Minnesota Department of Health
Environmental Health Tracking and Biomonitoring
Advisory Panel Meeting
June 12, 2012
1:00 p.m. – 4:00 p.m.
ENVIRONMENTALHEALTHTRACKINGANDBIOMONITORING
ADVISORYPANEL
MEETINGAGENDA
June12,2012
Time Agenda Item 1:00 Welcome and introductions 1:05 Health risk communication in the age of social media: a community case study Presenters Bruce Alexander Chair Description/anticipated outcome Members and audience members are invited to introduce themselves. John Soler, MDH MCSS Doug Schultz, MDH Communications Chuck Stroebel Discussion item. Presenters will review risk communication for a recent community issue and how social media and online EPHT data were used. Questions to the Panel: 

How might MDH better use social media for risk communication? What would be most effective? Can MN Public Health Data Access in its current form help MDH respond effectively to community‐level environmental concerns like this case? How can we make the portal more useful for communities? 1:45 1:50 Tracking updates  New cancer data  Facilitated Discussions  National workshop Water Quality Update Chuck Stroebel Jean Johnson Paula Lindgren 2:05 2:15 Break Refreshments Information update. Panel members are invited to ask questions. Information update. Paula Lindgren will discuss her work to improve the display of current measures for tracking drinking water hazards in MN. Panel members are invited to comment and ask questions. Adverse Child Health Outcomes & Agrichemical Water Contamination Rachael Jones, University of Illinois/Chicago Discussion item. UIC investigators will present an update of research to develop methods for assessing population exposure to agrichemicals in drinking water in the Midwest and linking to child health i outcomes. Question to the panel:  How can MN EPHT work to improve the available measures for characterizing population exposure to drinking water contaminants in order to link the exposures to health data? 2:50 Tracking air quality (PM) impacts Naomi Shinoda 3:35 Mercury biomonitoring Jean Johnson follow‐up project 3:45 3:50 Biomonitoring updates  PFCs  Great Lakes Initiative  National initiatives Legislative update Jean Johnson 3:55 New business Bruce Alexander 4:00 Motion to adjourn Bruce Alexander Discussion item. Staff will present recent results of a study to develop methods for tracking the impacts of particulate matter on respiratory disease in MN. Panel members are invited to comment and ask questions. DRAFT Questions to the panel:  How should MN EPHT display information about air quality health impacts that would be most informative for the public and policy makers?  Is population attributable fraction (PAF) a useful tracking measure if expanded to include more years of data? Information item. Jean will update the panel on progress with UM TIDES study collaboration to measure newborn mercury exposure in paired cord and heel stick specimens. Members are invited to ask questions and provide input. Information item. Members are invited to ask questions. Information item. Members are invited to comment or ask questions. Request for new topics for future discussion. Request for a motion to adjourn 2 TableofContents
EHTB Advisory Panel Meeting Agenda Table of Contents Section Overview: Health Risk Communication and Social Media…………………………….………5 Section Overview: Tracking Updates……………………………………………………………………….……....9 Section Overview: Water Quality Data Update………………………………………….…………………..15 Section Overview: Adverse Child Health Outcomes & Agrichemical Water Contamination…………………………………………………………………..………........19 Section Overview: Tracking Air Quality Health Impacts……………………………………..….…..……25 Section Overview: Mercury Biomonitoring Follow up Projects……………………………….….……33 Section Overview: Biomonitoring Updates……………………………………………………..………….……37 Section Overview: Legislative Report……………………………………………………………….………...……43 Section Overview: Other Information…………………………………………………..……….…….……………45 3 This page intentionally left blank. 4 SectionOverview:HealthRiskCommunicationandSocialMedia
This section examines MDH’s response to a community concern and the role that social media played in fueling the concern. Speakers review the event and discuss the role of risk communication in responding to a media firestorm that was fanned by a Facebook page. ACTION NEEDED: No action need be taken at this time. Panel members are asked to discuss the following questions: Questions to the Panel: 

How might MDH better use social media for risk communication? What would be most effective? Can MN Public Health Data Access in its current form help MDH respond effectively to community‐level environmental concerns like this case? How can we make the portal more useful for communities? 5 This page intentionally left blank. 6 HealthRiskCommunicationintheAgeofSocialMedia:ACommunityCaseStudy
A Data Request Meets Facebook This presentation will be a narrative of a data request at the zip code level for the city of Fridley. What makes this narrative somewhat different from other requests is that the results were posted on a Facebook page entitled "Fridley Cancer Cluster." This Facebook page contained information about: 1) cancer rates in Fridley; 2) the superfund sites in Fridley; and 3) the city water supply, which has had a history of low‐level contamination with TCE. The community group contacted Erin Brockovich, who expressed interest in the situation. Extensive media coverage followed. Containing a Social Media Firestorm The Fridley cancer “cluster” media firestorm may be MDH’s first instance of a risk communication conflagration ignited and fueled largely by social media. In his presentation, Doug Schultz will briefly review some basic principles of risk communication, discuss how they apply in communicating about cancer risks, look at how social media can affect good risk communication, and explore how communicators can prevent, dampen, or put out such flare‐ups in future, including whether social media can help—or only hinder—
MDH in doing so. Firestorm Feeds Flurry on MNPH Data Access portal MN EPHT routinely uses Google Analytics to evaluate web activity for Minnesota Public Health Data Access (MNPH Data Access). In March‐April 2012, these data show a series of spikes (increases above baseline) in the number of page views for the entry cancer data page (https://apps.health.state.mn.us/mndata/cancer). This time period corresponds with MDH’s news announcement about the availability of the new interactive cancer maps and media/news articles about the Fridley cancer excess. In April, there were approximately 1100 unique page views of the entry cancer data page alone, with a peak of over 500 views in one day. A unique page view represents the number of sessions during which a page was viewed one or more times by the same viewer. The top referring web sites to this page in April were: 1. duluthnewstribune.com (Duluth News Tribune) 2. peggysue.areavoices.com (Healthy Tidbits by Peggy Anderson) 3. startribune.com (Star Tribune) 4. pca.state.mn.us (MN Pollution Control Agency) 5. mncanceralliance.org (MN Cancer Alliance) 6. mncompass.org (MN Compass) 7. lpha‐mn.org (Local Public Health Association of MN) 8. childbirthcollective.ning.com (Childbirth Collective Social Network) 9. apb.directionsmag.com (Directions Magazine) 10. facebook.com (Facebook) 7 Overall, the web analytics data suggest that EPHT and other MDH efforts to make cancer information accessible helped inform MN communities. These data also illustrate the emerging importance of social media (e.g., Facebook) in communicating with the public, and the relatively high level of interest in MN cancer incidence data at the local level. Questions to the Panel: 1. How might MDH better use social media for risk communication? What would be most effective? 2. Can MN Public Health Data Access in its current form help MDH respond effectively to community‐level environmental concerns like this case? How can we make the portal more useful for communities? 8 SectionOverview:TrackingUpdates
These tracking updates are provided to let panel members know about progress in program areas that are not featured in the current meeting. This section contains status updates on the following: 


New cancer data Facilitated Discussions National Environmental Public Health Tracking workshop ACTION NEEDED: No action need be taken at this time. Panel members are invited to ask questions and offer comments on the project updates. 9 This page intentionally left blank. 10 TrackingUpdates
New Cancer NCDMs on MNPH Data Access In collaboration with the national Content Work Group (CWG) Cancer Team, CDC has chosen eight new Nationally Consistent Data & Measures (NCDMs) to track cancer incidence. These new cancer types will be added to MNPH Data Access by June 2012, including additions to the static pages (charts and messaging) and the Cancer Data Query. You can view the new static pages (charts, messaging) or query the new cancer types at MNPH Data Access: Cancer (https://apps.health.state.mn.us/mndata/cancer). The new cancer NCDMs include: 1. Esophageal cancer 2. Kidney cancer 3. Laryngeal cancer 4. Liver (and intrahepatic bile duct) cancer 5. Melanoma 6. Mesothelioma (tracked by MN EPHT since 2011) 7. Oral & pharyngeal cancer 8. Pancreatic cancer Mesothelioma, one of the new cancer NCDMs, is known to be caused by exposure to airborne asbestos and has been tracked independently by MN EPHT since 2011 because of its prevalence in certain regions of the state. Four of these NCDMs are tobacco‐related cancers, including esophageal, laryngeal, oral & pharyngeal, and pancreatic cancers. These cancers were strongly recommended as NCDMs by the CWG Cancer Team due to their strong link with tobacco use. Melanoma has a strong association with ultraviolet (UV) light exposure, and incidence rates for both males and females have been increasing in Minnesota. Liver cancer is associated with chronic hepatitis B or C infection, long‐term exposure to high levels of arsenic in drinking water, and some occupational exposures. Kidney cancer is also associated with tobacco use, specifically cigarette smoking, and some occupational exposures. Cancer incidence data, provided by the Minnesota Cancer Surveillance System (MCSS) at MDH, include the number of new cancer cases diagnosed and the age‐adjusted incidence 11 rate for each cancer type at the state level (per year) and at the county level (in 5‐year rollups). Cancer incidence data are currently available through 2008 on MNPH Data Access. Submitted by Blair Sevcik Tracking Program’s Facilitated Discussion with CDC and NACCHO In May 2012, the Centers for Disease Control and Prevention, National Association of City and County Health Officials (NACCHO), and MN EPHT sponsored a 1‐day facilitated discussion with approximately 25 participants representing MN local public health departments, non‐profit environmental organizations, and the legislative (house) research office. The goals of this discussion were to: 1) share information about the National and State Tracking Network, and 2) gather recommendations and advice about data needs at the local community level to inform MN EPHT activities in 2012‐13. This meeting included an interactive demonstration of MN Public Health Data Access (data portal) and examples of how tracking data being used in Minnesota (“Tracking in Action”). Highlights from the discussion included: 

Lack of granularity on the data portal: although participants generally thought the portal was a useful tool, they would like to see data at a finer spatial level (city, neighborhood, census tract), where possible. Additional data sets of interest: several participants identified data topics of interest to inform local assessment and planning, including obesity, diabetes, radon, mental health, and the built environment. Participants also expressed interest in additional data about health disparities. 
Need to engage additional audiences: as part of healthcare reform, healthcare organizations are required to conduct health assessments and might find that data on the portal would be useful. Participants also suggested that academic faculty and students might find the portal data useful for some applications. MN EPHT is using information from this discussion to inform the planning for grant Year 4 (August 1, 2012 to July 31, 2013). In addition, NACCHO is preparing a summary of the discussion and copies of presentation slides that will be available on their website in early summer. For questions or more information about this discussion, please contact Chuck Stroebel, MN EPHT Program Manager, 651‐201‐5662, [email protected]. 12 Updates from National Tracking Program Workshop, Denver, CO, May 1‐3, 2012 Tracking Impact: Advances in Data Use and Linkages The theme of the recent national Environmental Public Health Tracking workshop in Denver, CO was “Tracking Impact”. It represents the original vision of the PEW Environmental Health Commission for the Tracking program: that collecting and integrating data about environmental hazards and health outcomes would enable states and other data users to directly measure the impacts of public health actions in mitigating hazards and preventing disease. At one session, an interactive discussion explored current state grantee data‐use projects. Tracking program grantees were asked to list projects they are currently working on that use or link multiple health and environmental datasets. The 75 projects listed by the states covered a broad range of topics. Data on environmental hazards included particulate matter (PM), ozone, lead, benzene, arsenic, pollen, bedbugs, mercury, and others. Health outcomes included asthma, cardiovascular diseases, neurological disorders, birth defects, cancer, renal disease and others. In addition to the current EPHT data sources, states are exploring other datasets such as drivers’ license data, food safety, fish tissue mercury, community health surveys, USGS water quality data, traffic, pesticide exposures, and syndromic surveillance, which monitors for clusters of symptoms in near real time. After reviewing the wide range of projects, grantees discussed ways to improve collaboration among states working on similar projects. Some ideas included compiling information on a shared website, exchanging protocols and project reports, and special webinars or workshops to foster collaborations. In Minnesota, we are currently engaged in 2 such “linkage” projects. One project, funded by an EPA STAR grant, has been developing methods for linking ambient particulate matter monitoring data and traffic data with mortality and hospitalizations for respiratory and heart disease. The other project is being led by investigators at the University of Illinois‐
Chicago, an academic partner of the Tracking program, and is developing methods for linking data on agrichemicals in drinking water with child health outcomes across 8 Midwestern states. Both projects will be discussed at this June 2012 Advisory Panel meeting (see agenda). Submitted by Jean Johnson. Risk Factors, Demographics, and Environmental Justice The display of risk factor and demographic data on portals is a cross‐cutting issue that came up in several workshop sessions throughout the week. Because MN EPHT is exploring ways to add and link risk factor and demographic data using the Minnesota Public Health Data Access portal, the discussion was timely. 13 Currently, no National Tracking Network workgroup provides guidance and recommendations about which risk factor or demographic data to include, and how to relate them to existing NCDMs. CDC and several grantee states demonstrated examples of risk factor and demographic data on public portals, including: education, income, poverty, health insurance coverage, male/female, age group breakdown, ethnicity, smoking, housing quality, obesity and physical activity. Workshop discussions around these data focused on messaging, on which data should be linked (comparisons of all available data to look for new patterns versus comparisons of data on known/suspected epidemiologic associations for surveillance), and on barriers to linking data with existing NCDMs, such as differing spatial/temporal resolution. Several parts of the Tracking Network will be involved in adding and linking (“relating”) risk factor and demographic data. The Technical Aspects of Related Data Integration Subgroup (TARDIS) will focus on technical aspects and methods for management of displaying related data, CWG (Content Workgroup) teams will recommend content‐related data sets to be displayed, and the Geospatial workgroup would focus on the spatial methodologies for the visualization of demographic data. An exploratory group met at the workshop to discuss health disparities and Environmental Justice (EJ) concepts (minority and low‐income populations and Indian Tribes bear disproportionate burdens of exposure to environmental hazards, and environmental disparities contribute to many health disparities). EPHT is explicitly mentioned in the 2012 Health and Human Services EJ Strategy (strategic element #3 “Research and Data Collection”) as a way to expand information on the environmental health of minority and low‐income populations and Indian Tribes, and provide access to data in order to improve the understanding of the relationship between exposure to environmental hazards and health effects. The EJ workshop session discussed how CDC and several state portals already include information on disparity data, such as race, ethnicity, and income. The addition of demographic and risk factor data on CDC and grantee portals could also be used for EJ purposes. Workshop participants made a decision to look into a new taskforce to focus on EJ and disparity issues. Submitted by Jeannette Sample. 14 Overview:WaterQualityDataUpdate
Biostatistician Paula Lindgren will describe the current and future status of drinking water quality data on the MN Public Health Data Access portal (MNPH Data Access). ACTION NEEDED: Panel members are invited to ask questions and to provide advice and suggestions about the display and presentation of water quality data on the MNPH Data Access portal. 15 This page intentionally left blank. 16 MinnesotaWaterQualityDataUpdate
Paula Lindgren will describe the current and future status of drinking water quality data on the MN Public Health Data Access portal (MNPH Data Access). 1. Current status  Community Water Systems (CWS) in MN  Four current analytes on MN PHD Access o Arsenic o Nitrate o Disinfection By‐Products  Trihalomethanes (THM)  Haloacetic acid (HAA)  Data structure (NCDMs and sample level data) o Tables and Charts proposal for static pages  Examples from other state portals  Six new analytes required for CDC portal, optional for state portals o Atrazine o Radium o Uranium o DEHP (Bis(2‐ethylhexyl)phthalate) o TCE (Trichloroethylene o PCE (Perchloroethylene) 2. New analytes to be added to CDC tracking portal (These are optional for states) 


Atrazine‐ Atrazine is used to stop pre‐ and post‐emergence broadleaf and grassy weeds in major crops. The compound is both effective and inexpensive, and thus is well‐suited to growing crops with very narrow profit margins, such as maize. Atrazine is the most widely used herbicide in conservation tillage systems, which are designed to prevent soil erosion. Radium‐ In nature, radium is found in uranium ores in trace amounts as small as a seventh of a gram per ton of uraninite. Radium is not necessary for living organisms and, because of its radioactivity and chemical reactivity, can cause adverse health effects when it is incorporated into biochemical processes. Uranium‐ People can be exposed to uranium (or its radioactive daughters, such as radon) by inhaling dust in air or by ingesting contaminated water and food. The amount of uranium in air is typically minuscule. Yet people who work in factories that process phosphate fertilizers, live near government facilities that made or tested nuclear weapons, live or work near a modern battlefield where depleted 17 uranium weapons were used, or live or work near a coal‐fired power plant, facilities that mine or process uranium ore or enrich uranium for reactor fuel may be exposed to uranium. Houses or structures that are over uranium deposits (either natural or man‐made slag deposits) may have greater exposure to radon gas. 
