Next Article in Journal
Effect of COVID-19 Lockdown on Children’s Eating Behaviours: A Longitudinal Study
Next Article in Special Issue
The Association between NICU Admission and Mental Health Diagnoses among Commercially Insured Postpartum Women in the US, 2010–2018
Previous Article in Journal
Acupuncture for Pain Management in Pediatric Patients with Sickle Cell Disease
Previous Article in Special Issue
The Impact of Natural Disasters on Maternal Health: Hurricanes Irma and María in Puerto Rico
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Children
Volume 9
Issue 7
10.3390/children9071077
children-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents

by
Bridget Basile Ibrahim
1,2,*,
Julia D. Interrante
1,
Alyssa H. Fritz
1,
Mariana S. Tuttle
1 and
Katy Backes Kozhimannil
1
1
University of Minnesota Rural Health Research Center, Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, MN 55414, USA
2
School of Nursing, Yale University, Orange, CT 06477, USA
*
Author to whom correspondence should be addressed.
Children 2022, 9(7), 1077; https://doi.org/10.3390/children9071077
Submission received: 22 June 2022 / Revised: 13 July 2022 / Accepted: 16 July 2022 / Published: 19 July 2022
(This article belongs to the Special Issue Social Determinants of Disparities in Maternal and Infant Health Outcomes)
Versions Notes

Abstract

:
Rural residents in the United States (US) have disproportionately high rates of maternal and infant mortality. Rural residents who are Black, Indigenous, and People of Color (BIPOC) face multiple social risk factors and have some of the worst maternal and infant health outcomes in the U.S. The purpose of this study was to determine the rural availability of evidence-based supports and services that promote maternal and infant health. We developed and conducted a national survey of a sample of rural hospitals. We determined for each responding hospital the county-level scores on the 2018 CDC Social Vulnerability Index (SVI). The sample’s (n = 93) median SVI score [IQR] was 0.55 [0.25–0.88]; for majority-BIPOC counties (n = 29) the median SVI score was 0.93 [0.88–0.98] compared with 0.38 [0.19–0.64] for majority-White counties (n = 64). Among counties where responding hospitals were located, 86.2% located in majority-BIPOC counties ranked in the most socially vulnerable quartile of counties nationally (SVI ≥ 0.75), compared with 14.1% of majority-White counties. In analyses adjusted for geography and hospital size, certified lactation support (aOR 0.36, 95% CI 0.13–0.97), midwifery care (aOR 0.35, 95% CI 0.12–0.99), doula support (aOR 0.30, 95% CI 0.11–0.84), postpartum support groups (aOR 0.25, 95% CI 0.09–0.68), and childbirth education classes (aOR 0.08, 95% CI 0.01–0.69) were significantly less available in the most vulnerable counties compared with less vulnerable counties. Residents in the most socially vulnerable rural counties, many of whom are BIPOC and thus at higher risk for poor birth outcomes, are significantly less likely to have access to evidence-based supports for maternal and infant health.

1. Introduction

Many clinical services, care resources, and community supports [1] have strong evidence showing that they improve maternal and infant health outcomes. These evidence-based supports for maternal and infant health (hereafter evidence-based supports) improve health outcomes in a variety of ways. Having access to the full spectrum of perinatal care (prenatal and postpartum care) [2,3], perinatal mental health services [4,5,6,7], and formal lactation support from international board-certified lactation consultants (IBCLC) [8,9,10,11]) close to home, or even in the home with nurse home visiting [12,13,14,15], helps ensure that pregnant women and people get the screenings, clinical guidance, and monitoring they need to have the healthiest pregnancy and best outcomes possible. Models of care that are person- or family-centered, such as perinatal care with certified nurse-midwives [16,17], prenatal care offered in a group setting (often called group prenatal care) [18,19], and dedicated birth support from doulas (trained non-clinical birth support personnel) [20,21] have been associated with improved maternal and infant health outcomes, particularly for families who are at higher risk for poor outcomes [17,22,23,24,25,26]. Community supports in the form of postpartum [27] and breastfeeding peer support groups [27,28,29], childbirth education classes [30], and nutrition support programs for vulnerable families (Special Supplemental Nutrition Program for Women, Infants, & Children-WIC) [31,32] also have strong evidence in the literature for improving maternal and infant health outcomes.
Social vulnerability encompasses many social and structural determinants of health and health inequities such as household income, employment, education, health insurance, majority (English) language ability, housing, and transportation [33,34,35,36,37,38]. Race and ethnicity, a variable considered in the calculation of social vulnerability [38,39] can be considered as a proxy for exposure to racism [40,41], which impacts health when experienced both interpersonally and due to the upstream effects of social and political structures within society (i.e., institutional and structural racism) [36,42,43]. High social vulnerability has been linked to inequities in maternal and infant health outcomes, including delayed diagnosis of congenital heart anomalies and a resulting higher rate of infant mortality [44], increased preterm birth rates [45], higher teen birth rates [46], and COVID-19-related maternal and infant complications [47]. Specific social determinants of health that are components of social vulnerability have also been linked to adverse maternal and infant outcomes. Previous research has noted associations between: socioeconomic status with maternal health outcomes [35]; insurance status, adequate housing, and transportation with prenatal and postpartum care utilization [15,48]; and educational attainment and neighborhood quality with preterm birth [49].
Rural residents account for 15% of annual US births [50] and are disproportionately affected by poor maternal and infant outcomes [51,52,53,54,55]. Individuals who have intersecting identities that are both rural and Black, Indigenous, or People of Color (BIPOC) have some of the worst birth outcomes in the country [56,57]. In order to improve these outcomes, it is essential to first understand the landscape of available perinatal health services in rural areas. While prior research has noted that access to midwifery services [58,59] and lactation support [60,61,62] in rural US communities is limited, very little is known about the local availability of other evidence-based supports for maternal and infant health for rural families, especially contextualized by community social vulnerability. The purpose of this analysis is to describe the availability of these evidence-based supports (local access to care, family-centered models of care, peer and community supports for families, and health-focused programming) in rural communities that have hospital-based inpatient labor and birth services, with a focus on social vulnerability at the intersection of race/ethnicity and geography.

2. Materials and Methods

Study methods have been described in detail elsewhere [63]. In brief, we identified rural hospitals that were operating an inpatient labor and birth in 2018 based on an enhanced two-stage method [64]. Along with a random sample of hospitals in rural counties where the majority of the population is White, non-Hispanic (n = 200), we sampled all hospitals located in rural counties where the majority (≥50%) of residents are BIPOC (n = 110) due to documented disparities in maternal and infant health outcomes [50,51,52,53,54,55,56,57,65]. Our team confirmed via hospital website and/or telephone calls whether hospitals still offered inpatient care for labor and birth. Those that did not were removed, bringing the final sample to 285 rural hospitals located in all four US Census Regions [66].
A 47-question web-based survey was developed with expertise from rural clinicians and administrators and piloted with administrators at six rural hospitals [63]. Questions were edited for clarity after pilot review. We administered the survey from March to August 2021 via the Qualtrics (Provo, UT, USA) platform. Twelve questions asked about the availability of evidence-based supports in each hospital’s rural community, including: traditional model/individual prenatal care, nurse home visiting services in the prenatal and postpartum periods, perinatal mental health services, lactation support from IBCLC, maternity care with certified nurse-midwives, group prenatal care, birth support from doulas, postpartum peer support groups, breastfeeding support groups, childbirth education classes, and the Special Supplemental Nutrition Program for Women, Infants, & Children (WIC).
We emailed a letter describing our study to hospital chief executive officers (CEO) and chief nursing officers (CNO) and asked the CEO/CNO to forward the Qualtrics survey link to the nurse manager of their labor and birth unit. Follow-up efforts consisted of contacting hospitals by telephone, sending reminder emails to hospital leadership points-of-contact, and mailing postcards with a scannable Qualtrics survey QR code directly to the nurse managers of the labor and birth units.

