Associations Between Historically Redlined Districts and Racial Disparities in Current Obstetric Outcomes | Health Disparities | JAMA Network Open | JAMA Network
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Figure 1.  Historic Redlining Map of the City of Rochester
Historic Redlining Map of the City of Rochester

Source: Mapping Inequity initiative, as licensed under a Creative Commons Attribution.14 Red areas indicate most “Hazardous,” while green areas are “Best.”

Figure 2.  Incidence of Any Preterm Birth in the Modern Zip Code Regions Overlaid on the Historic Redlining Map
Incidence of Any Preterm Birth in the Modern Zip Code Regions Overlaid on the Historic Redlining Map

Darker red represents the highest preterm birth rates and yellow represents the lowest preterm birth rates.

Table 1.  Preterm Birth Incidence Organized by Historic HOLC Designation
Preterm Birth Incidence Organized by Historic HOLC Designation
Table 2.  Progressive Multivariable Regression Analysis of All Preterm Births in Historically Redlined Regions Compared With the “Best” or “Still Desirable” Historic Regions
Progressive Multivariable Regression Analysis of All Preterm Births in Historically Redlined Regions Compared With the “Best” or “Still Desirable” Historic Regions
Table 3.  Progressive Multivariable Regression Analysis of Periviable Birth in Historically Redlined Regions Compared With the “Best” or “Still Desirable” Historic Regions
Progressive Multivariable Regression Analysis of Periviable Birth in Historically Redlined Regions Compared With the “Best” or “Still Desirable” Historic Regions
1.
Kim  D, Saada  A.  The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review.   Int J Environ Res Public Health. 2013;10(6):2296-2335. doi:10.3390/ijerph10062296 PubMedGoogle ScholarCrossref
2.
Lorenz  JM, Ananth  CV, Polin  RA, D’Alton  ME.  Infant mortality in the United States.   J Perinatol. 2016;36(10):797-801. doi:10.1038/jp.2016.63 PubMedGoogle ScholarCrossref
3.
Tangel  V, White  RS, Nachamie  AS, Pick  JS.  Racial and ethnic disparities in maternal outcomes and the disadvantage of peripartum Black women: a multistate analysis, 2007-2014.   Am J Perinatol. 2019;36(8):835-848. doi:10.1055/s-0038-1675207 PubMedGoogle Scholar
4.
Ratnasiri  AWG, Parry  SS, Arief  VN,  et al.  Temporal trends, patterns, and predictors of preterm birth in California from 2007 to 2016, based on the obstetric estimate of gestational age.   Matern Health Neonatol Perinatol. 2018;4:25. doi:10.1186/s40748-018-0094-0 PubMedGoogle ScholarCrossref
5.
Eichelberger  KY, Doll  K, Ekpo  GE, Zerden  ML.  Black lives matter: claiming a space for evidence-based outrage in obstetrics and gynecology.   Am J Public Health. 2016;106(10):1771-1772. doi:10.2105/AJPH.2016.303313 PubMedGoogle ScholarCrossref
6.
Leonard  SA, Main  EK, Scott  KA, Profit  J, Carmichael  SL.  Racial and ethnic disparities in severe maternal morbidity prevalence and trends.   Ann Epidemiol. 2019;33:30-36. doi:10.1016/j.annepidem.2019.02.007 PubMedGoogle ScholarCrossref
7.
Petersen  EE, Davis  NL, Goodman  D,  et al.  Racial/ethnic disparities in pregnancy-related deaths—United States, 2007-2016.   MMWR Morb Mortal Wkly Rep. 2019;68(35):762-765. doi:10.15585/mmwr.mm6835a3PubMedGoogle ScholarCrossref
8.
Grobman  WA, Parker  CB, Willinger  M,  et al; Eunice Kennedy Shriver National Institute of Child Health and Human Development Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) Network.  Racial disparities in adverse pregnancy outcomes and psychosocial stress.   Obstet Gynecol. 2018;131(2):328-335. doi:10.1097/AOG.0000000000002441 PubMedGoogle ScholarCrossref
9.
Bekkar  B, Pacheco  S, Basu  R, DeNicola  N.  Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the US: a systematic review.   JAMA Netw Open. 2020;3(6):e208243. doi:10.1001/jamanetworkopen.2020.8243 PubMedGoogle Scholar
10.
Premkumar  A, Henry  DE, Moghadassi  M, Nakagawa  S, Norton  ME.  The interaction between maternal race/ethnicity and chronic hypertension on preterm birth.   Am J Obstet Gynecol. 2016;215(6):787.e1-787.e8. doi:10.1016/j.ajog.2016.08.019PubMedGoogle ScholarCrossref
11.
Holdt Somer  SJ, Sinkey  RG, Bryant  AS.  Epidemiology of racial/ethnic disparities in severe maternal morbidity and mortality.   Semin Perinatol. 2017;41(5):258-265. doi:10.1053/j.semperi.2017.04.001 PubMedGoogle ScholarCrossref
12.
Hernandez  DJ, ed.  Children of Immigrants: Health, Adjustment, and Public Assistance. National Academies Press; 1999.
13.
Bailey  ZD, Krieger  N, Agénor  M, Graves  J, Linos  N, Bassett  MT.  Structural racism and health inequities in the USA: evidence and interventions.   Lancet. 2017;389(10077):1453-1463. doi:10.1016/S0140-6736(17)30569-X PubMedGoogle ScholarCrossref
14.
Mapping Inequity: Redlining in New Deal America. Rochester, NY. Accessed July 17, 2019. https://dsl.richmond.edu/panorama/redlining/#loc=12/43.188/-77.718&city=rochester-ny
15.
Rothstein  R.  The Color of Law: A Forgotten History of How Our Government Segregated America. 1st ed. Liveright Publishing Corporation; 2017.
16.
Gee  GC.  A multilevel analysis of the relationship between institutional and individual racial discrimination and health status.   Am J Public Health. 2008;98(9)(suppl):S48-S56. doi:10.2105/AJPH.98.Supplement_1.S48 PubMedGoogle Scholar
17.
McClure  E, Feinstein  L, Cordoba  E,  et al.  The legacy of redlining in the effect of foreclosures on Detroit residents’ self-rated health.   Health Place. 2019;55:9-19. doi:10.1016/j.healthplace.2018.10.004 PubMedGoogle ScholarCrossref
18.
National Historical Geographic Information System. download U.S Census data tables & mapping files. Accessed September 1, 2021. https://www.nhgis.org/
19.
Nardone  AL, Casey  JA, Rudolph  KE, Karasek  D, Mujahid  M, Morello-Frosch  R.  Associations between historical redlining and birth outcomes from 2006 through 2015 in California.   PLoS One. 2020;15(8):e0237241. doi:10.1371/journal.pone.0237241 PubMedGoogle Scholar
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    Original Investigation
    Obstetrics and Gynecology
    September 30, 2021

