Skip to main content
American Journal of Epidemiology logoLink to American Journal of Epidemiology
. 2023 Sep 28;193(2):277–284. doi: 10.1093/aje/kwad192

Racial and Economic Segregation Over the Life Course and Incident Hypertensive Disorders of Pregnancy Among Black Women in California

Brittney Francis , Michelle Pearl, Cynthia Colen, Abigail Shoben, Shawnita Sealy-Jefferson
PMCID: PMC11031219  PMID: 37771041

Abstract

Black women in the United States have the highest incidence of hypertensive disorders of pregnancy (HDP) and are disproportionately burdened by its adverse sequalae, compared with women of all racial and ethnic groups. Segregation, a key driver of structural racism for Black families, can provide information critical to understanding these disparities. We examined the association between racial and economic segregation at 2 points and incident HDP using intergenerationally linked birth records of 45,204 Black California-born primiparous mothers (born 1982–1997) and their infants (born 1997–2011), with HDP ascertained from hospital discharge records. Women’s early childhood and adulthood neighborhoods were categorized as deprived, mixed, or privileged based on the Index of Concentration at the Extremes (a measure of concentrated racial and economic segregation), yielding 9 life-course trajectories. Women living in deprived neighborhoods at both time points experienced the highest odds of HDP (from mixed effect logistic regression, unadjusted odds ratio = 1.26, 95% confidence interval: 1.13, 1.40) compared with women living in privileged neighborhoods at both time points. All trajectories involving residence in a deprived neighborhood in early childhood or adulthood were associated with increased odds of HDP, whereas mixed-privileged and privileged-mixed trajectories were not. Future studies should assess the causal nature of these associations.

Keywords: Black, hypertensive disorders of pregnancy, life course, neighborhoods, segregation, structural racism

Abbreviations

CI

confidence interval

HDP

hypertensive disorders of pregnancy

OR

odds ratio

ICE

Index of Concentration at the Extremes

LCSC

Life Course Social Context and Disparities in Birth Outcomes

Maternal morbidity and mortality are urgent issues in the United States. For more than a decade there have been increases in maternal mortality rates, despite reduction in rates in most countries around the world (1, 2). However, the increase in rates has not been proportional across racial groups (2, 3). Significant racial disparities in maternal mortality and morbidity rates in the United States have persisted over time, with Black women disproportionately bearing the burden (3, 4). Black women are at higher risk of developing dangerous pregnancy complications that increase their risk for mortality and severe morbidity (1, 5, 6), significantly contributing to their 3-fold risk of maternal death relative to White women (4, 5).

One such group of complications are hypertensive disorders of pregnancy (HDP). Currently, approximately 10% of pregnancies are affected by HDP, and that has been rising over the past few years (69). They are among the leading causes of maternal morbidity and mortality, directly accounting for 7% of maternal deaths and 31% of postpartum hospitalization readmissions (10, 11). Women who have experienced a HDP also have higher risk for postpartum hypertension, stroke, diabetes, and heart disease (1214). Like the overall trend of maternal morbidity and mortality, Black women in the United States are disproportionately burdened by HDP and their adverse sequalae compared with women of all other racial, ethnic, and nativity groups (1517). Between 2017 and 2019, the prevalence of HDP among Black women was 20.9%, followed by 16.4% for American Indian/Alaska Native women (18) compared with 14.7% for White women.

Researchers have been unable to explain these disparities after adjusting for traditional microlevel socioeconomic factors like education, income, and insurance status (19, 20). Similar to outcomes for infant-related outcomes with wide racial disparities, Black race—assumed to be a natural category based on alleged inherent racial biological differences—was considered a risk factor for HDP until very recently (19). There has been significant research documenting how the various forms of oppression and violence that Black women experience during pregnancy, rather than socially assigned race, can increase risk for adverse birth outcomes for Black infants, contributing to the disparities we see. However, these associations are critically understudied for HDP among Black women.

One of the most salient and longstanding forms of anti-Black racism in the United States is residential segregation (21, 22). Since the advent of slavery and legal racial discrimination in the United States up through the Civil Rights Act of 1964, Black people were forced to live in certain neighborhoods through legalized racist housing policies and practices such as redlining, racial covenants, and real-estate steering (2224). Despite decades since the termination of legalized segregation, the United States remains very highly residentially segregated for racially minoritized people (25). Research shows that racialized residential segregation, especially when compounded with concentrated poverty, has adverse impacts on health by disproportionately exposing Black people to neighborhoods that: 1) are often underresourced and limit opportunities for upward socioeconomic mobility (26, 27), 2) have limited access to health-promoting goods and services (28, 29), and 3) overexpose them to harmful environmental pollutants (3032). Additionally, these neighborhoods are also often targeted with other forms of marginalization (e.g., overpolicing, evictions, food deserts) that create stress and additional barriers to accessing resources and goods necessary for a healthy lifestyle (33, 34).