2.1. Exposure: Social Vulnerability Index 2018

The Social Vulnerability Index (SVI), compiled and calculated by the Centers for Disease Control and Prevention (CDC), is a relative measurement of vulnerability, resources, and disadvantage [37,38] that encompasses four themes: (1) socioeconomic status, (2) household composition and disability, (3) minority status and language, and (4) housing and transportation [38]. SVI scores are reported at the county and census tract level as an overall score for vulnerability and a score for each of the four themes. While the SVI was initially intended to identify the most vulnerable areas during public health and natural disaster emergencies, it has also been used for public health/epidemiology research as an objective measure of neighborhood and county-level social vulnerability and disadvantage [44,46,67,68,69,70].
The SVI is a relative vulnerability score using 15 factors from US Census data. We used county-level SVI linked by county Federal Information Processing System (FIPS) codes as the exposure in this analysis [71]. Scores range from 0 to 1; scores closer to 1 indicate a county’s greater social vulnerability relative to other counties across the United States. The scores for each of the four themes use the census data factors as follows: (1) socioeconomic status: percentage of residents living below the poverty line, those who are unemployed, median household income, and high school diploma attainment for residents >25 years old, (2) household composition and disability: percentage of residents aged <18 years and >64 years, civilians with a disability, and single-parent households, (3) racial and ethnic minority and language: percentage of residents who identify as any race/ethnicity other than White, non-Hispanic, and those who speak English “less than well”, and (4) housing type and transportation: percentage of multi-unit structures, mobile homes, crowded dwellings, lack of household vehicle access, and institutionalized group quarters [37,38,72]. The method for SVI calculation and the complete description of data sources is publicly available from the CDC [37,38,72].

2.2. Outcome: Community Availability of Evidence-Based Supports for Maternal and Infant Health

Availability of twelve evidence-based supports was indicated by respondents on the survey. The specific evidence-based supports queried were (1) access to care: traditional model/individual prenatal care, nurse home visiting services in the prenatal and postpartum periods, perinatal mental health services, and lactation support from IBCLCs; (2) family-centered models of perinatal care: maternity care with certified nurse-midwives, group prenatal care, and birth support from doulas; (3) peer and community supports for families: postpartum peer support groups and breastfeeding support groups; and (4) health-focused programming: childbirth education classes and WIC.
Survey respondents indicated whether or not each evidence-based support was available in their respective hospitals’ community by selecting from the following options: “available in the community and affiliated with my hospital”, “available in the community and not affiliated with my hospital”, “not available in the community”, or “I don’t know”. The evidence-based supports described in our results as available in the community are composed of a combination of responding hospitals that indicated “available in the community and affiliated with my hospital” and “available in the community and not affiliated with my hospital”.

2.3. Statistical Analysis

Descriptive statistics, including median SVI scores and interquartile ranges (IQR) were calculated. Overall SVI score was dichotomized into two groups: the counties that fell into the most vulnerable quartile of counties on the national SVI scale (SVI score ≥ 0.75) and the remaining counties with less vulnerability (SVI score < 0.75), similar to other work using the SVI [44]. Logistic regression was used to determine the likelihood of availability of each of the evidence-based supports associated with county-level social vulnerability, comparing counties in the most vulnerable SVI quartile to the less vulnerable counties. Unadjusted and adjusted odds ratios and 95% confidence intervals are presented. All adjusted analyses controlled for U.S. Census region [66] and urban adjacency (from the Area Health Resources Files [73]), as well as hospital size (average daily census in 2018 from the American Hospital Association Annual Survey [74]). In order to account for regional variability in licensure, integration, and Medicaid reimbursement and expansion, we controlled for census region. To account for the fact that hospitals in rural areas that are adjacent to urban areas may offer more limited services and supports because they are available in nearby urban areas, we controlled for urban adjacency. Hospital size was controlled for to account for the variability in demand for services as well as capacity to offer them. Statistical analyses were completed using SAS software, Version 9.4 (Cary, NC, USA). This study was deemed exempt by the Institutional Review Board of The University of Minnesota (protocol code 00010917, 6 October 2020).

3. Results

3.1. Study Sample

Ninety-three hospitals (93/285) completed the survey for a response rate of 32.6% (Table 1). Responding hospitals were located in all four U.S. Census regions [66] with 5.4% located in the Northeast, 31.2% in the Midwest, 27.9% in the South, and 35.5% in the West. Approximately 1 in 3 (31.2%) responding rural hospitals were located in majority-BIPOC counties. Critical Access Hospitals comprised 35.5% of responding hospitals. Responding hospitals had a median of 274 births in 2019 (IQR 120–446) and a median average daily census of 22 (IQR 10–53). The sample is described in full detail elsewhere [63,75].

3.2. Social Vulnerability Index

Responding hospitals had a median overall SVI score of 0.55 (IQR 0.25–0.88), a socioeconomic status (theme 1) median score of 0.53 (IQR 0.23–0.92), a household composition (theme 2) score of 0.54 (IQR 0.33–0.82), a BIPOC status and language (theme 3) score of 0.59 (IQR 0.25–0.89), and a transportation and housing (theme 4) score of 0.62 (IQR 0.40–0.84) (Table 2). When the sample was disaggregated by majority county population (majority-BIPOC versus majority-White, non-Hispanic), SVI scores indicated higher social vulnerability for BIPOC counties, with a median score approximately twice that of the majority-White, non-Hispanic counties. Majority-BIPOC counties had a total SVI score of 0.93 (IQR 0.88–0.98), a socioeconomic status (theme 1) median score of 0.89 (IQR 0.75–0.96), a household composition (theme 2) score of 0.82 (IQR 0.54–0.94), a minority status and language (theme 3) score of 0.94 (IQR 0.91–0.96), and a transportation and housing (theme 4) score of 0.84 (IQR 0.61–0.91). In comparison, majority-White, non-Hispanic counties had an overall median SVI score of 0.38 (IQR 0.19–0.64), a socioeconomic status (theme 1) median score of 0.44 (IQR 0.18–0.63), a household composition (theme 2) score of 0.43 (IQR 0.21–0.67), a minority status and language (theme 3) score of 0.38 (IQR 0.19–0.63), and a transportation and housing (theme 4) score of 0.47 (IQR 0.30–0.71).
When the counties were dichotomized into those falling within the highest quartile for vulnerability on the national Social Vulnerability Index, (most vulnerable quartile = SVI score ≥ 0.75), counties with a majority of residents who were BIPOC fell into the most vulnerable quartile on overall SVI and all sub-themes at significantly higher rates than the majority-White counties (Table 3). A total of 34 responding rural hospitals were located in counties that were in the most socially vulnerable quartile, 25 of which were majority-BIPOC counties. For overall SVI score, 86.2% of majority-BIPOC counties were in the most vulnerable quartile compared with 14.1% of majority-White counties. For socioeconomic status (theme 1) 75.9% of majority-BIPOC vs. 14.1% of majority-White counties were in the most vulnerable quartile. For household composition (theme 2), 55.1% of majority-BIPOC counties compared with 15.6% of majority-White counties were most vulnerable. The minority status and language theme (theme 3) measures racial/ethnic composition and is therefore almost entirely overlapping with the comparison of majority-White and majority-BIPOC rural counties; as such, 93.1% of BIPOC counties were most vulnerable, compared with 9.4% of majority-White counties. Finally, on the transportation and housing theme (theme 4), 65.5% of majority-BIPOC counties compared with 21.9% of majority-White counties were in the most vulnerable quartile.

