Sage Journals: Discover world-class research

Abstract

Background:

Adverse pregnancy outcomes (APOs) are strongly associated with an increased risk of long-term cardiovascular disease (CVD), with physiological adaptations during pregnancy, such as vascular remodeling and endothelial dysfunction, possibly contributing to an elevated lifetime CVD risk. This review explores the complex interplay between APOs and long-term CVD risk, emphasizing how racial disparities and socioeconomic status (SES) shape maternal cardiovascular health.

Methods:

A comprehensive review of existing literature was conducted to evaluate the association between APOs and long-term CVD risk. This review also examines the influence of SES and racial disparities on maternal cardiovascular health, highlighting their roles in modifying disease progression and health care access.

Results:

Approximately 29% of women experience pregnancy complications, including gestational diabetes and hypertensive disorders, which are associated with at least a twofold increase in subsequent cardiovascular event risk. Socioeconomic factors play a critical role in shaping prenatal care quality and treatment adherence, as women from lower SES backgrounds, due to systemic barriers, face a heightened risk of APOs. Racial disparities further exacerbate these risks, with Black women experiencing disproportionately higher maternal mortality and APO rates compared with White women.

Conclusions:

This review underscores the intersection of race and SES in shaping maternal health disparities and long-term CVD risk. Targeted interventions to address these inequities by addressing social determinants of health are necessary. Future research should focus on elucidating the mechanisms linking SES and race to CVD following APOs, developing strategies to mitigate disparities, and conducting longitudinal studies to track CVD progression in affected populations.

Keywords

socioeconomic disparities cardiovascular complications adverse pregnancy outcomes race and health equity maternal cardiometabolic health

Introduction

Numerous vascular, metabolic, and physiological changes occur during pregnancy, including decreased vascular resistance, deposition of adipose tissues, hypercoagulability, increased insulin resistance, and cardiac remodeling.¹ These adaptations are essential for supporting fetal growth and preparing the mother for the energy demands of labor, delivery, and lactation.² However, they can also lead to vascular dysfunction, inflammation, and abnormal placentation, potentially exacerbating subclinical cardiovascular disease (CVD) after pregnancy.³ Research shows that adverse pregnancy outcomes (APOs) such as preterm delivery, small-for-gestational age (SGA) infants, preeclampsia, hypertensive disorders, and gestational diabetes are strongly associated with increased risks of CVD later in life.³ Approximately 29% of parous women experience at least one pregnancy-related complication, correlating with a twofold increase in cardiovascular events.⁴ For example, 3%–70% of women with a history of gestational diabetes mellitus develop type 2 diabetes within three decades postpregnancy, while those with preeclampsia are more likely to develop hypertension, coronary heart disease, stroke, and venous thromboembolism.⁴

Socioeconomic factors including income, education, health care access, and social support are pivotal in shaping accessibility to antenatal care, quality of health care, and treatment adherence, ultimately influencing long-term cardiovascular outcomes.⁵ These factors, in combination with the vascular and metabolic changes of pregnancy, significantly contribute to CVD risk postpregnancy. In the United States, maternal health disparities continue to worsen, with non-Hispanic Black women being three to four times more likely to die from pregnancy complications compared with non-Hispanic White women.⁶ Low socioeconomic status (SES) has also been linked to APOs, underscoring the complex interplay of factors contributing to maternal health disparities.⁷ The framework of intersectionality, acknowledging the link between social identities such as race, SES, and gender, is essential for understanding cardiovascular health disparities in maternal health.⁸ While socioeconomic factors critically shape prenatal care access and health outcomes, analyzing them in isolation fails to fully capture the multifaceted nature of these disparities. Further investigation into how race and SES intersect is crucial for developing effective strategies to prevent and mitigate the risk of CVD in women.

Methods

A comprehensive narrative literature review was conducted to evaluate the association between APOs and long-term CVD risk, with a specific focus on the influence of SES and racial disparities in maternal cardiovascular health. To ensure the inclusion of the most relevant and up-to-date research, a systematic search was performed across multiple databases, including PubMed, Scopus, Web of Science, and Google Scholar. The search terms used included “adverse pregnancy outcomes,” “long-term cardiovascular disease risk,” “preeclampsia,” “gestational diabetes,” “hypertensive disorders of pregnancy,” “socioeconomic status,” “racial disparities,” and “maternal cardiovascular health.” Articles were limited to peer-reviewed studies published in English between 2000 and 2023 to capture contemporary trends and outcomes. Additionally, references from key articles were reviewed to identify further studies that may have been overlooked in the initial search.

Studies were included based on specific inclusion criteria: (1) epidemiological studies, cohort studies, systematic reviews, and meta-analyses that examined the relationship between APOs and long-term cardiovascular outcomes, (2) studies that explored the impact of SES or racial disparities on maternal cardiovascular health, and (3) studies that involved diverse populations to understand how various factors, such as income, education, health care access, and race, influence health outcomes postpregnancy. Exclusion criteria were studies that focused on small sample sizes (less than 100 participants), nonhuman studies, and studies that did not provide clear definitions of APOs or cardiovascular endpoints. Data extraction involved a systematic review of study design, population demographics, sample size, methodology, and key outcomes, with particular attention to how SES and race were measured and their relationship with cardiovascular risk postpregnancy. The findings were synthesized to assess the broader implications of maternal health outcomes, with a focus on identifying patterns in CVD risk as influenced by pregnancy complications, SES, and racial disparities. This review highlights both established knowledge and gaps in the literature to inform future research directions and potential policy interventions. A total of 1200 records were identified through database searches. After removing 240 duplicates, 960 records were screened by title and abstract, resulting in 144 full-text articles assessed for eligibility. Of these, 25 studies met the inclusion criteria. Screening and duplicate removal were conducted using Rayyan. Full details of the search strategy can be found in the Supplementary Table S1.

Association between APOs and cardiovascular complications

There is a significant delay in recognizing and predicting CVD in women due to its presentation differing from that in men.⁹ Hence, efforts to identify women at increased risk for CVD have intensified to reduce the global disease burden. Increasing evidence links APOs with long-term cardiovascular risk, with Rich-Edwards et al. notably describing APOs as a physiological “stress test” for future CVD risk.⁴ Meta-analyses consistently demonstrate that women with a history of pregnancy complications, such as gestational diabetes or hypertensive disorders, are more likely to develop metabolic and CVDs later in life. For instance, women with gestational diabetes are at a significantly higher risk of type 2 diabetes compared with those with normoglycemic pregnancies.¹⁰ Similarly, women with gestational hypertension or preeclampsia are more than two times risk to develop chronic hypertension,¹¹ and those with elevated low-density lipoprotein and triglycerides during pregnancy show an increased risk for dyslipidemia years later.¹² Recent data from the Nulliparous Pregnancy Outcomes Study-Monitoring Mothers-to-Be Heart Health Study longitudinal cohort reinforces this association, revealing that women who experienced APOs in their first pregnancy have a markedly higher predicted risk of atherosclerotic CVD within 2–7 years postpartum.¹³ While many studies suggest shared risk factors between APOs and CVD, further research is needed to describe the causative mechanisms linking pregnancy complications to future CVD.^11–14 Table 1 shows a summary of the association between APOs and long-term cardiovascular risk.

Table 1.

