Inequities in Prenatal Care for Socially and Medically Vulnerable Pregnancies in North Carolina

Abstract

To examine the structural and health-related risk factors associated with prenatal care (PNC) adequacy among women in North Carolina as measured by the Kotelchuck Prenatal Care Index, a retrospective cohort study was designed to utilize data from the 2017 to 2021 Pregnancy Risk Assessment Monitoring System. The analysis used the independent t-test, chi-square tests, and logistic regression modeling to examine study objectives. The study population comprises 286,835 women with documented live births and recorded Kotelchuck PNC Index scores; 77% received adequate PNC. Receiving adequate PNC was more primarily attributed to White women, married, privately insured, and educated women (P < 0.001). Risk factors such as prepregnancy body mass index (BMI), smoking, diabetes, hypertension, previous preterm birth, and infections significantly impacted adequate PNC, often favoring White women. Black and American Indian/Alaska Native (AI/AN) women had a lower likelihood (P < 0.001) of receiving adequate PNC across BMI categories. AI/AN women who smoked during pregnancy had lower odds of adequate PNC (P < 0.001). Black and AI/AN women with previous poor pregnancy outcomes and previous preterm birth had lower odds of adequate PNC (P < 0.05). Sociodemographic factors, health behaviors, and preexisting medical conditions contribute to pervasive inequities among women of color. Targeted interventions and evidence-informed policy reforms are essential to reducing disparities and improving maternal and neonatal health outcomes.

Keywords

prenatal care health inequity maternal health high-risk pregnancy

What Is Already Known on This Topic

Smoking during pregnancy, abnormal prepregnancy body mass index (BMI), sexually transmitted and reproductive tract infections, and chronic conditions such as cardiovascular disease, hypertension, and diabetes are all associated with increased risks of adverse maternal and neonatal outcomes, including stillbirth, low birth weight, preterm birth, and neonatal mortality.

What This Study Adds

Racial disparities in prenatal care (PNC) access were evident, with White women consistently more likely to receive adequate care across medical conditions, while Black and American Indian/Alaska Native (AI/AN) women—especially those affected by smoking or infections—had significantly lower odds.

Medical risk factors such as underweight BMI, smoking, and infectious diseases were associated with reduced access to adequate PNC, underscoring the need for targeted interventions for high-risk populations.

How This Study Might Affect Research, Practice, or Policy

The findings call for policy reforms to address structural barriers to PNC, including insurance coverage, geographic access, and culturally competent services.

There is a clear need for targeted public health initiatives aimed at improving PNC access for AI/AN and Black women, particularly those affected by smoking and infectious diseases.

Pregnancy entails complex physiological and psychological adaptations, necessitating timely and comprehensive PNC to optimize maternal and fetal health outcomes. These outcomes are influenced by multiple interconnected factors, including individual health behaviors, underlying medical conditions, and sociodemographic characteristics. Maternal risk factors such as tobacco use, BMI, infectious diseases, and chronic conditions significantly influence pregnancy outcomes. Smoking during pregnancy is particularly harmful, increasing the risk of stillbirth, sudden infant death syndrome, asthma, and low birth weight.¹ It also raises the likelihood of spontaneous miscarriage by 2.66 times.² Prepregnancy BMI is another critical factor. A BMI ≥ 24 is associated with heightened metabolic and cardiovascular complications, including elevated glucose levels and blood pressure.³ Conversely, a BMI ≤ 18.5 elevates the risk of preterm birth and low birth weight.⁴ Sexually transmitted infections (STIs) and reproductive tract infections like urinary tract infections, chlamydia, and gonorrhea threaten pregnancy outcomes. Chronic conditions like cardiovascular disease, hypertension, and diabetes further elevate the risk of preeclampsia and neonatal mortality.⁵

North Carolina is particularly challenged due to inequities in adverse maternal health outcomes. In North Carolina, Black women account for 69.9 per 100,000 live births, well above the national average of 32.9 per 100,000 live births, and reflect 43% of pregnancy-related deaths despite representing only 22% of the population.⁶ Women of color, including Hispanic, Black, American Indian/Alaska, and Pacific Islander, are significant contributors to preterm birth relative to their White counterparts.⁷ Key contributors to these poor outcomes were due to maternal conditions such as diabetes (30.1%), hypertension (21.5%), smoking (17.0%), and unhealthy weight (12.7%).⁷ PNC is a fundamental component of maternal health, aimed at identifying and mitigating risks to both the mother and the fetus, and should be prioritized in areas that experience significant vulnerabilities. However, access to PNC is shaped by SDOH, which exacerbate inequities and strain the public health system. This study explores how clinical risks, health-related behaviors, and SDOH impact equity in PNC access. The research aims to deepen insight into how individual and structural risk factors affect the utilization of PNC. This research contributes to public health efforts aimed at improving maternal health outcomes and promoting equity in the accessibility of PNC.

