Discrimination Among Disabled Adults in the United States: Findings from the 2022 National Survey on Health and Disability

Abstract

Disabled people face discrimination in healthcare settings, yet the compounding effects of intersectional identities remain underexplored. This project examines how different types of discrimination affect healthcare access and outcomes. We conducted a cross-sectional study of disability-based, race-based, gender-based, and sexuality-based discrimination using the 2022 National Survey on Health and Disability (NSHD; n = 2725) administered October 2021–January 2022. Measures used in this study include: (1) demographics; (2) types of discrimination; (3) unmet healthcare needs. Our sample was not nationally representative, as it consisted primarily of white, college-educated participants. Data were analyzed using summary statistics (STATA crosstab) among respondents with health insurance (n = 2566). Chi-squared tests were used to determine statistical significance. We fit logistic regression models for categorical responses (STATA logit), adjusting for participant characteristics. Some participants (41%; n = 2566) reported experiencing at least one form of discrimination, with 4.9% reporting race-, 15.08% gender-, 5.9% sexuality-, and 38.3% disability-based discrimination. Most participants (94%; n= 2412) reported at least one unmet healthcare need, from unmet prostheses (2.6%) to unmet dental care (34.8%). Compared with other care types, participants had the lowest odds ratio (OR = 0.38, p < 0.001) of having their preventive care or specialist care needs met. These findings highlight that discrimination contributes to disparities in particular areas of healthcare access and emphasizes a need for tailored interventions and additional research.

1. Introduction

Discrimination is a common experience of minoritized groups [1]. In the United States, lesbian, gay, bisexual, transgender, queer, intersex, asexual and additional sexual and gender minorities (LGBTQIA2S+), racial minorities, and disabled people [2,3,4], commonly face discrimination and stigma, resulting in long-lasting deleterious health effects [1]. Further, experiences of discrimination and stigma have been linked to reduced quality of life and decreased feelings of self-worth, which contribute to increased mental health challenges [1,5,6,7].

Those who experience social disadvantages, such as discrimination and social exclusion, experience stress that negatively impacts health [8]. Specifically, structural forms of discrimination establish stressful environments, which can generate cognitive, affective, and behavioral stress [1]. The social–ecological model provides a framework for understanding the differing impacts discrimination may have on health [9]. For example, LGBTQIA2S+ youth have increased odds of suicidality when experiencing interpersonal discrimination or family rejection [10,11]. People experiencing discrimination at a macrosystem level (e.g., anti-LGBQTIA2S+ legislation) may experience more subtle, but lasting effects over time, including generational negative effects. Discrimination at this level contributes to inequality and oppression [12].

Negative health outcomes associated with perceived discrimination and stigmatization are largely explained by the increase in psychological and physiological stress. Chronic stress seen by increased cortisol output has been found to increase blood pressure, elevating cardiometabolic risk [1,13,14,15,16,17,18]. Increased cortisol output has also been correlated with a variety of physical health symptoms, such as nausea, headaches, and gastrointestinal distress [4,19]. In addition to physical health problems, perceived discrimination and stigma is associated with worse mental health outcomes, including anxiety, depression, suicidality, and psychological distress [16,17,19,20].

Intersectionality, a framework describing the interconnected nature of social categories (e.g., race, ethnicity, gender, sex, sexual orientation, socioeconomic status, and disability status) and the compounded discrimination individuals experience as a result, contributes to health disparities [21,22]. Despite increased health problems among people experiencing discrimination and stigma, fewer healthcare services are sought out or accessed. In fact, increased experiences of race-, sex-, gender-, orientation-, and disability-related discrimination and stigma are negatively correlated with utilization of services and prescriptions [1,2,23,24]. Individuals who report discrimination in healthcare settings are more likely to delay filling or forgoing prescriptions and medical care, including preventative cancer screenings [23,25,26,27,28]. Evidence indicates this may be due to eroded trust in health care systems from previous experiences of discrimination or stigma [17,23,29,30]. The most common forms of discrimination are based on racial and ethnic identity, but discrimination based on sex, sexual orientation, gender, and disability have also been commonly reported [25,26,27,28,30].

