Women with disabilities have a higher risk of severe maternal morbidity during delivery compared with those without disabilities, with the magnitude of risk varying by disability type.
Abstract
OBJECTIVE:
To estimate the risk of severe maternal morbidity (SMM) among women with disabilities compared with those without disabilities in a nationally representative sample of U.S. delivery hospitalizations.
METHODS:
We conducted a retrospective cohort analysis using the 2016–2021 Healthcare Cost and Utilization Project's Nationwide Inpatient Sample. We identified delivery hospitalizations and disability status using International Classification of Diseases, Tenth Revision diagnosis codes. The primary outcome was SMM, which was determined using 21 indicators specified by the Centers for Disease Control and Prevention. We used Poisson regression to estimate unadjusted and adjusted relative risks (aRRs) and 95% CIs for the association between disability status and type with SMM outcomes.
RESULTS:
Among 4,331,457 delivery hospitalizations, 128,413 (3.0%) were to women with disabilities. Women with disabilities had significantly higher rates of SMM compared with those without disabilities (396/10,000 deliveries vs 177/10,000 deliveries). In fully adjusted models, women with disabilities had an aRR of 1.86 (95% CI, 1.80–1.91) for one or more SMM indicators. The risk of SMM varied by disability type, with the highest risks observed for women who had vision disabilities (aRR 3.02, 95% CI, 2.70–3.38) or had physical disabilities (aRR 2.44, 95% CI, 2.34–2.55). Women with disabilities had the highest risk for other medical complications (puerperal cerebrovascular disorders and sickle cell disease with crisis), followed by other obstetric complications, respiratory complications, cardiovascular complications, acute renal failure, sepsis, and bleeding complications compared with women without disabilities.
CONCLUSION:
Women with disabilities have a significantly higher risk of SMM during delivery compared with those without disabilities, with the magnitude of risk varying by disability type. Efforts to reduce SMM and maternal mortality in the United States must prioritize the unique needs of this population and ensure equitable, disability-competent care for all women.
The United States is facing a maternal health crisis, with rates of severe maternal morbidity (SMM) increasing markedly from 2008 to 2021 to more than 179 SMM events per 10,000 deliveries.1 Despite considerable efforts to curb adverse maternal outcomes, significant disparities persist among marginalized groups.2
Approximately 18–19% of reproductive-aged women in the United States have disabilities.3,4 Prior studies have shown substantial disparities in perinatal care, complications, and adverse pregnancy, and birth outcomes experienced by women with disabilities compared with those without disabilities.5–11 Mitra et al leveraged U.S. hospital discharge records and found higher SMM risks among women with intellectual and developmental disabilities (IDD)12 and women who were deaf or hard of hearing (DHH)13 compared with those without disabilities, but national data on other types of disabilities are lacking. This knowledge gap hinders development of evidence-based practices and supports to mitigate risks in these vulnerable population groups.
A better understanding of SMM among women with different disabilities will inform the development of tailored risk assessments, counseling, and care coordination approaches across preconception, prenatal, and postpartum periods to address the unique needs of patients with specific types of disabilities. As such, this work is relevant to health care professionals, payors, policymakers, and other stakeholders seeking to improve care quality and reduce inequities.14
Supporting optimal perinatal care for patients with disabilities aligns with the American College of Obstetricians and Gynecologists' call to eliminate disparities in women's health.15 Our objective was to estimate the risk of SMM in women by disability status and type compared with peers without disabilities in nationally representative U.S. data. Based on prior evidence,12,16,17 we hypothesized that SMM risk would be elevated among women with disabilities, with the magnitude of risk varying by disability type.
METHODS
We conducted a retrospective cohort analysis of the HCUP-NIS (Healthcare Cost and Utilization Project's Nationwide Inpatient Sample), using data from 2016 to 2021. The HCUP-NIS contains discharge data for an approximately 20% stratified sample of hospital discharge from roughly 1,000 U.S. community hospitals.18 Each year consists of approximately 7 million hospital discharges. Each record details one hospitalization, with clinical resource use summarized using more than 100 data elements, including International Classification of Diseases, Tenth Revision (ICD-10) diagnosis and procedure codes. This study used publicly available deidentified secondary data and was granted a waiver of approval from the Brandeis University IRB.
The HCUP-NIS contained a combined total of 41,622,004 hospitalization records (Fig. 1). Of these, we identified 4,331,457 delivery hospitalizations using Kuklina et al's19 enhanced delivery identification method based on ICD-10 codes, which was shown to identify 3.4% more deliveries, including those with severe obstetric complications compared with other methods. From this cohort, we identified 128,413 deliveries to women with disability-related diagnoses for vision, hearing, physical, intellectual and developmental, and psychiatric disabilities using ICD-10 codes from validated algorithms20–22 that were ascertained from delivery discharge data (Appendix 1, available online at http://links.lww.com/AOG/D796); the psychiatric disabilities algorithms were based on the Americans with Disabilities Act enforcement guidance,23 which defines any mental or psychological disorder, including major depression, bipolar disorder, anxiety disorders (which include panic disorder, obsessive-compulsive disorder, and posttraumatic stress disorder), schizophrenia, and personality disorders. Deliveries to women without these disability diagnosis codes served as the comparison group of women without disabilities (n=4,203,044). The HCUP-NIS does not include unique patient identifiers, so the delivery hospitalization is the unit of analysis, not the woman.
Fig. 1. Flowchart for selecting the analytical sample. Obs, observations (refers to any hospitalizations or discharge records); IDD, intellectual and developmental disability.
Akobirshoev. Severe Maternal Morbidity by Disability Status and Type. O&G Open 2024.
The independent variables were the presence of any disability and disability type. Patients were classified as having any disability if diagnoses for vision, hearing, physical, intellectual and developmental, or psychiatric disabilities were present on the delivery hospitalization discharge record (Appendix 1, http://links.lww.com/AOG/D796). In addition to a binary variable indicating the presence of any disability, we also created a categorical independent variable for disability based on validated algorithms.20–22 Disability type categories were mutually exclusive and included no disability, vision disability only, hearing disability only, IDD only, physical disability only, psychiatric disability only, and multiple disabilities.
Our study used several variables to assess the presence, severity, and causes of SMM. First, we created a composite variable using 21 indicators specified in Centers for Disease Control and Prevention (CDC) criteria that reflect life-threatening complications (Appendix 2, available online at http://links.lww.com/AOG/D796).24,25 We analyzed two versions of this composite variable, with and without including blood transfusion. For each of these measures, SMM severity was assessed based on the number of CDC criteria met (2 or more, 3 or more, and 4 or more). Individual indicators included acute renal failure and sepsis. Due to low prevalence, other SMM indicators were combined into meaningful larger categories. Severe maternal morbidity for cardiovascular complications included indicators for acute heart failure, acute myocardial infarction, aneurysm aortic, cardiac arrest or ventricular fibrillation, conversion of cardiac rhythm, heart failure or arrest during surgery procedure, and pulmonary edema or acute heart failure. Severe maternal morbidity for respiratory complications included indicators for acute respiratory distress syndrome, temporary tracheostomy, and ventilation. Severe maternal morbidity for bleeding complications included indicators for disseminated intravascular coagulation, shock, and hysterectomy. Severe maternal morbidity for other obstetric complications included indicators for air and thrombotic embolism, amniotic fluid embolism, eclampsia, and severe anesthesia complications. Severe maternal morbidity for other medical complications included indicators for puerperal cerebrovascular disorders and sickle cell disease.
Covariates were identified based on prior research and included sociodemographic, hospital, clinical, and temporal factors associated with maternal morbidity.26–32 Sociodemographic characteristics included age at admission (younger than 20 years, 21–34, 35–39, 40 or older), primary payer (Medicare, Medicaid, private, uninsured), and median household income for patient's ZIP code (0–25th percentile, 26th–50th percentile, 51st–75th percentile, and 76th–100th percentile). Hospital factors included hospital capacity (small, medium, large), location and teaching status (rural, urban nonteaching, urban teaching), and geographic region (Northeast, Midwest, South, West). Clinical factors comprised pre-existing chronic conditions, including hypertension, diabetes, substance use disorder, and body mass index (BMI, calculated as weight in kilograms divided by height in meters squared) 40 or higher at delivery (Appendix 1, http://links.lww.com/AOG/D796). Due to substantial missingness (approximately 10%) and to avoid perpetuating harmful stereotyping, we did not impute or include race or ethnicity in our analyses, as they are social constructs reflecting racism and discrimination rather than inherent risk factors.33,34 All models were also adjusted for the hospital admission year.