    Associations Between Historically Redlined Districts and Racial Disparities in Current Obstetric Outcomes

    Author Affiliations
    • 1Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, University of Rochester Medical Center, Rochester, New York
    • 2Department of Biomedical Engineering, University of Rochester, Rochester, New York
    • 3Department of Public Health Sciences, University of Rochester Medical Center, Rochester, New York
    JAMA Netw Open. 2021;4(9):e2126707. doi:10.1001/jamanetworkopen.2021.26707
    Key Points

    Question  Is the legacy of structural racism in the housing market associated with disparate outcomes in a contemporary obstetric cohort?

    Findings  In this cohort study including 64 804 live births in 17 zip codes, historically redlined zip codes were associated with increased risk of preterm birth and periviable birth.

    Meaning  These findings suggest that historic discriminatory policies remain associated with poor obstetrical outcomes, suggesting intergenerational discrimination and disinvestment continue to have a role in modern health disparities.

    Abstract

    Importance  Despite much higher health care expenditure than comparable countries, striking racial and ethnic disparities exist in obstetric outcomes in the United States. A multifaceted exploration of the factors influencing these disparities, including the legacy of structural racism, is important to improve health outcomes for all.

    Objective  To characterize the association of the historic racially discriminatory home loan practice of redlining with disparities in modern obstetric outcomes.

