Copyright © 2007 Elsevier Ltd All rights reserved.
Evaluating options for measurement of neighborhood socioeconomic context: Evidence from a myocardial infarction case–control study
Geocoding in Cancer Research: A Review American Journal of Preventive Medicine |
Geocoding in Cancer Research: A Review American Journal of Preventive Medicine, Volume 30, Issue 2, Supplement 1, February 2006, Pages S16-S24 Gerard Rushton, Marc P. Armstrong, Josephine Gittler, Barry R. Greene, Claire E. Pavlik, Michele M. West, Dale L. Zimmerman Abstract AbstractThere is now widespread agreement that geographic identifiers (geocodes) should be assigned to cancer records, but little agreement on their form and how they should be assigned, reported, and used. This paper reviews geocoding practice in relation to major purposes and discusses methods to improve the accuracy of geocoded cancer data. Differences in geocoding methods and materials introduce errors of commission and omission into geocoded data. A common source of error comes from the practice of using digital boundary files of dubious quality to place addresses into areas of interest. Geocoded data are linked to demographic, environmental, and health services data, and each data type has unique accuracy considerations. In health services applications, the accuracy of distances computed from geocodes can differ markedly. Privacy and confidentiality issues are important in the use and release of geocoded cancer data. When masking methods are used for disclosure limitation purposes, statistical methods must be adjusted for the locational uncertainty of geocoded data. We conclude that selection of one particular type of geographic area as the geocode may unnecessarily constrain future work. Therefore, the longitude and latitude of each case is the superior basic geocode; all other geocodes of interest can be constructed from this basic identifier.Purchase PDF (130 K) |
Validation of a GIS Facilities Database: Quantification... Annals of Epidemiology |
Validation of a GIS Facilities Database: Quantification and Implications of Error Annals of Epidemiology, Volume 18, Issue 5, May 2008, Pages 371-377 Janne E. Boone, Penny Gordon-Larsen, James D. Stewart, Barry M. Popkin Abstract PurposeTo validate a commercial database of community-level physical activity facilities that can be used in future research examining associations between access to physical activity facilities and individual-level physical activity and obesity.MethodsPhysical activity facility characteristics and locations obtained from a commercial database were compared to a field census conducted in 80 census block groups within two U.S. communities. Agreement statistics, agreement of administratively defined neighborhoods, and distance between locations were used to quantify count, attribute, and positional error. ResultsThere was moderate agreement (concordance: nonurban: 0.39; urban: 0.46) of presence of any physical activity facility and poor to moderate agreement (κ range: 0.14 to 0.76) of physical activity facility type. The mean Euclidean distance between commercial database versus field census locations was 757 and 35 m in the nonurban and urban communities, respectively. However, 94%and 100%of nonurban and urban physical activity facilities, respectively, fell into the same 5-digit ZIP code, dropping to 92%and 98%in the same block group and 71%along the same street. ConclusionsOur findings suggest that the commercial database of physical activity facilities may contain appreciable error, but patterns of error suggest that built environment-health associations are likely biased downward. Purchase PDF (226 K) |
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Evaluating options for measurement of neighborhood socioeconomic context: Evidence from a myocardial infarction case–control study