Racial/Ethnic Differences in Socioeconomic Status and Medical Correlates of Trial of Labor After Cesarean and Vaginal Birth After Cesarean

Abstract

Objectives:

Black and Latinx women have higher rates of trial of labor after cesarean (TOLAC) compared with White women, but lower rates of vaginal birth after cesarean (VBAC). This study examined potential racial/ethnic differences in correlates of TOLAC and VBAC.

Materials and Methods:

The analytic sample includes term, singleton hospital births to women with one prior cesarean in birth certificate data for 2016. We estimated associations between medical factors (diabetes, hypertension, and prepregnancy obesity) and socioeconomic status (education level and insurance type) and TOLAC and VBAC using logistic regression, stratifying by race/ethnicity and testing whether coefficients differed across models.

Results:

Hypertension and obesity were more strongly related to reduced chances of TOLAC among White women than among women of color. For example, having a body mass index (BMI) between 30 and 39 (vs. normal BMI) was associated with a 6.3 percentage-point (pp) lower probability of TOLAC for White women, a 5.9 pp lower probability for Black women, and 2.9 pp lower probability for Latinx women. Paying out-of-pocket for birth was associated with a 5.5 pp increase in the probability of TOLAC among White women, versus a 3.2 pp decrease among Black women. Overweight and obesity were associated with lower probability of VBAC, but the magnitude of this association was smaller for Black and Latinx women than for White women.

Conclusions:

More research is needed to elucidate the underlying decision-making processes that lead to these associations. Future work should focus on ensuring equity in access to VBAC-supportive providers and hospitals and fostering informed decision-making after a prior cesarean.

Introduction

Despite small decreases in the U.S. cesarean rate in recent years, the overall cesarean rate remains high, at 32% of births.^1,2 The rate of vaginal birth after cesarean (VBAC) delivery is an important determinant of the overall cesarean rate, and it is a public health goal to increase the VBAC rate.³ There are well-documented racial/ethnic disparities in cesarean delivery, with Black and Latinx women more likely to deliver by cesarean compared with White women.^4

–9 For women with a prior cesarean, Black women are more likely to have a trial of labor compared with White women, but less likely to have a VBAC.^10
–12 Latinx women have a similar or lower likelihood of trial of labor after cesarean (TOLAC) compared with White women, but are less likely to have a VBAC.^12,13

Rates of maternal morbidity and mortality are higher among Black and Latinx women compared with White women.^14

–17 For women who have had a prior cesarean, maternal morbidity is least likely among women who have a successful VBAC, and highest among women who have a TOLAC that ends in an unplanned cesarean.¹⁸ Severe morbidity is also more likely the more cesareans a woman has.^18,19 This suggests that maternal morbidity may be further heightened for childbearing women of color who have a cesarean birth. A better understanding of why women of color are less likely to have a successful VBAC may have important implications for racial/ethnic disparities in maternal morbidity.

TOLAC rates and chances of VBAC success among women with TOLAC are impacted by both clinical and nonclinical factors.²⁰ Several studies have documented associations between measures of socioeconomic status (SES) and cesarean delivery generally, although some of these results are conflicting. For example, higher levels of education are associated with decreased chances of cesarean delivery,⁸ whereas private insurance—which is an indicator of higher income—is associated with increased chances of cesarean delivery relative to Medicaid.^21
–23 The relationship between SES and cesarean delivery or VBAC may change over time as practice patterns change, and few recent studies have addressed the relationship between SES and TOLAC and VBAC specifically.^20,24

An analysis of 2016 birth certificate data found that privately insured women were slightly less likely to have a TOLAC compared with women with Medicaid coverage, and also slightly less likely to have a VBAC among the subgroup with TOLAC.¹² This study also found a nonlinear relationship between education level and TOLAC/VBAC; women with less than a high school degree had substantially higher chances of TOLAC and successful VBAC, whereas higher levels of education were only associated with very small differences in chances of TOLAC and VBAC success.¹² However, the relationship between SES and cesarean delivery varies based on race/ethnicity⁸; this may also be the case for TOLAC and VBAC, but has not been explored empirically.