3.3. Availability of Evidence-Based Supports for Maternal and Infant Health

Responding hospitals were located in rural communities that lacked many of the investigated evidence-based supports (Table 4). At least half of the communities did not have the following evidence-based supports available: nurse home visiting in the prenatal and postpartum periods, midwifery care, group prenatal care, doula care, and postpartum peer support groups. Availability of evidence-based supports also varied significantly between the most and less socially vulnerable counties. Nurse home visiting in the prenatal period was significantly less available in the most vulnerable communities (24.2% vs. 47.4%; p = 0.03), as were lactation support from IBCLCs (48.5% vs. 70.2%; p = 0.04), doula care (33.3% vs. 59.7%; p = 0.02), postpartum support groups (27.3% vs. 61.4%; p < 0.01), and childbirth education classes (75.8% vs. 98.3%; p < 0.01). While not significantly different, many additional evidence-based supports were also less available in the most vulnerable counties, including traditional model/individual prenatal care, nurse home visiting in the postpartum period, perinatal mental health services, care from nurse-midwives, and breastfeeding support groups. The most vulnerable counties had greater availability of group prenatal care and WIC programming, but these differences were also not statistically significant.
In logistic regression models adjusted for geography (census region and urban adjacency) and hospital size, the likelihood of availability of many evidence-based supports was significantly lower in the most vulnerable counties compared with the less vulnerable counties (Table 5). Evidence-based supports that were significantly less likely to be available in the most vulnerable counties included: lactation support from IBCLCs (aOR 0.36, 95% CI 0.13–0.97), midwifery care from certified nurse-midwives (CNM; aOR 0.35, 95% CI 0.12–0.99), doula care (aOR 0.30, 95% CI 0.11–0.84), postpartum support groups (aOR 0.25, 95% CI 0.09–0.68), and childbirth education classes (aOR 0.08, 95% CI 0.01–0.69). WIC availability was nearly ubiquitous and was therefore not analyzed in logistic regression models.

4. Discussion

This study highlighted inequities in the availability of evidence-based supports for maternal and infant health for many of the nation’s most vulnerable residents, especially those with intersecting identities of rural resident and BIPOC race/ethnicity. The counties where responding hospitals were located differed in respect to their social vulnerability, with majority-BIPOC rural counties being more socially vulnerable across all dimensions of the SVI when compared to majority-White rural counties. The availability of evidence-based supports, programs and interventions that have been shown to improve maternal and infant health outcomes [2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,27,28,29,30,31,32] also differed, with more vulnerable counties having significantly less access to these resources. This inequitable access is noteworthy given known health inequities for rural BIPOC birthing people and their infants [56,76].
Structural racism has been associated with poor health in both urban and non-urban areas [57,65] as well as with poorer maternal and infant birth outcomes for Black and Indigenous people [57,77,78,79,80,81]. For example, Black infants in areas with high levels of structural racism have higher odds of preterm birth and infant mortality [57,80,82]. Many of the variables used to calculate the SVI have been identified as indicators of structural racism [43,70,83,84,85]. This analysis showed that majority-BIPOC rural counties had significantly higher rates of social vulnerability across all dimensions, further indicating that structural racism exists in many types of community, including rural spaces. Further, the decreased availability of evidence-based supports in the most vulnerable counties, which tend to be majority-BIPOC, and the inequities in birth outcomes experienced by rural BIPOC families may be evidence of structural racism.
These findings point toward a number of policy implications that may increase access to evidence-based supports to improve rural maternal and infant health. This analysis showed that lactation support from IBCLCs was significantly less likely to be available to birthing people in the most vulnerable rural counties. Breastfeeding rates are lower among Black and Indigenous women and birthing people in the US [86], who were more likely to live in the most vulnerable counties in our study. This study highlighted that WIC, which often provides peer lactation support but not as frequently IBCLC breastfeeding support [87], was available in almost all responding hospitals’ rural counties. If appropriations for WIC were increased, this could potentially increase the capacity of local WIC agencies to offer IBCLC lactation support and breastfeeding support groups in rural BIPOC communities, potentially increasing breastfeeding rates for those most at risk due to social vulnerability [10,11].
Medicaid is an important source of financing for care during pregnancy, childbirth, and postpartum in rural communities [88]. Medicaid policies regarding coverage may impact access to evidence-based supports for Medicaid participants, who by virtue of qualifying for Medicaid would be considered socioeconomically vulnerable. Medicaid coverage, which varies by state, may impact access to many of the resources discussed including midwifery care, doula coverage, group prenatal care, childbirth education classes, visiting nurse services, and breastfeeding support from IBCLC. Additional efforts to increase enrollment of pregnant people who qualify for WIC and Medicaid as early as possible in their pregnancy may further increase early access to evidence-based supports for those who would benefit from them most.
Workforce retention and recruitment programs are an additional policy lever to improving availability of evidence-based supports in rural communities. Workforce policies and programs that could improve access to evidence-based supports and services include: expanding insurance reimbursement for and systemic integration of midwifery services [89], increasing training opportunities in perinatal mental health screening and treatment for a variety of mental health clinicians who are already living and practicing in rural areas (primary care providers, social workers, clinical psychologists, etc.), expanding student loan forgiveness programs for health professionals practicing in rural communities [90], subsidizing training programs for doulas of color, and expanding insurance reimbursement for doula care [91].

5. Limitations

This study has a number of limitations. The SVI is the main exposure variable and includes race/ethnicity as a variable in the calculation of overall SVI score and for calculating theme 3; therefore, the overall SVI and theme 3 scores are skewed toward higher scores for majority-BIPOC counties. However, given that the majority-BIPOC counties were significantly more vulnerable in all subthemes, not solely the one that includes race and language variables as indicators, the SVI remains a relevant exposure variable to evaluate relative social vulnerability across the US. Because it was not possible to exclude the minority status (theme 3) portion from the overall SVI score as our outcome, we conducted sensitivity analyses controlling for theme 3 scores, and results were substantively unchanged. This analysis only included rural communities that have an operating hospital with a labor and birth unit and, therefore, did not examine availability of evidence-based supports in rural communities that do not have a hospital with a labor and birth unit, which includes more than half of all rural counties [92]. Given the characteristics of rural counties without hospital-based labor and birth care [50,92,93,94], it is likely that these communities have even less availability of evidence-based supports for pregnancy and childbirth.
Survey responses may be biased toward greater reporting of supports available in the community, as administrators who completed the survey may have felt more confident in their hospital and community resources than those who did not participate. This would likely over-represent support access. Alternatively, because the survey respondents were hospital-based, respondents may not be aware of all supports available in non-hospital settings in the community, which could undercount support. Future research could explore barriers to access to supports available within rural communities and broaden assessment of evidence-based sexual and reproductive supports beyond the pregnancy and postpartum period.
The ongoing COVID-19 pandemic impacted hospital administrator availability to participate in research and may also have influenced responses. Responding and non-responding hospitals were not significantly dissimilar, other than responding hospitals being more likely to be located in the West and less likely to be located in the South [63]. A strength of this study is that it is among the first to collect data about availability of evidence-based maternal and infant health resources from rural communities themselves, and it presents new information on social vulnerability and social determinants of maternal and infant health in rural US counties.

6. Conclusions

Rural communities have significant diversity in their social vulnerability, with majority-BIPOC counties having greater vulnerability across all dimensions. The most socially vulnerable rural communities (especially those with a majority-BIPOC population) are also the least likely to have access to community resources to promote maternal and infant health.