The Andersen Behavioral Model of Healthcare Use is a multilevel model encompassing individual and contextual determinants of healthcare use that are separated into predisposing, enabling, and need factors. This framework offers a way to understand the associations between discrimination in healthcare settings and decreased utilization [31,32]. The Andersen Model suggests that those who experience discrimination in healthcare settings have increased medical mistrust and, with greater mistrust of medical personnel and institutions, are less likely to follow through with recommendations or even seek out preventative care [33,34]. Thus, the goal of this study was to explore disability-based, race-based, gender-based, and sexuality-based discrimination among disabled adults in the US and their impact on unmet healthcare needs.

2. Methods

2.1. Authors Positionality

The authorship team includes an interdisciplinary team of researchers with intersecting identities, including white, LGBTQ+, neurodivergent, and disabled researchers. This interdisciplinary team includes professionals with backgrounds in health services, public health, medicine, and rehabilitation.

2.2. Study Design and Data Source

Data came from the 2022 National Survey on Health and Disability, which was conducted by the University of Kansas. Briefly, the NSHD is a national survey of disabled adults living in the US Participants were recruited for this online survey through disability-focused organizations, listservs, newsletters, and conferences in the US, and via social media outlets [35]. Participants included in this sample were not nationally representative. Eligible participants were any disabled residents of the US and its territories who were at least 18 years old at the time of the study. Disability was defined with a screener question: “Do you have a physical or mental condition, impairment, or disability that affects your daily activities OR that requires you to use special equipment or devices, such as a wheelchair, walker, TDD or communication device?” (TDD: telecommunications device for the deaf). The 2022 NSHD (NSHD; n = 2725) was administered October 2021–January 2022. The study was an observational and descriptive cross-sectional design. This study was approved by the University of Kansas Institutional Review Board (Study No. 00147878).

2.3. Measures

Measures included: (1) participant demographics; (2) types of discrimination experienced; (3) unmet healthcare needs. Demographic information included in this study were age, race, sex, gender, sexual orientation, level of education, insurance status, and income [35]. The NSHD does not include questions on disability severity or visibility, so these variables were not included.

Types of discrimination included race-, gender-, sexuality-, and disability-based discrimination taken directly from the Health Reform Monitoring Survey [36]. Specifically, we asked “in the last 12 months have you ever felt that a doctor, other health care provider, or their staff judged you unfairly or discriminated against you because of…” “your race and/or ethnicity”, “your gender and/or gender identity”, “your sexual orientation”, and “a disability and/or health condition” with answer options of “yes”, “no”, and “I don’t know”.

Unmet healthcare needs included primary care, prescriptions, specialist care, dental care, mental health care, personal assistant services (PAS; defined as “a person or persons who come to your home and give you help with personal care or daily activities, sometimes known as a personal care attendant, support worker or caregiver”), physical or occupational therapy (PT, OT), durable medical equipment (DME; defined as equipment ordered or prescribed by a doctor that provides medically necessary assistance in the home for people who have certain medical conditions. Examples of DME include wheelchairs, canes, walkers, orthotics or braces, hospital beds, insulin pumps, oxygen equipment, etc.”), and prostheses. Unmet healthcare need questions were asked only of those who had health insurance [36].

2.4. Analysis

We examined the relationship between discrimination and unmet healthcare needs among respondents with health insurance. Data were analyzed using summary statistics (STATA crosstab). Chi-squared tests were used to determine statistical significance. The models were controlled for socio-economic and demographic characteristics (age, race, ethnicity, sex, gender, sexual orientation, level of education, and income). We fit logistic regression models for categorical responses (STATA logit) to the data for each unmet healthcare need. We controlled for race, sex, and age. We collapsed our race variable into a binary white/non-white variable. We used a six-part variable for sex assigned at birth. We also used a three-part categorical age variable. Uninsured participants were excluded from key analyses because the validated discrimination items were only asked of participants with health insurance. All analyses were conducted using STATA 15 [37].

