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• Published: 02 January 2024

The impact of intersectional racial and gender biases on minority female leadership over two centuries

• Ganna Pogrebna 1 , 2 , 3 ,
• Spyros Angelopoulos 4 ,
• Immaculate Motsi-Omoijiade 1 , 5 ,
• Alexander Kharlamov 6 &
• Nataliya Tkachenko 7  

Scientific Reports volume  14 , Article number:  111 ( 2024 ) Cite this article

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• Human behaviour
• Social evolution

This study scrutinizes the enduring effects of racial and gender biases that contribute to the consistent underrepresentation of minority women in leadership roles within American private, public, and third sector organizations. We adopt a behavioural data science approach, merging psychological schema theory with sociological intersectionality theory, to evaluate the enduring implications of these biases on female leadership development using mixed methods including machine learning and econometric analysis. Our examination is concentrated on Black female leaders, employing an extensive analysis of leadership rhetoric data spanning 200 years across the aforementioned sectors. We shed light on the continued scarcity of minority female representation in leadership roles, highlighting the role of intersectionality dynamics. Despite Black female leaders frequently embracing higher risks to counter intersectional invisibility compared to their White counterparts, their aspirations are not realized and problems not solved generation after generation, forcing Black female leaders to concentrate on the same issues for dozens and, sometimes, hundreds of years. Our findings suggest that the compound influence of racial and gender biases hinders the advancement of minority female leadership by perpetuating stereotypical behavioral schemas, leading to persistent discriminatory outcomes. We argue for the necessity of organizations to initiate a cultural transformation that fosters positive experiences for future generations of female leaders, recommending a shift in focus from improving outcomes for specific groups to creating an inclusive leadership culture.

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Introduction.

Despite rising awareness of female minority leadership due to notable diversity gaps 1 and its pivotal role in strategic management 2 , 3 , practical advancements lag behind theoretical progress 4 , 5 , sustaining the underrepresentation of Black female leaders as a vital concern 6 , 7 . The statistics reflect this disparity: in 2021, White women held 32.6% of managerial positions in the US, while Black women occupied only 4.3% of such positions 8 . Additionally, there is a lack of Black women CEOs in Fortune 500 companies. In 2023, women led 10.4% of the Fortune 500 companies. Yet, only two of them had Black (more specifically, African American) heritage 9 . Despite modest progress in the representation of women in senior leadership positions, Black women continue to face unique challenges, being promoted at a slower pace and significantly underrepresented in top leadership roles 10 . The underrepresentation of minority women in leadership positions has been shown to hinder organizational success, and minority individuals who have had leadership opportunities were found to be more productive and efficient in their roles than their majority counterparts 11 , 12 .

The exploration of leadership outcomes for racial majorities versus minorities in underrepresented groups has predominantly been approached through the lens of intersectionality theory 13 , 14 . This theory examines the combined effects of “racist and gendered stereotypes” on female minority leaders who face compounded discrimination due to their association with both an underrepresented gender group and a specific ethnic minority 15 . However, the lack of progress in female minority leadership can be partly attributed to the limitations of the intersectionality approach and its policy recommendations. One of these limitations is the difficulty in measuring and defining intersectional effects, as the narrative-based nature of intersectionality theory hinders consensus on standardized measurement approaches 13 . Additionally, the static nature of intersectional effects overlooks the dynamic and complex historical development of multifaceted identities, often treating race and gender as fixed constructs 16 . Consequently, the literature has primarily focused on the bicultural competencies or leadership styles of ethnic minority females, with empirical studies relying predominantly on qualitative data due to the challenge of quantifying intersectionality 14 , 17 , 18 . As a result, intersectional effects are often derived from relatively small data samples, limiting generalizability.

To address these gaps, there is a need for a quantitatively testable theory that captures the dynamic intersectional effects and their influence on the development of female minority leaders. In this study, we propose a new theoretical approach, grounded in the interdisciplinary field of behavioural data science, which considers the intersectional impact of racial and gender stereotyping over time. Our approach combines hypothesis-driven views from intersectionality theory and schema theory, along with a data-driven approach that allows for quantitative testing using machine learning, statistical, and econometric techniques. Building on past minority leadership frameworks 19 , 20 , 21 , our approach diverges from previous research. While earlier models viewed gender and race as static factors in shaping female minority leadership, we see them as dynamic elements, continuously influencing leaders’ experiences and actions over time.

Historically, in the annals of American history, Black women have faced multi-dimensional challenges due to the intersections of their race and gender. The concept of intersectionality 22 offers an analytical lens to understand the unique experiences Black women undergo, especially when they hold authoritative roles in organizations dominated by White individuals. These challenges are not merely the sum of racial and gender-based prejudices; they intertwine in a manner that shapes the distinct social realities of these women. The experiences of Black women cannot be neatly compartmentalized into separate spheres of race, gender, and social class 23 . Instead, these spheres overlap, painting a picture that traditional feminist discourse often overlooks 12 . This intersectional approach is vital, given the long history of Black women being positioned as outsiders within dominant organizational cultures, both in academia and business. As they climb the leadership ladder, they grapple with unique obstacles that stem from historical stereotypes and prejudices. The dual challenges of racism and sexism mean that their leadership journey often involves navigating a “double jeopardy”. This double bind of facing discrimination due to their racial identity and their gender identity underscores the resilience and determination of Black women leaders.

Women collectively face challenges like sexism and discrimination 24 . Yet, Black women also grapple with racism’s added burden. Their dual challenges, rooted in gender and race, amplify the hurdles they confront in leadership roles. Using an example of African-American ethnic minority, previous literature demonstrated that Black women’s unique disadvantage arises from the intersectionality of race and gender, deeply tied to historical events such as slavery 25 . They face persistent stereotypes due to a legacy of slavery and systemic biases 26 . The combined racial and gender bias often leads to their isolation in workplaces 27 .They encounter heightened expectations, compelling them to consistently excel in their fields in pursuit of acknowledgment 24 . Their journey in leadership underscores their tenacity and drive, as they uniquely overcome numerous challenges distinct from those, encountered by their counterparts 12 .

Our proposed approach focuses on the three stages of female minority leadership:

Identification Stage leaders possess certain intersectional priors, such as being female and belonging to an ethnic minority group. Based on these priors, family development context, individual characteristics, and knowledge of previous leaders with similar priors, each leader determines their risk tolerance and self-selects into a leadership role within specific fields.

Progression Stage leaders interact with the world, gain experiences, and update their behavioral schemas. Behavioral schemas help individuals process information from new experiences and adapt to change. Goals are set, and learning occurs through successes and failures. Rigidity in behavioral schemas persists when goals and priorities are not achieved, whereas schema updating occurs when goals are attained. During this stage, leaders gain recognition from followers within their respective fields.

Achievement Stage leaders gain societal recognition as prominent figures in leadership. Achievement is viewed as a direct outcome of the previous two stages.

By considering the intersectional effects of gender and race and understanding how they influence risk attitudes in the identification stage and modify behavioral schemas in the progression stage, we gain a dynamic perspective on the determinants of diversity gaps in female leadership. Although our theory can be applied to individual leaders and groups of leaders, our empirical focus is on groups of female leaders with different intersectional priors, specifically comparing Black female leaders with those from the White majority group. We collect demographic, background, and speech data for 757 female leaders spanning a time period from the 19th century to the end of 2019, of which 608 were American. The end of 2019 is chosen as a cut-off date to avoid potential COVID-19 bias in leadership speeches from 2020 onwards. All women in our sample are recognized by both the college of experts and by the general public as influential leaders in one or more fields, ensuring a similar level of high leadership achievement.

The remainder of this paper is structured as follows. In section " Methods " describes methods used to conduct this research, justifies our theoretical assumptions, formulates hypotheses, and highlights contributions of our research. In section " Justification of assumptions " presents results of the empirical test of our model. Finally, we conclude by discussing the general implications of our study.

Our basic conceptual model is based on the cross-disciplinary behavioural data science approach. Consider a 3-stage dynamic problem with the timeline depicted on Fig. 1 . The leader goes through 3 stages in her development: Identification, Progression, and Achievement.

The Structure of Conceptual Behavioural Data Science Model and Empirical Strategy. Note The figure demonstrate a 3-stage leadership model describing Identification, Progression, and Achievement stages of leader’s development. It also explains observable and latent constructs associated with each stage.

During the Identification stage, the “Nature” determines a set of priors, which it assigns to the future leader. The future leader considers the amount of risk she wants to take in her leadership career by deciding on the number of areas or fields she wants to enter. Since each entry is inherently costly, requiring the leader to take on multiple visible responsibilities, and, therefore, it is also risky: the higher is the number of entered fields, the higher is the risk tolerance capacity of the future leader. The number of entered fields is observable (e.g., it is easy to collect information on whether a particular leader decided to concentrate on one particular field such as law or decided to diversify into several fields by entering the field of law and, in parallel, engaging into activism and then politics). Yet, the decision to enter multiple fields may result from multiple factors such as suffering from the intersectional invisibility (i.e., being overlooked as a non-prototypical representative of a cultural group) due to gender and racial stereotyping 14 , as well as many latent factors such as individual psychological characteristics, family context, preferences, beliefs, developmental opportunities, etc. 20 , 21 . It also may be the case that the future leaders consider the experience of previous leaders with similar cultural characteristics (i.e., they may have role models from their cultural group), yet, the degree of knowledge or awareness about these experiences as well as the way in which future leaders perceive these experiences are unobservable. Nevertheless, all these constructs may impact a leader’s decision-making process, which is why it is important to account for these possible effects in our empirical analysis.

In the Progression stage, the leader engages into leadership activity in organizational context through translating her set of leadership priorities by verbalizing her behavioral schemas. These schemas help the leader to set goals for herself as well as her followers and update the schemas once the goals are achieved. The verbalized schemas are measurable by considering the topics, on which leaders concentrate in their rhetoric as well as the speed with which these topics change over time. Apart from the gender and racial stereotyping, the leaders may be affected by a number of individual and contextual observable as well unobservable factors, which we are accounting for in our empirical analysis by controlling for individual effects as well as time effects.

Finally, in the Achievement stage, the leader gains prominence and is accepted by the broader society (not just by her immediate following within her organization) as a leader. At this stage, the observable construct is usually success level, which may have different measures from specific variables (such as the level of corporate profit, shareholder value, return on investment, etc.). It may also be as simple as a binary variable (where success is assumed to be 1 and failure is depicted as 0) or continuous (where success is distributed between 0 and 1). Similarly to previous stages, a number of important latent effects need to be taken into account in the empirical analysis. In our empirical strategy (described below) we assume that all leaders in our dataset are equally successful (in other words, we keep the leadership success level constant and assume it to be equal to 1 as this assumption most appropriately reflects our dataset).