Author Contributions

Conceptualization, K.B.K., B.B.I. and J.D.I.; methodology, B.B.I., J.D.I., A.H.F., M.S.T. and K.B.K.; software, J.D.I. and B.B.I.; formal analysis, B.B.I. and J.D.I.; investigation, B.B.I. and J.D.I.; data curation, J.D.I. and B.B.I.; writing—original draft preparation, B.B.I., M.S.T. and A.H.F.; writing—review and editing, B.B.I., M.S.T., J.D.I., A.H.F. and K.B.K.; supervision, K.B.K. and B.B.I.; project administration, K.B.K. and B.B.I.; funding acquisition, K.B.K. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Federal Office of Rural Health Policy (FORHP), Health Resources and Services Administration (HRSA), US Department of Health and Human Services (HHS) under PHS Cooperative Agreement No. 5U1CRH03717. This research was also supported by the NIH National Center for Advancing Translational Sciences, grant UL1TR002494. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and deemed exempt by the Institutional Review Board of The University of Minnesota (protocol code 00010917, 6 October 2020).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data used to create the sampling frame for this survey include information that is subject to a data use agreement and cannot be made available to others. The survey instrument is available as an online supplemental document (doi:10.1001/jamahealthforum.2022.0204), and analytic code can be provided by the corresponding author on request.

Acknowledgments

The authors gratefully acknowledge assistance from the American Hospital Association in supporting outreach to rural hospitals in this study. The authors appreciate input from the University of Minnesota Rural Health Research Center Expert Workgroup and the rural hospital administrators and clinicians that participated in pilot testing. None of these individuals or organizations received financial compensation for their input. The authors also appreciate research assistance from Mary Gilbertson, MPH and Phoebe Chastain as well as data collection support from Maria Bertrand, MPH. Gilbertson, Chastain, and Bertrand are affiliated with the Rural Health Research Center, University of Minnesota School of Public Health, and received salary support from the above-named grant (Cooperative Agreement No. 5U1CRH03717).

Conflicts of Interest

The authors declare no conflict of interest. Kozhimannil, Interrante, and Tuttle reported support from the Health Resources and Services Administration PHS Cooperative Agreement No. 5U1CRH03717. Kozhimannil and Basile Ibrahim reported support from the National Institutes of Health National Center for Advancing Translational Sciences, grant UL1TR002494.

