Minnesota Department of Health
Environmental Health Tracking and Biomonitoring
Advisory Panel Meeting
December 8, 2009
1:00 p.m. – 4:00 p.m.
Snelling Office Park
Red River Room
1645 Energy Park Drive
St. Paul, Minnesota
Meeting agenda
Minnesota Department of Health
Environmental Health Tracking and Biomonitoring Advisory Panel Meeting
December 8, 2009
1:00 p.m. – 4:00 p.m.
Red River Room at Snelling Office Park
1645 Energy Park Drive, St. Paul, MN
Time
Agenda item
Presenter(s)
1:00
Welcome and
introductions
Beth Baker, Chair
Item type/Anticipated outcome
BIOMONITORING
1:05
East metro PFC
biomonitoring study
water-blood analysis
Adrienne Kari
Discussion item.
Staff will present new data from an analysis
of the relationship between PFC levels in
water and PFC levels in blood. Panel
members are invited to ask questions and
provide input on the new analysis. In
particular, panel members are asked to
respond to the following questions:




1:35
East metro PFC
biomonitoring follow-up
study
Jean Johnson
Adrienne Kari
<<i>>
What are the most important findings?
Are the interpretations and conclusions
appropriate?
Are there methodological limitations
that should be emphasized?
Are there additional analyses of the data
that should be pursued?
Discussion item.
Staff will share some preliminary
information about planning for a PFC
follow-up study. The advisory panel is
asked to provide suggestions to help guide
the development of a PFC follow-up study.
In particular, the panel is invited to provide
input on the following questions:
Time
Agenda item
Presenter(s)
Item type/Anticipated outcome


2:35
Break
2:50
Biomonitoring updates
Adrienne Kari
 Lake Superior mercury Pat McCann
biomonitoring study
 Riverside prenatal
biomonitoring study
 South Minneapolis
children’s arsenic study
After reviewing the list of potential
research questions and abstracts, what is
the degree to which each research
question is feasible, scientifically
valuable, and responsive to community
needs?
Are there additional research questions
that should be considered?
Information sharing.
Staff will provide updates on the
biomonitoring projects that are still
underway. Panel members are invited to ask
questions or provide input on these items.
TRACKING
3:05
EPHT pesticides
indicators
Deanna Scher
Naomi Shinoda
Joe Zachmann
<<ii>>
Discussion item.
Staff will describe progress and challenges
in developing the new national pesticides
indicators. Panel members are asked to
provide suggestions to help guide further
development of the national indicators and
to help set priorities for Minnesota-specific
indicators related to pesticides. In particular,
the panel is invited to provide input on the
following questions:
 After reviewing the available sources of
national and state-level pesticide data,
what are the data gaps?
 National pesticides indicators will be
formed through a consensus building
process and will draw on data sources
that are available across many or all states.
 Regardless of what pesticides indicators
and data sources are adopted by the
national EPHT Network, what
pesticides-related information is
important for Minnesota to track as a
state priority?
Time
Agenda item
Presenter(s)
Item type/Anticipated outcome
3:35
Tracking updates:
 IBIS project
Michelle DeMist
Chuck Stroebel
Information sharing.
Panel member
recruitment
Michonne Bertrand
New business
Beth Baker
Staff will describe progress made and plans
for developing Minnesota’s web-based
information system. Panel members are
invited to ask questions or provide input on
this item.
OTHER
3:50
3:55
Information sharing.
Staff will describe the status of recruitment
efforts to fill vacant panel seats. Panel
members are invited to ask questions or
provide input.
Discussion item.
The chair will invite panel members to
suggest topics for future discussion.
4:00
Adjourn
Next meeting:
Tuesday, March 9, 2010, 1-4 p.m. Red River Room, Snelling Office Park
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<<iv>>
Meeting Materials for December 8, 2009
Environmental Health Tracking & Biomonitoring Advisory Panel
Table of Contents
Agenda........................................................................................................................................... i
Table of contents ........................................................................................................................v
Materials related to specific agenda items
East metro PFC biomonitoring study: Water-blood analysis
Section overview: East metro PFC biomonitoring study: Water-blood analysis .....................1
Analysis of PFC drinking water and other variables as predictors of PFC Blood Levels:
Preliminary results .....................................................................................................................3
MN East Metro Perfluorochemical Biomonitoring Study Results: Executive Summary........11
East metro PFC biomonitoring follow-up study
Section overview: East metro PFC biomonitoring follow-up study........................................15
East metro PFC biomonitoring follow-up study: Potential research questions .......................17
Abstracts and other background material related to potential research questions ...................19
Biomonitoring updates
Section overview: Biomonitoring updates...............................................................................29
Status update on the Lake Superior Mercury Biomonitoring Study........................................31
Status update on the Riverside Prenatal Biomonitoring Study................................................32
Status update on the South Minneapolis Children’s Arsenic Study ........................................33
EPHT pesticides indicators
Section overview: EPHT pesticides indicators ........................................................................35
Pesticide indicator content work group (CWG) update...........................................................37
Preliminary list of national and state-level data sources for pesticides indicators (DRAFT)..39
Data inventories for national data sources (DRAFT) ..............................................................41
Minnesota data inventories for state-level data sources (DRAFT)..........................................57
EPHT Pesticide Indicator Content Work Group Team Proposal (DRAFT)............................87
Tracking updates
Section overview: Tracking updates........................................................................................95
Status update on MN EPHT Web-Based Information System (IBIS).....................................97
Other information
Section overview: Other information.............................................................................................99
Minnesota Environmental Public Health Tracking & Biomonitoring Presentations, Posters and
Publications..................................................................................................................................101
Local, national and global biomonitoring and tracking news…..................................................103
-v-
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- vi -
Section overview: East Metro PFC Biomonitoring Study
Water-Blood Analysis
As reported previously, Adrienne Kari, Biomonitoring Coordinator, has been conducting an
analysis of the relationship between PFC levels in water and PFC levels in blood for a subset of
participants in the East Metro PFC Biomonitoring Study. The preliminary results are attached.
She will make a brief presentation at the advisory panel meeting on December 8 and will invite
panel members’ comments and suggestions on the analysis.
The following items are included in this section of the meeting materials:


Analysis of PFC drinking water and other variables as predictors of PFC Blood Levels:
Preliminary results
East Metro Perfluorochemical Biomonitoring Study: Executive summary (Note: The
executive summary is provided for panel members who wish to review the results of the
earlier analysis.)
ACTION NEEDED: Panel members are invited to ask questions and provide input on the new
analysis. In particular, panel members are asked to respond to the following questions:




What are the most important findings?
Are the interpretations and conclusions appropriate?
Are there methodological limitations that should be emphasized?
Are there additional analyses of the data that should be pursued?
No formal vote is anticipated.
1
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2
Analysis of PFC drinking water and other variables as predictors of PFC
Blood Levels: Preliminary results
In 2009 the Minnesota Department of Health (MDH) conducted a biomonitoring project to
measure seven PFC compounds in the blood of a random sample of 196 people from two east
metro area communities, including 98 people whose homes were served by private wells.
PFOA, PFOS, and PFHxS were found in the blood of all 196 people. PFBA was found in the
blood of 55 people (28%), and PFBS was found in 5 people (3%). PFPeA and PFHxA were not
found in any of the participants. The average blood levels for PFOA, PFOS, and PFHxS were all
higher in the study communities than they were in the general United States population.
MDH epidemiologist, Adrienne Kari, conducted a regression analysis examining the available
data on PFC levels measured in private well water as a measure of drinking water exposure and
the relationship with PFC blood levels among participants in the private well community. The
analysis was limited to two analytes, PFOA and PFOS, as the other PFC analytes were below the
level of detection in greater than 70% of the water and/or blood samples.
Method for estimating drinking water exposure level among project participants
The analytical results for previous monitoring of PFC levels in private well water in the study
community were provided by MDH Site Assessment and Consultation (SAC) Unit staff. Well
water samples were collected between 2005 and 2008, during the time when the extent of the
contamination was still being discovered and well sampling areas were being expanded. Some
private wells were only tested between 2005 and 2006, before a filter was installed or the
property was connected to municipal water. Other properties were first sampled in 2006 or
2007. Between 2006 and 2007 laboratory method detection limits improved and some wells that
had previously been below levels of detection were later found to have detectable levels.
Due to the variations in the available data for study participants, MDH examined two variables
for assessing past PFOA and PFOS drinking water exposure among participants: 1) the highest
level found in a given well in any available sample, and 2) the average level found in all
available samples from a given well (2005-2008). The distributions for the two estimates
(average and highest value) of drinking water exposure for the 98 participants are shown in
Figures 1-4.
Method for estimating drinking water exposure cessation time
An important factor in interpreting the relationship between drinking water exposure and blood
level in our study group is the amount of time that has passed since each study participant
stopped using their private well for drinking water and the date when the blood sample was
collected (referred to here as the “cessation time”). Although participants were asked about
their current drinking water source in a brief questionnaire given to study participants at the time
of recruitment, they were not specifically asked about the date when they stopped using their
well for drinking water. In an effort to estimate this date for each participant, MDH staff
reviewed available records for the following dates: 1) date a well water monitoring results letter
was mailed to the well owner/household, 2) date a drinking water advisory letter was mailed
(advising the homeowner to use an alternative drinking water source), and 3) date when a home
actually received an alternative source (bottled water was provided, a filter was installed, or a
home was hooked up to municipal water.)
3
All 98 participants received a results letter and 83 received an advisory letter, and these dates
provided the most consistent estimate of a cessation date. Some participants may have changed
their drinking water habits voluntarily when news of the water contamination in the community
was first released; however, we assume that most participants changed to an alternative water
source upon receiving a letter from MDH advising them not to drink their well water. For the 15
homes that did not receive an advisory letter, we used the date of the monitoring results letter to
estimate cessation time. This measure should be considered a proxy for actual exposure
cessation time. It should also be noted that other current sources of exposures (dietary or
consumer product use, for example) are assumed to have continued for most participants.
Cessation time was estimated for each participant as the number of months that passed between
the date of the drinking water advisory/results letter and the date of the blood draw. The
average cessation time was 27 months (range 0-45 months, median 29 months) for the 98
participants. One participant reported to us that she/he still used their well water for drinking.
Regression model results
A systematic regression analysis was conducted to measure the relationship between each of the
water exposure variables and the PFC blood level. In addition to highest and average PFC
measures in the water and exposure cessation time, the following additional predictor variables
were examined: participant’s age, sex, length of residence, and 3M employment. Multiple
models were created to test the contribution of each exposure measure and covariate as a
predictor of the PFC blood level. The average PFOA or PFOS level in a well was found to be a
better predictor of blood PFOA and PFOS levels than the highest PFOA or PFOS water level.
Results in Table 1 below show the beta coefficients and the square of the correlation coefficients
for the simple and final models. Scatterplots showing the relationships between PFC water and
blood levels (both linear and log transformed) are shown in Figures 5-8.
Table 1. Regression Model Results for Predictors of PFOA and PFOS Serum Levels
Simple PFOA Model: Average PFOA water level and blood level
Log blood PFOA level = β0 + β1 (log water average PFOA level)
β 0 = 3.39 β1 = .635 β1 p value < .0001
R2 = .3095 adj R2 = .3023
Final PFOA Model: Average PFOA water level, age and blood level
Log blood PFOA level = β0 + β1 (log water average PFOA level) + β2 (age)
β 0 = 1.87 β1 = .658 β2 = .029
β1 p value < .0001 β2 p value <.0001
R2 = .4295 adj R2 = .4175
Simple PFOS Model: Log average PFOS water level and log blood level
Log blood PFOS level = β0 + β1 (log water average PFOS level)
β 0 = 4.128 β1 = .4109 β1 p value < .0001
R2 = .3191 adj R2 = .3120
Final PFOS Model: Log average PFOS water level, age, sex, and log blood level
Log blood PFOS level = β0 + β1 (log water average PFOS level) + β2 (age) + β3 (sex)
β 0 = 2.99 β1 = .42 β2 = .02 β3 = .39
β1 p value < .0001 β2 p value = .0035 β3 p value = .0046
R2 = .4212 adj R2 = .4027
4
Interpretation and conclusions
We found that the PFOA and PFOS drinking water levels were strongly correlated with PFOA
and PFOS levels in blood. PFC drinking water levels alone accounted for 30% of the variability
seen in people’s blood levels. After testing with other covariates, drinking water level and age
were both significant predictors of blood PFOA levels and together they accounted for 42% of
the variability in blood PFOA. Drinking water level, age and gender were significant predictors
of PFOS levels in blood and together they accounted for 40% of the variability in blood PFOS.
Other covariates tested and found to be not significant predictors of blood levels in the
multivariate models were cessation time, length of residence, and history of 3M employment.
Based on these findings it is likely that PFOA and PFOS blood levels in the study group will
decline over the next several years due to the alternative water supplies now in place and the
cessation of exposure to contaminated drinking water. Unless other unique sources of exposure
are identified in the community, blood PFC levels in the study group should approach levels
found in the general US population. General population exposures measured in people are likely
due to continued exposure from other sources such as consumer product use (stain-resistant
treated products, stain-resistant sprays, coated paper products, etc.) and dietary sources.
5
Figure 1: Average Drinking Water PFOA Exposure Level (ng/mL) for 98 Project
Participants Estimated From Private Well Samples Collected in 2005 through 2008
60
Geomean = .29 ng/mL
Range = .035 – 1.87 ng/mL
40
30
20
10
Average PFOA Water Levels (ng/ml)
6
.2 5
<2
=
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1.7
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Number of Wells
50
Figure 2: Highest Drinking Water PFOA Exposure Level (ng/mL) for 98 Project
Participant Estimated From Private Well Samples Collected in 2005 through 2008
60
Geomean = .36 ng/mL
Range = .035 – 3.0 ng/mL
40
30
20
10
7
<3
.2 5
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High PFOA Water Levels (ng/ml)
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Number of Wells
50
Figure 3: Average Drinking Water PFOS Exposure Level (ng/mL) for 98 Project
Participant Estimated From Private Well Samples Collected in 2005 through 2008
60
Geomean = .22 ng/mL
Range = .035 – 2.47 ng/mL
Number of Wells
50
40
30
20
10
<2
.7 5
2 .5
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Average PFOS Water Levels (ng/mL)
Figure 4: Highest Drinking Water PFOS Exposure Level (ng/mL) for 98 Project
Participant Estimated From Private Well Samples Collected in 2005 through 2008
60
Geomean = .26 ng/mL
Range = .035 – 3.5 ng/mL
40
30
20
10
8
<3
.75
3.5
3.5
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High PFOS Water Levels (ng/ml)
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Number of Wells
50
Figure 5. Scatterplot of Average PFOA Water Level and PFOA Blood Level for 98 Project
Participants in Private Well Water Community
2
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PFOA Water Concentration ppb
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Figure 6. Scatterplot of Log Average PFOA Water Level vs. Log PFOA Blood Level for 98
Project Participants in Private Well Water Community
Log PFOA Water Concentration ppb
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1000
Figure 7: Scatterplot of Average PFOS Water Levels vs. PFOS Blood Levels in 98 Project
Participants from Private Well Water Community
PFOS Water Concentration ppb
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Figure 8: Scatterplot of Log of Average PFOS Water Level vs. Log of PFOS Blood Level in
98 Project Participants from Private Well Water Community
Log PFOS Water Concentration ppb
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East Metro Perfluorochemical Biomonitoring Study Results: EXECUTIVE
SUMMARY
In 2007 the Minnesota Legislature enacted legislation directing the Minnesota Department of
Health (MDH) to complete a series of biomonitoring pilot projects. These projects were directed
and implemented to provide MDH with the experience and knowledge to create a state
biomonitoring program by building both laboratory and epidemiological capacities. One of these
projects was to investigate the range and distribution of perfluorinated chemicals (PFCs) in 100
individuals from each of two communities likely to have been exposed.
Perfluorochemical contamination of private and municipal drinking water wells in Washington
County, east of the Minneapolis-St. Paul metropolitan area (also referred to as “East Metro”),
was first discovered in 2004 during an assessment of ground water contamination from nearby
waste disposal facilities by the Minnesota Pollution Control Agency (MPCA) and MDH1.
Drinking water supplies were analyzed for seven types of PFCs contaminants including but not
limited to perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), and
perfluorobutanoic acid (PFBA).
MDH selected two Washington County East Metro communities, Oakdale Municipal Water
Supply recipients and private well owners in Lake Elmo and Cottage Grove with known
contamination, to conduct the East Metro PFC Biomonitoring Pilot Project.
MDH defined
these communities by drinking water source as follows:
1. People currently living in households in Lake Elmo and Cottage Grove with a private
well with PFOA and/or PFOS contamination above trace levels (>0.01 ppb) in at least one well
water sample, and
2. People currently living in households served by the Oakdale Municipal Water Supply.
In the municipal water community (Oakdale), 500 homes were randomly selected from the
municipal water billing records to receive a household survey to identify eligible adults living in
the household. For the private well water community (Lake Elmo/Cottage Grove), all 169 homes
identified with contaminated wells received the household survey. Eligible individuals were
defined as household residents over 20 years of age living in the home prior to Jan. 1, 2005.
11
From the survey respondents in each community, a list of eligible residents was compiled and
100 people were randomly selected and invited to participate. If anyone declined participation, a
replacement individual was randomly selected. The project required participants to provide a
single 20 cc blood draw at a local clinic and answer a short telephone survey. Specimens were
collected from October 2008 through January 2009. At the conclusion of the project 98 people
from each community had completed all of the project requirements for a total of 196
participants. Project protocols were reviewed by the Environmental Health Tracking and
Biomonitoring (EHTB) Advisory Panel, presented to the community at public meetings for
community acceptance, and approved by the MDH Institutional Review Board.
Age and length of residence in the home were comparable among participants from the two
communities. In both communities, the average age of the participants was 53 years (range 2086). The average length of residence in the home was 18 years (range 4-62) in Oakdale and 20
years (range 4-60) in Lake Elmo and Cottage Grove. In both communities, more females
(n=108) than males participated (n=88).
The blood specimens provided by participants were collected at 2 local clinics according to
protocol and brought to the MDH Public Health Laboratory (PHL), where each specimen was
analyzed for the 7 PFCs previously analyzed for in water. Analytical methods used were
developed and based on methods utilized by the CDC for the National Health and Nutrition
Examination Survey (NHANES). Of the 7 types of PFCs analyzed for in the 196 blood
specimens; 3 PFCs (PFOA, PFOS, and PFHxs) were detected in all specimens, 1 PFC (PFBA)
was detected in 55 specimens (28%), 1 PFC (PFBS) was detected in 5 specimens (3%), and the
final 2 types of PFCs (PFPeA and PFHxA) were below the limit of detection (0.1 ng/mL) for all
196 specimens.
Concentrations of PFOA, PFOS, and PFHxS in the population sample were log-normally
distributed and geometric means were calculated. Levels did not differ significantly between the
two communities. In the combined communities, PFOA had a geometric mean of 15.4 ppb
(range 1.6-177ppb), PFOS had a geometric mean of 35.9 ppb (range 3.2-448 ppb), and PFHxS
had a geometric mean of 8.4 ppb (range 0.32-316 ppb). As with most other studies, mean levels
for PFOA, PFOS, and PFHxS were found to be higher in males than females and increased with
12
age. These PFC levels were also highly correlated with each other. Increasing length of residence
in the home was found to be positively associated with PFOA and PFHxS, but not PFOS.
PFC levels found in the 196 adults from the two communities were moderately elevated in
comparison with results reported for the US general population2 but comparable to or lower than
levels found in other studies of communities exposed via drinking water.
However,
comparisons with other general population and community studies are difficult to interpret due to
differing population characteristics and time periods involved. 3M ceased production of
ammonium PFOA in 2000 and as a result general population levels have been declining3.
Consequently, PFC levels will be expected to vary in populations when tested during different
time periods. As expected, community levels found in this study were much lower than levels
found in occupational studies of PFC manufacturing workers.
Additional analysis of these findings along with analyses of drinking water PFC contaminant
levels and community PFC serum levels will be completed in a follow up to this report. Any
further determination of routes and sources of exposure would require a more extensive
investigation and was beyond the scope of this pilot project. MDH staff will present these
findings to the community and solicit recommendations from the community for further public
health action in response to the project results.
The Environmental Health Tracking and Biomonitoring Science Advisory Panel recommended
on June 2, 2009 after viewing of the pilot project preliminary data, that follow up biomonitoring
be completed at a later date with these same communities to measure change in levels over time.
Blood levels of PFCs in the population are expected to decrease due to the actions that have been
taken to remove PFC from the drinking water in these communities.
The purpose and intent of this pilot project was to inform a future biomonitoring program for the
state of Minnesota. The project succeeded in this respect and the information and experience it
provided are necessary and valuable to the success of the Environmental Health Tracking and
Biomonitoring program at MDH.
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Section overview: East Metro PFC Biomonitoring
Follow-up Study
At the June 2, 2009, EHTB advisory panel meeting, the preliminary results of the East
Metro PFC Biomonitoring Study were presented and discussed. Based on the findings of
elevated PFC levels in the community (compared to the US population NHANES data), a
recommendation was voted on and passed by the advisory panel that additional
biomonitoring of the East Metro community for PFCs be conducted for the purpose of
understanding more about PFC exposures and for tracking the efficacy of the drinking
water interventions that are now in place.
The advisory panel’s recommendation was supported by the community members when
results were presented at community meetings (July 21 and 22, 2009).
The recommendation was also presented to the EHTB steering committee. The steering
committee has agreed that MDH staff should begin planning for a follow-up
biomonitoring project, with a goal of conducting specimen collection for the follow-up
project in 2010, two years after the initial pilot project specimens were collected.
Available EHTB state funding for the project in FY2010-11 is limited. Given the
currently available funds, a limited follow-up study could be conducted with the original
group of participants (longitudinal study design); 186 participants consented to being
contacted again in the future. If one or more research questions are selected that would
require a different study design or additional data collection, then additional funding
support may be needed in order to implement the study. Implementation of any follow-up
study is contingent on the continued availability of funds.
A PFC biomonitoring project team has been formed to discuss and plan for the follow-up.
Several possible research questions have been drafted for the follow-up study. Panel
members are asked to review and comment on these questions as to their feasibility,
scientific value, and responsiveness to community needs. Panel members are also invited
to pose other important questions that a follow-up study could answer.
The following items are included in this section of the meeting materials:
 East Metro PFC Biomonitoring Follow-Up Study: Potential Research Questions
 Abstracts and other background material related to potential research questions
ACTION NEEDED: The advisory panel is asked to provide suggestions to help guide
the development of a PFC follow-up study. In particular, the panel is invited to provide
input on the following questions:
 After reviewing the list of potential research questions and abstracts, what is the
degree to which each research question is feasible, adds scientific value, and is
responsive to community needs?
Are there additional research questions that should be considered?
No formal vote is anticipated.
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16
East Metro PFC Biomonitoring Follow-Up Study: Potential Research
Questions
1. What are current (2010) levels of PFOA, PFOS, and PFHxS in the study population
and how do they compare to levels that were measured in 2008? (Note: PFOA,
PFOS, and PFHxS are the only PFCs that were detected in all study participants.)
2. What is the rate of decline for PFOA, PFOS, and PFHxS blood levels in the study
population? What is the half life of PFOA, PFOS, and PFHxS in this population?
3. In addition to the drinking water, what other sources of exposure help to explain the
variability in the blood levels of PFOA, PFOS, and PFHxS?
4. What are the levels of other PFCs in the community, including those that have not
been detected in the water? [Note: The MDH laboratory can measure approximately
16 PFCs using methods comparable to NHANES.]
5. Is there a relationship between blood cholesterol and PFC levels in this study group?
Is the rate of decline for PFCs different for people with high vs. low blood cholesterol
levels?
6. Are there long-term health effects (cardiovascular, cancer, reproductive, etc.)
associated with PFC exposures:
a. In this community?
b. In the state?
7. Other research questions?
NOTE: For each research question panel members are asked to consider the degree to
which a follow-up study designed to answer the question is:
 is feasible
 adds scientific value
 is responsive to community needs.
Information and abstracts that follow are provided as background review for considering
these questions.
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18
Abstracts and other background material related to potential
research questions
1. What are current (2010) PFC levels in the original study population and how do they
compare to levels that were measured in 2008?
This research question would help determine whether the actions taken to reduce
community members’ exposure to PFCs in the water have been effective. At the
June 2 meeting of the EHTB advisory panel, the panel voted to recommend that
MDH conduct a follow-up study to answer this question. We propose to contact
the 186 individuals who agreed to be contacted again and invite them to
participate. Participation would involve providing a blood sample and
completing a telephone interview or questionnaire. Laboratory analysis would be
limited to the 3 PFCs measured in all participants: PFOA, PFOS, and PFHxS.
2. What is the rate of decline for PFOA, PFOS, and PFHxS blood levels in the study
population? What is the half life of PFOA, PFOS, and PFHxS in this population?
Rate of decline in the population is determined as the average of the decrease and
percent change in PFC levels from the first collection to the second. An estimate
of the rate of decline and half-lives of these three PFCs has been published only a
few times to date.
RELATED ABSTRACTS
Bartell S et al. (2009) Rate of decline in serum PFOA concentrations after
granular activated carbon filtration at two public water systems in Ohio and West
Virginia. Environmental Health Perspectives (online). doi: 10.1289/ehp.0901252.
Available online at http://dx.doi.org.
Background: Drinking water in multiple water districts in the Mid-Ohio Valley
has been contaminated with perflurooctanoic acid (PFOA), which was released by
a nearby DuPont chemical plant. Two highly contaminated water districts began
granular activated carbon filtration in 2007. Objectives: To determine the rate of
decline in serum PFOA, and its corresponding half-life, during the first year after
filtration. Methods: Up to 6 blood samples were collected from each of 200
participants, from May 2007 until August 2008. Primary drinking water source
varied over time for some participants; our analyses are grouped according to
water source at baseline. Results: For Lubeck Public Service District customers,
the average decrease in serum PFOA concentrations between May-June 2007 and
May-August 2008 was 32 ng/mL (26%) for those primarily consuming public
water at home (n=130), and 16 ng/mL (28%) for those primarily consuming
bottled water at home (n=17). For Little Hocking Water Association customers,