Summary of Associations Between Adverse Pregnancy Outcomes and Long-Term Cardiovascular Disease

Condition	Heart failure (OR/RR [95% CI])	Stroke (OR/RR [95% CI])	Myocardial infarction (OR/RR [95% CI])	Coronary heart disease (OR/RR [95% CI])	Metabolic syndrome (OR/RR [95% CI])	Hypertension (OR/RR [95% CI])
Preeclampsia^*	2.09^** (1.80–2.44)¹⁵	3.79⁺ (1.24–11.60)¹⁶	3.94⁺ (1.25–12.4)¹⁷	2.50⁺ (1.43–4.37)¹⁵	1.23^* (1.12–1.35)¹⁸	13.92^* (5.17–37.4)¹⁹
Gestational hypertension	5.16^* (3.89–6.85)²⁰	1.58^* (1.32–1.89)²¹	2.46⁺ (1.72–3.53)²²	1.08^* (1.00–1.17)²³	1.23^* (1.12–1.35)²⁴	4.2^* (1.0–17.5)²⁵
Gestational diabetes	1.62⁺ (1.28–2.05)²⁶	1.04^** (0.59–1.82)²⁷	1.92^* (1.36–2.71)²⁸	2.78⁺⁺ (1.37–5.66)²⁹	6.7⁺ (2.7–17)³⁰	1.58^* (1.02–2.45)³¹
Preterm birth	2.69⁺⁺⁺ (2.43–2.97)³²	1.61^** (1.45–1.79)³²	NA	2.85 (1.19–6.85)³³	4.30^** (1.90–10.10)³⁴	1.67^** (1.61–1.74)³²
Intrauterine growth restriction	NA	1.68⁺ (1.46–2.06)²⁰	NA	1.70^* (1.10–2.70)³⁵	1.76^* (1.06–2.80)³⁶	NA
Macrosomia	2.2^* (1.44–3.29)³⁷	NA	NA	NA	1.92^* (1.21–3.05)³⁸	6.78^*** (5.82–7.88)³⁹

Risk ratio.

Odds ratio.

Hazard ratio.

Incidence risk ratio.

+++

Adjusted for child characteristics and maternal characteristics.

Early preterm birth.

***

Risk when combined with maternal obesity.

CI, confidence interval; NA, not available; OR, odds ratio; RR, relative risk.

Socioeconomic disparities in APOs

Impact of SES on pregnancy outcomes

Pregnancy outcomes are greatly influenced by SES, with lower SES, despite stratification by race, being linked to APOs such as maternal mortality, low birth weight, preterm birth, and stillbirth.^40,41 This impact is complex, but it is mostly caused by limited access to prenatal care and other health care services because of financial limitations and insufficient health insurance coverage.⁴² The incidence of APOs is further increased by environmental triggers that are common among low SES communities, such as food shortages, pollution exposure, and insufficient housing.^7,41 The barriers to accessing prenatal care such as lack of insurance, poor transportation, and provider shortages result in delays that compromise early detection and management of pregnancy complications, increasing the likelihood of poor outcomes.⁴³

Moreover, SES influences exposure to air pollution and poor housing, two environmental factors that raise the risk of low birth weight and gestational hypertension.^44–46 Lead, particulate matter, sulfur dioxide, and ozone exposure are factors that cause oxidative stress, endocrine disruption, and vascular dysfunction. Preterm delivery and maternal depression are two APOs that are independently linked to the socioeconomic stresses associated with low SES, such as financial hardship and unemployment.⁴⁷ This complex interplay between socioeconomic disadvantages and maternal–fetal health underscores the urgent need for targeted interventions to mitigate these risks. Table 2 shows a summary of the association between SES and APOs.

Table 2.

Summary of Associations Between Socioeconomic Status and Adverse Pregnancy Outcomes

Variable	Preeclampsia (OR [95% CI])	Gestational hypertension (OR [95% CI])	GDM (OR [95% CI])	Preterm birth (OR [95% CI])	IUGR (OR [95% CI])	Macrosomia (OR [95% CI])	Placenta previa (OR [95% CI])
Low education level	4.91 (1.93–12.52)⁴⁸	1.74 (1.23–2.46)⁴⁹	3.07 (1.37–6.89)⁵⁰	1.59 (1.20–2.10)⁵¹	1.37 (1.01–1.87)⁵²	NA	NA
Low socioeconomic status	1.33 (0.59–2.94)⁵³	1.19 (1.14–1.18)⁵⁴	2.04 (1.07–3.89)⁵³	1.14 (1.10–1.17)⁵⁵	1.18 (1.15–1.21)⁵⁵	1.24 (1.14–1.36)⁵⁶	NA
Insurance status: Public/Uninsured	1.99^* (1.18–3.37)⁵⁷	NA	NA	1.15 (1.06–1.24)⁵⁸	NA	1.08 (0.57–2.04)⁵⁹	NA
Race: Non-Hispanic Black	1.41 (1.25–1.62)⁶⁰	NA	0.64 (0.56–0.74)⁶¹	1.51 (1.49–1.53)⁶²	1.39^* (1.13–1.72)⁶³	0.559 (0.572–0.546)⁶⁴	1.43 (1.19–1.72)⁶⁵

Hazard ratio.

GDM, gestational diabetes mellitus; IUGR, intrauterine growth restriction.

SES and cardiovascular outcomes

Low SES is a well-established contributor to increased CVD risk, associated with a higher prevalence of conditions such as diabetes, hypertension, coronary artery disease, congestive heart failure, and stroke.^66–68 This relationship is explained by biological and socioeconomic mechanisms, mediated by key surrogates of SES, including educational attainment, income level, employment status, and environmental factors.⁶⁹ These factors lead to lower health literacy, limited access to healthy food, substandard health care, and financial barriers to prescription drugs. For instance, the Jackson Heart Study revealed that neighborhood-level socioeconomic disadvantage correlated with higher rates of coronary heart disease.⁷⁰ Similarly, a study in the Netherlands found that low-income patients were less likely to undergo interventions like percutaneous coronary intervention after acute myocardial infarction.⁶⁹ These disparities extend to cardiovascular health among pregnant women from lower SES backgrounds who face higher risks of developing conditions such as preeclampsia, gestational diabetes, and intrauterine growth restriction, as shown in Table 3, all of which predispose them to CVD later in life.⁹² Limited access to quality health care, poor postpartum support, and ongoing socioeconomic problems are some factors that contribute to their increased vulnerability to long-term cardiovascular morbidity.^7,93

Table 3.

Summary of Associations Between Socioeconomic Status and Cardiovascular Disease

Condition	Heart failure (OR/HR [95% CI])	Stroke (OR/HR [95% CI])	Myocardial infarction (OR/HR [95% CI])	Coronary heart disease (OR/HR [95% CI])	Metabolic syndrome (OR/HR [95% CI])	Hypertension (OR/HR [95% CI])
Low educational level	1.64⁺ (1.37–2.0)⁷¹	1.41⁺ (1.16–1.71)⁷²	1.61^* (1.41–1.83)⁷³	NA	2.7⁺⁺ (1.1–6.8)⁷⁴	1.49⁺ (1.43–1.59)⁷⁵
Low socioeconomic status	Blacks: 1.39⁺(1.00–1.95) Whites: 1.32⁺ (1.06–1.64)⁷⁶	3.38^* (2.44–4.67)⁷⁷	1.136^* (1.12–1.136)⁷⁸	3.85^* (2.56–5.88)⁶⁷	2.81^* (1.46–5.43)⁷⁹	1.09^* (1.003–1.19)⁸⁰
Insurance status: Public/Uninsured	2.15⁺ (1.42–3.26)⁸¹	1.49^* (1.29–1.72)⁸²	1.52^* (1.24–1.85)⁸³	3.02^* (1.10–8.28)⁸⁴	NA	1.19^* (0.66–2.15)⁸⁵
Race: Non-Hispanic Black	2.63^* (1.71–4.05)⁸⁶	1.51⁺ (1.13–2.02)⁸⁷	1.29⁺ (0.92–1.81)⁸⁸	1.50⁺ (1.02–2.21)⁸⁹	1.20^* (1.02–1.40)⁹⁰	2.21^* (1.91–2.56)⁹¹

Hazard ratio.

Odds ratio.

Risk ratio.

HR, hazard ratio.