We calculated weighted proportions for categorical covariates and weighted means and standard deviations for continuous covariates. We then examined differences in sociodemographic, hospital, and clinical characteristics by disability status and disability type using standardized differences.35
To evaluate the association between disability status and disability type with the risk of SMM outcomes, we used Poisson regressions for binary outcomes, and estimated unadjusted relative risks (RRs) and adjusted relative risks (aRRs) and 95% CIs. To avoid over-adjustment bias,36 the main models were adjusted for sociodemographic and hospital characteristics and year of delivery (model 1). The second set of multivariable models (model 2) added clinical characteristics to assess how their inclusion changed the results from model 1.
HCUP-NIS hospital discharge weights were applied to the sample data to create national estimates.37 Because several model covariates (health insurance, income, and hospital bed size) had missing values, we conducted multiple imputations using chained equations and added 10 imputations for each missing value for the variables with missing data.38 All analyses were performed in Stata 18.0 MP. STROBE guidelines39 were followed when writing this article.
RESULTS
Among 4,331,457 delivery hospitalizations, 128,413 were to women with disabilities. Table 1 shows the differences in sociodemographic, hospital, and clinical characteristics by disability status and type. Women with disabilities had a similar mean age at delivery compared with those without disabilities. Women with disabilities were more likely to have Medicare or Medicaid insurance and less likely to have private insurance. They were also more likely to deliver in urban teaching hospitals and in the South. A greater proportion of those with disabilities compared with those without disabilities had chronic conditions, including hypertension, pre-existing diabetes, and substance use disorders. Differences were also observed by disability type. Women with vision disability only, hearing disability only, or physical disability only were older compared with women without disabilities. However, women with psychiatric disabilities were younger. Women with all disability types had higher rates of public health insurance. Women with IDD only, psychiatric disabilities only, or multiple disabilities were more likely to live in ZIP codes with lower median household incomes. Women who had vision disability only or multiple disabilities were more likely to deliver in large hospitals. Women with all disability types had higher rates of deliveries in urban teaching hospitals compared with women without disabilities. Except for women who were DHH only, women with all other types of disabilities, including those with multiple disabilities, had a higher proportion of chronic hypertension. Women with vision disability or multiple disabilities also had higher ratios of pre-existing diabetes and BMI 40 or higher. Women with physical disabilities only, IDD only, psychiatric disabilities only, or multiple disabilities had higher rates of substance use disorder compared with their peers without disabilities.
Table 1.
Summary of Demographics and Hospital and Clinical Factors of the Study Population by Disability Status, Healthcare Cost and Utilization Project National Inpatient Sample, 2016–2021 (N=4,331,457)
| Characteristic | Disability Status | Disability Type | ||||||
| No (n=4,203,044) | Yes (n=128,413) | Vision Only (n=3,498) | DHH Only (n=3,833) | Physical Only (n=46,903) | IDD Only (n=3,206) | Psychiatric Only (n=65,592)* | Multiple (n=5,381) | |
| Sociodemographics | ||||||||
| Maternal age at delivery (y) | ||||||||
| Younger than 20 | 4.8 | 5.1 | 2.3 | 4.4 | 3.7 | 8.7 | 6.2 | 4.7 |
| 20–24 | 19.1 | 20.3 | 13.4 | 18.3 | 16.7 | 23.5 | 23 | 22.4 |
| 35–39 | 72.8 | 70.6 | 78.6 | 71.9 | 74.8 | 61.9 | 67.7 | 68.6 |
| 40 or older | 3.3 | 4.0 | 5.8 | 5.5 | 4.8 | 5.9 | 3.2 | 4.2 |
| Standardized difference† | Ref | 0.052 | 0.238 | 0.104 | 0.109 | 0.253 | 0.119 | 0.100 |
| Age (y) | 29.0±5.8 | 29.0±6.0 | 30.6±5.7 | 29.7±6.2 | 29.9±5.9 | 28.5±6.7 | 28.4±2.9 | 28.8±6.1 |
| Standardized difference† | Ref | 0.000 | 0.264 | 0.122 | 0.142 | 0.090 | 0.114 | 0.041 |
| Insurance payer type | ||||||||
| Medicare | 0.6 | 4.4 | 5.0 | 8.6 | 3.7 | 7.6 | 3.9 | 9.9 |
| Medicaid | 41.9 | 49.4 | 38.7 | 43.3 | 41.1 | 50.8 | 55.5 | 59.4 |
| Private insurance | 52.1 | 41.9 | 53.2 | 45 | 51 | 37.7 | 36.2 | 26.5 |
| Uninsured | 5.3 | 4.1 | 2.8 | 3.1 | 4.2 | 3.8 | 4.3 | 4.1 |
| Standardized difference† | Ref | 0.314 | 0.304 | 0.412 | 0.225 | 0.446 | 0.392 | 0.665 |
| Median household income for patient's ZIP code | ||||||||
| 0–25th percentile | 27.6 | 29.4 | 26.9 | 26.4 | 27.6 | 33.6 | 30.5 | 34.1 |
| 26th–50th percentile | 25 | 26.1 | 23.7 | 25.3 | 25.2 | 25.5 | 26.9 | 26.7 |
| 51st–75th percentile | 24.5 | 24.2 | 25.2 | 26.3 | 24.4 | 22.1 | 24 | 23.7 |
| 76th–100th percentile | 22.1 | 19.3 | 23.6 | 21.1 | 22 | 18 | 17.5 | 14.4 |
| Standardized difference† | Ref | 0.074 | 0.044 | 0.046 | 0.006 | 0.152 | 0.123 | 0.220 |
| Hospital characteristics | ||||||||
| Bed size | ||||||||
| Small | 19.6 | 17.9 | 14.7 | 18.7 | 17.3 | 17.4 | 18.6 | 15.7 |
| Medium | 30.0 | 27.0 | 26.0 | 25.5 | 27.3 | 28.6 | 27.1 | 24.9 |
| Large | 50.4 | 55.1 | 59.3 | 55.8 | 55.4 | 54.0 | 54.3 | 59.4 |
| Standardized difference† | Ref | 0.094 | 0.185 | 0.114 | 0.101 | 0.075 | 0.079 | 0.183 |
| Location and teaching status | ||||||||
| Rural | 9.1 | 8.3 | 4.9 | 6.0 | 8.2 | 8.8 | 8.8 | 7.6 |
| Urban nonteaching | 19.7 | 15.1 | 13.2 | 15.0 | 15.5 | 15.9 | 15.0 | 13.3 |
| Urban teaching | 71.2 | 76.6 | 81.9 | 79.0 | 76.3 | 75.4 | 76.2 | 79.1 |
| Standardized difference† | Ref | 0.129 | 0.258 | 0.184 | 0.120 | 0.104 | 0.127 | 0.189 |
| Region | ||||||||
| Northeast | 15.9 | 17.7 | 17.4 | 16.4 | 17.0 | 17.5 | 18.3 | 18.0 |
| Midwest | 20.9 | 24.0 | 21.8 | 23.4 | 22.4 | 22.1 | 25.3 | 24.9 |
| South | 39.6 | 34.6 | 36.7 | 31.8 | 37.5 | 39.9 | 32.4 | 33.9 |
| West | 23.6 | 23.7 | 24.2 | 28.4 | 23.1 | 20.5 | 24.0 | 23.2 |
| Standardized difference† | Ref | 0.113 | 0.062 | 0.171 | 0.054 | 0.080 | 0.162 | 0.134 |
| Clinical characteristics | ||||||||
| Chronic hypertension | ||||||||
| No | 98.5 | 96.1 | 66.1 | 97.8 | 97.2 | 97.2 | 97.1 | 92.9 |
| Yes | 1.5 | 3.9 | 33.9 | 2.2 | 2.8 | 2.8 | 2.9 | 7.1 |
| Standardized difference† | Ref | 0.172 | 0.498 | 0.064 | 0.158 | 0.126 | 0.156 | 0.291 |
| Pre-existing diabetes mellitus | ||||||||
| No | 98.7 | 95.1 | 63.1 | 97.5 | 96.0 | 97.2 | 96.5 | 89.0 |
| Yes | 1.3 | 4.9 | 36.9 | 2.5 | 4.0 | 2.8 | 3.5 | 11.0 |
| Standardized difference† | Ref | 0.150 | 0.940 | 0.056 | 0.092 | 0.092 | 0.100 | 0.283 |
| Substance use disorder | ||||||||
