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American Journal of Epidemiology Advance Access published online on September 12, 2006
American Journal of Epidemiology, doi:10.1093/aje/kwj313
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American Journal of Epidemiology Copyright © 2006 by the Johns Hopkins Bloomberg School of Public Health All rights reserved; printed in U.S.A.
Received August 16, 2005
Accepted November 11, 2005

PRACTICE OF EPIDEMIOLOGY

Comparing Individual- and Area-based Socioeconomic Measures for the Surveillance of Health Disparities: A Multilevel Analysis of Massachusetts Births, 1989-1991

S. V. Subramanian 1 *, J. T. Chen 1, D. H. Rehkopf 1, P. D. Waterman 1, and N. Krieger 1

1 From the Department of Society, Human Development, and Health, Harvard School of Public Health, Boston, MA

* To whom correspondence should be addressed.
S. V. Subramanian, E-mail: svsubram{at}hsph.harvard.edu


  Abstract

The absence of individual-level socioeconomic information in most US health surveillance data necessitates using area-based socioeconomic measures (ABSMs) to monitor health inequalities. Using the 1989-1991 birth weight data from Massachusetts, the authors compared estimates of health disparities detected with census tract- and block group-level ABSMs pertaining to poverty and education, as well as parental education, both independently and together. In separate models, adjusted for infant's sex, mother's age, and parents' race/ethnicity, worst-off categories of census tract ABSMs and parental education had a comparable birth weight deficit of ~70 g. Similar results were observed for low birth weight (<2,500 g), with worst-off categories of census tract ABSMs and parental education having an odds ratio of ~1.37 (p < 0.001). In mutually adjusted models for birth weight and low birth weight, census tract ABSMs still detected an effect estimate nearly 50% of that detected by parental education. Additionally, census tract ABSMs detected socioeconomic gradients in birth weight among births to mothers aged less than 25 years, an age group in which educational attainment is unlikely to be completed. These results suggest that aptly chosen ABSMs can be used to monitor socioeconomic inequalities in health. The risk, if any, in the absence of individual-level socioeconomic information is a conservative estimate of socioeconomic inequalities in health.

Keywords: education; infant, low birth weight; multilevel model; poverty; socioeconomic factors; United States.
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