Potential mechanisms linking SES and APOs

SES significantly influences the development of APOs and the risk factors associated with CVD. Despite social mechanisms being the primary pathways through which SES impacts these conditions, molecular mechanisms also mediate long-term effects. Dysregulation of protein synthesis and inflammation is one speculated mechanism despite the marked paucity of data on such mechanisms. Research indicates that lower SES is correlated with heightened inflammation and immune system activation during pregnancy. A retrospective cohort study found that women from low SES backgrounds had significantly higher median serum concentrations of interleukin-6 (IL-6) at 13–18 weeks of gestation compared with their high SES counterparts.^71,72 IL-6 is a key protein associated with chronic inflammation and has been implicated in gestational complications, including preterm delivery.⁹⁴ Additionally, pregnant women from low SES backgrounds have been observed to have elevated oxidative stress. A pooled analysis across the United States evaluated urinary concentrations of 8-iso-prostaglandin F2α (8-iso-PGF2α)—an established biomarker of oxidative stress—at various times in the gestational period. The results indicated that women facing greater socioeconomic disadvantages exhibited higher levels of 8-iso-PGF2α in their urine.⁹⁵ This biomarker has been linked to preeclampsia, preterm birth, and SGA infants.^95,96 Moreover, psychosocial stress and depression contribute to inflammatory imbalances, increased adiposity, and immune dysregulation.⁹⁵ These factors increase the risk of complications such as SGA births, preterm delivery, and adverse outcomes postpartum.⁹⁷

Race and APOs

Impact of race on pregnancy outcomes

Black and Indigenous individuals experience disproportionately higher rates of APOs compared with White individuals.^6,98 Black women are over three times more likely to die from pregnancy-related complications than their White counterparts.⁶ Additionally, Black infants are more likely to be delivered preterm and have low birth weight.⁹⁹ These disparities persist even after controlling for socioeconomic factors,¹⁰⁰ highlighting the social determinants linked to race that heighten the risk of APOs.⁹³ Several factors contribute to these disparities, including racial bias, female underrepresentation in clinical trials, a lack of appreciation for nontraditional risk factors, and the undertreatment of disease.^6,93,99 Non-Hispanic Black infants experience higher rates of fetal death and infant mortality compared with White infants.¹⁰¹ Moreover, women from marginalized groups, including Black, American Indian/Alaska Native, and Native Hawaiian and Other Pacific Islander populations, after controlling for SES, face significantly higher risk of pregnancy-related mortality and morbidity, as well as higher incidences of preterm births, low birth weight, and inadequate prenatal care.¹⁰⁰

While biological factors, such as genetic predispositions to specific health conditions, may influence APOs, research indicates that environmental and health determinants play a more substantial role in racial disparities.^102–104 Some genetic polymorphisms are associated with preeclampsia; however, they are unlikely to account for all observed racial differences.^102,104 Socioeconomic disparities encompassing income levels, educational attainment, access to health care, and discrimination are pivotal in shaping these health inequities.¹⁰⁵ Individuals from the most affected racial and ethnic groups encounter various barriers at individual, provider, and health system levels. On a patient level, factors such as nontraditional risk factors, financial constraints, health literacy, and genetic variability come into play. At the provider level, implicit bias, underrecognition of atypical presentations, and suboptimal risk assessment further exacerbate disparities. Systemic issues, including a lack of diversity in clinical research, fragmented care, and insufficient infrastructure to meet diverse cultural needs, compound these challenges.¹⁰⁶ Moreover, individuals from racial minority groups often experience heightened stress due to discrimination and racism. Evidence suggests that these perceived and internalized stressors contribute to chronic inflammation and cardiovascular health disparities among minority populations, particularly minority women.^107,108 This chronic inflammation and toxic stress can lead to vascular damage, increasing the risk of inflammation-mediated APOs during pregnancy.^11,106–108 Chronic stress may also promote unhealthy behaviors such as smoking and substance abuse, along with physiological disturbances like hypertension and hormonal imbalances, all of which contribute to APOs.

Intersectionality: How race and SES intersect to exacerbate maternal cardiovascular disparities

Intersectionality, as articulated by Crenshaw (1991), highlights how overlapping social categorizations such as race, class, and gender create interconnected systems of disadvantage. The combined effects of race and SES intensify disparities in pregnancy outcomes, producing disproportionately adverse results for individuals experiencing multiple forms of marginalization. Historical injustices including slavery, segregation, and discriminatory health care policies have entrenched inequities in access to quality care and economic opportunity, particularly among Black and Indigenous communities.^109,110 For instance, Black women of lower SES face greater barriers to early and adequate prenatal care, fewer options for high-quality obstetric services, and higher rates of medical mistrust compared with White women of similar SES.⁶

The physiological toll of chronic stress from racism and poverty further compounds these inequities, increasing risks of hypertension, preterm birth, gestational diabetes, and preeclampsia, all of which elevate long-term cardiovascular risk.⁷⁶ A multisite prospective study demonstrated that individuals from racially marginalized groups with low SES experience the poorest pregnancy outcomes, indicating a synergistic rather than additive effect of race and socioeconomic disadvantage.¹¹¹ Specifically, Black birthing individuals from low SES backgrounds exhibit the highest rates of preterm delivery, preeclampsia, and SGA infants compared with both higher-SES Black women and White women of any SES.¹¹²

Geographic inequities further magnify these disparities. Rural areas report higher maternal mortality and cardiovascular risk factors than urban regions, with limited health care access, longer travel distances, and lower health literacy disproportionately affecting rural Indigenous, Black, and Hispanic women.¹¹³ These factors collectively restrict opportunities for timely diagnosis and management of hypertensive and metabolic disorders during pregnancy.

Optimizing pregnancy outcomes is essential, as pregnancy serves as a cardiovascular “stress test” with lasting implications for maternal health. Although complications such as preeclampsia and gestational diabetes increase future CVD risk, studies adjusting for race and SES show attenuation of these associations, suggesting that structural and social determinants are primary drivers of disparities rather than intrinsic biological differences.^114,115 Thus, inequities in health care access, neighborhood environment, income, and education sustain racial and geographic gaps in maternal cardiovascular outcomes. Addressing these disparities requires a comprehensive strategy that targets upstream social factors, mitigates structural inequities, and extends cardiovascular risk reduction beyond the postpartum period.

Addressing socioeconomic and racial disparities in cardiovascular health

Policy implications: Improving access to prenatal care, addressing social determinants of health

The research emphasizes how important social determinants of health (SDoH) are in influencing cardiovascular health and unfavorable pregnancy outcomes, especially in low SES and racially marginalized populations. The World Health Organization defines SDoH as the factors affecting people’s living situations, and it has a major impact on women’s health. Unfavorable pregnancy outcomes are increased when there is limited access to emergency services, wholesome food, suitable housing, and educational resources. Furthermore, to enhance maternal health and global public health outcomes, stressors such as racism, poverty, and unsafe living conditions call for immediate policy intervention.^116,117 Effective SDoH screening and referral require collaborative dialogue between patients and health care providers, fostering understanding of the associated risks and benefits. This approach can reduce stigma and improve health-seeking behaviors. The NC Maternal Mental Health MATTERS toolkit emphasizes how crucial it is to screen for hazardous SDoH in order to identify people who are at risk.¹¹⁸ Disparities in health care and resource access have been confirmed by recent studies, highlighting the necessity of policies that guarantee everyone gets safe SDoH.^118,119 Improving maternal cardiovascular outcomes and attaining health equity require addressing the factors contributing to SDoH inequities. Promoting paid maternity leave can help improve women’s health by allowing proper recovery without the stressor of not earning an income, which is a pressing issue for families living by paycheck.¹²⁰ Policies that promote women’s education can also reduce unwanted pregnancies and short birth intervals, which reduces unsafe practices for pregnancy termination and practices leading to high-risk pregnancies, such as quick concession conception and sexually transmitted diseases, while also providing women with greater occupational opportunities through educational advancement.¹²¹ In addition to improving access, universal health care and its expansion to neglected areas would advance gender equality and safer practices in prenatal care.¹¹⁷

