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      Quantifying geocode location error using GIS methods


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          The Metropolitan Atlanta Congenital Defects Program (MACDP) collects maternal address information at the time of delivery for infants and fetuses with birth defects. These addresses have been geocoded by two independent agencies: (1) the Georgia Division of Public Health Office of Health Information and Policy (OHIP) and (2) a commercial vendor. Geographic information system (GIS) methods were used to quantify uncertainty in the two sets of geocodes using orthoimagery and tax parcel datasets.


          We sampled 599 infants and fetuses with birth defects delivered during 1994–2002 with maternal residence in either Fulton or Gwinnett County. Tax parcel datasets were obtained from the tax assessor's offices of Fulton and Gwinnett County. High-resolution orthoimagery for these counties was acquired from the U.S. Geological Survey. For each of the 599 addresses we attempted to locate the tax parcel corresponding to the maternal address. If the tax parcel was identified the distance and the angle between the geocode and the residence were calculated. We used simulated data to characterize the impact of geocode location error. In each county 5,000 geocodes were generated and assigned their corresponding Census 2000 tract. Each geocode was then displaced at a random angle by a random distance drawn from the distribution of observed geocode location errors. The census tract of the displaced geocode was determined. We repeated this process 5,000 times and report the percentage of geocodes that resolved into incorrect census tracts.


          Median location error was less than 100 meters for both OHIP and commercial vendor geocodes; the distribution of angles appeared uniform. Median location error was approximately 35% larger in Gwinnett (a suburban county) relative to Fulton (a county with urban and suburban areas). Location error occasionally caused the simulated geocodes to be displaced into incorrect census tracts; the median percentage of geocodes resolving into incorrect census tracts ranged between 4.5% and 5.3%, depending upon the county and geocoding agency.


          Geocode location uncertainty can be estimated using tax parcel databases in a GIS. This approach is a viable alternative to global positioning system field validation of geocodes.

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          Urban Form and Thermal Efficiency:How the Design of Cities Influences the Urban Heat Island Effect

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            Associations between self-reported and objective physical environmental factors and use of a community rail-trail.

            To effectively promote physical activIty, researchers and policy makers have advocated for greater use of environmental approaches, such as the construction of community paths and trails. However, research on the use of these facilities is limited. In this cross-sectional community study, we examined associations between self-reported and objective physical environmental variables and use of the Minuteman Bikeway (Arlington, MA) in a random sample of 413 adults. Sociodemographic and perceived environmental variables were measured with a mail survey during September 1998. Geographic information system (GIS) data were used to geocode survey respondents' homes and create three objective environmental variables: distance to the Bikeway, steep hill barrier, and a busy street barrier. In logistic models, age and female gender showed statistically significant inverse associations with Bikeway use over the previous 4-week period. Increases in self-reported (OR = 0.65) and GIS distance (OR = 0.57) were associated with decreased likelihood of Bikeway use. Absence of self-reported busy street (OR = 2.01) and GIS steep hill barriers (OR = 1.84) were associated with Bikeway use. Environmental barriers such as travel distance and hilly terrain should be considered when planning community trails. A better understanding of such factors may lead to more effective promotion of trail use. Copyright 2001 American Health Foundation and Academic Press.
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              Positional accuracy of geocoded addresses in epidemiologic research.

              Geographic information systems (GIS) offer powerful techniques for epidemiologists. Geocoding is an important step in the use of GIS in epidemiologic research, and the validity of epidemiologic studies using this methodology depends, in part, on the positional accuracy of the geocoding process. We conducted a study comparing the validity of positions geocoded with a commercially available program to positions determined by Global Positioning System (GPS) satellite receivers. Addresses (N = 200) were randomly selected from a recently completed case-control study in Western New York State. We geocoded addresses using ArcView 3.2 on the GDT Dynamap/2000 U.S. Street database. In addition, we measured the longitude and latitude of these addresses with a GPS receiver. The distance between the locations obtained by these two methods was calculated for all addresses. The distance between the geocoded point and the GPS point was within 100 m for the majority of subject addresses (79%), with only a small proportion (3%) having a distance greater than 800 m. The overall median distance between GPS points and geocoded points was 38 m (90% confidence interval [CI] = 34-46). Distances were not different for cases and controls. Urban addresses (median = 32 m; CI = 28-37) were slightly more accurate than nonurban addresses (median = 52 m; CI = 44-61). This study indicates that the suitability of geocoding for epidemiologic research depends on the level of spatial resolution required to assess exposure. Although sources of error in positional accuracy for geocoded addresses exist, geocoding of addresses is, for the most part, very accurate.

                Author and article information

                Environ Health
                Environmental Health
                BioMed Central (London )
                4 April 2007
                : 6
                : 10
                [1 ]National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
                [2 ]Battelle Centers for Public Health Research and Evaluation, Atlanta, Georgia, USA
                [3 ]Computer Sciences Corporation, Atlanta, Georgia, USA
                [4 ]Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
                Copyright © 2007 Strickland et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 17 May 2006
                : 4 April 2007

                Public health
                Public health


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