Frontiers in measuring structural racism and its health effects

1. INTRODUCTION

A vast body research has documented the breadth and depth of racial inequalities in health. Studies consistently show, for example, that Black people are less healthy and live shorter lives than their White counterparts. ¹ , ² Fortunately, the field has largely moved beyond discredited biological and cultural deficit explanations for racial health disparities. ³ , ⁴ Studies over the last several decades on mechanisms underlying racial inequalities in health have provided foundational knowledge about the roles of individual‐level social determinants of health such as socioeconomic resources and exposure to directly perceived interpersonal discrimination. ⁴ , ⁵ Yet, it has become increasingly clear that focusing solely on individual‐level factors leads to an incomplete understanding of the root causes of racial inequities in health.

In recent years, there has been a growing recognition that the fundamental cause of health inequities along racial lines is structural racism, which involves systemic racial exclusion from power, resources, opportunities, and well‐being that is embedded in societal institutions. ⁶ , ⁷ Prominent theories highlight how structural racism harms the health of racially minoritized populations through “pathways of embodiment” such as unequal exposure to risks (e.g., social stressors, toxic living conditions, low control, stigma, and relative deprivation) and unequal access to material and psychosocial resources (e.g., social and economic capital, freedom, autonomy, power, and prestige). ⁵ , ⁸ , ⁹ Many theoretically oriented studies have provided important conceptual understandings about the role of structural racism in undermining the health of racially minoritized populations. ¹⁰ , ¹¹ , ¹² However, relative to advances in conceptual understandings, empirical studies on the topic are lagging behind: less than 1% of studies on the links between race and health have empirically measured structural racism, and its effects on health. ¹³ Health equity scholars have an opportunity to gain empirical traction by developing robust, theory‐informed approaches to measuring structural racism and its effects on health. ¹⁴

In this commentary, we aim to advance research on health equity by providing an ambitious roadmap for research priorities related to using innovative data and analytic approaches to study the impact of structural racism on health. By incorporating valid measures of structural racism in health research, we can move the field forward in several important respects, including: (a) addressing new, salient questions about the fundamental drivers of racialized health inequities, (b) employing rigorous research designs, and (c) building a knowledge base to inform efficacious racial equity solutions. To illustrate the utility of innovative methodological approaches for understanding the health consequences of structural racism, we highlight novel methods and insights from an article by Chantarat, Van Ripper, and Hardeman ¹⁵ in this issue of Health Services Research Journal (HSR) on “Multidimensional Structural Racism Predicts Birth Outcomes for Black and White Minnesotans” as well as an emerging corpus of research on related topics. We conclude with a summary of strategies for improving the measurement of structural racism, and a call for catalyzing research on structural racism's health consequences by lowering barriers to doing this type of research through building a publicly available data infrastructure on measures of structural racism.

2. ADVANCING HEALTH EQUITY RESEARCH THROUGH INNOVATIVE MEASURES OF STRUCTURAL RACISM

Using theory‐informed approaches to measure structural racism, the study by Chantarat and colleagues makes several important contributions to the literature on the health consequences of racism. First, Chantarat et al. shift the focus from documenting racial health disparities and exploring how proximate, individual‐level social determinants mediate disparities, to empirically investigating the distal, structural contexts at the root of racialized inequities in health (birth outcomes). In doing so, the study adds to a nascent body of quantitative research on the topic and provides a template for future research.

Second, consistent with structural theories highlighting how structural racism is multi‐sectoral and systemic, ¹⁰ , ¹⁶ , ¹⁷ the Chantarat et al. study utilizes Public Use Microdata Area (PUMA)‐level measures of structural racism within housing, education, economic, and judicial contexts. In contrast, the vast majority of prior empirical studies on links between structural racism and health have focused on single domain of structural racism (e.g., residential segregation or Black‐White areal inequalities in education) or examined how a small set of structural racism domains affect health independently—approaches that provide an incomplete picture of structural racism and its health consequences. Barbara Reskin underscores this point, noting that the “unit of analysis from a systems perspective is not individual subsystems but rather the entire system—the forests rather than the trees.” ^{17 (p18)} While taking a comprehensive measurement approach remains exceedingly rare, a growing chorus of scholars are pointing to the importance of operationalizing structural racism measures in ways that capture the broad, systemic nature of structural racism for understanding how it operates and affects population health. ¹⁰ , ¹⁴ , ¹⁸ , ¹⁹ , ²⁰

A third way in which the Chantarat study contributes to the literature is by using advanced analytic techniques that align with theoretical understandings of structural racism as a complex system that is often “hidden” or not directly observed. Specifically, they use a latent measure of structural racism, which is well‐suited for capturing phenomena that are difficult to directly measure. A handful of recent studies have adopted a latent variable approach because, relative to traditional approaches that rely on observed measures, they minimize measurement error and biases in estimating the impact of structural racism on health. ¹⁴ , ²¹ , ²² To answer questions about how structural forms of racism across different spheres cluster and shape health, the Chantarat et al. study uses a special case of latent variable methods—that is, a latent class approach. By using model‐based statistical fit criteria to identify three distinct typologies (or latent classes) of structural racism, findings show how structural racism across housing, education, economic, and judicial domains co‐occur or cluster within geographic areas. Further research is needed to assess the utility of using various types of latent measures structural racism for studying racialized health inequities.