Methods

Design and study population

The study drew upon the data collected through the North Carolina Pregnancy Risk Assessment Monitoring System (PRAMS) from 2017 to 2021. Centers for Disease Control and Prevention developed PRAMS to collect state-specific data on maternal and infant health. Data are obtained through a combination of mailed questionnaires, telephone interviews, follow-up approaches, and participant incentives to improve participation response rates. PRAMS data play a vital role in analyzing maternal and infant health, exploring racial inequities in pregnancy outcomes, and understanding patterns in infant mortality. In North Carolina, PRAMS samples approximately 1818 mothers annually, typically 2 to 3 months postpartum.⁸ The sampling strategy primarily uses stratification by birth weight, ensuring oversampling of low-birth-weight infants; about 91% of births fall within the normal weight range.⁹ To produce representative estimates, analysis weights incorporate 3 components: (1) the sampling weight, which reflects the inverse probability of selection within each stratum; (2) a nonresponse adjustment, calculated using birth certificate data for respondents and nonrespondents to account for differential response rates based on maternal characteristics; and (3) a noncoverage adjustment, derived by comparing the final cumulative birth certificate file with the PRAMS sampling frame to identify missed eligible records.⁸ These weighting procedures ensure that North Carolina PRAMS data accurately represent the target population while minimizing bias.^9,10 The weighted rate is 54.5%.⁸ Exclusions include out-of-state births, nonresident mothers, records missing maternal names, multiple gestations of 4 or more, and mothers aged 12 years or younger. This study includes only resident women in North Carolina with a live birth and a Kotelchuck PNC Index score. The university’s Institutional Review Board approved the study (approval #00006735).

Exposure and covariates

This study was guided by Andersen’s Health Care Utilization Model, which informed the inclusion of both predisposing and enabling factors potentially influencing PNC utilization.¹¹ Age was defined in years. Race categories included White, Black or African American, AI or AN, or Other. Ethnicity was defined as Hispanic or non-Hispanic. Education levels were grouped into categories: less than high school, high school or General Education Development (GED), some college, bachelor’s degree, master’s, or PhD, or unknown. Marital status was categorized as married, not married, or unknown. The source of payment was defined as Medicaid, private insurance, self-pay, other, or unknown. We also included health-related factors, such as behaviors and medical conditions. The BMI was categorized into 4 groups: normal weight, underweight, overweight, and obese. Several variables were recorded as binary indicators (yes/no), including participation in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC); cigarette smoking before and during pregnancy; preexisting diabetes; gestational diabetes; chronic hypertension; gestational hypertension; eclampsia; history of preterm birth; other adverse pregnancy outcomes; infertility treatments; and previous cesarean delivery. Infectious diseases considered in the analysis, also coded dichotomously, included chlamydia, gonorrhea, hepatitis B, hepatitis C, and syphilis.

Primary outcomes

The primary outcome was the adequacy of PNC as defined by PRAMS. This was based on birth certificate data, including the month of the first PNC visit, the total number of PNC visits, and the gestational age.¹² Kotelchuck PNC Index represents a standardized assessment tool for PNC adequacy, categorizing care delivery into 4 distinct classifications: inadequate (PNC initiated beyond the 4th gestational month or completion of <50% of recommended visits), intermediate (50%–79% of recommended visits), adequate (80%–109% of recommended visits), and adequate plus (≥110% of recommended visits).¹² For analysis purposes, “adequate PNC” was operationally defined as care meeting either adequate or adequate plus criteria, consistent with established clinical benchmarks. Consequently, PNC adequacy was dichotomized into 2 comparative groups: inadequate/intermediate versus adequate/adequate plus. This categorization underscores the importance of adhering to the PNC guidelines established by the American College of Obstetricians and Gynecologists (ACOG). Evidence indicates that women receiving inadequate or intermediate levels of care experience significantly poorer maternal and fetal outcomes compared to those achieving at least an adequate level of care. For example, a population-based cohort study found that inadequate care was associated with a 1.8 increase in severe maternal morbidity, while intermediate care increased risk by 1.6 times.¹³ Similarly, analyses using the Kotelchuck Prenatal Index reveal that inadequate care is correlated with higher rates of hypertensive disorders, gestational diabetes, and emergency interventions, whereas adequate and adequate-plus care are linked to improved maternal health and reduced complications.^14,15 Furthermore, PNC alone is insufficient to enhance maternal health and well-being unless it includes consistent visits and comprehensive monitoring in accordance with ACOG recommendations.¹⁶ This categorization supports that all women should engage with care recommended by the ACOG. Women who receive inadequate and intermediate care still exhibit poor maternal and fetal outcomes compared to those who receive the recommended, at least adequate level of care.¹⁷ PNC falls short of improving health and well-being unless regular visits and monitoring are completed.¹⁶

Statistical analysis

Sample characteristics were summarized using descriptive analysis, using frequencies and percentages and mean with standard deviation (±SD) for categorical and continuous data, respectively. Between-group comparisons for the dichotomized Kotelchuck PNC Index categories were conducted using independent samples t-tests and chi-square analysis. Multivariable logistic regression modeling was performed to examine adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between the Kotelchuck PNC Index classifications and maternal characteristics and health-related risk factors. To examine whether clinical and behavioral risk factors differentially affected PNC adequacy by race (effect modification), we employed a 2-stage analytical approach. First, we tested statistical interactions by including multiplicative interaction terms (Race × Clinical Risk Factor) in our logistic regression models. Each interaction model included main effects for race, the clinical risk factor of interest, all covariates, and the Race × Risk Factor interaction term. Statistical significance of interaction terms was assessed at α = 0.05. Second, for risk factors demonstrating significant interaction effects, we conducted race-stratified logistic regression analyses to quantify and interpret the differential effects. Separate models were estimated for each racial group (White, Black or African American, AI/AN, and Other), with each model including all clinical and behavioral risk factors while adjusting for age, year, Hispanic ethnicity, education, marital status, WIC participation, and principal source of payment. In these stratified models, White women without the risk factor of interest served as the reference category, allowing for direct comparison of risk factor effects across racial groups relative to this common reference. Statistical computations were performed using IBM SPSS, version 29.0 (IBM Corp, Chicago, IL, USA), and statistical significance was defined with a 2-tailed P value <0.05.