The association between residential segregation and HDP has been explored in the literature. One study examined the relationship between residential segregation and HDPs among Black women in Chicago between 2009 and 2013 and showed that residential segregation, especially the intersection of racial composition and neighborhood income levels, was associated with increased risk of experiencing a HDP among Black women (35). Specifically, they found that women who lived in areas that were predominantly Black and low income had the highest risk of developing a HDP (35). However, these associations have only been explored cross-sectionally (during pregnancy), never over the life course. This is important to explore because the life-course perspective highlights that similar experiences during different time points in life can have varying impacts (36, 37). It is recognized in studies of segregation that children and adults are affected differentially by segregation, with children experiencing additional impacts, such as educational inequality and exposures to environmental hazards during sensitive periods of development that can have future implications for pregnancy complications (38, 39).

To address this gap in the literature, this study explored the association between residential segregation at 2 sensitive key points over the life course in relation to reproductive health and incident HDP among Black women. To our knowledge, no prior study has explored the association between segregation over a woman’s life course and HDP.

METHODS

Study population and procedures

The present study uses a subset of a geocoded, intergenerational, population-based cohort created by the Life Course Social Context and Disparities in Birth Outcomes (LCSC) Study (40) from several sources. The California Biobank Program Linked Dataset (BLD) housed at the California Department of Public Health includes linked birth, fetal death, and death records with data from 2 statewide screening programs. The BLD intergenerationally linked births from 1982 to 2011. Singleton live birth records with an indication that the mother was born in California in or after 1982 were eligible for linkage to maternal birth certificate records (n = 98,464) (40).

Maternal information (sex, date of birth, and first, last, and maiden name) from birth certificates was used to create maternal-infant dyads and group births to the same women via a proprietary matching program using mathematical string-matching algorithms that model human decision making (Tibco Software Inc, Palo Alto, California), followed by programmed checks and extensive clerical review. Approximately 92% (n = 91,056) of the eligible birth certificates were successfully linked to the mother’s birth certificate (40). The LCSC study geocoded address data from maternal newborn-screening data and infant birth records to obtain census tract information from both time points (40) and linked to hospital discharge data for 2000–2011. Distributions of parity, education, age, insurance, and preterm birth were nearly identical for those eligible to link, those successfully linked, and those linked and successfully geocoded.

The final sample for analysis (n = 45,204) included first-time Black mothers who were not diagnosed with chronic hypertension prior to pregnancy and had complete geocoded address data from both birth certificates (see Web Tables 1–6, available at https://doi.org/10.1093/aje/kwad192, for sample derivation). The study was approved by the California Health and Human Services Agency Committee for the Protection of Human Subjects (Project # 14-01-1466) and Ohio State University’s Institutional Review Board (2020H0093).

Exposure ascertainment

The Index of Concentration at the Extremes (ICE) (4143) is an increasingly used multiscalar measure of residential segregation that classifies neighborhoods as deprived or privileged based on the racial and/or economic composition of residents within a determined geographical unit (44). For our study, we used the combined ICE to reflect racialized economic segregation. The ICE scale is a continuous score that ranges from −1 to 1, where −1 corresponds to a neighborhood that is completely composed of low-income Black residents (most deprived) and 1 corresponds to a neighborhood that is completely composed of high-income White residents (most privileged) (41, 43, 45). Although mathematically an ICE value of zero could indicate that a neighborhood either has no individuals or an equal number at the extremes, in actuality, as empirically demonstrated (4143), US patterns of segregation render it highly implausible that an area such as a census tract would have an equal distribution of Black people at the lowest income levels and White people at the highest income levels (4345). Studies show that neighborhoods comprised predominantly of low-income Black residents are more likely to experience underinvestment and be deprived of necessary healthy resources, while neighborhoods comprised predominantly of high-income and White residents receive significant investment in community infrastructure and are often located in close proximity to healthy resources (46, 47). ICE scores were developed in the LCSC Study at the census tract level for all women at the time of their own births and first pregnancies, as part of a prior study (48). Tracts were derived from geocoded addresses corresponding to the time of a woman’s birth and the time of her first pregnancy. ICE scores were calculated using data from the decennial census closest to each year of birth as follows: Within each tract, the number of non-Hispanic Black persons with household income below the 20th income percentile was subtracted from the number of non-Hispanic White persons with annual household income at or above the 80th percentile, then divided by the total population in the tract. Additional details on ICE measure calculation have been previously published (41, 42).