DEHP‐Bis(2‐ethylhexyl)phthalate‐ DEHP is widely used as a low‐cost plasticizer in manufacturing articles made of PVC. Plastics may contain 1% to 40% of DEHP. It is also used as a hydraulic fluid, as a dielectric fluid in capacitors, and as a solvent in glowsticks. 
TCE‐ Perhaps the greatest use of trichloroethylene has been as a degreaser for metal parts. The demand for TCE as a degreaser began to decline in the 1950s in favor of the less toxic 1,1,1‐trichloroethane, which has been phased out in most of the world under the terms of the Montreal Protocol. As a result, trichloroethylene has experienced some resurgence in use as a degreaser. TCE has also been used in the United States to clean kerosene‐fueled rocket engines to remove hydrocarbon deposits and vapors in the engine and to flush the engine's fuel system before and after each test firing. TCE is also used in the manufacture of a range of fluorocarbon refrigerants, such as 1,1,1,2‐Tetrafluoroethane, commonly known as HFC 134a.  PCE‐ Perchloroethylene is a manufactured chemical primarily used for dry cleaning fabrics and degreasing metals. It is also used to make other chemicals, such as chlorofluorocarbons and rubber coatings; as an insulating fluid and cooling gas in electrical transformers; and as a scouring, sizing, and de‐sizing agent in textiles. It is an ingredient in aerosol products, solvent soaps, printing inks, adhesives, sealants, paint removers, paper coatings, leather treatments, automotive cleaners, polishes, lubricants, and silicones. It is also an ingredient in some consumer products, including typewriter correction fluid, adhesives, spot removers, wood cleaners, and shoe polish. Background information Background information on water quality was obtained from the following sources: 1. MNPH Data Access: a. https://apps.health.state.mn.us/mndata/drinkingwater 2. 2008 MN EPHT Drinking water report: a. http://www.health.state.mn.us/divs/hpcd/tracking/pubs/dwreport.pdf 3. 2011 MDH Drinking Water Annual Report: a. http://www.health.state.mn.us/divs/eh/water/com/dwar/report2011.pdf 18 SectionOverview:AdverseChildHealthOutcomesandAgrichemical
WaterContaminationintheMidwest:ALinkageStudy
In 2010, CDC’s Environmental Public Health Tracking (EPHT) Program funded an academic center and study at the University of Illinois at Chicago (UIC). The primary objectives of the UIC study are to: 1) Enhance the methodology of drinking water contaminant and health data surveillance and linkage; 2) Explore potential associations between birth and childhood health outcomes and exposure to drinking water contaminants, beginning with atrazine and nitrate; and 3) Develop partnerships with the Midwestern states of Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, and Wisconsin. ACTION NEEDED: No action is needed, but the Panel is asked to consider and discuss the following question. Question to the panel:  How can MN EPHT work to improve the available measures for characterizing population exposure to drinking water contaminants in order to link these exposures to health data? 19 This page intentionally left blank. 20 AdverseChildhoodHealthOutcomesandAgrichemicalWaterContamination
intheMidwest:ALinkageStudy
Submitted by Rachael Jones, UIC Study Overview The Environmental Public Health Tracking (EPHT) Program of the Centers for Disease Control and Prevention (CDC) began funding an academic center at the University of Illinois at Chicago (UIC) in September 2010. The primary objectives of the UIC study are to: 1) enhance the methodology of drinking water contaminant and health data surveillance and linkage; 2) explore potential associations between birth and childhood health outcomes and exposure to drinking water contaminants, beginning with atrazine and nitrate; and 3) develop partnerships with the Midwestern states of Illinois, Indiana, Iowa, Michigan, Minnesota, Missouri, Ohio, and Wisconsin. Drinking Water Data Community water systems (CWSs) deliver drinking water to the majority of the population in the Midwest. The quality of water in CWSs is regulated by the Environmental Protection Agency, which specifies the maximum allowable contaminant concentrations and monitoring schedule. These data may be appropriate for surveillance and linkage in the context of EPHT because they are relevant to human exposures, and can indicate changes in potential hazards over time. UIC obtained water quality data for atrazine and nitrogen compounds from participating states, and found that, over the years 2000 to 2008, monitoring was conducted as frequently as required by law (e.g., atrazine is measured quarterly or once every three years and nitrogen compounds are measured quarterly or annually), and contaminant concentrations were indicative of good water quality. In the next year UIC will expand the scope to consider drinking water quality in private domestic wells. Health Outcome Data To date, the UIC study has focused on health outcomes (e.g., low birth weight and pre‐term birth) and statistics (e.g., sex ratio) derived from birth certificate data. These outcomes are defined as annual or monthly rates in each county. These data were obtained separately from the CDC and states, including Minnesota. Linkage Linkage of environmental quality and health outcome data requires that both measures be referenced to a common spatial and temporal scale. Drinking water quality is measured at several time‐scales in a CWS (e.g., quarterly, etc.). Health outcome data is measured monthly or annually, in a county. The mismatch between these data presents a challenge for linkage. 21 Addressing Temporal Scale Adverse birth outcomes resulting from environmental contaminants are often associated with exposures to contaminants occurring during particular time periods of fetal development. Given monthly rates of health outcomes, characterization of potential exposures during development requires estimates of drinking water quality for each calendar month. The UIC researchers have proposed to estimate drinking water quality in each month in each CWS using the statistical approach, multiple imputation. In multiple imputation, a statistical model uses the observed data and other variables relevant to water quality to predict contaminant concentrations for every month in which no measurement was collected. The imputation is repeated 5‐10 times. The health outcome data is linked to each of the 5‐10 imputed water quality data, and the epidemiological model is fitted. The coefficients of the epidemiological models fitted to each of the 5‐10 imputed data sets are then combined to yield the final epidemiological model coefficient estimates. Multiple imputation has not been used for drinking water quality data to date. As a result, we have been testing the method using data from the Atrazine Monitoring Program (AMP) of the EPA. In the AMP data, atrazine is measured in participating CWSs every two weeks. The frequency of measurement means that data can be deleted to create artificial patterns of missing data, and the results from multiple imputation can be compared to those obtained using the true values. Initial results indicate that this method may be appropriate for estimating monthly concentrations from quarterly measurements, and quarterly concentrations from annual measurements. Addressing Spatial Scale A county contains, typically, 6‐15 CWSs. Therefore, drinking water quality data from multiple CWSs must be combined to estimate the potential hazard at the county level for linkage with the health outcome data. Our approach has been to calculate a population‐
weighted average contaminant concentration for each county in the month, quarter, or year of interest. The population‐weighted average contaminant concentration is then linked to the health outcome data. A limitation to this approach, and to the linkage of individual‐level health status to drinking water quality, is the lack of information about CWS service areas in many states, including Minnesota. A CWS, for example, may serve a portion of a city, or multiple cities, and may serve more than one county. Databases of drinking water quality only indicate the address of the CWS office, which is not necessarily at the treatment and distribution plant. Exploring Associations Associations between agrichemicals and birth outcomes, low birth weight, and prematurity, measured as annual county‐level rates, have been explored using Poisson regression models. Environmental quality was described by the annual population‐weighted mean atrazine and nitrate concentrations in each county, and percentage of county land used for agriculture. Adjustments were made for potential demographic confounders. When a 22 random effect was added to account for correlations within counties, the association between atrazine and prematurity disappeared, as did the protective effect of nitrate for low birth weight and prematurity. In the next year, we will incorporate the spatial structure of the data in these epidemiological models. 23 This page intentionally left blank.
24 SectionOverview:TrackingAirQualityHealthImpacts
In this section, staff will describe work that has been done on an EPA STAR grant‐funded project to develop epidemiological methods for tracking the public health impacts of changes in particulate matter. This project used local air monitoring and health data to generate two kinds of measures that describe the air pollution exposure/health association: odds ratios and population‐attributable fractions. The methods were applied to two study locations, the Minneapolis‐St. Paul metropolitan area and Olmsted County, and results were compared over three time periods. ACTION NEEDED: Panel members are invited to ask questions and provide suggestions about how MN EPHT should use the project results to inform the public about the health impacts of air quality. Questions to the panel:  If MN EPHT were to continue with this work and build on it to develop an air quality health impact indicator, how should it proceed?  Is the population‐attributable fraction (PAF) a useful tracking measure that the public would understand? 25 This page intentionally left blank. 26 TrackingAirQualityHealthImpacts:Exploringthefeasibilityofusinglocal
airmonitoring&healthdatatotrackpublichealthimpactsofPM2.5inMN
Background A substantial body of scientific literature has associated airborne fine particulate matter (PM2.5) exposures with health outcomes, most significantly with cardiovascular and respiratory disease mortality and morbidity. These studies have suggested that PM2.5 has a “no‐threshold” effect on certain health outcomes, and that air pollution‐related adverse health effects continue to occur even in areas that are in attainment with the National Ambient Air Quality Standards (NAAQS) for PM2.5. The U.S. EPA sets the NAAQS to protect the public from the harmful effects of air pollutants, including PM2.5. The daily PM2.5 standard (currently 35μg/m3) protects against short‐term high exposures to PM2.5, and the annual standard (currently 15μg/m3) protects against long‐term average exposure. EPA is in the process of reevaluating the current PM2.5 standards. These revised standards are anticipated in 2013 and are expected to be more stringent than the current NAAQS, raising the possibility that some areas of the state (e.g. Twin Cities) may be considered out of attainment with the PM2.5 NAAQS. In recent years, several local and regional air pollution reduction strategies have been implemented in Minnesota communities. The largest among these was the Minnesota Emissions Reduction Project (MERP), a voluntary $1 billion energy project that involved the conversion of two coal‐fired power plants to natural gas and the installation of new emissions control equipment on a third plant during 2007‐2009. In another local initiative, a coal‐fired power plant in Rochester, MN was fitted with state‐of‐the‐art scrubbers in 2008 to offset increased emissions expected from planned expansion. In addition, the Clean Air Minnesota coalition, in partnership with the Minnesota Pollution Control Agency (MPCA), industry and other members, began implementing several voluntary diesel vehicle emission reduction pilot projects in 2005 that have since grown into a statewide effort. These projects include installing EPA‐verified retrofit technology to reduce diesel emissions from heavy duty public vehicles and school buses. These local air pollution reduction initiatives coincided with federal regulatory actions that were being implemented over the same time period. On a national level, the 24‐hour daily PM2.5 NAAQS was revised to the current stricter level in 2006. The ultralow sulfur diesel fuel rule was phased in beginning in 2006, and new advanced emission control devices were required for on‐road diesel engines beginning in 2007. The Clean Air Interstate Rule was adopted in 2005, and although it was remanded in 2008, emissions reductions were expected in anticipation of the rule. This rule became final in 2011 as the Cross‐State Air Pollution Rule. The expected outcome of these emissions reductions activities was that air concentrations of fine particles and other pollutants would decline over time. Since 2008, staff have been collaborating with partners at MPCA and Olmsted Medical Center on an EPA STAR grant‐funded project to develop epidemiological methods for 27 tracking the public health impacts of changes in particulate matter concentrations. Case‐
crossover and time series analytical methods were used to assess the short‐term effect of ambient PM2.5 concentrations on the risk of hospitalizations, emergency department (ED) visits, and mortality. Essentially, this indicator/method development project aimed to assess the feasibility of generating local concentration‐response functions by using local sources of data that are readily available to state and health environmental agencies (i.e., local air monitoring data and hospital discharge and mortality records). Methods The following data sources were used in the analyses:  Air quality data o Hourly ambient PM2.5 concentration measurements from MPCA’s PM2.5 continuous monitors (6 monitors in MSP; 1 monitor in Olmsted County). Data were summarized into daily 24‐hour average concentrations.  Health data  Hospitalizations for: total respiratory disease, chronic lower respiratory disease (CLRD), asthma, cardiovascular disease  Asthma‐related ED visits  Deaths for: all‐causes, cardiopulmonary disease Analyses were conducted in two study locations: the 7‐county Minneapolis‐St. Paul metropolitan area and Olmsted County. For each health outcome, case‐crossover and time series models were run using the entire study period length (2003‐2009), as well as using individual sub‐time periods (established a priori) that corresponded to the implementation timeline of the local and regional particulate matter reduction initiatives. These sub‐time periods were: 2003‐2005 (baseline), 2006‐2007 (pre‐implementation), 2008‐2009 (implementation). Several exposure lags were used in the analyses. The exposure lag represents the time between exposure and the health event. Lag 0 represents exposure on the day of the health event, lag 1 represents exposure on the day before the event, lag 2 exposure 2 days before the event, etc. The multi‐day moving average lag represents the cumulative exposure over many days; thus, lag01 would be the average of the exposure on the day of the event as well as the day before the event. Two measures of the exposure‐health association were developed in this project:  Odds ratios (from case‐crossover and time series analyses) o Percent change in hospitalizations/deaths per 10µg/m3 increase in PM2.5  Population attributable fractions (PAFs; only from case‐crossover analyses) o Number or percent of excess hospitalizations/deaths that occurred in the study population that were triggered by observed levels of PM2.5 above a “policy relevant” background concentration (5µg/m3). 28 The PAF quantifies excess hospitalizations (or deaths) triggered by PM2.5 exposure, assuming a causal association, and takes into account the proportion of people exposed to levels of PM2.5 above a defined “policy relevant” background concentration. The population‐attributable fractions of short‐term exposures to PM2.5 were estimated using the distribution of exposure in the cases and the results of the case‐crossover analyses. The following case‐based formula was used: 1
1
numberofcases