In addition, clinical factors may be taken into consideration in TOLAC decisions, and can also impact VBAC success among those with TOLAC. Medical risk factors, including obesity, diabetes, and hypertension, are more prevalent among pregnant women of color. Specifically, Black and Latinx women are more likely to be overweight or obese compared with White women.²⁵ Type 2 and gestational diabetes are more prevalent among Latinx versus White pregnant women,^26,27 and chronic hypertension is more common among Black versus White pregnant women.²⁸ A number of studies have shown reduced chances of VBAC success for women with obesity, hypertension, and diabetes, relative to women without these conditions.^29

–34 Although these medical characteristics impact VBAC success, they are far from deterministic. A 2015 study using Ohio birth certificate data found that only 17% of women with hypertension, diabetes, or obesity had TOLAC, but among those that did, 68% were successful.³⁵

Despite strong evidence of racial/ethnic differences in TOLAC uptake and VBAC success, it is unclear whether correlates of TOLAC and VBAC are different depending on a woman's race/ethnicity. Differences in correlates of TOLAC and VBAC success across racial/ethnic groups may reflect clinical and nonclinical factors, including exposure to structural and interpersonal racism.^36
–38 In this analysis, we examined potential racial/ethnic differences in the association between SES characteristics, medical characteristics, and TOLAC and VBAC.

Materials and Methods

Data and sample

This study used publicly available birth certificate data for 2016, which contains information on all births in the United States. The University of Massachusetts Amherst IRB determined that this was not human subjects research. The analytic sample was limited to singleton, term births to women with one prior cesarean that took place in the hospital. In addition, we restricted the sample to second births, as women with higher-order births and only one prior cesarean have had a previous vaginal birth, which greatly increases the chances of successful VBAC.¹³ The birth certificate ascertains race and Hispanic origin in separate fields, but the processed data include a merged race and Hispanic origin variable. Using this merged variable, we included in the analytic sample women who identified as White and not of Hispanic origin (“White”), Black and not of Hispanic origin (“Black”), or of any Hispanic origin (“Latinx”).

Measures

There were two outcome measures in this study: TOLAC (vs. planned repeat cesarean) and VBAC (vs. unplanned repeat cesarean) among women with a TOLAC. Women who had a cesarean delivery without a trial of labor were categorized as having a planned repeat cesarean. We categorized women as having a TOLAC if they had a trial of labor and a cesarean delivery, or if they had a VBAC. Among those with a trial of labor, those who gave birth vaginally were categorized as having a VBAC, whereas those who had a cesarean were categorized as having an unplanned repeat cesarean.

There were two categories of key predictor variables: measures of SES and medical factors impacting pregnancy. Measures of SES were (1) education level (less than high school, high school completed, some college, Bachelor's degree, graduate degree); and (2) insurance type (private insurance, Medicaid, self-pay, other). Medical factors impacting pregnancy were (1) prepregnancy diabetes or gestational diabetes; (2) prepregnancy hypertension or gestational hypertension; and (3) prepregnancy body mass index (BMI) category (underweight, normal, overweight, obesity, and extreme obesity).

We also included several control variables in our analyses: maternal age category, maternal residence in the county where the birth occurred, nativity, marital status, the Kotelchuck adequacy of prenatal care index,^39,40 WIC program participation, any cigarette use during pregnancy, and gestational age category (early term, term, late term). To retain observations, we constructed a missing category for each independent variable.

Analysis

First, we examined SES and medical characteristics by race/ethnicity, using chi-square tests to detect significant differences. Then we estimated multivariate logistic regression models for TOLAC and VBAC, including interaction terms between race/ethnicity and each SES and medical characteristic variable to identify statistically significant differences in associations by race/ethnicity. Finally, for interpretability,⁴¹ we estimated separate models for each race/ethnicity and outcome variable, and calculated average marginal effects. All analyses were conducted in Stata 15.

Results

There were 198,391 women in the analytic sample. Characteristics by race/ethnicity are given in Table 1. Just <8% of White and Black women had pregestational or gestational diabetes, whereas the prevalence of diabetes was ∼9% among Latinx women. Hypertension was least common among Latinx women (5.5%), and most common among Black women (10.2%). Overweight and obesity were more common among women of color than among White women. About 33% of White women and Latinx women were obese according to their prepregnancy BMI, compared with 45% of Black women. White women had higher education levels than Black and Latinx women, with 45% having a Bachelor's degree or higher, compared with 24% of Black women and 19% of Latinx women. Insurance type differed markedly by race/ethnicity, with 69% of White women covered by private insurance, compared with 34% among Black and Latinx women. There were statistically significant differences in TOLAC and VBAC rates by race/ethnicity. Among White women, 16% had TOLAC, versus 19% of Black women and 18% of Latinx women. Sixty-six percent of White women with TOLAC had a VBAC, versus 55% of Black women and 62% of Latinx women.