Results

Of 294,844 women with live births during the study period, 286,835 had a recorded Kotelchuck PNC Index and were included in the analysis. A total of 8009 women (2.7% of the initial sample) did not have a Kotelchuck PNC Index recorded and were excluded from the analysis. Compared to participants with a recorded index, those excluded showed significant demographic differences (P < 0.001): a lower proportion identified as White (50.0% vs. 57.9%), a higher proportion of Hispanic origin (24.6% vs. 16.1%), lower educational attainment (19.3% with less than high school vs. 12.8%), lower marriage rates (51.1% vs. 58.8%), and higher rates of Medicaid coverage (45.9% vs. 41.3%) and self-pay status (16.1% vs. 7.2%). (Table A1). In the final analytic sample of 286,835 women. A majority were White (165,989; 57.9%) and not-Hispanic (46,071; 83.9%), attended college (87,042; 30.4%), married (168,449; 58.8%), did not participate in the WIC program (172,996; 60.5%), and reported private insurance coverage (133,753; 46.7%). The mean maternal age was 29 years (SD ± 5.78). Approximately 77% of participants received adequate PNC. Women who received adequate PNC were older (mean age, 29.0 years; SD ± 5.7) than those who received inadequate/intermediate PNC (mean age, 27.6 years; SD ± 6.0), P < 0.001.

Women who received adequate PNC were White (13,565; 61.3%), non-Hispanic (189,935; 85.9%), married (139,063; 62.9%), and did not receive WIC benefits (137,989; 62.5%), P < 0.001. Among education levels, those who received adequate PNC had completed a bachelor’s degree (50,453; 22.9%) or a master’s or PhD (29,308; 13.3%), P < 0.001. Regarding the primary source of payment, most women who received adequate PNC were covered by private insurance (115,965; 52.4%). In contrast, those who received inadequate/intermediate PNC were covered by Medicaid (34,325; 52.5%), P < 0.001. Table 1 summarizes population characteristics by the Kotelchuck PNC Index.

Table 1.

Summary of Population Sociodemographic Characteristics by Kotelchuck Prenatal Care Index

Variables	All (N = 286,835)	Kotelchuck prenatal care index
Variables	All (N = 286,835)	Inadequate/intermediate (N = 65,526)	Adequate/adequate plus (N = 221,309)	P value
Age (years, mean ± SD)	28.64 ± 5.78	27.55 ± 5.97	28..97 ± 5.69	<0.001
Race (n, %)				<0.001
White	165,989 (57.9)	30,328 (46.3)	13,565 (61.3)
Black or African American	71,736 (25.0)	20,324 (31.0)	51,412 (23.2)
American Indian or Alaska Native	4020 (1.4)	1219 (1.9)	2801 (1.3)
Other	45,111 (15.7)	13,661 (20.8)	31,450 (14.2)
Hispanic origin (n, %)
Yes	46,071 (16.1)	14,834 (22.7)	31,237 (14.1)	<0.001
No	240,532 (83.9)	50,597 (77.3)	189,935 (85.9)
Education (n, %)				<0.001
Less than high school	36,542 (12.8)	14,633 (22.4)	21,909 (9.9)
High school graduate or GED	70,119 (24.5)	19,601 (30.1)	50,518 (22.9)
Some college	87,042 (30.4)	18,461 (28.3)	68,581 (31.1)
Bachelor’s degree	58,872 (20.6)	8419 (12.9)	50,453 (22.9)
Master’s or PhD	33,418 (11.7)	4110 (6.3)	29,308 (13.3)
Marital status (n, %)				<0.001
Married	168,449 (58.8)	29,386 (44.9)	139,063 (62.9)
Not married	118,260 (41.2)	36,085 (55.1)	821,775 (37.1)
WIC (n, %)				<0.001
Yes	113,061 (39.5)	30,206 (46.3)	82,855 (37.5)
No	172,996 (60.5)	35,007 (53.7)	137,989 (62.5)
Principal source of payment (n, %)				<0.001
Medicaid	118,336 (41.3)	34,325 (52.5)	84,011 (38.0)
Private insurance	133,753 (46.7)	17,788 (27.2)	115,965 (52.4)
Self-pay	20,740 (7.2)	9163 (14.0)	11,577 (5.2)
Other	13,693 (4.8)	4064 (6.2)	9629 (4.4)

Risk factors associated with PNC

As shown in Table 2, adjusted analysis for age, year, education, Hispanic origin, race, marital status, principal source of payment, and WIC status, underweight women (BMI < 18.5) had lower odds of adequate PNC (aOR = 0.92, 95% CI: 0.87–0.96, P < 0.001). Smoking before (aOR = 0.72) or during pregnancy (aOR = 0.59) also had reduced odds (P < 0.001) of receiving adequate PNC. In contrast, diabetes, hypertension, and hypertension-eclampsia were associated with adequate PNC (P < 0.001). Prior birth decreased odds (aOR = 0.93), while prior adverse outcomes (aOR = 1.08) and infertility treatment (aOR = 1.69) increased adequate PNC (P < 0.001). Infections (gonorrhea, syphilis, chlamydia, and Hepatitis B/C) were linked to reduced adequate PNC, with Hepatitis C showing the lowest odds of adequate PNC (aOR = 0.35, 95% CI: 0.32–0.39, P < 0.001).