where RRi represents the relative risk for each case (i), and where β represents the slope of the case‐crossover model, the case exposure is the ambient PM2.5 concentration on the day of the event (hospitalization, ED visit, or death), and the null exposure is the assumed background PM2.5 concentration. For this analysis, 5µg/m3 was used as the assumed background PM2.5 concentration, based on the most conservative of the EPA estimates of “policy relevant” background concentrations for PM2.5. Because attributable fractions carry the assumption that the exposure causes the outcome, the PAFs were calculated only for those outcomes for which there were statistically significant associations with PM2.5 in the case‐crossover analyses. Results Analyses over entire time period (2003‐2009) In general, results for both single‐day lag and multi‐day moving average lag PM2.5 exposures were similar across the two methods used (case‐crossover and time series), although this varied with the health outcome (See table 1). Respiratory hospitalization outcomes within the MSP metro displayed the strongest associations with PM2.5 in our analyses, with odds ratios ranging from 1.032 to 1.043 per 10µg/m3 increase in the 3‐day moving average (lag02) for PM2.5. The results for respiratory hospitalizations in the MSP metro are generally consistent with the literature. There were no consistent associations between ambient PM2.5 levels and the risk of cardiovascular hospitalizations in the MSP metro. Further, there was little agreement between case‐crossover and time series methods for the cardiovascular hospitalization analyses. This was surprising, given the large sample sizes for these outcomes in the 7‐year time period, and the consistent associations found in the literature. There were no consistent associations between ambient PM2.5 levels and the risk of mortality in the MSP metro. The time series analysis for all‐cause mortality in the MSP metro showed an odds ratio of 1.014 per 10µg/m3 at lag01. The case‐crossover analyses did not yield statistically significant associations. In the scientific literature, multi‐city studies have consistently shown statistically significant increases in mortality risk with PM2.5 concentrations. 29 Analyses by smaller time periods When case‐crossover and time series analyses were conducted by time period, changes in odds ratios over time, in so far as the loss of statistical significance in later time periods, were observed in the MSP metro for respiratory hospital admissions. This was a surprising finding because PM2.5 is thought to have a “no‐threshold” effect on health due to a linear relationship. However, it should be noted that time period‐specific odds ratios for a given health outcome were not statistically different from each other. Further, there was considerably less comparability between case‐crossover and time series results when analyses were conducted by individual time period rather than over the entire 7‐year study period. Due to lack of statistical significance and general lack of agreement across case‐crossover and time series results, it was difficult to detect any changes over time in the association of PM2.5 with either the cardiovascular hospitalization or the all‐cause and cardiopulmonary mortality outcomes. (See table 2) Time period‐specific population‐attributable fractions (PAFs) were calculated using the odds ratios generated from the case‐crossover analyses from the 7‐year study period (rather than the time period‐specific odds ratios). The PAFs showed change over time in the numbers of respiratory hospitalizations that were triggered by PM2.5. Results suggest that the proportions of total respiratory, CLRD, and asthma hospitalizations attributable to short‐term PM2.5 exposures declined by approximately 3‐4% after the 2003‐
2005 baseline period. Analyses for Olmsted County The ability to detect associations via case‐crossover and time series methods in Olmsted County was limited by small sample sizes and possible exposure misclassification resulting from the presence of only one continuous PM2.5 monitor within the county. Table 1. Case‐crossover and time series results for multi‐day moving average lags, MSP metro, 2003‐2009* Health outcome PM2.5 lag Total respiratory hospitalizations lag02 CLRD hospitalizations lag02 Asthma hospitalizations lag02 Asthma ED visits (2005‐2009) lag03 Total CVD hospitalizations lag03 Ischemic heart disease hospitalizations lag03 Congestive heart failure hospitalizations lag03 All‐cause mortality lag01 CPD mortality lag01 *Shaded cells show statistically significant associations. Odds ratio (per 10µg/m3 increase in PM2.5) Case‐crossover Time series 1.032 1.040 1.040 1.005 1.006 1.018 1.008 1.008 1.008 1.022 1.036 1.043 1.026 0.989 0.997 0.984 1.014 1.011 30 Table 2. Population‐attributable fractions (PAF) of PM2.5 exposure by time period, MSP metro, 2003‐2009 Population Attributable Fraction* # Events/year Time OR (lag02) % Events attributable Health outcome attributable to PM2.5 3
to PM2.5 exposure period (per µg/m ) exposure Total respiratory hosp. 2003‐2005 2.1% 244 2006‐2007 1.032 1.7% 203 2008‐2009 1.8% 214 CLRD hosp. 2003‐2005 2.5% 118 2006‐2007 1.040 2.2% 107 2008‐2009 2.2% 106 Asthma hosp. 2003‐2005 2.5% 60 1.040 2006‐2007 2.1% 53 2008‐2009 2.1% 47 *Based on case‐crossover analyses using PM2.5 exposure lag02 and an assumed PM2.5 reference level of 5µg/m3
Issues and considerations for expanding this work to other geographic areas within MN  Exposure assignment issues  Consider availability of air monitoring data at proper geographic (limited number of monitor locations) and temporal (continuous monitoring vs. 1‐in‐
3‐day or 1‐in‐6‐day monitoring) scales  Consider availability and usability of modeled air data (available statewide for years 2001‐2006 only)  Population size issues  Consider statistical limitations of conducting analyses in smaller populations and to what extent pooling of multiple years of data will help address those limitations 31 This page intentionally left blank. 32 SectionUpdate:MercuryBiomonitoringFollow‐upProjects
Jean Johnson will review progress in mercury biomonitoring since the March Advisory Panel meeting. She will briefly describe the upcoming collaboration with the University of Minnesota, The Pregnancy and Newborn Exposure Study, and will sketch out the program’s steps for planning future mercury biomonitoring projects. ACTION NEEDED: No action is needed at this time. Panel members are requested to provide comment and advice on the biomonitoring program’s current and future plans. 33 This page intentionally left blank. 34 MercuryBiomonitoringFollow‐upProjectsUpdate
Overview of accomplishments An internal team at MDH has been meeting monthly since November 2011 to coordinate data analysis, interpretation, and communications about the Mercury in Newborns of the Lake Superior Basin project results across multiple divisions and to advise staff on follow‐up investigations in response to panel recommendations. The Pregnancy and Newborn Exposure Study In March, the Advisory Panel recommended collaboration with UM investigators on a follow up study to compare mercury levels found in paired newborn cord blood and heel stick spots for aiding in the interpretation of the blood spot results. To date, staff working in collaboration with Dr. Ruby Nguyen at UM completed the necessary project protocols and a work contract for a study that, before January 1, 2013, will recruit between 50 and 100 pregnant women who are already participants in The Infant Development and Environment Study (TIDES). The Pregnancy and Newborn Exposure Study will measure mercury (total and speciated), lead, and cadmium in the cord blood of newborns, and total mercury in heel stick spots. The contract is now complete and UM IRB approval was granted on May 9, 2012. MDH IRB response is pending. In the meantime, UM and MDH staff are preparing for recruitment, and data and specimen collection to begin in early June. Further refining the laboratory method development of the blood spot methodology is a key component of this project. In addition, EHTB epidemiologists will work with PHL laboratory chemists to review decisions about the use of laboratory “qualified” results (analysis results that do not meet pre‐determined QA/QC criteria) in heel stick spot data analyses. EHTB staff propose conducting a sensitivity analysis to determine how various inclusion/exclusion criteria based on data qualifiers will affect the findings. Next Steps In December, the Advisory Panel recommended that MDH do more work on the questions raised by the Lake Superior mercury project “To enable MDH to keep on the table the idea of pursuing more studies as resources appear: 1) To what extent are other populations exposed, and 2) what are the sources of exposure? “ The panel also recommended that MDH should develop specific aims and long term objectives. “The long‐term objectives are to develop other long‐term research agendas to characterize exposure in broader portions of Minnesota—to learn the extent of the source of the problem. The program staff should come back to the panel with specific recommendations.” (Advisory Panel meeting notes, December 13, 2011) EHTB staff are planning a series of meetings over the next several months with external and internal stakeholders, including the MDH Fish Consumption Advisory program, local public health, MPCA mercury reduction programs, and child health advocacy organizations to gather more input on long‐term goals for public health tracking and biomonitoring of 35 mercury hazards, exposure, and health effects in Minnesota. Recommendations based on stakeholder feedback will be presented to the Advisory Panel in the fall and incorporated in our report to the Minnesota Legislature next session. 36 SectionOverview:BiomonitoringUpdates
Jean Johnson will briefly discuss the EHTB’s PFC biomonitoring project and will answer questions about the GLRI and National Biomonitoring Initiatives updates
 PFCs  Great Lakes Initiative  National Biomonitoring Initiatives ACTION NEEDED: No action need be taken at this time. Panel members are invited to ask questions and offer comments on the project updates. 37 This page intentionally left blank. 38 BiomonitoringUpdates
East Metro PFC Biomonitoring Follow‐up Project Update Overview of accomplishments While EHTB epidemiologist, Jessica Nelson, was on maternity leave this past quarter, staff continued to track the evolving epidemiology of PFCs. A graduate student worker, Christy Rosebush, was hired and has maintained our PFC literature database. A recent report from the database was provided to Environmental Health toxicology staff. The West Virginia‐Ohio community study of PFOA exposure and health outcomes (also known as C8) has released several “Probable Links” reports in recent months (see Other Information section), and more are expected this summer. Jean Johnson responded to several media inquiries about these reports. The local media are well informed and alert to new studies on PFCs, so media inquiries usually come to MDH within hours after a new epidemiological study article has been published and made public. Staff are able to provide general statements about the findings and the author’s interpretation. We also reinforce our main messages about the PFC biomonitoring findings in the East Metro compared to the West Virginia‐Ohio community and other study communities. Panel Members, Please Note: Media questions continue to focus on health concerns and whether MDH will or will not recommend additional health/biomonitoring study in the East Metro community or elsewhere in Minnesota in the future. Staff plan to address this question with the Advisory Panel at the September 2012 meeting, after all C8 “probable links” reports are expected to be public. Advisory Panel members will see summaries of these reports in the Advisory Panel book following their release. Status Update: the Great Lakes Initiative Community Biomonitoring Study Background This study has a non‐research public health focus on susceptible subpopulations with increased risk of exposure to persistent contaminants common to Great Lakes watersheds. Funding for the study originated from the Great Lakes Restoration Initiative (GLRI) and was provided through EPA to ATSDR, who funded cooperative agreements with public health agencies in Minnesota, Michigan, and New York to conduct human biomonitoring studies. In Minnesota, the Fond du Lac (FDL) Band of Lake Superior Chippewa Reservation is located in the Great Lakes Basin and within the St. Louis River Area of Concern (SLRAOC). The SLRAOC has been affected by industrial activities over decades, resulting in contaminated sediments, abandoned hazardous waste sites, landfill and industrial discharges, and surface runoff. American Indians affiliated with FDL or other tribes, who live in proximity to the SLRAOC (herein called the “FDL Community”), may experience greater exposure to contaminants as consumers of traditional foods from local aquatic environments, such as 39 fish and waterfowl. Within the FDL Community, certain subgroups are also more sensitive to the effects of contaminants due to life stage, including elders and women of child‐bearing age. MDH and the FDL Human Services Division are collaborating on the study. The overall strategy is to measure contaminant levels in, and to administer questionnaires to, a representative sample of 500 adults in the FDL Community. Study findings will be used by MDH and FDL to develop a public health action plan to prevent or reduce exposures to Great Lakes contaminants through targeted interventions. Timeline The project period is September 30, 2010 to September 29, 2013. MDH will request an additional one‐year, no‐cost extension to complete study activities. Recruitment and enrollment are anticipated to begin in July 2012 and will continue for one year. Status Update Community outreach is well underway, including the publication of newspaper articles and presentations at several community events. These efforts are being led by the on‐site study manager, who was hired by FDL in March 2012. FDL is currently in the process of hiring two recruiters/interviewers. MDH study staff are reviewing outreach materials, completing results communication materials, finalizing procedures, and validating the computer‐
assisted personal interview (CAPI). At the federal level, the Office of Management and Budget is expected to review the GLRI biomonitoring package and issue a Notice of Action (i.e., approve the data collection) in early June. National Biomonitoring Initiatives Update Association of Public Health Laboratories (APHL) The APHL Biomonitoring Subcommittee recently met at the CDC laboratories in Atlanta, GA and reviewed current progress on a 5‐year National Biomonitoring Plan that was published in 2010. The plan calls for the integration of multiple disciplines, expertise, and technologies in order to enable, across states: 1) a more coordinated approach, 2) more effective use of limited resources, 3) higher quality data, and 4) improved practice and data sharing. Other accomplishments include: 


APHL has also been engaging stakeholders, particularly state legislators, and sharing success stories of biomonitoring from their member laboratories. APHL is currently working on a database of state public health laboratory biomonitoring profiles that is expected to be public this summer (2012). APHL will soon publish a biomonitoring guidance document with best practices for laboratories. 40 APHL representatives will present at the upcoming EPHT fall conference to promote their national plan and engage with the EPHT Biomonitoring Task Force (co‐leader, Jean Johnson, MN EPHT). CDC EPHT Biomonitoring Task Force The EPHT Biomonitoring Task Force met in Denver, Colorado to review progress on their workplan. With the help of MN EPHT graduate student worker, Christy Rosebush, the Task Force is developing a survey tool for an assessment of available biomonitoring data and project information in all 50 states. The information will be used to identify data gaps and needs across the states, and develop recommendations. CDC PHL Biomonitoring Grantee Meeting CDC Biomonitoring Grantees, New York, California, and Washington State Public Health Laboratories will meet in late November 2012 to share their progress. All 3 grantees are working in collaboration with their state Environmental Public Health Tracking programs. CDC National EPHT Network Promotes Biomonitoring Data In late April, the CDC National EPHT network launched new tracking content on their national web‐based portal, using NHANES biomonitoring data for 11 analytes: arsenic, benzene, cadmium, chloroform, cotinine, lead, mercury, naphthalene, pyrene, toluene, and uranium. They plan to add additional analytes in the next year. To see this new content go to their webpage: http://ephtracking.cdc.gov/showBiomonitoringLanding.action 41 This page intentionally left blank. 42 LegislativeReport
Newborn Screening & Genetic Information Modifications (HF2967*/SF2558) Newborn Screening Program. This law defines newborn screening operations, establishes a standard retention schedule for positive and negative specimens and test results, and allows for the use of newborn screening specimens for program operations during the retention period. MDH is required to provide newborn screening information to expectant parents and/or the parents of newborns through healthcare providers on the purpose of the program and the options parents have to choose or reject screening. Parents may authorize MDH to store and use blood specimens and test results beyond the standard retention period. To obtain this authorization MDH must provide parents with a detailed consent form with information regarding how the sample may be stored and used, how privacy is protected, the benefits and risks of storing the specimen and test results, and must include a Tennessen Warning. The Commissioner must notify the public and the legislature when specimens and test results retained prior to November 16, 2011 have been destroyed. Genetic Information Public Health Exemption. The law delays application of the genetic information requirements under MS 13.386 to MDH programs for one year. The Commissioner is required to submit proposed legislation by January 15, 2013 to authorize collection and use of genetic information for existing activities where express authorization is not provided by law. Submitted by Matthew Collie, MDH Executive Office 43 This page intentionally left blank. 44 SectionOverview:OtherInformation
