The environment is a major determinant of health.
Locally, there are clear indications that the Pittsburgh region, once famous
for having “cleaned up its act” as one of the most polluted places in the
country, has been backsliding over the last decade or two in terms of certain
aspects of environmental health, including, for example, air quality and urban
sprawl. Despite these indications, certain key questions remain difficult to
answer. For example, what is the current local burden of disease related to
various environmental factors? How does this burden of disease in the
Before we can begin to try to answer these
questions, or even to know whether they are in fact answerable, it is first
advisable to examine the types and quality of existing environmental health
data. If available, such data would certainly be useful, for example, in helping
make decisions related to personal actions, planning research agendas, program
design, policy-making, and funding strategies. This report lays the groundwork
for an understanding of the data and data gaps related to local environmental
health, so as to allow such decision-making to be better informed by the
available data, as well as to prioritize areas where efforts to gather better
data are most needed. Our goal with this report in its present form is to
create the foundation for a consolidated information inventory and data needs
assessment that will serve the following purposes for environmental health
researchers, citizens, funders and policy makers in
· Provide an overview of several areas of environmental health information in one place, along with an understanding of their pertinence and interconnectedness
· Illustrate the large volume of information that is already available, and where much of it can be obtained, to lessen information seeking time and duplication of effort
· Describe some of the major strengths and weaknesses of existing information
· Outline some of the major gaps in information, so that we collectively know where the greatest efforts will be needed
· Highlight related data compilation, linkage and analysis endeavors, so that organizations may share resources and avoid duplication of efforts
· Provide an understanding of some of the political/systemic barriers to furthering the environmental health data base, so that future endeavors take such barriers into consideration
· Illustrate the “real life” connection to environmental health issues via case studies of successful and unsuccessful attempts to obtain and utilize environmental health data for specific purposes
Several efforts are underway to strengthen local environmental health information. These include the following:
Data inventory and quality assessments: For example, the statewide
Pennsylvania Consortium for Interdisciplinary Environmental Policy (PCIEP),
which includes several
· Indicators development: At least three groups--the Allegheny County Health Department, Sustainable Pittsburgh, and the Southwestern Pennsylvania Indicators Consortium--are looking at county or regional indicators that focus specifically on environmental health, or at broader sets of indicators including environmental health as one topic area. Over several years, these groups have already gathered a great deal of public and expert input that can provide some guidance in determining which data gaps to focus upon. A great deal of linkage still remains to be done in this area; and while these more general indicators are excellent summary tools for tracking general progress and motivating legislators, more specific data may be required to answer important environmental health questions.
· Technological tools: Given Pittsburgh’s vast amount of technological expertise and educational resources, it’s not surprising that several endeavors are already creating tools to synthesize, warehouse, analyze and present information to various potential audiences. This includes endeavors coordinated by university groups (SOVAT and Info-Pitt), a private-sector company (Community Information Commons), a government agency (HS.net) and small non-profits (the Community Information System). Much of the technology is already exists, some of which is among the most cutting-edge in the world—however, a multitude of data sharing concerns must be addressed before these tools can truly be put to the test.
· Environmental health tracking and network development: The Pennsylvania Department of Health, with funding from the U.S. Centers for Disease Control, is exploring statewide issues related to data availability—some of this is being linked with PCIEP, described above.
While there are already some common collaborating agencies across the above projects, great opportunity exists for the interdisciplinary linkages necessary for improving the state of regional environmental health data.
In a full discussion of environmental health, we cannot afford to ignore the driving forces behind pollution-related health risks, namely (1) consumer demand for the goods or services that a polluting industrial activity produces or allows, along with (2), polluting activities by individual persons that lead to directly to environmental pollution. Ultimately, it is we, through our own individual and collective demands and actions, who are the causes of the creation and release of toxins into the environment. The physical, psychic, and economic complexities of modern life and its products make it increasingly difficult to fully understand the consequences of our daily actions. And yet, if we ignore the connections between our own lives and deeds and the rest of the world, we are likely to act in ways that are wasteful, destructive, and dangerous. The science of environmental health not only helps us to understand how our environments influence our health, but also how our actions influence the world around us. In regard to the latter, environmental health can teach us the implications of how we spend our time, get around, build places, and make things. It can demonstrate the consequences of what we buy, breathe, eat, drink, wear, use, and throw away. An environmental health approach can lead us to examine our everyday lives anew, and point us towards ways of living that maximize good, both for ourselves and the for rest of the planet.
To reduce environmental impact through our power as voters and consumers we must have sufficient information on which to base our decisions, and we must also have feasible alternatives. It should not be necessary, for example, to buy one’s own windmill and “go off the grid” in order to use renewable energy, or to have a Ph.D. in order to eat the right thing for lunch. There is a need for simple, direct communication of information about the ways that our actions and purchases affect our health and environment. This information, of course, depends on adequate data. We describe examples of data tools related to consumer demand and polluting activities in two categories: (1) tools for person-based analysis (ecological footprints), and (2), tools for product-based analysis (household products database, life-cycle analysis, and product labeling).