Table 2.

Summary of Adjusted Odds Ratio for Maternal Physical and Behavioral Risk Factors for Adequacy of Prenatal Care

Variables	aORs	95% CI	P value
Maternal prepregnancy BMI
Normal (18.5–24.9)	1	Reference
Underweight (less than 18.5)	0.92	0.87–0.96	<0.001
Overweight (25.0–29.9)	1.12	1.09–1.14	<0.001
Obese (30.0+)	1.3	1.27–1.33	<0.001
Cigarette smoking before pregnancy
No	1	Reference
Yes	0.72	0.70–0.74	<0.001
Cigarette smoking during pregnancy
No	1	Reference
Yes	0.59	0.58–0.61	<0.001
Diabetes—prepregnancy
No	1	Reference
Yes	1.66	1.51–1.83	<0.001
Diabetes—gestational
No	1	Reference
Yes	1.49	1.43–1.55	<0.001
Hypertension—prepregnancy
No	1	Reference
Yes	1.43	1.35–1.52	<0.001
Hypertension—gestational
No	1	Reference
Yes	1.32	1.28–1.37	<0.001
Hypertension—eclampsia
No	1	Reference
Yes	1.06	0.92–1.23	0.409
Previous preterm birth
No	1	Reference
Yes	0.93	0.89–0.97	<0.001
Other previous poor pregnancy outcome^a
No	1	Reference
Yes	1.08	1.04–1.13	<0.001
Infertility treatment^b
No	1	Reference
Yes	1.69	1.50–1.91	<0.001
Previous cesarean
No	1	Reference
Yes	1	0.97–1.02	0.727
Gonorrhea
No	1	Reference
Yes	0.72	0.64–0.81	<0.001
Syphilis
No	1	Reference
Yes	0.71	0.56–0.89	0.003
Chlamydia
No	1	Reference
Yes	0.81	0.76–0.85	<0.001
Hepatitis B
No	1	Reference
Yes	0.66	0.51–0.84	<0.001
Hepatitis C
No	1	Reference
Yes	0.35	0.32–0.39	<0.001

Other previous poor pregnancy outcome includes perinatal death and small-for-gestational-age/intrauterine growth-restricted birth.

Infertility Treatment includes Fertility-enhancing drugs, artificial insemination, or intrauterine insemination.

Racial characteristics and risks related to PNC

The study aimed to understand the relationship between risks and access to adequate PNC. These findings indicate the intersectionality of health-related risk and racial identity on PNC access and quality, highlighting the need for targeted interventions to mitigate inequities. Table 3 presents a summary of the findings on the differential impact of risk factors on adequate PNC among women of color.

Table 3.

Summary of Adjusted Odds Ratio for Maternal Risk Factors and Race for Adequacy of Prenatal Care