To give a specific example of Black female leader, Fannie Lou Hamer’s trajectory from a Mississippi sharecropper to a nationally recognized leader epitomizes the three-stage leadership model 28 . Initially, during the Identification stage, Hamer confronted racial injustices and risked her safety to register to vote, later diversifying into civil rights activism with the SNCC and CORE. In the Progression stage, her grassroots leadership style and impactful speeches, especially during the 1964 Democratic National Convention, illuminated the barriers faced by Black voters. Transitioning to the Achievement stage, Hamer shifted focus to economic disparities, co-founding the Freedom Farm Cooperative and advocating policies promoting Black economic upliftment, education, and health, solidifying her legacy in American civil rights history.

Considering the three stages described above, our basic behavioural data science model can be specified as follows. Consider an individual leader k , characterized by a set of cultural and socio-demographic priors. We concentrate on female leaders with different racial and ethnic backgrounds, hence, we assume that \(k\in \{i,j\}\) , i.e., \(k=i\) if the female leader identifies herself with an ethnic minority and \(k=j\) if she identifies herself with the ethnic majority. The leader’s success (achievement) is depicted by \(s_k^T\) , which depends on the leader’s risk tolerance capacity \(r_k^t\) as well as her behavioral schema updating measure \(\sigma _k\) , capturing the relative importance of a particular topic of focus for the leader over time. This measure can be defined in many ways, but we use the average standard deviation of probabilistic measure of importance of all topics in leadership rhetoric over \(N\) number of time periods (years) as specified in subsequent sections. In other words, \(\sigma _k = \frac{1}{\eta } \sqrt{\left( \sum _{\tau =t+1}^{T-1} \left( e_k^{\tau }-\mu \right) ^2 \right) /N}\) , where \(e_k^\tau\) is each probabilistic value of topic importance from the pool of important topics considered in leadership rhetoric, \(\mu\) is the pool mean, N is a number of time periods and \(\eta\) is the number of important topics, which represent verbalized behavioral schemas of the leaders. Therefore, the leadership success (achievement) is determined by a combination of a leader’s ability to take risk (i.e., given by her risk tolerance capacity) combined with her experiences (i.e., experientially informed and constantly updating behavioral schemas) and is given by: \(s_k^T=r_k^t+\sigma _k+\varepsilon\) where \(\varepsilon\) is a normally distributed noise parameter, which captures any possible stochastic shocks to the leadership trajectory.

In understanding the leadership journey of Black women, it is imperative to consider the intersectionality of race and gender. Black women often face a unique set of challenges and experiences as they navigate leadership roles. This intersectionality does not simply mean they experience the additive challenges of being Black and being a woman, but rather, they face specific issues arising from the combination of these identities. For example, they might encounter racialized sexism or gendered racism in their roles. In our study, we specifically delved into these unique challenges and how they shape the leadership styles, strategies, and decisions of Black women.

We recognize that there is a significant difference between being a Black woman leader and being a Black woman leader who actively advocates for Black issues. While all Black women leaders bring their lived experiences into their leadership, not all choose or have the opportunity to center their leadership around advocacy for Black issues. Our research methodology differentiates between these two categories, ensuring we capture a holistic understanding of Black women’s leadership. We have ensured that our study both recognizes the diversity within Black women leaders and understands the specific nuances of those who are advocates for Black issues.

Justification of assumptions

Concentration on gender and ethnicity.

Even though intersectional stereotyping in organizations may arise from multiple intersectional systems in the society (race, gender, socio-economic class, ability, age), we concentrate on the ethnic background and gender for several reasons. First, the impacts of gender and ethnic background are often overlooked compared to other combinations such as, e.g., gender and age, etc. As Crenshaw puts it using an example of Black female leaders, “Black women’s intersectional experiences of racism and sexism have been a central but forgotten dynamic in the unfolding of feminist and antiracist agendas...” 29 . Second, the effects of gender and race are difficult to measure due to the fact that, unlike many other factors, both gender and race involve self-attribution. Unlike other characteristics, that are easy to measure objectively (e.g., age), an individual needs to associate herself with women and with a particular minority group in order for intersectionality analysis to be valid. Yet, our unique dataset allows us to focus on leaders, who identify themselves as females and as representatives of a particular racial and ethnical background.

Stability of gender and ethnical background identification

Our model assumes that gender as well as racial and ethnical identification remain constant throughout all three stages of the leader’s development. In practice, this may not always be the case as gender, racial, and ethnical identification may change over time. For example, a particular leader with a mixed ethnical background, e.g., Austrian and Japanese, may first identify as an Austrian because she was raised by her family as an Austrian. Yet, later is life she may decide to identify herself as Japanese. The leader may also undergo a trans gender transition through her life, e.g., first being known as a man and later as a woman. Consider, for example, the Wachowskis—leaders in the film making and authors of the Matrix movies—who were first known as men and are currently known as trans women. These processes are rare and complex and, most importantly, their intersectional effects are not very well understood in the literature, which is why we concentrate on women leaders with stable gender, race, and ethnicity identification over time.

Separability of risk tolerance determination and experiences

Our model implies that the leader’s risk tolerance capacity determination and behavioral schemas updating occur in different stages of a leader’s development (i.e., are time-separable). Specifically, the leader first makes a decision about how many fields she wants to enter (determines her risk tolerance capacity) and then proceeds to having experiences in these fields, updating her view of the word (behavioral schemas) and verbalizing these schemas as they emerge and update. This, however, may not always be the case. For example, the leader may initially decide to enter only one field (e.g., law) and through her experiences then decide to later enter another field (e.g., politics). The time separability is not an important assumption for our model: in principle, the Identification and Progression stages can be happening at the same time as long as we acknowledge that leaders’ risk tolerance capacity determination and behavioral schemas as products of experiences are distinct components of the leader’s development. Considering risk tolerance updating as a part of behavioral schemas updating would be an interesting extension of our model, which does not consider how the updating is happening (i.e., in order to incorporate risk tolerance updating into a model one would first need to explain the exact mechanism of behavioral schemas updating, which is outside the scope of this paper). We discuss this as a limitation of our model in the concluding section of this paper and provide several suggestions about how the updating process could be modeled in the future studies. Nevertheless, recent evidence from studies on female leadership and female ethnical minority leadership supports the validity of the separability assumption. Using qualitative interviews, these studies find that women leaders often make decisions to have multiple roles, take on many responsibilities, and diversify their efforts across several fields prior to engaging in leadership experiences in order to tackle gender and racial discrimination or to become more visible 13 , 14 , 30 , 31 .

Empirical methodology and testable hypotheses

Even though our model could be applied to the individual leaders, we are particularly interested in racial and ethnic minority female leaders as a group. Instead of looking at the difference in leadership success (achievement) given leader’s characteristics, our empirical strategy is to hold the level of success constant and explore the differences between risk tolerance capacity and experiential behavioral schemas of majority and minority female leaders. We focus on women who all achieved societal endorsement in the sense that they became widely known and accepted by people within and outside their organizations and fields as leaders. For simplicity, if 0 would constitute the failure to achieve societal acceptance as a leader and 1 would constitute success, we assume that in our sample all female leaders achieved \(s_k^T = 1\) irrespective of their background. This means, that the success level of minority and majority leaders is the same, i.e., \(s_i^T=s_j^T\) . This implies that \(r_i^t + \sigma _i + \varepsilon = r_j^t + \sigma _j + \varepsilon\) or, considering that \(\varepsilon\) is normally distributed and does not depend on whether the leader is or is not a representative of the racial or ethnic minority: \(r_i^t+\sigma _i=r_j^t+\sigma _j\) . This allows us to formulate a number of testable hypotheses, as if \(\sigma _i<\sigma _j\) , \(r_i^t\) should be greater than \(r_j^t\) . Alternatively, if \(\sigma _i>\sigma _j\) , \(r_i^t\) should be lower than \(r_j^t\) . There is also a theoretical possibility that both risk tolerance capacity and experiences are the same for both majority and minority leaders, i.e. if \(\sigma _i=\sigma _j\) , then \(r_i=r_j\) . Since we observe that female minority leaders are disadvantaged compared to the female majority leaders 13 , we expect their leadership experiences to be a lot less positive than those of the female majority leaders, meaning that minority female leaders should update their behavioral schemas less often than majority female leaders. This implies that minority female leaders are forced to concentrate on the same priorities and verbalize the same behavioral schemas over multiple time periods, whereas majority female leaders are able to change their priorities often. Therefore, the standard deviation of the probabilistic measure of topic importance should be lower for the minority leaders than for the majority leaders. Hence, our first hypothesis could be formulated as follows.

Hypothesis 1

Verbalized behavioral schemas of minority female leaders should be less time-variant and less dispersed than those of the majority female leaders.

This means that we should observe that \(\sigma _i<\sigma _j\) , i.e., the mean standard deviation of the topic probabilities (measured by the topic modelling in the leadership rhetoric) should be lower for the minority compared with the majority group. If minority leaders generally have less positive leadership experiences, this means that they should be compensating for the lack of positive progress in achieving their goals by taking more risk and concentrating on more fields than their majority counterparts. A recent longitudinal study approached 59 Black females twice over the course of 7 years and found through a series of qualitative interviews that these women tackled career challenges associated with intersectional invisibility by what we describe as a more risk-taking behavior 14 . Specifically, these women took on more responsibilities and engaged in larger number of visible leadership roles to progress in their careers. Importantly, the interview evidence suggests that these women first made the decisions about the number of roles and responsibilities and then proceeded to their experiences. Another study focused on minority female leaders in Pakistan, the United Kingdom as well as Brazil, who revealed through a set of qualitative interviews that they needed to deliberately plan to take more responsibility and engage in more roles before they could proceed to having leadership experiences 32 . Further studies have confirmed that the necessity for higher risk taking becomes apparent from an early age as future minority leaders are encouraged to respond to more opportunities by their families 30 as well as opt for more visible and diverse set of responsibilities throughout the school year 31 . Therefore, our second hypothesis can be formulated as follows.

Hypothesis 2

Minority female leaders tend to take more risk with their leadership careers than their majority counterparts.

Considering the lack of improvement in female minority leadership over time, our model also allows us to formulate the third hypothesis:

Hypothesis 3

Since experiences improve for majority, but not for minority female leaders over time, minority leaders (as a group) should take progressively more risk than majority leaders.

Data mining and analysis

One of the main constructs in our behavioural data science model is the construct of a behavioral schema, which allows the leaders to comprehend, internalize, and understand their goals and priorities. These priorities need to be communicated to others and if they are achieved, the leader develops a new set of behavioral schemas, which, in turn, need to be communicated again. The extant psychological and leadership literature stresses the importance of effectively expressing and communicating behavioral schemas to others: leaders often verbalize schemas as strategic directions, values, and vision, to achieve development of organizations, and empowerment of followers 33 , 34 , 35 . Hence, leadership rhetoric is suggested as a good proxy to measure leaders’ dynamic behavioral schemas 36 , 37 , 38 , 39 . We concentrate on female leaders’ rhetoric and communication.