We developed a novel segregation-mobility exposure variable for this analysis based on geocoded addresses at 2 sensitive time points related to the reproductive life course: time of the pregnant person’s birth and the time of delivery for their offspring. We utilized these data to reflect early-childhood neighborhood context and adulthood neighborhood context, as well as neighborhood change between those time periods. For each time point, tertile cutpoints of ICE scores were used to classify women’s census tracts as deprived (lowest tertile), mixed (middle tertile), or privileged (highest tertile) neighborhoods (see Web Tables). The final segregation-mobility variable was categorical in nature and had 9 categories: 1) childhood and adulthood privilege (life-course privilege), 2) childhood privilege and adulthood mixed, 3) childhood privilege and adulthood deprived, 4) childhood mixed and adulthood privileged, 5) childhood and adulthood mixed, 6) childhood mixed and adulthood deprived, 7) childhood deprived and adulthood privilege, 8) childhood deprived and adulthood mixed and 9) childhood deprived and adulthood deprived (life-course deprivation), representing all potential combinations of the proxied childhood and adulthood neighborhoods. Women living in privileged neighborhoods over the life-course were the referent group.

Outcome ascertainment

The outcome of interest was an incident HDP. HDP in our sample was defined as a new diagnosis of gestational hypertension, pre-eclampsia, or eclampsia (4951). HDP status was ascertained from linked hospital-discharge records. The final HDP variable was modeled as a binary variable (yes/no).

Statistical approach

Descriptive statistics for available sociodemographic variables and other known risk factors for HDP were used to assess sample characteristics and their relationship with HDP. Correlations between childhood and adulthood ICE scores were assessed, using Pearson’s correlation coefficient. We used a mixed effect logistic regression model to account for clustering of individuals at the census tract level based on the addresses of the women during pregnancy. This type of modeling is recommended for examining neighborhood level associations with individual health in social epidemiology studies (52). All analyses were completed using STATA IC, version 16.0 (StataCorp LLC, College Station, Texas).

RESULTS

The sociodemographic and behavioral characteristics for our final sample of 45,204 are shown in Table 1. The majority of women were between 18 and 22 years of age (65%, n = 29,359) and had at least completed high school (66%, n = 29,699). Most were born between 1982 and 1992 and gave birth between 2007 and 2011. Approximately 11% of the sample (n = 4,908) was diagnosed with HDP: 5% had gestational hypertension (n = 2,272), 5.8% had pre-eclampsia (n = 2,615), and 0.3% had eclampsia (n = 117). ICE scores in childhood ranged from −0.39 to 0.43, with a median and mean score of −0.02 in the overall sample. ICE scores during adulthood ranged from −0.25 to 0.46, with a median and mean score of −0.01 in the overall sample. Childhood and adulthood ICE scores were weakly correlated (ρ = 0.25). Approximately 44% of the women gave birth while living in a census tract with the same neighborhood classification category (deprived, mixed, privileged) as their childhood neighborhood. Twenty-nine percent of the women gave birth while living in a census tract that was less privileged than the census tract of their childhood (downward mobility), and 27% gave birth while living in a census tract that was more privileged than the census tract of their childhood (upward mobility). The most prevalent individual category was life-course deprivation (16%, n = 7,335), followed by the life-course privilege category (15%, n = 6,911). Distributions of ICE scores by participant characteristics are shown at both time points in the Web Tables.

Table 1.

Characteristics of and Association With Hypertensive Disorders of Pregnancy Among Black Women in California, 1982–2011

Characteristic Total Sample No HDP HDP OR 95% CI
No. % No. % No. %
Total 45,204 100 40,296 91 4,908 11.0
Age, years
 <18 9,165 20.3 8,174 20.3 991 20.2 1.00 Referent
 18–22 29,359 65.0 26,223 65.1 3,136 63.9 0.99 0.91, 1.06
 23–29 6,680 14.7 5,899 14.6 781 15.9 1.09 0.99,1.21
Education
 Less than high school graduation 14,562 32.2 12,956 32.2 1,606 32.7 1.00 Referent
 High school graduation 17,592 38.9 15,677 38.9 1,915 39.0 0.99 0.92, 1.06
 Beyond high school 12,107 26.8 10,829 26.8 1278 26.0 0.95 0.88, 1.03
 Missing 943 2.1 834 2.1 109 2.2

Abbreviations: CI, confidence interval; HDP, hypertensive disorders of pregnancy; OR, odds ratio.

In an unadjusted model, all but 2 trajectories were associated with increased odds of HDP compared with living in privileged neighborhoods over the life course (Table 2). Compared with life-course privilege, living in deprived neighborhoods over the life course was associated with the highest odds of having HDP (odds ratio (OR) = 1.26, confidence interval (CI): 1.13, 1.40), followed by living in a mixed neighborhood during childhood and deprived neighborhood during adulthood (OR = 1.24, CI: 1.09, 1.39). A clear stepwise increase in odds ratios of HDP relative to life-course privilege is evident for women who lived in privileged or mixed neighborhood during childhood, as they move from privilege to deprived neighborhoods in adulthood (Figure 1). However, this stepwise trend is not seen among women who lived in deprived neighborhoods during childhood. ORs and CIs of experiencing an incident HDP relative to life-course privilege were similar for women who lived in deprived neighborhoods during childhood but then lived in privileged (OR = 1.19, CI: 1.04, 1.34), mixed (OR = 1.18, CI: 1.04, 1.34), or deprived (OR = 1.26, CI: 1.13, 1.40) neighborhoods during adulthood. Notably, women who lived in a deprived neighborhood during childhood and lived in a privileged neighborhood during adulthood (fully upwardly mobile) had similar ORs for HDP relative to life-course privilege as women who lived in a privileged neighborhood during childhood and gave birth while living in a deprived neighborhood (fully downwardly mobile) Adjusting for age and education attenuated estimates slightly (data not shown).

