Interpreting and Addressing Racialized Inequities in Rheumatic Disease Care and Outcomes

Introduction

Health inequities, according to the World Health Organization, are “differences in health status or in the distribution of health resources between different population groups, arising from the social conditions in which people are born, grow, live, work, and age.”¹ Numerous published studies to date among individuals with rheumatic and musculoskeletal conditions demonstrate profound and persistent inequities in care and outcomes by race and ethnicity. Among individuals with systemic lupus erythematosus (SLE), studies consistently show that individuals of African descent receive poorer quality care- from inadequate treatment regimens to inconsistent access to care, to fragmented care utilization patterns – and have more damage accrual, adverse outcomes, and higher mortality.^2–6 In osteoarthritis, studies demonstrate racial disparities in receipt of joint arthroplasty and of recommended treatments like physical therapy, more severe disease at the time of presentation, and poorer outcomes.^7,8 While there are fewer published studies examining these factors in rheumatoid arthritis, racialized inequities have been observed in receipt of disease-modifying anti-rheumatic drugs, in disease activity, and in access to rheumatologists.^9–11 A recent study by Sowa et al. has similarly demonstrated significant racialized inequities in knee arthroplasty receipt among individuals cared for in the U.S. Military Health System.¹² Key challenges in rheumatology, and across all fields of medicine, include defining what race does and does not represent, understanding the mechanisms that drive these persistent racialized inequities, and developing sustainable, measurable interventions that close these gaps.

Defining Race and Ethnicity

Race and ethnicity are social constructs whose categories have changed over time based on geographic, cultural, and sociopolitical shifts.¹³ In general, race arbitrarily divides people based on ancestral origin and physical characteristics (e.g., skin color), whereas ethnicity captures shared values, language, and cultural norms among a group of people.¹³ Ethnicity is distinct from race; the two should not be conflated, as it risks minimizing other forms of discrimination such as xenophobia, colorism, and religious oppression.¹⁴ According to Bailey et al., “the modern concept of race emerged” in the U.S. as “early European settlers sought to preserve an economy” founded on exploiting the land and labor of Indigenous people and sustained by enslaving African people.^15–17 In the making of the U.S., the colonists created a racial hierarchy, based on the unfounded premise that Black and Native American individuals were inferior, to justify the subordination and oppression of these groups.^16–18 After slavery, state and federal governments continued to perpetuate racial domination through Jim Crow laws, racial residential segregation, and mass incarceration, among others, to maintain political, social, economic, and ideological power among White people.^19–21 Institutionalizing racial domination created lasting racial inequities across multiple domains, in which discriminatory practices in one sector reinforce discriminatory practices in the other.²² One example is the War on Drugs and tough-on-crime policies of the 1970s-80s, which disproportionately targeted Black individuals for policing and incarceration.²³ Subsequent association of Black Americans with “criminality” then limited access to employment, housing, public benefits, and education, with lasting impacts across generations.²⁴

In March 2024, the Editors of the Journal of the American Medical Association (JAMA) affirmed their support for the recommendation made by the March 2023 National Academies of Science, Engineering, and Medicine consensus report encouraging “a tectonic shift away from the use of race, ethnicity and geographic origin as proxies for genetic ancestry groups.”^25,26 While these recommendations were focused on genetics and genomics research, the Editors encouraged applications to other fields of research to prevent the perpetuation of biased assumptions that conflate self-identified race and ethnicity with genetic ancestry.²⁵ They specifically emphasized the importance of utilizing clear descriptors that reflect what was measured (i.e., self-identified race and ethnicity as social constructs vs. genetic ancestry), the rationale for the measurement, and how the categorizations influenced the analyses and interpretation of findings.²⁵ An editorial by Duncan and Montoya-Williams in JAMA Pediatrics further highlighted the importance of considering the multitude of intersecting social determinants of health for which race may be a proxy, including but not limited to socioenvironmental exposures, systemic, structural, institutional, interpersonal and internalized racism, and trauma exposures, as well as factors such as ancestral migration patterns when conducting health equity research.²⁷

Defining Racism

Systemic, structural, and institutional racism impact racialized health inequities and are often used interchangeably, yet have nuanced differences.²⁸ Systemic racism refers to the systems in their entirety – for example, political, legal, healthcare, education – that perpetuate unjust treatment of racially minoritized groups.²⁹ Structural racism refers to the structures – for example, policies, laws, institutional practices, deep-rooted norms developed and perpetuated by these systems – that “reinforce discriminatory beliefs, values, and distribution of resources.”^15,30 Institutional racism refers to the institutions – for example, courts, schools, hospitals – that foster and legitimize racial discrimination.³¹ For brevity, we will hereafter refer to racism at the institutional, systemic, and structural level as structural racism. Downstream, racism also manifests interpersonally, through “acts of commission and omission,” intentional or unintentional, that serve to maintain structural barriers.³¹ These structures also contribute to internalized racism, or the acceptance by racially minoritized individuals of negative messaging about their abilities or worth.³¹