Clinical interventions: Tailoring postpartum care for high-risk populations

The United States faces a higher incidence of mortality during or within 1 year of pregnancy compared with other high-income countries, despite significant investments in the health sector.^122–124 Approximately 83% of these pregnancy-related deaths are estimated to be preventable.¹²⁵ Alarmingly, the maternal mortality rate in the United States has risen from 7.2 per 100,000 live births in 1987 to 23.8 in 2020.^126,127 In response to this trend, the American College of Obstetricians and Gynecologists recommends that patients engage with their health care providers within 3 weeks postpartum, whether in person or via telehealth.^128,129 Following this initial contact, more comprehensive follow-up appointments should occur within 84 days postpartum.¹³⁰ However, a significant proportion of patients from low-income populations become disconnected from health care services after childbirth, and this further contributes to the disparities in health outcomes between low- and high-income groups.^131,132 This disengagement often results in inadequate screening and detection of future CVD.

Effective postpartum care depends on identifying people at risk using socioeconomic variables, including insurance status, employment, age, marital status, education, race, ethnicity, and proximity to health care facilities.^133,134 Substandard prenatal care remains a significant risk factor for poor postpartum follow-up.¹³⁵ Research consistently demonstrates that patients with private insurance from higher SESs are more likely to attend postpartum appointments than patients from lower socioeconomic backgrounds, especially those with public insurance such as Medicaid.¹³⁵ Interventions should concentrate on guaranteeing proper prenatal care, promoting early and frequent prenatal visits, and teaching underprivileged groups the value of prompt follow-ups in order to increase postpartum care attendance.¹³⁰ High-risk pregnancies require close monitoring throughout gestation to identify and address potential complications. Culturally tailored interventions such as phone reminders, text messages, home visits, and telehealth appointments are likely to improve compliance with postpartum follow-up.¹³⁰ Ultimately, expanding access to health care services is paramount for improving postpartum care attendance.

Future research directions

Understanding mechanisms

The processes by which racial and socioeconomic factors affect cardiovascular health after unfavorable pregnancy outcomes (APOs) are not well understood in the literature. Future studies should investigate whether there are prenatal common risk factors for CVD and whether APOs themselves increase the likelihood of developing CVD in the future. This could entail investigating the ways in which marginalized racial and ethnic groups are disproportionately impacted by SDoH, such as access to high-quality prenatal care, nutrition, and mental health assistance.

Policies and interventions

Future studies must concentrate on creating and assessing interventions that address racial and socioeconomic inequities in cardiovascular health. Community-based programs that encourage lifestyle changes, such as physical activity, nutrition education, and smoking cessation, as well as legislative efforts to eliminate systemic disparities in health care delivery and access, could be examples of these interventions. Improving the efficacy of these interventions will require addressing biases in health care systems and placing a strong emphasis on culturally competent care.

Longitudinal studies

Long-term, prospective studies are essential for long-term follow-up of individuals with APOs, assessing the cumulative risk of future CVD. Such research can provide valuable insights into the trajectory of CVD development and identify critical intervention periods. Understanding how socioeconomic and racial factors interplay in the progression of CVD can inform targeted prevention strategies, particularly for high-risk populations.

Precision medicine approaches

Research must investigate precision medicine strategies designed to meet the requirements of different ethnic and socioeconomic groups. This involves determining how genetic, epigenetic, environmental, and social factors interact to affect treatment outcomes and CVD risk. We can create individualized treatment plans that successfully address health inequities by integrating socioeconomic data into precision medicine frameworks.

Implementation science

Future studies should concentrate on implementation science to understand how evidence-based interventions can be effectively translated into real-world settings and adapted to diverse socioeconomic contexts. This includes investigating strategies for overcoming barriers to access, such as transportation and financial constraints, and identifying facilitators that promote the equitable uptake of cardiovascular health interventions among underrepresented communities.

Health equity policies

It is essential to examine the effect of health policies aimed at promoting equity in cardiovascular care. Future studies should assess the efficacy of policies that address SDoH—including housing stability, educational access, employment opportunities, and income support—in reducing cardiovascular disparities. An understanding of how these policies influence health outcomes across different racial and socioeconomic groups can inform more effective advocacy and reform initiatives.

Community engagement and participatory research

Community engagement in the research process is vital for developing culturally sensitive and contextually appropriate interventions to address socioeconomic disparities in cardiovascular health. Employing participatory research approaches can empower communities, ensuring that interventions reflect their needs and preferences. This collaborative effort fosters sustainable change and enhances community resilience against health disparities.

Future research focusing on racial and socioeconomic disparities in postpartum cardiovascular health is essential to advancing our understanding of these differences. Such investigations will provide critical insights necessary for the development of targeted interventions aimed at improving health outcomes and promoting health equity across diverse populations, irrespective of SES or race.

Conclusions

APOs, which might result in future CVD, are more likely to occur in people from poorer socioeconomic backgrounds and marginalized racial groups. These differences have a significant impact on cardiovascular health after pregnancy. These disparities result from environmental factors, toxic stress, and poor access to high-quality health care. We need health care policies that recognize the intricate relationships between gender, SES, and race to address these problems. By encouraging collaboration between legislators and medical professionals, we can address systemic disparities and increase access to high-quality care. Further research is necessary to better understand these differences and identify practical ways to help all women achieve improved health outcomes.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

Supplemental Material

Abbreviations

References

Parikh

, Gonzalez

, Anderson

CAM

, et al.; American Heart Association Council on Epidemiology and Prevention; Council on Arteriosclerosis, Thrombosis and Vascular Biology; Council on Cardiovascular and Stroke Nursing; and the Stroke Council. Adverse pregnancy outcomes and cardiovascular disease risk: Unique opportunities for cardiovascular disease prevention in women: A scientific statement from the American Heart Association. Circulation, 2021; 143(18):e902–e916.

Cardiovascular Journal of Africa: Vol 27 No 2 (March/April 2016) Internet. cited 2024 Nov 18. Available from: https://cvja.co.za/onlinejournal/vol27/vol27_issue2/files/assets/basic-html/page-35.html#

Crump

, Sundquist

, McLaughlin

, et al. Adverse pregnancy outcomes and long term risk of ischemic heart disease in mothers: National cohort and co-sibling study. BMJ, 2023; 380:e072112.

Rich-Edwards

, Fraser

, Lawlor

, et al. Pregnancy characteristics and women’s future cardiovascular health: An underused opportunity to improve women’s health? Epidemiol Rev, 2014; 36(1):57–70.

Sergeev

, Nyirati

. Abstract 296: Factors associated with inadequate prenatal care in women with pre-gestational hypertension. Circ: Cardiovascular Quality and Outcomes, 2012; 5(suppl_1).

Howell

. Reducing disparities in severe maternal morbidity and mortality. Clin Obstet Gynecol Internet, 2018; 61(2). Available from: https://journals.lww.com/clinicalobgyn/fulltext/2018/06000/reducing_disparities_in_severe_maternal_morbidity.22.aspx

Thomson

, Moffat

, Arisa

, et al. Socioeconomic inequalities and adverse pregnancy outcomes in the UK and Republic of Ireland: A systematic review and meta-analysis. BMJ Open, 2021; 11(3):e042753.

Bennett

, Stevens

, Mathers

, et al. NCD Countdown 2030: Worldwide trends in non-communicable disease mortality and progress towards Sustainable Development Goal target 3.4. Lancet, 2018; 392(10152):1072–1088.

Regitz-Zagrosek

, Oertelt-Prigione

, Prescott

, et al. Gender in cardiovascular diseases: Impact on clinical manifestations, management, and outcomes. Eur Heart J Internet, 2016; 37(1):24–34; doi: 10.1093/eurheartj/ehv598

10.

Bellamy

, Casas

, Hingorani

, et al. Type 2 diabetes mellitus after gestational diabetes: A systematic review and meta-analysis. Lancet, 2009; 373(9677):1773–1779.

11.

, Li

, Wang

, et al. The Association between hypertensive disorders in pregnancy and the risk of developing chronic hypertension. Front Cardiovasc Med, 2022; 9:897771.

12.

Adank

, Benschop

, van Streun

, et al. Gestational lipid profile as an early marker of metabolic syndrome in later life: A population-based prospective cohort study. BMC Med, 2020; 18(1):394.

13.

Venkatesh

, Khan

, Yee

, et al. Adverse pregnancy outcomes and predicted 30-year risk of maternal cardiovascular disease 2–7 years after delivery. Obstet Gynecol, 2024; 143(6). Available from: https://journals.lww.com/greenjournal/fulltext/2024/06000/adverse_pregnancy_outcomes_and_predicted_30_year.8.aspx

14.

Stuart

, Tanz

, Rimm

, et al. Cardiovascular risk factors mediate the long-term maternal risk associated with hypertensive disorders of pregnancy. J Am Coll Cardiol, 2022; 79(19):1901–1913.

15.

Williams

, Stout

, Rosenbloom

, et al. Preeclampsia predicts risk of hospitalization for heart failure with preserved ejection fraction. J Am Coll Cardiol, 2021; 78(23):2281–2290; doi: 10.1016/j.jacc.2021.09.1360

16.

de Havenon

, Delic

, Stulberg

, et al. Association of preeclampsia with incident stroke in later life among women in the Framingham Heart Study. JAMA Netw Open., 2021; 4(4):e215077; doi: 10.1001/jamanetworkopen.2021.5077

17.

Gastrich

, Zinonos

, Bachmann

, et al. Preeclamptic women are at significantly higher risk of future cardiovascular outcomes over a 15-year period. J Womens Health (Larchmt), 2020; 29(1):74–83; doi: 10.1089/jwh.2019.7671

18.

Yang

, Lee

, Choi

, et al. Subsequent risk of metabolic syndrome in women with a history of preeclampsia: Data from the Health Examinees Study. J Epidemiol, 2015; 25(4):281–288; doi: 10.2188/jea.JE20140136

19.

Edlow

, Srinivas

, Elovitz

. Investigating the risk of hypertension shortly after pregnancies complicated by preeclampsia. Am J Obstet Gynecol, 2009; 200(5):e60–e62; doi: 10.1016/j.ajog.2008.10.012

20.

Chang

, Ho

, Chen

, et al. Epidemiological profile and obstetric outcomes of patients with peripartum congestive heart failure in Taiwan: A retrospective nationwide study. BMC Pregnancy Childbirth, 2017; 17(1):302.

21.

Lykke

, Langhoff-Roos

, Sibai

, et al. Hypertensive pregnancy disorders and subsequent cardiovascular morbidity and type 2 diabetes mellitus in the mother. Hypertension, 2009; 53(6):944–951; doi: 10.1161/HYPERTENSIONAHA.109.130765

22.

Oliver-Williams

, Stevens

, Payne

, et al. Association between hypertensive disorders of pregnancy and later risk of cardiovascular outcomes. BMC Med, 2022; 20(1):19; doi: 10.1186/s12916-021-02218-8

23.

Rayes

, Ardissino

, Slob

EAW

, et al. Association of hypertensive disorders of pregnancy with future cardiovascular disease. JAMA Netw Open, 2023; 6(2):e230034; doi: 10.1001/jamanetworkopen.2023.0034

24.

, Lee

, Ha

. The presence of hypertension during pregnancy determines the future risk of metabolic syndrome: An observational study. Medicine (Baltimore), 2022; 101(42):e31272; doi: 10.1097/MD.0000000000031272

25.

Watanabe

, Sairenchi

, Nishida

, et al. Gestational hypertension as risk factor of hypertension in middle-aged and older women. Int J Environ Res Public Health, 2020; 17(11):4052; doi: 10.3390/ijerph17114052

26.

Echouffo-Tcheugui

, Guan

, Retnakaran

, et al. Gestational diabetes and incident heart failure: A cohort study. Diabetes Care, 2021; 44(10):2346–2352; doi: 10.2337/dc21-0552. Published online August 12.

27.

Heida

, Franx

, van Rijn

, et al. Earlier age of onset of chronic hypertension and type 2 diabetes mellitus after a hypertensive disorder of pregnancy or gestational diabetes mellitus. Hypertension, 2015; 66(6):1116–1122; doi: 10.1161/HYPERTENSIONAHA.115.06005

28.

Goueslard

, Cottenet

, Mariet

, et al. Early cardiovascular events in women with a history of gestational diabetes mellitus. Cardiovasc Diabetol, 2016; 15(1):15; doi: 10.1186/s12933-016-0338-0

29.

Daly

, Toulis

, Thomas

, et al. Increased risk of ischemic heart disease, hypertension, and type 2 diabetes in women with previous gestational diabetes mellitus, a target group in general practice for preventive interventions: A population-based cohort study. PLoS Med, 2018; 15(1):e1002488; doi: 10.1371/journal.pmed.1002488

30.

Kaiser

, Nielsen

, Kallfa

, et al. Metabolic syndrome in women with previous gestational diabetes. Sci Rep, 2021; 11(1):11558; doi: 10.1038/s41598-021-90832-0

31.

Bentley-Lewis

, Huynh

, Li

, et al. Hypertension risk subsequent to gestational dysglycemia is modified by race/ethnicity. Hypertension, 2016; 67(1):223–228; doi: 10.1161/HYPERTENSIONAHA.115.06360

32.

Crump

, Groves

, Sundquist

, et al. Association of preterm birth with long-term risk of heart failure into adulthood. JAMA Pediatr, 2021; 175(7):689–697; doi: 10.1001/jamapediatrics.2021.0131

33.

Catov

, Newman

, Roberts

, et al.; Health ABC Study. Preterm delivery and later maternal cardiovascular disease risk. Epidemiology, 2007; 18(6):733–739; doi: 10.1097/EDE.0b013e3181567f96

34.

Sipola-Leppanen

, Vaarasmaki

, Tikanmaki

, et al. Cardiometabolic risk factors in young adults who were born preterm. Am J Epidemiol, 2015; 181(11):861–873; doi: 10.1093/aje/kwu443

35.

Bukowski

, Davis

, Wilson

PWF

. Delivery of a small for gestational age infant and greater maternal risk of ischemic heart disease. PLoS One, 2012; 7(3):e33047; doi: 10.1371/journal.pone.0033047

36.

Catov

, Dodge

, Yamal

, et al. Prior preterm or small-for-gestational-age birth related to maternal metabolic syndrome. Obstet Gynecol, 2011; 117(2 Pt 1):225–232; doi: 10.1097/AOG.0b013e3182075626

37.

Kulthamrongsri

, Piewluang

, Suenghataiphorn

, et al. Exploring the link between fetal macrosomia in pregnancy and long-term heart failure risk: Insights from NHANES 2017-2020. J Am Coll Cardiol, 2025; 85(12):2641; doi: 10.1016/S0735-1097(25)03125-0

38.

, Wang

, Gu

, et al. Previous delivery of macrosomia is associated with maternal adiposity in later life in Chinese parous women with normal weight before and/or after pregnancy. Endocr Pract, 2019; 25(11):1176–1183; doi: 10.4158/EP-2019-0075

39.

Salihu

, Weldeselasse

, Rao

, et al. The impact of obesity on maternal morbidity and feto-infant outcomes among macrosomic infants. J Matern Fetal Neonatal Med, 2011; 24(9):1088–1094; doi: 10.3109/14767058.2010.546451

40.

Braveman

, Barclay

. Health disparities beginning in childhood: A life-course perspective. Pediatrics, 2009; 124(Suppl 3):S163–S175.

41.

Kramer

, Séguin

, Lydon

, et al. Socio-economic disparities in pregnancy outcome: Why do the poor fare so poorly? Paediatr Perinat Epidemiol, 2000; 14(3):194–210.

42.

Braveman

, Cubbin

, Egerter

, et al. Socioeconomic disparities in health in the United States: What the patterns tell us. Am J Public Health, 2010; 100(Suppl 1):S186–S196.

43.

Ladak

, Grewal

, Kim

, et al. Equity in prenatal healthcare services globally: An umbrella review. BMC Pregnancy Childbirth, 2024; 24(1):191.

44.

Triche

, Hossain

. Environmental factors implicated in the causation of adverse pregnancy outcome. Semin Perinatol, 2007; 31(4):240–242.

45.

Fussell

, Jauniaux

, Smith

, et al. Ambient air pollution and adverse birth outcomes: A review of underlying mechanisms. BJOG, 2024; 131(5):538–550.

46.

Mazumder

, Rimu

, Shimul

, et al. Maternal health outcomes associated with ambient air pollution: An umbrella review of systematic reviews and meta-analyses. Sci Total Environ, 2024; 914:169792.

47.

Margerison-Zilko

, Li

, Luo

. Economic conditions during pregnancy and adverse birth outcomes among singleton live births in the United States, 1990-2013. Am J Epidemiol, 2017; 186(10):1131–1139.

48.

Silva

, Coolman

, Steegers

, et al. Low socioeconomic status is a risk factor for preeclampsia: The Generation R Study. J Hypertens, 2008; 26(6):1200–1208; doi: 10.1097/HJH.0b013e3282fcc36e

49.

Maher

, Ward

, Hernandez

, et al. Association between socioeconomic status with pregnancy and neonatal outcomes: An international multicenter cohort. Acta Obstet Gynecol Scand, 2023; 102(11):1459–1468; doi: 10.1111/aogs.14659

50.

Bouthoorn

, Silva

, Murray

, et al. Low-educated women have an increased risk of gestational diabetes mellitus: The Generation R Study. Acta Diabetol, 2015; 52(3):445–452; doi: 10.1007/s00592-014-0668-x

51.

Dunlop

, Burjak

, Dean

, et al. Association of maternal education, neighborhood deprivation, and racial segregation with gestational age at birth by maternal race/ethnicity and United States Census region in the ECHO cohorts. Front Public Health, 2023; 11:1165089; doi: 10.3389/fpubh.2023.1165089

52.

Swaminathan

, Lahaie Luna

, Rennicks White

, et al. The influence of maternal and paternal education on birth outcomes: An analysis of the Ottawa and Kingston (OaK) birth cohort. J Matern Fetal Neonatal Med, 2022; 35(25):9631–9638; doi: 10.1080/14767058.2022.2049751

53.

Bittner

JMP

, Gilman

, Zhang

, et al. Relationships between early-life family poverty and relative socioeconomic status with gestational diabetes, preeclampsia, and hypertensive disorders of pregnancy later in life. Ann Epidemiol, 2023; 86:8–15; doi: 10.1016/j.annepidem.2023.08.002

54.

Nicholls-Dempsey

, Badeghiesh

, Baghlaf

, et al. How does high socioeconomic status affect maternal and neonatal pregnancy outcomes? A population-based study among American women. Eur J Obstet Gynecol Reprod Biol X, 2023; 20:100248; doi: 10.1016/j.eurox.2023.100248

55.

Luo

Z-C

, Wilkins

, Kramer

, Fetal and Infant Health Study Group of the Canadian Perinatal Surveillance System. Effect of neighbourhood income and maternal education on birth outcomes: A population-based study. CMAJ, 2006; 174(10):1415–1420; doi: 10.1503/cmaj.051096

56.

Boubred

, Pauly

, Romain

, et al. The role of neighbourhood socioeconomic status in large for gestational age. PLoS One, 2020; 15(6):e0233416; doi: 10.1371/journal.pone.0233416

57.

Cerón-Mireles

, Harlow

, Sánchez-Carrillo

, et al. Risk factors for pre-eclampsia/eclampsia among working women in Mexico City. Paediatr Perinat Epidemiol, 2001; 15(1):40–46.

58.

Thermidor

, Gaballa

, Hentz

, et al. Clinical, sociodemographic, and neighborhood characteristics associated with adverse pregnancy outcomes. J Womens Health (Larchmt), 2024; 33(3):308–317; doi: 10.1089/jwh.2023.0032

59.

Hiratsuka

, Reid

, Chang

, et al. Associations between rurality, pre-pregnancy health status, and macrosomia in American Indian/Alaska native populations. Matern Child Health J, 2022; 26(12):2454–2465; doi: 10.1007/s10995-022-03536-w

60.

Caughey

, Stotland

, Washington

, et al. Maternal ethnicity, paternal ethnicity, and parental ethnic discordance: Predictors of preeclampsia. Obstet Gynecol, 2005; 106(1):156–161; doi: 10.1097/01.AOG.0000164478.91731.06

61.

Liu

, Lamerato

, Misra

. A retrospective analysis of the relationship between race/ethnicity, age at delivery and the risk of gestational diabetes mellitus. The Journal of Maternal-Fetal & Neonatal Medicine, 2020; 33(17):2961–2969; doi: 10.1080/14767058.2019.1566310

62.

Blebu

, Waters

, Lucas

, et al. Variations in maternal factors and preterm birth risk among non-Hispanic Black, White, and mixed-race Black/White women in the United States, 2017. Womens Health Issues, 2022; 32(2):140–146; doi: 10.1016/j.whi.2021.10.010

63.

Sheikh

, Allotey

, Kew

, et al.; IPPIC Collaborative Network. Effects of race and ethnicity on perinatal outcomes in high-income and upper-middle-income countries: An individual participant data meta-analysis of 2 198 655 pregnancies. Lancet, 2022; 400(10368):2049–2062; doi: 10.1016/S0140-6736(22)01191-6

64.

Mydam

, Mellacheruvu

, Coler

, et al. The effect of maternal race, ethnicity, and nativity on macrosomia among infants born to mothers in the United States. Cureus, 2023; 15(5):e39391; doi: 10.7759/cureus.39391. Published online May 23.

65.

Kim

, Caughey

, Laguardia

, et al. Racial and ethnic differences in the prevalence of placenta previa. J Perinatol, 2012; 32(4):260–264; doi: 10.1038/jp.2011.86

66.

Odutayo

, Gill

, Shepherd

, et al. Income disparities in absolute cardiovascular risk and cardiovascular risk factors in the United States, 1999–2014. JAMA Cardiol, 2017; 2(7):782–790.

67.

Minhas

AMK

, Jain

, Li

, et al. Family income and cardiovascular disease risk in American adults. Sci Rep, 2023; 13(1):279.

68.

, Zhu

, Bundy

, et al. Trends in cardiovascular risk factors in US adults by race and ethnicity and socioeconomic status, 1999–2018. JAMA Internet, 2021; 326(13):1286–1298.

69.

Schultz

, Kelli

, Lisko

, et al. Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation, 2018; 137(20):2166–2178.

70.

Barber

, Hickson

, Kawachi

, et al. Neighborhood disadvantage and cumulative biological risk among a socioeconomically diverse sample of African American adults: An examination in the Jackson Heart Study. J Racial Ethn Health Disparities, 2016; 3(3):444–456.

71.

Christensen

, Mogelvang

, Heitmann

, et al. Level of education and risk of heart failure: A prospective cohort study with echocardiography evaluation. Eur Heart J, 2011; 32(4):450–458; doi: 10.1093/eurheartj/ehq435

72.