Our strategy is to concentrate on successful female leaders, who not only self-select into the leadership roles, but also achieve societal recognition as leaders. We use an inclusion into a leadership repository of high achievers as a proxy of success, which implies that women represented in these repositories are endorsed not only by their direct followers in organizations, but also by the broader society as being “worthy” of being included in the repository. We obtained data from two repositories: the Iowa State University Archives of Women’s Political Speech and the Gifts of Speech. Both repositories are hosted by universities and inclusion into the repositories is subject to expert review. The Iowa State University Archives of Women’s Political Speech is hosted by the Iowa State University, a public university in Ames, Iowa, and collects specimen of speech in English from prominent women who through their whole careers or at some point in their careers were leaders in activism, politics, civil service, public life, or assumed other leadership roles of power and public importance. The Gifts of Speech is hosted by Sweet Briar College, a private women’s college in Sweet Briar, Virgnia, and collects speech specimen in English from prominent female leaders representing a wide variety of fields. Though both repositories aim to suggest role models to the future generation of (female) leaders and a college of experts is consulted before including a particular individual into each of the repositories, the Iowa State repository includes women who are widely accepted as leaders by the American public (for example, prominent female American business women, lawyers, politicians, activists, journalists, etc., are included in the repository), the Gifts of Speech repository appears to apply additional success criteria such as winning an important global award such as the Nobel Prize or an well-known specialized prize such as Fields Medal, etc.

Our focus on Black women leaders who are widely recognized by the general public was chosen for its accessibility and relatability. However, we acknowledge the potential limitations inherent in focusing solely on these leaders. Historical and contemporary structures may determine which Black women are allowed or chosen to be in the limelight. For instance, certain personality traits, leadership styles, or even appearances might be deemed more “palatable” or “acceptable” by mainstream society, thereby allowing some Black women to rise to prominence over others. In our analysis, we aim to understand the systemic, societal, and cultural barriers and enablers that have shaped the public perception and acceptance of Black women leaders.

By combining the speech specimens from the two repositories, we obtain a unique dataset of female leadership speech. Yet, there are several important aspects about the dataset, which should be noted and which we take into account when conducting our analysis. Initially, we have mined all specimen of text available from both repositories and obtained 3,207 specimens of text in total. The only mining criteria we apply is that the latest date of the text specimen should be December 31, 2019. We deliberately avoided collecting text specimens from 2020 and 2022 due to the prevalence of COVID-19-themed speeches in those two years. While analyzing data from 2020 and 2022 is of interest, it would be more appropriate to consider these data in a separate investigation. The female speeches in the text format were collected using scripts coded in Python 3.7.7. Of 757 women in our total database, 608 (80.3 percent) were American (see Supplementary Materials for raw data). Considering our concentration on the comparison of majority and minority leaders, we concentrated on 608 female leaders from the US. Apart from collecting specimens of leadership speech, the Iowa State repository also contains specimens of political advertisement. Political advertisements are samples of text representing transcripts of televised advertisements used by politicians as a part of their election campaign. These text specimens are not suitable for our analysis as they are produced for the purpose of winning the election, have the goal of attracting attention to a particular individual rather than describe this individual’s agenda, and often contain direct speech from other individuals. Therefore, we excluded all specimens of political advertisement obtained from the Iowa State repository and concentrated on speeches only.

For inclusion into each repository, the speech has to go through the review scrutiny by an editorial committee. As a result, there are a number of speeches which are selected for both repositories. We removed the duplicated speeches, which appeared in both repositories and obtained unique 2181 specimens of speech from 608 women leaders from the US. Speech data was added to the database.

Speeches hold a pivotal role in the realm of leadership 40 . They not only provide a platform for leaders to convey their vision, strategies, and goals but also help in building rapport with their audience. The form of a speech, encompassing its structure, language, and delivery, reflects the leader’s intent, preparedness, and approach to their subject. It becomes a mirror to the leader’s mindset, revealing nuances about their priorities, concerns, and aspirations. Functionally, speeches serve multiple purposes for leaders. They act as tools of motivation, education, and persuasion. Leaders use speeches to inspire teams, educate stakeholders about shifts in strategy or market dynamics, and persuade audiences to align with their viewpoint or vision. The content of a speech can influence public opinion, drive organizational change, or even reshape industry perspectives. Considering our dataset of female leadership speech, it is important to note that the speeches collated provide a rich tapestry of insights into the leadership styles, communication strategies, and priorities of the women leaders represented. This collection, while vast and diverse, serves as a unique reflection of the evolving dynamics of female leadership in the US, especially when observed through the lens of its form and function.

From the repository speech data, we obtained the name of individual, date of speech, place of speech, exact text of the speech, and occupation of the individual at the time of the speech, type of organization where an individual worked at the time of the speech. These data were also merged with publicly available information about each speaker. This information included race, nationality, as well as profession or professions. Considering that engaging into a new profession requires risk taking, the number of professions obtained and mastered by each female leader was taken as a proxy of their individual risk parameter. These publicly available data were mined from the Wikipedia pages as well as from the official website of each woman leader (where available).

Nationality information was available for all 608 women, only 4 of whom had dual nationalities (US plus one other country). In terms of ethnical and racial composition, of the 608 women in our sample, 462 identified themselves as White, 87—as Black or African American, 10-Asian, 18-Hispanic or Latino , and 10 had other single race background. In our sample, 21 women had either mixed background or unknown background. Specifically, we could not find background information about 10 women, and 11 women were identified having several racial or ethnical backgrounds simultaneously, which made it difficult to place them in any one group. Information about the racial background was compiled from three main sources, which were cross-checked to form a unified classification: (i) a women leader’s own words in speeches, (ii) Wikipedia pages, as well as (iii) relevant lists (e.g., list of African American politicians, etc.). Black or African American group represents the largest minority group in our sample (see Fig. 2 ).

Selected Black Female Leaders’ Timeline. Note The figure shows at least one Black female leader per year. Where more than one woman leader was present, we have shown either all women if space permitted or selected one at random. If a female leader in our sample gave several speeches over a number of years, the year of the first speech in our sample was used for the figure.

Figure  2 shows minority female leaders in our database. Speeches from majority and minority leaders covered the period from 1828 to 2019. We obtained women leaders’ occupation information (main area of expertise), which was cross-checked using several sources, including the relevant speech repository pages about female leaders (Iowa State and Gifts of Speech repositories) and Wikipedia biography pages. In addition, we also collected data about all areas in which a particular female leader was a recognized expert (i.e., information about a particular leader’s profession). Hence, for each female leader in our database we had the main occupation and all areas where she was considered an expert. The speeches captured in the sample from this group spanned a period from 1851 to 2019 (i.e., pre-COVID19). As a result, we captured a diverse group of Black or African American women leaders, who represented a wide range of areas from activism and feminism to science and technology. Figure 2 showcases this heterogeneity.

Women in our database had different number of speech specimens per person. The average number of speeches per female leader was equal to 3.32 with the median of 1 and a standard deviation of 8.05. Over 70 percent of women in our sample had 1 speech specimen. There were 8 female leaders in the database with the number of specimens greater that 18: Carly Florina with 23 specimens, Madelaine Albright with 26 specimens, Elizabeth Dole with 27 specimens, Joni Ernst with 33 specimens, Carrie Chapman Catt with 45 specimens, Michelle Obama with 54 specimens, Elizabeth Warren with 64 specimens, and Hillary Rodham Clinton with 181 specimens. Importantly, many speeches from these female leaders were recorded in the same calendar year. For example, Hillary Clinton is the largest outlier in terms of number of speeches in our sample. Even though her speeches span a time period from 1969 to 2019, 64 of 181 of her speeches are from 2016 when she was running a presidential election campaign in the US. Similar pattern is observed for other outliers: for example, most speech specimens from Madeleine Albright (15 of 26) are from 1997 when she became the Secretary of State. In order to mitigate issues arising from multiple speeches per leader, our analysis takes into account the fact that some text specimens are from the same person (i.e., assumes that specimens from the same female leader are correlated). Furthermore, our text analysis is dynamic in the sense that it first considers the average trend in text from each individual in a particular year and only then calculates the overall behavioral schema trend for the whole year.

Our analysis is initiated with the utilization of a dataset comprising female leadership rhetoric for conducting a topic modelling exercise. Our corpus, designed specifically for this topic modelling, encompasses 2,181 speech samples attributed to 608 female leaders, collated between the years 1828 and 2019. This corpus includes over 3 million words. Following a pruning process that eliminates punctuation, frequently used function words, single occurrence words, and university names as well as organizational names, the total word count of the corpus stands at 1,000,401.

The final corpus contains both individual and temporal effects, necessitating consideration of the correlation of speech samples from the same leaders as well as the potential correlation of topics across time periods, with our unit of time being one year. Our approach addresses individual effects via the topic modelling process and temporal effects at a post-topic-modelling stage. This process is required since existing topic modelling methods are incapable of addressing both effects simultaneously. For instance, while Latent Dirichlet Allocation (LDA)-based Correlated Topic Model (CTM) procedures permit modelling of topic correlations, they are unable to model correlations between text samples from the same author. Similarly, Dynamic LDA permits the capture of topic evolution within a sequentially organised document corpus but cannot be jointly estimated with Correlated LDA due to its use of different distribution models.

Our findings can be categorized into three distinct areas. Initially, we use leadership rhetoric data to derive a suite of articulated behavioural schemas, expressed in the form of topics frequently discussed by female leaders. It is crucial to note that these speech samples originating from the same leaders demonstrate inherent correlations. During this initial phase, we deliberate whether the focus of these topics (i.e., behavioural schemas) is dependent on the leader’s racial heritage. More precisely, we investigate if there exists a unique specialization in the topics addressed by Black female leaders as contrasted with those addressed by White majority leaders. Subsequently, we delve into the evolution of behavioural schemas over time, unraveling the temporal dynamics of these schemas bifurcated by race. Finally, we amalgamate the insights gathered regarding behavioural schemas with those pertaining to female leaders’ risk-taking tendencies, with an aim to explore the differences in risk-taking patterns amongst leader populations of varying ethical origins.

Behavioral schemas of female minority leaders

Our approach first implements the topic modelling procedure accounting for individual-level dependencies, and subsequently measures individual and temporal effects using econometric methods in post-estimation. This methodology aligns with our focus on minority female leaders rather than a general temporal allocation of topics over time. To proceed with the topic modelling, we assume that each individual leader associates with a multinomial distribution of topics, and each topic associates with a multinomial distribution of words. A context-dependent Bidirectional Encoder Representations from Transformers (BERT)-based model (cdBERT) is employed. The method used in the cdBERT model is analogous to the approach used in contextualized models like Med-BERT by Rasmy et al. (2021), which utilise transformer architecture to integrate multi-level embeddings and bidirectional transformer (refer to Fig. 3 ).

Architecture of Transformer Model and the Topic Modelling Output. Note The figure part ( a ) shows our topic modelling architecture, while part ( b ) demonstrates the topic modelling output.

In our application, individual leader ID and speech dates are used to differentiate between individual leaders and their respective speeches. Topic modelling is executed using Python 3.7.7, returning 35 topics. A detailed presentation of the topic modelling results can be found in Fig. 2 , which illustrates the alignment between topics within female leadership speech and the United Nations’ 17 global goals established in 2015.

The BERT-based topics, although distinct, can be categorised into six groups via hierarchical clustering, as presented in Fig. 4 . General behavioural schemas related to life, family, education, and economy form a distinct group, as do schemas related to war, peace, defence, and international politics. Another group focuses on equality, rights of underrepresented groups and minorities, and economic fairness.