This meeting packet contains the documents that may be of interest to panel members.  March 2012 Advisory Panel Meeting Summary  2012 Advisory Panel Meeting dates  Advisory Panel Roster  Biographical Sketches of Advisory Panel Members  Biographical Sketches of Staff  Environmental Health Tracking and Biomonitoring Legislation  Summaries of Recent PFC Studies of Interest  Update on the Recruitment Phase of the National Children’s Study Pilot 45 This page intentionally left blank. 46 Summary:March13,2012MeetingoftheEHTBAdvisoryPanel
Attendees: Panel Members: Bruce Alexander, Alan Bender, Tom Hawkinson, Jill Heins‐
Nesvold, Cathi Lyman‐Onkka, Pat McGovern, Greg Pratt, Geary Olsen, Cathy Villas‐Horns, Lisa Yost (by phone). Steering Committee: Aggie Leitheiser, Mary Manning. Other MDH divisions: Carin Huset, Eric Zabel, Pat McCann, Carl Herbrandson, Betsy Edhlund, Jeff Brenner. Staff: Jean Johnson, Barbara Scott Murdock, Blair Sevcik, Dave Stewart, Chuck Stroebel. Bruce Alexander welcomed everyone, invited panel members, staff, and members of the audience to introduce themselves, and called the meeting to order. EastMetroPFCFollow‐upLaboratoryAnalysis
Public Health Laboratory (PHL) chemist Carin Huset presented results of paired re‐analyses of selected samples from the 2008 and 2010 East Metro PFC Biomonitoring Projects. The PHL originally presented the data for the 2010 East Metro PFC Biomonitoring Follow‐up Project at the October 2011 Advisory Panel meeting. The project had measured the concentration of perfluorochemicals (PFCs) in serum of residents of the East Metro who had participated in MDH’s 2008 pilot project to assess whether efforts to reduce drinking water exposure to PFCs had been successful in reducing body burden in the population. Because uncertainty is inherent in all analytical methods, and comparisons are being made between samples analyzed in two different years, the Advisory Panel suggested that the lab re‐
analyze specimens from 2008 at the same time as the corresponding 2010 sample to make sure that the measurements were comparable. Carin chose paired 2008 and 2010 samples from five individuals in whom PFHxS, PFOA, and/or PFOS had increased by a large percent, and another five paired samples from people in whom one or more of these PFCs had declined by a large percent. She then re‐extracted and re‐analyzed both specimens in each pair. The average relative duplicate precisions (RDPs) for the 2008 specimens were 10%, 5% and 9% for PFHxS, PFOA, and PFOS, respectively. The average RDPs for the 2010 specimens were 7%, 15%, and 12% for PFHxS, PFOA, and PFOS, respectively. These precision values are within the range of analytical uncertainty for the method. The correlation coefficient of agreement was >0.99 in the 2008 data and >0.97 in the 2010 data. In short, Carin concluded, the analytical technique was not the source of differences in PFC concentrations seen in the specimens between 2008 and 2010. The panel had no questions. Geary Olsen commented that he was comfortable with Carin’s analysis and conclusion. 47 LaboratorymethodforHginNewbornBloodSpots:
AssessmentandRecommendations
Betsy Edhlund reviewed the methods and quality controls used in measuring mercury in the residual dried blood spots (RDBS) used in the Lake Superior Mercury in Newborns Study (March Advisory Panel book). She compared MDH’s methods with those reported by Utah’s Public Health Laboratory, which has published a similar method for measuring mercury and other metals in newborn blood spots (Chaudhuri et al., 2008). Although their methods differ somewhat, both laboratories had similar detection limits. The MDH method detection limit (MDL) was 0.7 µg/L; the Utah laboratory’s MDL was 0.65 µg/L. MDH laboratory staff noticed some high bias in medium and high levels of mercury measured in the blood spots, but so far, have not been able to explain it. They also established that different storage conditions for the dried blood spots did not seem to affect mercury extraction (for details, please see March 13, 2012 Advisory Panel book). Betsy noted that there is ample scope for improving the method. First, better calibration standards are needed. When the project was underway, the PHL was able to find only one vendor that could supply a methylmercury (MeHg) standard. Later, someone discovered that the concentration of the standard differed from what was reported in the certificate of analysis. This meant that the laboratory had to re‐calculate the RDBS results, reducing the minimum detection limit (MDL) and the reporting level for the mercury concentration results. Had the laboratory used two different sources of materials, which now are available, staff would have discovered the discrepancy sooner. In future, now that more vendors are available, the laboratory would change the standard operating procedure for the method to require two separate sources of material and correct the vendor concentration to MeHg, rather than MeHg chloride. Other improvements available now include better toxic metal standards in goat blood. These come in four different concentrations of total mercury, including one with a concentration below the MDL, one with a reference value of 4.95 µg/L, and one with certified concentrations for methyl mercury, inorganic mercury, and ethyl Hg, with a total mercury concentration of 17.8 µg/L. Although both levels are higher than most in the study, they are much closer to the concentration range found in the blood spots than the original standard reference material (SRM). Now that these standards are available, the laboratory staff would like to do a study of extraction efficiency measures in various mercury species. This study would enable the staff to have a better understanding of the extraction efficiency of the method and how that relates to the mercury recoveries for the patient samples. The preparation of calibration curve standards could then be optimized for the best method performance. The laboratory would also like to analyze more RDBS, but would like to have more blood spots per newborn in case an analysis needs to be repeated, reducing the number of samples reported with a data qualifier. This could also reduce the MDL and the reporting level, and allow more samples to be reported above the detection limit. 48 Overall, Betsy considers RDBS from newborn screening programs as unlikely to be useful for identifying the full range of population exposure, but as potentially useful for identifying the high end range of mercury exposure and as a screen for follow up. Overall, the method has proved to give very consistent results. Discussion Tom Hawkinson asked whether PHL staff had considered non‐destructive methods, such as X‐ray fluorescence spectrometry (XRF), for analyzing the blood spots and whether staff had considered inconsistencies in the volume of blood in the spots. It’s a big assumption to assume consistency. Betsy answered that, yes, staff had to consider that variation, but they did assume that the volume would be consistent across the RDBS and within a spot. Greg Pratt followed up, saying, if a spot is not homogeneous for mercury, it would be a problem for the SRM as well. Tom added that the detection limits of XRF analysis were not in the appropriate range for this type of sample and it doesn’t allow for speciation of the sample. SpecificAims1:UmbilicalCord:NewbornBloodSpotComparisonStudy Barbara Scott Murdock reviewed the Advisory Panel’s motion in the December meeting that staff develop specific aims for a cord blood: newborn blood spot comparison as a follow up to the Lake Superior Mercury in Newborns findings. The project found that 10% of the Minnesota newborns measured had mercury concentrations in the newborn blood spots above the Environmental Protection Agency (EPA) reference level (5.8 µg/L, a “safe” level) in umbilical cord blood. The EPA reference level was derived from a benchmark dose level (BMDL) established by a National Research Council study requested by the EPA (NRC 2000). The BMDL (58 µg/L) is based on a well established, long‐term study of prenatal methylmercury exposure and its neurological effects in a population in the Faroe Islands. It is “the lowest dose… expected to be associated with a small increase in incidence of adverse outcomes…” Moreover, the NRC committee chose to measure mercury in umbilical cord blood because “[this measure] would be expected to correlate most closely with fetal‐brain Hg concentrations during late gestation.”1, 2 That is, cord blood is fetal blood, and therefore, comparing total mercury in cord blood with total mercury in newborn blood spots is a way to establish whether or not the blood spots accurately reflect or predict mercury exposure to the fetus in the last trimester of pregnancy. (For more detail, please see the December 2011 Advisory Panel book). For these reasons, EHTB staff developed the following goals, rationale, hypotheses, and specific aims. Staff then posed the questions below to the panel; the questions address both the laboratory presentation and the specific aims presentation. Goals • Goal 1: To compare total Hg content in paired cord blood: blood spots from sample of newborns to get a measure of the ratio. • Goal 2: To speciate the cord blood to obtain the MeHg: I‐Hg content. 49 •
Goal 3: To further refine the laboratory methods for measuring Hg exposure in newborns. Rationale • If newborn spots compare with or predict exposure measured in cord blood, then… • MDH can recommend the method for public health surveillance studies and compare the blood spot results to the EPA RfD (5.8µg/L) in cord blood. • The PHL can determine whether different ratios of organic‐Hg and I‐Hg in blood samples affect extraction efficiencies and the cord: blood spot ratio. Hypotheses • 1 (null) T‐Hg in blood spot: cord blood = 1 – Significance: comparing spot T‐Hg to the EPA RfD is appropriate for assessing health risk in a population of tested infants. • 1 (alt) T‐Hg in blood spot: cord blood ≠ 1 – Significance: if we use heel stick blood spots, we will need a correction factor to appropriately assess health risk in a population of tested infants. • 2 (null). Differences in the MeHg: I‐Hg ratio do not change the T‐Hg blood spot: cord blood ratio. – Significance: if the T‐Hg amounts in blood spot: cord blood pairs correspond and the Hg composition does not change the ratio, then we should be able to compare the MeHg exposure to the RfD and inform public health action. Specific Aims • Obtain paired cord blood & newborn blood spots from a small population of newborns. • Measure total mercury in both blood specimens for each pair; compare results for each pair and calculate an average ratio. • Speciate mercury in the cord blood sample for each pair; record cord MeHg & I‐Hg for each pair. • Categorize paired specimens based on differences in the ratio; analyze how different Hg species contribute to variability in the ratio • Analyze how differences in mercury speciation affect blood spot extraction efficiency. Questions to the Panel 1) Have panel members any suggestions for changes or clarifications to the Specific Aims? 2) Are we ready to develop a proposal based on these Specific Aims? 3) Given that the study must be small and conducted within limited resources, what population selection criteria should we use for this project? 4) Should the EHTB program support efforts by the MDH’s Public Health Lab to further improve & document the method so it can be disseminated to other laboratories? 50 5) Should the EHTB support further improvements to this method for biomonitoring in Minnesota? Note: Questions 2 and 3 were tabled so as to allow more time for Dr. Ruby Nguyen to describe a possible collaboration with MDH. Discussion Pat McGovern said the project would be an interesting and important contribution to Minnesota and to the literature in the field. Bruce Alexander was skeptical of the alternative hypothesis 1, which suggests that we could identify a consistent, but unequal, relationship between cord and newborn spot that would allow us to calculate an adjustment or correction ratio. Both Greg Pratt and Bruce Alexander pointed out that the adjustment sounds simple, but is probably more complex than just applying a correction ratio. Alan Bender suggested that EHTB staff work with laboratory staff to identify a priori boundaries for accepting and rejecting hypothesis 1 before you start testing. Tom Hawkinson, however, suggested that that approach might be a pretty high standard for this method. Aggie Leitheiser asked whether we would do this project in a small population. Jean said that staff had done an n calculation that suggests that, at minimum, 50 cord: newborn spot pairs might be enough to determine a spot and cord blood geometric mean. It might take as many as 100. Tom asked whether EHTB staff had looked in the literature for other studies that have addressed these questions, such as partition of mercury species in maternal blood and in animal studies. Pat McCann answered that many studies have looked at this and are the source of the cord blood: maternal blood ratio of 1.7. But there are differences in species and how they partition, and a lot of variability in the ratio. She added, “I think there will be a lot of variability in these results.” Alan said that, given the variability, staff should do a sequential analysis, rather than setting a sample size first. [Alan explained later that the variability of the data may not be known before the start of the study. Sequential analysis starts with an initial sample, determines the variability of that sample, and estimates the number of additional samples required to meet stated goals (type 1 and type 2 errors). Then additional samples are taken, tested again, and when the goals are met, the study ends. This method allows for “on the fly” determination of variability and for the earliest termination of the study, adjusting for improving knowledge of the variability as the study progresses.] Attention then turned to the laboratory question: Should EHTB financially support the PHL’s efforts to improve the RDBS method as Betsy described it in her presentation? Geary Olsen argued that the PHL should publish the method in an analytical journal to elicit the required critique of the method. You can get a good peer review that way, he said, although you may have to carry out this [cord: spot] step first. Pat McGovern asked whether the two processes, the [cord: spot] analysis and improvement of the method, could go on together. She suggested Betsy could turn her award‐winning poster into a publication. Pat McCann 51 noted that her group, MDH Environmental Health (not EHTB), is working on publishing the original Lake Superior Mercury in Newborns study, and that Betsy is working to publish the laboratory method. Alan asked, what must be known about the method before CDC’s laboratory would adopt the laboratory method? Betsy replied that she had spoken with CDC staff at her poster presentation in January, and that CDC is interested in the method and in seeing it published, but she doesn’t know what their process for adopting it would entail. Jean asked whether it is a goal for the laboratory to disseminate the method to other laboratories for their use and reproduce its results (for external validation). Betsy agreed with that goal, and Jean explained that sharing with other laboratories is how a method can become a standard. Geary pointed out that people typically publish methods before establishing inter‐laboratory consensus. Getting the methods out will generate the enthusiasm of others to look, tweak, and challenge your methods. Bruce suggested that the panel propose a motion on the specific aims and a recommendation for publication. Pat McGovern proposed a motion that includes Greg’s amendment to the specific aims hypothesis 1 (alternative). I move that EHTB staff develop a project proposal the addresses the specific aims above with hypothesis 1(alternative) amended to read that if blood spot mercury is not equal to cord blood mercury, does not necessarily enable us to conclude that it is possible to derive a ratio for adjustment. Cathi Lyman‐Onkka seconded it. Vote: All in favor. Geary Olsen then framed a recommendation: to encourage MDH to ensure the publication of results when MDH is comfortable with releasing the work. Panel members variously emphasized that publication of good work not only is important to public health, but also enhances the reputation of MDH, its staff, and the state of Minnesota. Bruce suggested taking a voice vote that the panel members are in support of that. All said yes. PotentialCollaborationwithTheInfantDevelopment&EnvironmentStudy(TIDES)