| No | 94.2 | 78.7 | 93.1 | 92.3 | 88.1 | 89.7 | 70.8 | 68.1 |
| Yes | 5.8 | 21.3 | 6.9 | 7.7 | 11.9 | 10.3 | 29.2 | 31.9 |
| Standardized difference† | Ref | 0.466 | 0.048 | 0.078 | 0.217 | 0.168 | 0.649 | 0.709 |
| BMI at delivery 40 or higher | ||||||||
| No | 97.9 | 96.5 | 95.4 | 97.1 | 96.8 | 97.4 | 96.3 | 95.7 |
| Yes | 2.1 | 3.5 | 4.6 | 2.9 | 3.2 | 2.6 | 3.7 | 4.3 |
| Standardized difference† | Ref | 0.084 | 0.138 | 0.051 | 0.068 | 0.031 | 0.094 | 0.120 |
| Calendar year | ||||||||
| 2016 | 17.6 | 13.8 | 14.0 | 15.1 | 15.5 | 13.8 | 12.5 | 12.7 |
| 2017 | 17.2 | 14.6 | 14.9 | 14.8 | 15.9 | 13.3 | 13.8 | 13.4 |
| 2018 | 16.8 | 15.9 | 15.7 | 15.0 | 16.7 | 16.6 | 15.4 | 16.0 |
| 2019 | 16.5 | 17.2 | 17.2 | 17.1 | 16.7 | 16.4 | 17.6 | 17.0 |
| 2020 | 15.9 | 18.3 | 17.5 | 18.7 | 16.8 | 19.1 | 19.2 | 19.2 |
| 2021 | 16.0 | 20.3 | 20.7 | 19.4 | 18.4 | 20.7 | 21.6 | 21.8 |
| Standardized difference† | Ref | 0.167 | 0.162 | 0.145 | 0.087 | 0.192 | 0.223 | 0.224 |
DHH, deaf or hard of hearing; IDD, intellectual and developmental disabilities; Ref, reference; BMI, body mass index.
Data are % or mean±SD unless otherwise specified.
Psychiatric disabilities were based on the Americans with Disabilities Act rule,23 according to which any mental or psychological disorder, such as “major depression, bipolar disorder, anxiety disorders (which include panic disorder, obsessive compulsive disorder, and posttraumatic stress disorder), schizophrenia, and personality disorders” is considered a psychiatric disability.
A standardized difference of more than 10% reflects a meaningful imbalance between the study and referent groups.
Women with disabilities had a significantly higher rate of one or more SMM indicators during delivery compared with those without disabilities (Table 2). In unadjusted analyses, women with disabilities had a more than two times higher risk of experiencing one or more SMM indicators compared with those without disabilities. After adjusting for sociodemographic, hospital, and clinical factors (model 2), the association remained significant and nearly twice as high.
Table 2.
Rates and Unadjusted and Adjusted Risk Ratios for Having a Higher Number of Severe Maternal Morbidity Indicators During Delivery Among Birthing Individuals by Disability Status, Healthcare Cost and Utilization Project National Inpatient Sample, 2016–2021 (N=4,331,457)
| Outcome | Disability Status* | |
| No (n=4,203,044) | Yes (n=128,413) | |
| 1 or more SMM indicators | ||
| Rate/10,000 deliveries (95% CI) | 177 (174–180) | 396 (384–408) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 2.24 (2.17–2.30) |
| Model 1† | 1.00 (1.00–1.00) | 2.04 (1.98–2.10) |
| Model 2‡ | 1.00 (1.00–1.00) | 1.86 (1.80–1.91) |
| 2 or more SMM indicators | ||
| Rate/10,000 deliveries (95% CI) | 25 (25–26) | 93 (88–98) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 3.70 (3.48–3.93) |
| Model 1† | 1.00 (1.00–1.00) | 3.17 (2.98–3.38) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.64 (2.47–2.81) |
| 3 or more SMM indicators | ||
| Rate/10,000 deliveries (95% CI) | 9 (9–10) | 43 (40–47) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 4.65 (4.25–5.08) |
| Model 1† | 1.00 (1.00–1.00) | 3.98 (3.62–4.37) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.30 (2.98–3.64) |
| 4 or more SMM indicators | ||
| Rate/10,000 deliveries (95% CI) | 4 (4–5) | 24 (21–27) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 5.53 (4.91–6.23) |
| Model 1† | 1.00 (1.00–1.00) | 4.79 (4.23–5.43) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.98 (3.48–4.55) |
| 1 or more SMM indicators without transfusion | ||
| Rate/10,000 deliveries (95% CI) | 61 (60–62) | 204 (196–212) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 3.33 (3.19–3.47) |
| Model 1† | 1.00 (1.00–1.00) | 2.91 (2.79–3.04) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.52 (2.41–2.63) |
| 2 or more SMM indicators without transfusion | ||
| Rate/10,000 deliveries (95% CI) | 1 (10–10) | 52 (48–56) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 5.28 (4.87–5.73) |
| Model 1† | 1.00 (1.00–1.00) | 4.39 (4.03–4.78) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.51 (3.21–3.85) |
| 3 or more SMM indicators without transfusion | ||
| Rate/10,000 deliveries (95% CI) | 4 (4–4) | 25 (22–28) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 6.03 (5.36–6.78) |
| Model 1† | 1.00 (1.00–1.00) | 4.96 (4.38–5.63) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.98 (3.47–4.55) |
| 4 or more SMM indicators without transfusion | ||
| Rate/10,000 deliveries (95% CI) | 2 (2–2) | 13 (11–15) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 7.25 (6.16–8.53) |
| Model 1† | 1.00 (1.00–1.00) | 5.90 (4.96–7.03) |
| Model 2‡ | 1.00 (1.00–1.00) | 4.64 (3.84–5.60) |
| SMM | ||
| Acute renal failure | ||
| Rate/10,000 deliveries (95% CI) | 14 (14–15) | 52 (48–56) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 3.70 (3.41–4.02) |
| Model 1† | 1.00 (1.00–1.00) | 2.98 (2.73–3.25) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.25 (2.06–2.46) |
| Sepsis | ||
| Rate/10,000 deliveries (95% CI) | 11 (10–11) | 3 (27–33) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 2.81 (2.52–3.13) |
| Model 1† | 1.00 (1.00–1.00) | 2.43 (2.18–2.71) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.08 (1.86–2.33) |
| Cardiovascular complications§ | ||
| Rate/10,000 deliveries (95% CI) | 8 (8–8) | 38 (34–41) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 4.65 (4.22–5.12) |
| Model 1† | 1.00 (1.00–1.00) | 3.78 (3.41–4.19) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.72 (2.44–3.03) |
| Respiratory complications‖ | ||
| Rate/10,000 deliveries (95% CI) | 12 (12–13) | 61 (57–66) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 5.03 (4.67–5.42) |
| Model 1† | 1.00 (1.00–1.00) | 4.22 (3.90–4.56) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.43 (3.15–3.72) |
| Bleeding complications¶ | ||
| Rate/10,000 deliveries (95% CI) | 34 (33–35) | 68 (63–72) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 1.97 (1.84–2.12) |
| Model 1† | 1.00 (1.00–1.00) | 1.81 (1.69–1.94) |
| Model 2‡ | 1.00 (1.00–1.00) | 1.68 (1.56–1.80) |
| Other obstetric complications# | ||
| Rate/10,000 deliveries (95% CI) | 11 (11–11) | 57 (52–61) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 5.17 (4.76–5.60) |
| Model 1† | 1.00 (1.00–1.00) | 4.96 (4.56–5.39) |
| Model 2‡ | 1.00 (1.00–1.00) | 4.55 (4.16–4.96) |
| Other medical complications** | ||
| Rate/10,000 deliveries (95% CI) | 4 (4–4) | 35 (31–38) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 9.27 (8.32–10.32) |
| Model 1† | 1.00 (1.00–1.00) | 7.04 (6.22–7.97) |
| Model 2‡ | 1.00 (1.00–1.00) | 6.39 (5.60–7.29) |
DHH, deaf or hard of hearing; IDD, intellectual and developmental disabilities; RR, risk ratios; SMM, severe maternal morbidity.