Hierarchical Clustering and Cluster Cross-distance Map. Note The figure demonstrates links and relationships between different topics in our analysis.

A static analysis of the relative plot of White and Black female leader topic specialisations does not suggest clustering in our sample by ethnicity or racial background (see Fig.   5 ). Each dot represents an individual female leader, whose probabilistic 35-topic allocation (behavioral schema allocation) obtained from the topic modelling is dropped onto a 2-dimentional space. Female leaders with Black background are shown using the red color, while female leaders with any White background are depicted using blue color. Figure 5 shows no clustering of red and/or blue dots.

Two-dimensional Factor Mapping of the Relative Topic Distancing. Note Red dots represent Black (minority) female leaders and White (majority) leaders are captured by blue dots. Figure 5 displays the results of a factor analysis, where “Component 1” and “Component 2” are the first two principal components capturing the most significant underlying patterns in the data. These components, derived from the original 35 behavioural schemas identified through the topic modelling, simplify the topic modelling output complexity into a 2-dimensional graph.

We verify this outcome through econometric estimation and a series of multilevel regressions, measuring fixed effects at the level of each year at level 1 and each individual leader at level 2 (see Fig. 6 ).

Results of A Series of Multilevel Regressions: A Summary.

Through the regression analysis, underrepresentation was identified in all female leader’s racial and ethnical groups in the behavioural schemas of Army and military service as well as Disability. A similar underrepresentation was observed in the Science and technology topic. Interestingly, Black leaders exhibited higher engagement in the Diplomacy topic and the areas of Rights of Black community as well as Cities and neighborhoods. All estimations control for the type of organization where a leader was employed at the time of the speech. Our analysis reveals no statistically significant differences between private, public, and third sector organizations. These observations suggest a degree of specialization for Black female leaders regarding racial discrimination and urban environments. Yet, it is apparent that static analysis does not allow to fully identify the differences between Black and White female leaders, which is why we turn to the dynamic analysis in the next subsection.

Dispersion in the behavioral schemas

In this study, a temporal review of the behavioural schemas demonstrated by American female leaders spanning from the 19th to the 21st century was carried out. Interestingly, although these leaders share similarities in their areas of focus, a certain level of specialisation associated with race or ethnicity was identified. Consequently, a closer examination of the dynamic evolution of these behavioural schemas within each group was warranted. Hence, all 35 behavioural schemas were mapped across a temporal spectrum for each racial or ethnical group of female leaders. The outcomes of this mapping exercise are depicted in a heatmap (Fig. 7 ), which uncovers intriguing patterns. Cooler hues (such as blue) on the heatmap represent lower concentrations of a specific behavioural schema within the leadership rhetoric in a given year. Conversely, warmer colours (such as red) indicate a higher concentration.

Temporal Evolution of Female Leaders’ Behavioural Schemas. Note Grey areas indicate the time periods when the identified topics were non-existent. For example, the term “Domestic violance” only appeared in 1973.

Primarily, Figure  7 illustrates that, despite the propensity of majority leaders (those from a White background, labelled ’White’ in the figure) to frequently alter their behavioural schemas, the behavioural schemas of minority leaders (Black background, labelled ’Black’) exhibit greater temporal stability. Notably, the group of Black minority leaders consistently exhibit a strong focus on specific topics over time, including Justice, Public Education and Children, Cities and Neighbourhoods, Space, Cybersecurity and Internet Technology, Mental Health and Self-help, and Labor Unions and Workers.

Since our study utilizes a BERT-based algorithm for topic modeling of both contemporary and historical speeches, our deep learning model, trained on data, where modern data has much more significant representation than historical data, demonstrates its capability to contextually interpret and classify text into relevant topics. BERT’s design, which analyzes words in their full context rather than in isolation, enables a nuanced understanding of language. This approach is especially effective in identifying contemporary topics related to historical texts. For example, historical discussions about ’Space’ often encompass broader celestial elements, such as stars and the heavens, rather than modern conceptions of space travel or technology. Historical terms like ’telegraphy’, which date back to 1832, are linked to modern terms like ’Internet’; and terms like ’communications security’, known since World War II, are associated with contemporary terms like ’Cybersecurity’. To avoid confusion, grey areas in Figure  7 indicate years when the modern terms, identified by BERT as topics, did not exist. To determine the origin of a term, we first used an etymological dictionary, which provided detailed histories of words, including their first known usage. We then cross-checked this information with the Macroscope tool ( http://macroscope.intelligence-media.com/ ), which offers a detailed historical analysis of terms, jointly with words associated with these terms.

Our findings imply that majority female leaders, who experience positive societal change over time, can adapt their focus swiftly, shifting their behavioural schemas to address new challenges as old ones are resolved. Meanwhile, minority female leaders, who do not experience such positive societal changes, maintain their focus on consistent behavioural schemas over time. Consequently, while rapid updates in the behavioural schemas of majority female leaders are observed, minority female leaders are compelled to maintain focus on consistent behavioural schemas. This conclusion holds true across private, public, and third-sector organisations.

If our initial hypothesis (Hypothesis 1) is valid, not only should there be temporal invariance in the behavioural schemas of minority female leaders, but also a lower degree of dispersion in prevalence coefficients for the same behavioural schema (or topic) within the minority group compared to the majority group. To ascertain this, standard deviations of the prevalence coefficients for each topic were compared, with a specific focus on the contrast between White majority and Black minority female leaders. The outcomes of this comparison, presented in Fig. 8 , reveal that 27 of 35 topics exhibit a greater dispersion in behavioural schemas in the majority group than in the minority group. The observed differences are statistically significant as per the F-test, thereby substantiating Hypothesis 1. This finding suggests that minority leaders have more time-invariant and less dispersed behavioural schemas than majority leaders, implying that they continuously grapple with the same issues over time, without observing progress in resolving these critical matters. Consequently, the rate at which behavioural schemas are updated for minority leaders lags behind that of majority leaders. This slower rate of update leads to a static behavioural schema for minority leaders over time, thereby influencing their psychological states, expectations, and professional development.

Comparison of Dispersion in the Behavioral Schemas between White (W) and Black (B) Leaders.

Risk-taking

Our theoretical framework suggested that minority leaders, given their lack of progress over time, may resort to risk-taking as a form of compensation for this stagnation. This theory was backed by our analysis, which showed that minority leaders demonstrated a greater risk-taking propensity ( \(\sigma _i<\sigma _j\) , thereby implying \(r_i^t > r_j^t\) ).

We calculated the average number of areas entered and excelled in by each female leader in our study by collecting the data from the publicly accessible Wikipedia profiles. Taking Hazel R. O’Leary’s Wikipedia profile as an example, it states that “Hazel Reid O’Leary (born May 17, 1937) is an American lawyer, politician, and university administrator who served as the 7th United States secretary of energy from 1993 to 1997.” From this description, we identified and catalogued three distinct professions or areas: lawyer, politician, and university administrator/educator. To ensure the precision of our data extraction, manual cross-referencing was undertaken using individual official websites, such as Hazel O’Leary’s website. For Hazel R. O’Leary, based on our methodology, the risk parameter was established at a value of 3, representing the three professional areas she engaged in and excelled at. This systematic approach was employed for all female leaders incorporated in our study. While White female leaders on average engaged in 1.59 areas, Black female leaders ventured into an average of 2.13 fields, indicating a significantly higher risk-taking propensity. This was further corroborated by the Mann-Whitney-Wilcoxon test, which validated these differences as statistically significant (z = − 5.708, p  = 0.0000).

These findings confirm our Hypothesis 2: minority female leaders, in the face of a lack of positive societal changes and behavioral schema updating, compensate for this stagnation by demonstrating higher risk-taking behavior.

The analysis of longitudinal data further solidified our findings, showing a diminishing risk-taking trend among White female leaders over time (estimation of trend function revealed a declining pattern with the coefficient of − 0.0054). In contrast, Black female leaders displayed an increasing propensity towards risk-taking (estimation of trend function revealed a declining pattern with the coefficient of 0.0084). This pattern not only confirms our Hypothesis 3, but also provides additional insights into the dynamic landscape of risk-taking behavior across racial and ethnic groups in female leadership.

These results provide a comprehensive, nuanced understanding of the behavioral schemas of female leaders across racial and ethnic groups and over time. Our findings underscore the importance of recognizing the distinct experiences and challenges faced by minority female leaders. They call attention to the need for devising policies and strategies that are not only supportive but also empowering, tailored to the unique needs and experiences of minority female leaders.

Many studies talk about racial inequality in organizational leadership identifying important problems faced by the minority female leaders (see, e.g., Parker 1996 for early literature on Black female leadership). Yet, to date, few attempts were made to quantify racial bias and measure its impact on women leaders. In this paper, we propose a new theoretical behavioural data science approach inspired by the Bourdieusian leadership framework 19 and building on the dynamic leadership development models by 20 as well as 21 and test this framework quantitatively using a large sample of female speech.

Recent literature highlights the significant underrepresentation and challenges faced by Black female leaders in the corporate sector 41 . According to the 2020 report by LeanIn, for every 100 men promoted to their first managerial role, only 58 Black women receive a similar advancement. One in 3 Black women feel they are less empowered and supported to overcome professional challenges than the general population. Additionally, the IBM Institute for Business Value (IBV) found that over half of Black women perceive discrimination against them in their workplace based on race. Furthermore, while 84% of Black women believe there is discrimination against women, only 64% of White women share this sentiment. Despite these challenges, Black women exhibit a strong drive for leadership; research from the Center for Talent Innovation notes that they are more likely than White women to aspire for executive leadership roles. This underlines the importance of organizations to recognize and address the unique hurdles Black female leaders face.

Using 200 years of female leaders’ rhetoric history in the US, we demonstrate that even though a static view shows that women representing different backgrounds are not different in their aspirations to make the world a better place, dynamic analysis reveals that sustained intersectional effects (due to a combination of gender and racial bias) produce unequal outcomes for minority and majority leaders. This study demonstrates that Black female leaders often take on greater risks to address the compounded challenges of intersectional invisibility. Yet, compared to their White peers, their goals often remain unachieved. This has resulted in recurring challenges that successive generations of Black female leaders have had to confront for extended periods, spanning decades and even centuries.

Specifically, female leaders representing racial minorities tend to experience lack of change in their social outcomes over time due to sustained discrimination. This causes the lack of updating in their behavioral schemas—i.e., their perceptions of the world and their place in the world. As a result, for many generations, they tend to focus on the same problems, which fail to get resolution over time. This lack of experiential change and time-invariant behavioral schemas cause them to engage in more and more risky behaviors in order to succeed. Using the Burna Boy’s (an award winning rap artist’s) analogy, we find that Black female leaders have to be “twice as tall” compared to their majority counterparts in order to succeed, suffering from significant adverse effects of racial bias.