References

  1. West, R.; DiMeo, A.; Langer, A.; Shah, N.; Molina, R.L. Addressing Racial/Ethnic Inequities in Maternal Health Through Community-Based Social Support Services: A Mixed Methods Study. Matern. Child Health J. 2021, 26, 708–718. [Google Scholar] [CrossRef] [PubMed]
  2. Kitsantas, P.; Gaffney, K.F.; Cheema, J. Life Stressors and Barriers to Timely Prenatal Care for Women with High-Risk Pregnancies Residing in Rural and Nonrural Areas. Women’s Health Issues 2012, 22, e455–e460. [Google Scholar] [CrossRef] [PubMed]
  3. Phillippi, J.C.; Myers, C.R.; Schorn, M.N. Facilitators of prenatal care access in rural Appalachia. Women Birth 2014, 27, e28–e35. [Google Scholar] [CrossRef] [PubMed]
  4. Sambrook Smith, M.; Lawrence, V.; Sadler, E.; Easter, A. Barriers to Accessing Mental Health Services for Women with Perinatal Mental Illness: Systematic Review and Meta-Synthesis of Qualitative Studies in the UK. BMJ Open 2019, 9, 24803. [Google Scholar] [CrossRef]
  5. Galbally, M.; Blankley, G.; Power, J.; Snellen, M. Perinatal Mental Health Services: What Are They and Why Do We Need Them? Australas. Psychiatry 2013, 21, 165–170. [Google Scholar] [CrossRef]
  6. Adane, A.A.; Bailey, H.D.; Morgan, V.A.; Galbally, M.; Farrant, B.M.; Marriott, R.; White, S.W.; Shepherd, C.C. The Impact of Maternal Prenatal Mental Health Disorders on Stillbirth and Infant Mortality: A Systematic Review and Meta-Analysis. Arch. Women’s Ment. Health 2021, 24, 543–555. [Google Scholar] [CrossRef]
  7. Reno, R.; Burch, J.; Stookey, J.; Jackson, R.; Joudeh, L.; Guendelman, S. Preterm Birth and Social Support Services for Prenatal Depression and Social Determinants. PLoS ONE 2021, 16, e0255810. [Google Scholar] [CrossRef]
  8. Haase, B.; Brennan, E.; Wagner, C.L. Effectiveness of the IBCLC: Have We Made an Impact on the Care of Breastfeeding Families over the Past Decade? J. Hum. Lact. 2019, 35, 441–452. [Google Scholar] [CrossRef]
  9. Chetwynd, E.M.; Wasser, H.M.; Poole, C. Breastfeeding Support Interventions by International Board Certified Lactation Consultants: A Systemic Review and Meta-Analysis. J. Hum. Lact. 2019, 35, 424–440. [Google Scholar] [CrossRef]
  10. Patel, S.; Patel, S. The Effectiveness of Lactation Consultants and Lactation Counselors on Breastfeeding Outcomes. J. Hum. Lact. 2016, 32, 530–541. [Google Scholar] [CrossRef]
  11. Cohen, S.S.; Alexander, D.D.; Krebs, N.F.; Young, B.E.; Cabana, M.D.; Erdmann, P.; Hays, N.P.; Bezold, C.P.; Levin-Sparenberg, E.; Turini, M.; et al. Factors Associated with Breastfeeding Initiation and Continuation: A Meta-Analysis. J. Pediatr. 2018, 203, 190–196.e21. [Google Scholar] [CrossRef] [Green Version]
  12. Olds, D.L.; Kitzman, H.; Anson, E.; Smith, J.A.; Knudtson, M.D.; Miller, T.; Cole, R.; Hopfer, C.; Conti, G. Prenatal and Infancy Nurse Home Visiting Effects on Mothers: 18-Year Follow-up of a Randomized Trial. Pediatrics 2019, 144, e20183889. [Google Scholar] [CrossRef]
  13. Kitzman, H.; Olds, D.L.; Knudtson, M.D.; Cole, R.; Anson, E.; Smith, J.A.; Fishbein, D.; DiClemente, R.; Wingood, G.; Caliendo, A.M.; et al. Prenatal and Infancy Nurse Home Visiting and 18-Year Outcomes of a Randomized Trial. Pediatrics 2019, 144, e20183876. [Google Scholar] [CrossRef]
  14. Olds, D.L.; Kitzman, H.; Knudtson, M.D.; Anson, E.; Smith, J.A.; Cole, R. Effect of Home Visiting by Nurses on Maternal and Child Mortality: Results of a 2-Decade Follow-up of a Randomized Clinical Trial. JAMA Pediatr. 2014, 168, 800–806. [Google Scholar] [CrossRef]
  15. Gadson, A.; Akpovi, E.; Mehta, P.K. Exploring the social determinants of racial/ethnic disparities in prenatal care utilization and maternal outcome. Semin. Perinatol. 2017, 41, 308–317. [Google Scholar] [CrossRef]
  16. Loewenberg Weisband, Y.; Klebanoff, M.; Gallo, M.F.; Shoben, A.; Norris, A.H. Birth Outcomes of Women Using a Midwife versus Women Using a Physician for Prenatal Care. J. Midwifery Women’s Health 2018, 63, 399–409. [Google Scholar] [CrossRef]
  17. McRae, D.N.; Muhajarine, N.; Stoll, K.; Mayhew, M.; Vedam, S.; Mpofu, D.; Janssen, P.A. Is Model of Care Associated with Infant Birth Outcomes among Vulnerable Women? A Scoping Review of Midwifery-Led versus Physician-Led Care. SSM Popul. Health 2016, 2, 182–193. [Google Scholar] [CrossRef] [Green Version]
  18. Catling, C.J.; Medley, N.; Foureur, M.; Ryan, C.; Leap, N.; Teate, A.; Homer, C.S. Group versus conventional antenatal care for women. Cochrane Database Syst. Rev. 2015, 2015, CD007622. [Google Scholar] [CrossRef] [Green Version]
  19. Ickovics, J.R.; Kershaw, T.S.; Westdahl, C.; Magriples, U.; Massey, Z.; Reynolds, H.; Rising, S.S. Group Prenatal Care and Perinatal Outcomes: A Randomized Controlled Trial. Obstet. Gynecol. 2007, 110, 330–339. [Google Scholar] [CrossRef] [Green Version]
  20. Gruber, K.J.; Cupito, S.H.; Dobson, C.F. Impact of Doulas on Healthy Birth Outcomes. J. Perinat. Educ. 2013, 22, 49–58. [Google Scholar] [CrossRef] [Green Version]
  21. Kozhimannil, K.B.; Hardeman, R.R.; Alarid-Escudero, F.; Vogelsang, C.A.; Blauer-Peterson, C.; Howell, E.A. Modeling the Cost-Effectiveness of Doula Care Associated with Reductions in Preterm Birth and Cesarean Delivery. Birth 2016, 43, 20–27. [Google Scholar] [CrossRef]
  22. Mallick, L.M.; Thoma, M.E.; Shenassa, E.D. The role of doulas in respectful care for communities of color and Medicaid recipients. Birth 2022, 1–10. [Google Scholar] [CrossRef] [PubMed]
  23. Thomas, M.P.; Ammann, G.; Brazier, E.; Noyes, P.; Maybank, A. Doula Services within a Healthy Start Program: Increasing Access for an Underserved Population. Matern. Child Health J. 2017, 21 (Suppl. S1), 59–64. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Platt, T.; Kaye, N. Four State Strategies to Employ Doulas to Improve Maternal Health and Birth Outcomes in Medicaid. 2020. Available online: https://www.nashp.org/wp-content/uploads/2020/07/Doula-Brief-7.6.2020.pdf (accessed on 3 March 2021).
  25. Hadebe, R.; Seed, P.T.; Essien, D.; Headen, K.; Mahmud, S.; Owasil, S.; Turienzo, C.F.; Stanke, C.; Sandall, J.; Bruno, M.; et al. Can Birth Outcome Inequality Be Reduced Using Targeted Caseload Midwifery in a Deprived Diverse Inner City Population? A Retrospective Cohort Study, London, UK. BMJ Open 2021, 11, e049991. [Google Scholar] [CrossRef]
  26. Novick, G.; Womack, J.A.; Lewis, J.; Stasko, E.C.; Rising, S.S.; Sadler, L.S.; Cunningham, S.C.; Tobin, J.N.; Ickovics, J.R. Perceptions of Barriers and Facilitators During Implementation of a Complex Model of Group Prenatal Care in Six Urban Sites. Res. Nurs. Health 2015, 38, 462–474. [Google Scholar] [CrossRef] [Green Version]
  27. Kamalifard, M.; Yavarikia, P.; Babapour Kheiroddin, J.; Salehi Pourmehr, H.; Iraji Iranagh, R. The Effect of Peers Support on Postpartum Depression: A Single-Blind Randomized Clinical Trial. J. Caring Sci. 2013, 2, 237–244. [Google Scholar]
  28. Silbert Flagg, J.; Balbier, E. Impact of Mother’s Breastfeeding Support: Lactation Support Provided in a Group Setting. J. Pregnancy Child Health 2016, 3, 274. [Google Scholar] [CrossRef]
  29. Demirtas, B. Strategies to Support Breastfeeding: A Review. Int. Nurs. Rev. 2012, 59, 474–481. [Google Scholar] [CrossRef]
