TY - JOUR
T1 - Black–White Disparities in Preterm Birth
T2 - Geographic, Social, and Health Determinants
AU - Thoma, Marie E.
AU - Drew, Laura B.
AU - Hirai, Ashley H.
AU - Kim, Theresa Y.
AU - Fenelon, Andrew
AU - Shenassa, Edmond D.
N1 - Funding Information:
The Eunice Kennedy Shriver National Center for Child Health and Human Development grant number P2C-HD041041, Maryland Population Research Center, and the University of Maryland Graduate School Research and Scholarship Award provided support for this study.
Funding Information:
The Eunice Kennedy Shriver National Center for Child Health and Human Development grant number P2C-HD041041, Maryland Population Research Center, and the University of Maryland Graduate School Research and Scholarship Award provided support for this study. The study sponsor had no role in the study design, collection, analysis, and interpretation of data; writing of the manuscript; or decision to submit the report for publication. Federal employees performed this work under the employment of the U.S. federal government and did not receive any outside funding. The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Health Resources and Services Administration or HHS. No financial disclosures were reported by the authors of this paper.
Publisher Copyright:
© 2019 American Journal of Preventive Medicine
PY - 2019/11
Y1 - 2019/11
N2 - Introduction: Reducing racial/ethnic disparities in preterm birth is a priority for U.S. public health programs. The study objective was to quantify the relative contribution of geographic, sociodemographic, and health determinants to the black, non-Hispanic and white, non-Hispanic preterm birth disparity. Methods: Cross-sectional 2016 U.S. birth certificate data (analyzed in 2018–2019) were used. Black–white differences in covariate distributions and preterm birth and very preterm birth rates were examined. Decomposition methods for nonlinear outcomes based on logistic regression were used to quantify the extent to which black–white differences in covariates contributed to preterm birth and very preterm birth disparities. Results: Covariate differences between black and white women were found within each category of geographic, sociodemographic, and health characteristics. However, not all covariates contributed substantially to the disparity. Close to 38% of the preterm birth and 31% of the very preterm birth disparity could be explained by black–white covariate differences. The largest contributors to the disparity included maternal education (preterm birth, 11.3%; very preterm birth, 9.0%), marital status/paternity acknowledgment (preterm birth, 13.8%; very preterm birth, 14.7%), source of payment for delivery (preterm birth, 6.2%; very preterm birth, 3.2%), and hypertension in pregnancy (preterm birth, 9.9%; very preterm birth, 8.3%). Interpregnancy interval contributed a more sizable contribution to the disparity (preterm birth, 6.2%, very preterm birth, 6.0%) in sensitivity analyses restricted to all nonfirstborn births. Conclusions: These findings demonstrate that the known portion of the disparity in preterm birth is driven by sociodemographic and preconception/prenatal health factors. Public health programs to enhance social support and preconception care, specifically focused on hypertension, may provide an efficient approach for reducing the racial gap in preterm birth.
AB - Introduction: Reducing racial/ethnic disparities in preterm birth is a priority for U.S. public health programs. The study objective was to quantify the relative contribution of geographic, sociodemographic, and health determinants to the black, non-Hispanic and white, non-Hispanic preterm birth disparity. Methods: Cross-sectional 2016 U.S. birth certificate data (analyzed in 2018–2019) were used. Black–white differences in covariate distributions and preterm birth and very preterm birth rates were examined. Decomposition methods for nonlinear outcomes based on logistic regression were used to quantify the extent to which black–white differences in covariates contributed to preterm birth and very preterm birth disparities. Results: Covariate differences between black and white women were found within each category of geographic, sociodemographic, and health characteristics. However, not all covariates contributed substantially to the disparity. Close to 38% of the preterm birth and 31% of the very preterm birth disparity could be explained by black–white covariate differences. The largest contributors to the disparity included maternal education (preterm birth, 11.3%; very preterm birth, 9.0%), marital status/paternity acknowledgment (preterm birth, 13.8%; very preterm birth, 14.7%), source of payment for delivery (preterm birth, 6.2%; very preterm birth, 3.2%), and hypertension in pregnancy (preterm birth, 9.9%; very preterm birth, 8.3%). Interpregnancy interval contributed a more sizable contribution to the disparity (preterm birth, 6.2%, very preterm birth, 6.0%) in sensitivity analyses restricted to all nonfirstborn births. Conclusions: These findings demonstrate that the known portion of the disparity in preterm birth is driven by sociodemographic and preconception/prenatal health factors. Public health programs to enhance social support and preconception care, specifically focused on hypertension, may provide an efficient approach for reducing the racial gap in preterm birth.
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U2 - 10.1016/j.amepre.2019.07.007
DO - 10.1016/j.amepre.2019.07.007
M3 - Article
C2 - 31561920
AN - SCOPUS:85072571246
SN - 0749-3797
VL - 57
SP - 675
EP - 686
JO - American Journal of Preventive Medicine
JF - American Journal of Preventive Medicine
IS - 5
ER -