the average decrease in serum PFOA concentrations between NovemberDecember 2007 and May-June 2008 was 39 ng/mL (11%) for public water
consumers (n=39) and 28 ng/mL (20%) for bottled water consumers (n=11). The
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covariate-adjusted average rate of decrease in serum PFOA concentration after
water filtration was 26% per year (95% CI: 25-28% per year). Conclusions: The
observed data are consistent with first order elimination and a median serum
PFOA half-life of 2.3 years. Ongoing follow-up will lead to improved half-life
estimation.
Holzer J et al. (2009) One-year follow-up of perfluorinated compounds in plasma
of German residents from Arnsberg formerly exposed to PFOA-contaminated
drinking water. International Journal of Hygiene and Environmental Health. 212:
499-504
In Arnsberg, Sauerland area Germany, 40000 residents were exposed to PFOAcontaminated drinking water (500-640 ng PFOA/l; May2006). In July 2006, the
PFOA-concentrations in drinking water were lowered significantly by activated
charcoal filtering in the waterworks, mostly below the limit of detection (10ng/l).
A first human biomonitoring study performed in autumn 2006 revealed that
PFOA-concentrations in blood plasma of residents living in Arnsberg were 4.5–
8.3 times higher than in the reference groups. One year after the first survey, all
participants (2006:164 mothers, 90children, 101men) were invited to take part in
a follow-up study. It was the aim of the study to determine the decline of the
PFOA-concentrations in blood plasma. 288 persons (81%) were included in the
statistical analysis. The (geometric) mean PFOA-concentrations in blood plasma
of Arnsberg’s residents decreased from 22.1to17.4 mg/l in children, from 23.4 to
18.8 mg/l in mothers and from 25.3 to 23.4 mg/l in men within one year. The
average (geometric mean) changes in each individual’s PFOA-concentrations
were approximately 10 (men), 17 (mothers) and 20(children) percent/year. The
observed decline in PFOA-concentrations indicates a slow elimination in humans.
This finding in groups of the general population is in agreement with data on long
elimination half-lives observed in occupationally exposed workers.
Olsen GW et al. (2007) "Half-life of serum elimination of
perfluorooctansulfonate, perfluorohexanesulfonate, and perfluorooctanotate in
retired fluorochemical production workers." Environmental Health Perspectives.
Sep;115(9):1298-305.
BACKGROUND: The presence of perfluorooctanesulfonate (PFOS),
perfluorohexanesulfonate (PFHxS), and perfluorooctanoate (PFOA) has been
reported in humans and wildlife. Pharmacokinetic differences have been observed
in laboratory animals. OBJECTIVE: The purpose of this observational study was
to estimate the elimination half-life of PFOS, PFHS, and PFOA from human
serum. METHODS: Twenty-six (24 male, 2 female) retired fluorochemical
production workers, with no additional occupational exposure, had periodic blood
samples collected over 5 years, with serum stored in plastic vials at -80 degrees C.
At the end of the study, we used HPLC-mass spectrometry to analyze the
samples, with quantification based on the ion ratios for PFOS and PFHS and the
internal standard (18)O(2)-PFOS. For PFOA, quantitation was based on the
internal standard (13)C(2)-PFOA. RESULTS: The arithmetic mean initial serum
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concentrations were as follows: PFOS, 799 ng/mL (range, 145-3,490); PFHxS,
290 ng/mL (range, 16-1,295); and PFOA, 691 ng/mL (range, 72-5,100). For each
of the 26 subjects, the elimination appeared linear on a semi-log plot of
concentration versus time; therefore, we used a first-order model for estimation.
The arithmetic and geometric mean half-lives of serum elimination, respectively,
were 5.4 years [95% confidence interval (CI), 3.9-6.9] and 4.8 years (95% CI,
4.0-5.8) for PFOS; 8.5 years (95% CI, 6.4-10.6) and 7.3 years (95% CI, 5.8-9.2)
for PFHxS; and 3.8 years (95% CI, 3.1-4.4) and 3.5 years (95% CI, 3.0-4.1) for
PFOA. CONCLUSIONS: Based on these data, humans appear to have a long
half-life of serum elimination of PFOS, PFHxS, and PFOA. Differences in
species-specific pharmacokinetics may be due, in part, to a saturable renal
resorption process.
3. In addition to the drinking water, what other sources of exposure help to explain the
variability in the blood levels of PFOA, PFOS, and PFHxS?
Several studies have attempted to measure multiple sources of PFC exposure and
examined the relationship to blood levels. Methods for assessing other exposure
sources have included self-report questionnaires, ambient environmental
sampling, property and indoor dust sampling, and diet sampling. The two
abstracts below are examples of this work.
Emmett AE et al. (2006) “Community exposure to perfluorooctanoate: relationships
between serum concentrations and exposure sources.” J Occup Environ Med. Aug;
48(8):759-70.
OBJECTIVE: The objective of this study was to determine serum (perfluorooctanoate
[PFOA]) in residents near a fluoropolymer production facility: the contributions from
air, water, and occupational exposures, personal and dietary habits, and relationships
to age and gender. METHODS: The authors conducted questionnaire and serum
PFOA measurements in a stratified random sample and volunteers residing in
locations with the same residential water supply but with higher and lower potential
air PFOA exposure. RESULTS: Serum (PFOA) greatly exceeded general population
medians. Occupational exposure from production processes using PFOA and
residential water had additive effects; no other occupations contributed. Serum
(PFOA) depended on the source of residential drinking water, and not potential air
exposure. For public water users, the best-fit model included age, tap water drinks per
day, servings of home-grown fruit and vegetables, and carbon filter use.
CONCLUSIONS: Residential water source was the primary determinant of serum
(PFOA).
Fromme H et al. (2007) “Exposure of an adult population to perfluorinated substances
using duplicate diet portions and biomonitoring data.” Environ Sci Technol. Nov
15;41(22):7928-33.
Because dietary intake is supposed to be an important route of human exposure we
quantified the dietary intake of perfluorooctane sulfonate (PFOS), perfluorooctanoate
(PFOA), perfluorohexane sulfonate (PFHxS), perfluorohexanoate (PFHxA), and
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perfluorooctane sulfonamide (PFOSA) using 214 duplicate diet samples. The study
was carried out with a study population of 15 female and 16 male healthy subjects
aged 16-45 years. The participants collected daily duplicate diet samples over seven
consecutive days in 2005. Duplicate samples were homogenized and their ultrasonic
extracts were cleaned up by SPE and subjected to HPLC-ESI-MS/MS. In addition,
individual intakes were estimated based on blood levels of PFOS and PFOA using a
pharmacokinetic model. Blood samples were collected once during the sampling
period. The median (90th percentile) daily dietary intake of PFOS and PFOA was 1.4
ng/kg b.w. (3.8 ng/kg b.w.) and 2.9 ng/kg b.w. (8.4 ng/kg b.w.), respectively. PFHxS
and PFHxA could be detected only in some samples above detection limit with
median (maximum) daily intakes of 2.0 ng/kg b.w. (4.0 ng/kg b.w.) and 4.3 ng/kg
b.w. (9.2 ng/kg b.w.), respectively. Because PFOSA could not be detected above the
limit of detection of 0.2 ng/g f.w. this indirect route of exposure seems to be of less
significance. Overall, the results of this study demonstrate that the German population
is exposed to PFOS and PFOA, but the median dietary intake did not reach the
recommended tolerable daily intake by far. Biomonitoring data predict an exposure in
a comparable range. We suppose that, normally, food intake is the main source of
exposure of the general population to PFOS and PFOA.
4. What are the levels of other PFCs in the community, including those that have not
been detected in the water?
The scope of the original PFC biomonitoring study was to measure the 7 PFCs that
had been measured in the east metro drinking water. However, the CDC has
developed the laboratory methods and measured additional PFCs in the US
population. The MDH laboratory currently has the capacity to analyze for
approximately 16 PFCs using NHANES methods. There has been little research
conducted on the potential health effects or sources of other PFCs, which can make
communicating results and recommendations to the public challenging.
Calafat AM et al. (2007) "Polyfluoroalkyl Chemicals in the U.S. Population: Data
From the National Health and Nutrition Examination Survey (NHANES) 2003-2004
and Comparisons to NHANES 1999-2000." Environmental Health Perspectives. 111:
1596-602.
BACKGROUND: Polyfluoroalkyl chemicals (PFCs) have been used since the 1950s
in numerous commercial applications. Exposure of the general U.S. population to
PFCs is widespread. Since 2002, the manufacturing practices for PFCs in the United
States have changed considerably. OBJECTIVES: We aimed to assess exposure to
perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA),
perfluorohexane sulfonic acid (PFHxS), perfluorononanoic acid (PFNA), and eight
other PFCs in a representative 2003-2004 sample of the general U.S. population >or=
12 years of age and to determine whether serum concentrations have changed since
the 1999-2000 National Health and Nutrition Examination Survey (NHANES).
METHODS: By using automated solid-phase extraction coupled to isotope dilutionhigh-performance liquid chromatography-tandem mass spectrometry, we analyzed
2,094 serum samples collected from NHANES 2003-2004 participants. RESULTS:
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We detected PFOS, PFOA, PFHxS, and PFNA in > 98% of the samples.
Concentrations differed by race/ethnicity and sex. Geometric mean concentrations
were significantly lower (approximately 32% for PFOS, 25% for PFOA, 10% for
PFHxS) and higher (100%, PFNA) than the concentrations reported in NHANES
1999-2000 (p < 0.001). CONCLUSIONS: In the general U.S. population in 20032004, PFOS, PFOA, PFHxS, and PFNA serum concentrations were measurable in
each demographic population group studied. Geometric mean concentrations of
PFOS, PFOA, and PFHxS in 2003-2004 were lower than in 1999-2000. The apparent
reductions in concentrations of PFOS, PFOA, and PFHxS most likely are related to
discontinuation in 2002 of industrial production by electrochemical fluorination of
PFOS and related perfluorooctanesulfonyl fluoride compounds.
5. Is there a relationship between blood cholesterol and PFC levels in this study group?
Is the rate of decline for PFCs different for people with high and low blood cholesterol
levels?
Several studies have demonstrated an association between PFOA and PFOS levels
and lipid levels measured concurrently in blood serum. This relationship has been
observed both in the general population (Nelson et al. 2009), and in adult
populations and children exposed to contaminated drinking water (Steenland et
al., 2009). In the Steenland study, the predicted increase in total cholesterol from
lowest to highest decile of PFOA and PFOS was about 11-12 mg/dL. Due to the
cross-sectional design of these studies, it is not possible to know whether an
increase in cholesterol followed or preceded an increase in PFOA or PFOS. Some
have hypothesized that PFC binding to some factor in the blood is correlated with
both increased lipids and increased retention of PFCs (decreased elimination).
RELATED ABSTRACTS:
Nelson J, E Hatch and T Webster. (2009) Exposure to Polyfluoroalkyl Chemicals
and Cholesterol, Body Weight, and Insulin Resistance in the General U.S.
Population. Environmental Health Perspectives (online). doi:
10.1289/ehp.0901165 (Available online at http://dx.doi.org/)
Polyfluoroalkyl chemicals (PFCs) are used commonly in commercial applications
and are detected in humans and the environment world-wide. Concern has been
raised that they may disrupt lipid and weight regulation. Objectives. We
investigated the relationship between PFC serum concentrations and lipid and
weight outcomes in a large publicly-available dataset. Methods. We analyzed
data from the 2003-2004 National Health and Nutrition Examination Survey
(NHANES) for participants aged 12-80. Using linear regression to control for
covariates, we studied the association between serum concentrations of
perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctane
sulfonic acid (PFOS), and perfluorohexane sulfonic acid (PFHxS), and measures
of cholesterol, body size, and insulin resistance. Results. We observed a positive
association between concentrations of PFOS, PFOA, and PFNA and total and
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non-HDL-cholesterol. We found the opposite for PFHxS. Those in the highest
quartile of PFOS exposure had total cholesterol levels 13.4 mg/dL (95%
CI, 3.8, 23.0) higher than those in the lowest. For PFOA, PFNA, and PFHxS, this
effect estimate was 9.8 (95% CI, -0.2, 19.7), 13.9 (95% CI, 1.9, 25.9), and -7.0
(95% CI, -13.2, -0.8), respectively. A similar pattern emerged when exposures
were modeled continuously. We saw little evidence of a consistent association
with body size or insulin resistance. Conclusions. This exploratory crosssectional study is consistent with other epidemiologic studies in finding a positive
association between PFOS and PFOA and cholesterol, despite much lower
exposures in NHANES. Results for PFNA and PFHxS are novel, emphasizing the
need to study PFCs other than PFOS and PFOA.
Steenland K et al. (2009) Association of perfluorooctanoic acid and
perfluorooctane sulfonate with serum lipds among adults living near a chemical
plant. American Journal of Epidemiology. 170(10): 1268-1278.
Perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) are
compounds that do not occur in nature but have been widely used since World
War II and persist indefinitely in the environment. They are present in the serum
of Americans with median levels of 4 ng/mL and 21 ng/mL, respectively. PFOA
has been positively associated with cholesterol in several studies of workers. A
cross-sectional study of lipids and PFOA and PFOS was conducted among 46,294
community residents aged 18 years or above, who drank water contaminated with
PFOA from a chemical plant in West Virginia. The mean levels of serum PFOA
and PFOS in 2005-2006 were 80 ng/mL (median, 27 ng/mL) and 22 ng/mL
(median, 20 ng/mL), respectively. All lipid outcomes except high density
lipoprotein cholesterol showed significant increasing trends by increasing decile
of either compound; high density lipoprotein cholesterol showed no association.
The predicted increase in cholesterol from lowest to highest decile for either
compound was 11-12 mg/dL. The odds ratios for high cholesterol (>/=240
mg/dL), by increasing quartile of PFOA, were 1.00, 1.21 (95% confidence
interval (CI): 1.12, 1.31), 1.33 (95% CI: 1.23, 1.43), and 1.40 (95% CI: 1.29,
1.51) and were similar for PFOS quartiles. Because these data are cross-sectional,
causal inference is limited. Nonetheless, the associations between these
compounds and lipids raise concerns, given their common presence in the general
population.
Steenland K, T Fletcher and D Savitz. (2009) Status report: Association of
perfluorooctanic acid (C8/PFOA) and perfluoroctanesulfonate (PFOS) with lipids
among children in the Mid-Ohio Valley. (Available online at
http://www.c8sciencepanel.org/pdfs/Status_Report_C8_and_lipids_in_children_2
8Oct2009.pdf)
Background: Serum perfluorooctanoic acid (PFOA) has been associated with total
cholesterol and other lipids in some studies of exposed workers. Here we examine the
association of PFOA and a related chemical, perfluoroctanesulfonate (PFOS), with
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lipids in a large population of children in the mid-Ohio valley. Many in this
population have high levels of serum PFOA due to drinking water contaminated from
a nearby chemical plant. Methods: The study population consisted of 12,476
community residents under age 18 living at some point in six water districts
contaminated by PFOA, who participated in a large health survey in 2005-2006.
Participants in the health survey (the C8 Health Project) were required to have lived,
worked, or gone to school in one of the contaminated water districts for at least one
year. The relationship between PFOA and PFOS with total cholesterol, low density
lipoprotein (LDL), high density lipoprotein (HDL), and triglycerides was examined
via linear and logistic regression, after adjustment for other variables which affect
these lipids. Results: The average level of PFOA in the serum was 69 ng/ml, while
the average level of PFOS was 23 ng/ml. The PFOA levels were much higher than
the US population average level of about 5 ng/ml, while the PFOS levels were similar
to the average level for the US population. In multivariate models adjusting for other
factors (age, body mass index, sex, fasting status prior to blood collection), higher
PFOA and PFOS were each significantly associated with higher total cholesterol and
LDL cholesterol. There were no consistent trends between PFOA and either HDL or
triglycerides. Higher PFOS was associated with higher HDL, but showed no trend
with triglycerides. The predicted increase in cholesterol from lowest to highest
quintile of PFOA (the lowest 20% to the highest 20% of the population) was 5 mg/dl,
for example an increase from 160 to 165 mg/dl cholesterol. The corresponding
increase in cholesterol for high vs. low PFOS was 9 mg/dl. The risk for high
cholesterol in children (total cholesterol >=170 mg/dl), and high LDL in children,
(LDL>=110 mg/dl) was also studied. There was a modest but statistically significant
extra risk of high total cholesterol with increasing PFOA; there was a 20% extra risk
for those with the highest 20% of PFOA vs. the lowest 20%. Also, there was a 60%
extra risk of high cholesterol for those with the highest 20% of PFOS, vs. those with
the lowest 20%. Similar increases in risk were seen for both chemicals for high levels
of LDL (the ‘bad cholesterol’); a 40% extra risk of high LDL for the highest quintile
PFOA vs. the lowest, and a 60% extra risk for the highest quintile of PFOS vs. the
lowest. For HDL (the ‘good cholesterol’) higher levels of PFOS were associated with
decreased risk of low HDL (<40 mg/dl), i.e., a change in a favorable direction. No
trends for high triglycerides were observed for either fluorocarbon. Intepretation:
We have seen modest associations between PFOA and PFOS and some lipids in
children. Interpretation of these results is made difficult by the cross-sectional design
of our study, which prohibits knowing whether an increase in cholesterol (or LDL
cholesterol) may have followed or preceded an increase in PFOA or PFOS. The
mechanism by which these chemicals might be related to cholesterol in humans is not
known. These data alone cannot prove whether the PFOA and PFOS differences in
these children caused the observed shift in cholesterol, or whether there is another
explanation. For example, another explanation could be that there is some unknown
exposure (such as another substance in the blood), which itself correlates both with
increased lipids, and with increased retention of PFOA/PFOS in the blood. The
Science Panel is conducting further more definitive studies to try to determine which
of these possibilities is more likely. The fact that both PFOA and PFOS were
associated with increases in cholesterol may indicate an association with this
chemical class (perfluorinated compounds) in general, rather than specifically either
PFOA or PFOS. These findings for total cholesterol and LDL cholesterol in children
are similar to a previous finding in adults in this same population.
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Olsen GW et al. (2003) “Epidemiologic assessment of worker serum
perfluorooctanesulfonate (PFOS) and perfluorooctanoate (PFOA) concentrations and
medical surveillance examinations.” J Occup Environ Med. Mar;45(3):260-70.
Perfluorooctanesulfonyl fluoride (POSF, C8F17SO2F) is used to create applications
for surfactants and paper, packaging, and surface (e.g., carpets, textiles) protectants.
Such POSF-based products or their residuals may degrade or metabolize to PFOS
(C8F17SO3-). PFOS concentrates in liver and serum and results in hypolipidemia as
an early effect of cumulative dosages. Male and female employees of two
perfluorooctanyl-manufacturing locations (Antwerp, Belgium and Decatur, Alabama)
participated in a periodic medical surveillance program that included hematology,
clinical chemistry, thyroid hormone, and urinalysis testing. Serum concentrations of
PFOS and perfluorooctanoate (PFOA, C7F15CO2-, used as a fluoropolymer
emulsifier) were measured via mass spectrometry methods. The mean serum PFOS
and PFOA concentrations for 263 Decatur employees were 1.32 parts per million
(ppm; geometric mean 0.91, range 0.06-10.06 ppm) and 1.78 ppm (geometric mean
1.13, range 0.04-12.70 ppm), respectively. Mean concentrations were approximately
50% lower among 255 Antwerp workers. Adjusting for potential confounding factors,
there were no substantial changes in hematological, lipid, hepatic, thyroid, or urinary
parameters consistent with the known toxicological effects of PFOS or PFOA in
cross-sectional or longitudinal analyses of the workers' measured serum
fluorochemical concentrations.
6. Are there long-term health effects (cardiovascular, cancer, reproductive, etc.)
associated with PFC exposures in this community? In the state?
Several epidemiological studies of workers exposed to PFCs have been conducted
and published in the scientific literature (example abstract below) and work
continues in this area, including current research at the University of Minnesota.
Currently, a large-scale longitudinal study, called the “C8” study, is investigating
the possible relationship between PFOA exposure in the general population living
near a manufacturing plant and increased risk of cardiovascular disease,
reproductive outcomes, and a range of clinical measures. The US EPA announced
in September that PFCs are now a top priority for health risk reassessment. Staff
and east metro area legislators continue to receive requests from the community
for a health study. Given the research that is currently underway elsewhere, is
there something valuable that could be learned by conducting a longitudinal
community cohort study in Minnesota? Should Legislators push for funding such
a study or push for MDH and the University of Minnesota to seek funds for such a
study?
Alexander BH and Olsen GW. (2007) “Bladder cancer in perfluorooctanesulfonyl
fluoride manufacturing workers.” Ann Epidemiol. Jun;17(6):471-8.
26
PURPOSE: To determine whether bladder cancer is associated with exposure to
perfluorooctane sulfonate (PFOS) in an occupational cohort. METHODS: Incidence
of bladder cancer was ascertained by postal questionnaire to all living current and
former employees of the facility (N = 1895) and death certificates for deceased
workers (N = 188). Exposure to PFOS was estimated with work history records and
weighted with biological monitoring data. Standardized incidence ratios (SIRs) were
estimated using U.S. population-based rates as a reference. Bladder cancer risk within
the cohort was evaluated using Poisson regression by cumulative PFOS exposure.
RESULTS: Questionnaires were returned by 1,400 of the 1895 cohort members
presumed alive. Eleven cases of primary bladder cancer were identified from the
surveys (n = 6) and death certificates (n = 5). The SIRs were 1.28 (95% confidence
interval [CI] = 0.64-2.29) for the entire cohort and 1.74 (95% CI = 0.64-3.79) for
those ever working in a high exposed job. Compared with employees in the lowest
cumulative exposure category, the relative risk of bladder cancer was 0.83 (95% CI =
0.15-4.65), 1.92 (95% CI = 0.30-12.06), and 1.52 (95% CI = 0.21-10.99).
CONCLUSIONS: The results offer little support for an association between bladder
cancer and PFOS exposure, but the limited size of the population prohibits a
conclusive exposure response analysis.
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28
SECTION OVERVIEW: BIOMONITORING UPDATES
Given the limited time available for advisory panel meetings, updates on some items will
be provided to the panel as information items only. This information is intended to keep
panel members apprised of progress being made in program areas that are not a featured
part of the current meeting’s agenda and/or to alert panel members to items that will need
to be discussed in greater depth at a future meeting.
Included in this section of the meeting packet are status updates on three of the
biomonitoring pilot projects:

Lake Superior Mercury Biomonitoring Study

Riverside Prenatal Biomonitoring Study

South Minneapolis Children’s Arsenic Study
ACTION NEEDED: At this time no formal action is needed by the advisory panel. Panel
members are invited to ask questions or provide input on any of these topics during the
designated time on the meeting agenda.
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30
Status Update on the Lake Superior Mercury Biomonitoring
Study
Participant recruitment
Participants continue to be enrolled in the Lake Superior Mercury Biomonitoring Study.
As of October 27, 2009, written informed consent has been received from 743
participants; 76 of these were recruited through local public health staff. Participation rate
during the first 9 months of the study has averaged 47%. Given this rate, recruitment will
likely continue through February 2010. Newborn Screening staff have punched spots
from 200 participant screening cards for mercury analysis.
Wisconsin has completed specimen collection and provided blood spots to MDH for
mercury analysis. (Informed consent is not required in Wisconsin.). Michigan may be
participating in the project again, but details of their participation are still being worked
out. (They previously needed to withdraw from the study due to changes in the storage of
specimens and informed consent requirements in Michigan.)
Specimen analysis
The Quality Assurance Project Plan (QAPP) and the mercury analysis SOP have been
updated to reflect changes to the method resulting from the switch to using 96-well
plates. These documents were sent to the EPA program office for review and approval to
begin analysis was granted in the beginning of October. The laboratory has received all
180 of the punched specimens from Wisconsin and, to date, 80 of the specimens from
Minnesota. Analysis of these specimens is expected to begin by the end of November.
Once analysis begins, additional punched specimens from Minnesota will be forwarded
to the lab for analyzing.
31
Status update on the Riverside Prenatal Biomonitoring Study
As of November 12, 2009, 39 urine samples (of the 90 samples required by statute) have
been received and are now being stored in the MDH public health laboratory. The initial
goal was to enroll 30 women in each of three ethnic/racial communities (Hispanic, nonHispanic black, and non-Hispanic white). The Riverside Birth Study as a whole has had a
difficult time enrolling Hispanic women, so the biomonitoring study may be unable to
reach its goal of enrolling 30 Hispanic women.
Dr. Logan Spector the Principal Investigator for the Riverside Birth Study recently
changed his recruitment protocol, designating that 100 of the 500 participants be of
Somali descent. With this consideration we translated all of our study documents into
Somali so as to best recruit in this population.
We will continue to recruit throughout the entirety of the Riverside Birth Study
recruitment period, expected to continue through early 2010, in order to achieve the goal
of recruiting 90 participants. Laboratory analysis for environmental phenols and cotinine
will begin when all samples are received in the laboratory.
We are also currently developing materials and planning for health provider education for
clinicians at the Riverside Prenatal Clinic to help with interpretation of the project results
and responding to questions from patients and the community. This requires conducting
a current review and summary of the available health effects literature on each of the
phenols being analyzed: BPA, benzophenone, parabens, and triclosan. We will be
seeking assistance from the MDH Tobacco Control Program for materials related to
health effects of cotinine and environmental tobacco smoke on the fetus and newborn.
32
Status Update on the South Minneapolis Children’s Arsenic
Study
Interest continues to be expressed in the South Minneapolis Children’s Arsenic Study.
Adrienne Kari, biomonitoring coordinator, presented a brief overview of the methods and
results of the South Minneapolis Children’s Arsenic Study at the Phillips Environmental
Steering Committee Initiative’s (PESCI) Feast and Environmental Justice Forum on
Monday, November 9.
At the meeting, some community members expressed concerns about the limitations of
the study and questioned what was learned by doing the study. Other community
members stated that they felt the results were “good news,” in that the study did not
detect a widespread pattern of high arsenic levels in children.
After the formal presentation, several community members participated in a breakout
session organized by PESCI in order to develop community recommendations for future
biomonitoring efforts that might include the Phillips neighborhood. Project staff clarified
that, because arsenic has a short half-life and the contaminated soil has been remediated,
further biomonitoring for arsenic in the children is not being recommended. Instead,
MDH has recommended continuing education with parents on ways to reduce arsenic
exposure from all sources.
The group recommended expanding future biomonitoring efforts to include other
chemicals of interest to the community (e.g., lead); having PESCI write a letter of support
on behalf of MDH obtaining additional resources to make expanded biomonitoring
possible; and forming a team to assist MDH in ensuring that scientific communications
are understandable to the community.
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SECTION OVERVIEW: EPHT PESTICIDES INDICATORS
As reported at the September 15, 2009, meeting of the EHTB advisory panel, the content
area of pesticides was recently added to the national EPHT network. Staff from the
Minnesota Department of Health (MDH) and the Minnesota Department of Agriculture
(MDA) have been participating in the Pesticide Indicator Content Work Group (CWG),
which is given the charge of developing nationally consistent data and measures (NCDMs)
related to this content area.
The development of the pesticide-related NCDMs is in the early stages. Input from the
advisory panel is sought to help guide the development of the national indicators and to
identify state-specific priorities. Background material is provided here to help inform panel
discussion.
The following items are included in this section of the meeting materials:





Pesticide Indicator Content Work Group (CWG) update
Preliminary list of national and state-level data sources for pesticides indicators
(Note: This list is under development; data sources may be added or removed after
further evaluation)
Draft data inventories for national data sources (Note: These data inventories were
completed by the co-leads of the pesticide indicator CWG.)
Draft data inventories for Minnesota-specific data sources (Note: These data
inventories are in draft form, as the CWG is still in the process of determining the
scope of the inventories, exactly what the inventories should contain, and which
data sources will advance at the national level for purposes of NCDM
development.)
EPHT Pesticide Indicator Content Work Group Team Proposal (Note: This
proposal was developed in September and includes the rationale for developing
indicators on pesticides for the tracking network; a list of stakeholders; a
description of potential data sources; and a timeline.)
ACTION NEEDED: The advisory panel is asked to provide suggestions to help guide
further development of the national pesticides indicators and to help set priorities for
Minnesota-specific pesticides indicators. In particular, the panel is invited to provide
input on the following questions:


After reviewing the available sources of national and state-level pesticide data and
reviewing the data inventories, where are there gaps in the data?
National pesticides indicators will be formed through a consensus building process
and will draw on data sources that are available across many or all states. Regardless
of what pesticides indicators and data sources are adopted by the national EPHT
Network, what pesticides-related information is important for Minnesota to track as a
state priority?
No formal vote is anticipated.
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36
Pesticide Indicator Content Work Group (CWG) Update
In the summer of 2009, the national Environmental Public Health Tracking (EPHT)
program formed a new content work group (CWG) to develop recommendations regarding
specific pesticides indicators to be included as part of the national tracking network.
The New York City (NYC) EPHT program volunteered to take a leadership role in the
Pesticide Indicator CWG, and originally proposed indicators addressing the following
topics, which the CWG is in the process of evaluating:
a. Pesticide product sales and use;
b. Pesticide regulatory actions (these can be thought of as a subset of pesticide related
interventions);
c. Pesticide need – these may include pest population trends in agriculture, structural
and other sectors;
d. Pesticide exposures;
e. Pesticide-related acute health outcomes;
f. Pesticide-suspected chronic health outcomes (these may involve recommended
linkages to already established EPHT indicators and measures, or novel ones); and
g. Pest- or pesticide-related interventions (an example from NYC was the adoption of
a local regulation to limit the use of pesticides).
Development of the indicators will be a consensus building process involving the
participating states and will involve finalizing a list of preliminary indicators and a plan for
calculating the measures. After the measures receive preliminary approval from CDC,
states will then test the indicators and calculate measures.
Given the challenging nature of developing nationally consistent data and measures
(NCDMs), progress of the Pesticide Indicator CWG to date has been slow. Early
discussions have focused on defining what the group considers to be a pesticide and
identifying potential national data sources and data sources in each state.
Staff from the Minnesota Department of Health (MDH) and the Minnesota Department of
Agriculture (MDA) have been participating in Pesticide Indicator CWG development and
planning activities. As part of the CWG, staff have completed pesticide data inventory
templates (see attached) that describe state-level data sources, quality and availability.
These templates will then be pooled with those of other states, and the CWG will look for
commonalities that might support the development of NCDMs (aka indicators) through the
EPHT network. MDH and MDA’s work can also be used to inform state-level priorities
outside of the national EPHT Network.
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38
Preliminary list of national and state-level data sources
for pesticides indicators (DRAFT)
The following is a working list of potential data sources; some data sources may be added
or removed after further evaluation by the pesticide indicator CWG.
National data sources:
1) USDA-National Agricultural Statistics Service (NASS)
a. Ag Chemical Usage Reports
b. QuickStats
2) USDA Pesticide Data Program
a. Food residue data
3) EPA Pesticide Market Estimates
4) CDC National Health and Nutrition Examination Survey (NHANES)
a. National Report on Human Exposure to Environmental Chemicals
5) FDA Pesticide Residue Monitoring Data
6) USGS National Water Quality Assessment Program (NAWQA)
a. USGS Synthesis Project
State-level data sources:
1)
2)
3)
4)
Pesticide ambient water quality (MDA, PCA, MDH, local units of government)
Pesticide use data (MDA)
Pesticide sales data (MDA)
Minnesota Drinking Water Information System (Safe Drinking Water Act monitoring
data) (MDH)
5) Compliance Information System (Pesticide misuse/complaints data) MDA)
6) Aquatic pesticide use data (DNR)
7) School/daycare pesticide use surveys (MDA, Dept of Educ.)
8) Pesticide disposal program data (MDA)
9) Pesticide storage and chemigation permit data (MDA)
10) Pesticide dealer and applicator licensure (MDA)
11) Worker Protection Standard program data (MDA)
12) Crop pest surveys (MDA)
13) Cooperative Agricultural Pest Surveys (gypsy moth, emerald ash borer, etc.) (MDA)
14) Mosquito control (MMCD)
15) Right-of-way and green space weed management (MnDOT)
16) Gypsy Moth Treatment Program (MDA)
17) Inpatient Hospital Discharge Data (Pesticide hospitalizations)
18) Outpatient Hospital Discharge Data (Pesticide emergency department visits)
19) Mortality Database (Pesticide poisoning deaths)
20) Poison Control System Call Data (Pesticide exposure calls)
21) Hazardous Substances Emergency Events Surveillance System
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40
Data inventories for national data sources (DRAFT)
(Completed by the Pesticide Indicator CWG co-leads)
1) USDA-National Agricultural Statistics Service (NASS)
a. Ag Chemical Usage Reports
b. QuickStats
2) USDA Pesticide Data Program
a. Food residue data
3) EPA Pesticide Market Estimates
4) CDC National Health and Nutrition Examination Survey (NHANES)
a. National Report on Human Exposure to Environmental Chemicals
5) FDA Pesticide Residue Monitoring Data
6) USGS National Water Quality Assessment Program (NAWQA)
a. USGS Synthesis Project
USDA National Agricultural Statistics Service (NASS) Ag Chemical Usage Reports
Data Format
CSV
Identification
Purpose:
NASS is part of the Agricultural Survey Records system provides effective and efficient
electronic survey management, data entry, data collection, data editing, data analysis, and
data summarization or tabulation for hundreds of agricultural surveys annually. These
surveys cover topics such as crop production, grain stocks, livestock inventories, prices
paid and received by farmers and ranchers, farm labor, farm income, farm expenditures,
farm numbers, chemical usage, and special follow-on surveys to the Census of Agriculture.
The program generates county, state, regional, and national agricultural statistics.
http://www.ocio.usda.gov/NASS-1_April09.txt
Abstract:
The Ag Chemical Usage Reports provide access to CSV files and interactive access to data
from NASS, as part of a cooperative effort among USDA, the USDA Regional Pest
Management Centers and the NSF Center for Integrated Pest Management (CIPM). All
data available have been previously published by NASS and have been consolidated at the
state level. Commodity acreages and active ingredient (ai) agricultural chemical use (%
acres treated, ai/acre/treatment, average number of treatments, ai/acre, total ai used) data
are available. All data can be searched by commodity, year, state and active ingredient.
Data are available in table, map, and graphical format (all in a Web browser) as well as
CSV format for download.
41
Environmental Public Health Tracking Notes:
Provides an estimate of the active ingredients of pesticides applied per state which could be
compared to state level health outcome data.
Maintenance/Update Frequency:
Data is classified by crop type and the update cycle for each crop is different. Most
frequent is every two years.
From Mark Miller of USDA NASS
“Our sampling procedures do not allow us to make estimates on smaller geographic scale.
Agricultural chemical usage data has been collected since 1990. Initially, the major field
crops (corn, soybeans, wheat, cotton, potatoes) we collected annually. Around the year
2000 we adjusted our data collections to occur on a two year cycle. Corn, Cotton and
potato data were collected in the odd numbered years. Soybeans and wheat data were
collected in the even numbered year. Fruit and vegetable data have always been on an
alternate year cycle. Fruit data collected in the odd numbered years. Vegetable data was
collected in the even numbered years. Nursery and Floriculture data has been collected
three times (2000, 2003 and 2006)” and includes 6 states (FL, TX, CA, OR, MI, and PA)
Rice, peanuts and sorghum are hit and miss. States with the most acreage of the crop is
surveyed and the number of states are compiled until 80% of the acreage in the US is
covered.
Dates Covered:
1990 - 2006
Type of Data:
Commodity acreages and active ingredient (ai) agricultural chemical use (% acres treated,
ai/acre/treatment, average number of treatments, ai/acre, total ai used). Sample screen shot.
42
Available Geographies:
State level (Note, county use of pesticides applied available every 5 years from the
Agricultural Census but does not include type of pesticide)
Data Release Date:
Ongoing
Publisher:
USDA
Data Quality
None I could find. The NASS program works by sending trained specialists, called
enumerators, to a statistically determined selection of farms across the country to survey
farmers' actual application rates of pesticides and fertilizers. Enumerators helped farmers
with calculations to produce more reliable data than self-reporting typically provides.
Because of the cost and time required, not all crops or states were surveyed annually.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (N)
Pesticide product (N)
43
Data Dictionary (if applicable)
Web access to queries are available at http://www.pestmanagement.info/nass/. To acquire
the entire dataset would require contacting USDA
Data Access
Availability of Source Data for Public:
None.
Availability of Source Data for Investigators/EPHT States/Cities:
None
Associated Websites

News article about USDA surveying growers.
http://westernfarmpress.com/news/10-5-05-fruit-chemical-survey/

USDA stopped surveys of chemical and fertilizer use for a short period of time.
http://www.organicconsumers.org/articles/article_13866.cfm