  30. Gluck, O.; Pinchas-Cohen, T.; Hiaev, Z.; Rubinstein, H.; Bar, J.; Kovo, M. The Impact of Childbirth Education Classes on Delivery Outcome. Int. J. Gynecol. Obstet. 2020, 148, 300–304. [Google Scholar] [CrossRef]
  31. Figlio, D.; Hamersma, S.; Roth, J. Does prenatal WIC participation improve birth outcomes? New evidence from Florida. J. Public Econ. 2009, 93, 235–245. [Google Scholar] [CrossRef]
  32. Chorniy, A.; Currie, J.; Sonchak, L. Does Prenatal WIC Participation Improve Child Outcomes? Am. J. Health Econ. 2020, 6, 169–198. [Google Scholar] [CrossRef]
  33. Crear-Perry, J.; Correa-De-Araujo, R.; Lewis Johnson, T.; Mclemore, M.R.; Neilson, E.; Wallace, M. Social and Structural Determinants of Health Inequities in Maternal Health. J. Women’s Health 2021, 30, 230–235. [Google Scholar] [CrossRef]
  34. World Health Organization. A Conceptual Framework for Action on the Social Determinants of Health; World Health Organization: Geneva, Switzerland, 2010; p. 78. [Google Scholar]
  35. Jones, G.L.; Mitchell, C.A.; Hirst, J.E.; Anumba, D.O.C. Understanding the relationship between social determinants of health and maternal mortality. BJOG Int. J. Obstet. Gynaecol. 2022, 129, 1211–1228. [Google Scholar] [CrossRef]
  36. Dagher, R.K.; Linares, D.E. A Critical Review on the Complex Interplay between Social Determinants of Health and Maternal and Infant Mortality. Children 2022, 9, 394. [Google Scholar] [CrossRef]
  37. CDC. Agency for Toxic Substances and Disease Registry. CDC Social Vulnerability Index (SVI). Available online: https://www.atsdr.cdc.gov/placeandhealth/svi/index.html (accessed on 13 December 2020).
  38. Flanagan, B.E.; Hallisey, E.J.; Adams, E.; Lavery, A. Measuring Community Vulnerability to Natural and Anthropogenic Hazards: The Centers for Disease Control and Prevention’s Social Vulnerability Index. J. Environ. Health 2018, 80, 34–36. Available online: https://svi.cdc.gov/Documents/Publications/CDC_ATSDR_SVI_Materials/JEH2018.pdf (accessed on 12 August 2020).
  39. Centers for Disease Control. CDC SVI 2018 Documentation. Atlanta. 2020. Available online: https://svi.cdc.gov/Documents/Data/2018_SVI_Data/SVI2018Documentation.pdf (accessed on 28 January 2021).
  40. Phyllis Jones, C. “Race,” Racism, and the Practice of Epidemiology Jones Invited Commentary: “Race,” Racism, and the Practice of Epidemiology. Am. J. Epidemiol. 2001, 154, 299–304. [Google Scholar] [CrossRef] [Green Version]
  41. Slaughter-Acey, J.C.; Caldwell, C.H.; Misra, D.P. The influence of personal and group racism on entry into prenatal care among-African American Women. Women’s Health Issues 2013, 23, e381–e387. [Google Scholar] [CrossRef] [Green Version]
  42. Gee, G.C.; Hicken, M.T. Structural Racism: The Rules and Relations of Inequity. Ethn. Dis. 2021, 31 (Suppl. S1), 293–300. [Google Scholar] [CrossRef]
  43. Bailey, Z.D.; Krieger, N.; Agénor, M.; Graves, J.; Linos, N.; Bassett, M.T. Structural Racism and Health Inequities in the USA: Evidence and Interventions. Lancet 2017, 389, 1453–1463. [Google Scholar] [CrossRef]
  44. Perez, M.T.; Bucholz, E.; Asimacopoulos, E.; Ferraro, A.M.; Salem, S.M.; Schauer, J.; Holleman, C.; Sekhavat, S.; Tworetzky, W.; Powell, A.J.; et al. Impact of Maternal Social Vulnerability and Timing of Prenatal Care on Outcome of Prenatally Detected Congenital Heart Disease. Ultrasound Obstet. Gynecol. 2022. [Google Scholar] [CrossRef]
  45. Givens, M.; Teal, E.N.; Patel, V.; Manuck, T.A. Preterm Birth among Pregnant Women Living in Areas with High Social Vulnerability. Am. J. Obstet. Gynecol. MFM 2021, 3, 100414. [Google Scholar] [CrossRef] [PubMed]
  46. Yee, C.W.; Cunningham, S.D.; Ickovics, J.R. Application of the Social Vulnerability Index for Identifying Teen Pregnancy Intervention Need in the United States. Matern. Child Health J. 2019, 23, 1516–1524. [Google Scholar] [CrossRef] [PubMed]
  47. Angelidou, A.; Sullivan, K.; Melvin, P.R.; Shui, J.E.; Goldfarb, I.T.; Bartolome, R.; Chaudhary, N.; Vaidya, R.; Culic, I.; Singh, R.; et al. Association of Maternal Perinatal SARS-CoV-2 Infection with Neonatal Outcomes during the COVID-19 Pandemic in Massachusetts. JAMA Netw. Open 2021, 4, e217523. [Google Scholar] [CrossRef]
  48. Wilcox, A.; Levi, E.E.; Garrett, J.M. Predictors of Non-Attendance to the Postpartum Follow-up Visit. Matern. Child Health J. 2016, 20 (Suppl. S1), 22–27. [Google Scholar] [CrossRef] [PubMed]
  49. Sealy-Jefferson, S.; Misra, D.P. Neighborhood Tax Foreclosures, Educational Attainment, and Preterm Birth among Urban African American Women. Int. J. Environ. Res. Public Health 2019, 16, 904. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  50. Kozhimannil, K.B.; Hung, P.; Prasad, S.; Casey, M.; Moscovice, I. Rural-Urban Differences in Obstetric Care, 2002–2010, and Implications for the Future. Med. Care 2014, 52, 4–9. [Google Scholar] [CrossRef] [Green Version]
  51. Kozhimannil, K.B.; Interrante, J.D.; Henning-Smith, C.; Admon, L.K. Rural-Urban Differences in Severe Maternal Morbidity and Mortality in The US, 2007–2015. Health Aff. 2019, 38, 2077–2085. [Google Scholar] [CrossRef] [PubMed]
  52. National Academies of Sciences Engineering and Medicine. Birth Settings in America: Outcomes, Quality, Access, and Choice; National Academies of Sciences Engineering and Medicine: Washington, DC, USA, 2020. [Google Scholar]
  53. Rossen, L.M.; Ahrens, K.A.; Womack, L.S.; Uddin, S.F.G.; Branum, A.M.; Rossen, L. Rural-Urban Differences in Maternal Mortality Trends in the US, 1999–2017: Accounting for the Impact of the Pregnancy Status Checkbox. Am. J. Epidemiol. 2022, 191, 1030–1039. [Google Scholar] [CrossRef]
  54. Beal, J.A. Infant Mortality is Higher in Rural Counties. MCN Am. J. Matern. Child Nurs. 2021, 46, 118. [Google Scholar] [CrossRef]
  55. Ely, D.M.; Driscoll, A.K.; Mathews, T.J. Infant Mortality Rates in Rural and Urban Areas in the United States, 2014 Key Findings Data from the National Vital Statistics System; US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics: Hyattsville, MD, USA, 2014.
  56. Singh, G. Trends and Social Inequalities in Maternal Mortality in the United. Int. J. Matern. Child Health AIDS 2021, 10, 29–42. [Google Scholar] [CrossRef]
  57. Vilda, D.; Hardeman, R.; Dyer, L.; Theall, K.P.; Wallace, M. Structural Racism, Racial Inequities and Urban–Rural Differences in Infant Mortality in the US. J. Epidemiol. Community Health 2021, 75, 788–793. [Google Scholar] [CrossRef]
  58. Kozhimannil, K.B.; Henning-Smith, C.; Hung, P. The Practice of Midwifery in Rural US Hospitals. J. Midwifery Women’s Health 2016, 61, 411–418. [Google Scholar] [CrossRef]
  59. Koschwanez, H.; Harrington, J.; Fischer, M.L.; Beck, E.; Kennedy, M. Certified Nurse-Midwives in Rural Kansas Hospitals: A Survey of Senior Hospital Administrators. J. Midwifery Women’s Health 2021, 66, 512–519. [Google Scholar] [CrossRef]
  60. Blair, A.; MacGregor, E.; Lee, N. Childhood Obesity and Breastfeeding Rates in Pennsylvania Counties—Spatial Analysis of the Lactation Support Landscape. Front. Public Health 2020, 8, 123. [Google Scholar] [CrossRef] [Green Version]
  61. Flood, J.L. Breastfeeding Supports and Services in Rural Hawaii: Perspectives of Community Healthcare Workers. Nurs. Res. Pract. 2017, 2017, 6041462. [Google Scholar] [CrossRef] [Green Version]