Ruby Nguyen (UMN) Jean Johnson Jean introduced Dr. Ruby Nguyen and briefly reviewed the background for the next presentation. To find a source of cord blood and dried blood spots for the two mercury follow‐up studies, staff first contacted Dr. Logan Spector, who collaborated with the EHTB to carry out the Riverside Prenatal Biomonitoring Pilot Project as an ancillary to his Riverside Birth Study. Dr. Spector collected maternal blood, cord blood, and extra newborn blood spots for research, with informed consent. Unfortunately for the EHTB projects, Dr. Spector’s study kept the blood plasma, but discarded the red blood cells, which would have 52 contained most of the methylmercury; the blood spots may still be useful to MDH in future. Dr. Spector recommended that the EHTB staff should talk with Ruby Nguyen, who is carrying out the Minnesota arm of The Infant Development and Environment Study (TIDES). Ruby explained that TIDES is a four‐year NIH‐funded project focused on four sites: Minnesota (Minneapolis), Washington (Seattle), New York State (Rochester), and California (San Francisco). The principal investigator is Dr. Shanna Swan, currently at Mt. Sinai School of Medicine in New York. The study’s primary focus is on learning more about the effects of phthalates and anti‐androgen receptors on infants during gestation. The study will measure such physical indicators as anal‐genital distance and other changes in estrogen‐responsive organs in the infant boys at one year. The study is beginning to look at infant girls as well. The study has been recruiting women at six to 10 weeks of pregnancy at all four sites. The study collects maternal blood in the first trimester and urine for all trimesters, and follows up with infant examinations at birth and at one year. Future plans for the project include looking at gender play in the children. The total number of babies is expected to be 800 to 900. At the Riverside clinic in Minneapolis, the study currently has enrolled nearly 100 women, English speakers only, and expects to enroll 220 by the end of recruitment in May or June 2012. Less than 10% of the women decline enrollment. Drs. Nguyen and Swan are very interested in collaborating with the EHTB. They propose to work with the obstetrics staff to add the collection of cord blood and extra newborn blood spots obtained by routine heel stick. They also propose to give MDH access to food frequency data in their questionnaire. These changes would require changes in the IRB (institutional review board) protocol, but because the addition of more blood spots would be minimally invasive, would involve no new procedure for the infant, and no effect on the mother, the investigators expect a quick approval from the IRB. The MDH IRB will also need to review the protocol. Discussion Pat McGovern asked whether the proposed project could learn what kinds of fish that the women in the study might be eating. The work in the Lake Superior Mercury in Newborns study focused on women who lived in the Lake Superior basin, but this project would involve only women in the Twin Cities. Ruby said that the questionnaire asks only for the amount of fish that the women eat, not the type or origin. She added that the investigators do not yet have the ethnic identities of the women, but said that most are Caucasian. In response to Aggie Leitheiser’s concern about generalizability of the study, she said that TIDES is also sampling from other newborns in the nursery [infants whose mothers were not recruited during pregnancy] to increase the generalizability of the findings. The TIDES study will not provide the phthalate findings to the women because health effects from phthalate exposure have not been established in humans. Mercury results in 53 the Minneapolis study, however, would be sent to the mothers because the health effects of mercury exposure are well understood. Pat McGovern observed that if the population is mostly Caucasian, the [cord: spot] study is another step forward, but maybe the next step [could involve] a more diverse population that would generate more generalizable data. Aggie agreed, saying this is an incremental process. But, Cathi Lyman‐Onkka noted, given that this first study is simply looking at the cord blood: heel stick ratio, it may not matter if the results of the paired samples are not generalizable. Bruce agreed that the ratio is the objective of this project. Saying that “it absolutely makes sense to go ahead with this study,” Greg Pratt argued that, although the study would not be generalizable [with respect to differences among demographic groups], it would provide valuable information about the method. The PHL staff raised questions about the amount of blood for laboratory analyses, particularly for blood spots. Ruby commented that Logan Spector (anecdotally) had some trouble with blood volume when his project was collecting blood spots. The first priority was to ensure enough blood for the newborn screening procedure, and then three spots were taken for the research project. Quantity was an issue. He considered a second heel stick for babies “who aren’t bleeders,” but to be collected only on a case‐by‐case basis. Pat McCann asked whether that study followed quality control parameters for the extra three spots, especially with respect to the concern about the volume of blood mentioned earlier. She said the collection should make all of the spots meet the criteria used for newborn blood spots, since [uniformity of the sample] is important for mercury analysis. Pat also asked whether TIDES planned to get informed consent for additional newborn spots. Ruby said the study would add a supplemental consent form or, if the investigators decide to gather more blood with a second heel stick, they might use a new consent form. When Betsy asked whether the study would use the same filter paper as that used for the newborn blood spots, Ruby said the study would use the same filter paper if the laboratory recommended it. Ruby asked about any concerns for processing cord blood, and Aggie asked whether any method had been established. Betsy answered that the PHL had an established method for processing whole blood. She had no recommendations for collecting and processing cord blood per se, but would research that. For speciating forms of mercury in whole blood, the laboratory would need 50 µg of blood. She speculated that the laboratory might develop speciation procedures for blood spots [if they had enough spots to provide the amount of blood necessary]. Pat McCann asked whether TIDES had an interest in mercury before. Ruby explained that, although mercury was not an initial focus, the TIDES investigators had discussed mercury as an environmental exposure. Thus, they are interested in collaborating with MDH. They would like to add lead and cadmium to the analysis and were willing to pay for those analytes, as they want to follow up on cognitive development in these children. 54 Ruby asked for a recommendation on timeline. She said that protocols should go to the IRB quickly, as 10‐12 babies are being born each month, and TIDES plans to stop recruiting in May or June. Jean turned to the panel and, noting the time sensitivity of this project, asked, “How would the panel like to proceed?” Bruce suggested that EHTB staff draw up the methods and send them by email to the panel members for review and comment. Cathi Lyman‐Onkka said, “I move that MDH pursue collaboration with TIDES to compare mercury in cord blood to mercury in newborn blood spots in paired samples from newborns. Pat McGovern seconded the motion. All in favor, motion passed. BiomonitoringUpdates
East Metro PFC Follow‐up and the Great Lakes Initiative Although this section had no presentation scheduled, Jean Johnson noted that Jessica Nelson is on maternity leave but, on her return, would continue to follow the literature on PFCS and other material on biomonitoring, and resume Phase II of the PFC study by analyzing the PFC questionnaire data. ChemicalsinPeople
Biomonitoring as a Content Area for Tracking: Evaluation of Content and Rationale Jean Johnson explained that Minnesota’s legislation directs the EHTB program to integrate biomonitoring (exposure) data with state environmental health hazard and health outcome data. Minnesota will be the first state to feature biomonitoring data as content on its state EPHT (Tracking) data portal. The objective of this content area is to address the exposure category of the hazard  exposure health outcome paradigm. Most of the data will be drawn from CDC’s National Health and Nutrition Examination Survey (NHANES). The chemicals of interest will be vetted through the content area process developed in the MN EPHT program: exploration, feasibility, and recommendation. Minnesota‐specific biomonitoring data may be added as available. Jean reviewed the feasibility criteria for using NHANES data sources and data from EHTB pilot projects to provide biomonitoring data on environmental chemicals of public health interest in Minnesota (for details, see March 2012 Advisory Panel book). She then demonstrated the new webpages, which highlight biomonitoring of PFCs and mercury both in NHANES data and in EHTB pilot project findings in Minnesota (Jessica Nelson prepared the text and graphics for the pages). And she asked panel members to respond to the questions below: Discussion item 1. Do panel members have suggestions for improving the content or messaging for biomonitoring data displays on the portal? 2. What other important Minnesota priority chemicals should be included in data display in this content area? 55 Discussion The conversation first focused on question 1: content and messaging. Alan Bender asked, how do members of the public ask questions about the website? What is the feedback mechanism? Chuck Stroebel answered that the home page has a “contact us” link that leads people to Dave Stewart’s email address, so they can ask questions directly. During the website’s usability testing period, the home page also linked to a Vovici survey that allowed website users to provide feedback on the website’s content and ease of use. Jill Heins‐Nesvold suggested that the “About the Biomonitoring Data” link might be a good place to manage expectations and to inform policymakers that this is new, cutting‐edge science, which develops incrementally. It’s a place to highlight progress and point to future research directions. Jean noted that the “What can these data not tell us?” section lists some of the limitations of biomonitoring data, but agreed that elaborating on this message might be helpful. Jill suggested that the messages might clarify that more research is necessary, that we are only beginning to learn about exposures in Minnesota, and that we need resources to gather data and identify problems. Jean pointed out that we have no state biomonitoring data on most chemicals—we miss pockets of high exposure. Alan agreed, saying that people often are shocked when they learn that MDH has such limited population‐based data on such illnesses as cardiac morbidity. When asked about other chemicals that the panel would like to see on the “Chemicals in People” webpage, Pat McGovern asked whether the program would need to find more funding if the panel proposed additional chemicals for the website. Jean clarified that we would not need more funding to promote the national data, as we would add only biomonitoring data from NHANES. Jean suggested EHTB could start with chemicals selected for the EHTB program’s other pilot projects, which examined exposure to BPA, parabens, cotinine and arsenic. Jean added that the national tracking program (EPHT) Biomonitoring Task Force is working with CDC to integrate biomonitoring into tracking with 11 chemicals added to the national EPHT network portal. CDCTrackingDataofDevelopmentalDisabilities Blair Sevcik In January, CDC launched a new content area that tracks data for two indicators: (Indicator 1) prevalence of autism and (Indicator 2) children receiving services or interventions for a developmental disability. The data, which come from the CDC and from the US Department of Education (USDE), differ in focus and in selection criteria. As the first step in the evaluation process for adding new content to the MN EPHT data portal, Blair Sevcik discussed the two data sources for tracking developmental disabilities on CDC’s data portal: CDC’s Autism & Developmental Disabilities Monitoring (ADDM) and USDE’s Individuals with Disabilities Education Act (IDEA). ADDM collects data on the prevalence of autism spectrum disorders (ASDs) among children 8 years of age from network sites in 15 states. IDEA tracks the number of children who 56 receive services or interventions for developmental disabilities. Blair pointed out that ADDM has data by year, gender, and race/ethnicity, but the data are not representative, and ADDM has no data for Minnesota. IDEA, on the other hand, has good temporal and spatial data at the state level across the US, but because it focuses on services, cannot be used to estimate the prevalence of any one disability. It has no prevalence data; the classification of disabilities is defined by the services needed; and the program and funding differ by state and over time as state funding for special education and other services fluctuates. Moreover, many children in IDEA are identified at ages 3‐5 years, but often drop out of the system after receiving a service or intervention. As a result, the data are artificially low for children over 6 years of age, according to MDH Maternal and Child Health Section staff who were consulted about the quality of this data source. The full IDEA dataset collects about a dozen types of developmental disabilities; CDC tracks seven of those among children aged 3‐17 years. Children are included in Indicator 2 (receiving services) if they a) are receiving services or interventions and b) are found to have one of the seven developmental disabilities, according to IDEA. Blair’s conclusion is that MN EPHT should look at other data sources, such as the National Survey of Children with Special Health Care Needs (NS‐CSHCN), if the program begins the evaluation process for developmental disabilities as a Minnesota‐specific content area. Phase 1 of this process includes determining what data sources could feasibly be used to develop new indicators. She asked the panel to address the following questions: 1. What concerns do you have about the data sources? Do you share concerns about IDEA? 2. Should we evaluate Developmental Disabilities as a new content area in Minnesota? 3. If we explore this content area, which Minnesota data sources would you recommend we evaluate? Tom Hawkinson commented that the diagnostic criteria for autism spectrum disorders (ASDs) are changing, and also differ by state. The higher bar for diagnosis means that fewer children might be receiving services in future. Blair responded that, in Minnesota, children can receive services for ASDs without a physician’s diagnosis, but it’s true that other states require a medical diagnosis of ASD prior to receiving services tracked by IDEA. Cathi indicated she agrees with the listed limitations for the IDEA data source. Alan suggested looking at data in Minnesota’s Department of Human Services (DHS), which has an extensive database for children receiving services, but Jill said that DHS would not have data on specific disabilities. In Minnesota, children are not eligible for services until they are either in 3rd grade or have fallen two years behind their peers. “I support this effort [to track developmental disabilities],” she added. Pat McGovern recommended that the MN EPHT program should look further at the strengths and weaknesses of the data sources and share their assessments with the panel. She commented that both services and disease prevention are important, but they 57 shouldn’t be confused. Blair commented that Phase 2 of Minnesota’s evaluation process would examine the quality of potential data sources in more detail. Cathi asked whether it would be possible to partner with medical and healthcare systems to share data on developmental disabilities. Bruce pointed out that getting access to and interpreting data in medical databases might be challenging in terms of generalizability, but would be worth exploring. Jill has found that healthcare plans are willing to share data sets; Medica has shared data with the American Lung Association (ALA), and ALA and Medica have published some data jointly. Pat McGovern noted that working with healthcare plans can be fruitful, but warned that successful collaboration depends on their current leadership and priorities. Still, she said, keep the options on the table and explore them. Both Cathy Villas‐Horns and Cathi Lyman‐Onkka suggested looking at environmental ties to development disabilities. Blair said that CDC indicated the seven developmental disabilities included in Indicator 2 (from IDEA) were chosen “because evidence suggests environmental exposures may play a role in developing these conditions,” and that MN EPHT could explore those issues. Bruce recommended that MN EPHT should explore what the data sources are, and what they represent, and especially explore IDEA. Jill added that staff should also see how the data relate to the environment. Pat McGovern suggested that staff might want to look at the NRC report, Children’s Health, the Nation’s Wealth, both because it describes a spectrum of what is normal, and because it includes a section on data sources. Pat also suggested that EHTB invite someone from Maternal and Child Health to speak at the Advisory Panel meeting [when it next addresses developmental disabilities]. In summary, members of the panel were supportive of MN EPHT’s suggestion to begin formally evaluating developmental disabilities, exploring Minnesota‐specific data sources. Staff plan to present Phase 1 at the June 2012 panel and consult the panel for next steps. Trackingupdates
