(3) Water Supply Systems and Wastewater Treatment Facilities Advisory Council,
21.6
created in Minnesota Statutes, section 115.741; and
21.7
(4) Prescription Electronic Reporting Advisory Committee, created in Minnesota
21.8
Statutes, section 152.126, subdivision 3,
21.9
EFFECTIVE DATE: This section is effective the day following final enactment
21.10 and applies retroactively from June 30, 2009.
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