    Design, Setting, and Participants  In this retrospective cohort study of a 9-county birth certificate database in the Finger Lakes region of New York state from 2005 to 2018, modern obstetric outcomes were matched with regions classified by the federal government for mortgage loan servicing based on racially discriminatory criteria from the 1940 Home Owners’ Loan Corporation map (HOLC; also known as the redline map). Patients with a live birth recorded in the data system with a recorded home zip code within the historic HOLC categories were included. Data were analyzed from July to December 2019.

    Exposure  Regions previously categorized by historic, racially discriminatory criteria.

    Main Outcomes and Measures  Each HOLC area was analyzed for the primary outcome of preterm birth and secondary outcomes of obstetric and medical complications, with logistic regression to address regional and patient-level covariates.

    Results  From 2005 until 2018, there were 64 804 live births within the 15 zip codes overlaying historic HOLC regions. Prevalence of preterm birth increased with decreasing HOLC categories, from the lowest overall preterm birth rate of 217 of 2873 births (7.55%) in the zip code historically defined as “Best” or “Still Desirable” and the highest overall preterm birth rate of 427 of 3449 births (12.38%) in the zip code historically defined as “Hazardous.” These associations with preterm birth remained significant in logistic regression controlling for poverty levels and educational attainment (adjusted odds ratio, 1.46; 95% CI, 1.08-1.97) and parental race (adjusted odds ratio, 1.38; 95% CI, 1.25-1.53).

    Conclusions and Relevance  In this cohort study, the linkage of historic and modern community data sets with an obstetric data set offered the opportunity to characterize modern obstetric disparities associated with a system of historic inequity. The persistence of these findings after correcting for contemporary community socioeconomic characteristics suggest potential influences of a system of profound structural inequity that ripple forward in time, with impacts that extend beyond measurable socioeconomic inequity.

    Introduction

    The US has higher infant and maternal mortality rates than nearly any other Organization for Economic Cooperation and Development nation despite also having the largest health expenditures.1,2 Racial and ethnic disparities in outcomes are well documented, with Black women carrying a disproportionate burden of increased morbidity and mortality due to a range of obstetric outcomes.3-6 These disparities are persistent across regions in the US; when statewide pregnancy-related mortality rate is used to group states into low, medium, and high pregnancy-related mortality groups, the risk for Black women is persistently around 3-fold higher than for White women in each risk strata. Additionally, risk of death in pregnancy is higher for Black women with at least a college degree than for White women who have not completed a high school diploma.7

    These disparities remain pronounced across the spectrum of obstetric experiences. Preterm birth demonstrates particularly prominent racial and ethnic disparities in the US, with non-Hispanic Black women experiencing a preterm birth rate at least 50% higher than non-Hispanic White women.8

    Increasing focus of the medical community on health care disparities has revealed a wide array of contributions to the inequity of health outcomes, ranging from the physical environment to socioeconomic factors, individual health behaviors, stress, and genetic factors.8-11 The cumulative effect of structural racism is one driver of the disproportionate negative outcomes faced by Black women.3 This is the factor that likely gives rise to the so-called immigrant paradox, in which immigrant women have better health outcomes on arrival to the US than after multiple years of living within the US.12 The legacy of structural racism is extensive in the US13; one historic vehicle of discrimination and disinvestment was the practice of redlining: a formal practice of the federal government’s Home Owners’ Loan Corporation (HOLC) beginning in the 1930s to delineate areas where mortgages could be insured based on overtly racially discriminatory criteria.14

    From the 1930s into the 1940s, the federal government created thousands of area descriptions for cities across the US. First created by the HOLC, redline policies were then adopted by the Federal Housing Administration and the Department of Veterans Affairs, all of which ostensibly used these classifications to guide where it was financially “safe” to issue mortgages, although “safety” frequently represented a categorization for the racial composition of neighborhoods, with predominantly White neighborhoods categorized in lowest risk categories (ie, grades A and B).15 This structure of disinvestment, which formally stretched forward into the 1960s, has far reaching impacts. Owing to a range of sequelae of community disinvestment, as well as the critical role of home ownership in intergenerational wealth-building, the legacy of historic redline racial discrimination correlates with modern social and health inequities.3,14-17 We conducted this study to evaluate our hypothesis that the legacy of racial discrimination measured by historic redlining is associated with modern obstetric outcome disparities.

