Analyzing exposure of school children to accidental releases of hazardous substances

Chakraborty, Jayajit

doi:10.1038/sj.jea.7500166

Cited by 7 publications

(3 citation statements)

References 22 publications

(13 reference statements)

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“…In a study conducted in Hillsborough County, Florida, a major metropolitan county, areas potentially exposed to accidental releases of hazardous substances were identified (18). The number and type of schools and school children potentially exposed to multiple releases of hazardous chemicals were assessed using GIS.…”

Section: Exposure To Disease Agents Assessing Exposurementioning

confidence: 99%

GIS and Disease

Cromley

2003

Annu. Rev. Public Health

161

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Geographic information systems (GIS) and related technologies like remote sensing are increasingly used to analyze the geography of disease, specifically the relationships between pathological factors (causative agents, vectors and hosts, people) and their geographical environments. GIS applications in the United States have described the sources and geographical distributions of disease agents, identified regions in time and space where people may be exposed to environmental and biological agents, and mapped and analyzed spatial and temporal patterns in health outcomes. Although GIS show great promise in the study of disease, their full potential will not be realized until environmental and disease surveillance systems are developed that distribute data on the geography of environmental conditions, disease agents, and health outcomes over time based on user-defined queries for user-selected geographical areas. OVERVIEWThe geography of disease, an important component of medical geography, comprises the spatial analysis of pathological factors (causative agents, vectors, hosts, reservoirs, and people) and their relationships to geographical environments (physical, cultural, and biological) (35,46). The medical geographic approach to the study of disease has not been the dominant perspective in the United States. Nevertheless, efforts to map the spatial distribution of human cases of disease and the geography of environmental risk at local, regional, and even global scales have been made again and again throughout our history (45,47,62,66). The development of geographic information systems (GIS), computer-based systems for integrating and analyzing spatially referenced data, has provided new tools for medical geographic research on disease. GIS and related technologies such as remote sensing are enabling technologies (22,38), applicable in many academic disciplines and professions and adopted in some of these well before the earliest applications in public health. Recent books describing public health applications of GIS in the United States (21, 48) and the other contributions on GIS published in this volume suggest that the diffusion of GIS into health research and public health practice has moved beyond the early innovation phase.

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Section: Exposure To Disease Agents Assessing Exposurementioning

confidence: 99%

GIS and Disease

Cromley

2003

Annu. Rev. Public Health

161

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“…Two aspects of geocoding quality are considered: positional accuracy (difference between gecoded locations and the actual school locations) and repeatability (difference between the results of different geocoding techniques). We selected school locations for this study because they represent the second most important location where children spend their time, after the home residence, and because geocoding has been widely employed in studies that have tried to determine exposure potential to air pollution at school locations (e.g., Chakraborty 2001; Green et al 2004; Ong et al 2006). We selected multiple geocoding techniques to determine the sensitivity of the results to variability in geocoding quality.…”

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confidence: 99%

Error and Bias in Determining Exposure Potential of Children at School Locations Using Proximity-Based GIS Techniques

Zandbergen

Green

2007

Environ Health Perspect

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BackgroundThe widespread availability of powerful tools in commercial geographic information system (GIS) software has made address geocoding a widely employed technique in spatial epidemiologic studies.ObjectiveThe objective of this study was to determine the effect of the positional error in geocoding on the analysis of exposure to traffic-related air pollution of children at school locations.MethodsFor a case study of Orange County, Florida, we determined the positional error of geocoding of school locations through comparisons with a parcel database and digital orthophotography. We used four different geocoding techniques for comparison to establish the repeatability of geocoding, and an analysis of proximity to major roads to determine bias and error in environmental exposure assessment.ResultsResults indicate that the positional error in geocoding of schools is very substantial: We found that the 95% root mean square error was 196 m using street centerlines, 306 m using TIGER roads, and 210 and 235 m for two commercial geocoding firms. We found bias and error in proximity analysis to major roads to be unacceptably large at distances of < 500 m. Bias and error are introduced by lack of positional accuracy and lack of repeatability of geocoding of school locations.ConclusionsThese results suggest that typical geocoding is insufficient for fine-scale analysis of school locations and more accurate alternatives need to be considered.

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“…For this type of polygon-on-polygon overlay analysis, a range of possibilities exists [ 13 ], including polygon containment (tracts which fall completely inside the buffer), centroid containment (tracts whose centroids fall inside the buffer), and simple areal interpolation (use the proportion of a tract's area that falls inside the buffer to determine the proportion of the population that resides inside the buffer, assuming uniform population distribution within each tract). All of these methods have been widely employed in environmental exposure analysis [ 2 , 11 , 25 , 26 ] and no single best technique has emerged. The application of dysametric mapping [ 27 , 28 ] in combination with areal interpolation has been suggested as a promising approach.…”

Section: Introductionmentioning

confidence: 99%

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Zandbergen

Chakraborty

2006

Int J Health Geogr

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Background: Assessments of environmental exposure and health risks that utilize Geographic Information Systems (GIS) often make simplifying assumptions when using: (a) one or more discrete buffer distances to define the spatial extent of impacted regions, and (b) aggregated demographic data at the level of census enumeration units to derive the characteristics of the potentially exposed population. A casestudy of school children in Orange County, Florida, is used to demonstrate how these limitations can be overcome by the application of cumulative distribution functions (CDFs) and individual geocoded locations. Exposure potential for 159,923 school children was determined at the childrens' home residences and at school locations by determining the distance to the nearest gasoline station, stationary air pollution source, and industrial facility listed in the Toxic Release Inventory (TRI). Errors and biases introduced by the use of discrete buffer distances and data aggregation were examined.

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Analyzing exposure of school children to accidental releases of hazardous substances

Cited by 7 publications

References 22 publications

GIS and Disease

GIS and Disease

Error and Bias in Determining Exposure Potential of Children at School Locations Using Proximity-Based GIS Techniques

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