  62. Grubesic, T.H.; Durbin, K.M. Breastfeeding Support: A Geographic Perspective on Access and Equity. J. Hum. Lact. 2017, 33, 770–780. [Google Scholar] [CrossRef]
  63. Kozhimannil, K.B.; Interrante, J.D.; Admon, L.K.; Basile Ibrahim, B.L. Rural Hospital Administrators’ Beliefs About Safety, Financial Viability, and Community Need for Offering Obstetric Care Key Points. JAMA Health Forum 2022, 3, e220204. [Google Scholar] [CrossRef]
  64. Interrante, J.; Carroll, C.; Handley, S.; Kozhimannil, K. An Enhanced Method for Identifying Hospital Based Obstetric Unit Status: Methodology Brief. Minneapolis. 2022. Available online: https://3pea7g1qp8f3t9ooe3z3npx1-wpengine.netdna-ssl.com/wp-content/uploads/2022/01/UMN-OB-Unit-Identification-Methods_7.pdf (accessed on 13 January 2022).
  65. Bell, C.N.; Owens-Young, J.L. Self-Rated Health and Structural Racism Indicated by County-Level Racial Inequalities in Socioeconomic Status: The Role of Urban-Rural Classification. J. Urban Health 2020, 97, 52–61. [Google Scholar] [CrossRef]
  66. US Census Bureau. Census Regions and Divisions of the United States. 2019. Available online: https://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf (accessed on 21 August 2019).
  67. An, R.; Xiang, X. Social vulnerability and leisure-time physical inactivity among US adults. Am. J. Health Behav. 2015, 39, 751–760. [Google Scholar] [CrossRef]
  68. Dasgupta, S.; Bowen, V.B.; Leidner, A.; Fletcher, K.; Musial, T.; Rose, C.; Cha, A.; Kang, G.; Dirlikov, E.; Pevzner, E.; et al. Association between Social Vulnerability and a County’s Risk for Becoming a COVID-19 Hotspot—United States, June 1–July 25, 2020. MMWR Morb. Mortal. Wkly. Rep. 2020, 69, 1535–1541. [Google Scholar] [CrossRef]
  69. Diaz, A.; Chavarin, D.; Paredes, A.Z.; Tsilimigras, D.I.; Pawlik, T.M. Association of Neighborhood Characteristics with Utilization of High-Volume Hospitals among Patients Undergoing High-Risk Cancer Surgery. Ann. Surg. Oncol. 2020, 28, 617–631. [Google Scholar] [CrossRef]
  70. Basile Ibrahim, B.; Barcelona, V.; Condon, E.M.; Crusto, C.A.; Taylor, J.Y. The Association between Neighborhood Social Vulnerability and Cardiovascular Health Risk among Black/African American Women in the InterGEN Study. Nurs. Res. 2021, 70, S3. [Google Scholar] [CrossRef]
  71. Federal Office of Rural Health Policy (FORHP) Data Files | HRSA. Available online: https://www.hrsa.gov/rural-health/about-us/what-is-rural/data-files (accessed on 18 May 2022).
  72. Flanagan, B.E.; Gregory, E.W.; Hallisey, E.J.; Heitgerd, J.L.; Lewis, B. A Social Vulnerability Index for Disaster Management. J. Homel. Secur. Emerg. Manag. 2011, 8. [Google Scholar] [CrossRef]
  73. Area Health Resources Files. Available online: https://data.hrsa.gov/topics/health-workforce/ahrf (accessed on 15 June 2022).
  74. AHA Annual Survey DatabaseTM | AHA Data. Available online: https://www.ahadata.com/aha-annual-survey-database (accessed on 15 June 2022).
  75. Basile Ibrahim, B.; Tuttle, M.; Fritz, A.H.; Interrante, J.; Kozhimannil, K.B. Racial Inequities in the Availability of Evidence-Based Supports for Maternal and Infant Health in Rural US Counties: Policy Brief; University of Minnesota Rural Health Research Center: Minneapolis, MN, USA, 2022. [Google Scholar]
  76. Kozhimannil, K.B.; Interrante, J.D.; Tofte, A.N.; Admon, L.K. Severe Maternal Morbidity and Mortality among Indigenous Women in the United States. Obstet. Gynecol. 2020, 135, 294–300. [Google Scholar] [CrossRef] [Green Version]
  77. Chantarat, T.; Van Riper, D.C.; Hardeman, R.R. Multidimensional Structural Racism Predicts Birth Outcomes for Black and White Minnesotans. Health Serv. Res. 2022, 57, 448–457. [Google Scholar] [CrossRef]
  78. Vilda, D.; Wallace, M.; Dyer, L.; Harville, E.; Theall, K. Income inequality and racial disparities in pregnancy-related mortality in the US. SSM Popul. Health 2019, 1, 100477. [Google Scholar] [CrossRef]
  79. Wang, E.; Glazer, K.B.; Howell, E.A.; Janevic, T.M. Social Determinants of Pregnancy-Related Mortality and Morbidity in the United States: A Systematic Review. Obstet. Gynecol. 2020, 135, 896–915. [Google Scholar] [CrossRef]
  80. Pabayo, R.; Ehntholt, A.; Davis, K.; Liu, S.Y.; Muennig, P.; Cook, D.M. Structural Racism and Odds for Infant Mortality among Infants Born in the United States 2010. J. Racial Ethn. Health Disparities 2019, 6, 1095–1106. [Google Scholar] [CrossRef]
  81. Liu, S.; Fiorentini, C.; Bailey, Z.; Huynh, M.; McVeigh, K.; Kaplan, D. Structural Racism and Severe Maternal Morbidity in New York State. Clin. Med. Insights Women’s Health 2019, 12. [Google Scholar] [CrossRef] [Green Version]
  82. Chambers, B.D.; Baer, R.J.; McLemore, M.R.; Jelliffe-Pawlowski, L.L. Using Index of Concentration at the Extremes as Indicators of Structural Racism to Evaluate the Association with Preterm Birth and Infant Mortality—California, 2011–2012. J. Urban Health 2019, 96, 159–170. [Google Scholar] [CrossRef] [Green Version]
  83. Wallace, M.; Crear-Perry, J.; Richardson, L.; Tarver, M.; Theall, K. Separate and unequal: Structural racism and infant mortality in the US. Health Place 2017, 45, 140–144. [Google Scholar] [CrossRef] [PubMed]
  84. Groos, M.; Wallace, M.; Hardeman, R.; Theall, K. Measuring Inequity: A Systematic Review of Methods Used to Quantify Structural Racism. J. Health Disparities Res. Pract. 2018, 11, 13. [Google Scholar]
  85. Bailey, Z.D.; Feldman, J.M.; Bassett, M.T. How Structural Racism Works—Racist Policies as a Root Cause of U.S. Racial Health Inequities. N. Engl. J. Med. 2021, 384, 768–773. [Google Scholar] [CrossRef] [PubMed]
  86. Chiang, K.V.; Li, R.; Anstey, E.H.; Perrine, C.G. Racial and Ethnic Disparities in Breastfeeding Initiation—United States, 2019. MMWR Morb. Mortal. Wkly. Rep. 2021, 70, 769–774. [Google Scholar] [CrossRef]
  87. Enhancing Breastfeeding Support in WIC: The Case for Increasing the Number of International Board Certified Lactation Consultants. Available online: www.cdc.gov/breastfeeding/ (accessed on 7 June 2022).
  88. Medicaid and CHIP Payment and Access Commission (MACPAC). Chapter 5: Medicaid’s Role in Maternal Health. In Medicaid’s Role in Maternal Health; Medicaid and CHIP Payment and Access Commission (MACPAC): Washington, DC, USA, 2020. [Google Scholar]
  89. Vedam, S.; Stoll, K.; MacDorman, M.; Declercq, E.; Cramer, R.; Cheyney, M.; Fisher, T.; Butt, E.; Yang, Y.T.; Powell Kennedy, H. Mapping integration of midwives across the United States: Impact on access, equity, and outcomes. PLoS ONE 2018, 13, e0192523. [Google Scholar] [CrossRef]
  90. Scholarships, Loans, and Loan Repayment for Rural Health Professions Overview—Rural Health Information Hub. Available online: https://www.ruralhealthinfo.org/topics/scholarships-loans-loan-repayment (accessed on 7 February 2022).
  91. Hardeman, R.R.; Kozhimannil, K.B. Motivations for Entering the Doula Profession: Perspectives from Women of Color. J. Midwifery Women’s Health 2016, 61, 773–780. [Google Scholar] [CrossRef]
  92. Hung, P.; Henning-Smith, C.E.; Casey, M.M.; Kozhimannil, K.B. Access to Obstetric Services in Rural Counties Still Declining, with 9 Percent Losing Services, 2004–2014. Health Aff. 2017, 36, 1663–1671. [Google Scholar] [CrossRef]