3. Results

There were 2566 adult participants with health insurance in the 2022 NSHD. Mean age was 45 years (SD, Standard Deviation), the majority were White (85%), assigned female at birth (74%), had a college degree (72%), and were above the Federal Poverty Level (72%). Participants came from all four major Census regions. Nearly 60% of respondents identified as straight or heterosexual, 6.4% as gay/lesbian/homosexual, 13.8% bisexual, 5.1% asexual, and 12.8% of respondents endorsed a gender identity that did not align with their sex assigned at birth (see

Table 1. Population Characteristics, 2022 NSHD.

	Count	%
Race
White	2288	84%
Non-white	437	16%
Sex
Female	2008	74%
Male	673	24.8%
Gender
Woman	1682	61.8%
Man	645	23.7%
Transgender	23	0.8%
Non-binary	166	6.1%
Two-Spirit	6	0.2%
Agender	52	1.9%
Other	125	4.6%
Sexual Orientation
Gay/Lesbian	173	6.4%
Heterosexual	1632	59.9%
Bisexual	375	13.8%
Asexual	140	5.1%
Age
18–44	1476	54.2%
45–64	940	34.5%
65+	306	11.3%
Level of Education
High School Diploma	741	27.2%
College Graduate	1968	72.2%
Graduate Degree	16	0.6%
Income (%FPL)
under 75% FPL	302	11.3%
75–99% FPL	210	7.9%
100–137% FPL	235	8.8%
138–249% FPL	526	19.7%
250–399% FPL	563	21.1%
400% FPL and over	821	30.8%
Location (Census region)
South	722	26.5%
West	775	28.4%
Midwest	652	23.9%
Northeast	574	21.1%

Percentages may not total 100 due to the exclusion of missing responses. NSHD = National Survey on Health and Disability. FPL = Federal Poverty Level.

).

More than 41% of participants reported experiencing at least one form of discrimination, with 4.9% reporting race-, 15.1% gender-, 5.9% sexuality-, and 38.3% disability-based discrimination; 1.1% (30 participants) reported experiencing all forms of discrimination. Of those who reported disability-based discrimination, roughly 32% reported gender-, 13% sexuality-, or 10% race-based discrimination. Among non-white participants, 19.1% reported race-based discrimination. For non-heterosexual participants, we found 12.7% reported sexual orientation-based discrimination. In non-cisgender male participants, we found 12.6% of women and 39.6% of gender-diverse adults reported gender-based discrimination.

More than 94% of respondents reported at least one unmet healthcare need. The rate of unmet need differed by type of care. The lowest rates of unmet healthcare need were reported in unmet prostheses (2.6%) and unmet primary care (5.6%). The highest rates of unmet healthcare need were reported in unmet mental health care (27.7%) and unmet dental care (34.8%) (see

Table 2. Rates of Unmet Care Need, 2022 NSHD population with health insurance.

Care Type	Rate
Primary Care	5.6%
Rx	20.3%
Specialist	15.1%
Dental Care	34.8%
Preventative Care	15.8%
Mental Health	27.7%
Personal Support	19.8%
Physical/Occupational Therapy	15.8%
Durable Medical Equipment	17.7%
Prostheses	2.6%

).

When we aggregated any unmet need, we did not see a statistically significant relationship between reporting any discrimination and unmet healthcare need. However, when we focused on specific unmet needs, we found that experiencing any discrimination resulted in lower odds of having healthcare needs met. Participants reporting any type of discrimination had the lowest odds (OR = 0.38, p < 0.001) of having their preventive care or specialist care needs met compared with other care types (see

Table 3. Odds Ratios of Unmet Care Need, 2022 NSHD population with health insurance experiencing any discrimination, adjusted for race, sex, and age.

