Socioeconomic domains and associations with preterm birth.
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.
Messer
Lynne C
LC
Duke University, Durham, NC, USA. lynne.messer@duke.edu
Vinikoor
Lisa C
LC
Laraia
Barbara A
BA
Kaufman
Jay S
JS
Eyster
Janet
J
Holzman
Claudia
C
Culhane
Jennifer
J
Elo
Irma
I
Burke
Jessica G
JG
O'Campo
Patricia
P
D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D007231:Infant, Newborn; D016015:Logistic Models; D011247:Pregnancy; D047928:Premature Birth; D012307:Risk Factors; D012923:Social Class; D012959:Socioeconomic Factors; D014481:United States