Although this section had no scheduled presentation, the first update prompted a discussion about CDC’s cuts to programs to identify lead poisoning in children. The funding cut, said Assistant Commissioner Aggie Leitheiser, reduced CDC’s national budget for lead programs from $30 million to $2 million. EPA funds are focused on cleaning up lead hazards, but not on identifying children who are lead‐poisoned. In addition, the funding cut will severely hamper MDH’s ability to track lead poisoning cases in Minnesota. The tracking updates address:  Childhood Lead Poisoning  Environmental Tobacco Smoke  Birth Defects  Interactive Cancer Incidence Maps  Nationally Consistent Data and Measures  New Arsenic Measures for Private Wells 58 
Communications and Outreach LegislativeUpdate
Aggie Leitheiser summarized several proposed bills. A bill introduced by Senator Sieben would fund more PFC work, but it has not had a hearing. Two bills focus on surveillance: One proposes that all data collected by MDH should be done with consent; it has not yet had a hearing. Another bill proposes that if MDH receives a grant that involves a surveillance program or a registry, the grant must undergo legislative review and approval. Pat McGovern commented that the latter bill raises questions of federal executive authority. The two bills MDH is working on respond to the [State] Supreme Court decision on newborn screening blood spots [these blood spots are tested for heritable or congenital disorders that can cause health‐ or life‐threatening problems that are treatable or avoidable if treated early]. The Court said that MDH has implied authority to collect newborn screening blood spots, but doesn’t have express authority in law to use and store the spots, or to disseminate data derived from the spots. MDH is proposing new language around the newborn screening program that would allow the department to keep spots and data for quality assurance & quality improvement for 71 days and keep the data for two years for newborn studies. MDH is asking for language and an approach that would allow the department to ask parents for permission to keep their information and newborn spots for use in research in future. A current suit on the newborn screening program, plus two class action suits, is scheduled for trial for damages. For genetic information, MDH is now filing to modify language that refers to “biological specimens or genetic information,” which can be applied to almost everything, to limit the term to genetic tests of chromosomes and DNA. Aggie also noted that the governor has proposed a modest supplemental budget. Newbusiness
Bruce Alexander suggested a more complete discussion of sources for tracking developmental disabilities. Pat McGovern suggested that staff prepare a high level summary of EHTB biomonitoring pilot projects and a review of other chemicals that staff propose to add to the website so that panel members who have not been on the panel for all four years will have a better sense of the program’s accomplishments. Pat McGovern made a motion to adjourn; the motion was seconded, and the meeting was adjourned. 59 2012AdvisoryPanelMeetings
Next Meeting Tuesday, Sept. 11,2012 1 – 4pm The Red River Room Snelling Office Park 1645 Energy Park Drive St. Paul, Minnesota Tuesday, Dec. 11 1‐4pm All meetings for 2012 will take place in The Red River Room Snelling Office Park 1645 Energy Park Drive St. Paul 60 ENVIRONMENTALHEALTHTRACKINGANDBIOMONITORING
ADVISORYPANELROSTER
AsofApril2011
Bruce Alexander, PhD University of Minnesota School of Public Health Environmental Health Sciences Division MMC 807 Mayo 420 Delaware Street SE Minneapolis, Minnesota 55455 612‐625‐7934 [email protected] At‐large representative Fred Anderson, MPH Washington County Department of Public Health and Environment 14949 62nd St N Stillwater MN 55082 651‐430‐6655 [email protected] At‐large representative Alan Bender, DVM, PhD Minnesota Department of Health Health Promotion and Chronic Disease Division 85 East 7th Place PO Box 64882 Saint Paul, MN 55164‐0882 651‐201‐5882 [email protected] MDH appointee David DeGroote, PhD St. Cloud State University 740 4th Street South St. Cloud, MN 56301 320‐308‐2192 [email protected] Minnesota House of Representatives appointee Thomas Hawkinson, MS, CIH, CSP Toro Company 8111 Lyndale Avenue S Bloomington, MN 55420 [email protected] Statewide business org representative Jill Heins Nesvold, MS American Lung Association of Minnesota 490 Concordia Avenue St. Paul, Minnesota 55103 651‐223‐9578 [email protected] Nongovernmental organization representative Cathi Lyman‐Onkka, MA Preventing Harm Minnesota Home office 1525 28th Ave. NW, New Brighton 651‐647‐9017 [email protected] Nongovernmental organization representative 61 Pat McGovern, PhD, MPH University of Minnesota School of Public Health Environmental Health Sciences Division MMC Mayo 807 420 Delaware St SE Minneapolis MN 55455 612‐625‐7429 [email protected] University of Minnesota representative Geary Olsen, DVM, PhD 3M Medical Department Corporate Occupational Medicine MS 220‐6W‐08 St. Paul, Minnesota 55144‐1000 651‐737‐8569 [email protected] Statewide business organization representative Gregory Pratt, PhD Minnesota Pollution Control Agency Environmental Analysis and Outcomes Division 520 Lafayette Road St. Paul, MN 55155‐4194 651‐757‐2655 [email protected] MPCA appointee Cathy Villas‐Horns, MS, PG Minnesota Department of Agriculture Pesticide and Fertilizer Management Division 625 Robert Street North St. Paul, Minnesota 55155‐2538 651‐201‐6291 cathy.villas‐[email protected] MDA appointee Lisa Yost, MPH, DABT ENVIRON International Corporation 333 West Wacker Drive, Suite 2700 Chicago, IL 60606 Local office 886 Osceola Avenue St. Paul, Minnesota 55105 Phone: 651‐225‐1592 Cell: 651‐470‐9284 [email protected] At‐large representative Vacant Minnesota Senate appointee 62 BiographicalSketchesofAdvisoryPanelMembers
Bruce H. Alexander is an Associate Professor in the Division of Environmental Health Sciences at the University of Minnesota’s School of Public Health. Dr. Alexander is an environmental and occupational epidemiologist with expertise in cancer, reproductive health, respiratory disease, injury, exposure assessment, and use of biological markers in public health applications. Fred Anderson is an epidemiologist at the Washington County Department of Public Health and Environment and has over 30 years of public health experience. .He holds a Master of Public Health (MPH) in environmental and infectious disease epidemiology from the University of Minnesota and is a registered environmental health specialist. For over 20 years, he has led county‐wide disease surveillance and intervention programs, including numerous multidisciplinary epidemiologic investigations. Alan Bender is the Section Chief of Chronic Disease and Environmental Epidemiology at the Minnesota Department of Health. He holds a Doctor of Veterinary Medicine degree from the University of Minnesota and a PhD in Epidemiology from Ohio State University. His work has focused on developing statewide surveillance systems, including cancer and occupational health, and exploring the links between occupational and environmental exposures and chronic disease and mortality. David DeGroote is Dean of the College of Science and Engineering and Professor of Biological Sciences at St. Cloud State University. He has been at St. Cloud State University since 1985, initially as an Assistant Professor in Biological Sciences. He served as Department Chair from 1996 to 2003 before moving to the Dean’s Office. Most recently he had focused on providing up‐to‐date academic programming and facilities that serve the needs of Minnesota employers in the health sciences, engineering, computing, biosciences, and STEM education. Tom Hawkinson is the Corporate Environmental, Health, and Safety Manager for the Toro Company in Bloomington, MN. He completed his MS in Public Health at the University of Minnesota, with a specialization in industrial hygiene. He is certified in the comprehensive practice of industrial hygiene and a certified safety professional. He has worked in EHS management at a number of Twin Cities based companies, conducting industrial hygiene investigations of workplace contaminants and done environmental investigations of subsurface contamination both in the United States and Europe. He has taught statistics and mathematics at both graduate and undergraduate levels as an adjunct, and is on the faculty at the Midwest Center for Occupational Health and Safety A NIOSH‐Sponsored Education and Research Center School of Public Health, University of Minnesota. Jill Heins Nesvold serves as the Director of the Respiratory Health Division for the American Lung Association in Iowa, Minnesota, North Dakota, and South Dakota. Her responsibilities 63 include program oversight and evaluation related to asthma, chronic obstructive lung disease (COPD), lung cancer, and influenza. Jill holds a master’s degree in health management and a short‐course master’s of business administration. Jill has published extensively in a variety of public health areas. Cathi Lyman‐Onkka worked in local public health with the Saint Paul – Ramsey County Department of Public Health for nearly 34 years, until her retirement in 2006. From 1997 through May 2006 she was supervisor of the Community Involvement Program in the Environmental Health Section. The Community Involvement Program provided community and professional education related to environmental health, administered the county Household Hazardous Waste Collection Program, and administered the county Waste Management Service Charge and its transition to the County Environmental Charge. Cathi has a B.A. in Biology with a concentration in Environmental Studies from Macalester College, Saint Paul, Minnesota, and a M.A. in Public Administration from Hamline University, Saint Paul, Minnesota. From 2002 to May 2006 Cathi was associated with Preventing Harm through her work for Ramsey County. She has been active on the Preventing Harm Board since November 2007. Pat McGovern is a Professor in the Division of Environmental Health Sciences at the University of Minnesota’s School of Public Health. Dr. McGovern is a health services researcher and nurse with expertise in environmental and occupational health policy and health outcomes research. She serves as the Principal Investigator for the National Children’s Study (NCS) Center serving Ramsey County, one of 105 study locations nationwide. The NCS is the largest, long‐term study of children’s health and development in the US and the assessment of environmental exposures will include data collection from surveys, biological specimens and environmental samples. Geary Olsen is a corporate scientist in the Medical Department of the 3M Company. He obtained a Doctor of Veterinary Medicine (DVM) degree from the University of Illinois and a Master of Public Health (MPH) in veterinary public health and PhD in epidemiology from the University of Minnesota. For 27 years he has been engaged in a variety of occupational and environmental epidemiology research studies while employed at Dow Chemical and, since 1995, at 3M. His primary research activities at 3M have involved the epidemiology, biomonitoring (occupational and general population), and pharmacokinetics of perfluorochemicals. Greg Pratt is a research scientist at the Minnesota Pollution Control Agency. He holds a Ph.D. from the University of Minnesota in Plant Physiology where he worked on the effects of air pollution on vegetation. Since 1984 he has worked for the MPCA on a wide variety of issues including acid deposition, stratospheric ozone depletion, climate change, atmospheric fate and dispersion of air pollution, monitoring and occurrence of air pollution, statewide modeling of air pollution risks, and personal exposure to air pollution. He is presently cooperating with the Minnesota Department of Health on a 64 research project on the Development of Environmental Health Outcome Indicators: Air Quality Improvements and Community Health Impacts. Cathy Villas Horns is the Hydrologist Supervisor of the Incident Response Unit (IRU) within the Pesticide and Fertilizer Management Unit of the Minnesota Department of Agriculture. Cathy holds a Master of Science in Geology from the University of Delaware and a Bachelor of Science in Geology from Carleton College and is a licensed Professional Geologist in MN. The IRU oversees or conducts the investigation and cleanup of point source releases of agricultural chemicals (fertilizers and pesticides including herbicides, insecticides, fungicides, etc. as well as wood treatment chemicals) through several different programs. Cathy has worked on complex sites with Minnesota Department of Health and MPCA staff, and continues to work with interagency committees on contaminant issues. She previously worked as a senior hydrogeologist within the IRU, and as a hydrogeologist at the Minnesota Pollution Control Agency and an environmental consulting firm. Lisa Yost is a Principal Consultant at ENVIRON, an international consulting firm. She is in their Health Sciences Group, and is based in Saint Paul, Minnesota. Ms. Yost completed her training at the University of Michigan’s School of Public Health and is a board‐certified toxicologist with expertise in evaluating human health risks associated with substances in soil, water, and the food chain. She has conducted or supervised risk assessments under CERCLA, RCRA, or state‐led regulatory contexts involving a wide range of chemicals and exposure situations. Her areas of specialization include exposure and risk assessment, risk communication, and the toxicology of such chemicals as PCDDs and PCDFs, PCBs, pentachlorophenol (PCP), trichloroethylene (TCE), mercury, and arsenic. Ms. Yost is a recognized expert in risk assessment and has collaborated in original research on exposure issues, including background dietary intake of inorganic arsenic. She is currently assisting in a number of projects, including a complex multi‐pathway risk assessment for PDDD/Fs that will integrate extensive biomonitoring data collected by the University of Michigan. Ms. Yost is also an Adjunct Instructor at the University of Minnesota’s School of Public Health. 65 BiographicalSketchesofStaff
Wendy Brunner, PhD, serves as surveillance epidemiologist for the MDH Asthma Program since 2002, and joined the MN EPHT program on a part‐time basis in fall 2009. Previously, she worked on occupational respiratory disease studies for MDH. She has a masters degree in Science and Technology Studies from Rensselaer Polytechnic Institute and a masters degree in Environmental and Occupational Health from the University of Minnesota. She is currently a doctoral student in the Division of Epidemiology and Community Health at the University of Minnesota. Eric Hanson, MS, is an Information Technology Specialist with the Environmental Public Health Tracking program. His work is focused in Geographic Information Systems (GIS), application development, cartography, data visualization, data management and providing GIS technical assistance. He has a Masters degree in Geographic Information Systems (GIS) and Masters Minor in Public Health from the University of Minnesota. Jean Johnson, PhD, MS, is Program Director/Principal Investigator for Minnesota’s Environmental Public Health Tracking and Biomonitoring Program. Dr. Johnson received her Ph.D. and M.S. degrees from the University of Minnesota, School of Public Health in Environmental Health and has 25 years of experience working with the state of Minnesota in the environmental health field. As an environmental epidemiologist at MDH, her work has focused on special investigations of population exposure and health, including studies of chronic diseases related to air pollution and asbestos exposure, and exposure to drinking water contaminants. She is currently the Principal Investigator on an EPA grant to develop methods for measuring the public health impacts of population exposure to particulate matter (PM) in air. She is also an adjunct faculty member at the University of Minnesota School of Public Heath. Mary Jeanne Levitt, MBC, is the communications coordinator with the Minnesota Environmental Public Health Tracking program. She has a Masters in Business Communications and has worked for over 20 years in both the public and non‐profit sector in project management of research and training grants, communications and marketing strategies, focus groups and evaluations of educational needs of public health professionals. She serves on 3 institutional review boards which specialize in academic research, oncology research, and overall clinical research. Paula Lindgren, MS, received her Master of Science degree in Biostatistics from the University of Minnesota. She works for the Minnesota Department of Health as a biostatistician, and provides statistical and technical support to the MN EPHT and Biomonitoring programs for data reports, publications, web‐based portal dissemination and presentations in the Chronic Disease and Environmental Epidemiology section. Ms. Lindgren has also received training in the area of GIS for chronic disease mapping and analysis. In addition to her work for MN EPHT, she works for various programs within Chronic Disease and Environmental Epidemiology including the Asthma program, Center 66 for Occupational Health and Safety, Minnesota Cancer Surveillance System, and Cancer Control section. Barbara Scott Murdock, MA, MPH, is the Program Planner for the state Environmental Public Health Tracking and Biomonitoring (EHTB) program, responsible for leading strategic planning and communications with