Variables	Race				Partial Eta-Squared	Interaction term P value
	White	Black or African American	American Indian or Alaska Native	Other
	aOR (95% CI)	aOR (95% CI)	aOR (95% CI)	aOR (95% CI)
Maternal prepregnancy BMI					0.005	<0.001
Normal (18.5–24.9)	1.00 (reference)	0.71 (0.69–0.74)**	0.68 (0.60–0.77)**	0.71 (0.69–0.74)**
Underweight (less than 18.5)	0.85 (0.80–0.91)**	0.76 (0.69–0.83)**	0.62 (0.46–0.85)*	0.64 (0.57–0.73)**
Overweight (25.0–29.9)	1.16 (1.12–1.19)**	0.76 (0.73–0.79)**	0.78 (0.67–0.90)**	0.83 (0.80–0.87)**
Obese (30.0+)	1.36 (1.32–1.40)**	0.90 (0.87–0.93)**	0.96 (0.85–1.08)	0.95 (0.90–0.99)*
Cigarette smoking before pregnancy					0.006	<0.001
No	1.00 (reference)	0.64 (0.63–0.66)**	0.69 (0.64–0.75)**	0.63 (0.62–0.65)**
Yes	0.58 (0.56–0.60)**	0.47 (0.45–0.50)**	0.37 (0.32–0.42)**	0.57 (0.48–0.68)**
Cigarette smoking during pregnancy					0.009	<0.001
No	1.00 (reference)	0.64 (0.62–0.66)**	0.70 (0.64–0.76)**	0.63 (0.61–0.64)**
Yes	0.47 (0.46–0.49)**	0.37 (0.35–0.40)**	0.30 (0.26–0.35)**	0.47 (0.37–0.59)**
Diabetes—prepregnancy					0.003	<0.001
No	1.00 (reference)	0.70 (0.69–0.72)**	0.67 (0.63–0.72)**	0.71 (0.69–0.72)**
Yes	1.55 (1.33–1.81)**	1.22 (1.04–1.43)*	0.60 (0.35–1.05)	1.37 (1.11–1.69)*
Diabetes—gestational					0.004	<0.001
No	1.00 (reference)	0.71 (0.70–0.73)**	0.67 (0.62–0.72)**	0.71 (0.69–0.72)**
Yes	1.58 (1.48–1.67)**	0.96 (0.89–1.03)	1.26 (0.88–1.80)	1.01 (0.94–1.09)
Hypertension—prepregnancy					0.003	<0.001
No	1.00 (reference)	0.70 (0.68–0.72)**	0.66 (0.62–0.71)**	0.71 (0.69–0.73)**
Yes	1.35 (1.23–1.48)**	1.02 (0.93–1.11)	1.17 (0.73–1.87)	1.17 (0.97–1.42)
Hypertension—gestational					0.004	<0.001
No	1.00 (reference)	0.71 (0.69–0.72)**	0.67 (0.62–0.72)**	0.72 (0.70–0.74)**
Yes	1.35 (1.29–1.42)**	0.90 (0.85–0.96)**	1.06 (0.78–1.44)	0.88 (0.80–0.97)*
Hypertension—eclampsia					0.003	0.218
No	1.00 (reference)	0.70 (0.69–0.72)**	0.67 (0.62–0.72)**	0.71 (0.69–0.73)**
Yes	0.98 (0.79–1.20)	0.90 (0.69–1.16)	0.43 (0.10–1.82)	0.71 (0.51–0.99)*
Previous preterm birth					0.003	0.581
No	1.00 (reference)	0.70 (0.69–0.72)**	0.67 (0.62–0.72)**	0.69 (0.68–0.71)**
Yes	0.84 (0.79–0.90)**	0.65 (0.61–0.69)**	0.62 (0.47–0.81)**	0.87 (0.78–0.96)*
Other previous poor pregnancy outcome^a					0.003	<0.001
No	1.00 (reference)	0.69 (0.67–0.70)**	0.66 (0.61–0.71)**	0.78 (0.76–0.81)**
Yes	1.00 (0.94–1.06)	0.79 (0.74–0.84)**	0.72 (0.56–0.93)*	0.96 (0.87–1.06)
Infertility treatment^b					0.003	<0.001
No	1.00 (reference)	0.69 (0.68–0.71)**	0.66 (0.61–0.71)**	0.79 (0.76–0.82)**
Yes	1.57 (1.36–1.81)**	1.07 (0.76–1.50)	3.95 (0.53–29.56)	1.40 (0.99–2.00)
Infections present and/or treated during this pregnancy
Gonorrhea					0.003	<0.001
No	1.00 (reference)	0.69 (0.67–0.70)**	0.66 (0.61–0.70)**	0.78 (0.75–0.81)**
Yes	0.47 (0.39–0.58)**	0.64 (0.55–0.74)**	0.35 (0.18–0.70)*	0.78 (0.42–1.45)
Syphilis					0.003	<0.001
No	1.00 (reference)	0.69 (0.67–0.70)**	0.65 (0.61–0.70)**	0.78 (0.76–0.81)**
Yes	0.58 (0.39–0.88)*	0.54 (0.39–0.74)**	0.71 (0.06–8.78)	0.65 (0.35–1.21)
Chlamydia					0.003	<0.001
No	1.00 (reference)	0.69 (0.67–0.70)**	0.65 (0.61–0.70)**	0.78 (0.75–0.80)**
Yes	0.72 (0.66–0.80)**	0.63 (0.58–0.67)**	0.61 (0.42–0.89)*	0.73 (0.63–0.85)**
Hepatitis B					0.003	<0.001
No	1.00 (reference)	0.69 (0.67–0.70)**	0.65 (0.61–0.70)**	0.78 (0.76–0.81)**
Yes	0.42 (0.27–0.65)**	0.54 (0.35–0.83)*	0.97 (0.08–11.58)	0.68 (0.45–1.05)
Hepatitis C					0.005	<0.001
No	1.00 (reference)	0.67 (0.66–0.69)**	0.65 (0.61–0.70)**	0.77 (0.75–0.80)**
Yes	0.27 (0.24–0.30)**	0.32 (0.20–0.52)**	0.16 (0.09–0.27)**	0.44 (0.23–0.86)*

*Statistical significance P value < 0.05; **P value < 0.001.

Other previous poor pregnancy outcome includes perinatal death and small-for-gestational-age/intrauterine growth-restricted birth.

Infertility treatment includes fertility-enhancing drugs, artificial insemination, or intrauterine insemination.

aOR, adjusted odds ratio; BMI, body mass index; CI, confidence interval.

Body mass index

In our sample, overweight and obesity were most common among Black (41.9%) and AI/AN women (38.2%) (Table A2). Overweight and obese Black women, as well as overweight AI/AN women, were less likely to receive adequate PNC (P < 0.001). No statistically significant association was observed for AI/AN women with obesity (P > 0.05).