Racial inequities in rheumatic disease care and outcomes, and across all fields of medicine, stem from structural racism. Centuries of state-sanctioned, harmful policies – colonialism, slavery, segregation, allowing racial terror, withholding wealth-building resources for homeownership, and more – resulted in the unequal distribution of health-supporting resources, largely along racial and ethnic lines.^32,33 Although structural racism is a root cause of inequities in social determinants of health and in health outcomes, its role in producing these inequities is infrequently measured or studied in rheumatology.^34,35

Frameworks to Study Racialized Health Inequities

Applying existing frameworks can shed light on potential mechanisms by which the observed racial inequities in care and outcomes in rheumatic conditions may occur. The National Institute on Minority Health and Health Disparities (NIMHD) framework conceptualizes determinants of health inequities across five domains (biological, behavioral, physical and built environment, sociocultural environment, healthcare system) and four levels (individual, interpersonal, community, societal) of influence on health.³⁶ The combination of these dimensions produces 20 distinct determinants that may be studied or targeted for intervention. This framework includes discrimination, at the individual level (response to this treatment), at the interpersonal level, and at the local and the societal structural levels. The NIMHD framework emphasizes that conducting research entirely on one determinant may be insufficient and allows researchers to consider the compounding and interdependent impacts of multiple determinants on health inequity.³⁷ Leveraging this framework to study rheumatic conditions may help ensure that critical variables at multiple levels and domains of influence are collected and thoughtfully included in statistical models, or targeted in interventions, to better understand and address known inequities. A variation of this model has been proposed to frame health equity research in SLE.³⁸

The 2010 World Health Organization (WHO) Conceptual Social Determinants of Health (SDOH) Framework also demonstrates ways in which multilevel factors can be considered mechanistically to understand inequities in rheumatic conditions. This model categorizes SDOH into “structural determinants,” which include socioeconomic status and sociopolitical context, as well as socioeconomic position and “intermediary determinants,” which include the living and working conditions of people.³⁹ The WHO framework highlights various pathways and levels through which upstream, structural mechanisms may operate to shape health outcomes. The categorization of SDOH into “structural” and “intermediary” determinants emphasizes the “causal priority of structural factors” to investigate in health equity research.³⁹ In this framework, race and ethnicity, and specifically racism are considered structural determinants, which intersect with other determinants (e.g., measures of socioeconomic position).³⁹ This has been applied to the study of inequities related to the material circumstances of economic insecurities among individuals with SLE to facilitate understanding of a mechanism by which social risk factors may impact patient reported outcomes.⁴⁰ This conceptual framework allows one to consider how structural and intermediary determinants may be modeled simultaneously to understand pathways resulting in inequities.

In February 2024, the WHO released a new document entitled “Operational framework for monitoring social determinants of health, ”⁴¹ which includes both metrics to monitor what they term as “social determinants of health equity” and “areas and actions for implementation.” This framework includes two components: 1) a set of indicators to standardize the global monitoring of social determinants of health pertaining to economic security and equality, education, physical environment, social and community context, health behaviors and healthcare, and 2) considerations for action regarding monitoring and addressing inequities that result from these factors.⁴¹ The document includes globally relevant indicators, specific recommendations regarding how to obtain and operationalize these variables, and strategies to analyze, report, monitor and collaborate across different sectors, which will be an important resource for global health equity research. Specifically, the authors incorporate a recommendation to disaggregate both SDOH data and action measures by “equity stratifiers,” such as income, gender, race, and ethnicity, to prioritize, monitor, and address inequities, track progress and promote accountability.⁴¹

Ecosocial theory, as developed by social epidemiologist Dr. Krieger, provides another strategy to consider the multilevel influences and pathways by which discrimination at the structural and individual level influence health.⁴² This theory’s core construct is embodiment, whereby “we literally incorporate, biologically, in societal and ecological context, the material and social world in which we live.”⁴² There are multiple intersecting pathways of embodiment, including but not limited to adverse exposures (e.g., to economic deprivation, to toxins), insufficient or poor healthcare, and experiences of trauma (e.g., discrimination) that occur over a life course and shape population-level racialized inequities.⁴² Application of this theory allows one to consider the role structural determinants and SDOH play in shaping racialized inequities in rheumatic conditions that have previously been attributed to biological differences alone.