Data are RR (95% CI) unless otherwise specified.
Disability status was based on validated algorithms20–22 (see Appendix 1, available online at http://links.lww.com/AOG/D796) for vision, hearing, physical, and intellectual and developmental disabilities. Psychiatric disabilities were also included as part of the any disability group. They were based on the Americans with Disabilities Act rule23 and included major depression, bipolar disorder, anxiety disorders (which include panic disorder, obsessive compulsive disorder, and posttraumatic stress disorder), schizophrenia, and personality disorders.
Model 1 was adjusted for age, insurance, median income for patient's ZIP code, hospital bed size, hospital region, and admission year.
Model 2 was adjusted for the covariates in model 1, plus chronic hypertension, pre-existing diabetes, substance use disorder, and body mass index 40 or higher at delivery.
Includes indicators for acute heart failure, acute myocardial infarction, aneurysm aortic, cardiac arrest/ventricular fibrillation, conversion of cardiac rhythm, heart failure/arrest during surgery procedure, and pulmonary edema/acute heart failure.
Includes indicators for acute respiratory distress syndrome, temporary tracheostomy, and ventilation.
Includes indicators for disseminated intravascular coagulation, shock, and hysterectomy, all with no blood transfusion.
Includes indicators for air and thrombotic embolism, amniotic fluid embolism, eclampsia, and severe anesthesia complications.
Includes indicators for puerperal cerebrovascular disorders and sickle cell disease with crisis.
Women with disabilities were at even greater risk of having multiple indicators of SMM compared with their peers without disabilities. In fully adjusted models (model 2), the aRRs were approximately 2.6 for two or more SMM indicators, approximately 3.3 for three or more SMM indicators, and approximately 4.0 for four or more SMM indicators, which demonstrates higher severity as measured by multimorbidity.
Similarly, high rates and risk patterns were observed for SMM indicators, excluding blood transfusions. In fully adjusted models (model 2), the aRRs ranged from approximately 2.5 for one or more SMM indicators without blood transfusion and approximately 3.5 for two or more SMM indicators without blood transfusion to approximately 4.6 for four or more SMM indicators without blood transfusion.
Women with disabilities had significantly higher rates and risks for all specific SMM indicators during delivery compared with those without disabilities. In our fully adjusted models (model 2), the aRRs were highest for other medical complications (puerperal cerebrovascular disorders and sickle cell disease with crisis), followed by other obstetric complications, respiratory complications, cardiovascular complications, acute renal failure, sepsis, and bleeding complications compared with women without disabilities.
Compared with women without disabilities, women with all disability types were at significantly higher risk for SMM outcomes during delivery. The magnitude of the association varied by disability type (Table 3).
Table 3.
Rates and Unadjusted and Adjusted Risk Ratios for Having a Higher Number of Severe Maternal Morbidity Indicators During Delivery Among Birthing Individuals by Disability Type, Healthcare Cost and Utilization Project National Inpatient Sample, 2016–2021 (n=4,331,457)
| Outcome | Disability Type* | ||||||
| No Disability (n=4,203,044) | Vision Only (n=3,498) | DHH Only (n=3,833) | Physical Only (n=46,903) | IDD Only (n=3,206) | Psychiatric Only (n=65,592) | Multiple (n=5,381) | |
| 1 or more SMM indicators | |||||||
| Rate/10,000 deliveries (95% CI) | 177 (174–180) | 849 (757–951) | 295 (246–353) | 488 (468–509) | 312 (258–377) | 302 (289–316) | 561 (502–627) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 4.80 (4.28–5.38) | 1.67 (1.39–2.00) | 2.76 (2.64–2.87) | 1.76 (1.46–2.13) | 1.71 (1.63–1.78) | 3.17 (2.84–3.55) |
| Model 1† | 1.00 (1.00–1.00) | 4.36 (3.89–4.88) | 1.49 (1.24–1.79) | 2.60 (2.49–2.71) | 1.52 (1.25–1.84) | 1.54 (1.47–1.61) | 2.62 (2.35–2.94) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.02 (2.70–3.38) | 1.48 (1.23–1.77) | 2.44 (2.34–2.55) | 1.46 (1.20–1.76) | 1.39 (1.33–1.45) | 2.21 (1.97–2.47) |
| 2 or more SMM indicators | |||||||
| Rate/10,000 deliveries (95% CI) | 25 (25–26) | 229 (184–284) | 39 (24–65) | 143 (133–155) | 53 (33–85) | 5 (45–56) | 151 (121–187) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 9.10 (7.31–11.34) | 1.56 (0.94–2.58) | 5.71 (5.28–6.18) | 2.11 (1.32–3.38) | 1.98 (1.77–2.22) | 5.99 (4.80–7.49) |
| Model 1† | 1.00 (1.00–1.00) | 7.27 (5.84–9.05) | 1.25 (0.76–2.08) | 5.02 (4.63–5.44) | 1.72 (1.07–2.76) | 1.71 (1.53–1.91) | 4.40 (3.51–5.52) |
| Model 2‡ | 1.00 (1.00–1.00) | 4.23 (3.39–5.28) | 1.24 (0.75–2.05) | 4.48 (4.13–4.85) | 1.60 (1.00–2.58) | 1.36 (1.22–1.53) | 3.14 (2.50–3.95) |
| 3 or more SMM indicators | |||||||
| Rate/10,000 deliveries (95% CI) | 9 (9–10) | 66 (44–99) | 18 (9–38) | 75 (67–83) | 12 (5–33) | 21 (18–25) | 65 (47–90) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 7.04 (4.61–10.76) | 1.96 (0.93–4.10) | 8.02 (7.18–8.95) | 1.34 (0.50–3.55) | 2.24 (1.89–2.65) | 6.97 (5.00–9.71) |
| Model 1† | 1.00 (1.00–1.00) | 5.56 (3.63–8.50) | 1.56 (0.74–3.28) | 7.00 (6.25–7.84) | 1.09 (0.41–2.88) | 1.92 (1.62–2.28) | 5.07 (3.61–7.11) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.32 (2.16–5.12) | 1.55 (0.74–3.25) | 6.22 (5.55–6.98) | 1.02 (0.38–2.70) | 1.52 (1.28–1.80) | 3.58 (2.54–5.04) |
| 4 or more SMM indicators | |||||||
| Rate/10,000 deliveries (95% CI) | 4 (4–5) | 29 (15–53) | 8 (3–24) | 43 (38–50) | 9 (3–29) | 11 (8–13) | 33 (21–53) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 6.62 (3.35–13.07) | 1.81 (0.59–5.60) | 10.02 (8.68–11.56) | 2.17 (0.70–6.70) | 2.47 (1.95–3.13) | 7.74 (4.87–12.31) |
| Model 1† | 1.00 (1.00–1.00) | 5.25 (2.65–10.39) | 1.48 (0.48–4.58) | 8.81 (7.61–10.20) | 1.79 (0.58–5.54) | 2.15 (1.69–2.73) | 5.75 (3.58–9.22) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.37 (1.68–6.75) | 1.45 (0.47–4.51) | 7.80 (6.72–9.06) | 1.68 (0.54–5.21) | 1.68 (1.32–2.14) | 4.07 (2.52–6.58) |
| 1 or more SMM indicators without transfusion | |||||||
| Rate/10,000 deliveries (95% CI) | 61 (60–62) | 483 (416–561) | 133 (101–174) | 278 (264–294) | 140 (105–187) | 132 (124–142) | 335 (290–386) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 7.89 (6.79–9.17) | 2.17 (1.66–2.85) | 4.55 (4.30–4.81) | 2.29 (1.72–3.06) | 2.16 (2.02–2.31) | 5.46 (4.73–6.31) |
| Model 1† | 1.00 (1.00–1.00) | 6.56 (5.65–7.61) | 1.79 (1.36–2.35) | 4.08 (3.86–4.32) | 1.93 (1.45–2.58) | 1.89 (1.76–2.02) | 4.20 (3.63–4.87) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.71 (3.19–4.31) | 1.77 (1.35–2.32) | 3.71 (3.51–3.93) | 1.82 (1.36–2.43) | 1.61 (1.50–1.73) | 3.20 (2.76–3.70) |
| 2 or more SMM indicators without transfusion | |||||||