Smoking

Marked inequities in adequate PNC were evident across racial groups in relation to smoking status. Compared to White women who did not smoke either before or during pregnancy, both Black and AI/AN women were disproportionately underrepresented among those receiving adequate PNC (P < 0.001). Within the subset of women who smoked, AI/AN demonstrated the lowest odds of receiving adequate care, both prior to pregnancy (aOR = 0.37; 95% CI: 0.32–0.42, P < 0.001) and during pregnancy (aOR = 0.30, 95% CI: 0.26–0.35, P < 0.001). Furthermore, smoking prevalence was highest among AI/AN women, with 22.4% reporting prepregnancy smoking and 18.5% smoking during pregnancy.

Diabetes

Among women with prepregnancy diabetes, White women had the highest likelihood of receiving adequate PNC (aOR = 1.55, 95% CI:1.33–1.81, P < 0.001) while Black women had lower odds (aOR = 1.22, 95% CI: 1.04–1.43, P < 0.05). During pregnancy, White women with diabetes continued to show the highest likelihood of receiving adequate PNC (aOR = 1.58, 95% CI: 1.48–1.67, P < 0.001).

Hypertension

White women with prepregnancy hypertension were most likely to receive adequate PNC (P < 0.001). A comparable pattern was observed for gestational hypertension, with White women again more likely than Black women to receive adequate care (P < 0.001).

Previous birth outcomes and infertility treatment

Women with a history of preterm birth were less likely to receive adequate PNC (P < 0.001). Among those with other adverse pregnancy outcomes (eg, perinatal death and small-for-gestational-age/intrauterine growth-restricted birth), women of color were less likely than White women to receive adequate PNC. This disparity was particularly evident for Black women (aOR = 0.65, 95% CI: 0.61–0.69, P < 0.001) and AI/AN women (aOR = 0.62, 95% CI: 0.47–0.81, P < 0.001). In contrast, White women who had undergone infertility treatment were more likely to receive adequate PNC (aOR = 1.57, 95% CI: 1.36–1.81, P < 0.001).

Infections

Infections had pronounced disparities in adequate PNC across racial groups and infection types such as gonorrhea, syphilis, chlamydia, Hepatitis B, and Hepatitis C. AI/AN women with Hepatitis C were least likely to receive adequate PNC odds (aOR = 0.16, 95% CI: 0.09–0.27, P < 0.001). Black women with syphilis (aOR = 0.54, 95% CI: 0.39–0.74, P < 0.001), gonorrhea (aOR = 0.64, 95% CI: 0.55–0.74, P < 0.001), Hepatitis C (aOR = 0.32, 95% CI: 0.20–0.52, P < 0.001), chlamydia (aOR = 0.63, 95% CI: 0.58–0.67, P < 0.001), and Hepatitis B (aOR = 0.54, 95% CI: 0.35–0.83, P < 0.05). Similarly, AI/AN had significantly lower odds with gonorrhea (aOR = 0.35, 95% CI: 0.18–0.70, P < 0.05), chlamydia (aOR = 0.61, 95% CI: 0.42–0.89, P < 0.05), and Hepatitis C (aOR = 0.16, 95% CI: 0.09–0.27 P < 0.001).

Discussion

Individual and structural factors shape access to adequate PNC. Women of color, women with lower education, unmarried women, WIC participants, and Medicaid beneficiaries face disproportionate barriers to care that were exacerbated by health-related risks.¹⁸ Snowden findings suggested that communities with larger White populations showed greater explicit and implicit bias toward Black women and offered fewer Federally Qualified Health Care (FQHC) maternal care services.¹⁹ The shortage of FQHCs in areas of higher racial bias directly impacts PNC availability, as FQHCs serve as primary access points for pregnant women. Snowden’s work suggested that anti-Black biases may impede proper recognition of health care access limitations.¹⁹ Harbell emphasized that public health systems should address these inequities through implicit bias training and culturally competent measurement tools that better reflect Black patient experiences.²⁰ The author argued that culture change and training for health care professionals are essential for improving maternal outcomes across diverse populations.²⁰

Health behaviors

While sociodemographic factors are key barriers to access to care, this study further demonstrates how clinical and behavioral risk factors amplify inequities in PNC access. Although being overweight and obesity per se did not predict inadequate PNC, racial stratification revealed that women of color who report obesity or overweight have decreased access to care. In addition, Black and AI/AN women reported the highest rates of overweight and obesity, yet experienced reduced access to care. Structural drivers like obesogenic environments, inequitable obesity treatment, and limited access to nutrient-dense foods exacerbate these challenges among women of color.²¹

Smoking emerged as a significant health-related barrier to adequate PNC, particularly among AI/AN women. AI/AN women are 3 times more likely to smoke during pregnancy and have the lowest PNC utilization.²² Prenatal smoking elevates risks of infant mortality and autism spectrum disorders.²³ In addition to smoking behavior, AI/AN women also reported greater socioeconomic barriers to care and lower satisfaction with prenatal services, underscoring the need for culturally responsive and accessible health care support. Individuals with lower socioeconomic and educational status are more likely to smoke and less likely to attempt quitting.²⁴ Lifestyle interventions such as healthy weight maintenance, diet quality, regular exercise, and smoking cessation correlate with lower rates of gestational diabetes, hypertensive disorders, and preterm birth.²⁵ However, programs targeting behaviors alone often fail without concurrent measures to address poverty, resource scarcity, and systemic discrimination.²⁶ Together, these highlight that integrating behavioral and structural reforms is critical to reducing maternal risk and racial bias in PNC.²⁷