    Methods

    This cohort study was approved by the University of Rochester Research Subjects Review Board, including a waiver of informed consent consistent with institutional review board approval for use of deidentified data. This study is reported following the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.

    Study Design

    We performed a retrospective cohort study of patients with live births from 2005 until 2018 in the Finger Lakes Region perinatal and obstetric data system—a New York State Department of Health electronic birth certificate database. This includes the city of Rochester, New York, in Monroe county, plus 8 counties south and east of Monroe county, known as the Finger Lakes region.

    Outcome and Covariate Data

    Deidentified data, with 5-digit zip codes retained, from the perinatal and obstetric data system were tabulated for obstetric outcomes and patient demographic characteristics, including race. In the obstetric data system, patient race is collected from self-identification on the data collection form filled out by the patient at the time of the delivery hospitalization.

    Zip codes with at least 100 deliveries during the study period were stratified into cohorts, and frequencies of patient-level obstetric outcomes were calculated for each. Zip codes with fewer than 100 deliveries over the study period were excluded to avoid introducing confounding from small groups.

    Preterm birth is defined as any gestation length less than 37 weeks. We also included extreme preterm birth (ie, births <28 weeks) and periviable birth (births at 22-25 weeks), as these births impart the greatest risks for neonatal morbidity and mortality and are thus of particular focus. Secondary outcomes of interest included maternal diagnoses of pregnancy-related hypertension, severe depression, and substance use and additional pregnancy-related outcomes, including neonatal intensive care unit admission, 5-minute APGAR score less than 7, and exclusive breastfeeding in the immediate postpartum period.

    The data set then was merged with publicly available community data from the US Census Bureau. Zip code cohorts were linked to income, poverty, and educational attainment data, as described by the US Census Bureau based on the 2017 American Community Survey.18 Median gross income of community members, percentage of community members with a high school diploma, and percentage of community members living below the US poverty level were tabulated for each zip code.

    Defining Exposure

    We categorized each zip code in our birth registry based on the 1940 HOLC map of the city of Rochester14 to classify them according to the classification by the federal government as A, “Best”; B “Still Desirable”; C, “Definitely Declining”; and D, “Hazardous” for mortgage loan servicing based on racially discriminatory criteria (Figure 1; eFigure 1 in the Supplement). Assignment to category was based on direct visual overlay with the modern zip code regions to correlate these zip codes with either a single historic designation or potentially 2 or more historic designations because modern zip codes geography differs from these historic regions. Zip code cohorts were separately included in the statistical analysis if they contained 3 or more historic designations to avoid confounding from modern zip codes that contained many types of historic designations.

    Statistical Analysis

    Our unit of analysis was live births clustered within zip codes that were coded by HOLC grades. We used logistic regression with a random effect for each zip code and clustered SEs at the zip code level to account for correlation within zip code. We then adjusted separately for community economic factors (poverty levels, categorized as <10%, 10 to <20%, or ≥20% of community members living at or below the federal poverty level, and educational attainment, categorized as <75%, 75% to <85%, or ≥85% of community members graduated from high school) and maternal and paternal race.

    Stata statistical software version 16.0 (StataCorp) was used to collapse the obstetric data set into zip code cohorts to describe geographic distribution of outcomes as well as to perform the statistical analyses. Graphic representations of the distributions of obstetric, and community socioeconomic data were generated in ArcGISPro version 2.5.0 (Esri). P values were 2-sided, and statistical significance was set at P = .05. Data were analyzed from July to December 2019.

    Results

    From 2005 until 2018, the birth data system contained detailed information for 210 984 live births. A total of 199 088 live births were eligible for inclusion as being associated with a zip code containing more than 100 deliveries in the study period with resulting 120 zip code cohorts.

    Of these births, there were 64 804 within the 15 zip codes that were redlined and had HOLC grades in Rochester, New York. One contemporary zip code overlapped with the historic D “Hazardous” designation, and 1 contemporary zip code overlapped with historic regions characterized as A “Best” or B “Still Desirable.” Ten zip codes were distributed in 1 or 2 categories between these extremes, and 3 contained 3 or more of the historic designations and thus were tabulated but not included in the statistical analysis.