In examining the challenges encountered by female leaders from racial minority backgrounds, it is imperative to elucidate the profound implications of Burna Boy’s “twice as tall” metaphor. This analogy, while resonant, is emblematic of the broader principle of “working twice as hard” to attain equivalent success within an inherently biased system. This sentiment has its roots in the socio-medical construct of John Henryism 42 , which delineates the exhaustive endeavors of Black individuals, often culminating in adverse health outcomes. Concurrently, the theory of Racial Battle Fatigue highlights the psychological duress experienced by individuals of color due to incessant racial microaggressions. Together, these frameworks underscore the profound physiological and psychological toll exacted by the persistent drive to surpass racialized expectations. In any discourse regarding the experiences of Black female leaders, it is paramount to acknowledge these multidimensional challenges, born from a legacy of systemic discrimination.

Even though we observe some degree of specialization, similar to the studies highlighting the inconsequentiality of the socially constructed notions of race, our analysis of Black female leadership reveals that race has not determined the priorities and interests of global female leaders. Yet, understanding of female minority leadership in organizations has been incomplete as in many societies we continue to consider static rather than dynamic effects of intersectionality. Much of the organizational diversity training if focused on acceptance and equality at a particular moment in time rather than through time. Yet, our study shows that there are rigid behavioral schemas and negative experiences, which affect minority leaders from generation to generation, making them take more and more risk in order to fight the lack of positive experiences as well as intersectional invisibility.

This suggests that diversity in leadership should be addressed by organizations holistically as a dynamic concept, concentrating around improving the outcomes not only for one particular leader or a particular group of (minority) leaders, but rather increasing the number of positive experiences for the entire generation of leaders and promoting positive change. Our findings demonstrate that it is not enough to address diversity through increasing the number of minority leaders by creating promotion opportunities. Rather, it is important to facilitate the change in their behavioral schemas through positive experiences such that more minority leaders can emerge. Currently, becoming a successful leader has a very costly barrier for minority leaders—they face a large cost to entering the leadership scene, because they are required to take a lot of risk to succeed. If they start to see that problems are resolved and if their experiences become more positive, minority representatives will enter the leadership scene more as the cost of entry will be reduced because they will not need to compensate the lack of change with risk taking.

The core argument in many previous studies has revolved around identifying the issues faced by minority female leaders, primarily through qualitative means or non-intersectional quantitative analyses 12 . While these studies have been instrumental in shedding light on racial inequality in leadership, our research takes a pioneering step by quantitatively merging the concepts of intersectionality with leadership rhetoric spanning 200 years in the US. The emphasis on intersectionality, drawing from both gender and racial perspectives, allows us to observe unique trends and outcomes that would otherwise remain unseen in a non-intersectional approach. In a non-intersectional quantitative study, these challenges might be reduced to singular issues related to either gender or race. Similarly, qualitative studies, while rich in detail, may not always be able to highlight the recurrent patterns and sustained effects over extended periods as a quantitative approach can. By juxtaposing the static and dynamic effects of intersectionality, our study reveals that while aspirations of women leaders across various backgrounds remain consistently benevolent, their outcomes and experiences significantly diverge due to the intersection of gender and racial bias.

It is paramount to emphasize that the success of diversity initiatives should not be solely measured by increasing the representation of minority leaders. Instead, a more holistic approach, as suggested by our findings, should consider improving the experiential landscape for these leaders, addressing generational challenges, and facilitating changes in their behavioral schemas through positive experiences. In essence, this research bridges a critical gap by providing a quantitative testament to the intersectional challenges minority female leaders face, emphasizing the need for systemic and long-term solutions in organizational settings.

It is also important to note that black women have historically navigated a landscape where their speech and actions were heavily restricted. Our results suggest that this constraint was entrenched in systemic racial and gender biases, limiting their opportunities to assert leadership and influence. The historical narrative for white women, while also marked by gender-based restrictions, presented a relatively broader scope for self-expression and leadership, albeit within confined boundaries. This differential historical experience has invariably shaped the trajectory of leadership behavior and opportunities for women of different racial backgrounds.

These historical constraints may have contemporary implications. For black women, the enduring legacy of more stringent speech restrictions has likely translated into a form of leadership that often necessitates cautious navigation of both racial and gender norms. In contrast, white women’s leadership behaviors, though still influenced by gender norms, have evolved differently due to their historical access to relatively more freedom of speech and action.

By integrating these historical nuances into our analysis, we deepen our understanding of how intersectional factors shape leadership behaviors. It is crucial to acknowledge that the leadership landscape for women is not monolithic; it is sculpted by the complex interplay of race, gender, and historical context. This recognition allows us to more accurately capture the varying experiences and challenges faced by black and white women in leadership roles. We propose that future research should further explore how these historical constraints continue to influence contemporary leadership styles and opportunities for women of different racial backgrounds. Such research could provide valuable insights into the development of more inclusive and effective leadership strategies that recognize and address the unique challenges faced by women of diverse racial and gender identities.

Our study has a number of limitations, which could be addressed by the future research. Our model assumes that the risk-taking decision and leaders’ experiences are separable. This limitation can be addressed by considering a Bayesian modelling approach, where a leader starts with a set of priors and then updates her priors with each experience. We also assume that gender and ethnicity identification of a leader does not change over time. Our model allows to relax this assumption by introducing endogenous or exogenous shocks to the priors and measuring how the changes in priors affect outcomes. Finally, we capture individual effects of leaders by econometric and statistical means (e.g., via fixed effects). Another option would be to collect more detailed (preferably experimental) data on leaders measuring their behavioral traits, risk attitudes, as well as other individual variables in order to explore the link between these characteristics and leadership rhetoric. It is left to future research to explore these exciting endeavors, which would allow to expand our understanding of dynamic and intersectional effects of racial and gender bias and their impact on minority female leadership in organizations.

Data availability

To simplify the refereeing process, the data, analysed in this paper, is provided in the Supplementary Materials to this manuscript.

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Acknowledgements

The authors are grateful to the participants at research seminars at the University of Sydney (Australia), The Alan Turing Institute (UK), the National Institute of Technology at Warangal (India), the University of Birmingham (UK), and various online venues in the US, South Africa, UK, and the Netherlands for many insightful comments and suggestions. We are also grateful to leaders from the Black and African American communities, whose work inspires us to continue our research on diversity and inclusion. The paper reflects own opinions of the authors.

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The idea for the paper came from G.P. and S.A.; G.P., I.M.O. and A.K. developed the theoretical model; N.T. and A.K. mined the data; the analysis was conducted by G.P., A.K., and S.A. G.P., S.A., I.M.-O., and A.K. wrote the paper.

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Pogrebna, G., Angelopoulos, S., Motsi-Omoijiade, I. et al. The impact of intersectional racial and gender biases on minority female leadership over two centuries. Sci Rep 14 , 111 (2024). https://doi.org/10.1038/s41598-023-50392-x

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Pierce’s (The Black seventies: an extending horizon book, 1970) conception of “subtle and stunning” daily racial offenses, or microaggressions, remains salient even 50 years after it was introduced. Microaggressions were defined further by Sue and colleagues (Am Psychol 62:271, 2007), and this construct has found growing utility as the deleterious effects of microaggressions on the health of people of color continues to mount. Microaggressions are common on campuses and contribute to negative social, academic, and mental health outcomes.

This paper explores how Black college students’ experiences correspond to or differ from the microaggression types originally proposed by Sue et al. (Am Psychol 62:271, 2007). Themes were identified from focus group data of students of color ( N  = 36) from predominately White institutions (PWIs) of higher learning ( N  = 3) using interpretative phenomenological analysis.

We identified 15 categories of racial microaggressions, largely consistent with the original taxonomy of Sue et al. but expanded in several notable ways. New categories in our data and observed by other researchers, included categories termed Connecting via Stereotypes, Exoticization and Eroticization, and Avoidance and Distancing. Lesser studied categories identified included Sue et al.’s Denial of Individual Racism, and new categories termed Reverse Racism Hostility, Connecting via Stereotypes, and Environmental Attacks.

While previous literature has either embraced the taxonomy developed by Sue and colleagues or proposed a novel taxonomy, this study synthesized the Sue framework in concert with our own focus group findings and the contributions of other researchers. Improving our understanding of microaggressions as they impact people of color may better allow for improved understanding and measurement of this important construct.

Peer Review reports

Almost 50 years ago, Pierce [ 33 ] sought to unpack the mechanism of “subtle and stunning” daily racial offenses, known as microaggressions. Pierce’s seminal description of the construct of microaggressions laid the groundwork for a re-framing by Sue et al. [ 41 ], who defined racial microaggressions as subtle, daily, and unintentional racial slights committed against people of color because they are members of a racialized group. Sue et al. [ 41 ] proposed nine categories of racial microaggressions, described as (a) assumptions that a person of color is not a true American; (b) assumptions of lesser intelligence; (c) statements that convey colorblindness or denial of the importance of race; (d) assumptions of criminality or dangerousness; (e) denials of individual racism; (f) promotion of the myth of meritocracy; (g) assumptions that one’s cultural background and communication styles are pathological; (h) being treated as a second-class citizen; and (i) having to endure environmental messages of being unwelcome or devalued. Since Sue and colleagues’ taxonomy was proposed, numerous researchers have examined these categorizations, finding generally similar but not identical groupings based on qualitative and factor analytic studies (e.g., [ 28 , 44 ]).

There has been a surge of qualitative, quantitative, and theoretical work (reviewed by [ 53 ]) expanding our understanding of the nature, experience and consequences of microaggressions since Sue and colleagues proposed their taxonomy of microaggressions in 2007 [ 41 ]. Microaggressions towards targeted racial or ethnic groups are persistent and occur frequently in academic settings [ 40 ]. They are increasingly recognized to compound with the intersections of gender, sexual orientation, and other stigmatized identities (e.g., [ 2 , 22 , 46 ]), and these additional identities have been incorporated into Sue et al’s. original taxonomy [ 42 ]. As of this writing, multiple overlapping yet distinct taxonomies have been proposed, including several with empirical support (e.g., [ 18 , 24 , 28 , 44 ]). In this paper, we examine the experience of racial microaggressions among African American college students and provide a qualitative description of the resulting taxonomy using focus group data, comparing our findings to Sue and colleagues [ 41 ] original work and the expanded set of themes in Sue and Spanierman [ 42 ].

Nature and maintenance of microaggressions

Although there has been some debate about the nature of microaggressions and how they should be defined, we contend that microaggressions are actual things that can be identified and measured, and not simply the subjective experience of the target (i.e., [ 47 ]), although this not universally agreed upon by scholars. Due to the subtle nature of microaggressions, they are sometimes minimized as simple cultural missteps or racial faux pas [ 47 ]. Microaggressions are not, however, innocuous gaffes but are a form of oppression that reinforces existing power differentials between groups, whether or not this was the conscious intention of the offender [ 35 , 47 ]. This reinforcement of a power differential contributes to the maintenance of microaggressions because it favors the in-group and, in an effort to retain the extant power structure, outgroup members are punished socially when they challenge microaggressions. Essed [ 11 ] has written extensively about “everyday racism,” as a tripartite framework whereby racist practices involve the marginalization of those identified as racially or ethnically different; the problematization of those cultures and identities; and repression of (potential) resistance against racism through humiliation or aggression. Simply put, racial microaggressions are a subtle and common form of racism that maintains White supremacy.

