Perinatal Health Risks And Outcomes Among US Women With Self-Reported Disability, 2011–19

The reproductive rights of people with disabilities have long been neglected,¹ and the right to bear and raise children (integral to achieving progress toward reproductive justice) especially has been challenged.^2,3 Despite their often overlooked and threatened rights, people with disabilities are increasingly becoming pregnant and giving birth.^4,5 The large majority of these pregnancies end in healthy live births.⁶ However, multiple studies have found that the risk for complications and adverse outcomes (for example, preterm birth and low birthweight) is greater among women with disabilities than among those without disabilities.^7–12 Women with disabilities also have been found to be more likely to experience prenatal risk factors for poor birth outcomes, such as tobacco use during pregnancy and delayed entry into prenatal care.^13,14 (Acknowledging that most people who experience pregnancy are women and that some people who experience pregnancy are not women, and seeking to be inclusive of all genders, we use both gender-specific and gender-neutral terms throughout this article.)

Most research to date on the association between disability and pregnancy outcomes has relied on data from hospital discharge records and medical claims data.^7,9 In these studies, disability is approximated through the presence of diagnosis codes that may be associated with functional limitations in hearing, vision, mobility, or cognition. This approach has opened the door to a greater range of population-based research addressing disability, but it has substantial limitations. The link between diagnoses and functional limitation or disability is not always clear cut,^15–17 and recent research suggests that reliance on diagnosis codes in delivery discharge records may miss many birthing parents with disabilities.¹⁸

In US studies using hospital discharge data, the proportion of births in which the birthing parent is coded with a disability of any kind has been found to range from less than 1 percent to 6.6 percent.^4,19 This is substantially lower than the estimated 12–18 percent of women of reproductive age identified as having disabilities in self-reported survey data sources.^20–25 Thus, findings from studies using hospital discharge data might not apply to the broader population of reproductive-age women with disabilities. Diagnoses coded in delivery discharge records may represent only the most obvious disabilities or those that were judged by a clinician to be particularly salient to the course of pregnancy, labor, or delivery.⁴ Studies relying on these data likely undercount and misclassify many women with milder or less visible disabilities, distorting the true extent of disability-related disparities. A better understanding of the proportion of pregnancies affected by disparities associated with disability is needed for informing efforts to address those disparities.

Innovations in survey data collection within the past decade enable more comprehensive assessment of disability status in the birthing population. Notably, there are now relevant data sources that rely on a person’s own responses to disability questions instead of indirectly inferring disability from other data sources. This change was driven in part by Section 4302 of the Affordable Care Act (ACA), which mandated measurement and monitoring of health disparities, including those associated with disability. As a result, the Department of Health and Human Services adopted a set of six disability questions as the minimum standard for disability data collection in federally funded population-based health surveys.²⁶ We present findings from one such survey to improve understanding of disability-related inequities in prenatal risk factors and pregnancy outcomes. Our results further illuminate the scope of such disparities and highlight the need for greater attention to the reproductive health of this population. We also discuss current approaches to the collection of disability status in public health surveys and in clinical practice, shedding light on best practices to guide policy decisions and facilitate progress toward health equity.

Study Data And Methods

Data And Variables

We analyzed pooled cross-sectional data from four waves (2011–13, 2013–15, 2015–17, 2017–19) of the National Survey of Family Growth (NSFG). The NSFG is designed and administered by the National Center for Health Statistics in the Centers for Disease Control and Prevention. It provides nationally representative estimates of aspects of family and reproductive life, including marriage, sexual activity, contraceptive use, and pregnancy.²⁷ Details of NSFG methods are available online.²⁸

The NSFG provides pregnancy data in two files. The “female respondent file” (the survey does not currently collect gender identity data) includes sociodemographic characteristics of respondents at the time of the survey interview, along with information about sexual and contraceptive history. A separate “pregnancy file” contains retrospective data about each pregnancy experienced by survey participants in their lifetimes thus far. We merged data from the pregnancy files and female respondent files to create a single data set allowing us to determine the disability status of the respondent associated with each pregnancy. We restricted our analyses to singleton pregnancies that lasted twenty weeks or longer and ended in a live birth. Because these were deidentified publicly available data, Institutional Review Board approval was not required.