Rheumatology Health Equity Research in Practice

Rather than including race and ethnicity as proxies for one’s experiences of racism, researchers may instead consider systemic historical and contemporary factors and their interplay with downstream factors, building upon these conceptual frameworks to study racialized inequities in rheumatic disease care and outcomes.²⁷ These structural factors can be operationalized in different ways. Previous work has measured structural racism by examining the many domains through which it operates.^32,43 These domains (e.g., housing, employment, education, criminal justice, etc.) largely encompass the structural determinants outlined in previous examples of conceptual frameworks. Variables to quantify these domains can be collected from various readily available federal, state, and census tract data sources and linked to individual-level geocoded addresses. In addition to operationalizing different domains, incorporation of area-level composite measures may be important components of a multilevel analysis of inequities. Examples include the Area Deprivation Index (ADI),⁴⁴ Social Vulnerability Index (SVI),⁴⁵ Child Opportunity Index,⁴⁶ and Index of Concentration at the Extremes.^47,48 A recent publication presents the Structural Racism Effect Index, which compiles information across multiple domains to capture the effect of “mutually reinforcing inequitable systems” described by Bailey and colleagues.^15,32 This race-neutral composite measure includes variables from the American Community Survey and other federal data for built environment, criminal justice, education, employment, housing, income and poverty, social cohesion and transportation. The Structural Racism Effect Index was found to be better correlated with life expectancy and poor mental and physical health compared to the ADI and SVI.³² Other studies may choose to disaggregate structural factor variables depending on their hypothesized mechanisms and pathways. Intentional decisions should be made based on the study question as to whether variables for race and ethnicity should be included in composite metrics or analyses.⁴³

Applicability to the Article by Sowa et al.

The recently published article, “Racialized Inequities in Knee Arthroplasty Receipt After Osteoarthritis Diagnosis in the U.S. Military Health System,” offers a case example to consider how researchers may define, measure, and interpret racialized inequities. Dr. Sowa and colleagues aimed to study inequities in receipt of knee arthroplasty by race and ethnicity within three years of osteoarthritis diagnosis. Their premise was that any inequities observed, after accounting for other modalities used for treatment including physical therapy and medications, would be representative of racism as there are no biologically based reasons for differences that may be observed. They framed this study by highlighting three levels of racism – systemic and structural, institutional, and personally-mediated. They described their primary predictor (or exposure), as racialized care inequities, for which race would serve as a proxy, and their proposed mechanism was that through these varying pathways of racism, they would observe inequities in arthroplasty by race. The authors were clear in their manuscript about what race did and did not represent, which set the stage for the analyses conducted.

In their methodologically rigorous analyses, the authors did in fact find significant racialized inequities in receipt of knee arthroplasty. White patients were most likely to receive a knee arthroplasty, followed by Asian and Pacific Islander, then Black and Latinx patients. Moreover, Black and Latinx patients were more likely to have bilateral osteoarthritis at the time of diagnosis. The authors also found fewer physical therapy sessions and lower likelihood of receiving a non-opioid prescription among White individuals compared to other racial/ethnic groups. In adjusted model, there were significantly lower rates of knee arthroplasty among Asian and Pacific Islander, Black and Latinx patients compared with White patients.

The challenge the authors faced was that they lacked specific measures of any of the levels of racism that they highlighted as potential root causes for the racialized inequities observed, or of any other factor for which race may serve as a proxy. The authors stated that race served as a proxy for racism, but without these measures, the specific mechanisms that would have been pathways for future targeted interventions, could not be studied. For example, at the societal or structural level, there were no measures available for the neighborhoods where the patients lived, to account for the role of factors like racialized economic segregation that may have resulted from historical redlining policies, on care utilization. At the institutional level, there was no ordering or referral pathway, institutional policy, scheduling system, or patient access measure that would have allowed for a quasi-experimental design comparing potential racialized inequities prior to and following implementation to target for future intervention. At the individual and interpersonal level, there were no patient-level measures of experiences of discrimination that may have impacted patient healthcare access patterns and decisions, or measures of provider implicit bias or explicit racism that may have contributed to the care provided. Measures of other factors that may have contributed to the associations observed, like disproportionate racialized burden of social risk factors like financial insecurity, which go hand in hand with the levels of racism described, were also not available.