The final contribution of the Chantarat et al. study is a thoughtful discussion about how their findings regarding the multi‐sectoral, systemic nature of structural racism have policy implications. They note that, because structural racism involves multifaceted and interconnected domains of oppression, interventions aimed at addressing racism in a single domain will do little to disrupt the broad‐based and complex system of structural racism and the impact it has on population health. This aligns with a growing recognition that complex systems thinking and multi‐sectoral interventions are necessary for creating efficacious policy solutions to dismantle structural racism and achieve health equity. ⁵ , ¹⁰ , ²³

Despite a great deal of theorizing about structural racism and its consequences for population health, as well as emerging empirical studies on the topic, there are still critical gaps in our knowledge. Below we highlight unanswered, salient questions about structural racism and its effect on health. We also provide examples of how to answer these questions using innovative data and methodological strategies.

2.1. How is health shaped by discriminatory policy contexts?

In order to achieve health equity, studies should directly measure how structural racism embedded in policies affects population health. While a large body of research shows that policy contexts matter for health, ²⁴ , ²⁵ relatively little is known about how and why policies undergirding structural racism compromise the health of minoritized groups. Nonetheless, several recent studies provide examples of novel strategies to understand how racially discriminatory policy contexts undermine population health. For example, research suggests that place‐based legacies of historical racial violence such as slavery and Jim Crow laws harm contemporary health among Black Americans. ²⁶ , ²⁷ In addition, several recent studies examine more than a dozen immigration‐focused measures to create indices of immigration policy contexts, and estimate their health effects. Findings show that greater degrees of racism and xenophobia characterized by more exclusionary policy contexts at the state level are predictive of worse health among Latinx populations. ²⁸ , ²⁹ It would also be useful to examine the extent to which health is shaped by recent discriminatory policies aimed at banning the teaching of Critical Race Theory and disenfranchising Black voters. ⁶ , ³⁰ Notably, a recent study by Agénor and colleagues provides a publicly available database on 843 racism‐related laws spanning 10 legal domains. ³¹ These and other similar data can serve as important resources for health equity research.

2.2. To what extent do cultural racism and racist ideologies harm health?

In addition to institutional and legal aspects of racism, cultural and ideological forms of racism are also likely to contribute to racialized health inequities. ³² , ³³ Indeed, findings from a handful of recent studies are suggestive of the deleterious consequences of cultural and ideological racism. For example, research has shown that poor health among Black people is linked to exposure to environments with greater degrees of anti‐Black ideologies, sentiments, and practices. ⁹ , ³² , ³⁴ , ³⁵ Examples of measures of anti‐Blackness from the literature include areal variation in explicit and implicit biases, racial resentment, rates of N‐word searches on Google, rates of police‐involved deaths of Black people, and number of hate groups (per capita). ³⁴ , ³⁵ , ³⁶ , ³⁷ Furthermore, using emerging computational methods will provide opportunities to scrape social media websites and other internet sources to capture novel, online racist content. Future research should use these measurement strategies to address a range of critical questions, such as: Which aspects of anti‐Black cultural frames and ideologies are most deleterious? What are the relationships among institutional, legal and cultural/ideological forms of racism, and what are their relative and collective effects on population health?

2.3. What can we learn about health equity by measuring structural racism across multiple spatial scales?

Both theoretical and empirical researches suggest that structural racism operates on multiple spatial scales or levels. ⁸ , ¹⁹ , ³⁸ , ³⁹ For example, quantitative studies have measured structural racism across a range of geographic levels, from census tracts, to PUMAs, to counties, to designated market areas, to states. ²¹ , ³⁴ , ⁴⁰ , ⁴¹ , ⁴² Although a plethora of studies point to structural racism being a multilevel phenomenon, health equity research on racism often only examines a single level. As a result, many critical questions remain unanswered, including: How is structural racism linked across different levels? What is the relative contribution of structural racism across different levels to racial inequities? Do the different levels of structural racism operate in a synergistic fashion to shape population health? How do we leverage policies at different levels to eliminate health inequities? Research that examines the health effects of structural racism at multiple levels—and their linkages—is essential for a better understanding of the role of place as a racialized social determinant of health.