The NSFG includes six yes-or-no disability questions, consistent with current Department of Health and Human Services standards.²⁶ These questions are as follows: Do you have serious difficulty hearing? Do you have serious difficulty seeing, even when wearing glasses? Because of a physical, mental, or emotional condition, do you have serious difficulty concentrating, remembering, or making decisions? Do you have serious difficulty walking or climbing stairs? Do you have difficulty dressing or bathing? Because of a physical, mental, or emotional condition, do you have difficulty doing errands alone such as visiting a doctor’s office or shopping?²⁸ The first four questions address difficulty with basic actions (hearing, seeing, moving, thinking), whereas the last two provide an indication of impact on daily life (that is, need for assistance).²⁹ Our first disability measure was a yes-or-no variable specifying whether a respondent answered yes to any of the disability questions versus none of them. Second, we created a more fine-grained disability variable that reflected the type, number, and impact of disabilities. The categories of this variable were mutually exclusive and exhaustive: no disability; sensory disability only (difficulty with either vision or hearing but not both); cognitive disability only; mobility disability only; two or more sensory, cognitive, or mobility disabilities; and any difficulty with self-care or independent living activities.

We used several variables that are markers of health risks during pregnancy or adverse pregnancy outcomes. These included smoking during pregnancy, delayed initiation of prenatal care, preterm birth, and low birthweight. A yes response on the smoking variable indicated that the respondent smoked after they knew they were pregnant. We defined delayed initiation of prenatal care as beginning at week fourteen or later (after the first trimester) or receiving no care. Preterm births were those that occurred before thirty-seven weeks of gestation. Low birthweight was defined as less than 2,500 grams at birth, regardless of gestational age. Data on smoking and prenatal care initiation were only collected for pregnancies within the past five years (from the time of NSFG participation). Data on preterm birth and low birthweight were available for all pregnancies, regardless of how long ago they occurred.

Statistical Analyses

We compared respondents with any disability to those without disabilities on each of the perinatal variables, using two-sided chi-square tests. Similarly, we compared respondents in each disability category with those without disabilities, also using chi-square tests. Because of the smaller sample sizes for smoking and prenatal care initiation (data only available from the past five years), we reduced the number of disability categories for these analyses to the following groups: none, cognitive only (the largest disability group, consistent with other survey data pertaining to the reproductive age range),^23,25 other single disability (vision, hearing, or mobility), multiple disabilities, and any self-care or independent living difficulty.

We used regression models to assess how disability status was associated with prenatal health risks and pregnancy outcomes, adjusting for potential confounders. We obtained adjusted relative risks and 95% confidence intervals from modified Poisson regression analyses that included the following covariates: age at conception, race and ethnicity, marital status at conception, education, income, parity, and body mass index. See the online appendix for details about our analytic approach and model specifications.³⁰ We analyzed each of the four perinatal variables in a separate regression model. Because data on preterm birth and low birthweight were available for all pregnancies regardless of when they occurred, we conducted sensitivity analyses for these outcomes restricted to births within the five years before NSFG participation. We established a $p$ value of <0.05 as indicating a statistically significant difference between groups for our bivariate and multivariable analyses. We performed all analyses with Stata, version 15. We used the necessary clustering (accounting for the number of pregnancies per respondent) and weights to obtain accurate results applicable to the entire US population.

Limitations

Our study was limited by the nature of the data source. NSFG respondents must be able to listen to or read questions without assistance and respond to survey questions independently;³¹ thus, some people with disabilities might not be able to participate. Further, the survey does not collect information on timing of disability onset, so we were unable to determine a respondent’s disability status in relation to when a pregnancy occurred. Although some disabilities are lifelong, others are acquired later in life and can be temporary, episodic, or permanent.^32,33 We attempted to mitigate the impact of uncertainty about timing of disability by conducting sensitivity analyses restricted to pregnancies that occurred in the preceding five years, thus shortening the time window for acquiring a disability after delivery and increasing the likelihood that disability was present during pregnancy. However, it is still possible that disability status for some of the included pregnancies was miscategorized, such that some respondents might not actually have had a disability at the time of the pregnancy. Such miscategorizations would have resulted in the appearance of a weaker association between disability and our perinatal variables than is actually true. In addition, small numbers in specific disability categories meant that we were only able to conduct regression analyses for overall disability (any versus none). We were also limited in the outcomes we could analyze. Assessing size for gestational age would account for correlation between preterm birth and low birthweight, but size for gestational age data were not available. However, low birthweight remains an important outcome in itself.^34,35

Study Results

We analyzed 27,033 pregnancies reported by 9,899 respondents. Of these respondents, 19.5 percent had a disability, and their pregnancies constituted 21 percent of the included pregnancies. Characteristics of respondents with and without disabilities are shown in exhibit 1. Compared to those without disabilities, respondents with disabilities were substantially more likely to be younger than age twenty at the time they conceived, living in poverty, and categorized as having obesity; they were much less likely to have a college education or to have been married or cohabiting with a partner at the time of conception.

