Bishop-Royse J, Lange-Maia B, Murray L, Shah RC, DeMaio F. Structural racism, socio-economic marginalization, and infant mortality.
Public Health 2020;
190:55-61. [PMID:
33348089 DOI:
10.1016/j.puhe.2020.10.027]
[Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Revised: 10/02/2020] [Accepted: 10/29/2020] [Indexed: 02/05/2023]
Abstract
OBJECTIVES
We examine associations between infant mortality rates (IMRs) and measures of structural racism and socio-economic marginalization in Chicago, Illinois. Our purpose was to determine whether the Index of Concentration at the Extremes (ICE) was significantly related to community-level IMRs.
STUDY DESIGN
We use a cross-sectional ecological public health design to examine community-level factors related to IMRs in Chicago neighborhoods.
METHODS
We use data from the Chicago Department of Public Health and the American Community Survey to examine IMR inequities during the period 2012-2016. Calculations of the ICE for race and income were undertaken. In addition, we calculated racialized socio-economic status, which is the concentration of affluent Whites relative to poor Blacks in a community area. We present these ICE measures, as well as hardship, percent of births with inadequate prenatal care (PNC), and the percent of single-parent households as quintiles so that we can compare neighborhoods with the most disadvantage with neighborhoods with the least. Negative binomial regression was used to determine whether the ICE measures were independently related to community IMRs, net of hardship scores, PNC, and single-parent households.
RESULTS
Spearman correlation results indicate significant associations in Chicago communities between measures of racial segregation and economic marginalization and IMRs. Community areas with the lowest ICERace scores (those with the largest concentrations of Black residents, compared with White) had IMRs that were 3.63 times higher than those communities with the largest concentrations of White residents. Most associations between community IMRS and measures of structural racism and socioeconomic marginalization are accounted for in fully adjusted negative binomial regression models. Only ICERace remained significantly related to IMRs.
CONCLUSIONS
We show that structural racism as represented by the ICE is independently related to IMRs in Chicago; community areas with the largest concentrations of Blacks residents compared with Whites are those with the highest IMRs. This relationship persists even after controlling for socio-economic marginalization, hardship, household composition/family support, and healthcare access. Interventions to improve birth outcomes must address structural determinants of health inequities.
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