| Rate/10,000 deliveries (95% CI) | 1 (10–10) | 77 (53–112) | 21 (10–42) | 90 (82–100) | 31 (17–58) | 23 (20–27) | 89 (67–118) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 7.82 (5.37–11.39) | 2.12 (1.06–4.23) | 9.16 (8.29–10.13) | 3.16 (1.71–5.86) | 2.35 (1.99–2.77) | 9.04 (6.81–12.00) |
| Model 1† | 1.00 (1.00–1.00) | 6.14 (4.21–8.95) | 1.66 (0.83–3.32) | 7.96 (7.18–8.83) | 2.50 (1.34–4.65) | 1.93 (1.64–2.28) | 6.31 (4.73–8.41) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.17 (2.15–4.68) | 1.63 (0.81–3.27) | 6.92 (6.23–7.68) | 2.31 (1.24–4.30) | 1.47 (1.24–1.73) | 4.20 (3.13–5.62) |
| 3 or more SMM indicators without transfusion | |||||||
| Rate/10,000 deliveries (95% CI) | 4 (4–4) | 23 (11–46) | 8 (3–24) | 46 (40–52) | 6 (2–25) | 11 (9–14) | 43 (28–64) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 5.50 (2.75–11.01) | 1.88 (0.61–5.84) | 10.97 (9.51–12.65) | 1.50 (0.38–5.99) | 2.64 (2.09–3.34) | 10.28 (6.83–15.47) |
| Model 1† | 1.00 (1.00–1.00) | 4.23 (2.11–8.48) | 1.45 (0.47–4.50) | 9.40 (8.11–10.91) | 1.17 (0.29–4.67) | 2.15 (1.70–2.73) | 6.98 (4.59–10.61) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.18 (1.07–4.44) | 1.43 (0.46–4.43) | 8.16 (7.02–9.50) | 1.08 (0.27–4.33) | 1.63 (1.28–2.08) | 4.62 (3.02–7.08) |
| 4 or more SMM indicators without transfusion | |||||||
| Rate/10,000 deliveries (95% CI) | 2 (2–2) | 17 (8–38) | 3 (0–19) | 24 (20–29) | 3 (0–22) | 5 (4–8) | 22 (13–39) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 9.45 (4.23–21.09) | 1.44 (0.20–10.20) | 13.27 (10.93–16.12) | 1.72 (0.24–12.18) | 3.02 (2.15–4.24) | 12.28 (6.95–21.71) |
| Model 1† | 1.00 (1.00–1.00) | 7.07 (3.15–15.85) | 1.08 (0.15–7.68) | 11.19 (9.14–13.70) | 1.32 (0.19–9.28) | 2.46 (1.75–3.46) | 8.11 (4.52–14.55) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.79 (1.67–8.64) | 1.06 (0.15–7.58) | 9.57 (7.77–11.78) | 1.22 (0.17–8.58) | 1.80 (1.28–2.55) | 5.20 (2.85–9.47) |
| SMM: Acute renal failure | |||||||
| Rate/10,000 deliveries (95% CI) | 14 (14–15) | 309 (254–375) | 42 (26–68) | 53 (47–60) | 62 (40–96) | 36 (31–40) | 78 (58–105) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 22.01 (18.02–26.89) | 2.98 (1.83–4.85) | 3.77 (3.31–4.29) | 4.45 (2.87–6.88) | 2.53 (2.22–2.88) | 5.56 (4.12–7.51) |
| Model 1† | 1.00 (1.00–1.00) | 16.29 (13.34–19.89) | 2.20 (1.35–3.59) | 3.16 (2.77–3.60) | 3.42 (2.20–5.31) | 2.04 (1.79–2.34) | 3.73 (2.75–5.05) |
| Model 2‡ | 1.00 (1.00–1.00) | 5.78 (4.71–7.10) | 2.17 (1.33–3.55) | 2.64 (2.32–3.02) | 3.01 (1.93–4.69) | 1.54 (1.34–1.77) | 2.24 (1.66–3.03) |
| SMM | |||||||
| Sepsis | |||||||
| Rate/10,000 deliveries (95% CI) | 11 (10–11) | 34 (20–60) | 16 (7–35) | 4 (35–47) | 22 (10–46) | 23 (19–27) | 35 (23–55) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 3.25 (1.84–5.72) | 1.48 (0.67–3.28) | 3.81 (3.29–4.42) | 2.07 (0.98–4.34) | 2.13 (1.81–2.52) | 3.34 (2.13–5.25) |
| Model 1† | 1.00 (1.00–1.00) | 2.77 (1.57–4.89) | 1.20 (0.54–2.65) | 3.49 (3.00–4.05) | 1.70 (0.81–3.58) | 1.81 (1.53–2.14) | 2.52 (1.60–3.97) |
| Model 2‡ | 1.00 (1.00–1.00) | 1.79 (1.01–3.18) | 1.18 (0.53–2.61) | 3.20 (2.76–3.72) | 1.62 (0.77–3.40) | 1.49 (1.26–1.77) | 1.92 (1.21–3.04) |
| Cardiovascular complications§ | |||||||
| Rate/10,000 deliveries (95% CI) | 8 (8–8) | 106 (75–149) | 34 (20–58) | 45 (40–52) | 34 (19–62) | 25 (22–30) | 8 (59–108) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 13.07 (9.25–18.46) | 4.19 (2.44–7.21) | 5.58 (4.86–6.41) | 4.24 (2.35–7.63) | 3.15 (2.69–3.67) | 9.87 (7.29–13.37) |
| Model 1† | 1.00 (1.00–1.00) | 9.68 (6.82–13.75) | 3.06 (1.76–5.30) | 4.67 (4.06–5.38) | 3.24 (1.80–5.81) | 2.60 (2.22–3.05) | 6.51 (4.78–8.87) |
| Model 2‡ | 1.00 (1.00–1.00) | 3.76 (2.65–5.34) | 3.04 (1.76–5.26) | 3.74 (3.24–4.33) | 2.86 (1.59–5.15) | 1.81 (1.54–2.14) | 3.63 (2.64–4.98) |
| Respiratory complications‖ | |||||||
| Rate/10,000 deliveries (95% CI) | 12 (12–13) | 74 (51–109) | 26 (14–48) | 103 (94–112) | 22 (10–46) | 31 (27–35) | 108 (84–139) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 6.11 (4.11–9.09) | 2.15 (1.16–3.98) | 8.45 (7.70–9.28) | 1.80 (0.86–3.76) | 2.53 (2.20–2.91) | 8.87 (6.84–11.49) |
| Model 1† | 1.00 (1.00–1.00) | 4.83 (3.25–7.19) | 1.70 (0.91–3.16) | 7.40 (6.73–8.14) | 1.43 (0.68–2.99) | 2.10 (1.83–2.42) | 6.25 (4.80–8.13) |
| Model 2‡ | 1.00 (1.00–1.00) | 2.56 (1.71–3.82) | 1.67 (0.90–3.11) | 6.47 (5.88–7.13) | 1.32 (0.63–2.76) | 1.64 (1.42–1.89) | 4.28 (3.27–5.59) |
| Bleeding complications¶ | |||||||
| Rate/10,000 deliveries (95% CI) | 34 (33–35) | 91 (64–130) | 5 (32–77) | 85 (77–94) | 5 (31–81) | 55 (49–61) | 84 (62–112) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 2.67 (1.88–3.80) | 1.45 (0.93–2.26) | 2.48 (2.25–2.74) | 1.46 (0.90–2.37) | 1.59 (1.43–1.77) | 2.44 (1.83–3.25) |
| Model 1† | 1.00 (1.00–1.00) | 2.26 (1.59–3.21) | 1.27 (0.81–1.99) | 2.26 (2.05–2.50) | 1.34 (0.82–2.17) | 1.49 (1.34–1.65) | 2.07 (1.55–2.77) |
| Model 2‡ | 1.00 (1.00–1.00) | 1.86 (1.30–2.66) | 1.26 (0.81–1.97) | 2.16 (1.96–2.39) | 1.30 (0.80–2.12) | 1.35 (1.21–1.50) | 1.80 (1.35–2.41) |
| Other obstetric complications# | |||||||
| Rate/10,000 deliveries (95% CI) | 11 (11–11) | 8 (55–116) | 16 (7–35) | 104 (95–113) | 19 (8–42) | 24 (20–28) | 84 (63–112) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 7.31 (5.06–10.57) | 1.43 (0.64–3.18) | 9.47 (8.61–10.41) | 1.71 (0.77–3.80) | 2.16 (1.83–2.54) | 7.64 (5.67–10.29) |
| Model 1† | 1.00 (1.00–1.00) | 7.32 (5.06–10.59) | 1.39 (0.62–3.10) | 9.40 (8.53–10.35) | 1.52 (0.69–3.39) | 2.02 (1.72–2.38) | 6.87 (5.09–9.27) |
| Model 2‡ | 1.00 (1.00–1.00) | 5.07 (3.45–7.43) | 1.37 (0.61–3.04) | 8.78 (7.96–9.68) | 1.46 (0.66–3.25) | 1.82 (1.54–2.15) | 5.79 (4.27–7.85) |
| Other medical complications** | |||||||
| Rate/10,000 deliveries (95% CI) | 4 (4–4) | 106 (77–145) | 1 (4–28) | 67 (60–75) | NA | 9 (7–11) | 61 (44–86) |
| Unadjusted RR (95% CI) | 1.00 (1.00–1.00) | 28.28 (20.58–38.87) | 2.79 (1.05–7.44) | 17.90 (15.86–20.20) | NA | 2.32 (1.77–3.06) | 16.40 (11.7–23.1) |
| Model 1† | 1.00 (1.00–1.00) | 20.07 (14.53–27.72) | 1.81 (0.68–4.85) | 14.33 (12.54–16.38) | NA | 1.76 (1.33–2.33) | 9.35 (6.53–13.39) |
| Model 2‡ | 1.00 (1.00–1.00) | 15.42 (10.72–22.19) | 1.83 (0.68–4.90) | 13.29 (11.61–15.22) | NA | 1.52 (1.14–2.03) | 7.58 (5.26–10.92) |
DHH, deaf or hard of hearing; IDD, intellectual and developmental disabilities; RR, risk ratios; SMM, severe maternal morbidity; NA, not available.
Data are RR (95% CI) unless otherwise specified.
*Disability status was based on validated algorithms20–22 (see Appendix 1, available online at http://links.lww.com/AOG/D796) for vision, hearing, physical, and intellectual/developmental disabilities. Psychiatric disabilities were also included as part of the any disability group. They were based on the Americans with Disabilities Act rule23 and included major depression, bipolar disorder, anxiety disorders (which include panic disorder, obsessive compulsive disorder, and posttraumatic stress disorder), schizophrenia, and personality disorders.
Model 1 was adjusted for age, insurance, median income for patient's ZIP code, hospital bed size, hospital region, and admission year.