Exhibit 2 shows the prevalence of each perinatal variable by disability status and category. Overall, births to respondents with disabilities were significantly more likely to be characterized by smoking during pregnancy, delayed entry into prenatal care, preterm birth, and low birthweight. Differences were particularly notable for smoking during pregnancy, which occurred in 19.0 percent of pregnancies among respondents with disabilities versus 8.9 percent of pregnancies among respondents without disabilities ($p<0.001$). Prevalence of risks and outcomes differed by disability category. Smoking during pregnancy, delayed prenatal care, and low birthweight were most common in the multiple disability category. The proportion of preterm births was highest in the mobility disability category.

Results of our adjusted regression analyses are shown in exhibit 3, including our sensitivity analyses, which were restricted to pregnancies that occurred in the preceding five years. Pregnancies among respondents with disabilities had higher risk of smoking during pregnancy (risk ratio: 1.46; $p=0.005$), preterm birth (RR: 1.24; $p=0.002$), and low birthweight (RR: 1.29; $p=0.006$) compared with pregnancies among respondents without disabilities. The association between disability and delayed prenatal care was not significant. When we restricted our analyses of preterm birth and low birthweight to births within the past five years, associations with disability were slightly stronger than in models not restricted by period.

SOURCE Authors’ analysis of data from the National Survey of Family Growth, 2011–19. NOTES Whiskers represent 95% confidence intervals. Data on prenatal care and smoking during pregnancy were only available for births in the past 5 years. Reference category is women without disabilities. ^aSensitivity analysis results.

Discussion

Using self-reported disability data, we found that 19.5 percent of National Survey of Family Growth respondents who had given birth indicated at least one disability. This is very similar to the most recent (2016) prevalence estimate of disability (18 percent) among all women of reproductive age in the US.²³ One in five of the births we analyzed were to respondents with a disability. This is a much larger proportion than has been identified in previous research in the US that has used diagnosis codes in delivery discharge records to extrapolate disability, confirming concerns that such studies may miss large numbers of births to people with disabilities.

Diagnosis codes may yield somewhat more representative results in countries with comprehensive health care systems. For example, a study in Ontario, Canada, for which researchers had access to patients’ full medical histories, identified the birthing parent as having a disability for 13 percent of pregnancies in 2017–18.⁵ Compared with the range from less than 1 percent to 6.6 percent reported in US studies using diagnosis codes,^4,19 the estimate from Canada is much closer to the prevalence we observed in the NSFG data. Given that health services researchers in the US rarely can access medical data across a person’s entire lifespan, the need for self-reported disability data takes on additional importance.

Similar to previous US studies, we found that smoking during pregnancy, delayed entry into prenatal care, preterm birth, and low birthweight were more common in pregnancies among respondents with versus without disabilities. The size of the difference we observed for smoking was similar to results of prior research using diagnosis codes.^19,36 Patterns for delayed prenatal care were also generally comparable to those found previously, with larger disparities for people with cognitive disabilities or multiple disabilities and relatively small differences between people with disabilities overall and those without disabilities.^14,19,36 The differences we observed for preterm birth and low birthweight were smaller than those reported in some studies using diagnosis codes.^9–11 However, direct comparisons are challenging, given other methodological differences from prior studies (for example, in specific disability types addressed, inclusion of covariates, and measures of association reported).

Implications For Policy

Our findings suggest that tracking of disparities associated with disability, as mandated by the Affordable Care Act, would be greatly facilitated by collecting self-reported disability data in clinical settings. Without these data, methods of identifying people with disabilities in the US through patient records have substantial limitations and yield incomplete and potentially unrepresentative results.^15–18 Collection of self-reported data could also facilitate the provision of reasonable accommodations and improve the quality of care. For these reasons, patients with disabilities have expressed strong support for collection of disability information and have indicated that they would be comfortable with doctors, nurses, or schedulers asking them about disability and recording the information in their medical records.^37–39

The same six questions adopted for use in population-based surveys provide a promising foundation for data collection in clinical settings. However, disability scholars have noted that the cognitive disability question does not differentiate reasons for cognitive limitation (for example, psychiatric disability, learning disability, intellectual disability) and thus does not allow analysis of those groups separately.^40,41 In particular, experts have raised concerns that the six-question set likely does not adequately identify people with intellectual and developmental disabilities⁴⁰ and does not assess communication difficulty.⁴² Additional questions have been recommended to address these gaps.^40,42,43 A pilot test of a modified question set in a Colorado health system found that data collection by telephone agents during patient registration and scheduling dramatically increased documentation of disability status in electronic health records, added minimal additional time to calls, and was well-received by patients.³⁹ Use of a similar but slightly expanded question set, including questions on age at disability onset, is now required for all health care providers in Oregon as well as all Oregon Health Authority and Department of Human Services programs, following state-level legislation and rule-making processes.^43,44 These efforts seek to fill the current void regarding federal standards for disability data collection by health care organizations³⁹ and allow health services researchers and health systems to identify and address disparities in care and outcomes experienced by people with disabilities.^39,44