Table 2.

Odds Ratios and 95% Confidence Intervals for the Association Between Life-Course Segregation Mobility and Hypertensive Disorders of Pregnancy Among Black Women in California, 1982–2011

Mobility Category No. % HDP Unadjusted
OR 95% CI
Childhood privilege
 Adulthood privilege 6,911 9.7 1.00 Referent
 Adulthood mixed 5,340 10.1 1.05 0.92, 1.18
 Adulthood deprivation 2,810 11.2 1.18 1.02, 1.36
Childhood mixed
 Adulthood privilege 4,574 9.9 1.02 0.90, 1.16
 Adulthood mixed 5,554 10.9 1.14 1.01, 1.27
 Adulthood deprivation 4,944 11.7 1.24 1.09, 1.39
Childhood deprivation
 Adulthood privilege 3,583 11.3 1.19 1.04, 1.35
 Adulthood mixed 4,153 11.3 1.18 1.04, 1.34
 Adulthood deprivation 7,335 11.9 1.26 1.13, 1.40

Abbreviations: CI, confidence interval; HDP, hypertensive disorders of pregnancy; OR, odds ratio.

Figure 1.

Figure 1

Odds ratios (ORs) and 95% confidence intervals (CIs) from mixed effects logistic regression for life-course segregation mobility and hypertensive disorders of pregnancy among black women in California, 1982–2011.

DISCUSSION

In our analysis of life-course neighborhood racialized economic segregation among Black women, most trajectories were associated with higher odds of HDP compared with living in neighborhoods of privilege over their life course. In particular, trajectories including residence in a deprived neighborhood at either time point were associated with increased odds of HDP, whereas mixed-privileged and privileged-mixed trajectories were not. Living in deprived neighborhoods at both time points was associated with the highest odds of HDP compared with living in privileged neighborhoods over the life course.

One interesting and important finding is that upward socioeconomic mobility (living in a more privileged neighborhood in adulthood than in childhood) was not associated with increased risk of HDP among Black women who grew up in mixed neighborhoods, but it is associated with increased risk of HDP among Black women who grew up in deprived neighborhoods, compared with women who lived in privilege at both time points. Clear stepwise gradients, whereby the likelihood of experiencing HDP increases as their adulthood neighborhood worsened, were evident among women who lived in mixed and privileged neighborhoods during childhood. However, this stepwise gradient is not evident among Black women who were residents of deprived neighborhoods during childhood. Regardless of the neighborhood they resided in during adulthood, their risk of HDP did not substantially differ. These results are particularly notable for 3 overarching reasons. First, they point to the importance and enduring impact of childhood residence in addition to adulthood residence. Specifically, childhood residence in deprived neighborhoods may have long-lasting effects that should be explored. Second, the results suggest that Black women who grew up in deprived neighborhoods may not experience the same health benefits typically attributable to upward social mobility (5355). As such, it is vital to study and address neighborhood inequalities during early life as potential life-course risk factors for HDP. Third, the results suggest that living in a deprived neighborhood during childhood may partially explain the increased risk of HDP among Black women and is a potential pathway through which racial disparities in health are socially passed from one generation to the next, even among Black women of higher socioeconomic position. The finding of increased HDP risk for those living in deprived neighborhoods, regardless of privileged or mixed neighborhoods during childhood, emphasizes the importance of understanding adulthood neighborhood environments in relation to Black women’s health. Taken together, the study findings suggest that equitable neighborhood opportunities and resources for both children and adults are necessary for improving health equity.

Collectively, these findings are consistent with the sociological and epidemiologic literature suggesting that impacts of segregation should be explored over the life course (36, 56). During childhood, living in a highly segregated and underresourced neighborhood is associated with the quality and years of education children receive (57, 58), the risk of exposure to environmental toxins during key developmental periods (59), increased exposure to smoking advertisements (60, 61), and reduced access to fresh food (56, 62). All of these factors have long-term impacts on adult health, including pregnancy. During adulthood, living in a highly segregated and underresourced neighborhood is associated with limited job opportunities (63), longer commutes on public transportation (64), limited access to health-care providers (65), increased exposure to deadly interactions with police officers (66), reduced access to fresh and nutritious foods (28), and increased stress due to neighborhood conditions (67). This study points to the need to explore residential history over the life course and the differential temporal pathways through which segregation may affect HDP and other pregnancy complications to further understand the life-course impacts of structural racism on health.