Model 2 was adjusted for the covariates in model 1, plus chronic hypertension, pre-existing diabetes, substance use disorder, and body mass index 40 or higher at delivery.
Includes indicators for acute heart failure, acute myocardial infarction, aneurysm aortic, cardiac arrest/ventricular fibrillation, conversion of cardiac rhythm, heart failure/arrest during surgery procedure, and pulmonary edema/acute heart failure.
Includes indicators for acute respiratory distress syndrome, temporary tracheostomy, and ventilation.
Includes indicators for disseminated intravascular coagulation, shock, and hysterectomy, all with no blood transfusion.
Includes indicators for air and thrombotic embolism, amniotic fluid embolism, eclampsia, and severe anesthesia complications.
Includes indicators for puerperal cerebrovascular disorders and sickle cell disease with crisis.
Women with vision disability had the highest risk of one or more SMM indicators during delivery, with an unadjusted RR of nearly 5, which attenuated to about 3 after full adjustment (model 2). They also had elevated risks for multiple SMM indicators, ranging from an aRR of approximately 4.2 for two or more SMM indicators to approximately 3.3 for three or more SMM indicators and similarly higher risks for SMM indicators without blood transfusion. Women who had vision disabilities had the highest fully adjusted RR, at more than 15 times higher for other medical complications (eg, puerperal cerebrovascular disorders and sickle cell disease with crisis), and the lowest risk for sepsis at approximately 1.8 times higher.
Women who were DHH had a lower risk of one or more SMM indicators than women with other disability types, with an unadjusted RR of approximately 1.7 times higher that attenuated to approximately 1.5 after full adjustment. They had significantly higher risks for acute renal failure and cardiovascular complications than their peers without disabilities.
Women with physical disabilities only had an unadjusted RR of approximately 2.8 times higher for one or more SMM indicators, which attenuated to approximately 2.4 after full adjustment. They had notably high risks for multiple SMM indicators, with fully adjusted RRs of 4.5 times higher for two or more indicators, approximately 6.2 for three or more indicators, and approximately 7.8 for four or more indicators. Severe maternal morbidity indicators without blood transfusion also showed similar elevated risks. For specific SMM indicators, women with physical disabilities had fully adjusted RRs ranging from approximately 2.12 times higher for bleeding complications (eg, disseminated intravascular coagulation, shock, and hysterectomy) to 13.3 for other medical complications (eg, puerperal cerebrovascular disorders and sickle cell disease with crisis).
Women with IDD had an unadjusted RR of approximately 1.8 times higher for one or more SMM indicators, which attenuated to approximately 1.5 after full adjustment. They had significantly elevated risks for acute renal failure and cardiovascular complications (eg, acute heart failure, acute myocardial infarction, aneurysm aortic, cardiac arrest or ventricular fibrillation) in fully adjusted models.
Women with psychiatric disabilities had an unadjusted RR of approximately 1.7 times higher for one or more SMM indicators, which attenuated to approximately 1.4 after full adjustment. Their fully adjusted RRs for multiple SMM indicators ranged from 1.4 times higher for two or more, approximately 1.5 for three or more, to 1.7 for four or more. Severe maternal morbidity indicators without blood transfusion showed similar elevated risks. For specific SMM indicators, women with psychiatric disabilities had fully adjusted RRs ranging from approximately 1.4 times higher for bleeding complications (eg, disseminated intravascular coagulation, shock, and hysterectomy) to approximately 1.8 for other obstetric complications (air and thrombotic embolism, amniotic fluid embolism, eclampsia, and severe anesthesia complications).
Women with multiple disabilities had an unadjusted RR of approximately 3.2 times higher for one or more SMM indicators, which attenuated to approximately 2.2 after full adjustment. They had elevated risks for multiple SMM indicators, with fully adjusted RRs ranging from approximately 3.1 times higher for two or more and approximately 3.6 for three or more to approximately 4.1 for four or more. Higher risks for SMM indicators without blood transfusion also were observed. For specific SMM indicators, women with multiple disabilities had fully adjusted RRs ranging from approximately 1.8 times higher for bleeding complications (eg, disseminated intravascular coagulation, shock, and hysterectomy) to approximately 7.6 (95% CI, 5.26–10.92) for other medical complications (eg, puerperal cerebrovascular disorders and sickle cell disease with crisis).
DISCUSSION
We found that women with disabilities had significantly higher risks for SMM outcomes during delivery compared with women without disabilities. The magnitude of the association varied by disability type, with the highest risks observed for women who had vision or physical disabilities. These findings are consistent with previous studies that have reported elevated SMM risks among women with physical, sensory, or intellectual and developmental disabilities compared with women without disabilities.12,13,16,17
The elevated risk of SMM among women with disabilities may be attributed to several factors. First, women with disabilities are more likely to have pre-existing chronic conditions.40 In our study, we found that women with disabilities had higher rates of hypertension, diabetes, and high BMI at delivery compared with their peers without disabilities. Second, women with disabilities may face barriers in accessing and receiving timely and adequate prenatal care, which is critical for identifying and managing potential complications.41–43
Moreover, health care professionals may lack the knowledge, skills, and resources to offer quality care for women with disabilities during pregnancy and childbirth.42,44 These findings highlight the need for formal education and training on disability-competent care, which involves providing accommodations, modifying standard procedures for managing pregnancy and childbirth, and ensuring effective communication to meet the unique needs of women with different disabilities.45
In fall 2023, people with disabilities were designated by the National Institutes of Health as a population with health disparities.46 People with disabilities are significantly more likely to experience a wide range of unfavorable social determinants of health, including inequalities in education, employment, income, social support, and other structural and attitudinal factors, which can contribute to adverse health outcomes, including SMM.47 Addressing these social determinants of health is critical for reducing health disparities and improving maternal outcomes among women with disabilities.