Doane Marketing Research is an alternate source of this data but is not free.
Doane's collection methods differ from NASS's, and there are strict limits on how
data can be publicly released to protect the company's proprietary information.
And Doane's price tag-about $500,000 per year for a full national data set-is too
steep for most academic and nonprofit users.
http://www.organicconsumers.org/articles/article_13866.cfm
44
USDA National Agricultural Statistics Service QuickStats
Data Format:
CSV via online
Identification
Abstract:
NASS publishes U.S., state, and county level agricultural statistics for many commodities
and data series. Quick Stats offers the ability to query by commodity, state(s) and year(s),
providing the most up-to-date statistics including all revisions. The query dataset can be
downloaded for easy use in your database or spreadsheet. Our Quick Stats system handles
statistics for all Agricultural Statistics Board (ASB) releases.
Environmental Public Health Tracking Notes:
Identify crops by county as an indicator of agricultural use of possible pesticides
Maintenance/Update Frequency:
Dates Covered:
1909-2009
Type of Data:
Available Geographies:
Crop data by State and county. Chemical use by state.
Data Release Date:
Publisher:
USDA http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/ and
http://www.nass.usda.gov/Statistics_by_Subject/Environmental/index.asp
Data Quality
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (Y)
Pesticide product (N)
45
Data Access
Availability of Source Data for Public:
None.
Availability of Source Data for Investigators/EPHT States/Cities:
None
46
USDA Pesticide Data Program Food Residue Data
Data Format:
Annual Access databases
Identification
Purpose:
Data is collected to provide information on levels of pesticide residues on agricultural food
products such as fruits, vegetables, dairy and meat products. The commodities are
especially focused on foods eaten by children such as fruit juices.
Abstract:
Data is collected on the residue levels for samples of various commodities and the levels of
pesticides measured on each sample. Samples are collected in between 15-30 states with
about a dozen collecting a large variety of samples annually. The group of commodities
sampled each year changes but many commodities, especially certain fruits and vegetables,
are repeatedly sampled each year. Foods like dairy and meat are sampled less regularly.
The testing of samples is done at a series of state and federal labs.
Environmental Public Health Tracking Notes:
In the EPHT tracking network, state level data can be derived on annual or multiyear
groupings on aggregates of commodities and types of pesticides and levels of toxicity.
Metrics on % with detectible residues, mean concentrations, etc. could be derived.
Maintenance/Update Frequency:
Annual updates.
Dates Covered:
Annual data available from 1992 to 2007.
Type of Data:
Pesticide Exposures from Food
Available Geographies:
State data available for all years, more states have been included in recent years.
International samples have also been included in recent years.
Data Release Date:
Annual data released in December.
Publisher:
USDA
47
Data Quality
Data quality is excellent. A small percentage of data has missing geography classified as
unknown state or country. The national nature of the dataset would lend itself to nationally
consistent data measures.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (N)
Pesticide product (N)
Data Access
Existing Data Summaries:
Annual data summary reports are available at:
http://www.ams.usda.gov/AMSv1.0/ams.fetchTemplateData.do?template=TemplateG&nav
ID=&rightNav1=&topNav=&leftNav=ScienceandLaboratories&page=PDPDownloadData/
Reports&resultType=&acct=pestcddataprg.
Availability of Source Data for Public:
Annual databases to download:
http://www.ams.usda.gov/AMSv1.0/ams.fetchTemplateData.do?template=TemplateG&nav
ID=&rightNav1=&topNav=&leftNav=ScienceandLaboratories&page=PDPDownloadData/
Reports&resultType=&acct=pestcddataprg.
Availability of Source Data for Investigators/EPHT States/Cities:
Data is publicly available.
Associated Websites
PDP Program homepage
http://www.ams.usda.gov/AMSv1.0/ams.fetchTemplateData.do?template=TemplateC&nav
ID=PDPDownloadNav1Link1&rightNav1=PDPDownloadNav1Link1&topNav=&leftNav
=ScienceandLaboratories&page=PesticideDataProgram&resultType=&acct=pestcddataprg
48
EPA Pesticide Market Estimates
Note: This is a preliminary assessment that will be expanded in future discussion with the
EPA
Data Format:
Published pdf and html reports. Source data format is unknown.
Identification
Purpose:
To estimate amount of pesticide used and sold in the US.
Abstract:
Data are gathered from various federal, state, and private sources to build a robust estimate
of the national pesticide market in dollar amounts of products used and sold over a two
year period.
Environmental Public Health Tracking Notes:
This data could be useful in providing national and state level estimates of trends in the
amount of major pesticide classes used and sold by different market sectors such as
agriculture, commercial/industry, and home and garden.
Maintenance/Update Frequency:
Data are updates every two years approximately with a two year lag. (No new updates
have been released since the 2000-2001 estimates in 2004.)
Dates Covered:
Earliest report is from 1994-1995 but historical comparison data goes back as far as 1964.
Type of Data:
Hazard data
Available Geographies:
The publicly available data is mainly at national level with some regional metrics.
However, source data may be available on the state level if access is given by EPA.
Data Release Date:
Data is generally released after two years.
Publisher:
EPA in collaboration with many federal, state and private partners.
49
Data Quality
Data as currently available is in broad aggregate estimates. Once more fine grained data is
available more in depth data quality issues can be addressed. Pesticide market data is a
statistical estimate based on numerous sources.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (Y)
Pesticide product (N)
Data Access
Existing Data Summaries:
Online market estimate reports are available at:
http://www.epa.gov/oppbead1/pestsales/index.htm
Availability of Source Data for Public:
No source data is available to the public
Availability of Source Data for Investigators/EPHT States/Cities:
Under yet to be determined agreements. Some of the source data may be accessible for
EPHT use.
50
CDC National Health and Nutrition Examination Survey (NHANES) National Report
on Human Exposure to Environmental Chemicals
Data Format:
Electronic, may need to be electronically manipulated.
Identification
Purpose:
Provides an ongoing assessment of the U.S. population's exposure to environmental
chemicals using biomonitoring.
Abstract:
The Second National Report on Human Exposure to Environmental Chemicals (Second
Report) was released in 2003 and presented biomonitoring exposure data for 116
environmental chemicals for the noninstitutionalized, civilian U.S. population over the 2year period 1999-2000. This Third Report presents similar exposure data for the U.S.
population for 148 environmental chemicals over the 2-year period 2001-2002. The Third
Report also includes the data from the Second Report. Chemicals or their metabolites were
measured in blood and urine samples from a random sample of participants from the
National Health and Nutrition Examination Survey (NHANES) conducted by CDC’s
National Center for Health Statistics. NHANES is a series of surveys designed to collect
data on the health and nutritional status of the U.S. population.
Environmental Public Health Tracking Notes:
Provide a national level of pesticide residue in the US population that could be linked to
pesticide use or pesticide levels in the environment
Maintenance/Update Frequency:
Every 2 years. For example, (e.g., 2003-2004, 2005-2006, and 2007-2008).
Dates Covered:
1999-2000; 2001-2002
Type of Data:
Exposure
Available Geographies:
National; regional may be possible.
Data Release Date:
2005
Publisher:
CDC, NCEH, Division of Laboratory Services; CDC Regional Data Center
51
Data Quality
Not determined at this time
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (Y)
Pesticide product (N)
Data Access
Existing Data Summaries:
http://www.cdc.gov/exposurereport/
Availability of Source Data for Public:
Readily available. Data may not be easy to handle.
Availability of Source Data for Investigators/EPHT States/Cities:
No constraints if we use national data. Constraints exist if we try regional data.
52
FDA Pesticide Residue Monitoring Data
Data Format:
Text files
Identification
Purpose:
To monitor unprocessed food to enforce EPA established pesticide tolerance levels for
domestic and imported foods and to confiscate those products that exceed regulatory levels.
The Total Diet Study also monitors the incidence of pesticide residues at much lower levels
than for regulatory monitoring for foods processed to approximate the state when foods are
consumed.
Abstract:
Data are gathered as close to the point of production or point of import in generally raw
unprocessed form. Data are collected in agreement with participating state agencies.
Environmental Public Health Tracking Notes:
The data presented here, especially the Total Diet Study, could supplement data available
in USDA PDP.
Maintenance/Update Frequency:
Data are update annually.
Dates Covered:
Data has been published on the FDA program from 1987 through 2007.
Type of Data:
Hazard data
Available Geographies:
The publicly available data is mainly at national and international level. The national data
may be available on the state level.
Data Release Date:
Data is generally released annually after one year.
Publisher:
FDA in collaboration with state partners.
53
Data Quality
Data is currently available for 2007 at the sample level. Hopefully historical data will be
available soon. FDA is making great strides to provide better public access to their data.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (N)
Pesticide product (N)
Data Dictionary (if applicable)
Source Data Dictionary:
Pesticide Residue Monitoring 2002 Database Users’ Manual
Link Description:
Description of text files that make up annual source data
Link Address:
http://www.fda.gov/Food/FoodSafety/FoodContaminantsAdulteration/Pesticides/ResidueM
onitoringReports/ucm126233.htm#introduction
Data Access
Existing Data Summaries:
Residue monitoring reports from 1993-2007 are available at:
http://www.fda.gov/Food/FoodSafety/FoodContaminantsAdulteration/Pesticides/ResidueM
onitoringReports/default.htm
Availability of Source Data for Public:
2007 data is currently available
Availability of Source Data for Investigators/EPHT States/Cities:
FDA should be releasing more historical data soon.
Associated Websites
Residue Monitoring Reports
http://www.fda.gov/Food/FoodSafety/FoodContaminantsAdulteration/Pesticides/ResidueM
onitoringReports/default.htm
54
USGS National Water Quality Assessment Program (NAWQA) Pesticide National
Synthesis Project
Data Format:
Database and electronic map.
Identification
Purpose:
To evaluate sources of chemicals contributing to chemicals in groundwater
Abstract:
Pesticide use for 1992, 1997, and 2002 modeled from state average of pesticide use per
crop and acreage of crops via remote sensing data.
Environmental Public Health Tracking Notes:
Agricultural pesticide use as a source/hazard term for linking to environmental or health
outcome data.
Maintenance/Update Frequency:
Every 5 years beginning in 1992. An expected 2007 version is not known to exist without
further checking.
Dates Covered:
1992, 1997, 2002.
Type of Data:
Hazard data
Available Geographies:
County and subcounty (down to the square mile)
Data Quality
The pesticide use maps provided on this web site show the geographic distribution of
estimated average annual pesticide use intensity. Use intensity rates are expressed as the
average pounds applied per square mile of agricultural land in a county. The area of
mapped agricultural land for each county was obtained from an enhanced version of the
1992 USGS National Land Cover Data (NLCD). The key limitations of the data used to
produce these maps include the following: (1) use coefficients for each crop are averages
for each state and consequently do not reflect the local variability of pesticide management
practices found within states and counties, (2) pesticide use estimates represent typical use
patterns for the five year period surrounding each particular year
55
shown on the maps, (3) pesticide use coefficients were not available for all states where a
pesticide may have been applied to agricultural land, and and such areas are not included,
(4) county crop acreages are form the Census of Agriculture and may not represent all crop
acreage because of Census nondisclosure rules, and (5) agricultural land area used to
calculate the pesticide use intensity and display the data was derived from 30-meter
satellite remote sensing data that may over estimate or underestimate the actual agricultural
land area. The maps are not intended for reliably making local-scale estimates of pesticide
use, such as estimates for a specific individual county level. Please refer to Method for
Estimating Pesticide Use for a detailed discussion of how the pesticide use data were
developed. Each set of maps identified below by Census year includes a description of
specific data sources and methods applied to make the maps.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) Pesticide class (N)
Pesticide product (N)
Data Access
Existing Data Summaries:
http://water.usgs.gov/nawqa/pnsp/usage/maps/
Availability of Source Data for Public:
Do not seem to be restricted as it is already on USGS’s website.
Availability of Source Data for Investigators/EPHT States/Cities:
Need to determine.
56
Minnesota data inventories for state-level data sources
(DRAFT)
1)
2)
3)
4)
Pesticide ambient water quality
Pesticide use data
Pesticide sales data
Minnesota Drinking Water Information System (Safe Drinking Water Act monitoring
data)
5) Compliance Information System (Pesticide misuse/complaints data)
6) Aquatic pesticide use data
7) School/daycare pesticide use surveys
8) Pesticide disposal program data
9) Pesticide storage and chemigation permit data
10) Pesticide dealer and applicator licensure
11) Worker Protection Standard program data
12) Crop pest surveys
13) Cooperative Agricultural Pest Surveys (gypsy moth, emerald ash borer, etc.)
14) Mosquito control
15) Right-of-way and green space weed management
16) Gypsy Moth Treatment Program
17) Inpatient Hospital Discharge Data (Pesticide hospitalizations)
18) Outpatient Hospital Discharge Data (Pesticide emergency department visits)
19) Mortality Database (Pesticide poisoning deaths)
20) Poison Control System Call Data (Pesticide exposure calls)
21) Hazardous Substances Emergency Events Surveillance System
Minnesota Pesticide Ambient Water Quality
Data Format:
Excel; Environmental Data Access System; In-house Laboratory Information System;
Program Reports.
Identification
Purpose:
To help preserve and protect Minnesota water resources, the Minnesota Department of
Agriculture (MDA) has been monitoring the impacts of pesticides and fertilizers on the
State's water resources for over 20 years.
Abstract:
Information includes:
 Statewide groundwater (monitoring well networks) and surface water (monitoring
stations) pesticide detections and concentrations;
57



Detection and concentration trends with time;
Drinking water and environmental standards or comparative benchmarks; and
Activities based on annual workplans;
Environmental Public Health Tracking Notes:
This data would likely have to be normalized with other state monitoring data if nationally
comparable data measures are desired, then used as a proxy for potential drinking water
exposure in areas where groundwater sources, as identified in individual studies, are likely
to be used as actual drinking water sources.
Maintenance/Update Frequency:
Annually.
Dates Covered:
To varying degrees and in consideration of historic program changes, the data has been
collected since 1989. The current groundwater datasets in the most vulnerable area of the
state are consistent since 2000.
Type of Data:
Hazard
Available Geographies:
Minnesota
Data Release Date:
Annually ca. May-June
Publisher:
Monitoring Unit, Pesticide & Fertilizer Management Division, Minnesota Department of
Agriculture
Data Quality
Data is collected under a Quality Assurance Project Plan that includes collection of
duplicate samples, blanks, chain-of-custody protocols, laboratory analytical protocols, etc.
A principal data caveat is that concentration data is not linked directly to actual exposure,
since data is collected for ambient monitoring purposes and not from actual drinking water
sources (except in the case of special projects focused on drinking water wells or
distribution sources).
58
Specificity of Pesticide Data (if applicable)
Active ingredient (Y)
Pesticide class (Y)
Pesticide product (Y)
Data Access
Existing Data Summaries:
http://www.mda.state.mn.us/chemicals/pesticides/maace.aspx
Availability of Source Data for Public:
http://www.mda.state.mn.us/chemicals/pesticides/maace.aspx
Availability of Source Data for Investigators/EPHT States/Cities:
http://www.mda.state.mn.us/chemicals/pesticides/maace.aspx
Associated Websites
Environmental Data Access System
http://www.pca.state.mn.us/data/eda/search.cfm
MN Dept. of Agriculture Pesticide Monitoring Program Reports
http://www.mda.state.mn.us/chemicals/pesticides/maace.aspx
59
Minnesota Pesticide Use Surveys
Data Format:
Program Reports.
Identification
Purpose:
To collect agricultural pesticide use information in support of various Minnesota
Department of Agriculture (MDA) programs and in support of statutory mandates.
Abstract:
Information includes:
 Pesticide usage information (pounds a.i. per acre) for corn, soybeans, wheat and hay
in even-numbered years;
 Pesticide use practices information (e.g., adoption of Best Management Practices)
in odd-numbered years; and
 Pesticide usage and use practices trend analysis
Environmental Public Health Tracking Notes:
This data would likely have to be normalized with other state monitoring data if nationally
comparable data measures are desired, then somehow adjusted for use as a proxy for
potential human exposure via dermal, inhalation or ingestion pathways to applicators and
residents near crop production sites.
Maintenance/Update Frequency:
Biennially as described.
Dates Covered:
Since 2003.
Type of Data:
Hazard
Available Geographies:
Minnesota
Data Release Date:
Biennially
Publisher:
Pesticide Management Unit and Fertilizer Management Unit, Pesticide & Fertilizer
Management Division, Minnesota Department of Agriculture
60
Data Quality
Data collection methods, quality and limitations are described in each report.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y)
Pesticide class (Y)
Pesticide product (Y)
Data Access
Existing Data Summaries:
http://www.mda.state.mn.us/chemicals/pesticides/pesticideuse.aspx
Availability of Source Data for Public:
Summarized and aggregated data only; individual pesticide usage data from survey
respondents is protected information in Minnesota.
Availability of Source Data for Investigators/EPHT States/Cities:
Summarized and aggregated data only; individual pesticide usage data from survey
respondents is protected information in Minnesota.
Associated Websites
MDA website: Pesticide Use in Minnesota
http://www.mda.state.mn.us/chemicals/pesticides/pesticideuse.aspx
61
Minnesota Pesticide Sales Data (Agricultural and Non-agricultural)
Data Format:
Searchable Database; Program Reports.
Identification
Purpose:
To collect pesticide sales data in support of various Minnesota Department of Agriculture
(MDA) programs and in support of statutory mandates.
Abstract:
Information includes:
 Pesticide sales data information (pounds a.i. sold per year) for all twelve categories
of pesticides (both agricultural and non-agricultural).
Environmental Public Health Tracking Notes:
This data would likely have to be normalized with other state sales data if nationally
comparable data measures are desired. Since mere sales is not an indicator of actual
exposure (and may be difficult to extrapolate to potential exposure), data would somehow
need to be adjusted for use as a proxy for potential human exposure via dermal, inhalation
or ingestion pathways to professional and non-professional applicators and users.
Maintenance/Update Frequency:
Annually.
Dates Covered:
Agricultural pesticides – from 1991 to 1995 through annual posting (non-searchable
database); from 1996 to present, searchable database. For non-agricultural pesticides,
searchable database from 2006.
Type of Data:
Hazard
Available Geographies:
Minnesota
Data Release Date:
Annually.
Publisher:
Pesticide Management Unit, Pesticide & Fertilizer Management Division, Minnesota
Department of Agriculture
62
Data Quality
Data collection methods, quality and limitations are described at the website for the
database.
Specificity of Pesticide Data (if applicable)
Active ingredient (Y)
Pesticide class (Y)
Pesticide product (N) – considered proprietary under Minnesota law.
Data Access
Existing Data Summaries:
http://www.mda.state.mn.us/chemicals/pesticides/useandsales.aspx
Availability of Source Data for Public:
http://www.mda.state.mn.us/chemicals/pesticides/useandsales.aspx
Availability of Source Data for Investigators/EPHT States/Cities:
http://www.mda.state.mn.us/chemicals/pesticides/useandsales.aspx
Associated Websites
MDA website: Minnesota Pesticide Sales Information
http://www.mda.state.mn.us/chemicals/pesticides/useandsales.aspx
63
Minnesota Drinking Water Information System (SDWIS-state)
Data Format:
database
Identification
Purpose:
MDH is empowered by the Public Water Supply rules (Minnesota Rules Chapter 4720) and
the federal Safe Drinking Water Act (SDWA) as the primary state agency responsible for
ensuring that public water systems provide a safe and adequate supply of drinking water.
The Minnesota Drinking Water Information System (MNDWIS) is a database designed to
help MDH-Drinking Water Protection (DWP) supervise public water systems to ensure that
each system meets state and EPA standards for safe drinking water. MNDWIS stores four
major categories of information: inventory, sampling, monitoring, and enforcement.
Inventory data include information on individual drinking water systems such as the system
location, size, and population served. Sampling data include lab results for contaminants
regulated by EPA and the state. Monitoring information contains the schedule for sampling
required under each EPA rule. The enforcement component of MNDWIS allows DWP to
track rule violations and the associated enforcement actions taken against the water systems
to address rule violations. Other than specific information required to be reported to EPA
under SDWA, data contained within MNDWIS is not available to EPA or otherwise
accessible in a national dataset. Drinking water primacy agencies such as MDH are the
stewards of their own data.
In addition to pesticides with maximum contaminant levels (MCLs), data from the the
original unregulated contaminant monitoring program is available in MNDWIS.
Abstract:
 sample collection dates
 sampling results
 System ID number and name
 primary water source
 population served
 principal city served
 principal county served
 seller ID number for purchasing systems
64
Pesticides with MCLs:
Alachlor
Atrazine
Carbofuran
Chlordane
2,4-D
Dalapon
DBCP
Dinoseb
Diquat
Endothall
Endrin
Glyphosate
Heptachlor/heptachlor epoxide
Hexachlorobenzene
Lindane
MCPA
Methoxychlor
Oxamyl
Pentachlorophenol
Picloram
Simazine
Toxaphene
2,4,5-TP
Pesticides on UCMR1
List 1 and 2:
Acetochlor
DCPA+degradates
DDE
EPTC
Molinate
Terbacil
Alachlor ESA
Diazinon
Disulfoton
Diuron
Fonofos
Linuron
Prometon
Terbufos
65
Pesticides on Second
UCMR2 List 1 and 2:
Dimethoate
Terbufos sulfone
Acetochlor
Alachlor
Metolachlor
Six Acetanilide
degradate
Environmental Public Health Tracking Notes:
Could be used to track pesticides in PWS over time; however, detections are relatively rare.
Maintenance/Update Frequency:
Updated continuously
Dates Covered:
1988-To present.
Type of Data:
Hazard
Available Geographies:
State-wide, except PWS on tribal lands and those systems serving Minnesota but located in
neighboring states.
Data Release Date:
Data are updated continuously in MNDWIS.
Publisher:
Minnesota Department of Health, Drinking Water Protection.
Data Quality
Data are of good quality. One issue is that some LODs are set relatively high if the MCL is
also high.
Specificity of Pesticide Data (if applicable)
Active ingredient
Data Access
Existing Data Summaries:
MDH DWP produces a report each year of contaminant results for the state:
http://www.health.state.mn.us/divs/eh/water/com/dwar/report08.html
Availability of Source Data for Public:
Data are not available to the public unless requested.
Availability of Source Data for Investigators/EPHT States/Cities:
The data are considered public information and are available to the EPHT program
Associated Websites
MDH Drinking Water Protection
http://www.health.state.mn.us/divs/eh/water/index.html
66
Compliance Information System (Pesticide Misuse/Human Exposure Complaints)
Data Format:
Mostly in .pdf, or reports It depends on what is being asked for.
Identification
Purpose:
Pesticide misuse complaints involving injury/damage to humans (and, animals, food/feed
products and the environment) are submitted to MDA for follow-up investigation by an
MDA Agricultural Chemical Investigator.
Abstract:






