Geocoding Accuracy and the Recovery of Relationships Between Environmental Exposures and Health

Details

• Personal Author:
  Donham KJ ; Mazumdar S ; Rushton G ; Smith BJ ; Zimmerman DL
• Description:
  Background: This research develops methods for determining the effect of geocoding quality on relationships between environmental exposures and health. The likelihood of detecting an existing relationship - statistical power - between measures of environmental exposures and health depends not only on the strength of the relationship but also on the level of positional accuracy and completeness of the geocodes from which the measures of environmental exposure are made. This paper summarizes the results of simulation studies conducted to examine the impact of inaccuracies of geocoded addresses generated by three types of geocoding processes: a) addresses located on orthophoto maps, b) addresses matched to TIGER files (U.S Census or their derivative street files); and, c) addresses from E-911 geocodes (developed by local authorities for emergency dispatch purposes). Results: The simulated odds of disease using exposures modelled from the highest quality geocodes could be sufficiently recovered using other, more commonly used, geocoding processes such as TIGER and E-911; however, the strength of the odds relationship between disease exposures modelled at geocodes generally declined with decreasing geocoding accuracy. Conclusion: Although these specific results cannot be generalized to new situations, the methods used to determine the sensitivity of results can be used in new situations. Estimated measures of positional accuracy must be used in the interpretation of results of analyses that investigate relationships between health outcomes and exposures measured at residential locations. Analyses similar to those employed in this paper can be used to validate interpretation of results from empirical analyses that use geocoded locations with estimated measures of positional accuracy. [Description provided by NIOSH]
• Subjects:
  Demography Environmental Exposure Geographic Information Systems Occupational Health Photography Public Health Safety Software
• Keywords:
  Computerized Simulation Computer Models Data Processing Demographic Characteristics Environmental Exposure Geographic Information Systems Geologic Models Health Effects Humans Imaging Techniques Mathematical Models Models Proximity Detection Public Health Regression Analysis Simulation Methods Statistical Analysis Statistical Quality Control

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• ISSN:
  1476-072X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Iowa ; OSHA Region 7
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  13
• Volume:
  7
• NIOSHTIC Number:
  nn:20063116
• Citation:
  Int J Health Geogr 2008 Apr; 7:13
• Contact Point Address:
  Soumya Mazumdar, Department of Geography, University of Iowa, Iowa City, IA, USA
• Email:
  soumyamazumdar@yahoo.com
• Federal Fiscal Year:
  2008
• Performing Organization:
  University of Iowa
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  International Journal of Health Geographics
• End Date:
  20290630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:90d8f45a8d93609ab03caf736dff8b2d39ae8ec77f474470aa852fe9e2c7b9345aa876fc31213448ba37812db6dc8ff5307528b191dbde6f9e066c65a42d2aeb
• Download URL:
  https://stacks.cdc.gov/view/cdc/226238/cdc_226238_DS1.pdf
• File Type:
  [PDF - 1.96 MB ]