This includes data on pollution at the release point of large stationary sources (e.g., coal-fired power plants), smaller and more diffuse “area sources” (e.g., dry cleaners), and mobile sources (e.g., motorized vehicles). The most comprehensive set of information on data for pollution released from larger stationary sources remains the Environmental Protection Agency’s Toxic Release Inventory (TRI), compiled at the federal level. It includes individual sites’ reported emissions into various environmental media including land, water and air. While tools have very recently been developed to assist with querying, presentation and linkage of the TRI’s impressive volume of information (e.g., the U.S. National Library of Medicine’s TOXMAP and Environmental Defense’s Scorecard), TRI data still have a number of limitations. Some of the more serious are that the TRI data are self-reported by companies and often cannot be checked, that the data generally rely upon estimation methodologies rather than actual monitoring data, and that the data exclude many industries and smaller stationary and mobile sources (whose combined emissions may represent a significant aggregate health risk).
This includes data on the levels of pollutants in “the environment around us”—air, water and land—regardless of its source, and represents potential human exposure. Following are a few highlights on environmental monitoring data for each of the three media:
Ambient air monitoring: As one
interviewee suggested for particulate matter, a harmful pollutant found in
diesel exhaust and coal-fired power plant emissions, “More may be known about
particulate matter in
Land monitoring: Brownfields, which
include sites heavily polluted by former industrial issues, are a significant
Water monitoring: This includes data on potentially
hazardous pollution in rivers and streams, municipal drinking water, wells and
Data commonly used for exposure modeling include release data (e.g., TRI), ambient environmental monitoring data (e.g. air quality), estimates of contaminated food intake obtained by population-based dietary surveys such as the National Health and Nutrition Examination Survey (NHANES), activity surveys such as the National Human Activity Pattern Survey (NHAPS), biomonitoring measurements taken from groups of people with known exposures, and epidemiologic studies.
the direct measurement of people's exposure to toxic substances in the
environment by measuring the substances or their metabolites in human
specimens, such as blood or urine. Biomonitoring
measurements are the most health-relevant assessments of exposure because they
indicate the amount of chemicals that actually get into people (from all
environmental sources (e.g., air, soil, water, dust, food) combined. The CDC
Second National Report on Human Exposure to Environmental Chemicals Second
National Report presented biomonitoring exposure data
for 116 environmental chemicals in the civilian
The Allegheny County Childhood Lead Poisoning
Prevention Program (CLPPP) conducts blood lead screening for children ages 0-6
door-to-door in high-risk communities and at fixed-site locations such as day
care facilities, head start programs, and health fairs.
Although it might seem that it would be easier to obtain health information about a group of people living in a certain place than to obtain environmental information about that place, this is not always the case. Some environmental data, as for example the levels of certain chemicals in the air, can be monitored mechanically, whether continuously or at periodic intervals. This is not possible for health outcomes, which must be reported or detected in order to be known. If people get sick with a certain disease, but do not either seek health care (or die), the disease will not appear on any information “radar screen”. Personal health data, unlike environmental data, also often involves issues of privacy and confidentiality.
Common secondary sources of health information include hospital, emergency department, and ambulatory care records, school nurse records, health insurance company records, medication sales records, birth and death certificates. It is also possible to conduct surveys, screenings, or studies that actively detect risk, exposure, sub-clinical disease, or clinical disease. These surveys, screenings, and studies are sometimes the only way that the incidence and prevalence of an exposure or health outcome can be known in a population. Surveys, although expensive in terms of the required time, staff, and money involved, are especially important to understanding disease in medically underserved populations, such as low-income and minority groups, whose disease profiles may be underrepresented in data from health facilities.
Registry data are very helpful in elucidating
relationships between environmental factors and health outcomes. Cancer
registries are the prototypical health registry, and in many parts of the
country cancer is still the only chronic disease health outcome that has a
registry available for examining its relationship with environmental factors.
Other than the beginnings of a system for tracking asthma,
Health-related data on the built environment encompasses a broad range of information traditionally collected by groups such as economic development organizations, urban planners, and transportation analysts. Findings for this section fall under four areas:
· Residential characteristics: Recent research suggests that urban sprawl may be linked to poor health outcomes due to people walking less, weighing more and having greater rates of hypertension. A recent Brookings Institution Study (“Back to Prosperity”) utilized various data sets describing the degree of sprawl in our region—data on factors such as how land is being used (e.g., urban, tree-covered), and how quickly urban areas are growing, are available from several sources including the Census Bureau and Landsat satellite imagery. The Community Information System collaboration has already compiled data on locations of vacant properties; and given the availability of resources, may eventually add various other data items related to neighborhood appearance and safety. Because walking and bicycling engage people in exercise and decrease vehicle pollution, data on walkability and bikeability are vital to the environmental health community. While aggregate data on cycling and pedestrian fatalities are available for larger geographic areas (e.g., via the national Fatality Analysis Reporting System), the local group Ghost Bike endeavors to assemble data for smaller-area analysis. Data on non-fatal injuries also poses a challenge.
Businesses and other amenities: Data on locations of
businesses and amenities help to measure how much people are likely to exercise
(i.e., walk or bicycle) rather than take a car. As illustrated by at
least two studies, data on grocery stores can be used to analyze access to
nutritious foods. The City of
· Transportation: Traffic counts are pertinent to environmental health due to the effects of mobile emissions and time spent sitting in cars. Several agencies collect data on traffic counts and modes of transportation, including the Pennsylvania Department of Transportation, the U.S. Census Bureau, and the Southwestern PA Commission (SPC). Data sets are often for extended timeframes and don’t often distinguish between different types of vehicles, but SPC’s regional travel survey offers a significant amount of detail for at least a sample of regional residents. Comprehensive sources of data on bicycling and trail use are still limited because they usually require observational or survey methods.
This report brings
together in one place an examination of the state of information related to
environmental health in the