The Use of Census Data for Determining Race and Education as SES Indicators:
A Validation Study
Abstract
PURPOSE: Little research has examined the validity of using census data to determine an individual's socio-economic status (SES), as measured by race and educational level. This study assessed the accuracy of using aggregate level data from United States Census Block Groups in determining race and education as SES indicators in a cohort of women from North Carolina.
METHODS: The study analyzed patient data from the Carolina Mammography Registry and 1990 United States Census in 21 North Carolina counties. Women
were geocoded to their census block group and their block group characteristics (surrogate measures) were validated with their self-reported values on race and education. An analysis was performed to explore whether using these surrogate measures would affect measured associations with the self-reported values.
RESULTS: Whites were accurately identified (84.8%) more consistently than Blacks (14.1%) regardless of their urban/rural status. Women without a high school diploma or equivalent were accurately identified (56.2%) more often than those with higher education levels (45.9%). Analyses using the surrogate measures were significantly different than the true values according to chi-square statistics.
CONCLUSIONS: Use of census data to derive SES indicators tends to be more accurate for the majority than the minority population. Researchers must be sensitive to the ecologic fallacy when using aggregate level data such as the census to determine individual level characteristics.
Keywords: Census Data, Education, Race, Socioeconomic Status, Ecologic Fallacy, Validation Study
Abbreviations: CMR = Carolina Mammography Registry, GIS = Geographic Information System, ITRE = Institute for Transportation Research and Education, MSA = Metropolitan Statistical Area, SES = socio-economic status, STF 1-A = Summary Tape File 1-A, STF 3-A = Summary Tape File 3-A, TIGER = Topologically Integrated Geographic Encoding and Referencing data format, TIMS = Transportation Information Management System
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PII: S1047-2797(00)00205-2
© 2001 Elsevier Science Inc. All rights reserved.