Table 1.

Characteristics of Women with One Prior Cesarean and a Singleton Hospital Birth by Race/Ethnicity, United States, 2016 (N = 198,391)

	White		Black		Latinx		p
	n	%	n	%	n	%	p
Any diabetes							<0.001
No	11,5407	92.3	28,291	92.1	38,822	91.2
Yes	9,687	7.7	2,415	7.9	3,769	8.9
Any hypertension							<0.001
No	116,043	92.8	27,588	89.9	40,247	94.5
Yes	9,051	7.2	3,118	10.2	2,344	5.5
Prepregnancy BMI							<0.001
Underweight <18.5	2,325	1.9	478	1.6	711	1.7
Normal 18.5–24.9	46,569	37.2	7,318	23.8	14,065	33.0
Overweight 25.0–29.9	32,013	25.6	8,032	26.2	12,503	29.4
Obesity 30.0–39.9	31,874	25.5	9,980	32.4	11,492	27.0
Extreme obesity ≥40.0	9,961	8.0	3,899	12.7	2,760	6.5
Missing	2,352	1.9	999	3.3	1,060	2.5
Education							<0.001
Less than high school	5,832	4.7	2,873	9.4	9,233	21.7
High school grad or GED completed	23,397	18.7	9,519	31.0	12,689	29.8
Some college	38,182	30.4	10,895	35.5	12,111	28.4
Bachelor's degree	34,693	27.7	4,500	14.7	5,744	13.5
Graduate degree	22,584	18.1	2,742	8.9	2,482	5.8
Unknown	406	0.3	177	0.6	332	0.8
Insurance type							<0.001
Medicaid	32,948	26.3	18,434	60.0	22,546	52.9
Private insurance	86,588	69.2	10,313	33.6	14,505	34.1
Self-pay	1,498	1.2	924	3.0	3,086	7.3
Other or missing	4,060	3.3	1,035	3.4	2,454	5.8
TOLAC	20,054	16.0	5,817	18.9	7,676	18.0	<0.001
Vaginal birth after cesarean (among those with TOLAC)	13,255	66.1	3,198	55.0	4,777	62.2	<0.001

BMI, body mass index; GED, general equivalency diploma; TOLAC, Trial of labor after cesarean.

Table 2 provides the results from the stratified logistic regression models for TOLAC. Among White and Black women, diabetes was associated with lower odds of TOLAC, whereas among Latinx women, diabetes was not associated with TOLAC odds. Among White women, hypertension was associated with lower odds of TOLAC, whereas among Black and Latinx women, there was no association between hypertension and TOLAC odds. These differences in associations by race/ethnicity were statistically significant. Among White women, overweight and obesity were associated with lower odds of TOLAC compared with being normal weight. Among Black and Latinx women, overweight and obesity were also associated with lower odds of TOLAC, but the reductions in odds of TOLAC were smaller in magnitude than for White women. For example, having a BMI between 30 and 39 (vs. normal BMI) was associated with a 6.3 percentage-point (pp) lower probability of TOLAC for White women, a 5.9 pp lower probability of TOLAC for Black women, and 2.9 pp lower probability of TOLAC for Latinx women. Taken together, these results suggest that for White women, the associations between medical risk factors and reduced chances of having TOLAC were more pronounced than for women of color, even when controlling for education and insurance type.

Table 2.

Adjusted Odds of Trial of Labor After Cesarean and Average Marginal Effects by Race/Ethnicity, United States, 2016