who/what was exposed/injured/damaged,
where event occurred,
what are the symptoms of exposure/injury/damage, if any
date and time that the pesticide misuse or exposure occurred,
who is allegedly or found responsible, and
pesticide product(s), alleged or confirmed.
For specific elements on the complaint report form, see:
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/ag
00155pestfert.aspx
Maintenance/Update Frequency:
Real time as complaints are received and investigations are assigned.and
performed/completed.
Type of Data:
Hazard, Health outcome
Minn. Stat. Chapter 18 D authorized Investigations. Alleged complaint, investigation
evidence (investigator reports, interviews, statements, photographs, sample receipts/chain
of custody/laboratory analysis reports, etc.)
Available Geographies:
State-wide
Data Release Date:
As requested; data provided pursuant to MN Data Practices Act.
Publisher:
67
Minnesota Department of Agriculture (MDA), Pesticide & Fertilizer Management
Division l, Inspections and Permitting Unit
Data Quality
Are any relevant fields allowed to contain missing data? Yes.
Are missing data ever imputed by the data Source before they are released? When available
and verified as correct and accurate.
Are there caveats to consider inherent in the collection of the data?
Personal testimonials, exposure/ injury complaints received period of time post-alleged
exposure/injury, contradictions in available data (for example: no official medical records
or verification of exposure/injury; official weather records vs. personal records; uncertainty
or unknown pesticide(s) allegedly involved, etc.)
Specificity of Pesticide Data (if applicable)
Active ingredient (Y) If known or discoverable.
Pesticide class (Y) same
Pesticide product (Y) same
Specificity will vary depending on knowledge of the person filing the complaint, and on the
ability of the investigation to determine pesticide(s) involved.
Data Access
Existing Data Summaries:
Internal MDA reports only.
Availability of Source Data for Public:
All investigation case file data is available after the investigation is closed, except as
prohibited or otherwise managed by the Minnesota Government Data Practices Act. The
Act classifies the identity of persons who register complaints with a government agency
regarding a licensee or applicant as private data on individuals (Minn. Stat. § 13.41, Subd.
2(a)). The identity of persons who register complaints regarding violations of state law
pertaining to the use of real property is classified as confidential (Minn. Stat § 13.44).
Availability of Source Data for Investigators/EPHT States/Cities:
All investigation case data information is available after the investigation is closed, except
SEE ABOVE
Associated Websites
MDA website on reporting pesticide complaints
http://www.mda.state.mn.us/en/chemicals/pesticides/complaints.aspx
68
Other Pesticide Hazard Data Sources
Aquatic pesticide use data (DNR)
Any pesticide control of aquatic pests, such as duckweed or snails (Swimmer’s Itch) in
public waters requires a DNR aquatic plant management permit. About 4,500 permits are
issued each year. Information on the permit application includes address of applicant, lake
name, county, name of the chemical, applicator type (either commercial applicator or the
permit applicant).
http://www.dnr.state.mn.us/eco/apm/index.html
School/daycare pesticide use surveys (MDA)
MDA conducted a pesticide use survey in hundreds of schools in 1999. An update is
planned in the next few months. A similar survey of daycares was conducted in 2001. A
third, legislatively-mandated survey was also conducted in 2001 by MDA’s agricultural
chemical inspectors, who conducted in-depth interviews with 2 schools in each of the
inspectors’ districts.
http://www.mda.state.mn.us/plants/pestmanagement/ipm/ipmschools.aspx
http://www.mda.state.mn.us/licensing/licensetypes/schoolpestapp.aspx
Note that schools are also required by the MN statute: "Parents' Right to Know Act of
2000, (M.S. 121A.30)" to send out a notice letting parents know if the school intends to use
pesticides in or around schools. By law, parents must be notified by September 15 of each
school year. Any parent wanting information on pesticide applications other than those
listed in the Pesticide Notice can request it by filling out and returning the Individual
Notice for Parents or Guardians. However, these notices are not compiled, tracked, or sent
to a state agency.
Pesticide disposal program data (MDA)
Pesticide users in every county in MN have the opportunity to dispose of unwanted
agricultural pesticides once a year and household pesticide products more than once a year.
Pesticides collected include: insecticides, fungicides, herbicides, rodenticides and other
pesticides in the form of liquids, granulars, powders, baits, paste and aerosols. MDA
partners with Household Hazardous Waste facilities (and provides funding to them) to
record information on collected products, including product name and EPA registration
number. The information is tied to collection site, not an individual or residence.
Agricultural pesticide information has been collected since 1990. Specific household
pesticide information was collected starting in the mid-1990’s.
http://www.mda.state.mn.us/chemicals/spills/wastepesticides.aspx
Pesticide storage and chemigation permit data (MDA)
MDA issues bulk agrichemical storage permits to bulk agricultural facilities. A bulk
pesticide is defined as a liquid pesticide that is held in an individual container with a
pesticide content of 56 U.S. gallons or more, or 100 lbs. or more net dry weight, including
mini-bulk pesticides unless otherwise specified. Only technical grade, formulated grade,
and other similar grades are included in this definition. MDA collects information on the
facilities via permit applications.
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/ag010
74bulk.aspx
69
Permits are also issued for chemigation systems. The permit application includes the
location of the site to be chemigated, the pesticide brand name, type of water source, and
amount of pesticide to be applied via chemigation.
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/ag010
73chem.aspx
Pesticide dealer and applicator licensure (MDA)
The MDA trains and certifies applicators and issues licenses. There are different license
types with specific categories depending on the intended application site. Commercial
pesticide applicator licenses are for pesticide applicators who apply any pesticide “for
hire”. Noncommercial licenses are for pesticide applicators that apply restricted use
pesticides (RUP) as part of their job on property owned or contracted by their employer.
Structural Pest Control Applicator licenses are for applicators that apply pesticides on or in
structures. License types include: Core (Pesticides using hand or ground equipment),
General Aerial, Field Crop Pest Management, Turf & Ornamentals, Aquatic, Forest
Spraying, Seed Treatment, Anti-Microbial, Rights-of-Way, Agricultural Pest ControlAnimal, Mosquito and Black Fly Control, Food Processing Pest Management, Stored Grain
and Fumigation, Pocket Gopher, Wood Preservatives, Sewer Root Control, Noncommercial
Structural, Structural-Master. Collected information is stored in a searchable database and
includes applicator address, license type, and license expiration. Note that applicators
applying RUPs must keep records of applications for two years. This information is not
routinely collected but may be used during an MDA investigation or inspection.
http://www.mda.state.mn.us/licensing/licensetypes/pesticideapplicator.aspx
Pesticide dealers must maintain an MDA-issued Pesticide Dealer License to sell restricted
use pesticides (RUP) and/or bulk pesticides to Minnesota end users. Dealers must record all
RUP sales to end-users by the end of the business day the RUP is made available. The
dealer must maintain a copy of the year’s Report of RUP sales on-site for 5 years. Sales
information includes pesticide brand name, EPA registration number, amount sold, full
name of applicator, applicator license number, date RUP was picked-up or delivered, and
name/address of the person other than the applicator to whom the product was made
available. This information is not collected by MDA.
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/whone
edpdl.aspx
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/salesp
osting.aspx
http://www.mda.state.mn.us/sitecore/content/Global/MDADocs/licensing/chemicals/rupsal
es.aspx
Worker Protection Standard program data (MDA)
MDA conducts The Worker Protection Standard (WPS) Train-the-Trainer Program to
qualify participants to conduct WPS pesticide safety training for workers and handlers. For
registration purposes, information is collected on the participant’s mailing address and
location of the training. Note that the WPS requires employer pesticide recordkeeping for
30 days after the restricted entry interval (REI) expires (as opposed to applicator RUP
records that must be kept for two years). Information required to be displayed by the WPS
includes date of treatment, location and description of treated area, product name and active
ingredient, EPA registration number, and REI information. There is also employer
70
recordkeeping of worker training. WPS records are not collected by MDA but may be used
during an investigation or inspection. http://www.mda.state.mn.us/chemicals/spills/workerprotection-standard.aspx
Crop pest surveys (MDA)
The Plant Pest Survey collects data on insects, diseases and weeds during the growing
season. Surveys are conducted by field staff throughout the state in five agronomic crops:
corn, soybeans, small grains, alfalfa and sunflowers. The sampling program is designed to
serve as a resource for information on regional pest conditions. For major crops (corn,
soybeans, small grains), approximately five fields of a given crop are sampled in an
average sized county. The number of fields needed to make an accurate estimate varies by
geography, the target pest, etc. Typically a surveyor will employ multiple sampling
methods in an individual field and will be estimating numbers of multiple insect species as
well as the presence of disease or weeds.
http://www.mda.state.mn.us/plants/pestmanagement/plant-pest-survey-program.aspx
Cooperative Agricultural Pest Surveys (MDA)
MDA conducts the surveys, with technical support, regional standardization and partial
funding provided by USDA APHIS. Survey data are entered into a national pest database
called the National Agricultural Pest Information System (NAPIS). MN survey targets for
2007 included emerald ash borer, potato cyst nematode, Karnal bunt, Sirex wood wasp,
exotic bark beetles, Asian longhorned beetle, small hive beetle, soybean cyst nematode,
soybean rust, sudden oak death.
http://www.mda.state.mn.us/plants/pestmanagement/invasivesunit/mncaps.aspx\
Mosquito control (MMCD)
The Metropolitan Mosquito Control District (MMCD) provides services to 2.7 million
people living in an area covering 2,800 square miles in the seven county Minneapolis and
St. Paul, Minnesota metropolitan area. MMCD surveys for and controls mosquitoes that
transmit human diseases, monitors deer tick populations, and surveys for and controls
nuisance-causing mosquitoes, biting gnats, and mosquitoes that transmit dog heartworm.
Two larvicides are used (Bti and methoprene). For adult mosquito spraying, pyrethroids are
used. Staff compile and analyze population and disease surveillance data and keep records
of treatments. This information is also compiled into reports (2008 report:
http://www.mmcd.org/pdf/tab009final.pdf)
Right-of-way and green space weed management (MnDOT)
MnDOT and contract pesticide applicators treat up to 10% (approximately 17,500 acres) of
MnDOT owned greenspace (roadsides, rest areas, storage yards, etc.) with pesticides
(primarily herbicides). The Pesticide Applicator Log System began in 2006 as a repository
for all daily application records. Each record is inputted for permanent record and retrieval
of statewide or district wide acreages by weed control objective, target weed and pesticide.
http://www.dot.state.mn.us/environment/forestry/veg_mgmt/herbicide.html
Pesticide incident response (MDA)
71
MDA is the lead agency for response to, and cleanup of, agricultural chemical
contamination (pesticides and fertilizers) in Minnesota. State law requires that agricultural
chemical incidents must be immediately reported to MDA. The Incident Response Program
and other units within the MDA maintain databases on incident sites and agricultural
chemical facilities.
http://www.mda.state.mn.us/chemicals/spills/incidentresponse.aspx
Gypsy Moth Treatment Program (MDA)
The Minnesota “Slow the Spread” Action Zone covers the Arrowhead region and a few
counties in extreme southeast Minnesota. Bacillus thuringiensis var. kurstaki is applied by
aircraft. County tax lists are used to identify residents within the proposed treatment area,
and the MDA attempts to notify everyone in the area by mail. Local law enforcement,
health departments, schools and hospitals are also notified.
http://www.mda.state.mn.us/plants/pestmanagement/gmunit/gmtreatments.aspx
72
Minnesota Inpatient Hospital Discharge Data (Pesticide hospitalizations)
Data Format:
Electronic (Can be Excel, dbase, SAS, etc.)
Identification:
Purpose:
The MN Hospital Discharge Database collects hospital discharge information from the
Uniform Bill, 1992 version (UB-92), which was created for the purpose of making
payments.
Abstract:
The MN Hospital Discharge Database collects hospital discharge information from acute
care hospitals submitting data to the Minnesota Hospital Association (MHA). Requests for
injury-related hospital discharge data (injuries encompass poisonings) can be made to the
MDH Injury and Violence Prevention Unit, which obtains data directly from MHA.
Hospital discharge data are processed annually, and generally require approximately 16-24
months of processing before becoming available for use by MDH programs.
Data fields available include:
 Patient demographics (age, sex, county, ZIP code, and state of residence)
 Discharge and admission dates
 Discharge disposition code
 Billing type
 Payer code
 Diagnosis codes
 External cause of injury codes (includes place of occurrence codes)
 Procedure codes.
Environmental Public Health Tracking Notes:
If this is a measure that we will potentially consider tracking, then look at the EPHT carbon
monoxide poisoning indicator as a similar model.
Possible ICD-9 codes: 989.0 – 989.4, E861.4, E863.0 – E863.9, E950.6, E980.7
Source: NIOSH publication #2006-102 (Pesticide-related illness and injury surveillance:
A how-to guide for state-based programs)
ICD-9 code
Condition
989.9
Toxic effect of hydrocyanic acid and cyanides
989.1
Toxic effects of strychnine and its salts
989.2
Toxic effects of chlorinated hydrocarbons, excluding chlorinated
hydrocarbon solvents
989.3
Toxic effects of organophosphates and carbamates
989.4
Toxic effects of other pesticides and mixtures, not elsewhere classified
Accidental
poisoning by household & other disinfectants not ordinarily used on the person
E861.4
E863.0
Accidental poisoning by insecticides of organochlorine compounds
E863.1
Accidental poisoning by insecticides of organophosphorus compounds
E863.2
Accidental poisoning by carbamates
73
E863.3
E863.4
E863.5
E863.6
E863.7
E863.8
E863.9
E950.6
E980.7
Accidental poisoning by mixtures of insecticides
Accidental poisoning by other and unspecified insecticides
Accidental poisoning by herbicides
Accidental poisoning by fungicides
Accidental poisoning by rodenticides
Accidental poisoning by fumigants
Accidental poisoning by other and unspecific pesticides
Suicide/self-inflicted poisoning by agricultural and horticultural chemical
and pharmaceutical preparation other than plant foods and fertilizers
Poisoning by agricultural and horticultural chemical and pharmaceutical
preparations other than plants, foods, and fertilizers
Maintenance/Update Frequency:
Data are processed annually by MHA, and require 16-24 months of preprocessing before
becoming available.
Dates Covered:
Discharge dates of January 1, 1998 – December 31, 2007.
Type of Data:
Health outcome
Available Geographies:
State, county, ZIP code.
Data Release Date:
Released annually, date varies.
Publisher:
Data owner: Minnesota Hospital Association (MHA);
Data steward: Minnesota Department of Health, Injury and Violence Prevention Unit
(MDH IVPU)
Data Quality
Data submission to MHA is voluntary on the part of Minnesota hospitals. Admissions to
Veteran’s Administration and other federal facilities are not included. According to IVPU
(as of June 2009), they receive hospital discharge data from approximately 85% of the
hospitals in the state, representing approximately 95-98% of all Minnesota injury data,
under which pesticide poisonings would be classified.
Hospitalizations of MN residents that occurred out of state are not included. Hospital
discharge data lack personal identifiers, which limits the ability to distinguish repeat
follow-up visits for a single event from independent events.
Because the data are collected for the purpose of establishing billing records, the quality of
some health-related data fields may be limited. Some fields are allowed to contain missing
74
data; the place of occurrence code (which denotes where the injury or poisoning occurred)
and procedure code typically have low level of completeness. The external cause of injury
code (e-code) is routinely collected, but not mandated, in MN hospitalization datasets.
Although ZIP code of patient’s residence is collected, this may not be the location where
the individual was poisoned or hospitalized.
Hospitalizations for pesticide poisonings would represent severely poisoned cases. They do
not include patients treated in outpatient settings, those who receive medical care but are
not hospitalized, those who do not seek medical care, or those who die from pesticide
poisoning without having received medical care.
Specificity of Pesticide Data (if applicable)
Pesticide class (Y, some)
Data Access
Availability of Source Data for Public:
In order to maintain confidentiality, small counts ( 5) should be suppressed. Therefore,
analyses at smaller geographic resolutions (e.g. ZIP code level) may not be limited.
Availability of Source Data for Investigators/EPHT States/Cities:
Consider establishing data sharing agreements.
Associated Websites
Pesticide-Related Illness and Injury Surveillance: A How-To Guide for State-Based
Programs (This manual [NIOSH Publication No. 2006-102] provides information on how
to establish state-based surveillance programs for pesticide-related illnesses.)
http://www.cdc.gov/niosh/docs/2006-102/
75
Minnesota Outpatient Hospital Discharge Data (Pesticide Emergency Department
Visits)
Data Format:
Electronic (Can be Excel, dbase, SAS, etc.)
Identification
Purpose:
The MN Hospital Discharge Database collects hospital discharge information from the
Uniform Bill, 1992 version (UB-92), which was created for the purpose of making
payments.
Abstract:
The MN Hospital Discharge Database collects hospital discharge information from acute
care hospitals submitting data to the Minnesota Hospital Association (MHA). Requests for
injury-related hospital discharge data (injuries encompass poisonings) can be made to the
MDH Injury and Violence Prevention Unit, which obtains data directly from MHA.
Hospital discharge data are processed annually, and generally require approximately 16-24
months of processing before becoming available for use by MDH programs.
Data fields available include:
 Patient demographics (age, sex, county, ZIP code, and state of residence)
 Discharge and admission dates
 Discharge disposition code
 Billing type
 Payer code
 Diagnosis codes
 External cause of injury codes (includes place of occurrence codes)
 Procedure codes.
Environmental Public Health Tracking Notes:
If this is a measure that we will potentially consider tracking, then look at the EPHT carbon
monoxide poisoning indicator as a similar model.
Possible ICD-9 codes: 989.0 – 989.4, E861.4, E863.0 – E863.9, E950.6, E980.7 (same as
hospitalizations)
Maintenance/Update Frequency:
Data are processed annually by MHA, and require 16-24 months of preprocessing before
becoming available.
Dates Covered:
Discharge dates of January 1, 1998 – December 31, 2007.
Type of Data:
Health outcome
76
Available Geographies:
State, county, ZIP code.
Data Release Date:
Annually, date varies.
Publisher:
Data owner: Minnesota Hospital Association (MHA);
Data steward: Minnesota Department of Health, Injury and Violence Prevention Unit
(MDH IVPU)
Data Quality
Data submission to MHA is voluntary on the part of Minnesota hospitals. Admissions to
Veteran’s Administration and other federal facilities are not included. According to IVPU
(as of June 2009), they receive hospital discharge data from approximately 85% of the
hospitals in the state, representing approximately 95-98% of all Minnesota injury data,
under which pesticide poisonings would be classified.
ED visits of MN residents that occurred out of state are not included. Hospital discharge
data lack personal identifiers, which limits the ability to distinguish repeat follow-up visits
for a single event from independent events.
Because the data are collected for the purpose of establishing billing records, the quality of
some health-related data fields may be limited. Some fields are allowed to contain missing
data; the place of occurrence code (which denotes where the injury or poisoning occurred)
and procedure code typically have low level of completeness. The external cause of injury
code (e-code) is routinely collected, but not mandated, in MN hospitalization datasets.
Although ZIP code of patient’s residence is collected, this may not be the location where
the individual was poisoned or hospitalized.
In previous years, there have been concerns about the overall data quality of MN outpatient
claims. In 2006, a quality assurance assessment of outpatient claims revealed that some
MN hospitals were not reporting all of their outpatient claims, and thus pre-2006 ED visit
data might not be usable. MDH IVPU has since conducted extensive analyses on injury and
poisoning-related ED visit claims, and has concluded that there is no significant difference
between pre-2006 and post-2006 data for injury and poisoning-related ED visits.
ED visits for pesticide poisoning might represent a wide range of exposures, from
suspected exposure to severe poisoning. The ED visits may result in treatment and release,
or in hospitalization or death. ED visits that result in hospitalizations are counted as
inpatient hospitalization cases and do not appear in the ED visit dataset.
Specificity of Pesticide Data (if applicable)
Pesticide class (Y, some)
77
Data Access
Availability of Source Data for Public:
In order to maintain confidentiality, small counts ( 5) should be suppressed. Therefore,
analyses at smaller geographic resolutions (e.g. ZIP code level) may not be limited.
Availability of Source Data for Investigators/EPHT States/Cities:
Consider establishing data sharing agreements.
Associated Websites
Pesticide-Related Illness and Injury Surveillance: A How-To Guide for State-Based
Programs. (This manual [NIOSH Publication No. 2006-102] provides information on how
to establish state-based surveillance programs for pesticide-related illnesses.)
http://www.cdc.gov/niosh/docs/2006-102/
78
Minnesota Mortality Database (Pesticide Poisoning Deaths)
Data Format:
Electronic (Can be Excel, dbase, SAS, etc.)
Identification
Purpose:
The MN Mortality Database contains information on demographic and cause of death data
collected from death certificates. These mortality data are used for statistical analyses.
Abstract:
The MN Mortality Database collects information from death certificates. Cause of death for
death records is reported by the attending physician or coroner/medical examiners. Funeral
directors often provide demographic information on the decedent. These data are entered
directly into the Vital Records Vision (VRV 2000) system at the Minnesota Department of
Health. Currently 100% of death records are filed electronically. Typically there is a one
year lag until data are available for analysis by MDH programs.
Data fields available include:
 Death certificate number
 Date and time of death
 Date and time of injury
 City, county, state of death
 ZIP code, city, county, state of injury
 Underlying cause of death
 Contributing causes of death
 Manner of death
 Demographics of decedent (gender, date of birth, location – city, county, state – of
birth and residence at time of death, marital status, race, ethnicity, education level,
occupation
Environmental Public Health Tracking Notes:
If this is a measure that we will potentially consider tracking, then look at the EPHT carbon
monoxide poisoning indicator as a similar model.
79
Possible ICD-10 codes: T60.0 – T60.9, X48, X68, X87, Y18 and maybe T54, X49, X69,
X86, Y19
Source: NIOSH publication #2006-102 (Pesticide-related illness and injury surveillance:
A how-to guide for state-based programs)
ICD-10 code Condition
T60.0
Toxic effect of organophosphate and carbamate insecticides
T60.1
Toxic effect of halogenated insecticides
T60.2
Toxic effect of other insecticides
T60.3
Toxic effect of herbicides and fungicides
T60.4
Toxic effect of rodenticides
Toxic effect of other pesticides
T60.8
T60.9
Toxic effect of pesticide, unspecified
X48
Accidental poisoning by and exposure to pesticides
X68
Intentional self-poisoning by and exposure to pesticides
X87
Assault by pesticides
Y18
Poisoning by and exposure to pesticides
*Note: ICD-10 does not have specific codes for disinfectants. To find disinfectant
poisonings, try T54, X49, X69, X86, and Y19, which are codes for corrosive and noxious
substances.
T54
Toxic effect of corrosive substances
X49
Accidental poisoning by and exposure to other and unspecified chemicals
and noxious substances
X69
Intentional self-poisoning by and exposure to other and unspecified
chemicals and noxious substances
X86
Assault by corrosive substance
Y19
Poisoning by and exposure to other and unspecified chemicals and
noxious substances, undetermined intent
Maintenance/Update Frequency:
Data are processed annually, and generally are available for analysis after a one year lag.
Dates Covered:
Dates of death January 1, 1989 – December 31, 2007.
Type of Data:
Health outcome
Available Geographies:
State, county, ZIP code.
Data Release Date:
Annually, date varies
Publisher:
Data owner: Minnesota Department of Health, Center for Health Statistics;
80
Location of Data source: Minnesota Department of Health, Injury and Violence Prevention
Unit (MDH IVPU)
Data Quality
Unlike hospital discharge datasets, death certificate datasets contain both resident deaths
that occur out of state as well as non-resident deaths that occur in Minnesota. Thus, the
border leakage problem that is inherent in the hospital discharge dataset is not an issue for
mortality data. Some fields are allowed to contain missing data; notably, date of injury and
place of injury are sometimes left missing.
Though not always complete, the narratives from death certificates often provide valuable
information that may not be contained at the same level of detail in the cause of death
codes. Death certificate data requests can be made to MDH Injury and Violence Prevention
Unit (IVPU), whose epidemiologist has a direct electronic view of MN death certificates
maintained at the MDH Center for Health Statistics. Obtaining mortality datasets from
IVPU is advantageous because of the ability to view death certificate narrative fields
electronically.
It is important to note that cause of death may not correctly be attributed to pesticide
poisoning. Deaths may be misclassified and attributed to other causes.
Specificity of Pesticide Data (if applicable)
Pesticide class (Y, some)
Data Access
Availability of Source Data for Public:
In order to maintain confidentiality, small counts ( 5) should be suppressed. Therefore,
analyses at smaller geographic resolutions (e.g. ZIP code level) may not be limited.
Availability of Source Data for Investigators/EPHT States/Cities:
Consider establishing data sharing agreements.
Associated Websites
Pesticide-Related Illness and Injury Surveillance: A How-To Guide for State-Based
Programs (This manual [NIOSH Publication No. 2006-102] provides information on how
to establish state-based surveillance programs for pesticide-related illnesses.)
http://www.cdc.gov/niosh/docs/2006-102/
81
Minnesota Poison Control System call data (pesticide exposure poison control call
data)
Data Format:
Toxicall data reports (PDF), or other electronic (Excel, etc.)
Identification
Purpose:
The Minnesota Poison Control System (MPCS) collects call data from the general public
and healthcare providers, mostly for calls involving an acute or suspected exposure to a
toxic substance. The primary function of the poison center is to provide the caller with
toxicologic and treatment information, and to refer the patient to a healthcare facility if
necessary.
Abstract:
Calls to MPCS are answered by trained pharmacists, who provide the caller with guidance
about exposure to toxic substances, and when needed, refer the caller to a healthcare
facility for further treatment. The call information are entered into a Toxicall database,
from which data reports can be generated. Toxicall data are fed realtime via FTP server to
MDH in order to support real-time toxicosurveillance for early warning signs of a public
health event.
Data fields include:
 Call date
 Time of exposure
 Patient demographics (gender, age, ZIP code and state)
 ZIP code, state of caller
 Caller site
 Exposure site
 Call type (exposure vs. informational)
 Exposure reason
 Substance
 Medical outcome
 Management site
Environmental Public Health Tracking Notes:
If this is a measure that we will potentially consider tracking, then look at the EPHT carbon
monoxide poisoning indicator as a similar model.
For PCC database query criteria, use NIOSH publication #2006-102 (Pesticide-related
illness and injury surveillance: A how-to guide for state-based programs), Appendix C
Section 8
Maintenance/Update Frequency:
Real-time
Dates Covered:
82
January 1, 2000 – current
Type of Data:
Exposure
Available Geographies:
state
Data Release Date:
upon request
Publisher:
Data owner: Minnesota Poison Control System
Data steward: Minnesota Poison Control System, or MDH Infectious Disease and
Prevention Control
Data Quality
The catchment area for calls to MPCS includes anyone (both residents and non-residents)
who have access to a telephone and are aware of the services provided by MPCS. Thus,
poison control call data are highly reliant on the knowledge, attitudes, and practices by
local residents around the use of poison control centers. Furthermore, in the event of an
overload of calls to MPCS, calls are re-routed to another state’s poison control center.
Those calls would not be included in the MPCS dataset, although they are contained in the
national dataset maintained by the American Association of Poison Control Centers.
In years 2002-2007, over 50% of the call volume for calls involving human exposure to a
potentially harmful substance pertained to children under 5 years of age. Adults may be
more likely to call 911 or a doctor, or go to the emergency department rather than call the
poison center. Thus, poison center calls may not necessarily be representative of pesticide
exposure for some population subgroups. Most calls involving pesticide exposure are more
likely to involve household exposures, rather than agricultural or occupational exposures.
There are data fields that may remain missing in MPCS. Furthermore, patient
demographics are obtained from the caller and are not verified. For example, the age of the
patient may be an estimated guess made by the caller. The location of the caller is often
used as a surrogate measure for the patient’s residence. This limits the geographic unit of
analysis to state-wide analyses.
Finally, it is important to realize that poison center calls are not confirmed exposures, much
less confirmed poisoning cases.
Specificity of Pesticide Data (if applicable)
Pesticide class (Y, some)
Data Access
83
Availability of Source Data for Public:
Presenting summary data should be ok, however consider suppressing small counts ( 5) to
maintain confidentiality.
Availability of Source Data for Investigators/EPHT States/Cities:
Consider establishing data sharing agreements.
Associated Websites
Pesticide-Related Illness and Injury Surveillance: A How-To Guide for State-Based
Programs (This manual [NIOSH Publication No. 2006-102] provides information on how
to establish state-based surveillance programs for pesticide-related illnesses.)
http://www.cdc.gov/niosh/docs/2006-102/
Acute work-related pesticide poisonings reported to poison control centers (This is one of
the CSTE/NIOSH occupational health indicators)
http://www.cste.org/dnn/ProgramsandActivities/OccupationalHealth/OccupationalHealthIn
dicators/Indicator11/tabid/107/Default.aspx
84
Minnesota Hazardous Substances Emergency Events Surveillance System
Data Format:
electronic
Identification
Purpose:
The HSEES system collects information to describe events involving unplanned and illegal
releases of hazardous substances and the resulting acute public health effects.
Abstract:
Information on hazardous substance incidents is collected from the Minnesota Duty
Officer, the National Response Center, the U.S. Department of Transportation Hazardous
Materials Incident Reporting System, media reports, responders, businesses or other
sources. Further information is then gathered by contacting others with knowledge about
the incident.
Data fields include:
 Type and quantity of substance involved
 Time, place, cause of incident
 Event type (fixed-facility or transportation-related event)
 Number of victims and injuries sustained
 Response actions and responding agencies
 Public health protection actions taken
Environmental Public Health Tracking Notes:
Only a few states currently have HSEES funding, and so it may be difficult to establish
HSEES data as a nationally consistent data measure.
The MN HSEES program ended on September 29, 2009, but MDH is still able to receive
regular incident reports from the MN Duty Officer.
Maintenance/Update Frequency:
Official HSEES funding ended 9/29/09, but still receiving ongoing reports from Duty
Officer
Dates Covered:
1995-2008
Type of Data:
Exposure
Available Geographies:
state, county
Data Release Date:
upon request
Publisher:
85
Minnesota Department of Health, Division of Environmental Health
Data Quality
HSEES data represent aggregate data about incidents, and individual patient characteristics
are not collected or verified. There may be unplanned or illegal releases of pesticides that
occur but are not reported. Some incidents may be excluded from the dataset because the
minimum quantity of 10 pounds or one gallon was not met.
Specificity of Pesticide Data (if applicable)
Pesticide class (Y, some)
Data Dictionary (if applicable)
HSEES Protocol March 2004
http://www.atsdr.cdc.gov/HS/HSEES/protocol030804.html
Data Access
Existing Data Summaries:
http://www.health.state.mn.us/divs/eh/hazardous/surv/index.html#healthtables
Availability of Source Data for Public:
reports available on website
Availability of Source Data for Investigators/EPHT States/Cities:
upon request to MDH HSEES coordinator
Associated Websites
HSEES home site on ATSDR
http://www.atsdr.cdc.gov/HS/HSEES/
HSEES home site on the MDH website (Includes pesticide incident reports.)
http://www.health.state.mn.us/divs/eh/hazardous/surv/index.html#healthtables
86
EPHT Pesticide Indicator Content Work Group Team
Proposal (DRAFT 9-8-09)
Rationale:
Pesticides remain a significant public concern and their health impacts have been the
subject of increasing study. From prospective studies of agricultural workers to cohort
studies of newborn-mother pairs, pesticides are implicated and being extensively studied
for their impacts on cancer, birth outcomes, neurodegenerative illnesses and many other
health effects.
The confluence of several phenomena makes pesticides an ideal subject for inclusion in the
National EPHT network, and for their exploration and adaptation in state and local tracking
portals. First, there is no current unified national surveillance system for pesticides. The US
EPA, CDC, NIOSH and the Department of Agriculture each evaluate different aspects of
pesticide use, hazard, exposure and health outcomes, but their respective efforts have never
been systematically evaluated for their ability to tell the story of pesticides. Second, a
variety of data sources exist that are valuable and under-utilized for promoting an
understanding of pesticides. Third, pesticide use, exposure and health outcomes vary
substantially by personal, socio-economic, economic sector and spatial factors, which
makes nationally consistent reporting critical. And, this variability lends itself well to the
functionality that is being built in national and state portals.
Stakeholders:

US EPA – Office of Pesticide Programs
o Health Effects Division - Incident Data Workgroup
o Biological and Economic Analysis Division (BEAD)
o Emergency Planning and Community Right-to-Know Act (EPCRA) Tier II
data

US EPA – Office of Water
o Drinking Water Protection
o Standards and Risk Management Division
o Unregulated Contaminant Monitoring Program

USDA
o Pesticide Data Program (PDP)
o National Agricultural Statistics Service (NASS)
o Economic Research Service (ERS)

CDC
o National Center of Health Statistics (NHANES)
o NIOSH (SENSOR)
87
o Behavioral Risk Factor Surveillance System (BRFSS)
o National Center on Birth Defects and Developmental Disabilities

US FDA – Pesticide Program Residue Monitoring

USGS –
o National Water Quality Assessment (NAWQA)

National Pesticide Use Database
o National Water Information System
o The Geochemical Landscapes Project
(http://minerals.cr.usgs.gov/projects/geochemical_landscapes/index.html)

CDC EPHT Funded and Non-Funded State and Local Agencies
o State Agricultural, Environmental, and Health Departments

American Association of Poison Control Centers (AAPCC)

Other potential stakeholders, subject to discussion:
o Doane Marketing, Inc. (Private Agricultural Marketing Firm)
o IPM Institute of North America, Inc.
o National Pest Management Association, Inc. (NPMA)
o Pesticide Action Network (http://www.panna.org/)
o Pesticide industry representation
o National environmental organizations (e.g., NRDC, Env Defense Fund)
o Environmental Defense
o Pesticide advocacy groups (e.g., Beyond Pesticides, PANNA, Silent Spring)
88
Existing Data Sources and Measures:
Pesticide Sales, Use, Environmental Levels and Pest Conditions:
USA EPA BEAD have created market estimate of national pesticide sales and use in
agricultural, commercial and residential markets using data from the USDA, private
sources and EPA’s own data. The data supporting these market estimates might possibly be
used to characterize pesticide sales and usage at the state and local level. However, much
of this data is proprietary and may not be possible to use in indicators intended for public
use. 1
The USDA NASS estimates agricultural use with the estimates of types and
amounts of pesticide used on different crops and commodities. This data source could be
used to provide state level agricultural use estimates. 2
Two states have additional state pesticide surveillance data. New York has use data
which summarizes commercial, structural and landscape use along with sales data which
can estimate agricultural use. California has a system to track agricultural use which also
includes large outdoor institutional uses. Other funded states may also be able to use their
own agriculture departments as a data source to characterize agricultural use. The
enactment of Oregon’s Pesticide Use Reporting System (PURS) has been delayed until
2013. 3
The EPA Emergency Planning and Community Right-to-Know Act (EPCRA) Tier
II data may also be a source of information on the amount of pesticides stored in a
jurisdiction which could be used as a proxy for local use. However, due to the sensitivity
of this information the data would most likely need to be aggregated at larger geography. 4
USGS National Water Quality Assessment (NAWQA) data could be used to
characterize levels of pesticide contamination in ground and surface water sources serving
both urban and agricultural communities.
1
EPA - BEAD 2000 - 2001 Pesticide market estimates as viewed at
ttp://www.epa.gov/oppbead1/pestsales/01pestsales/introduction2001.htm
2
USDA, National Agricultural Statistics Service (NASS) as viewed at
http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1001
3
Oregon Department of Agriculture - Oregon Pesticide Use Reporting System
at http://www.oregon.gov/ODA/PEST/purs_index.shtml
4
EPA Emergency Planning and Community Right-to-Know Act (EPCRA)as viewed at
http://www.epa.gov/OEM/content/epcra/epcra_storage.htm
89
There is a need to further investigate data sources which characterize illegal use of
pesticides. EPA may be a good source for data on enforcement actions for these types of
products. 5
To characterize patterns of pest problems in states and localities it might be possible
to characterize a few problematic plant, animal, and microbe species in both agricultural
and residential settings. In agriculture the USDA APHIS Cooperative Agricultural Pest
Survey (CAPS) may be useful. 6 For residential pest surveys the CDC’s national
Behavioral Risk Factor Surveillance System (BRFSS) might be a way of characterizing the
presence of common household pest like ants, roaches, and rodents or the personal
residential use of pesticides. In NYC, survey data developed internally and data on
housing quality contracted through the Census Bureau have been useful in characterizing
geographic and socioeconomic disparities in the distribution of pests and subsequent
personal pesticide use. National sources of data on housing conditions could also be used
as an indicator predicting pest problems. [Sources of this data?]
Pesticide Exposures:
All funded states except Maine participate in the AAPCC National Poison Data
System (NPDS). This system covers most of the nation and provides detailed annual data
on possible exposures, broken down by class and type of pesticide.
Most of the funded states have additional surveillance programs that cover pesticide
poisonings, though some states’ poisoning reporting requirements are not pesticide specific
or mandate only occupational injury reporting. These surveillance systems include states
who participate in the NIOSH SENSOR program which maintain a consistent data
structure and case definition. 7 Other funded states not using NIOSH data standards may be
able to work towards implementation of those standards through their existing poisoning
surveillance data systems. Pennsylvania is the only funded state with no poisoning
reporting requirements. Some state agriculture departments may also maintain agricultural
worker pesticide poising case data.
5
EPA Office of Civil Enforcement as viewed at http://www.epa.gov/compliance/about/offices/oce.html
USDA – CAPS as viewed at
http://www.aphis.usda.gov/plant_health/plant_pest_info/pest_detection/pestlist.shtml
7
Calvert GM, Barnett M, Blondell JM, Mehler LN, Sanderson WT. 2001 Surveillance of pesticide-related
illness and injury in humans. Chapter in Handbook of Pesticide Toxicology, Second Edition, edited by R.
Kreiger, Academic Press, San Diego. p.603-641
6
90
Additional sources for reports of pesticide incidences include EPA’s Incident Data
System (IDS) and National Pesticide Information Center (NPIC). NPIC could be a source
of data on public and physician reports that are not captured elsewhere. However, IDS
would need to be used exclusively instead of NPDS and SENSOR to avoid case duplication
as IDS incorporates data from these other systems.
USDA Pesticide Data Program (PDP) provides food residue sampling data collected
in 6 funded states and drinking water samples in four additional funded states. The data is
broken down by commodity type and over samples items such as apple juice which is more
frequently consumed by children. The FDA Pesticide Residue Monitoring Program also
analyzes food for pesticide residues but collects a much smaller number of samples.
However, the data is collected in many more states and would fill in some of the gaps in the
USDA data. 8 Both data system have sample results going back more than ten years.
NHANES data can be used to present state population means of biomonitoring data
to present actual pesticide exposure body burdens levels. NHANES data provides
measurements of metabolites of organohlorines, organophosphates, pyrethroids,
carbamates, and herbicides. Additional data on metabolites of fungicides and urea-based
herbicides have recently been added to the 2003-2004 NHANES analysis. 9 Demographic
stratification of NHANES data could allow specific focus on the exposures to more
sensitive populations such as mothers and children.
Health Outcomes:
The PCC NPDS system data gathers health outcome information. From a review of
1993-1996 PCC data, an outcome was recorded in 49% of all possible unintentional
poisoning cases with 38% of all cases with no or minor effects requiring no follow up.
Therefore, most cases with significant acute health effect are followed up. 10 Health effects
are categorized as no effect, minor, moderate, or severe/death.
The state poisoning surveillance systems mentioned above, especially in those state
that use NIOSH data standards, also provide a rich source for detailed reporting of health
outcomes. This data could also be enhanced by additional use of hospital discharge data,
8
FDA, Pesticide Program Residue Monitoring 1993-2006 as viewed at
http://vm.cfsan.fda.gov/~dms/pesrpts.html
9
Chemicals Measured in Selected Participants for NHANES 2003-2004 as viewed at
www.cdc.gov/exposurereport/pdf/NHANES03-04List_03_2007.pdf
10
Calvert GM, Barnett M, Blondell JM, Mehler LN, Sanderson WT. 2001 Surveillance of pesticide-related
illness and injury in humans. Chapter in Handbook of Pesticide Toxicology, Second Edition, edited by R.
Kreiger, Academic Press, San Diego. p. 603-641.
91
workers compensation claims, and vital statistics for unintentional pesticide poisoning
deaths. This process may enhance the poisoning case surveillance already in place in these
states, casting a wider net where many cases are missed or only occupational injury data is
collected.
Chronic health outcomes could also be investigated. The EPHT national networks
existing data capacity with access to a variety of health outcome data could provide an
opportunity to explore linkages with pesticide exposures to such areas as neurodegenerative
disease, birth outcomes, cancer, and autoimmune conditions.
Interventions and Best Practices:
It will also be important to track interventions that are reducing the risk posed by the
use of pesticides. In coordination with state environmental agencies or other appropriate
bodies, states could track the number/percentage of counties or municipal governments
implementing integrated pest management (IPM), other pesticide use reduction programs,
or public notification systems.
States could track the percentage of schools adopting IPM using data from National
Working Group for School IPM organized through the IPM Institute. 11 The IPM Institute
could also be a resource for tracking levels of adoption of certified IPM programs or
businesses in states through the “Green Shield” and “IPM Star” programs. 12 The NPMA
also offers QualityPro certification for applicators who maintain high professional
standards. 13
The agricultural marketing company, Doane Marketing research, Inc., used by the EPA
to estimate market trends, could provide data on the increase in acreage treated with
reduced risk pesticide or given over to organic production. The USDA ERS also tracks
amounts of pasture and cropland acreage in organic production. This data is available by
state, year and commodity from 2000 to 2005. 14
Leadership Ideas:
New York City’s EPHT program has volunteered to take a leadership role in the
Pesticide Content Work Group. NYC has been using pest and pesticide data as a part of its
tracking program from the beginning. It will work to gain consensus from a group of
11
IPM Institute, Schools IPM 2015: Reducing Pest Problems and Pesticide Hazards in Our Nation’s Schools
as viewed at http://www.ipminstitute.org/school_ipm_2015/school_ipm_2015_Updates.htm
12
IPM Institute of North America as viewed at http://www.ipminstitute.org/
13
NPMA – What is QualityPro? as viewed at http://npmapestworld.org/QualityPro/WhatIs.asp
14
USDA, ERS – Organic Production as viewed at http://www.ers.usda.gov/Data/Organic/#statedata
92
funded and non-funded states who have a strong stake in this topic. CDC will also
actively participate in leadership. Non-funded states and cities will be looked to for
evaluation of what is working for them and for stakeholder involvement.
NYC intends to facilitate an efficient distributed workgroup process whereby
participants and stakeholders divide up data inventory, quality review, indicator proposal
activities, and unite in Webex and conference calls to discuss progress. The pesticide team
would meet in-person at each of the biannual EPHT national meetings.
Time Line:
Based on a six to nine month process of consensus building, NYC and CDC
proposes to convene a series of 3-6 biweekly meetings to finalize a list of preliminary
indicators, along with a detailed plan for calculating the measures. NYC and CDC will
share these data with the Content Workgroup and CDC, and seek preliminary approval to
proceed with indicator testing and calculation. NYC proposes the following indicators that
address the following topics: a) pesticide product sales and use; b) pesticide regulatory
actions (these can be thought of as a subset of pesticide related interventions); c) pesticide
need – these may include pest population trends in agriculture, structural and other sectors;
d) pesticide exposures; 3) pesticide-related acute health outcomes; 4) pesticide-suspected
chronic health outcomes (these may involve recommended linkages to already established
EPHT indicators and measures, or novel ones); and 5) pest or pesticide related
interventions (an example from NYC was the adoption of a local regulation to limit the use
of pesticides).
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Section overview: Tracking updates
Given the limited time available for advisory panel meetings, updates on some items will
be provided to the panel as information items only. This information is intended to keep
panel members apprised of progress being made in program areas that are not a featured
part of the current meeting’s agenda and/or to alert panel members to items that will need
to be discussed in greater depth at a future meeting.
Included in this section of the meeting packet are status updates on the following:

Minnesota EPHT web-based information system
ACTION NEEDED: At this time no formal action is needed by the advisory panel. Panel
members are invited to ask questions or provide input on any of this topic during the
designated time on the meeting agenda.
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Status update on MN EPHT Web-Based Information System (IBIS)
Background
As reported at the September 15, 2009, EHTB advisory panel meeting, MDH is
developing a web-based information system to display MN EPHT data and measures on
the department’s web site by fall 2010. This system will allow the public to select
standard views and reports, as well as conduct customized queries of health and
environment data. The successful deployment of this system is a primary goal of the MN
EPHT Program – i.e., to make Minnesota health and environment data accessible to the
public in one place via the Internet.
As a part of this effort, MDH has selected an open source system called IBIS (Indicator
Based Information System) for displaying MN EPHT data. Five states in the Tracking
Network currently use (or are planning to use) IBIS, including Utah, New Mexico,
Missouri, New Jersey, and Minnesota. In addition to allowing customized data queries,
this system allows for presentation of state-specific data and measures that supplement
information provided by the National Environmental Public Health Tracking Network.
For examples of current state-based IBIS systems, see:
 Utah Department of Health
http://ibis.health.utah.gov/
 New Mexico Department of Health
http://ibis.health.state.nm.us/home/Welcome.html
Initially, Minnesota’s system will include aggregate data on hospitalizations, carbon
monoxide poisonings, and drinking water quality (community water systems). By 2011
MDH plans to expand this system to include additional data and measures (e.g., air
quality, blood lead, birth defects) and analysis features (e.g., GIS). The MN EPHT
system will continue to be developed and enhanced as new EPHT data and measures are
developed in Minnesota.
Progress to date
Currently, MDH is working with IT experts and the other tracking states, including Utah
and New Mexico, to customize IBIS for use in Minnesota. MDH has hired an IBIS
Project Manager (Michelle DeMist) and a programmer (Tim McGuire) to work on this
project. In addition, MDH has developed several elements to ensure successful
management and execution of this project, including a charter, organizational chart, and
plans for establishing an IBIS Steering Committee.
Future plans
In fall 2010 MDH will provide training to state and local agencies and other interested
parties who are potential users of the MN EPHT system. In addition, MDH plans to
evaluate the web site and training so that the end products are useful and user friendly.
For questions or additional information about the MN EPHT system, please contact the
MN EPHT Program Manager, Chuck Stroebel at [email protected] or 651/2015662.
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Section overview: Other information
These documents are included in this meeting packet as items that may be of interest to
panel members:

Minnesota Environmental Public Health Tracking and Biomonitoring presentations,
posters and publications

Local, national and global biomonitoring and tracking news
In previous meeting packets, a number of items were included as reference materials. To
limit the amount of paper used and to contain costs, unless changes are made to these
documents, they will no longer be included in the meeting packet. These materials are
available online at www.health.state.mn.us/tracking/.
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Minnesota Environmental Public Health Tracking & Biomonitoring
Presentations, posters and publications
September-November, 2009
SEPTEMBER
Finding Linkages Between Human Health and Chemicals in our Air and Water, Part 1
 Environmental Public Health Tracking and Biomonitoring: Bridging the Gap, Minnesota
Biomonitoring Pilot Projects
 Presented at the Minnesota Pollution Control Agency
 Presenters: Jean Johnson, PhD and Adrienne Kari, MPH
 Date: 9/21/2009
OCTOBER
Finding Linkages Between Human Health and Chemicals in our Air and Water, Part 2
 Asthma surveillance and linking air pollution and asthma data in Minnesota
 Presented at the Minnesota Pollution Control Agency
 Presenters: Wendy Brunner, MS and Paula Lindgren, MS
 Date: 10/12/09
Biomonitoring for Perfluorinated Chemicals in Minnesota: A Pilot Project
 Presented by phone to the Federal-State Toxicology and Risk Analysis Committee (FSTRAC) for
the Fall FSTRAC 2009 Meeting “Safe and Clean Water”
 Presenters: Jean Johnson, PhD and Adrienne Kari, MPH
 Date: 10/22/09
NOVEMBER
Approaches to Interpreting Biomonitoring Data from Population-level Studies
 Symposium convened at the International Society of Exposure Science (ISES) Conference
 Symposium organizers: Jean Johnson, PhD and Doug Haines, PhD (Health Canada, Ottawa,
Ontario)
 Date: 11/5/09
Biomonitoring for Perfluorinated Chemicals
 Presented at the Society of Environmental Toxicology and Chemistry (SETAC) Annual Meeting
 Presenters: Adrienne Kari, MPH and Carin Huset, PhD
 Date: 11/22/09
Method Development for Human Biomonitoring of Fluorochemicals
 Poster presented at the Society of Environmental Toxicology and Chemistry (SETAC) Annual
Meeting
 Presenter: Carin Huset, PhD; Authors: Carin Huset, PhD, Adrienne Kari, MPH, Martin Bevan,
PhD, and Andrew Mittendorff, BS
 Dates: 11/22/09
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Local, national and global biomonitoring and tracking news
BIOMONITORING
The Association of Public Health Laboratories recently issued two publications on
biomonitoring. Both articles feature quotes from MDH laboratory staff. They can be
found online.
Is the Environment Making You Sick? Biomonitoring is the Missing Piece
Lab Matters, Fall 2009
http://www.aphl.org/AboutAPHL/publications/Pages/LMFeatFall2009.aspx
Moving Forward: Biomonitoring stories from the states
October 2009
http://www.aphl.org/aphlprograms/eh/chemicalpeople/Documents/Biomonitoring
Report2009.pdf
The Association of Public Health Laboratories is also developing a national
biomonitoring plan. Joanne Bartkus (director of the MDH laboratory division) and Jean
Johnson attended a meeting in Atlanta to discuss and provide input on APHL’s draft plan.
Information about the national biomonitoring plan can be found online at
http://www.aphl.org/aphlprograms/eh/Pages/nationalbioplan.aspx.
TRACKING
Information about MN EPHT was featured in MDH’s Waterline publication, a quarterly
newsletter for water operators, city officials, and others interested in news related to
public water systems in Minnesota. The article can be found online at
http://www.health.state.mn.us/divs/eh/water/com/waterline/waterlinewinter20092010.pdf
.
PFCs
On November 14, the Star Tribune published an article (“New fears of 3M chemicals)
about studies showing a possible link between PFC exposure and high blood cholesterol.
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