stakeholders and the EHTB Advisory Panel. A biologist and public health professional by education, she has over 30 years of experience in writing and editing professional publications. Recently a grants coordinator/writer for social science faculty at the University of Minnesota, she also served as the biomonitoring project manager at the Minnesota Department of Health (2001‐2003); senior research fellow in the Center for Environment & Health Policy, UMN School of Public Health (1995‐2001); director of water and health programs at the Freshwater Foundation (1991‐1992); and founding editor of the Health & Environment Digest, a peer‐reviewed publication for environmental health and management professionals in the US and Canada (1986‐1992). She holds a BS in biochemistry from the University of Chicago, an MA in zoology from Duke University, and an MPH from the University of Minnesota. Jessica Nelson, PhD, is an epidemiologist with the Minnesota Environmental Public Health Tracking and Biomonitoring Program, working primarily on design, coordination, and analysis of biomonitoring projects. Jessica received her PhD and MPH in Environmental Health from the Boston University School of Public Health where her research involved the epidemiologic analysis of biomonitoring data on perfluorochemicals. Jessica was the coordinator of the Boston Consensus Conference on Biomonitoring, a project that gathered input and recommendations on the practice and uses of biomonitoring from a group of Boston‐area lay people. Jeannette M. Sample, MPH, is an epidemiologist with the Minnesota Environmental Public Health Tracking program at the Minnesota Department of Health, working primarily with the collection and statistical analysis of public health surveillance data for EPHT. She also works on research collaborations with academic partners relating to reproductive outcomes and birth defects. Prior to joining EPHT, she was a CSTE/CDC Applied Epidemiology Fellow with the MDH Birth Defect Information System. Jeannette received her Masters degree in epidemiology and biostatistics from The George Washington University in Washington, DC. Blair Sevcik, MPH, is an epidemiologist with the Minnesota Environmental Public Health Tracking (EPHT) program at the Minnesota Department of Health, where she works on the collection and statistical analysis of public health surveillance data for EPHT. Prior to joining EPHT in January 2009, she was a student worker with the MDH Asthma Program. She received her Master of Public Health degree in epidemiology from University of Minnesota School of Public Health in December 2010. Naomi Shinoda, MSPH, is an epidemiologist at the Minnesota Department of Health, where she works on surveillance of carbon monoxide poisonings and conducts analyses 67 relating air pollution and adverse respiratory and cardiovascular health outcomes. She has international work experience, most notably from her Peace Corps service as a science and environmental educator at the Palau Environmental Quality Protection Board in the Republic of Palau. Ms. Shinoda holds a M.S.P.H. degree in epidemiology from Emory University and a B.S. in molecular biology and music from Yale University. Dave Stewart, MPH, is the Program Consultant for MDH’s Environmental Public Health Tracking Program, where he oversees content development, layout, and design for the MPH Data Portal. He develops and delivers demonstrations and trainings of the Web Portal for key data users and stakeholders. Dave has a Master’s of Public Health degree with a concentration in Health Behavior and Health Education. Before coming to MDH, Dave worked at the Suicide Prevention Resource Center, providing technical assistance to Federal Suicide Prevention Grantees on developing comprehensive suicide prevention programs. He is experienced in web development, training design, and health program planning. Dave is also working on a community level collaboration with Hennepin County. Chuck Stroebel, MSPH, is the MN EPHT Program Manager. He provides day‐to‐day direction for program activities, including: 1) development and implementation of the state network, 2) development and transport of NCDMs and metadata for the national network, and 3) collaboration and communication with key EPHT partners and stakeholders. Chuck received a Master’s of Public Health in Environmental Health Sciences from the University of North Carolina (Chapel Hill). He has over 15 years of expertise in environmental health, including areas of air quality, pesticides, climate change, risk assessment, and toxicology. Chuck also played a key role in early initiatives to build tracking capacity at the Minnesota Department of Health. Currently, he is a member of the IBIS Steering Committee (state network), the MDH ASTHO Grant Steering Committee (climate change), and the Northland Society of Toxicology. He also serves on the MN EPHT Technical and Communications Teams. Allan N. Williams, MPH, PhD, is an environmental and occupational epidemiologist in the Chronic Disease and Environmental Epidemiology Section at the Minnesota Department of Health. He is the supervisor for the MDH Center for Occupational Health and Safety, which currently includes both the state‐funded and federally‐funded Environmental Public Health Tracking and Biomonitoring programs. For over 25 years, he has worked on issues relating to environmental and occupational cancer, cancer clusters, work‐related respiratory diseases, and the surveillance and prevention of work‐related injuries among adolescents. He has served as the PI on two NIOSH R01 grants, as a co‐investigator on four other federally‐funded studies in environmental or occupational health, and is an adjunct faculty member in the University of Minnesota’s School of Public Health. He received an MA in Biology from Indiana University, an MPH in Environmental Health and Epidemiology from the University of Minnesota, and a PhD in Environmental and Occupational Health from the University of Minnesota 68 2007 ENVIRONMENTAL HEALTH TRACKING AND
BIOMONITORING STATUTE
$1,000,000 each year is for environmental health tracking and biomonitoring. Of this amount, $900,000 each year is for transfer to the Minnesota Department of Health. The base appropriation for this program for fiscal year 2010 and later is $500,000. 144.995 DEFINITIONS; ENVIRONMENTAL HEALTH TRACKING AND BIOMONITORING. (a) For purposes of sections 144.995 to 144.998, the terms in this section have the meanings given. (b) "Advisory panel" means the Environmental Health Tracking and Biomonitoring Advisory Panel established under section 144.998. (c) "Biomonitoring" means the process by which chemicals and their metabolites are identified and measured within a biospecimen. (d) "Biospecimen" means a sample of human fluid, serum, or tissue that is reasonably available as a medium to measure the presence and concentration of chemicals or their metabolites in a human body. (e) "Commissioner" means the commissioner of the Department of Health. (f) "Community" means geographically or nongeographically based populations that may participate in the biomonitoring program. A "nongeographical community" includes, but is not limited to, populations that may share a common chemical exposure through similar occupations, populations experiencing a common health outcome that may be linked to chemical exposures, populations that may experience similar chemical exposures because of comparable consumption, lifestyle, product use, and subpopulations that share ethnicity, age, or gender. (g) "Department" means the Department of Health. (h) "Designated chemicals" means those chemicals that are known to, or strongly suspected of, adversely impacting human health or development, based upon scientific, peer‐
reviewed animal, human, or in vitro studies, and baseline human exposure data, and consists of chemical families or metabolites that are included in the federal Centers for Disease Control and Prevention studies that are known collectively as the National Reports on Human Exposure to Environmental Chemicals Program and any substances specified by the commissioner after receiving recommendations under section 144.998, subdivision 3, clause (6). (i) "Environmental hazard" means a chemical or other substance for which scientific, peer‐
reviewed studies of humans, animals, or cells have demonstrated that the chemical is known or reasonably anticipated to adversely impact human health. (j) "Environmental health tracking" means collection, integration, analysis, and dissemination of data on human exposures to chemicals in the environment and on diseases potentially caused or aggravated by those chemicals. 144.996 ENVIRONMENTAL HEALTH TRACKING; BIOMONITORING. Subdivision 1. Environmental health tracking. In cooperation with the commissioner of the Pollution Control Agency, the commissioner shall establish an environmental health tracking program to: (1) coordinate data collection with the Pollution Control Agency, Department of Agriculture, University of Minnesota, and any other relevant state agency and work to promote the sharing of and access to health and environmental databases to develop an environmental health tracking system for Minnesota, consistent with applicable data practices laws; (2) facilitate the dissemination of aggregate public health tracking data to the public and researchers in accessible format; (3) develop a strategic plan that includes a mission statement, the identification of core priorities for research and epidemiologic surveillance, and the identification of internal and external stakeholders, and a work plan describing future program development and addressing issues having to do with compatibility with the Centers for Disease Control and Prevention's National 69 Environmental Public Health Tracking Program; (4) develop written data sharing agreements as needed with the Pollution Control Agency, Department of Agriculture, and other relevant state agencies and organizations, and develop additional procedures as needed to protect individual privacy; (5) organize, analyze, and interpret available data, in order to: (i) characterize statewide and localized trends and geographic patterns of population‐based measures of chronic diseases including, but not limited to, cancer, respiratory diseases, reproductive problems, birth defects, neurologic diseases, and developmental disorders; (ii) characterize statewide and localized trends and geographic patterns in the occurrence of environmental hazards and exposures; (iii) assess the feasibility of integrating disease rate data with indicators of exposure to the selected environmental hazards such as biomonitoring data, and other health and environmental data; (iv) incorporate newly collected and existing health tracking and biomonitoring data into efforts to identify communities with elevated rates of chronic disease, higher likelihood of exposure to environmental hazards, or both; (v) analyze occurrence of environmental hazards, exposures, and diseases with relation to socioeconomic status, race, and ethnicity; (vi) develop and implement targeted plans to conduct more intensive health tracking and biomonitoring among communities; and (vii) work with the Pollution Control Agency, the Department of Agriculture, and other relevant state agency personnel and organizations to develop, implement, and evaluate preventive measures to reduce elevated rates of diseases and exposures identified through activities performed under sections 144.995 to 144.998; and (6) submit a biennial report to the chairs and ranking members of the committees with jurisdiction over environment and health by January 15, beginning January 15, 2009, on the status of environmental health tracking activities and related research programs, with recommendations for a comprehensive environmental public health tracking program. Subd. 2. Biomonitoring. The commissioner shall: (1) conduct biomonitoring of communities on a voluntary basis by collecting and analyzing biospecimens, as appropriate, to assess environmental exposures to designated chemicals; (2) conduct biomonitoring of pregnant women and minors on a voluntary basis, when scientifically appropriate; (3) communicate findings to the public, and plan ensuing stages of biomonitoring and disease tracking work to further develop and refine the integrated analysis; (4) share analytical results with the advisory panel and work with the panel to interpret results, communicate findings to the public, and plan ensuing stages of biomonitoring work; and (5) submit a biennial report to the chairs and ranking members of the committees with jurisdiction over environment and health by January 15, beginning January 15, 2009, on the status of the biomonitoring program and any recommendations for improvement. Subd. 3. Health data. Data collected under the biomonitoring program are health data under section 13.3805. 144.997 BIOMONITORING PILOT PROGRAM. Subdivision 1. Pilot program. With advice from the advisory panel, and after the program guidelines in subdivision 4 are developed, the commissioner shall implement a biomonitoring pilot program. The program shall collect one biospecimen from each of the voluntary participants. The biospecimen selected must be the biospecimen that most accurately represents body concentration of the chemical of interest. Each biospecimen from the voluntary participants must be analyzed for one type or class of related chemicals. The commissioner shall determine the chemical or class of chemicals to which community members were most likely exposed. The program shall collect and assess biospecimens in accordance with the following: (1) 30 voluntary participants from each of three communities that the commissioner identifies as likely to have been exposed to a designated chemical; (2) 100 voluntary participants from each of two communities: (i) that the commissioner identifies as likely to have been exposed to arsenic; and (ii) that the commissioner identifies as likely to have been exposed to mercury; and 70 (3) 100 voluntary participants from each of two communities that the commissioner identifies as likely to have been exposed to perfluorinated chemicals, including perfluorobutanoic acid. Subd. 2. Base program. (a) By January 15, 2008, the commissioner shall submit a report on the results of the biomonitoring pilot program to the chairs and ranking members of the committees with jurisdiction over health and environment. (b) Following the conclusion of the pilot program, the commissioner shall: (1) work with the advisory panel to assess the usefulness of continuing biomonitoring among members of communities assessed during the pilot program and to identify other communities and other designated chemicals to be assessed via biomonitoring; (2) work with the advisory panel to assess the pilot program, including but not limited to the validity and accuracy of the analytical measurements and adequacy of the guidelines and protocols; (3) communicate the results of the pilot program to the public; and (4) after consideration of the findings and recommendations in clauses (1) and (2), and within the appropriations available, develop and implement a base program. Subd. 3. Participation. (a) Participation in the biomonitoring program by providing biospecimens is voluntary and requires written, informed consent. Minors may participate in the program if a written consent is signed by the minor's parent or legal guardian. The written consent must include the information required to be provided under this subdivision to all voluntary participants. (b) All participants shall be evaluated for the presence of the designated chemical of interest as a component of the biomonitoring process. Participants shall be provided with information and fact sheets about the program's activities and its findings. Individual participants shall, if requested, receive their complete results. Any results provided to participants shall be subject to the Department of Health Institutional Review Board protocols and guidelines. When either physiological or chemical data obtained from a participant indicate a significant known health risk, program staff experienced in communicating biomonitoring results shall consult with the individual and recommend follow‐up steps, as appropriate. Program administrators shall receive training in administering the program in an ethical, culturally sensitive, participatory, and community‐based manner. Subd. 4. Program guidelines. (a) The commissioner, in consultation with the advisory panel, shall develop: (1) protocols or program guidelines that address the science and practice of biomonitoring to be utilized and procedures for changing those protocols to incorporate new and more accurate or efficient technologies as they become available. The commissioner and the advisory panel shall be guided by protocols and guidelines developed by the Centers for Disease Control and Prevention and the National Biomonitoring Program; (2) guidelines for ensuring the privacy of information; informed consent; follow‐up counseling and support; and communicating findings to participants, communities, and the general public. The informed consent used for the program must meet the informed consent protocols developed by the National Institutes of Health; (3) educational and outreach materials that are culturally appropriate for dissemination to program participants and communities. Priority shall be given to the development of materials specifically designed to ensure that parents are informed about all of the benefits of breastfeeding so that the program does not result in an unjustified fear of toxins in breast milk, which might inadvertently lead parents to avoid breastfeeding. The materials shall communicate relevant scientific findings; data on the accumulation of pollutants to community health; and the required responses by local, state, and other governmental entities in regulating toxicant exposures; (4) a training program that is culturally sensitive specifically for health care providers, health educators, and other program administrators; (5) a designation process for state and private laboratories that are qualified to analyze biospecimens and report the findings; and (6) a method for informing affected communities and local governments representing those communities concerning biomonitoring activities and for receiving 71 comments from citizens concerning those activities. (b) The commissioner may enter into contractual agreements with health clinics, community‐based organizations, or experts in a particular field to perform any of the activities described under this section. 