Harms of microaggressions

The cumulative “day-to-day stress” caused by microaggressions [ 33 ] has been reliably associated with negative physical and emotional health outcomes for decades. Multiple studies indicate significant associations between experiencing microaggressions and higher levels of depression [ 18 , 30 ] anxiety [ 51 ], posttraumatic stress disorder symptoms [ 52 ], impaired psychological wellbeing [ 1 , 16 ], and decreased self-esteem [ 9 , 31 ]. Studies also have demonstrated a relationship between discriminatory stress and physical ailments, including hypertension [ 8 ], hypothalamic-pituitary-adrenal (HPA) axis dysfunction [ 19 ], higher body mass index [ 21 ], and coronary heart disease [ 36 ].

Microaggressions are damaging to young people and adults alike, and the context of students of color in academic settings is particularly salient. School campuses in the United States have long been recognized as sites that magnify racial tensions present in the broader society [ 17 ], and young people may be exposed to racially-focused situations and conversations more frequently at school than at home [ 43 ]. Studies of college students have demonstrated a significant relationship between racial discrimination and increased substance use [ 4 , 34 ], delinquency [ 6 ], decreased academic outcomes [ 20 ] and self-esteem [ 54 ]. Depression symptoms have been found to mediate a relationship between racial microaggressions and suicidality in students [ 32 ], raising grave concerns about the consequences of daily microaggression-related stress on young people.

Focus of this study

Given the many harm of microaggressions [ 48 ], it is critical that we understand the experience of the targets of microaggressive actions. As the field moves towards the development of effective tools for the reduction of racial microaggressions, our taxonomies must be based increasingly on empirical findings for greatest utility in identifying both their occurrence and the harms that occur as a result. This paper seeks to elucidate the experience of racial microaggressions experienced by Black students at predominately White institutions of higher learning (PWIs) with a focus group design utilizing qualitative data and compare findings to Sue and colleagues’ taxonomies of racial microaggressions. The question being explored was how current Black college students’ experiences might correspond to or differ from these original and revised types.

Recruitment

Study participants were recruited from one private and two public PWIs located in the Southern/Midwestern and Pacific Northwest United States. Participants were recruited using a combination of posted fliers, the undergraduate psychology recruiting pool, and word of mouth. Interested parties were directed toward an online screening tool, which included a demographic questionnaire. The lead research assistant contacted eligible participants to schedule a time for focus group participation. Study eligibility criteria were self-identification as Black, African American, Biracial (with Black), or Continental African.

The Institutional Review Boards’ (IRB) Social and Behavioral Sciences Committees for the various institutions approved the research, and all respondents were consented according to the rules and regulations of their respective IRBs. The informed consent procedure included a preamble consent provided online for the initial collection of demographic and self-report data, and a written form that was reviewed with researchers and signed right before the focus groups commenced.

Analytical approach

The research team selected an interpretative phenomenological analysis (IPA) approach to codify the data [ 10 ]. This method of analysis is well suited to small homogeneous samples and the use of a semi-structured interview format. IPA utilizes “prompts and funneling” to identify and connect themes among individual perspectives on how study participants make sense of their social and personal worlds [ 37 ]. Data from each of the focus groups were audio recorded and transcribed verbatim by the research team. After the initial transcription, each transcription was checked by a second trained research assistant.

Focus groups

The research team consisted of a diverse group of clinical psychologists, graduate assistants, and research assistants. Each of the focus groups was conducted by either one of the principal investigators or an advanced level graduate or research assistant. In every case, at least one of the facilitators was an African American faculty member.

Background information about the definition and types of microaggressions were provided during each focus group, with some examples from Sue et al.’s [ 41 ] paper. Focus group questions centered on the participants’ experience with racial microaggressions, with six initial prompts and a variety of suggested subprompts that might be used to clarify discussion following each prompt, though facilitators were encouraged to also explore topics that organically arose in the room. The primary prompts used in each group were:

What examples of microaggressions have occurred in your life?

What examples of microaggressions have you witnessed or heard about in friends, family or others in your life?

Are there certain situations where you are more likely to experience a microaggression?

What do you do?

How do you cope?

Participants

The final sample consisted of 36 undergraduate and graduate students from 219 students who completed the online screening survey. A total of six focus groups were conducted across three campuses, with group sizes from 2 to 11 participants. The mean age was 23.0 (SD = 6.64) with 84.4% of the participants identifying as African American, 3.1% of the participants were Latino/a, and 68.8% were female.

Data analysis

Initial coding was completed exclusively by two pairs of graduate and undergraduate students at the institutions where the focus groups occurred. The initial coding results were reviewed and discussed by the coders as well as the faculty research team, which included an expert on racial microaggressions (MTW), as well as one with IPA experience who had trained the team (MDS). During these discussions, themes would be explored for convergence, and sent back to the coders to determine if consensus might be reached that the codes appeared to capture the meaning that each team intended. Finally, the identified themes were compared to the theoretical groupings of microaggressions from Sue et al.’s [ 41 ] taxonomy and reviewed a final time by the authors to further verify agreement across the study team on the categorization of the data. This allowed for the consideration of whether terms that already existed in the literature might serve as better labels that would bridge these results to existing literature, as well as to avoid unclearly renaming a well-described phenomenon.

The following section details the 15 resultant categories from our IPA analysis, which are also summarized in Table  1 .

Not a true citizen

This type of microaggression, first described by Sue et al. [ 41 ] as “Alien in Own Land,” is based on assumptions that the target is not a “true American,” reinforcing notions that non-Whites are probably immigrants. Communicating exclusion, illegitimacy, and lack of belonging that can make people of color feel like outsiders. This type of microaggression has often been described in relation to the experiences of Asian and Latino/a Americans, but African American focus group participants reported experiencing it as well. Some exemplars of this theme are as follows:

My head is shaved, actually. I hear a lot of things. It’s really annoying about… a lot of people, especially from my friends. They think that I shaved my head for like, “Oh, do shave your head for a religious thing? Or like an African ritual or something?” Because they see, like you know, like the pictures and stuff in the media. And they automatically assume that like, and I hear it a lot too… “Oh, where are you from? Are you from like Africa?” – Female respondent

Just a few months ago, someone who works in the office of admissions was with students from Tanzania and she asked me where I was from. I said Cadence, Kentucky, and she said “No, before that, where are you from?” And I said, “Kentucky. I was born here. And she said, ‘No seriously your name is [redacted] so you have to be from outside of America. But we were in the presence of Tanzanian students who obviously didn’t want to be asked where they were from.” – Female respondent

Racial categorization & sameness

This category is intended to describe the microaggressions that occur when a person of color is compelled to disclose their racial identity to others, often leading to the expression of pathological stereotypes based on that identity (e.g., the next category; [ 49 ]). It also applies when people make comments or assumptions that people of a given race are all alike. This results in the harmful ascription of stereotypes that may serve to disconnect an individual from their actual heritage or lived experience, to incorrectly ascribe attributes to one’s heritage or experience, or to force unwanted attributes or group responsibility to an individual.

I was folding t-shirts one day and this boy came up to me and said, [deepens voice] “I’ve been meaning to ask you this, what are you?” I said, “I’m a girl.” He was like, “No, no, no, no, no. What’s your race?” I’m like, “I’m Black.” He was like, “No way, no way!” I’m like, “If you see my entire family, I’m literally Black.” And I don’t think I look anything but Black, but he like wouldn’t believe it. – Female respondent

Sometimes my friends are like, “You’re so White,” or something like that. And I mean, I’m half-White. But I’m just like annoyed with it. I know I’m mixed, I understand that I am Black and White. I don’t have to act a certain way. – Female respondent

…I always find that whenever a topic of fashion comes up, people are like, “Why do Black people droop their pants?” And it’s just like I speak for all Black people because I’m Black? Maybe you should ask someone who is drooping their pants? I don’t know. – Female respondent

Further, those who identify as biracial or multiracial may struggle to feel accepted, feel confused about their identity, and may experience social pressure to align with a single identity [ 52 ]. Intersectionality due to characteristics like gender, sexual identity, or religion may also be overlooked. One student shared her frustration during the group discussion.

And they’ll bring up that we’re being divisive. But we’re like, “You need to recognize that black Muslims exist and issues about Muslim people, I guess, probably do affect us. But the issues regarding Black people, like police brutality, also affect us.” But they just seem to forget that. They just ignore it. – Female respondent

Assumptions about intelligence, competence, or status

This category is intended to include any positive or negative ascriptions of intellectual abilities, competence, education, or social standing based on racial assumptions. A common phenomenon encountered in the focus groups was counter-stereotypical surprise or assumed exceptionalism (e.g., “You’re not like other Black people.”) Many African American focus group respondents reported they encountered disbelief when they demonstrated academic excellence or expressed professional career ambitions.

We were deciding where we wanted to go to college, and these people were supposed to help us. And she, like I went in there, and I was like, “Oh, here are the places I want to apply to and I’m interested in.” And she’s like, “I think you should look at community colleges.” I’m like, “What are you talking about?” I had a 3.7 GPA – what do you mean I should look at community colleges?! I was like, “Well, I’m not really interested in community college, this is my list I’ve already decided.” She was like, “No, let’s look at this,” and it was some random college I had never heard of like in the middle of nowhere. I got really upset. I went home, I cried. – Female respondent

On the first day of class you get a lot of looks like “Are you in the right class? Why are you here?” – Female respondent

People will say sometimes, “Oh, you have a Master’s.” Like they feel so surprised when they find out that you are actually educated or you have a higher degree. And when she said that to me, “Oh, you’re such a good writer.” I just didn’t know how to respond, cause I’ve heard that said to me by other people that are White, and to me it was not a compliment. I was just kind of like, “Well, did you not think that I would be a good writer? Is there a reason why I wouldn’t be a good writer?” – Female respondent

False colorblindness / invalidating racial or ethnic identity

Colorblindness includes statements that indicate a person does not want to acknowledge race and instead focus on shared humanity [ 41 ]. Not all forms of colorblindness were considered negative by focus group participants, who often welcomed the idea that they could be treated equally by others rather than being racialized. However, they did not typically believe that their race was unseen or unnoticed by those professing colorblindness. Thus, the category is renamed here as “false colorblindness,” to account for the various examples in the data where “colorblindness” functionally prevents honest discussions about important racial issues.

I think just from professors as well as from students that are like, “Oh I don’t see color” or ignoring the fact that they might have said something that was bigoted or racist and not acknowledging that they have an issue or being able to address people as people, and also acknowledging that they have different ethnicities and different ethnic backgrounds. – Female respondent

I’ve taken a lot of women and gender studies classes, and it’s [privilege] a topic that we talk about a lot…And I don’t know if I’m the only Black person in that class, there may be two or three more, but definitely not a lot of us. And when we’re discussing it there are a lot of people who are like, “Yeah, I don’t know. I just can’t see it from y’all’s point of view.” – Female respondent

I told my roommate that I was going to a Black Lives Matter event, and he said, “No bro, it’s all lives matter.” And I was like, “Ah, come on man. Where are all of the All Lives Matter events? Who is doing the All Lives Matter protests?” – Male respondent

Criminality or dangerousness

This occurs when someone demonstrates belief in or acts on stereotypes that people of color are dangerous, untrustworthy, or likely to commit crimes or cause bodily harm (e.g., [ 49 ]). It could also include concerns about being treated badly by people of color (i.e., verbal aggressions) leading to emotional harm. This category garnered the largest number of comments from focus group participants.