Studying and Addressing Mechanisms of Racial Inequities

Sowa et al. continued an important conversation by demonstrating that there are racialized inequities in receipt of arthroplasty within the U.S. Military Health System that are like those previously shown in other health systems, and that are not explainable by biology. The critical next step is to try to disentangle the multilevel mechanisms that drive these inequities. A paper by Howe et al. guides us in the building of causal diagrams to facilitate the exploration of different, potentially intervenable pathways by which these inequities may be occurring.⁴⁹ Here, Howe et al. propose outlining “mechanisms of racism as health determinants operating at multiple levels,” including relevant examples of structural and institutional racism, alongside “downstream biological determinants.”⁴⁹ These causal diagrams allow for a clearer understanding of race as a socially constructed variable, the pathways by which racism may be operating, and the health behaviors, care inequities and adverse outcomes that may result.⁴⁹ This can guide decisions regarding the populations being studied, the variables that should be explicitly measured and those that are unmeasured, and the types of statistical models and confounding adjustments that should be employed to account for potential biases.⁴⁹

Another approach is to pivot and state that we have enough data that demonstrate racialized inequities and to instead, design and test interventions that are multilevel and that cross several hypothesized mechanisms, acknowledging that any one pathway may be insufficient to fully explain all the inequities observed, as noted in the NIMHD framework. Multilevel interventions can begin to address and assess the complex interplay between multiple levels of influence (e.g., interpersonal, organizational, community, educational, occupational, environmental, policy) on health.^50,51 Because several structural determinants of health often compound into inequitable outcomes, multilevel interventions have the potential to produce far-reaching, long-lasting results.^50,52 Moving directly to a multilevel, multifaceted intervention without a foundational mechanistic study is certainly justifiable given the overwhelming evidence of ongoing racialized inequities. However, the sustainability of these complex interventions is important to consider, and it may be challenging to tease apart the most influential aspect without understanding the contribution of different mechanistic pathways. Causal diagrams like those proposed by Howe et al. can facilitate exploration of the impact of hypothetical interventions and the pathways by which they may operate.

Recommendations for Studying Racialized Inequities in Rheumatology

This study by Sowa et al. highlights the importance of clear definitions for race and ethnicity, hypothesized pathways to guide a study on racialized inequities, and measurable variables to facilitate comprehensive, mechanistic analyses with potentially actionable results. In their editorial, Duncan and Montoya-Williams emphasized the importance of considering the factors that lead to racial inequities, with clear justification provided for including race and ethnicity as variables, a conceptual framework to guide analyses, and interpretation that recognizes the systemic factors that contributed to the inequities observed.²⁷ Our proposal draws upon Duncan and Montoya-Williams’ important commentary and Howe et al.’s causal diagram recommendations.^27,49 Before engaging in a study in rheumatic conditions that investigates racial and ethnic inequities, we propose several questions for consideration:

1. Is there an existing conceptual framework that can be leveraged or expanded upon to guide the study question and the proposed analyses?

2. What are the multilevel factors and hypothesized mechanisms driving the anticipated inequities by race and/or ethnicity, and how will these be measured?

3. What does race and/or ethnicity represent in the proposed study?³⁸ Does the study question justify the inclusion of these variables?

4. How were race and ethnicity variables collected, defined, and categorized? Is the study population racially and ethnically diverse? How will missing data related to these variables be addressed?²⁷

5. Are the multilevel variables necessary to tease apart potential mechanisms behind these inequities (e.g., structural factors, social determinants of health, measures of racism), available for inclusion in the study?

6. What are the hypothesized relationships between the variables (e.g., the primary exposure, demographic factors, social determinants of health, health-related variables)? What is the proposed directionality between these variables? How will the statistical models test potential associations while appropriately accounting for potential biases?

7. Can intersectionality between race, ethnicity, age and/or gender, for example, be examined using the data available and the statistical models proposed?

8. How will the findings of this study elucidate understudied mechanisms and/or reveal a potential target for a future testable, multilevel intervention?

Conclusion

As our field of rheumatology works towards eliminating the racialized inequities in care and outcomes that persist across rheumatic conditions, we need to be clear and intentional about how we define and interpret race and ethnicity in our research. We need to apply conceptual models that demonstrate the intersecting, multilayered influences from the structural to the individual level. We need to rigorously collect relevant variables for inclusion in our models that will allow us to interpret mechanisms driving these inequities and targets for future interventions. The persistent racialized inequities in rheumatic disease care and outcomes are both unacceptable and remediable. They represent the harms caused by centuries of racist policies that built inequitable systems that continue to perpetuate and maintain a racial hierarchy today. We need to bring rigorous methods, thoughtful interpretations, and multilevel interventions grounded in anti-racist praxis to close these gaps and work toward redressing past injustices.