144.998 ENVIRONMENTAL HEALTH TRACKING AND BIOMONITORING ADVISORY PANEL. Subdivision 1. Creation. The commissioner shall establish the Environmental Health Tracking and Biomonitoring Advisory Panel. The commissioner shall appoint, from the panel's membership, a chair. The panel shall meet as often as it deems necessary but, at a minimum, on a quarterly basis. Members of the panel shall serve without compensation but shall be reimbursed for travel and other necessary expenses incurred through performance of their duties. Members appointed by the commissioner are appointed for a three‐year term and may be reappointed. Legislative appointees serve at the pleasure of the appointing authority. Subd. 2. Members. (a) The commissioner shall appoint eight members, none of whom may be lobbyists registered under chapter 10A, who have backgrounds or training in designing, implementing, and interpreting health tracking and biomonitoring studies or in related fields of science, including epidemiology, biostatistics, environmental health, laboratory sciences, occupational health, industrial hygiene, toxicology, and public health, including: (1) at least two scientists representative of each of the following: (i) nongovernmental organizations with a focus on environmental health, environmental justice, children's health, or on specific chronic diseases; and (ii) statewide business organizations; and (2) at least one scientist who is a representative of the University of Minnesota. (b) Two citizen panel members meeting the scientific qualifications in paragraph (a) shall be appointed, one by the speaker of the house and one by the senate majority leader. (c) In addition, one representative each shall be appointed by the commissioners of the Pollution Control Agency and the Department of Agriculture, and by the commissioner of health to represent the department's Health Promotion and Chronic Disease Division. Subd. 3. Duties. The advisory panel shall make recommendations to the commissioner and the legislature on: (1) priorities for health tracking; (2) priorities for biomonitoring that are based on sound science and practice, and that will advance the state of public health in Minnesota; (3) specific chronic diseases to study under the environmental health tracking system; (4) specific environmental hazard exposures to study under the environmental health tracking system, with the agreement of at least nine of the advisory panel members; (5) specific communities and geographic areas on which to focus environmental health tracking and biomonitoring efforts; (6) specific chemicals to study under the biomonitoring program, with the agreement of at least nine of the advisory panel members; in making these recommendations, the panel may consider the following criteria: (i) the degree of potential exposure to the public or specific subgroups, including, but not limited to, occupational; (ii) the likelihood of a chemical being a carcinogen or toxicant based on peer‐reviewed health data, the chemical structure, or the toxicology of chemically related compounds; (iii) the limits of laboratory detection for the chemical, including the ability to detect the chemical at low enough levels that could be expected in the general population; (iv) exposure or potential exposure to the public or specific subgroups; (v) the known or suspected health effects resulting from the same level of exposure based on peer‐reviewed scientific studies; (vi) the need to assess the efficacy of public health actions to reduce exposure to a chemical; (vii) the availability of a biomonitoring analytical method with adequate accuracy, precision, sensitivity, specificity, and speed; (viii) the availability of adequate biospecimen samples; or (ix) other criteria that the panel may agree to; and (7) other aspects of the design, implementation, and evaluation of the environmental health tracking and biomonitoring system, including, but not limited to: (i) identifying possible community partners 72 and sources of additional public or private funding; (ii) developing outreach and educational methods and materials; and (iii) disseminating environmental health tracking and biomonitoring findings to the public. Subd. 4. Liability. No member of the panel shall be held civilly or criminally liable for an act or omission by that person if the act or omission was in good faith and within the scope of the member's responsibilities under sections 144.995 to 144.998. INFORMATION SHARING. On or before August 1, 2007, the coStudy mmissioner of health, the Pollution Control Agency, and the University of Minnesota are requested to jointly develop and sign a memorandum of understanding declaring their intent to share new and existing environmental hazard, exposure, and health outcome data, within applicable data privacy laws, and to cooperate and communicate effectively to ensure sufficient clarity and understanding of the data by divisions and offices within both departments. The signed memorandum of understanding shall be reported to the chairs and ranking members of the senate and house of representatives committees having jurisdiction over judiciary, environment, and health and human services. Effective date: July 1, 2007 This document contains Minnesota Statutes, sections 144.995 to 144.998, as these sections were adopted in Minnesota Session Laws 2007, chapter 57, article 1, sections 143 to 146. The appropriation related to these statutes is in chapter 57, article 1, section 3, subdivision 4. The paragraph about information sharing is in chapter 57, article 1, section 169. The following is a link to chapter 57: http://ros.leg.mn/bin/getpub.php?type=law&ye
ar=2007&sn=0&num=57 73 SummariesofRecentPFCStudiesofInterest
Background on the C8 Study The C8 Science Panel and the Science Panel research program gathers and assesses information on health status and C8 exposure in the Mid‐Ohio Valley communities potentially affected by releases of C8 (PFOA) from the Washington Works plant in Parkersburg, West Virginia. The Science Panel consists of three epidemiologists chosen jointly by the parties to the legal settlement of a case between plaintiffs and DuPont regarding releases of C8 from the plant. The Science Panel members are Drs. Tony Fletcher, London School of Hygiene and Tropical Medicine; David Savitz, Brown University; and Kyle Steenland, Emory University. The Science Panel delivered two Probable Link reports dealing with cancers and diabetes, which were filed with the Wood County Court, West Virginia on Monday, April 16, 2012. The Science Panel concluded that there is a Probable Link between C8 (PFOA) and both kidney cancer and testicular cancer; and that there is no Probable Link between C8 and other cancers or adult onset diabetes. C8 Probable Link Reports Below are summaries and links to two probable link evaluation reports submitted to the Wood County Court in Parkersburg, West Virginia under the C8 Settlement. C8 Probable Link Report: Cancer On the basis of epidemiologic and other data available, the C8 Science Panel concluded that there is a probable link between exposure to C8 (also known as PFOA) and testicular cancer and kidney cancer but not any of the other cancers that were considered. Download Report: Probable Link Evaluation of Cancer Given that the C8 investigators did not supply a full abstract, MDH staff took the following section, which summarizes the report’s conclusions in the evaluation section, from the Probable Link Report. Evaluation The Science Panel concludes that there is a probable link between PFOA and both testicular and kidney cancer. The Science Panel concludes there is no probable link between PFOA and either thyroid cancer or melanoma, for which limited but insufficient evidence to support an association was found. We also conclude that there are no probable links with any of the other cancers considered. 74 In its evaluation, the Science Panel considered evidence from all published studies done by others, and from published and unpublished work done by the Science Panel. The Panel considered the weight of the evidence, looking for consistency across studies, taking into account the capability of different study designs to detect a cancer risk if such a risk exists. The Science Panel gave the most weight to studies of the Mid‐Ohio Valley community, as other studies are very small with little data of value for specific cancers, or in the case of the Danish population study, with much lower ranges of exposure than in this population. For testicular cancer, there is evidence of a positive trend in risk across exposure groups, in some analyses, with the highest exposure group in both the internal analyses of the cohort study and the geographical cancer study showing estimated relative risks ranging from 3 to over 6 comparing the highest to lowest exposure groups. On the other hand there was little or no evidence of increasing risk in analyses from the same cohort compared with the US population, and in the period after 2005, there were no new cases compared to about five expected). The high exposure group, where the higher risk was observed, comprises only six cases therefore there remains some uncertainty. The Science Panel notes that there is experimental evidence of testis cancer being increased in exposed animals. The Science Panel considers observed excesses to indicate a probable link between PFOA and testicular cancer. For kidney cancer, the worker mortality study conducted by the Science Panel showed a higher risk in the most highly exposed group compared to lower exposure groups among the workforce, but the risks were not elevated compared to the US population. In the cohort study, there was a gradient of increasing risk with increasing exposure but most strongly in the analyses that included exposure up to the time of diagnosis. When the 10 years of exposure prior to diagnosis was excluded, the association was less evident. No association was seen in the prospective analysis of cohort data, although the latter is limited by small numbers. In the geographic study some results suggested an increasing risk of kidney cancer with increasing exposure and others did not. The science panel considers that the excesses observed indicate a probable link between PFOA and kidney cancer. For thyroid cancer, positive evidence comes from the external analysis of the cohort compared to the US population. Internal analyses of the cohort study provided some suggestive of positive trends but with limited statistical support (p‐values did not indicate strong trends). Prospective analyses in the cohort were negative, although somewhat limited by small numbers. There is no animal evidence nor did the geographical study of cancer indicate positive trends linking PFOA to thyroid cancer. For melanoma, positive evidence comes from prospective internal analyses of the cohort study and from an external analysis with the US population. Without other supportive evidence, we believe the 11 positive evidence is likely to be a chance finding and do not conclude that there is a probable link between PFOA and melanoma. 75 There were no suggestions of positive trends with increasing exposure for any other cancer sites in our cohort study and only limited evidence from other studies, although for rare and fatal cancers the evidence remains inadequate to make well‐founded determination. C8 Probable Link Report: Diabetes On the basis of epidemiologic and other data available, the C8 Science Panel concluded that there is no probable link between exposure to C8 (also known as PFOA) and Type II (adult‐onset) diabetes. The summary below is from the evaluation section of the report. Download Report: Probable Link Evaluation of Diabetes Evaluation In the Science Panel’s opinion, the evidence for an association between PFOA exposure and diabetes (Type II) is insufficient to conclude that PFOA has a probable link to this disease among class members. While two mortality studies of highly exposed workers found a two‐fold excess of diabetes mortality, mortality is not the best way to study diabetes, which is usually not fatal. Mortality also involves effects of treatment as well as disease occurrence. Death certificate coding practices also may differ in different places. A recent study of 540 patients with diabetes who subsequently died found that only 39% had diabetes listed anywhere on their death certificate, and only 10% had diabetes listed as an underlying cause (McEwen et al. 2006). Furthermore, the one worker mortality study with the most thorough evaluation of past exposure to PFOA found no trend of increased risk of death from diabetes with increased exposure (estimated cumulative serum level). In a comprehensive analysis of diabetes incidence in the mid‐Ohio valley, combining community residents and exposed workers, and controlling for other risk factors known to influence diabetes, the Science Panel found no trend of increased risk of diabetes with increasing exposure to PFOA. This study included 4900 cases of diabetes, with an accurate estimate of exposure prior to disease occurrence, and could reasonably be expected to detect an elevated risk of diabetes due to PFOA if such a risk existed. The lack of any indication of increased risk with more exposure in these data does not support a probable link finding. The URL for the C8 Probable Link page is: http://www.c8sciencepanel.org/prob_link.html 76 UpdateontheRecruitmentPhaseoftheNationalChildren’sStudyPilot
As of March 1, 2012, the National Children’s Study (NCS) successfully completed enrollment for the pilot recruitment phase. The NCS reached the first goal of enrolling 6,950 families throughout the U. S., including approximately 200 families in Ramsey County, as part of the Vanguard (pilot study) phase.* Additionally, 2,850 infants nationwide and more than 50 Ramsey County NCS babies have been born.* The NCS Program Office staff at the National Institutes of Health reported preliminary findings from the Alternative Recruitment Strategies (ARS) in a report for the April 24th NCS Federal Advisory Committee Meeting held in Bethesda, Maryland. Nationwide, the 37 Study Centers identified 84,350 age‐eligible women living in geographically selected neighborhoods. Of these, 78,350 (93 percent) were eligible for pregnancy screening; 68,650 (88 percent) completed a pregnancy screener; 9,750 (14 percent) women were identified as pregnant or trying; and 6,950 (71 percent) were enrolled. Preliminary results revealed that a provider‐based recruitment strategy, in which health care providers refer women into the study, identified a higher percentage of pregnant women (87 percent) more rapidly compared to other recruitment strategies conducted during the same period, such as household‐based recruitment (51‐55 percent), or the direct outreach to the community recruitment strategy (i.e., High‐Low recruitment) (51percent). Identification of preconception (versus pregnant) women at enrollment was higher in the household‐based and direct outreach to community recruitment strategies (46‐49 percent) than in the provider‐based strategy (13 percent). Both groups of women – pregnant and preconception – are important for understanding environmental exposures that may affect the fetus and influence birth outcomes and chronic health conditions later in life. The NCS Program Office is analyzing the recruitment data to identify the best recruitment model(s) for the main study and will make a decision later this year. In the months ahead, the NCS will focus its resources and attention on connecting with the families who have joined the study and gathering participant data. The National Children’s Study plans to continue activity for all Vanguard Study participants and their communities, including Ramsey County, until the study is completed more than 20 years from now. The information gained from these families will be used to design the larger main study, which is planned to start in 2013 and has the goal of enrolling about 100,000 children from around the U.S. *All data on the Vanguard Recruitment phase are rounded in accordance with the NCS data disclosure rules. Download a PDF of the full newsletter at the Ramsey County NCS website. http://centers.nationalchildrensstudy.gov/umn/NewsEvents/newsletters/Pages/UMinn_Newslette
r_Spring2012.pdf 77