It’s like an everyday thing. Well, not necessarily every day, but just like on campus like… I remember I was walking over toward the law school to meet somebody… Like I’m walking, and this White dude was in front of me, and he looked back and seen me walking behind him and he literally kept [checks over each shoulder] looking over his shoulder like I was going to do something. – Male respondent

I was coming down the stairs and this really tall White guy was going up [the stairs] and I was in his way. He flinched! I’m 5’3”, I’m not going to injure you. – Female respondent

Another instances when I see microaggressions play out is in the differences in the way that you dress. I can dress in you know a pair of Timbs or a pair of boots and just a baggy sweatshirt. You go out because I’m feeling a little lazy that day and have everybody walk to the other side of the street. But the second I put on a button down and a little bit tighter pants and some dress shoes or you know something along the lines of that then everybody feels a little bit more comfortable, you know, and it’s like why is it that all of a sudden my perception is changing just because of the attire that I have on? – Female respondent

Denial of individual racism

In contrast to False Colorblindness, this type of microaggression occurs when a person tries to make a case that they do not have any racial biases, which may be triggered by perceived scrutiny of the offender’s behavior. This may take the form of talking about anti-racist things the person has done or connections the person has with other people of color. This category was supported by our data, however, and when employed as a response to criticism, it can be invalidating to people of color who are trying to draw attention to a problematic behavior (e.g., [ 26 ]).

I was dating a [White Bulgarian]guy for a little bit. … every time we hung out he’d be like “Yeah, I have lot of Black friends. I listen to this kind of rap music.” And I’m like, “Why are you telling me this?” Like, ok, I guess I don’t know if he was trying to fix something. – Female respondent

When I bring it up to them, about something, they kinda say, “Well, it’s not anything offensive.” Well some of them think of themselves as being Black, like some girls I know really have this identity crisis, where they just think they can relate so much to our culture that they are like… They want to be Black, like they date the Black boys and stuff like that, so they feel like the comments they make don’t matter, because they feel like they already are within our culture. But they don’t understand like, if you understood what it meant to be us, you wouldn’t make comments like that towards us. – Female respondent

Myth of meritocracy / race is irrelevant for success

This microaggression occurs when people deny the ongoing existence of systemic racism or harmful discriminatory behavior, specifically in regard to personal achievement or barriers to achievement. They embrace the myth of meritocracy and the notion that the determinants of success are unequivocally rooted in personal efforts, refuting that White privilege is an unearned benefit resulting in tangible differences in outcomes at a personal or societal level.

I’ve had a mixed girlfriend of mine sit there and say … “Black people are just blaming the system, and they just need to take advantage of, you know, the opportunities they have.” And it’s like well really what – how many opportunities do we have? Can you sit up here and put on a list of how many opportunities we as African Americans have compared to all the opportunities that Whites have, or you know, Asian Americans or Mexican Americans? Because if you sat up there and compared the list, our list is going to be pretty short. You know, can you explain to me why it is that we have [so many] African American men in prisons, a lot of African American women in prisons who still haven’t gone through trial, and it’s two years later that they’ve been sitting in jail. I know friends who have seen their friends sitting in jail awaiting trial for two years. – Female respondent

Reverse racism hostility

This microaggression includes expressions of jealousy or hostility surrounding the notion that people of color get unfair advantages and benefits due to their race, often coupled with the assertion that White people are being treated unjustly and are suffering as a result. The idea that people of color are undeserving of success is often embedded in this sentiment.

Then he said that Black on White crime is also very prevalent and that we should stop killing them because of their race, and that I have Black privilege. At that point, I was like… I didn’t want to know what he meant by that. If there is Black privilege, I haven’t seen it. I would like some. – Male respondent

“Why are you still calling yourself African American? You’re no more African than I am Australian!” and I was like, it’s not my fault that I was cut off from my heritage. I did not choose that life, but instances like that are where it gets sensitive. – Female respondent

I see a lot of people have problems with Porter Scholarship. That was something that was brought up in our class and one girl was like “I don’t understand why African Americans can have lower grades than me, then why do they get a scholarship?” – Female respondent

Pathologizing minority culture or appearance

This occurs when people of color are criticized due to real or perceived cultural differences in appearance, traditions, behaviors, or preferences.

I went to a predominantly White school and lived in a predominantly White town in western Kentucky and one of my really close friends told me, “You would be the perfect girlfriend if you were White.” – Female respondent

The manager brought in this Black guy to interview. He was clean cut, he had dreads but they were nice and stuff. Like no big deal, he has dreads. And I know our doctor was like, “Is she going to hire him?” I was listening and I was like “Is this a racial thing?” Cause he looked perfectly fine: clean-cut, nice suit, super nice guy. – Female respondent

Also embedded in this sentiment is the idea that Whiteness is preferred, and consequently there is something negative or shameful about a non-White identity. Hence, microaggressions may include statements that advance pronouncements of apparent Whiteness as complimentary. Our focus group participants overwhelmingly reported statements such as these to be upsetting and insulting.

I was studying with this kid in my sociology class. And we had been studying for a while throughout the quarter and pretty much this time we were studying and he was like, “You know C., you’re not that Black. You’re pretty White.” – Male respondent

Second class citizen / ignored & invisible

This microaggression captures situations in which people of color are treated with less respect, consideration, or care than is normally expected or customary. This category is meant to include both the experience of being treated as a “second class citizen” (e.g., the preferential treatment of White individuals; [ 41 , 42 ]), and the experience of being ignored, unseen, or invisible.

My name is [redacted] and people think it’s difficult for people to say, and some people assume that it’s ghetto even though it is a last name. Whenever she [her former manager] would see me or ask me to do something she would be like, “Oh, I can’t think of your name.” It was going on for weeks to the point that it was getting ridiculous. I think that she felt like that because my name was harder or different that she didn’t need to try and learn it. She didn’t have enough respect for me to learn my name and treat me like everybody else. - Female respondent

With all the shootings that have been happening in the Black community, I kind of felt a certain way when I didn’t hear anything from my school that there was some kind of support for us. To just acknowledge that there are people that are here that can be affected, but with the Orlando shootings there was a different response. There were emails, there were ceremonies, and I was just like I thought they weren’t allowed to interfere…the first thing I said to myself was like, “They’re not allowed to probably bring it politics and other things into schools. That’s why they didn’t send an email.” But then there was such an overwhelmingly, overwhelming response to the Orlando shootings, I was like, “That’s not the case.” – Female respondent

Connecting via stereotypes

Many focus group participants described awkward situations in which White students attempted to communicate or connect through use of stereotyped speech or behavior, believing that will help them be accepted or understood.

He just came up to me, and he was like so “Wassup?” And he’s like talking with his hands and doing all these [gestures]. Just like wassup, like trying to talk to me but using like things that he thinks like – I guess to connect with me – like cause we’re… I don’t know what it was, but it was just weird and made me feel uncomfortable. Um, so I just asked him. I was like, “What, like, what are you trying to say? What are you doing?” And basically I just had to end the conversation. … Why try to use like this hip cool language to try to connect when we could have had like a conversation just as well. – Female respondent

This category can include using racial jokes or even racist epitaphs to try to fit in or as terms of endearment.

She’s Caucasian, and like we hang around a lot of Black people. So she just generally has a pretty Black group of friends, you know, and she’s always dated African American people. And so she feels like it’s ok for her to freely use the N-word. – Female respondent

Exoticization and eroticization

This occurs when a person of color is treated according to sexualized stereotypes, or perceived differences are characterized as exotic in some way. Some examples shared by our participants included the following.

I dated quite a few White women, and I agree that they fetishize us. They don’t really look at me as like a man. It’s ah “Oh, a Black man!” or a stereotypical big dude kind of thing. – Male respondent

I’ve actually been to a few frat parties, and I stopped going because every time I go they’ll be like, “Hey, the Black girl’s here!” They’ll be like, “Hey, can you twerk on me or something?” And I always get that, and I’m just like, ugh. And it’s really sad, because like White women will come up to me and ask, “Can you teach me how to twerk?” – Female respondent

Many participants also shared microaggressions they had experienced surrounding their hair, and the frustration they felt over people asking pointed questions or attempting to touch it.

When I don’t wear my headscarf, I have really curly thick hair. So it’s like, “Ohhh, can I touch it?” No, you can’t touch my hair. Or, yeah, “How do you get your hair like that?” I’m like, “It’s water. Just water.” Or “Is that a wig?” No it’s not a wig, it’s my hair. And then it has taken me awhile to like accept my hair, and how you know curly it is, and it’s high maintenance. And to accept my curl pattern and then to have people tell me, “Oh maybe you should wear your hair straight.” It’s like… it’s like a slap in the face. – Female respondent

These types of microaggressions were not described in Sue et al.’s [ 41 ] original taxonomy, but are similarly represented in a category called “Sexual Objectification” in Sue and Spanierman [ 42 ].

Avoidance and distancing

This occurs when people of color are avoided, or measures are taken to prevent physical contact or close proximity. This includes the exclusion of members of targeted groups through physical distancing. It can also include avoiding close relationships and difficult discussions about race.

We were alternating group leaders to lead discussions about a paper we read for the week. And it was kind of like this random thing, so I was excited when it was my turn to be the group leader because I was interested in the subject. I had spent hours thinking of, you know, thoughtful questions to talk about, and then nobody showed up to my group… There was like five different group leaders, and so everyone kind of dispersed to the other four groups and no one showed up to my group, and I was just in tears because this has happened my whole life. Like no one has ever wanted to hear what I had to say. – Female respondent

I ride the bus every day, and so often like I’ll have like two open seats next to me, and like so much of a person avoids. And they’ll go choose to sit next to someone really close than have, like, have open space next to them. That happens to me a lot. – Male respondent

Environmental exclusion

Certain microaggressions that are more apparent on systemic and environmental levels have been defined previously as “environmental microaggressions” [ 41 ]. Environmental exclusion is a microaggression that occurs when someone’s racial identity is minimized or made insignificant through the exclusion of decorations, depictions, or literature that represents their racial group. It can also be used to describe situations where representations of people of color are not present in the classroom or workplace [ 25 ].