The United States is currently facing a maternal health crisis, with increasing rates of maternal mortality and SMM, particularly among minoritized and marginalized populations.1,48,49 Our study adds to the growing evidence that women with all disability types are at high risk for SMM and should be prioritized in efforts to improve maternal health outcomes.
According to the CDC and Maternal Mortality Review Committees, approximately two-thirds of maternal deaths are preventable.50 Although our study did not specifically evaluate the preventability of SMM among women with disabilities, a significant proportion of these adverse outcomes could likely be avoided with appropriate interventions and care.
There are several limitations to this study. First, there is the potential for misclassification of disability status because ICD codes may not adequately capture disability, especially if women did not seek care related to their disability or discuss the history of their disability with their health care professionals during delivery. This misclassification is likely to reduce the estimated differences in outcomes between women with and without disabilities (shift towards the null). We attempted to mitigate this bias by using a comprehensive list of disability codes from validated algorithms in peer-reviewed literature,20–22 but cannot rule out the possibility of misclassification. Second, we examined disability status and type but lacked details on disability onset and severity, which could further modify risks. Fourth, although giving birth more than once within a single calendar year is rare,51 any woman who delivered more than once during the 2016–2021 period was counted each time she delivered. Finally, given the cross-sectional nature of the data, cause-and-effect relationships cannot be established.
Our study demonstrates that women with disabilities are at significantly higher risk of SMM during delivery compared with those without disabilities, with the magnitude of risk varying by disability type. These findings underscore the urgent need to address the unique needs of this vulnerable population in efforts to reduce maternal morbidity and mortality in the United States. Health care professionals and policymakers must prioritize disability-competent care when developing interventions to improve maternal outcomes.
Footnotes
Research reported in this publication was supported by the National Institute on Disability, Independent Living, and Rehabilitation Research under Award Number 90DPHF0011. The content is solely the responsibility of the authors and does not represent the policy of NIH, NICHD, NIDILRR, ACL, or HHS, and you should not assume endorsement by the Federal Government.
Financial Disclosure The authors did not report any potential conflicts of interest.
Each author has confirmed compliance with the journal's requirements for authorship.
Peer reviews and author correspondence are available at http://links.lww.com/AOG/D797.
The authors acknowledge the experiences of transgender and nonbinary individuals who become pregnant; however, this study collected data only on women, and the findings may not apply equally to all gender identities.
REFERENCES
- 1.Fink DA, Kilday D, Cao Z, Larson K, Smith A, Lipkin C, et al. Trends in maternal mortality and severe maternal morbidity during delivery-related hospitalizations in the United States, 2008 to 2021. JAMA Netw Open 2023;6:e2317641. doi: 10.1001/jamanetworkopen.2023.17641 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Crear-Perry J, Correa-de-Araujo R, Lewis Johnson T, McLemore MR, Neilson E, Wallace M. Social and structural determinants of health inequities in maternal health. J Womens Health 2021;30:230–5. doi: 10.1089/jwh.2020.8882 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Okoro CA, Hollis ND, Cyrus AC, Griffin-Blake S. Prevalence of disabilities and health care access by disability status and type among adults—United States, 2016. MMWR Morb Mortal Wkly Rep 2018;67:882–7. doi: 10.15585/mmwr.mm6732a3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Horner-Johnson W, Akobirshoev I, Valentine A, Powell R, Mitra M. Preconception health risks by presence and type of disability among U.S. women. Disabil Health J 2024;17:101588. doi: 10.1016/j.dhjo.2024.101588 [DOI] [PubMed] [Google Scholar]
- 5.Mitra M, Clements KM, Zhang J, Iezzoni LI, Smeltzer SC, Long-Bellil LM. Maternal characteristics, pregnancy complications, and adverse birth outcomes among women with disabilities. Med Care 2015;53:1027–32. doi: 10.1097/MLR.0000000000000427 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Brown H, Cobigo V, Lunsky Y, Vigod S. Maternal and offspring outcomes in women with intellectual and developmental disabilities: a population‐based cohort study. BJOG 2016;124:757–65. doi: 10.1111/1471-0528.14120 [DOI] [PubMed] [Google Scholar]
- 7.Akobirshoev I, Parish SL, Mitra M, Rosenthal E. Birth outcomes among US women with intellectual and developmental disabilities. Disabil Health J 2017;10:406–12. doi: 10.1016/j.dhjo.2017.02.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Mitra M, Clements K, Zhang J, Smith LD. Disparities in adverse preconception risk factors between women with and without disabilities. Matern Child Health J 2016;20:507–15. doi: 10.1007/s10995-015-1848-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Tarasoff LA, Ravindran S, Malik H, Salaeva D, Brown HK. Maternal disability and risk for pregnancy, delivery, and postpartum complications: a systematic review and meta-analysis. Am J Obstet Gynecol 2020;222:27.e1–32. doi: 10.1016/j.ajog.2019.07.015 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Morton C, Le JT, Shahbandar L, Hammond C, Murphy EA, Kirschner KL. Pregnancy outcomes of women with physical disabilities: a matched cohort study. PM R 2013;5:90–8. doi: 10.1016/j.pmrj.2012.10.011 [DOI] [PubMed] [Google Scholar]
- 11.Schiff MA, Doody DR, Crane DA, Mueller BA. Pregnancy outcomes among deaf women in Washington State, 1987-2012. Obstet Gynecol 2017;130:953–60. doi: 10.1097/AOG.0000000000002321 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Mitra M, Akobirshoev I, Valentine A, Brown HK, Moore Simas TA. Severe maternal morbidity and maternal mortality in women with intellectual and developmental disabilities. Am J Prev Med 2021;61:872–81. doi: 10.1016/j.amepre.2021.05.041 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Mitra M, Akobirshoev I, Valentine A, McKee K, McKee MM. Severe maternal morbidity in deaf or hard of hearing women in the United States. Prev Med 2024;180:107883. doi: 10.1016/j.ypmed.2024.107883 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Reichard A, Alvarado M, Ruiz S, King T, King R, Cruz T, et al. Disability and pregnancy: research from NIDILRR and NICHD. Administration for Community Living; 2021. [Google Scholar]
- 15.American College of Obstetricians and Gynecologists. Our commitment to changing the culture of medicine and eliminating racial disparities in women’s health outcomes. Accessed January 10, 2024. https://www.acog.org/about/our-commitment-to-changing-the-culture-of-medicine-and-eliminating-racial-disparities-in-womens-health-outcomes [Google Scholar]
- 16.Horner-Johnson W, Garg B, Darney BG, Biel FM, Caughey AB. Severe maternal morbidity and other perinatal complications among women with physical, sensory, or intellectual and developmental disabilities. Paediatr Perinat Epidemiol 2022;36:759–68. doi: 10.1111/ppe.12873 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Brown HK, Ray JG, Chen S, Guttmann A, Havercamp SM, Parish S, et al. Association of preexisting disability with severe maternal morbidity or mortality in Ontario, Canada. JAMA Netw Open 2021;4:e2034993. doi: 10.1001/jamanetworkopen.2020.34993 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Agency for Healthcare Research and Quality. Introduction to the HCUP national inpatient sample (NIS); 2020. Accessed February 12, 2023. https://www.hcup-us.ahrq.gov/db/nation/nis/NIS_Introduction_2020.jsp [Google Scholar]