This study had a few limitations that should be taken into consideration. First, data on HDP came from hospital discharge data, which could result in missed cases of HDP and misclassification bias. However, an internal cross check at the California Department of Health against maternal medical records found 97% sensitivity for HDP from hospital discharge data among Black women and did not vary by neighborhood type. Secondly, the study’s conclusions are limited to associations. These associations may support future causal analysis in studies with richer covariate information, and the ability to distinguish mediating pathways through health behaviors. Such analyses should consider that a reduction in segregation may also decrease chronic hypertension (excluded in this study), and thereby increase the number of women susceptible to incident HDP. Finally, based on the timeframe of the linkages (1982–2011), the maximum age possible in the sample was 29. Although only 18% of Black women delivering their first infant in California in 2011 were age 30 or older, older women are at increased risk of HDP (18). Including older women could affect the distribution of the trajectories and allow for more upward mobility. Future studies should explore this association among women of a wider age range.

The study also had several strengths. Primarily, it is the first study, to our knowledge, to explore the relationship between residential segregation over the life course and HDP. The results from this study highlight the need for epidemiologic studies that examine neighborhoods both prior to and during pregnancy to understand the variable and temporal impacts of segregated neighborhoods over the life course. Second, the linking of several statewide data sources allowed us to build life-course trajectories and examine 2 critical time periods over the life course for pregnancy outcomes. The analysis showed that women can live in the same types of neighborhoods during pregnancy but have differential risk of HDP due to early-life exposure. Future studies should explore additional meaningful time points over the life course. Finally, our intracategorical sample allowed us to examine the differential impact of neighborhood quality among Black women. Such an analysis requires a large sample size, and the California data set includes the largest sample of Black women with cross-generational neighborhood information in the country. An intracategorical analysis also contributes to dispelling the myth that Black race itself should be used as a clinical risk factor, by highlighting heterogeneity among Black women and the important role of life-course neighborhoods. Risk assessment should address other structural factors that can have biological and behavioral impacts on the risk of developing HDP among Black women, creating the disparities we see.

An environmental oppression framework posits that residential environments composed predominantly of low-income and racially marginalized people are harmed by various inequitable policies and practices that create adverse social, built, and natural environments (33, 68, 69). Since one’s residential environment is linked to key resources needed to create and maintain a health-promoting lifestyle in our society (69), living in a neighborhood where resources are consistently extracted, exploited, or underfunded (deprived neighborhoods) can adversely affect health outcomes for the people living there. For example, neighborhood-level inequities in infrastructure and access to fresh and nutritious foods directly affect Black women’s ability to implement key individual-level prevention and management interventions and recommendations for HDP, such as diet and exercise. Exploring the complex impact of segregation as a fundamental cause of inequitable outcomes in hypertensive disorders of pregnancy is necessary given the current maternal morbidity and mortality crisis among Black women. The findings of this research suggest that equitable resources in all neighborhoods and for all residents, such that women do not live in a deprived neighborhood during their life course, may serve as a strong population health intervention for hypertensive disorders of pregnancy and creating equity for Black women.

Supplementary Material

Web_Material_kwad192
web_material_kwad192.pdf (179.5KB, pdf)

ACKNOWLEDGMENTS

Author affiliations: FXB Center for Health and Human Rights, Harvard University, Boston, Massachusetts, United States (Brittney Francis); Harvard Center for Population and Development Studies, Boston, Massachusetts, United States (Brittney Francis); California Department of Public Health, Richmond, California, United States (Michelle Pearl); Department of Sociology, Ohio State University, Columbus, Ohio, United States (Cynthia Colen); Division of Biostatistics, College of Public Health, Ohio State University College of Public Health, Columbus, Ohio, United States (Abigail Shoben); and Division of Epidemiology, College of Public Health, Ohio State University, Columbus, Ohio, United States (Shawnita Sealy-Jefferson).

This project was in funded through the support of the Health Policy Research Scholars Program’s Dissertation Award and The JPB Foundation. Funding for the Life Course Social Context and Birth Outcomes study was provided by Maternal and Child Health Bureau (grant/award number R40MC28306).

Data from this study is not publicly available and must be accessed through the California Department of Health directly.

Data used in this study were obtained from the California Biobank Program (SIS request number 539). We thank Dennis Kunichoff for helping with the data visualization.

The findings and conclusions in this article are those of the authors and do not necessarily represent the views or opinions of the California Department of Public Health or the California Health and Human Services Agency.

Conflict of interest: none declared.