  93. Kozhimannil, K.B.; Casey, M.M.; Hung, P.; Prasad, S.; Moscovice, I.S. Location of childbirth for rural women: Implications for maternal levels of care. Am. J. Obstet. Gynecol. 2016, 214, 661.e1–661.e10. [Google Scholar] [CrossRef] [Green Version]
  94. Kozhimannil, K.B.; Hung, P.; Henning-Smith, C.; Casey, M.M.; Prasad, S. Association between Loss of Hospital-Based Obstetric Services and Birth Outcomes in Rural Counties in the United States. J. Am. Med. Assoc. 2018, 319, 1239–1247. [Google Scholar] [CrossRef]
Table
Table 1. Demographics of responding rural hospitals with labor and birth units, n = 93.
Table 1. Demographics of responding rural hospitals with labor and birth units, n = 93.
n (%) or Median [IQR]
Region
Northeast5 (5.4)
Midwest29 (31.2)
South26 (27.9)
West33 (35.5)
Rural county type by urban adjacency
Micropolitan, adjacent28 (30.1)
Micropolitan, non-adjacent32 (34.4)
Noncore, adjacent18 (19.4)
Noncore, non-adjacent15 (16.1)
Majority (≥50%) of county population is BIPOC29 (31.2)
Critical Access Hospital33 (35.5)
Number of births, 2019, median [IQR]274 [120–446]
Hospital average daily census, 2018, median [IQR]22 [10–53]
BIPOC = Black, Indigenous, People of Color.
Table
Table 2. Social Vulnerability Index scores of counties with responding rural hospitals with inpatient labor and birth services.
Table 2. Social Vulnerability Index scores of counties with responding rural hospitals with inpatient labor and birth services.
Social Vulnerability Index (SVI) ScoreFull Sample, n = 93
Median [IQR]		Majority-BIPOC County, n = 29
Median [IQR]		Majority-White, NH County, n = 64
Median [IQR]
Overall SVI score0.55 [0.25–0.88]0.93 [0.88–0.98]0.38 [0.19–0.64]
Theme 1-Socioeconomic status0.53 [0.23–0.92]0.89 [0.75–0.96]0.44 [0.18–0.63]
Theme 2-Household composition0.54 [0.33–0.82]0.82 [0.54–0.94]0.43 [0.21–0.67]
Theme 3-Minority status/language0.59 [0.25–0.89]0.94 [0.91–0.96]0.38 [0.19–0.63]
Theme 4-Transportation/housing0.62 [0.40–0.84]0.84 [0.61–0.91]0.47 [0.30–0.71]
SVI—Social Vulnerability Index; NH—non-Hispanic.
Table
Table 3. County-level social vulnerability (SVI) by racial majority of county population, for counties with responding rural hospitals with inpatient labor and birth services.
Table 3. County-level social vulnerability (SVI) by racial majority of county population, for counties with responding rural hospitals with inpatient labor and birth services.
Full Sample, n = 93 (%)Majority-BIPOC County n = 29 (%)Majority-White, NH County, n = 64 (%)p-Value
Overall SVI score in most vulnerable quartile ^34 (36.6)25 (86.2)9 (14.1)<0.01
Theme 1-Socioeconomic status31 (33.3)22 (75.9)9 (14.1)<0.01
Theme 2-Household composition26 (28.0)16 (55.1)10 (15.6)<0.01
Theme 3-Minority status/language33 (35.5)27 (93.1)6 (9.4)<0.01
Theme 4-Transportation/housing33 (35.5)19 (65.5)14 (21.9)<0.01
p-values are chi-square for responding hospitals in majority-BIPOC counties vs. majority-White counties. SVI—Social Vulnerability Index; NH—non-Hispanic. ^ Most vulnerable quartile = SVI score ≥ 0.75 on national scale.
Table
Table 4. County-level social vulnerability and availability of evidence-based supports in 93 counties with responding rural hospitals.
Table 4. County-level social vulnerability and availability of evidence-based supports in 93 counties with responding rural hospitals.
Total,
n = 90 (%)		Most Vulnerable
Quartile, ^
n = 33 (%)		Less Vulnerable Quartiles, n = 57 (%)p-Value
Local access to care
Individual (traditional model) prenatal care85 (94.4)30 (90.9)55 (96.5)0.27
Nurse home visiting-prenatal period35(38.9)8 (24.2)27 (47.4)0.03
Nurse home visiting-postpartum period43 (47.8)12 (36.4)31 (54.4)0.10
Perinatal mental health services59 (65.6)19 (57.6)40 (70.2)0.23
Lactation support from IBCLC56 (62.2)16 (48.5)40 (70.2)0.04
Family-centered models of care
Midwifery care with CNM42 (46.7)13 (39.4)29 (50.9)0.29
Group prenatal care34 (38.2)13 (39.4)21 (37.5)0.86
Doula care45 (50.0)11 (33.3)34 (59.7)0.02
Peer and community supports for families
Postpartum support groups44 (48.9)9 (27.3)35 (61.4)<0.01
Breastfeeding support groups72 (80.0)23 (69.7)49 (86.0)0.06
Health-focused programming
Childbirth education classes81 (90.0)25 (75.8)56 (98.3)<0.01
Nutrition program (WIC)88 (97.8)33 (100)55 (96.5)0.28
p-values are chi-square for responding hospitals in the most socially vulnerable counties vs. the remainder of counties with responding rural hospitals. IBCLC—International Board-Certified Lactation Consultants; CNM—certified nurse-midwife; WIC—Special Supplemental Nutrition Program for Women, Infants, and Children. ^ Most vulnerable quartile = SVI score ≥ 0.75 on national scale.
Table
Table 5. Likelihood of availability of evidence-based birth supports and services in most vulnerable rural counties with rural hospitals with inpatient labor and birth services.
Table 5. Likelihood of availability of evidence-based birth supports and services in most vulnerable rural counties with rural hospitals with inpatient labor and birth services.
Evidence-Based Support/ServiceOR(95% CI)aOR ^(95% CI)
Local access to care
Individual (traditional model) prenatal care0.36(0.06–2.30)0.17(0.01–2.34)
Nurse home visiting-prenatal period0.36(0.14–0.92)0.41(0.15–1.15)
Nurse home visiting-postpartum period0.48(0.20–1.16)0.48(0.18–1.24)
Perinatal mental health services0.58(0.24–1.41)0.67(0.26–1.74)
Lactation support from IBCLC0.40(0.17–0.97)0.36(0.13–0.97)
Family-centered models of care
Midwifery care with CNM0.63(0.26–1.50)0.35(0.12–0.99)
Group prenatal care1.08(0.45–2.62)1.01(0.38–2.67)
Doula support0.34(0.14–0.83)0.30(0.11–0.84)
Peer and community supports for families
Postpartum support groups0.24(0.09–0.60)0.25(0.09–0.68)
Breastfeeding support groups0.38(0.13–1.08)0.42(0.14–1.29)
Health-focused programming
Childbirth education classes0.06(0.01–0.47)0.08(0.01–0.69)
Reference = less vulnerable counties (overall SVI < 0.75). ^ adjusted for geography (U.S. census region and urban adjacency) and hospital size (average daily census in 2018). IBCLC—International Board-Certified Lactation Consultants; CNM—certified nurse-midwife; OR—odds ratio; aOR—adjusted odds ratio; CI—confidence interval.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Basile Ibrahim, B.; Interrante, J.D.; Fritz, A.H.; Tuttle, M.S.; Kozhimannil, K.B. Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents. Children 2022, 9, 1077. https://doi.org/10.3390/children9071077

AMA Style

Basile Ibrahim B, Interrante JD, Fritz AH, Tuttle MS, Kozhimannil KB. Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents. Children. 2022; 9(7):1077. https://doi.org/10.3390/children9071077

Chicago/Turabian Style

Basile Ibrahim, Bridget, Julia D. Interrante, Alyssa H. Fritz, Mariana S. Tuttle, and Katy Backes Kozhimannil. 2022. "Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents" Children 9, no. 7: 1077. https://doi.org/10.3390/children9071077

APA Style

Basile Ibrahim, B., Interrante, J. D., Fritz, A. H., Tuttle, M. S., & Kozhimannil, K. B. (2022). Inequities in Availability of Evidence-Based Birth Supports to Improve Perinatal Health for Socially Vulnerable Rural Residents. Children, 9(7), 1077. https://doi.org/10.3390/children9071077

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop