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Janet Gray, Ph.D.
Janet Gray, Ph.D.

As author of our 2008 and 2010 State of the Evidence reports, Dr. Gray drives the science behind all our work.

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Environmental Health Tracking: Spatial Epidemiology

Overview

Definition: The collection, integration, analysis, interpretation, and dissemination of data from environmental hazard monitoring, and from human exposure and health effects surveillance. (Source: CDC)

Classification: Human

To address the complexities of environmental health, health tracking attempts to create systems that provide the kinds of long-term surveillance data that can be analyzed for links between environmental factors and disease outcomes in people. This work often requires large amounts of data over long periods of time, and ongoing health tracking can fill gaps that traditional epidemiological studies face (long disease latency, early life exposures, etc.). Health tracking that relies mostly on linking different kinds of surveillance data can bolster the number of data points. (Kyle, 2006, p. 982).

Examples

Centers for Disease Control and Prevention
In 2001, Congress mandated the development of an environmental public health tracking (EPHT) program. The program is housed at the Centers for Disease Control and Prevention. The CDC currently funds 23 state and local health programs, each of which feeds its data into the national network (CDC Tracking Network website). The goals include production of an introductory report (in progress) of the public health profile of the United States from an environmental health perspective. Among the many disease and health outcomes being evaluated are environmental links to breast cancer.

The CDC EPHT network offers an important foundation for tracking these complex relationships at a national level. However, since exposures and disease rates can vary considerably across the country, there is a need for a closer analysis of some of the more geographically targeted programs that are being run at the state and community levels. These networks will likely include more detailed data that will help scientists examine more complex interactions between community profiles, environmental exposures and disease outcomes (Portier, 2011). 

California Environmental Health Screening Tool
The CalEnviroScreen allows for a zip-code level analysis of many environmental exposure levels and indicators, detailed socioeconomic and other demographic profiles, and several health outcomes. While breast cancer data are not currently entered into the database, the project as a whole indicates the possibilities offered by this approach to tracking health outcomes associated with geographically defined environmental, social and economic factors. In addition, since California does collect detailed data about cancer diagnoses, breast cancer data could be integrated into this project.

Strengths

Uses large amounts of data over long periods of time.

Limitations

Though this is starting to change, most exposure surveillance was undertaken with the goal of ensuring compliance with EPA and other regulatory mandates regarding environmental exposures, and not with the goal of associating these critical data with health outcomes (Kyle, 2006). When health outcomes were evaluated, it was often as an afterthought, with health data being collected and evaluated in order to address a particular question, not as a regular part of the general surveillance protocol (Beale, 2010).

Public health disease surveillance has focused on acute, often infectious, diseases as a model. This works well for diseases that have rapid onset and resolution, especially if symptoms are clear and unique. It is often easier to determine the causes of acute illnesses than chronic ones because acute disease onset is more rapid and can more easily be linked to an infectious agent or to environmental factors that allowed for disease transmission. It is also easier to establish the effectiveness of interventions for acute disease. However, environmental health tends to have more in common with occupational health, since both address chemical agents, diseases with long latency, multiple exposures, and institutional and economic factors that shape exposures, health and disease (Kyle, 2006, p. 980).

Data linkage alone may not provide a means to analyze exposures across the lifespan or developmental origins of health and disease, unless data are tracked over time explicitly for this purpose. In addition, data may not capture complex mixtures of exposures, or interactions of environmental factors with genetic, behavioral or social factors (Kyle, 2006, p. 982).