REFERENCES

  • 1. Lu MC, Noursi S. Summary and conclusion: framing a new research agenda on maternal morbidities and mortality in the United States. J Womens Health. 2021;30(2):280–284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Douthard RA, Martin IK, Chapple-McGruder T, et al. US maternal mortality within a global context: historical trends, current state, and future directions. J Womens Health. 2021;30(2):168–177. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. 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] [PMC free article] [PubMed] [Google Scholar]
  • 4. Louis JM, Menard MK, Gee RE. Racial and ethnic disparities in maternal morbidity and mortality. Obstet Gynecol. 2015;125(3):690–694. [DOI] [PubMed] [Google Scholar]
  • 5. Lu MC. Reducing maternal mortality in the United States. JAMA. 2018;320(12):1237–1238. [DOI] [PubMed] [Google Scholar]
  • 6. Hitti J, Sienas L, Walker S, et al. Contribution of hypertension to severe maternal morbidity. Am J Obstet Gynecol. 2018;219(4):405.e1–405.e7. [DOI] [PubMed] [Google Scholar]
  • 7. Hutcheon JA, Lisonkova S, Joseph K. Epidemiology of pre-eclampsia and the other hypertensive disorders of pregnancy. Best Pract Res Clin Obstet Gynaecol. 2011;25(4):391–403. [DOI] [PubMed] [Google Scholar]
  • 8. Bateman BT, Shaw KM, Kuklina EV, et al. Hypertension in women of reproductive age in the United States: NHANES 1999–2008. PloS One. 2012;7(4):e36171. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Kuehn BM. Hypertensive disorders in pregnancy are on the rise. JAMA. 2022;327(24):2387–2387. [DOI] [PubMed] [Google Scholar]
  • 10. Division of Reproductive Health, NCCDPHP . Causes of pregnancy-related deaths. 2022. https://www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm. Accessed January 30, 2023.
  • 11. Mogos MF, Salemi JL, Spooner KK, et al. Hypertensive disorders of pregnancy and postpartum readmission in the United States: national surveillance of the revolving door. J Hypertens. 2018;36(3):608–618. [DOI] [PubMed] [Google Scholar]
  • 12. Bushnell C, Chireau M. Preeclampsia and stroke: risks during and after pregnancy. Stroke Res Treat. 2011;2011:858134. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Rana S, Lemoine E, Granger JP, et al. Preeclampsia: pathophysiology, challenges, and perspectives. Circ Res. 2019;124(7):1094–1112. [DOI] [PubMed] [Google Scholar]
  • 14. Savitz DA, Danilack VA, Elston B, et al. Pregnancy-induced hypertension and diabetes and the risk of cardiovascular disease, stroke, and diabetes hospitalization in the year following delivery. Am J Epidemiol. 2014;180(1):41–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Singh GK, Siahpush M, Liu L, et al. Racial/ethnic, nativity, and sociodemographic disparities in maternal hypertension in the United States, 2014–2015. Int J Hypertens. 2018;2018:1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Ghosh G, Grewal J, Männistö T, et al. Racial/ethnic differences in pregnancy-related hypertensive disease in nulliparous women. Ethn Dis. 2014;24(3):283–289. [PMC free article] [PubMed] [Google Scholar]
  • 17. Miranda ML, Swamy GK, Edwards S, et al. Disparities in maternal hypertension and pregnancy outcomes: evidence from North Carolina, 1994–2003. Public Health Rep. 2010;125(4):579–587. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Ford ND, Cox S, Ko JY, et al. Hypertensive disorders in pregnancy and mortality at delivery hospitalization—United States, 2017–2019. Morb Mortal Wkly Rep. 2022;71(17):585–591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Johnson JD, Louis JM. Does race or ethnicity play a role in the origin, pathophysiology, and outcomes of preeclampsia? An expert review of the literature. Am J Obstet Gynecol. 2022;226(2S):S876–S885. [DOI] [PubMed] [Google Scholar]
  • 20. Tanaka M, Jaamaa G, Kaiser M, et al. Racial disparity in hypertensive disorders of pregnancy in New York state: a 10-year longitudinal population-based study. Am J Public Health. 2007;97(1):163–170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Massey DS, Denton NA. American Apartheid: Segregation and the Making of the Underclass. 1st ed. Cambridge, MA: Harvard University Press; 1993. [Google Scholar]
  • 22. Rothstein R. The Color of Law: A Forgotten History of How Our Government Segregated America. 1st ed. New York, NY: Liveright Publishing; 2017. [Google Scholar]
  • 23. Boustan LP. Racial Residential Segregation in American Cities. Vol. No. w19045. Cambridge, MA: National Bureau of Economic Research; 2013. [Google Scholar]
  • 24. Besbris M, Faber JW. Investigating the Relationship Between Real Estate Agents, Segregation, and House Prices: Steering and Upselling in New York State. Hoboken, NJ: Wiley Online Library; 2017:850–873. [Google Scholar]
  • 25. Faber JW. Segregation and the geography of creditworthiness: racial inequality in a recovered mortgage market. Hous Policy Debate. 2018;28(2):215–247. [Google Scholar]
