Elsevier

Social Science & Medicine

Volume 67, Issue 8, October 2008, Pages 1247-1257
Social Science & Medicine

Socioeconomic domains and associations with preterm birth☆

https://doi.org/10.1016/j.socscimed.2008.06.009Get rights and content

Abstract

Neighborhood socioeconomic effects on health have been estimated using multiple variables and indices. This inconsistent estimation approach makes comparison across geographic areas challenging. In this paper, we developed indices representing specific socioeconomic domains that can be reproduced in other areas to estimate elements of the neighborhood socioeconomic environment on health outcomes, specifically preterm birth. Using year 2000 U.S. census data and principal components analysis, socioeconomic indices were developed representing a priori – defined domains of education, employment, housing, occupation, poverty and residential stability. These socioeconomic indices were subsequently used in race-stratified multilevel logistic regression models of preterm birth in eight socioeconomically distinct study areas in the U.S. Maternal residence was obtained from birth records and was geocoded to census tracts. In maternal age and education adjusted models, living in tracts with high unemployment, low education, poor housing, low proportion of managerial or professional occupation and high poverty was associated with increased odds of preterm birth for non-Hispanic white women at most sites. Among non-Hispanic black women, similar associations were noted for tract-level low education, high unemployment, low occupation, and high poverty, but the effect estimates were generally smaller than those seen for white women. Increasing amounts of residential stability were not associated with preterm birth in these analyses. We combined the domain estimates across the eight study sites to produce pooled effect estimates for the socioeconomic domains on preterm birth. The research reported here suggests that specific neighborhood-level socioeconomic features may be especially influential to health outcomes. These socioeconomic domains represent potential targets for intervention or policy efforts designed to improve maternal and child health and reduce health disparities.

Section snippets

Methods

The Multilevel Modeling of Disparities to Explain Preterm Delivery (MODE-PTD) project is a collaborative partnership of four universities and their government health department partners. The project was established to identify policy-relevant contextual factors associated with birth outcome disparities to inform state and city Maternal and Child Health officials of potentially modifiable environmental risk factors relevant for policy and program planning.

Results

The percent of PTB across the eight study sites ranged from 7.0 to 14.3% while the low birth weight percentage ranged from 4.8 to 11.9% in Montgomery County and Baltimore City, respectively (Table 1). Michigan cities (MI 16 cities) had the fewest births to women ≥ 35 years of age (8.3%) while Montgomery County had the most (31.1%). Baltimore City had the highest percent which received <12 years of education (31.7%) compared with 4.1% in Montgomery County. In Wake County 73.5% of women had >12

Discussion

Based on an extensive literature review, we identified six socioeconomic domains previously associated with health outcomes in the epidemiologic literature. We created domain-specific indices to more thoroughly capture the meaning of each respective domain. Site-specific analyses, using adjusted multilevel models, were conducted to determine the contribution of these six socioeconomic indices to the PTB differentials for black and white women across eight study areas.

We sought to first

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    ☆

    Financial and technical support for this study was provided by the NHEERL – DESE Cooperative Training in Environmental Sciences Research, CR83323601 and the Maternal and Child Health Bureau of the Health Resources and Services Administration, U.S. Department of Health and Human Services. The authors are indebted to Michael Kogan, John Park, Mary Kay Kenney, Paul Buescher, Violanda Grigorescu, Brian Castrucci and Isabelle Horon. Jennifer Culhane, Claudia Holzman, Barbara Laraia, and Patricia O'Campo are principal investigators and share equal responsibility for this project. The information in this document has been funded in party by the U.S. Environmental Protection Agency. It has been subjected to review by the National Health and Environmental Effects Research Laboratory and approved for publication. Approval does not signify that the contents reflect the views of the Agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

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