	White; N = 125,094		Black; N = 30,706		Latinx; N = 42,591
	AOR (95% CI)	AME	AOR (95% CI)	AME	AOR (95% CI)	AME
Diabetes	0.81 (0.76–0.87)	−0.025	0.85 (0.75–0.96)	−0.023	0.95 (0.86–1.05)	−0.008^a
Hypertension	0.82 (0.76–0.88)	−0.025	0.99 (0.89–1.10)	−0.002^a	1.02 (0.91–1.15)	0.003^a
Prepregnancy BMI (Ref = normal)
Underweight <18.5	0.96 (0.86–1.08)	−0.005	1.04 (0.84–1.29)	0.008	0.95 (0.78–1.15)	−0.008
Overweight 25.0–29.9	0.82 (0.79–0.85)	−0.028	0.79 (0.73–0.85)	−0.039	0.96 (0.90–1.02)	−0.006^a
Obesity 30.0–39.9	0.62 (0.59–0.64)	−0.063	0.69 (0.64–0.75)	−0.059^a	0.86 (0.80–0.92)	−0.029^a
Extreme obesity ≥40.0	0.43 (0.40–0.46)	−0.098	0.49 (0.44–0.55)	−0.102	0.58 (0.51–0.65)	−0.072^a
Missing	0.83 (0.74–0.93)	−0.026	0.83 (0.70–0.98)	−0.031	1.09 (0.94–1.28)	0.015
Education (Ref = high school completed)
Less than high school	1.00 (0.91–1.09)	0.000	1.20 (1.08–1.33)	0.028^a	1.41 (1.27–1.55)	0.037^a
Some college	1.08 (1.03–1.14)	0.009	0.99 (0.92–1.07)	−0.001^a	0.97 (0.90–1.04)	−0.002^a
Bachelor's degree	1.33 (1.26–1.41)	0.036	1.05 (0.95–1.17)	0.008^a	1.09 (1.00–1.20)	0.012^a
Graduate degree	1.49 (1.40–1.58)	0.052	1.01 (0.89–1.16)	0.002^a	1.23 (1.07–1.41)	0.034^a
Unknown	1.23 (0.94–1.60)	0.025	1.99 (1.43–2.76)	0.122^a	1.65 (1.27–2.14)	0.079
Insurance type (Ref = medicaid)
Private insurance	0.97 (0.92–1.02)	−0.004	0.94 (0.87–1.01)	−0.010^a	0.90 (0.84–0.97)	−0.015^a
Self-pay	1.45 (1.28–1.65)	0.055	0.80 (0.67–0.95)	−0.032^a	1.10 (1.00–1.21)	0.016^a
Other or missing	1.22 (1.12–1.34)	0.028	1.30 (1.12–1.51)	0.043	1.21 (1.09–1.34)	0.030

Model controls for maternal age, maternal residence in the county where the birth occurred, nativity, marital status, adequacy of prenatal care, WIC program participation, any cigarette use during pregnancy, and gestational age category.

Interaction term in full model was significant at p < 0.05.

AOR, adjusted odds ratio; AME, average marginal effect; CI, confidence interval; WIC, Special Supplemental Nutrition Program for Women, Infants, and Children.

Among White women, education beyond high school was associated with higher odds of TOLAC relative to women with a high school degree (Table 2). Among Black women, however, there was no relationship between education beyond high school and chances of TOLAC. Among White women, paying out-of-pocket for birth was associated with a 5.5 pp increase in the probability of TOLAC compared with Medicaid coverage. This association differed across racial/ethnic groups. Black women paying out-of-pocket had a 3.2 pp lower probability of TOLAC compared with women with Medicaid coverage. For Latinx women, out-of-pocket payment was associated with a 1.6 pp increase in the probability of TOLAC, but this was a smaller increase than for White women.

Results from the stratified logistic regression models for VBAC are given in Table 3. Among women of all race/ethnicities who had a TOLAC, hypertension and diabetes were associated with reduced odds of VBAC, and there were no statistically significant differences in associations of these conditions with VBAC odds by race/ethnicity. Among all women, overweight and obesity were associated with lower odds of VBAC, compared with women with BMIs in the normal range. However, the magnitude of this association was smaller for Black women and Latinx women for some of the BMI categories. For example, White women with a prepregnancy BMI between 30 and 39 had a 12.8 pp lower probability of VBAC compared with White women with a prepregnancy BMI in the normal range; for Black women, the analogous reduction in probability of VBAC was 10.2 pp and for Latinx women, it was 7.1 pp.

Table 3.

Adjusted Odds of Vaginal Birth After Cesarean Among Those with Trial of Labor After Cesarean by Race/Ethnicity, United States, 2016