- 19.Kuklina EV, Whiteman MK, Hillis SD, Jamieson DJ, Meikle SF, Posner SF, et al. An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity. Matern Child Health J 2008;12:469–77. doi: 10.1007/s10995-007-0256-6 [DOI] [PubMed] [Google Scholar]
- 20.U.S. Commission on Civil Rights. Sharing the dream: is the ADA accommodating all? Chapter 5 psychiatric disabilities and the ADA. Accessed February 13, 2023. https://www.usccr.gov/files/pubs/ada/ch5.htm [Google Scholar]
- 21.Darney BG, Biel FM, Quigley BP, Caughey AB, Horner-Johnson W. Primary cesarean delivery patterns among women with physical, sensory, or intellectual disabilities. Womens Health Issues 2017;27:336–44. doi: 10.1016/j.whi.2016.12.007 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Brown HK, Varner C, Ray JG, Scime NV, Fung K, Guttmann A, et al. Comparison of emergency department use between pregnant people with and without disabilities in ontario, Canada. JAMA Netw Open 2023;6:e2327185. doi: 10.1001/jamanetworkopen.2023.27185 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.U.S. Equal Employment Opportunity Commission. Enforcement guidance on the ADA and psychiatric disabilities. Accessed April 1, 2024. https://www.eeoc.gov/laws/guidance/enforcement-guidance-ada-and-psychiatric-disabilities [Google Scholar]
- 24.Centers for Disease Control and Prevention. Severe maternal morbidity in the United States. Accessed June 16, 2020. https://www.cdc.gov/reproductivehealth/maternalinfanthealth/severematernalmorbidity.html [Google Scholar]
- 25.Centers of Disease Control and Prevention (CDC). How does CDC identify severe maternal morbidity?. Accessed August 22, 2023. https://www.cdc.gov/reproductivehealth/maternalinfanthealth/smm/severe-morbidity-ICD.htm [Google Scholar]
- 26.Kozhimannil KB, Arcaya MC, Subramanian SV. Maternal clinical diagnoses and hospital variation in the risk of cesarean delivery: analyses of a National US Hospital Discharge Database. PLoS Med 2014;11:e1001745. doi: 10.1371/journal.pmed.1001745 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Albrecht SS, Kuklina EV, Bansil P, Jamieson DJ, Whiteman MK, Kourtis AP, et al. Diabetes trends among delivery hospitalizations in the U.S., 1994-2004. Diabetes Care 2010;33:768–73. doi: 10.2337/dc09-1801 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Maeda A, Bateman BT, Clancy CR, Creanga AA, Leffert LR. Opioid abuse and dependence during pregnancy: temporal trends and obstetrical outcomes. Anesthesiology 2014;121:1158–65. doi: 10.1097/ALN.0000000000000472 [DOI] [PubMed] [Google Scholar]
- 29.Chauhan A, Potdar J. Maternal mental health during pregnancy: a critical review. Cureus 2022;14:e30656. doi: 10.7759/cureus.30656 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Satyanarayana VA, Lukose A, Srinivasan K. Maternal mental health in pregnancy and child behavior. Indian J Psychiatry 2011;53:351–61. doi: 10.4103/0019-5545.91911 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Leddy MA, Power ML, Schulkin J. The impact of maternal obesity on maternal and fetal health. Rev Obstet Gynecol 2008;1:170–8.10.1 [PMC free article] [PubMed] [Google Scholar]
- 32.Catalano PM. The impact of gestational diabetes and maternal obesity on the mother and her offspring. J Dev Orig Health Dis 2010;1:208–15. doi: 10.1017/S2040174410000115 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kaplan JB, Bennett T. Use of race and ethnicity in biomedical publication. JAMA 2003;289:2709–16. doi: 10.1001/jama.289.20.2709 [DOI] [PubMed] [Google Scholar]
- 34.Boyd RW, Lindo EG, Weeks LD, McLemore MR. On racism: a new standard for publishing on racial health inequities. Health Affairs Blog 2020 Jul 2. doi: 10.1377/forefront.20200630.939347 [DOI] [Google Scholar]
- 35.Austin PC. Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Commun Stat Simulation Comput 2009;38:1228–34. doi: 10.1080/03610910902859574 [DOI] [Google Scholar]
- 36.Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology 2009;20:488–95. doi: 10.1097/EDE.0b013e3181a819a1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Agency for Healthcare Research and Quality . Introduction to the HCUP Nationwide Inpatient Sample (NIS). Accessed March 22, 2023. https://hcup-us.ahrq.gov/nisoverview.jsp [Google Scholar]
- 38.Schenker N, Raghunathan TE, Chiu PL, Makuc DM, Zhang G, Cohen AJ. Multiple imputation of missing income data in the national health interview survey. J Am Stat Assoc 2006;101:924–33. doi: 10.1198/016214505000001375 [DOI] [Google Scholar]
- 39.Cuschieri S. The STROBE guidelines. Saudi J Anaesth 2019;13(suppl 1):S31–4. doi: 10.4103/sja.SJA_543_18 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Leonard SA, Kennedy CJ, Carmichael SL, Lyell DJ, Main EK. An expanded obstetric comorbidity scoring system for predicting severe maternal morbidity. Obstet Gynecol 2020;136:440–9. doi: 10.1097/AOG.0000000000004022 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Nishat F, Lunsky Y, Tarasoff LA, Brown HK. Prenatal care adequacy among women with disabilities: a population-based study. Am J Prev Med 2022;62:39–49. doi: 10.1016/j.amepre.2021.05.037 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Tarasoff LA. “We don't know. We’ve never had anybody like you before”: barriers to perinatal care for women with physical disabilities. Disabil Health J 2017;10:426–33. doi: 10.1016/j.dhjo.2017.03.017 [DOI] [PubMed] [Google Scholar]
- 43.Horner-Johnson W, Biel FM, Caughey AB, Darney BG. Differences in prenatal care by presence and type of maternal disability. Am J Prev Med 2019;56:376–82. doi: 10.1016/j.amepre.2018.10.021 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Heideveld-Gerritsen M, van Vulpen M, Hollander M, Oude Maatman S, Ockhuijsen H, van den Hoogen A. Maternity care experiences of women with physical disabilities: a systematic review. Midwifery 2021;96:102938. doi: 10.1016/j.midw.2021.102938 [DOI] [PubMed] [Google Scholar]
- 45.National Council on Disability. Framework to end health disparities of people with disabilities. Accessed March 1, 2024. https://www.ncd.gov/report/framework-to-end-health-disparities-of-people-with-disabilities/ [Google Scholar]
- 46.National Institutes of Health . NIH designates people with disabilities as a population with health disparities. Accessed September 29, 2023. https://www.nih.gov/news-events/news-releases/nih-designates-people-disabilities-population-health-disparities [Google Scholar]
- 47.Berndl A, Ladhani N, Wilson RD, Basso M, Jung E, Tarasoff LA, et al. Guideline no. 416: labour, delivery, and postpartum care for people with physical disabilities. J Obstet Gynaecol Can 2021;43:769–80.e1. doi: 10.1016/j.jogc.2021.02.111 [DOI] [PubMed] [Google Scholar]
- 48.Louis JM, Menard MK, Gee RE. Racial and ethnic disparities in maternal morbidity and mortality. Obstet Gynecol 2015;125:690–4. doi: 10.1097/AOG.0000000000000704 [DOI] [PubMed] [Google Scholar]
- 49.Admon LK, Winkelman TNA, Zivin K, Terplan M, Mhyre JM, Dalton VK. Racial and ethnic disparities in the incidence of severe maternal morbidity in the United States, 2012-2015. Obstet Gynecol 2018;132:1158–66. doi: 10.1097/AOG.0000000000002937 [DOI] [PubMed] [Google Scholar]
- 50.Petersen EE, Davis NL, Goodman D, Cox S, Mayes N, Johnston E, et al. Vital signs: pregnancy-related deaths, United States, 2011-2015, and strategies for prevention, 13 States, 2013-2017. MMWR Morb Mortal Wkly Rep 2019;68:423–9. doi: 10.15585/mmwr.mm6818e1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Adams M, Delaney K, Stupp P, McCarthy B, Rawlings J. The relationship of interpregnancy interval to infant birthweight and length of gestation among low-risk women, Georgia. Paediatric perinatal Epidemiol 1997;11(suppl 1):48–62. doi: 10.1046/j.1365-3016.11.s1.8.x [DOI] [PubMed] [Google Scholar]