title: Methods for retrospective geocoding in population studies: the Jackson Heart Study.
abstract: The increasing use of geographic information systems (GIS) in epidemiological population studies requires careful attention to the methods employed in accomplishing geocoding and creating a GIS. Studies have provided limited details,hampering the ability to assess validity of spatial data. The purpose of this paper is to describe the multiphase geocoding methods used to retrospectively create a GIS in the Jackson Heart Study (JHS). We used baseline data from 5,302 participants enrolled in the JHS between 2000 and 2004 in a multiphase process to accomplish geocoding2 years after participant enrollment. After initial deletion of ungeocodable addresses(n=52), 96% were geocoded using ArcGIS. An interactive method using data abstraction from participant records, use of additional maps and street reference files,and verification of existence of address, yielded successful geocoding of all but 13 addresses. Overall, nearly 99% (n=5,237) of the JHS cohort was geocoded retrospectively using the multiple strategies for improving and locating geocodable addresses. Geocoding validation procedures revealed highly accurate and reliable geographic data. Using the methods and protocol developed provided a reliable spatial database that can be used for further investigation of spatial epidemiology. Baseline results were used to describe participants by select geographic indicators, including residence in urban or rural areas, as well as to validate the effectiveness of the study's sampling plan. Further, our results indicate that retrospectively developing a reliable GIS for a large, epidemiological study is feasible. This paper describes some of the challenges in retrospectively creating a GIS and provides practical tips that enhanced the success.
authors.affiliation: School of Nursing, University of Mississippi Medical Center, 2500 North State Street, Jackson, MS 39216-4505, USA. jcrobinson@son.umsmed.edu
authors.forename: Jennifer C
authors.initials: JC
authors.lastname: Robinson
authors.forename: Sharon B
authors.initials: SB
authors.lastname: Wyatt
authors.forename: DeMarc
authors.initials: D
authors.lastname: Hickson
authors.forename: Danielle
authors.initials: D
authors.lastname: Gwinn
authors.forename: Fazlay
authors.initials: F
authors.lastname: Faruque
authors.forename: Mario
authors.initials: M
authors.lastname: Sims
authors.forename: Daniel
authors.initials: D
authors.lastname: Sarpong
authors.forename: Herman A
authors.initials: HA
authors.lastname: Taylor
mesh_terms: D000328:Adult; D001741:Black or African American / Q000706:statistics & numerical data*; D000368:Aged; D000369:Aged, 80 and over; D050197:Atherosclerosis / Q000453:epidemiology; D019352:Censuses; D016208:Databases, Factual; D003710:Demography; D004812:Epidemiologic Methods; D005260:Female; D040362:Geographic Information Systems / Q000592:standards; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D008922:Mississippi / Q000453:epidemiology; D012424:Rural Population / Q000706:statistics & numerical data*; D014505:Urban Population / Q000706:statistics & numerical data*