	White; N = 20,054		Black; N = 5,817		Latinx; N = 7,676
	AOR (95% CI)	AME	AOR (95% CI)	AME	AOR (95% CI)	AME
Diabetes	0.78 (0.69–0.89)	−0.055	0.75 (0.60–0.94)	−0.070	0.83 (0.69–0.99)	−0.044
Hypertension	0.72 (0.63–0.82)	−0.073	0.75 (0.61–0.90)	−0.071	0.65 (0.52–0.80)	−0.103
Pre-pregnancy BMI (Ref = normal)
Underweight <18.5	1.36 (1.08–1.72)	0.059	0.90 (0.62–1.31)	−0.025	1.03 (0.71–1.49)	0.006
Overweight 25.0–29.9	0.72 (0.67–0.78)	−0.070	0.77 (0.67–0.89)	−0.062	0.85 (0.76–0.96)	−0.036^a
Obesity 30.0–39.9	0.56 (0.52–0.61)	−0.128	0.65 (0.57–0.75)	−0.102^a	0.73 (0.65–0.83)	−0.071^a
Extreme obesity ≥40.0	0.39 (0.33–0.45)	−0.219	0.53 (0.43–0.66)	−0.153^a	0.51 (0.40–0.65)	−0.157
Missing	1.05 (0.84–1.32)	0.010	0.75 (0.56–1.01)	−0.068	1.08 (0.81–1.45)	0.017
Education (Ref = high school completed)
Less than high school	1.10 (0.93–1.31)	0.022	1.04 (0.87–1.26)	0.011	0.97 (0.85–1.10)	−0.008
Some college	1.04 (0.94–1.14)	0.008	1.10 (0.96–1.25)	0.022	0.96 (0.84–1.10)	−0.008
Bachelor's degree	1.29 (1.16–1.44)	0.057	1.23 (1.02–1.49)	0.050	0.95 (0.80–1.13)	−0.012^a
Graduate degree	1.37 (1.22–1.55)	0.069	1.29 (1.02–1.64)	0.061	1.09 (0.86–1.39)	0.019^a
Unknown	1.74 (1.01–2.99)	0.115	1.00 (0.59–1.71)	0.001	1.21 (0.76–1.95)	0.043
Insurance type (Ref = medicaid)
Private insurance	0.98 (0.89–1.07)	−0.005	0.97 (0.85–1.12)	−0.006	0.95 (0.83–1.08)	−0.013
Self-pay	1.20 (0.94–1.53)	0.039	1.43 (1.03–1.97)	0.083	1.33 (1.11–1.60)	0.063
Other or missing	1.18 (1.00–1.41)	0.035	1.10 (0.84–1.43)	0.022	1.48 (1.21–1.81)	0.085

Interaction term in full model was significant at p < 0.05.

The associations between SES and VBAC did not vary based on race/ethnicity. The one exception was that White and Black women with a bachelor's degree or graduate degree had higher odds of VBAC success compared with White and Black women with a high school degree, whereas a bachelor's degree was not associated with VBAC success among Latinx women.

Discussion

Black and Latinx women who have medical characteristics that may negatively impact their VBAC chances are more likely to have a TOLAC compared with White women. There are many factors not captured in birth certificate data that could impact the TOLAC decision, including preferences, access to hospitals and providers that allow or encourage TOLAC, and provider counseling.^42

–45 It is also possible that negative experiences with the first cesarean could lead to a stronger preference for a vaginal birth in a subsequent pregnancy; previous research has shown that Black women who experienced cesareans reported very low levels of shared decision making in first births,⁴⁶ and that Black women were much more likely than White women to prefer a VBAC at 12 months after the first birth.⁴²

The relationship between SES and TOLAC varied by race/ethnicity. White women with higher levels of education were more likely to have a TOLAC, whereas there was no positive association between education level and TOLAC utilization among Black or Latinx women. This is consistent with previous research showing variation by race/ethnicity in the relationship between SES and cesarean delivery.⁸ In addition, among White women, those paying out-of-pocket for maternity care were more likely to have TOLAC, whereas there was a weaker relationship among Latinx women and a reverse trend among Black women. This may be owing to differences by race/ethnicity in other characteristics of those paying out-of-pocket for maternity care that are not available in birth certificate data, such as income level or immigration status.⁴⁷

There were fewer racial/ethnic differences in correlates of successful VBAC among women with TOLAC. Women in all racial/ethnic groups with diabetes, hypertension, or obesity were less likely to have a VBAC. Of note, however, the reduction in chances of successful VBAC associated with obesity was smaller for Black and Latinx women compared with White women. This is similar to recent findings regarding nulliparous term vertex singleton cesarean delivery, in which overweight and obesity were associated with greater chances of cesarean delivery among all racial/ethnic groups, but the increase in risk was greatest among White women.⁴⁸