  • 26. Ray R, Perry AM, Harshbarger D, et al. Homeownership, Racial Segregation, and Policy Solutions to Racial Wealth Equity. Washington, DC: The Brookings Institution; September 2021:1. [Google Scholar]
  • 27. Perry A, Rothwell J, Harshbarger D. The Devaluation of Assets in Black Neighborhoods: The Case of Residential Property. Washington, DC: Metropolitan Policy Program at Brookings; 2018. [Google Scholar]
  • 28. Bower KM, Thorpe RJ Jr, Rohde C, et al. The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States. Prev Med. 2014;58:33–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Arcaya MC, Schnake-Mahl A. Health in the segregated city. In: The Dream Revisited: Contemporary Debates About Housing, Segregation, and Opportunity. New York, NY: Columbia University Press; 2019:165–168. [Google Scholar]
  • 30. Woo B, Kravitz-Wirtz N, Sass V, et al. Residential segregation and racial/ethnic disparities in ambient air pollution. Race Soc Probl. 2019;11(1):60–67. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31. Sampson RJ, Winter AS. The racial ecology of lead poisoning: toxic inequality in Chicago neighborhoods, 1995–2013. Du Bois Rev. 2016;13(2):261–283. [Google Scholar]
  • 32. Casey JA, Morello-Frosch R, Mennitt DJ, et al. Race/ethnicity, socioeconomic status, residential segregation, and spatial variation in noise exposure in the contiguous United States. Environ Health Perspect. 2017;125(7):077017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Sewell AA. The racism-race reification process: a mesolevel political economic framework for understanding racial health disparities. Sociol Race Ethn. 2016;2(4):402–432. [Google Scholar]
  • 34. Riley AR. Neighborhood disadvantage, residential segregation, and beyond—lessons for studying structural racism and health. J Racial Ethn Health Disparities. 2018;5(2):357–365. [DOI] [PubMed] [Google Scholar]
  • 35. Mayne SL, Yellayi D, Pool LR, et al. Racial residential segregation and hypertensive disorder of pregnancy among women in Chicago: analysis of electronic health record data. Am J Hypertens. 2018;31(11):1221–1227. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36. Gee GC, Walsemann KM, Brondolo E. A life course perspective on how racism may be related to health inequities. Am J Public Health. 2012;102(5):967–974. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Elder GH, Johnson MK, Crosnoe R. The emergence and development of life course theory. In: Mortimer JT, Shanahan MJ, eds. Handbook of the Life Course. New York, NY: Springer US; 2003:3–19. [Google Scholar]
  • 38. Poropat AE, Laidlaw MA, Lanphear B, et al. Blood lead and preeclampsia: a meta-analysis and review of implications. Environ Res. 2018;160:12–19. [DOI] [PubMed] [Google Scholar]
  • 39. Teye SO, Yanosky JD, Cuffee Y, et al. Exploring persistent racial/ethnic disparities in lead exposure among American children aged 1–5 years: results from NHANES 1999–2016. Int Arch Occup Environ Health. 2021;94(4):723–730. [DOI] [PubMed] [Google Scholar]
  • 40. Pearl M, Ahern J, Hubbard A, et al. Life-course neighbourhood opportunity and racial-ethnic disparities in risk of preterm birth. Paediatr Perinat Epidemiol. 2018;32(5):412–419. [DOI] [PubMed] [Google Scholar]
  • 41. Krieger N, Feldman JM, Waterman PD, et al. Local residential segregation matters: stronger association of census tract compared to conventional city-level measures with fatal and non-fatal assaults (total and firearm related), using the Index of Concentration at the Extremes (ICE) for racial, economic, and racialized economic segregation, Massachusetts (US), 1995–2010. J Urban Health. 2017;94(2):244–258. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Krieger N, Waterman PD, Batra N, et al. Measures of local segregation for monitoring health inequities by local health departments. Am J Public Health. 2017;107(6):903–906. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Krieger N, Waterman PD, Spasojevic J, et al. Public health monitoring of privilege and deprivation with the Index of Concentration at the Extremes. Am J Public Health. 2016;106(2):256–263. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Larrabee Sonderlund A, Charifson M, Schoenthaler A, et al. Racialized economic segregation and health outcomes: a systematic review of studies that use the Index of Concentration at the Extremes for race, income, and their interaction. PloS One. 2022;17(1):e0262962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Chambers BD, Baer RJ, McLemore MR, et al. Using Index of Concentration at the Extremes as indicators of structural racism to evaluate the association with preterm birth and infant mortality—California, 2011–2012. J Urban Health. 2018;96(2):159–170. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Kramer MR, Hogue CR. Is segregation bad for your health? Epidemiol Rev. 2009;31(1):178–194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Beaulieu M, Continelli T. Benefits of segregation for White communities: a review of the literature and directions for future research. J Afr Am Stud. 2011;15(4):487–507. [Google Scholar]