Jackson

, Sudlow

CLM

, Mishra

. Education, sex and risk of stroke: A prospective cohort study in New South Wales, Australia. BMJ Open, 2018; 8(9):e024070; doi: 10.1136/bmjopen-2018-024070

73.

Kelly

, Weitzen

. The association of lifetime education with the prevalence of myocardial infarction: An analysis of the 2006 Behavioral Risk Factor Surveillance System. J Community Health, 2010; 35(1):76–80; doi: 10.1007/s10900-009-9189-x

74.

Wamala

, Lynch

, Horsten

, et al. Education and the metabolic syndrome in women. Diabetes Care, 1999; 22(12):1999–2003; doi: 10.2337/diacare.22.12.1999

75.

Sun

, Lin

, Li

, et al. Association of education levels with the risk of hypertension and hypertension control: A nationwide cohort study in Chinese adults. J Epidemiol Community Health, 2022; 76(5):451–457; doi: 10.1136/jech-2021-217006. Published online January 7.

76.

Roberts

, Couper

, Chang

, et al. Influence of life-course socioeconomic position on incident heart failure in blacks and whites: The atherosclerosis risk in communities study. Am J Epidemiol, 2010; 172(6):717–727; doi: 10.1093/aje/kwq193

77.

Fan

, Ma

, Liu

, et al. Associations between socioeconomic status and stroke in American adults: A population-based study. Prev Med Rep, 2023; 35:102354; doi: 10.1016/j.pmedr.2023.102354

78.

Matetic

, Bharadwaj

, Mohamed

, et al. Socioeconomic status and differences in the management and outcomes of 6.6 million US patients with acute myocardial infarction. Am J Cardiol, 2020; 129:10–18; doi: 10.1016/j.amjcard.2020.05.025

79.

Kim

, Kim

, Cho

. Socioeconomic status in association with metabolic syndrome and coronary heart disease risk. Korean J Fam Med, 2013; 34(2):131–138; doi: 10.4082/kjfm.2013.34.2.131

80.

Kaplan

, Huguet

, Feeny

, et al. Self-reported hypertension prevalence and income among older adults in Canada and the United States. Soc Sci Med, 2010; 70(6):844–849; doi: 10.1016/j.socscimed.2009.11.019

81.

Fujito

, Kitano

, Saito

, et al. Association between the health insurance status and clinical outcomes among patients with acute heart failure in Japan. Heart Vessels, 2022; 37(1):83–90; doi: 10.1007/s00380-021-01895-y

82.

Hasan

, Orav

, Hicks

. Insurance status and hospital care for myocardial infarction, stroke, and pneumonia. J Hosp Med, 2010; 5(8):452–459; doi: 10.1002/jhm.687

83.

Parikh

, Gruberg

, Jeremias

, et al. Association of health insurance status with presentation and outcomes of coronary artery disease among nonelderly adults undergoing percutaneous coronary intervention. Am Heart J, 2011; 162(3):512–517; doi: 10.1016/j.ahj.2011.06.002

84.

Brooks

, Preis

, Hwang

, et al. Health insurance and cardiovascular disease risk factors. Am J Med, 2010; 123(8):741–747; doi: 10.1016/j.amjmed.2010.02.013

85.

Talha

, Almas

, Minhas

AMK

, et al. Disparities in heart failure between White, Black, and Hispanic young adults: Insights from the National Health and Nutrition Examination Survey. Ther Adv Cardiovasc Dis, 2024; 18:17539447241239814; doi: 10.1177/17539447241239814

86.

Gardener

, Sacco

, Rundek

, et al. Race and ethnic disparities in stroke incidence in the Northern Manhattan Study. Stroke, 2020; 51(4):1064–1069; doi: 10.1161/STROKEAHA.119.028806

87.

Spertus

, Jones

, Masoudi

, et al. Factors associated with racial differences in myocardial infarction outcomes. Ann Intern Med, 2009; 150(5):314–324; doi: 10.7326/0003-4819-150-5-200903030-00007

88.

Safford

, Brown

, Muntner

, et al.; REGARDS Investigators. Association of race and sex with risk of incident acute coronary heart disease events. JAMA, 2012; 308(17):1768–1774; doi: 10.1001/jama.2012.14306

89.

Moore

, Chaudhary

, Akinyemiju

. Metabolic syndrome prevalence by race/ethnicity and sex in the United States, National Health and Nutrition Examination Survey, 1988-2012. Prev Chronic Dis, 2017; 14:E24; doi: 10.5888/pcd14.160287

90.

Kramer

, Han

, Post

, et al. Racial/ethnic differences in hypertension and hypertension treatment and control in the multi-ethnic study of atherosclerosis (MESA). Am J Hypertens, 2004; 17(10):963–970; doi: 10.1016/j.amjhyper.2004.06.001

91.

Muscatell

, Brosso

, Humphreys

. Socioeconomic status and inflammation: A meta-analysis. Mol Psychiatry, 2020; 25(9):2189–2199. Available from: https://pubmed.ncbi.nlm.nih.gov/31628416/

92.

Shah

, Varma

, Nasir

, et al. Reducing disparities in adverse pregnancy outcomes in the United States. Am Heart J, 2021; 242:92–102.

93.

Garapati

, Jajoo

, Aradhya

, et al. Postpartum mood disorders: Insights into diagnosis, prevention, and treatment. Cureus Internet, 2023; 15(7):e42107.

94.

Poliektov

, Forrest

, Easley

, et al. Characterization of the maternal serum inflammatory profile during pregnancy according to socioeconomic status. Am J Reprod Immunol Internet, 2023; 90(6). Available from: https://pubmed.ncbi.nlm.nih.gov/38009052/

95.

Prins

, Gomez-Lopez

, Robertson

. Interleukin-6 in pregnancy and gestational disorders. J Reprod Immunol, 2012; 95(1–2):1–14.

96.

Eick

, Geiger

, Alshawabkeh

, et al. Associations between social, biologic, and behavioral factors and biomarkers of oxidative stress during pregnancy: Findings from four ECHO cohorts. Sci Total Environ Internet, 2022; 835. Available from: https://pubmed.ncbi.nlm.nih.gov/35490822/

97.

Boldeanu

, Văduva

C-C

, Caragea

, et al. Association between serum 8-iso-prostaglandin F2α as an oxidative stress marker and immunological markers in a cohort of preeclampsia patients. Life (Basel), 2023; 13(12):2242.

98.

Miller

, Culhane

, Grobman

, et al. Mothers’ childhood hardship forecasts adverse pregnancy outcomes: Role of inflammatory, lifestyle, and psychosocial pathways. Brain Behav Immun, 2017; 65:11–19.

99.

Bryant

, Worjoloh

, Caughey

, et al. Racial/ethnic disparities in obstetric outcomes and care: Prevalence and determinants. Am J Obstet Gynecol, 2010; 202(4):335–343.

100.

Racial disparities in maternal and infant health: Current status and efforts to address them | KFF Internet. cited 2024 Nov 18. Available from: https://www.kff.org/racial-equity-and-health-policy/issue-brief/racial-disparities-in-maternal-and-infant-health-current-status-and-efforts-to-address-them/

101.

Lorch

, Enlow

. The role of social determinants in explaining racial/ethnic disparities in perinatal outcomes. Pediatr Res, 2016; 79(1–2):141–147.

102.

Conklin

, Wells

, Doe

, et al. Understanding health disparities in preeclampsia: A literature review. Am J Perinatol, 2024; 41(S 01):e1291–e1300.

103.

Johnson

, Louis

. 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.

104.

Minopoli

, Noël

, Dagge

, et al. Maternal ethnicity and socioeconomic deprivation: Influence on adverse pregnancy outcomes. Ultrasound Obstet Gynecol, 2024; 64(2):187–192.