Because morbidity is highest among unplanned repeat cesareans following a TOL (vs. a planned repeat cesarean or successful VBAC), estimating chances of VBAC success is useful in counseling patients in TOLAC decision-making. A number of VBAC success calculators have been created for this purpose, with some only including information that would be available during pregnancy and others including information that would be available upon admission to a hospital.^13,49 However, the observation of the lower VBAC success rate among Black and Latinx women has led to the inclusion of race/ethnicity in the most widely used calculator,¹³ implying that it is racial biology rather than racism that leads to this outcome.^50,51 Given that cesarean delivery is the result of human decision-making processes, including race/ethnicity in such calculators could easily become a self-fulfilling prophecy. It is important to emphasize that women's preferences and attitudes could impact not only decision-making regarding having a TOLAC, but also decision-making that occurs during the course of labor. In addition, racism can shape the perceptions and attitudes of clinicians in ways that may influence how they counsel patients and their decision-making process during labor.^36
–38

Limitations

Our results must be considered in light of some limitations. First, birth certificate data are a valuable source of national information, but some items contain measurement error. Birth certificate data tends to underreport diabetes and hypertension.^52,53 In addition, the quality of the trial of labor variable varies by state, with the misclassification in the direction of identifying trial of labor as occurring when it did not.⁵⁴ Second, the birth certificate does not contain information on the indication for prior cesarean, which is an important determinant of VBAC success.¹³ Finally, our data source did not include hospital, provider, or geographic identifiers, so we could not account for clustering by these factors in our analysis.

Conclusions

Understanding the reasons for racial and ethnic disparities in TOLAC rates and VBAC success is important in decreasing the overall cesarean delivery rate and reducing disparities in maternal morbidity and mortality. We found that the reduction in chances of TOLAC associated with medical risk factors was smaller among women of color compared with White women. For women who had a trial of labor, there were fewer racial/ethnic differences in correlates of successful VBAC, but overweight and obesity were more weakly associated with the reduction in probability of successful VBAC among women of color than among White women. More research is needed to elucidate the underlying patient and provider decision-making processes that lead to these results. Future work should focus on ensuring equity in access to VBAC-supportive providers and hospitals and fostering informed decision-making after a prior cesarean.

Footnotes

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

References

Martin

, Hamilton

, Osterman

MJK

, Driscoll

, Drake

. Births: Final data for 2017. Natl Vital Stat Rep, 2018; 67:1–50.

Martin

, Hamilton

, Osterman

MJK

, Driscoll

, Drake

. Births: Final data for 2016. Natl Vital Stat Rep, 2018; 67:1–55.

U.S. Department of Health and Human Services. Healthy people 2020, objective MICH-7.2. Available at: https://www.healthypeople.gov/2020/topics-objectives/topic/maternal-infant-and-child-health/objectives Accessed December 10, 2019 .

Edmonds

, Hawkins

, Cohen

. The influence of detailed maternal ethnicity on cesarean delivery: Findings from the U.S. Birth Certificate in the State of Massachusetts. Birth, 2014; 41:290–298.

Washington

, Caughey

, Cheng

, Bryant

. Racial and ethnic differences in indication for primary cesarean delivery at term: Experience at one US institution. Birth, 2012; 39:128–134.

Bryant

, Washington

, Kuppermann

, Cheng

, Caughey

. Quality and equality in obstetric care: Racial and ethnic differences in caesarean section delivery rates. Paediatr Perinat Epidemiol, 2009; 23:454–462.

Janevic

, Loftfield

, Savitz

, Bradley

, Illuzzi

, Lipkind

. Disparities in cesarean delivery by ethnicity and nativity in New York City. Matern Child Health J, 2014; 18:250–257.

Roth

, Henley

. Unequal motherhood: Racial-ethnic and socioeconomic disparities in cesarean sections in the United States. Soc Probl, 2012; 59:207–227.

Stark

, Grobman

, Miller

. The association between maternal race and ethnicity and risk factors for primary cesarean delivery in nulliparous women. Am J Perinatol, 2019; 1, DOI: 10.1055/s-0039-1697587.

10.

Cahill

, Stamilio

, Odibo

, Peipert

, Stevens

, Macones

. Racial disparity in the success and complications of vaginal birth after cesarean delivery. Obstet Gynecol, 2008; 111:654.

11.

Srinivas

, Stamilio

, Stevens

, Odibo

, Peipert

, Macones

. Predicting failure of a vaginal birth attempt after cesarean delivery. Obstet Gynecol, 2007; 109:800–805.

12.

Attanasio

, Paterno

. Correlates of trial of labor and vaginal birth after cesarean in the United States. J Womens Heal, 2019:1–11.