    Prevalence of preterm birth increased with worse HOLC grades, with the lowest overall preterm birth rate of 217 of 2873 births (7.55%) in the zip code historically defined as “Best” or “Still Desirable” and the highest overall preterm birth rate of 427 of 3449 births (12.38%) in the zip code historically defined as “Hazardous.” Overall preterm birth, extreme preterm birth, and periviable birth by HOLC designation are presented in Table 1. The rate of periviable birth was 3-fold higher in the “Hazardous” neighborhood than the “Best” or “Still Desirable” neighborhood (26 births [0.75%] vs 7 births [0.24%]) (eFigure 3 and eFigure 4 in the Supplement). Figure 2 depicts concentrations of preterm birth among modern zip code regions and eFigure 2 in the Supplement depicts concentrations of income, poverty, and educational attainment across modern zip code regions. Adjusting for patient-level birth data and with “Best” HOLC designation as the reference category, there was a graded increase in preterm birth with worsening HOLC designation, with adjusted odds ratios of 1.19 (95% CI, 1.08-1.31) for “Definitely Declining” (P = .001) to 1.38 (95% CI, 1.25-1.53) for “Hazardous” (P < 001) (Table 2).

    Geographic disparities in modern preterm birth rates across the entire region remained statistically significant in multivariable regression controlling for community-level poverty levels and educational attainment and patient-level maternal race and paternal race in rates of all preterm births (Table 2 and Table 3). Thus, even when controlling separately for community and patient-level characteristics, patients living in the “Hazardous” region had higher odds of any preterm birth (community-level adjusted OR, 1.46; 95% CI, 1.08-1.97; patient-level adjusted OR, 1.38; 95% CI, 1.25-1.53). This association persisted across the most heavily redlined groups. For periviable birth, women living in the “Hazardous” region had highest odds in unadjusted models (OR, 3.11; 95% CI, 3.11-3.11), with modest attenuation after controlling for community resource characteristics (adjusted OR, 2.16; 95% CI, 1.56-2.98) and patient-level race (adjusted OR, 1.74; 95% CI, 5 1.37-2.21). In contrast, the association of periviable birth with higher HOLC grade were no longer statistically significant after multivariable regression controlling for patient-level characteristics, although they remained significant when controlling for community-level characteristics.

    When comparing secondary outcomes between the extremes of HOLC grades, there was a significant difference in all measured secondary complications and outcomes (eTable in the Supplement). This correlated with a particularly prominent increased odds of severe maternal depression (OR, 4.40; 95% CI, 3.15-6.17) and a diagnosed substance use disorder (OR, 16.37; 95% CI, 5.97-22.40) as well as a decreased odds of exclusive breastfeeding at the time of hospital discharge (OR, 0.12; 95% CI, 0.11-0.13).

    Discussion

    This cohort study found associations between modern obstetric outcome disparities and historic policies driving intergenerational inequity based on race. Our findings provide further evidence of the influence of a legacy of structural racism on the disproportionate burden of adverse pregnancy outcomes for Black women in the US.

    In our study population of a single midsized US city, historic redlining was associated with increased risk of preterm birth in the modern day. This association between historic redlining and contemporary preterm birth rates is striking across the gestational age range. The historic redlining was associated with contemporary increased odds of any preterm birth that did not resolve when factoring in community or patient-level characteristics, particularly in the regions historically designated with the greatest “Hazard.” The persistence of the association of any preterm birth with increasing “Hazard” designation by the HOLC, even when accounting for contemporary community income levels, poverty levels, and educational attainment, suggests that current community resource distribution alone does not explain these disparities in outcome. Potentially, the overarching influence of a system of profound structural inequity ripples forward in time with impacts that extend beyond measurable socioeconomic inequity.

    In contrast, when analyzing the most extreme forms of preterm birth, the unadjusted risk of periviable birth with decreasing HOLC grade ceased to be statistically significant when we controlled for patient-level racial characteristics but not when we controlled for community-level economic characteristics. This finding may generate new hypotheses surrounding the relative association of social and environmental factors across the spectrum of preterm birth, including the roles that income, insurance access, and life stressors may play in the pathogenesis of preterm birth. Moreover, future studies may have the opportunity to explore the potentially differential associations of these factors with preterm births that occur spontaneously vs those that are iatrogenically created owing to medically indicated deliveries.