Medical risk

Our study found that women with medical diagnoses like diabetes and hypertension had greater odds of adequate PNC. However, this trend did not hold for women of color, who were less likely to receive adequate PNC despite having these same conditions. Notably, perinatal diabetes and hypertension were more prevalent among women of color, yet their access to adequate PNC was disproportionately lower. This observation is consistent with prior research suggesting that while medical risk typically correlates with elevated care utilization, women of color do not experience the same benefits.²⁸ Krans et al. reported that 70% of women of color with medical risks received less than adequate PNC.²⁹ Lee et al. observed that women with hypertension were less likely to receive adequate PNC.³⁰

Our findings revealed mixed outcomes in adequate PNC among women with adverse pregnancy-related conditions. Women with a history of preterm birth, prior cesarean delivery, or poor pregnancy outcomes generally had lower odds of adequate PNC. Women who had undergone infertility treatments were more likely to receive adequate care, likely due to their preexisting engagement with health care providers. Stratification by race illuminated inequities. Women of color were more likely to report previous cesareans and poor pregnancy outcomes yet were less likely to receive adequate PNC compared to White women. This pattern aligns with findings from Jardine et al., who identified a higher prevalence of prior pregnancy complications among women of color.³¹

Infectious diseases further exacerbated inequities in adequate PNC. Women diagnosed with STIs, including gonorrhea, syphilis, and chlamydia, experienced significant inequities in accessing adequate PNC, regardless of race. These infections disproportionately affect women of color and are strongly associated with poor birth outcomes, including elevated risk of preterm birth.^32,33 Similarly, Hepatitis B and C, which also disproportionately impact women of color, were associated with reduced access to adequate PNC.³⁴ Hepatitis C prevalence has increased over the past 2 decades, linked to opioid use disorder, substance use, mental health conditions, and tobacco use,³⁵contributing significantly to maternal morbidity, adverse perinatal events, and poor pregnancy outcomes.³⁶ Salemi et al. found Hepatitis B and C are increasingly prevalent among high-risk pregnancy groups, particularly those with co-occurring infections, advanced maternal age, and lower socioeconomic status.³⁷ While race and ethnicity did not independently affect PNC among infected women in our study, the disproportionate infection burden among women of color highlights the need to address these factors within the broader maternal health inequities.

Implications for practice

Comprehensive PNC is critical for managing high-risk pregnancies; it improves complication detection, glycemic and blood pressure control, and smoking cessation efforts.³⁸ PNC also reduces the risks of preeclampsia and preterm birth.³⁹ However, sociodemographic and health-related factors complicate access to adequate PNC. Targeted interventions enhance PNC access and effectiveness among minority high-risk women.⁴⁰ PNC participation is linked to reduced medication use in diabetic patients, and smokers were 5 times more likely to quit.⁴¹ Adequate PNC lowers odds of preterm birth by 38% (P = 0.001) and low birth weight by 28% (P = 0.003). Despite these benefits, inequities in access for women of color persist, demanding fundamental changes.⁴²

Cultural competency among maternal care providers is a key step in mitigating access to PNC. The patient–provider relationship must include elements of communication built on trust and mutual understanding, which involves more listening than giving general advice.⁴³ While labor is common among all cultures, the wants and needs during the labor process are subject to cultural norms and customs.⁴¹ Early detection of maternal risk is another key strategy. Frontline health care workers, particularly in FQHCs, hospitals, and community-based health centers, should routinely screen for unmet non-medical needs. Collaborations among medical and social services organizations can promote access to PNC while also mitigating non-medical factors that influence health, such as food insecurity, unemployment, and housing challenges.⁴⁴ In addition, expanding services to reach communities that experience vulnerabilities can enhance access to care. The Transforming Maternal Health Model (TMaH), launched in January 2025, offers a strategic framework to improve outcomes for women of color by expanding access, enhancing care quality, and tailoring services for Medicaid recipients.⁴⁵ By leveraging programs like Medicaid and the Children’s Health Insurance Program, TMaH strengthens infrastructure and workforce capacity.⁴⁶ Achieving its goals requires alignment of financial investments and a robust data system to monitor outcomes.⁴⁷ By expanding infrastructure and increasing workforce capacity, this and similar programs can meet needs in maternity care deserts.

Limitations

The study has several limitations that should be taken into consideration. A significant limitation is the exclusion of women who lacked a recorded Kotelchuck PNC Index score, who were more likely to experience vulnerabilities. This suggests our findings may underestimate the true extent of PNC inadequacy. The exclusion of women without documented PNC indices may reflect barriers to care access and incomplete health system documentation, potentially biasing our results. The study includes only data from North Carolina, which restricts the generalizability of findings to other areas. Maternal health outcomes may vary significantly due to differences in health care infrastructure and policies, which limit their applicability to other states.⁴⁸ In addition, the study period encompasses key initiatives related to maternal health outcomes, such as the H.R. 4995-Maternal Health Quality Improvement Act of 2020⁴⁹ and the Preventing Maternal Deaths Act of 2018.⁵⁰ These policy initiatives may be adopted at different rates across states. While this study controlled for the pandemic, COVID-19 had profound and unprecedented effects on maternal health that led to disruption in PNC due to workforce shortages and health infrastructure strain, increased maternal mental health challenges, domestic violence, and socioeconomic stressors.⁵¹ Therefore, caution should be exercised when applying these findings. Future studies should employ a prospective study design to capture the personal perspectives of women, thereby increasing representation across diverse racial and ethnic groups. It is essential to address other barriers to PNC for culturally appropriate access to care.