105.

Simoncic

, Deguen

, Enaux

, et al. A comprehensive review on social inequalities and pregnancy outcome-identification of relevant pathways and mechanisms. Int J Environ Res Public Health, 2022; 19(24):16592.

106.

Conway-Phillips

, Dagadu

, Motley

, et al. Qualitative evidence for resilience, stress, and ethnicity (RiSE): A program to address race-based stress among Black women at risk for cardiovascular disease. Complement Ther Med, 2020; 48:102277.

107.

Mwendwa

, Sims

, Madhere

, et al. The influence of coping with perceived racism and stress on lipid levels in African Americans. J Natl Med Assoc, 2011; 103(7):594–601.

108.

Kershaw

, Lewis

, Diez Roux

, et al. Self-reported experiences of discrimination and inflammation among men and women: The multi-ethnic study of atherosclerosis. Health Psychol, 2016; 35(4):343–350.

109.

Bailey

, Krieger

, Agénor

, et al. Structural racism and health inequities in the USA: Evidence and interventions. Lancet, 2017; 389(10077):1453–1463.

110.

Creanga

, Bateman

, Kuklina

, et al. Racial and ethnic disparities in severe maternal morbidity: A multistate analysis, 2008-2010. Am J Obstet Gynecol, 2014; 210(5):435.e1–435.e8.

111.

Lee

, Park

, Boylan

. Cardiovascular health at the intersection of race and gender: Identifying life-course processes to reduce health disparities. J Gerontol B Psychol Sci Soc Sci, 2021; 76(6):1127–1139.

112.

Keenan-Devlin

, Smart

, Grobman

, et al. The intersection of race and socioeconomic status is associated with inflammation patterns during pregnancy and adverse pregnancy outcomes. Am J Reprod Immunol Internet, 2022; 87(3). Available from: https://pubmed.ncbi.nlm.nih.gov/34958140/

113.

Harrington

, Cameron

, Culler

, et al. Rural-urban disparities in adverse maternal outcomes in the United States, 2016-2019. Am J Public Health, 2023; 113(2):224–227.

114.

Minhas

, Ogunwole

, Vaught

, et al. Racial disparities in cardiovascular complications with pregnancy-induced hypertension in the United States. Hypertension, 2021; 78(2):480–488; doi: 10.1161/HYPERTENSIONAHA.121.17104

115.

Søndergaard

, Hlatky

, Stefanick

, et al. Association of adverse pregnancy outcomes with risk of atherosclerotic cardiovascular disease in postmenopausal women. JAMA Cardiol, 2020; 5(12):1390–1398; doi: 10.1001/jamacardio.2020.4097

116.

A Conceptual Framework for Action on the Social Determinants of Health Internet. cited 2024 Nov 18. Available from: https://www.who.int/publications/i/item/9789241500852

117.

Girardi

, Longo

, Bremer

. Social determinants of health in pregnant individuals from underrepresented, understudied, and underreported populations in the United States. Int J Equity Health, 2023; 22(1):186.

118.

MATTERS_Toolkit-Brief-Nov-2019.

119.

Tully

, Gibson

, Pearsall

, et al. Screening and referral for social determinants of health: Maternity patient and health care team perspectives. Health Equity, 2022; 6(1):887–897.

120.

Crear-Perry

, Correa-de-Araujo

, Lewis Johnson

, et al. Social and structural determinants of health inequities in maternal health. J Womens Health (Larchmt), 2021; 30(2):230–235; doi: 10.1089/jwh.2020.8882

121.

Weitzman

. The effects of women’s education on maternal health: Evidence from Peru. Soc Sci Med, 2017; 180:1–9; doi: 10.1016/j.socscimed.2017.03.004

122.

(15) (PDF) Maternal mortality and maternity care in the United States compared to 10 other developed countries Internet. cited 2024 Nov 18. Available from: https://www.researchgate.net/publication/347257336_Maternal_Mortality_and_Maternity_Care_in_the_United_States_Compared_to_10_Other_Developed_Countries

123.

Shulman

, D’Angelo

, Harrison

, et al. The pregnancy risk assessment monitoring system (PRAMS): Overview of design and methodology. Am J Public Health, 2018; 108(10):1305–1313.

124.

Thakrar

, Forrest

, Maltenfort

, et al. Child mortality in the US and 19 OECD comparator nations: A 50-year time-trend analysis. Health Aff (Millwood) Internet, 2018; 37(1):140–149. Available from: https://pubmed.ncbi.nlm.nih.gov/29309221/

125.

Illinois maternal morbidity and mortality report. 2016.

126.

Martin

, Hamilton

, Osterman

MJK

. Births in the United States, 2018 Key findings data from the National Vital Statistics System. 2018. Available from: https://www.cdc.gov/nchs/products/index.htm

127.

Hoyert

. Maternal mortality rates in the United States, 2020. 2022. 2021. Available from: https://stacks.cdc.gov/view/cdc/113967

128.

Stuebe

, Auguste

, Gulati

. ACOG Committee Opinion No. 736: Optimizing Postpartum Care. Obstet Gynecol, 2018131(5):E140–E50. Available from: https://pubmed.ncbi.nlm.nih.gov/29683911/

129.

Paladine

, Blenning

, Strangas

. Postpartum care: An approach to the fourth trimester. Am Fam Physician, 2019; 100(8):485–491. Available from: https://www.aafp.org/pubs/afp/issues/2019/1015/p485.html

130.

Tenfelde

, Joyce

, Tell

, et al. Reducing disparities in postpartum care utilization: Development of a clinical risk assessment tool. J Midwifery Womens Health, 2023; 68(2):179–186.

131.

Howell

, Balbierz

, Beane

, et al. Timely postpartum visits for low-income women: A health system and medicaid payer partnership. Am J Public Health, 2020; 110(S2):S215–S218.

132.

Geissler

, Ranchoff

, Cooper

, et al. Association of insurance status with provision of recommended services during comprehensive postpartum visits. JAMA Netw Open, 2020; 3(11):e2025095.

133.

Wilcox

, Levi

, Garrett

. Predictors of non-attendance to the postpartum follow-up visit. Matern Child Health J, 2016; 20(Suppl 1):22–27.

134.

Dibari

, Yu

, Chao

, et al. Use of postpartum care: Predictors and barriers. J Pregnancy. 2014. 2014. Available from: https://pubmed.ncbi.nlm.nih.gov/24693433/

135.

Morgan

, Hughes

, Belcher

, et al. Maternal sociodemographic characteristics, experiences and health behaviors associated with postpartum care utilization: Evidence from Maryland PRAMS dataset, 2012-2013. Matern Child Health J, 2018; 22(4):589–598.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.02 MB

Socioeconomic Disparities in Adverse Cardiovascular Pregnancy Outcomes: The Intersection of Race and Socioeconomic Status

Abstract

Background:

Methods:

Results:

Conclusions:

Keywords

Introduction

Methods

Association between APOs and cardiovascular complications

Socioeconomic disparities in APOs

Impact of SES on pregnancy outcomes

SES and cardiovascular outcomes

Potential mechanisms linking SES and APOs

Race and APOs

Impact of race on pregnancy outcomes

Intersectionality: How race and SES intersect to exacerbate maternal cardiovascular disparities

Addressing socioeconomic and racial disparities in cardiovascular health

Policy implications: Improving access to prenatal care, addressing social determinants of health

Clinical interventions: Tailoring postpartum care for high-risk populations

Future research directions

Understanding mechanisms

Policies and interventions

Longitudinal studies

Precision medicine approaches

Implementation science

Health equity policies

Community engagement and participatory research

Conclusions

Footnotes

Author Disclosure Statement

Funding Information

Supplemental Material

Abbreviations

References

Supplementary Material