    When we compared secondary outcomes between the extremes of historic HOLC designation, giving birth when living in the regions historically designated with the greatest “Hazard” was associated with contemporary increased odds of experiencing a range of pregnancy-related comorbidities, as well as increased odds of adverse obstetric outcomes. Odds of severe maternal depression and a diagnosis of substance use disorder were markedly increased among women delivering from the historically “Hazardous” area. By the time of their delivery, these women then also experienced increased odds of maternal complications, such as pregnancy-related hypertension, and neonatal complications, such as low APGAR scores and higher rates of neonatal intensive care unit admission. These associations underscore the echoes of the past—imparting higher morbidity for members of communities impacted by a legacy of disinvestment.

    Limitations

    This study has some limitations. Our study characterized the modern impacts associated with historic, racially discriminatory policy in a single, midsized US city. Given the size of the region, the extremes of HOLC designation included only 1 zip code each, which limits our power and may introduce additional unidentifiable confounders in our multivariable regression. Findings from this single region may also not be applicable to other regions in the US.

    These data have the possible limitations of all large data sets, including the potential for inaccurate data and residual confounding, although the extensive training and codification of birth certificate data in our system lessens these risks. Moreover, owing to the fact that this is a registry of live births, the impact of the assessed factors by definition did not include stillbirths.

    While limited in scope, our study design provides the opportunity to perform an in-depth analysis that integrated community-level data into a data set of patient-level obstetric outcomes, superimposed on historic HOLC designations. This reinforces the findings of a 2020 study delineating associations between historical redlining and birth outcomes in a modern cohort of deliveries in California19 and also adds the opportunity to integrate zip code–level economic and educational attainment data into the regression models, independent of patient-level socioeconomic data.

    Conclusions

    This cohort study integrated historic and modern community data sets into obstetric data sets, offering the opportunity to analyze the contemporary health legacy of historic inequity. Given the sweeping impacts of disproportionate burden of adverse pregnancy outcomes on Black women and their families associated with historical racially discriminatory housing policy, attempts to dismantle these disparities must be multifaceted and informed by increasingly integrated analysis of previously disparate data sets. The observation that racially discriminatory home lending patterns of the 1940s were associated with contemporary preterm birth rates can inform us that the legacy of government-sanctioned discrimination persists today.

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    Article Information

    Accepted for Publication: July 23, 2021.

    Published: September 30, 2021. doi:10.1001/jamanetworkopen.2021.26707

    Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Hollenbach SJ et al. JAMA Network Open.

    Corresponding Author: Stefanie J. Hollenbach, MD, MS, 601 Elmwood Ave, Box 668, Rochester, NY 14642 (stefanie_hollenbach@urmc.rochester.edu).

    Author Contributions: Dr Hollenbach had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Hollenbach, Thornburg, Hill.

    Acquisition, analysis, or interpretation of data: Hollenbach, Glantz, Hill.

    Drafting of the manuscript: Hollenbach, Thornburg, Hill.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Hollenbach, Glantz, Hill.

    Administrative, technical, or material support: Hollenbach, Thornburg.

    Supervision: Hollenbach, Thornburg, Hill.

    Conflict of Interest Disclosures: None reported.

    Meeting Presentation: This work was presented at the 40th Annual Pregnancy Meeting of the Society for Maternal-Fetal Medicine; February 7, 2020; Grapevine, Texas. This work was awarded best poster of the session.

    Additional Contributions: Evan Volkin (University of Rochester) and Erin Campbell, BA (Resources for the Future), assisted in text editing during preparation of this manuscript. They were compensated for this work.