	Odds Ratio	CI	p-Value
Primary Care	0.56	0.40–0.79	0.001
Rx	0.41	0.34–0.50	<0.001
Specialist	0.36	0.29–0.45	<0.001
Dental Care	0.53	0.45–0.63	<0.001
Preventative Care	0.36	0.30–0.45	<0.001
Mental Health	0.41	0.34–0.49	<0.001
Personal Support	0.38	0.31–0.46	<0.001
Physical/Occupational Therapy	0.4	0.32–0.50	<0.001
Durable Medical Equipment	0.39	0.32–0.48	<0.001
Prostheses	0.61	0.37–1.00	0.052
Any unmet care	1.05	0.76–1.46	0.753

CI = Confidence Interval.

). None of the demographic variables included were statistically significant in all models. However, age was statistically significant in dental, mental health, personal support, durable medical equipment, and prosthetics at p < 0.05. We did not find any instances where experiencing discrimination was positively associated with having healthcare needs met.

4. Discussion

In this study, we found that 41% of disabled adults reported at least experiencing some form of race-, gender-, sexuality-, or disability-based discrimination in healthcare settings, with most reporting disability-based discrimination. Because the majority of our sample endorsed white race, race-based discrimination was least reported among our whole sample; among non-white participants, however, 19% reported race-based discrimination. Similarly, among non-cisgender participants, 39.5% reported gender-based discrimination. Different rates of unmet need—as low as 2% (prostheses) and as high as 34% (unmet dental care)—were reported across different types of care. With the exception of prostheses, experiencing any discrimination resulted in lower odds of having healthcare needs met. While our findings highlight important relationships between healthcare-related discrimination and unmet healthcare needs, they should be interpreted with caution given the study’s non-representative sample and cross-sectional design, which limit generalizability and preclude causal conclusions.

When compared to national healthcare data sources such as the National Health Interview Survey (NHIS) and the Behavior Risk Factor Surveillance System (BRFSS), our findings expand on previous work that explored health disparities by race or ethnicity [38,39] and highlight the prevalence of healthcare access challenges for disabled people [40,41]. Importantly, our study advances existing literature using national healthcare data sources by specifically exploring race-, gender-, sexuality-, and disability-based discrimination in healthcare settings and the relationships between healthcare-related discrimination and access to services.

Given our findings indicate experiencing any healthcare-related discrimination results in lower odds of having healthcare needs met, we can hypothesize that these disparities exist, in part, due to discrimination people experience in healthcare settings. Previous research corroborates this hypothesis by providing evidence that many people experience racial-, ethnic-, and sex-based discrimination in healthcare settings [29]. Additionally, research indicates that increased experiences of discrimination are negatively correlated with utilization of hospital services and prescriptions [1,2,23,25,26,27,28]. This is especially true given our findings suggest that disability-based discrimination was the most reported form of discrimination experienced in healthcare systems, which is likely to contribute to worsened disability and healthcare outcomes more generally [42].

The compounded discrimination people with intersecting minority identities experience contributes to inequitable healthcare access and the quality of care received [21,22]. Specifically, research has demonstrated that disabled individuals who are also members of racial or ethnic minority groups encounter both disability-based and race-based discrimination, resulting in unique and compounded unmet healthcare needs related to preventative care, timely diagnosis, and quality treatment [22,41]. Disabled women also frequently report higher rates of discrimination related to both gender and disability, particularly in reproductive health services, which is heightened for Black disabled women [43,44]. Similarly, LGBTQIA2S+ disabled individuals are at increased risk of experiencing stigma and bias from healthcare providers, which can discourage them from seeking necessary care or prescriptions [25,26,27,28]. The compounded impact of these experiences fosters distrust in healthcare systems, delays in diagnosis and treatment, and inadequate access to preventive services [33,34]; this is true even within programs established to reduce negative healthcare outcomes for this population (e.g., safety-net organizations) [45,46,47]. While prior research has largely focused on racial and gender discrimination in healthcare, our study uniquely highlights the prevalence and impact of disability-based healthcare-related discrimination. In our sample, disability-based healthcare-related discrimination was the most commonly reported form, and it was consistently associated with unmet healthcare needs across multiple types of care. These findings extend existing literature by quantifying the distinct burden of disability-focused inequities and underscoring the need for interventions that address this often-overlooked source of healthcare disparity.

