Abstract
Environmental exposures have profound effects on health and disease. While public repositories exist for a variety of exposures data, these are generally difficult to access, navigate, and interpret. We describe the research, development, and application of three open application programming interfaces (APIs) that support access to usable, nationwide, exposures data from three public repositories: airborne pollutant estimates from the US Environmental Protection Agency; roadway data from the US Department of Transportation; and socio-environmental exposures from the US Census Bureau’s American Community Survey. Three open APIs were successfully developed, deployed, and tested using random latitude/longitude values and time periods as input parameters. After confirming the accuracy of the data, we used the APIs to extract exposures data on 2550 participants from a cohort within the Environmental Polymorphisms Registry (EPR) at the National Institute of Environmental Health Sciences, and we successfully linked the exposure estimates with participant-level data derived from the EPR. We then conducted an exploratory, proof-of-concept analysis of the integrated data for a subset of participants with self-reported asthma and largely replicated our prior findings on the impact of select exposures and demographic factors on asthma exacerbations. Together, the three open exposures APIs provide a valuable resource, with application across environmental and public health fields.
Highlights
Environmental exposures profoundly impact health and disease, both independently and by virtue of established interactions with the genome [1]
For research and development of the Translator Exposures application programming interfaces (APIs), we focused on 2550 study participants who were successfully geocoded from a total of 4130 total participants in the Environmental Polymorphisms Registry (EPR)
We explored the impact of select demographic features and environmental exposures on asthma exacerbations, chosen again to facilitate comparison with our prior work: sex; race; history of smoking; obesity; exposure to PM2.5
Summary
Environmental exposures profoundly impact health and disease, both independently and by virtue of established ( not well understood) interactions with the genome [1]. A variety of publicly available data sources offer access to data on environmental exposures such as chemical hazards [2,3,4], water quality [5,6], air quality [7,8], and socio-environmental exposures [9,10,11] Even though these datasets are public, they are generally not obtained, navigated, or interpreted [12,13]. Many public environmental data sets are difficult to access and/or download in a form that is readily usable [14] These data sets typically require field-specific knowledge and/or a specialized skill set that most public health researchers and environmental health scientists do not possess [15,16]. Compounding these challenges is an often lack of sufficient documentation to understand and interpret the data [17]
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