    References
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    Kim  D, Saada  A.  The social determinants of infant mortality and birth outcomes in Western developed nations: a cross-country systematic review.   Int J Environ Res Public Health. 2013;10(6):2296-2335. doi:10.3390/ijerph10062296 PubMedGoogle ScholarCrossref
    2.
    Lorenz  JM, Ananth  CV, Polin  RA, D’Alton  ME.  Infant mortality in the United States.   J Perinatol. 2016;36(10):797-801. doi:10.1038/jp.2016.63 PubMedGoogle ScholarCrossref
    3.
    Tangel  V, White  RS, Nachamie  AS, Pick  JS.  Racial and ethnic disparities in maternal outcomes and the disadvantage of peripartum Black women: a multistate analysis, 2007-2014.   Am J Perinatol. 2019;36(8):835-848. doi:10.1055/s-0038-1675207 PubMedGoogle Scholar
    4.
    Ratnasiri  AWG, Parry  SS, Arief  VN,  et al.  Temporal trends, patterns, and predictors of preterm birth in California from 2007 to 2016, based on the obstetric estimate of gestational age.   Matern Health Neonatol Perinatol. 2018;4:25. doi:10.1186/s40748-018-0094-0 PubMedGoogle ScholarCrossref
    5.
    Eichelberger  KY, Doll  K, Ekpo  GE, Zerden  ML.  Black lives matter: claiming a space for evidence-based outrage in obstetrics and gynecology.   Am J Public Health. 2016;106(10):1771-1772. doi:10.2105/AJPH.2016.303313 PubMedGoogle ScholarCrossref
    6.
    Leonard  SA, Main  EK, Scott  KA, Profit  J, Carmichael  SL.  Racial and ethnic disparities in severe maternal morbidity prevalence and trends.   Ann Epidemiol. 2019;33:30-36. doi:10.1016/j.annepidem.2019.02.007 PubMedGoogle ScholarCrossref
    7.
    Petersen  EE, Davis  NL, Goodman  D,  et al.  Racial/ethnic disparities in pregnancy-related deaths—United States, 2007-2016.   MMWR Morb Mortal Wkly Rep. 2019;68(35):762-765. doi:10.15585/mmwr.mm6835a3PubMedGoogle ScholarCrossref
    8.
    Grobman  WA, Parker  CB, Willinger  M,  et al; Eunice Kennedy Shriver National Institute of Child Health and Human Development Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (nuMoM2b) Network.  Racial disparities in adverse pregnancy outcomes and psychosocial stress.   Obstet Gynecol. 2018;131(2):328-335. doi:10.1097/AOG.0000000000002441 PubMedGoogle ScholarCrossref
    9.
    Bekkar  B, Pacheco  S, Basu  R, DeNicola  N.  Association of air pollution and heat exposure with preterm birth, low birth weight, and stillbirth in the US: a systematic review.   JAMA Netw Open. 2020;3(6):e208243. doi:10.1001/jamanetworkopen.2020.8243 PubMedGoogle Scholar
    10.
    Premkumar  A, Henry  DE, Moghadassi  M, Nakagawa  S, Norton  ME.  The interaction between maternal race/ethnicity and chronic hypertension on preterm birth.   Am J Obstet Gynecol. 2016;215(6):787.e1-787.e8. doi:10.1016/j.ajog.2016.08.019PubMedGoogle ScholarCrossref
    11.
    Holdt Somer  SJ, Sinkey  RG, Bryant  AS.  Epidemiology of racial/ethnic disparities in severe maternal morbidity and mortality.   Semin Perinatol. 2017;41(5):258-265. doi:10.1053/j.semperi.2017.04.001 PubMedGoogle ScholarCrossref
    12.
    Hernandez  DJ, ed.  Children of Immigrants: Health, Adjustment, and Public Assistance. National Academies Press; 1999.
    13.
    Bailey  ZD, Krieger  N, Agénor  M, Graves  J, Linos  N, Bassett  MT.  Structural racism and health inequities in the USA: evidence and interventions.   Lancet. 2017;389(10077):1453-1463. doi:10.1016/S0140-6736(17)30569-X PubMedGoogle ScholarCrossref
    14.
    Mapping Inequity: Redlining in New Deal America. Rochester, NY. Accessed July 17, 2019. https://dsl.richmond.edu/panorama/redlining/#loc=12/43.188/-77.718&city=rochester-ny
    15.
    Rothstein  R.  The Color of Law: A Forgotten History of How Our Government Segregated America. 1st ed. Liveright Publishing Corporation; 2017.
    16.
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