13.

Grobman

, Lai

, Landon

, et al. Development of a nomogram for prediction of vaginal birth after cesarean delivery. Obstet Gynecol, 2007; 109:806–812.

14.

Howell

, Egorova

, Janevic

, Balbierz

, Zeitlin

, Hebert

. Severe maternal morbidity among Hispanic women in New York City: Investigation of health disparities. Obstet Gynecol, 2017; 129:285–294.

15.

Leonard

, Main

, Scott

, Profit

, Carmichael

. Racial and ethnic disparities in severe maternal morbidity prevalence and trends. Ann Epidemiol, 2019; 33:30–36.

16.

Howell

, Egorova

, Balbierz

, Zeitlin

, Hebert

. Site of delivery contribution to black-white severe maternal morbidity disparity. Am J Obstet Gynecol, 2016; 215:143–152.

17.

Howell

, Egorova

, Balbierz

, Zeitlin

, Hebert

. Black-white differences in severe maternal morbidity and site of care. Am J Obstet Gynecol, 2016; 214:122.e1–122.e7.

18.

Committee on Practice Bulletins—Obstetrics. ACOG practice bulletin no. 205: Vaginal birth after cesarean delivery. Obstet Gynecol, 2019; 133:e110–e127.

19.

Clark

EAS

, Silver

. Long-term maternal morbidity associated with repeat cesarean delivery. Am J Obstet Gynecol, 2011; 205(6 Suppl.):S2–S10.

20.

Gregory

, Fridman

, Korst

. Trends and patterns of vaginal birth after cesarean availability in the United States. Semin Perinatol, 2010; 34:237–243.

21.

Huesch

. Association between type of health insurance and elective cesarean deliveries: New Jersey, 2004–2007. Am J Public Health, 2011; 101:e1–e7.

22.

Kozhimannil

, Shippee

, Adegoke

, Vernig

. Trends in hospital-based childbirth care: The role of health insurance. Am J Manag Care, 2013; 19:e125–e132.

23.

Lipkind

, Duzyj

, Rosenberg

. Disparities in cesarean delivery rates and associated adverse neonatal outcomes in New York City hospitals. Obstet Gynecol, 2010; 113:1239–1247.

24.

Misra

. Impact of the HealthChoice program on cesarean section and vaginal birth after C-section deliveries: A retrospective analysis. Matern Child Health J, 2008; 12:266–274.

25.

Singh

, Dibari

. Marked disparities in pre-pregnancy obesity and overweight prevalence among US women by race/ethnicity, nativity/immigrant status, and sociodemographic characteristics, 2012–2014. J Obes, 2019; 2019:2419263.

26.

Deputy

, Kim

, Conrey

, Bullard

. Prevalence and changes in preexisting diabetes and gestational diabetes among women who had a live birth—United States, 2012–2016. Morb Mortal Wkly Rep, 2018; 67:1201.

27.

Zhou

, Sun

, Li

, et al. Prevalence and trends in gestational diabetes mellitus among women in the United States, 2006–2016. Diabetes, 2018; 67(Suppl. 1):121-OR.

28.

Singh

, Siahpush

, Liu

, Allender

. Racial/ethnic, nativity, and sociodemographic disparities in maternal hypertension in the United States, 2014–2015. Int J Hypertens, 2018; 2018:1–4.

29.

Durnwald

, Ehrenberg

, Mercer

. The impact of maternal obesity and weight gain on vaginal birth after cesarean section success. Am J Obstet Gynecol, 2004; 191:954–957.

30.

Goodall

, Ahn

, Chapa

, Hibbard

. Obesity as a risk factor for failed trial of labor in patients with previous cesarean delivery. Am J Obstet Gynecol, 2005; 192:1423–1426.

31.

Kominiarek

, Vanveldhuisen

, Hibbard

, et al. The maternal body mass index: A strong association with delivery route. Am J Obstet Gynecol, 2010; 203:264.e1–264.e7.

32.

Cormier

, Landon

, Lai

, et al. White's classification of maternal diabetes and vaginal birth after cesarean delivery success in women undergoing a trial of labor. Obstet Gynecol, 2010; 115:60–64.

33.

Dharan

, Srinivas

, Parry

, Ratcliffe

, MacOnes

. Pregestational diabetes: A risk factor for vaginal birth after cesarean section failure?. Am J Perinatol, 2010; 27:265–270.

34.

, Kataria

, Wang

, Ming

, Ellervik

. Factors associated with successful vaginal birth after a cesarean section: A systematic review and meta-analysis. BMC Pregnancy Childbirth, 2019; 19:360.

35.

Regan

, Keup

, Wolfe

, Snyder

, Defranco

. Vaginal birth after cesarean success in high-risk women: A population-based study. J Perinatol, 2015; 35:252–257.

36.

McLemore

, Altman

, Cooper

, Williams

, Rand

, Franck

. Health care experiences of pregnant, birthing and postnatal women of color at risk for preterm birth. Soc Sci Med, 2018; 201:127–135.

37.

van Ryn

, Burgess

, Dovidio

, et al. The impact of racism on clinician cognition, behavior, and clinical decision making. Du Bois Rev Soc Sci Res Race, 2011; 8:199–218.

38.

Altman

, Oseguera

, McLemore

, Kantrowitz-Gordon

, Franck

, Lyndon

. Information and power: Women of color's experiences interacting with health care providers in pregnancy and birth. Soc Sci Med, 2019; 238:112491.

39.

Kotelchuck

. The adequacy of prenatal care utilization index: Its US distribution and association with low birthweight. Am J Public Health, 1994; 84:1486–1489.

40.

Kotelchuck

. An evaluation of the Kessner adequacy of prenatal care index and a proposed adequacy of prenatal care utilization index. Am J Public Health, 1994; 84:1414–1420.

41.

Karaca-Mandic

, Norton

, Dowd

. Interaction terms in nonlinear models. Health Serv Res, 2012; 47:255–274.

42.

Attanasio

, Kozhimannil

, Kjerulff

. Women's preference for vaginal birth after a first delivery by cesarean. Birth, 2019; 46:51–60.

43.

Attanasio

, Hardeman

, Kozhimannil

, Kjerulff

. Prenatal attitudes toward vaginal delivery and actual delivery mode: Variation by race/ethnicity and socioeconomic status. Birth, 2017; 44:306–314.

44.

Barger

, Dunn

, Bearman

, DeLain

, Gates

. A survey of access to trial of labor in California hospitals in 2012. BMC Pregnancy Childbirth, 2013; 13:83.

45.

Leeman

, Beagle

, Espey

, Ogburn

, Skipper

. Diminishing availability of trial of labor after cesarean delivery in New Mexico hospitals. Obstet Gynecol, 2013; 122:242–247.

46.

Attanasio

, Kozhimannil

, Kjerulff

. Factors influencing women's perceptions of shared decision making during labor and delivery: Results from a large-scale cohort study of first childbirth. Patient Educ Couns, 2018; 101:1130–1136.

47.

Garfield

, Majerol

, Damico

, Foutz

. The uninsured: A primer. Key facts about health insurance and the uninsured in the era of health reform. 2016. Available at: http://files.kff.org/attachment/the-uninsured-a-primer-key-facts-about-health-insurance-and-the-uninsured-in-america-primer Accessed June 10, 2019 .

48.

Glazer

, Danilack

, Werner

, Field

, Savitz

. Elucidating the role of overweight and obesity in racial and ethnic disparities in cesarean delivery risk. Ann Epidemiol, 2020; 42:4.e4–11.e4.

49.

Grobman

, Lai

, Landon

, et al. Does information available at admission for delivery improve prediction of vaginal birth after cesarean?. Am J Perinatol, 2009; 26:693–701.

50.

Vyas

, Jones

, Meadows

, Diouf

, Nour

, Schantz-Dunn

. Challenging the use of race in the vaginal birth after cesarean section calculator. Womens Heal Issues, 2019; 29:201–204.

51.

Thornton

. Limitations of vaginal birth after cesarean success prediction. J Midwifery Womens Heal, 2018; 63:115–120.

52.

Dietz

, Bombard

, Mulready-Ward

, et al. Validation of selected items on the 2003 U.S. Standard certificate of live birth: New York City and Vermont. Public Health Rep, 2015; 130:60–70.

53.

Devlin

, Desai

, Walaszek

. Reviewing performance of birth certificate and hospital discharge data to identify births complicated by maternal diabetes. Matern Child Health J, 2009; 13:660–666.

54.

Martin

, Wilson

, Osterman

, Saadi

, Sutton

, Hamilton

. Assessing the quality of medical and health data from the 2003 birth certificate revision: Results from two states. Natl Vital Stat Rep, 2013; 62:1–20.