Similarly, for survey data collection, the current six questions were adopted by the Department of Health and Human Services as a minimum standard. Additional questions would be helpful for identifying other types of disabilities and clarifying timing of disability. Our sensitivity analyses highlighted the relevance of the latter point. When we restricted our analyses of preterm birth and low birthweight to pregnancies in the past five years, the association of disability with these outcomes was stronger than when we included all pregnancies during a respondent’s lifetime. That shift in the strength of association suggests that disability status for some older pregnancies was misclassified such that some respondents did not actually have disabilities at the time of pregnancy. This misclassification could be avoided if the NSFG collected data on timing of disability onset. Moreover, for health surveys in general, data on disability onset are relevant for better understanding health experiences and disparities, which may differ substantially for people with lifelong versus later-onset disabilities.^32,45

Our findings also have implications for the delivery of care. We found large differences between birthing parents with and without disabilities on prevalence of smoking during pregnancy. Similarly large differences have been found in previous pregnancy studies^13,19,36 and among people of reproductive age who can potentially get pregnant.^21,24,46 There is a clear need for public health smoking prevention and cessation efforts to be inclusive of people with disabilities. In health care settings, clinicians should ask people with disabilities about tobacco use and provide support for quitting. Research in the general population⁴⁷ has linked smoking during pregnancy to preterm birth and low birthweight. The high prevalence of smoking among respondents with disabilities in our sample may partially explain the greater risk for preterm birth and low birthweight in this population. Although investigation of causal mechanisms was outside the scope of this study, detailed examination of associations between disability, smoking, and pregnancy outcomes is warranted.

We found smaller overall differences for delayed prenatal care. However, our descriptive results and prior research show that timing of prenatal care initiation differs by type and number of disabilities.¹⁴ For some people with disabilities, delayed entry into care may be related to delayed recognition of pregnancy, particularly for those who were not expecting to get pregnant.^22,36 Unfortunately, as shown in the present study and prior research,^{12,13,19,21,24,36,46} people with disabilities are more likely to have modifiable risk factors for adverse pregnancy outcomes (for example, smoking, obesity, depression) and thus have particular need for prompt care and support to have the healthiest pregnancies possible.

Our findings underscore the need for preconception care that assesses the pregnancy desires of people with disabilities.

The issues noted above underscore the need for preconception care that assesses the opportunities for conception and pregnancy desires of people with disabilities. The American College of Obstetricians and Gynecologists recommends that clinicians discuss reproductive plans at every visit, for example, by asking one key question⁴⁸ (“Would you like to become pregnant in the next year?”) of every woman of reproductive age.⁴⁹ Application of this approach to people with disabilities may be affected by clinicians’ biases. Women with disabilities have described clinicians treating them as nonsexual, assuming or implying that they would not or should not get pregnant.^50,51 Such biases could be reduced through increased provider education.^52,53 Section 5307 of the ACA authorized federal funding for training health care professionals in disability-competent care.⁵⁴ As yet, however, few clinicians receive instruction in addressing the reproductive health needs of people with disabilities.⁵⁵ Closing this gap would improve clinicians’ readiness to initiate conversations with people with disabilities about reproductive goals and preparing for healthy pregnancies.

Conclusion

Perinatal disparities associated with disability may be much more widespread than has been indicated by prior research.

Consistent with prior research, we found that respondents with disabilities were more likely than those without disabilities to have smoked during pregnancy, delayed entry into prenatal care, given birth prematurely, and had infants with low birthweight. However, the proportion of pregnancies in which the birthing parent had a disability was substantially higher than in US studies using diagnosis codes to identify disability, suggesting that perinatal disparities associated with disability may be much more widespread than has been indicated by prior research. Our findings highlight the need to collect self-reported disability data in health care settings to better assess disparities in care and outcomes and more fully address the health equity provisions of the ACA.

ACKNOWLEDGMENTS

Willi Horner-Johnson’s effort was supported in part by Award No. 90DPHF0011 and Award No. 90DDUC0039 from the Administration for Community Living, Department of Health and Human Services. Mekhala Dissanayake was supported in part by a training grant (No. T32 HD52468) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and is also employed by the Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill. Jonathan Snowden was supported in part by an Antiracism Faculty Fellowship from the Oregon Health & Science University–Portland State University School of Public Health. The contents are those of the authors and do not necessarily represent the official views of, or an endorsement by, the funding agencies or the US government. This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt, and build upon this work, for commercial use, provided the original work is properly cited. See http://creativecommons.org/licenses/by/4.0/. [Published online September 21, 2022.]

NOTES

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