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Estimating racial health disparities among adverse birth outcomes as deviations from the population rates
BACKGROUND: Despite significant research, the reasons for racial health disparities among adverse birth outcomes (ABO) remain largely unknown. The bulk of research into racial health disparities among ABO in the United States has concentrated on the risk of race and ethnic groups relative to the spe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7069047/ https://www.ncbi.nlm.nih.gov/pubmed/32164616 http://dx.doi.org/10.1186/s12884-020-2847-9 |
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author | Thompson, James A. Suter, Melissa A. |
author_facet | Thompson, James A. Suter, Melissa A. |
author_sort | Thompson, James A. |
collection | PubMed |
description | BACKGROUND: Despite significant research, the reasons for racial health disparities among adverse birth outcomes (ABO) remain largely unknown. The bulk of research into racial health disparities among ABO in the United States has concentrated on the risk of race and ethnic groups relative to the specific sub-population of non-Hispanic white women and their children. The objective of this study was to estimate the racial and ethnic risks among a set of neonatal and maternal health disparities while minimizing bias attributable to how the baseline risk was established. METHODS: All birth records were obtained from the United States Natality database for the years 2014 to 2017. A Bayesian modeling approach was used to estimate the risk disparity for disorders by race. The estimation of the race-specific risks used a sum-to-zero constraint for the race regression coefficients. RESULTS: Estimating racial health disparities relative to the overall population rate yielded novel results and identified perinatal health disparities for all the race groups studied. CONCLUSIONS: Unbiased risk estimates for racial disparities among ABO are now available for stimulating and initiating more complex causal modeling that can lead to understanding how racial health disparities for ABO are mediated and how they can be prevented. |
format | Online Article Text |
id | pubmed-7069047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-70690472020-03-18 Estimating racial health disparities among adverse birth outcomes as deviations from the population rates Thompson, James A. Suter, Melissa A. BMC Pregnancy Childbirth Research Article BACKGROUND: Despite significant research, the reasons for racial health disparities among adverse birth outcomes (ABO) remain largely unknown. The bulk of research into racial health disparities among ABO in the United States has concentrated on the risk of race and ethnic groups relative to the specific sub-population of non-Hispanic white women and their children. The objective of this study was to estimate the racial and ethnic risks among a set of neonatal and maternal health disparities while minimizing bias attributable to how the baseline risk was established. METHODS: All birth records were obtained from the United States Natality database for the years 2014 to 2017. A Bayesian modeling approach was used to estimate the risk disparity for disorders by race. The estimation of the race-specific risks used a sum-to-zero constraint for the race regression coefficients. RESULTS: Estimating racial health disparities relative to the overall population rate yielded novel results and identified perinatal health disparities for all the race groups studied. CONCLUSIONS: Unbiased risk estimates for racial disparities among ABO are now available for stimulating and initiating more complex causal modeling that can lead to understanding how racial health disparities for ABO are mediated and how they can be prevented. BioMed Central 2020-03-12 /pmc/articles/PMC7069047/ /pubmed/32164616 http://dx.doi.org/10.1186/s12884-020-2847-9 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Thompson, James A. Suter, Melissa A. Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title | Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title_full | Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title_fullStr | Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title_full_unstemmed | Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title_short | Estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
title_sort | estimating racial health disparities among adverse birth outcomes as deviations from the population rates |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7069047/ https://www.ncbi.nlm.nih.gov/pubmed/32164616 http://dx.doi.org/10.1186/s12884-020-2847-9 |
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