2.4. What is the geography of racism and how is it linked to health?

While a robust literature shows that race and place are intertwined ³⁹ , ⁴³ , ⁴⁴ and that place matters for health, ²⁴ , ⁴⁵ we know surprisingly little about the geography of structural racism and its relationship to health. Several population health studies have used color‐coded maps illustrating substantial variation in area racism as measured by racial inequalities, Jim Crow policies, and racist attitudes. ²⁷ , ³⁴ However, this literature has tended to use different measures and spatial scales; we lack a comprehensive picture of the geography of racism across the country. Where is racism especially high? Does the geography of racism differ across societal domains? Addressing these types of questions through “countermapping” projects—that is, using geocoded data to better understand the spatial distribution of racialized power and inequities ⁴⁶ , ⁴⁷ —is essential for understanding the place‐based experiences of racism and their health consequences. Future research should integrate insights across fields (especially critical geography, social sciences, and population health) for creating comprehensive heat maps of structural racism that can be useful tools for examining how the geography of structural racism affects health.

2.5. Can we improve our understanding of the effects of structural racism by incorporating temporality?

Most research on the relationship between structural racism and health has used cross‐sectional data, which provides a useful snapshot at a specific point in time but does not elucidate how these processes unfold over time. Notably, life course research underscores the importance of timing for understanding the role of social determinants of health, such as structural racism. ¹⁹ , ⁴⁸ , ⁴⁹ , ⁵⁰ The lack of attention to temporal aspects of structural racism has left important gaps in our understanding of its role in shaping health. Are the health effects of structural racism contingent upon life stage? Does duration of exposure to structural racism matter for health? Does exposure to structural racism have a lagged effect on health? To what extent do changes in structural racism exposure lead to changes in health? To address these and other life course questions about the health consequences of structural racism, future research should use longitudinal data to investigate the role of temporality.

2.6. How can we utilize measures of intersecting forms of oppression to study health?

Structural racism does not operate in a vacuum. Instead, it is part of a matrix of domination. ⁵¹ Structural racism, sexism, heterosexism, cissexism, xenophobia, ageism, ableism, and many other forms of oppression combine to shape individuals' health and life chances. ⁵² , ⁵³ , ⁵⁴ , ⁵⁵ By combining structural measurements and intersectional perspectives, scholars can use a structural intersectionality approach to expand scientific knowledge of how structural racism affects health. ²⁰ A structural intersectionality approach to studying racism can help answer a number of pressing questions such as: how does structural racism relate to other forms of oppression such as structural sexism, ⁵⁶ and in a given social context and how do these structural injustices jointly shape health? How do racism and other intersecting forms of structural oppression differentially affect the health of population subgroups defined by specific constellations of statuses such as race, gender, class, and sexuality? One example of a structural intersectionality approach is Pirtle and Wright's concept of “structural gendered racism.” ⁵⁷ Structural intersectionality approaches such as this represent an important opportunity for advancing future health equity research.

3. CONCLUSION: A ROADMAP FOR MEASURING STRUCTURAL RACISM AND ITS HEALTH EFFECTS

While prominent theoretical frameworks on racialized health inequities underscore the central role played by structural racism, empirical measurement of structural racism in population health research is lagging behind its conceptualization in the literature. Scholars have noted that challenges in measuring structural racism in society are one of the reasons that there are relatively few empirical studies on its health effects. ¹⁹ , ⁵⁸ Scant empirical research on the topic has left critical gaps in our understanding of the inequitable distribution of health between and among racialized groups.

This commentary provides a roadmap for research to address critical questions about the links between structural racism and health by utilizing innovative measurement approaches. We spotlight novel methods used by Chantarat et al. ¹⁵ and a nascent body of research to demonstrate the utility of innovative data and analytic strategies for understanding the health consequences of structural racism. We also highlight key questions to be addressed and provide suggestions for how to address them by incorporating several novel measurement approaches, including: latent variable measurement strategies, discriminatory policy contexts, racist ideologies, multilevel measurement, and mapping geographic variation in structural racism, temporality, and intersecting forms of structural oppression. There is no single optimum approach to measuring structural racism; instead, each of these (and many yet to be created) can make important contributions to knowledge when implemented in theoretically driven ways.

Moving forward, we should lower barriers to doing this type of research by building a publicly available, user‐friendly data infrastructure for measures of structural racism. Doing so will catalyze research on the health effects of structural racism. The innovation in and dissemination of structural racism measures will drive scientific progress in the field and not only allow us to address salient new questions about the fundamental causes of racialized health disparities but will also create an invaluable knowledge base that can serve as a foundation for racial equity policy solutions.

CONFLICTS OF INTEREST

Authors have no conflicts of interest.

Brown TH, Homan PA. Frontiers in measuring structural racism and its health effects. Health Serv Res. 2022;57(3):443‐447. doi: 10.1111/1475-6773.13978