Conclusion

This study highlights persistent inequities in PNC adequacy among women in North Carolina, primarily affecting Black and AI/AN women with high-risk pregnancies. Despite overall high rates of adequate care, sociodemographic and health-related risk factors, such as prepregnancy BMI, smoking, chronic conditions, and prior adverse birth outcomes, disproportionately limit access to adequate care. These findings emphasize structural and clinical vulnerabilities in maternal health equity. Addressing these inequities requires targeted, culturally responsive interventions and systemic policy reforms aimed at expanding access, improving care coordination, and enhancing provider capacity in communities that experience vulnerabilities.

Authors’ Contributions

Williams was responsible for the study’s conceptualization and design, interpretation of the findings, and drafting and revising the article. Both Williams and Battle contributed to the writing and revision of the article. Chou played a key role in the study’s design, data interpretation and analysis, and article revision. All authors reviewed and approved the final version of the article.

Footnotes

Author Disclosure Statement

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding Information

No funding was received for this article.

Ethical Considerations

The University of Central Florida Institutional Review Board provided Ethical Approval #00006735.

Data Availability

The data supporting the findings of this study are available from the North Carolina Department of Health; however, access is restricted. These data were used under license for the current study and are not publicly available. Interested parties may request access by contacting the corresponding author and obtaining the necessary permissions from the department.

Ethics Approval for Consent to Participate

A waiver of informed consent of participants was provided by the University IRB; thus, participant written informed consent was not needed.

Appendix

Table A2.

Summary of Clinical Characteristics by Race

Variables	Race				P value
Variables	White (N = 165,979)	Black or African American (N = 71,736)	American Indian or Alaska Native (N = 4,020)	Other (N = 45,111)	P value
Maternal prepregnancy BMI
Normal (18.5–24.9)	5400 (3.3%)	2136 (3.0%)	179 (4.7%)	1320 (3.0%)	<0.001
Underweight (less than 18.5)	72,979 (44.6%)	21,110 (30.1%)	1220 (32.0%)	17,777 (40.5%)	<0.001
Overweight (25.0–29.9)	41,270 (25.2%)	17,503 (24.9%)	961 (25.2%)	13,525 (30.8%)	<0.001
Obese (30.0+)	43,991 (26.9%)	29,417 (41.9%)	1458 (38.2%)	11,234 (25.6%)	<0.001
Cigarette smoking before pregnancy	19,897 (12.0%)	7237 (10.1%)	900 (22.4%)	637 (1.4%)	<0.001
Cigarette smoking during pregnancy	15,167 (9.1%)	4974 (6.9%)	745 (18.5%)	338 (0.7%)	<0.001
Diabetes—prepregnancy	1423 (0.9%)	1152 (1.6%)	61 (1.5%)	592 (1.3%)	<0.001
Diabetes—gestational	10,658 (6.4%)	4514 (6.3%)	219 (5.4%)	4413 (9.8%)	<0.001
Hypertension—prepregnancy	3946 (2.4%)	3451 (4.8%)	121 (3.0%)	657 (1.5%)	<0.001
Hypertension—gestational	14,387 (8.7%)	7106 (9.9%)	250 (6.2%)	2288 (5.1%)	<0.001
Hypertension—eclampsia	591 (0.4%)	337 (0.5%)	8 (0.2%)	168 (1.4%)	<0.001
Previous preterm birth	6537 (3.9%)	5632 (7.9%)	255 (6.3%)	2049 (4.5%)	<0.001
Other previous poor pregnancy outcome^a	8314 (5.0%)	5893 (8.2%)	309 (7.7%)	2419 (5.4%)	<0.001
Infertility treatment^b	2407 (1.5%)	296 (0.4%)	22 (0.5%)	327 (0.7%)	<0.001
Previous cesarean	22,160 (13.4%)	11,574 (16.1%)	693 (17.2%)	6699 (14.9)	<0.001
Infections present and/or treated during this pregnancy
Gonorrhea	394 (0.2%)	827 (1.2%)	33 (0.8%)	46 (0.1%)	<0.001
Syphilis	110 (0.1%)	171 (0.2%)	3 (0.1%)	46 (0.1%)	<0.001
Chlamydia	2038 (1.2%)	3294 (4.6%)	118 (2.9%)	806 (1.8%)	<0.001
Hepatitis B	92 (0.1%)	99 (0.1%)	3 (0.1%)	117 (0.3%)	<0.001
Hepatitis C	1395 (0.8%)	73 (0.1%)	58 (1.5%)	37 (0.1%)	<0.001

Other previous poor pregnancy outcome includes perinatal death and small-for-gestational-age/intrauterine growth-restricted birth.

Infertility treatment includes fertility-enhancing drugs, artificial insemination, or intrauterine insemination.

BMI, body mass index.

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