The analysis presented here only begins to unpack the ways multiple forms of discrimination compound or interact. However, understanding the impact of multiple marginalized identities is critical for addressing disparities and unmet healthcare needs. Efforts to improve access and equity must consider the layered nature of discrimination and its cumulative effects on health outcomes. Interventions should prioritize culturally competent, trauma-informed care that acknowledges and mitigates the ways intersecting forms of discrimination affect health-seeking behaviors and healthcare delivery. This can be done through tailored interventions that account for the nuanced needs of disabled individuals and other intersecting marginalized identities. Tailored interventions are interventions that reflect the specific needs and preferences of individuals within a certain culture [48,49]. Tailored interventions have been found to improve disease knowledge, health system access, clinical outcomes and overall quality and satisfaction [28,48,50]. Tailored interventions should be grounded in an in-depth understanding of how multiple forms of oppression shape healthcare needs and outcomes [50,51]. Tailored approaches must also address systemic inequities, including the implementation of policies and practices within healthcare institutions that explicitly challenge discrimination. In fact, evidence suggests that most tailored interventions fail to do this which is identified as a substantial weakness that needs to be ameliorated [52]. Strategies such as embedding disability navigators or case managers into healthcare systems to assist individuals in accessing care, or offering providers ongoing training on intersectional inequities, can help mitigate structural barriers [28,50,53,54,55]. Tailored interventions that directly address the specific needs of diverse populations and acknowledging/addressing the compounded discrimination people experience in healthcare systems can reduce unmet healthcare needs and improve health outcomes.

Our findings also underscore the need for policy-level changes to address systemic discrimination in healthcare. Strengthening existing disability rights legislation within healthcare systems may ensure more consistent accountability for discriminatory practices [56]. Further, policies that incentivize inclusive training for healthcare providers, such as requiring disability competency continuing education for licensure renewal, may help decrease discrimination in healthcare settings [56].

Limitations and Future Directions

This study has several limitations that should be considered when interpreting the findings. The NSHD data is not derived from a nationally representative sample, which limits the generalizability of the results to the broader population of disabled individuals in the US The sample is over-represented by white, college-educated adults. This over-representation may skew findings and reduce their applicability to diverse populations. While the tables provide informative subgroup data, some cell sizes (e.g., for Two-Spirit respondents) were very small. These findings should therefore be interpreted with caution, as small sample sizes limit the generalizability and stability of estimates for these groups. Additionally, participants were recruited primarily through disability-focused organizations, listservs, newsletters, conferences, and social media outreach, which may have preferentially reached individuals who are actively engaged in the disability community. As a result, the sample may underrepresent disabled individuals who are less connected to disability networks or who do not self-identify as disabled. And lastly, the data is exclusively self-reported, which introduces the potential for response bias related to recall inaccuracies, social desirability bias, and other subjective influences that may affect the accuracy and reliability of the data [57].

While the findings highlight important associations between discrimination and unmet healthcare needs, the cross-sectional nature of this data precludes causal inferences. Future longitudinal, experimental, and mixed-methods research studies are needed to establish causality and explore the mechanisms underlying these relationships. Additionally, quality improvement studies within would be beneficial to identify whether these interventions, or additional interventions, may be necessary to improve equity to access and quality healthcare for disabled people with intersecting minority identities.

5. Conclusions

Although our findings should be interpreted with caution given the study’s non-representative sample and cross-sectional approach, our findings support previous research that has found disabled adults continue to experience unmet healthcare needs. In alignment with intersectionality theory, disabled individuals with additional marginalized identities measured in the NSHD experienced greater race-, gender-, sexuality, and disability-based discrimination from their healthcare provider dependent on their specific identities. Tailoring interventions to consider these experiences and address individual and structural discrimination by these identities has the potential to reduce unmet healthcare needs.