  • 48. Shrimali BP, Pearl M, Karasek D, et al. Neighborhood privilege, preterm delivery, and related racial/ethnic disparities: an intergenerational application of the Index of Concentration at the Extremes. Am J Epidemiol. 2020;189(5):412–421. [DOI] [PubMed] [Google Scholar]
  • 49. Brown MA, Magee LA, Kenny LC, et al. Hypertensive disorders of pregnancy: ISSHP classification, diagnosis, and management recommendations for international practice. Hypertension. 2018;72(1):24–43. [DOI] [PubMed] [Google Scholar]
  • 50. Mammaro A, Carrara S, Cavaliere A, et al. Hypertensive disorders of pregnancy. J Prenat Med. 2009;3(1):1–5. [PMC free article] [PubMed] [Google Scholar]
  • 51. Khedagi AM, Bello NA. Hypertensive disorders of pregnancy. Cardiol Clin. 2021;39(1):77–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Merlo J, Chaix B, Yang M, et al. A brief conceptual tutorial on multilevel analysis in social epidemiology: interpreting neighbourhood differences and the effect of neighbourhood characteristics on individual health. J Epidemiol Community Health. 2005;59(12):1022–1029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Colen CG, Krueger PM, Boettner BL. Do rising tides lift all boats? Racial disparities in health across the lifecourse among middle-class African-Americans and Whites. SSM Popul Health. 2018;6:125–135. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Colen CG. Addressing racial disparities in health using life course perspectives. Du Bois Rev. 2011;8(1):79–94. [Google Scholar]
  • 55. Colen CG, Ramey DM, Cooksey EC, et al. Racial disparities in health among nonpoor African Americans and Hispanics: the role of acute and chronic discrimination. Soc Sci Med. 2018;199:167–180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 56. McArdle N, Acevedo-Garcia D. Consequences of Segregation for Children’s Opportunity and Wellbeing. 2017.
  • 57. Reardon SF. School segregation and racial academic achievement gaps. Russell Sage J Soc Sci. 2016;2(5):34–57. [Google Scholar]
  • 58. Bhargava A. In: Helbert C, et al., eds. The Interdependence of Housing and School Segregation. 2017. https://www.jchs.harvard.edu/sites/default/files/a_shared_future_interdependence_of_housing_and_school_segregation.pdf. Accessed September 26, 2023.
  • 59. Morello-Frosch R, Lopez R. The riskscape and the color line: examining the role of segregation in environmental health disparities. Environ Res. 2006;102(2):181–196. [DOI] [PubMed] [Google Scholar]
  • 60. Landrine H, Klonoff EA. Racial segregation and cigarette smoking among blacks: findings at the individual level. J Health Psychol. 2000;5(2):211–219. [DOI] [PubMed] [Google Scholar]
  • 61. Mills SD, Henriksen L, Golden SD, et al. Disparities in retail marketing for menthol cigarettes in the United States, 2015. Health Place. 2018;53:62–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Ellen IG, Glied S. Housing, neighborhoods, and children's health. Future Child. 2015;25(1):135–153. [Google Scholar]
  • 63. Dickerson NT. Black employment, segregation, and the social organization of metropolitan labor markets. Econ Geogr. 2007;83(3):283–307. [Google Scholar]
  • 64. Urban Institute . Access to Opportunity Through Equitable Transportation. Washington DC: Urban Institute; 2020. https://www.urban.org/sites/default/files/publication/102992/access-to-opportunity-through-equitable-transportation_0.pdf. Accessed on January 30, 2023. [Google Scholar]
  • 65. White K, Haas JS, Williams DR. Elucidating the role of place in health care disparities: the example of racial/ethnic residential segregation. Health Serv Res. 2012;47(3pt2):1278–1299. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Feldman JM, Gruskin S, Coull BA, et al. Police-related deaths and neighborhood economic and racial/ethnic polarization, United States, 2015–2016. Am J Public Health. 2019;109(3):458–464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67. Culhane JF, Elo IT. Neighborhood context and reproductive health. Am J Obstet Gynecol. 2005;192(5):S22–S29. [DOI] [PubMed] [Google Scholar]
  • 68. Wilson SM. An ecologic framework to study and address environmental justice and community health issues. Environ Justice. 2009;2(1):15–24. [Google Scholar]
  • 69. Diez Roux AV, Mair C. Neighborhoods and health. Ann N Y Acad Sci. 2010;1186(1):125–145. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Web_Material_kwad192
web_material_kwad192.pdf (179.5KB, pdf)

Articles from American Journal of Epidemiology are provided here courtesy of Oxford University Press

RESOURCES