I feel like there isn’t enough representation of prominent Black people anywhere, or people of color. Or see it at all. The news or on the Internet. I mean you can search for it but it’s not going to be like anywhere you can find. – Male respondent

We’re learning about what happens to White people when they get sick for instance. So, a White person is pale when they get anemia. Well, how do you tell if a Black person is anemic? I mean there is a way to tell, but they don’t ever talk about that. So I think that it is mostly geared towards White people, treating White people and not people of color. – Female respondent

Diversity in leadership can be incredibly valuable to students’ interest and engagement. One noted:

I finally have like a Black female professor that, like, I didn’t even realize it until I had her this semester, that I couldn’t really relate and get interested in the topics that I’m studying. I’m interested in them, obviously, but like I couldn’t get interested in them like I am now because she… I relate to her more. And so like when I first walked into my classroom at the beginning of the semester and saw a Black woman like [intakes full excited breath] I was like overwhelmed. I was excited. – Female respondent

Environmental attacks

The category of Environmental Attacks is intended to describe situations in which decorations or depictions pose a known affront or insult to a person’s cultural group, history, or heritage (e.g., buildings named after slave owners, Confederate monuments, Columbus Day). For example, on the topic of Confederate flags, participants reported feeling afraid and uncomfortable:

Like oh my gosh, that’s so uncomfortable. I’m like “uh oh” … It’s like I’m unwanted in that area. You’re just like, oh my gosh, what if they do something to me? They must hate me, they don’t want me to be here. Like maybe, I should leave. – Female respondent

If you were to see a swastika or any other symbol of somebody who went through a similar situation they would immediately take it down, but anything that has to do with pertaining to the Black struggle, what we went through, they don’t really seem to acknowledge it. Just like they arrested that lady, I think it was in South Carolina, when she went up and took that flag down and she got arrested for it. That really makes me mad.. – Female respondent

At one point, members of the executive office at one of the universities had dressed up in stereotypical Mexican garb for a Halloween party. Students expressed feelings of hurt about the event, especially because the university president had participated [ 50 ].

Personally, I felt that although I’m not Hispanic, when he wore the sombrero and threw the party I felt it affected me to, because if you can disrespect those students at [this university] then you are disrespecting me as well. – Female respondent

Overall, the students in this study reported a variety of microaggressive experiences on campus, and these caused distress, confusion, and led them to question their perceptions of events. Students were not quick to ascribe racist intentions to perpetrators, but often did so after careful evaluation of the situation and many times opted to ascribe no motivations to offenders at all. This is consistent with Essed [ 11 ], who explains that accounts reflect interpretations of reality-based inferences from the target’s general knowledge, and rational comparisons between racist and non-racist situations. The pain, frustration, and helplessness which racism often causes are strong incentives to carefully examine an event before judging it discriminatory, and lends further support to the need for as comprehensive a taxonomy as possible.

The accounts shared by our participants are not unlike accounts from other Black university students. In one sample of Black students attending a PWI Midwestern campus, students described their uncertainty and withdrawal from the heavy pressure to speak for a homogenous Black experience in light of both faculty and classmate pressure to do so [ 45 ]. In qualitative studies across the United States, including Ivy League universities, Black students report a variety of experiences that saturate both campus and social environments adjacent to schools that emphasize a lack of belonging, and Black men describe specific Black misandry that served as a constant sources of environmental stress [ 38 , 39 ]. Young Black women’s experiences emphasize the challenging, narrow range of expectations and stereotypes, ranging from exotic sexualization to an expectation of strength or irrational anger [ 24 ]. These findings highlight the taxing necessity for Black college students to carefully monitor their environments for signs of threat, while simultaneously restricting and monitoring their own behavior to avoid the pitfalls of fulfilling a stereotype that leads to further racist mistreatment.

Subtle forms of racism, such as microaggressions, can be difficult to identify, quantify, and rectify because of their nebulous and unnamed nature. Although racial maltreatment exists on a continuum of discriminatory action ranging from gross and intentional to tiny unconscious slights [ 12 ], there is a need for a unified language in the study of the experience of this form of covert racism. The burgeoning research on the topic of microaggressions, while important in identifying the vast scope and depth of the problem, has made it increasingly difficult to identify such a common language that integrates multiple perspectives and provides an opportunity to adequately capture emerging categories. Our study identified 15 common categories of microaggressions as experienced by people of color, including the 9 originally described by Sue et al. [ 41 ].

In comparing our findings to Sue and colleagues’ 9 categories, which are also a part of the Sue and Spanierman [ 42 ] taxonomy, we find many similarities, and some notable differences as well. Sue et al’s “Alien in Own Land” was split into two distinct categories, “Not a True Citizen” and “Racial Categorization & Sameness” to differentiate questions about nationality to those surrounding ethnicity and race. Our category, “Assumptions About Intelligence, Competence, or Status” directly maps onto Sue et al.’s “Ascription of Intelligence,” with the addition of ascription of social class. Our category “False Colorblindness / Invalidating Racial or Ethnic Identity,” maps onto Sue et al.’s “Color blindness,” with the specification that colorblindness is only negative when it serves to invalidate an important facet of a person’s identity. Our category “Criminality or Dangerousness” directly maps onto Sue et al.’s “Criminality/assumption of criminal status” with no difference, and “Denial of Individual Racism” is identical to Sue et al.’s category of the same name, and likewise “Myth of Meritocracy,” which we clarify by adding “Race is Irrelevant for Success.”

We added a category called “Reverse Racism Hostility,” which in some ways extends “Myth of Meritocracy.” This category is represented in the literature by Lewis et al. [ 23 ] conceptualization of “White Resentment and Hostility about Affirmative Action” toward people of color and Clark et al.’s [ 3 ] theme of “Withstanding Jealous Accusations” in relation to indigenous people in Canada.

Our category called “Pathologizing Minority Culture or Appearance” extends Sue et al.’s category called “Pathologizing cultural values/communication styles,” by adding judgements about appearance. Our category called “Second Class Citizen / Ignored & Invisible” is the same as Sue et al.’s “Second-class citizen” but we added invisibility to the name to underscore that being unseen is also prevalent among people of color, especially Black women (e.g., [ 24 ]). Other new categories were “Connecting via Stereotypes” which has been noted in the literature in various contexts (e.g., [ 13 ]), and “Exoticization and Eroticization” which has come up repeatedly in both the quantitative and qualitative literature (e.g., [ 22 , 29 ]). As noted previously, Sue and Spanierman [ 42 ] added a category called Sexual Objectification, but this only refers to women, whereas men of color are often sexually objectified as well.

We also added “Avoidance and Distancing” which is captured only a little by Sue et al.’s “Criminality/assumption of criminal status,” but this category seemed inadequate because there were many reasons apart from danger that people of color may be avoided [ 14 ]. We split Sue et al.’s “Environmental microaggressions” into two categories, the first focusing on macro-level exclusion and the second called “Environmental Attacks.” We split this from the larger category of environmental microaggressions to capture these particularly hurtful and often frightening depictions [ 7 , 27 ], which have been an ongoing source of consternation, public attention, and institutional resistance [ 5 , 50 ].

Finally, although we found evidence for a “tokenism” category, we did not have enough responses to formalize this. Tokenism is often described as the inclusion of individuals only because of their race for the illusion of inclusivity [ 25 ]. While this theme has been documented in the literature surrounding racial aggression, it was not specifically addressed by the moderators during the focus groups, thus the data did not yield exemplary material that would fall into this category. It is also not discussed by Sue et al. [ 41 ] or Sue and Spanierman [ 42 ].

The IPA approach utilized in this study may differ from expectations of those familiar with IPA research. Particularly, the final number of themes (15) is greater than the general approach to the identification of meta-themes most common in qualitative work. This is an artifact of the researchers’ goals and philosophy in approaching the topic. That is, this is not only an elaboration of themes revealed in the discussions of the focus groups, it is also an attempt to consider themes at a common level of analysis with existing microaggressions literature. This is reflected in the greater frequency of specific microaggression types in empirical research compared to the less frequent utilization of proposed meta-categories of microaggressions (i.e., microassault, microinsult, and microinvalidation; [ 41 ]).

Limitations and future directions

This study is not without limitations. The sample included self-identified predominately Black students from three institutions in only two geographical regions. Some types of microaggressions are more common for Black people than people in other ethnoracial groups [ 42 ]. Future work on this topic may result in an updated taxonomy that accounts for the increasing intersectionality of marginalized identities such as gender, sexual orientation, or religion. For example, Donovan et al. [ 9 ] assessed the intersectionality of race and gender among female graduate and post-graduate students, and Weber et al. [ 46 ] interviewed graduate students that identified as sexual minorities. These studies explicated unique categories not represented here but relevant for those specific groups.

This paper has focused on a classification system based the actions of perpetrators, but there may be better and more equitable ways to classify these behaviors. For example, in some situations it may be better to classify microaggressions based on the intention of the perpetrator (e.g., superordinate forms of microaggressions; [ 15 , 41 ]) or the impact on the victim (e.g., [ 3 ]). Likewise, future research should examine the differential harms to victims resulting from the different types of microaggressions described herein.

Conclusions

Without an adequate understanding of the illusive dynamics of subtle racism, microaggressions will remain invisible and harmful to the well-being, self-esteem, and standard of living of people of color. While previous literature has either embraced the taxonomy developed by Sue et al. [ 41 ], or proposed a novel taxonomy unique to specific data, this study utilizes the Sue et al. [ 41 ] and Sue and Spanierman’s [ 42 ] framework as a starting point toward understanding our own focus group findings. We also move that work forward by splitting the original “Alien in One’s Own Land” and “Environmental Microaggressions” into two categories, and drawing attention to the need to further examine microaggressions that typify connecting though stereotypes and tokenism.

Although this paper is not the last word on how to best categorize microaggressions, we hope this serves as a step in the right direction and call for more work in this area based on a systematic review of research of studies to date. Ultimately, a unified language of microaggressions may better allow for improved measurement of this construct in both qualitative and quantitative studies. It may also facilitate self-report of microaggressions by aggressors to better enable them to honestly and earnestly explore personal biases and minimize the associated negative social outcomes. It may further relieve the onus of those who are the recipients of repeated microaggressions to “prove” the validity of their perceptions and experiences [ 1 ].

It is our hope that this work will contribute to moving the field toward a shared language of microaggressions, and thus a consensus will emerge across multiple fields of interest surrounding the study of prejudice and racism.

Availability of data and materials

Data is available from the corresponding author (MTW) by reasonable request.

Abbreviations

Grade point average

Hypothalamic-pituitary-adrenal

Interpretative phenomenological analysis

Institutional Review Board

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Acknowledgements

The authors would like to acknowledge Chandler Smith for transcription work.

Funding for this study was provided in part by a Visionary grant to Monnica T. Williams from the American Psychological Foundation and the Canada Research Chairs Program. The funders had no role in the study design, data collection, analysis, interpretation of data, or writing the manuscript.

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Williams, M.T., Skinta, M.D., Kanter, J.W. et al. A qualitative study of microaggressions against African Americans on predominantly White campuses. BMC Psychol 8 , 111 (2020). https://doi.org/10.1186/s40359-020-00472-8

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Expert Commentary

Research raises new questions about missing and murdered Indigenous women

The bodies of Native American women, when found, are most likely to be categorized as unidentified in the National Missing and Unidentified Persons System, a study finds.

Republish this article

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource April 26, 2023

This <a target="_blank" href="https://journalistsresource.org/criminal-justice/indigenous-women-missing-unidentified-research/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

An analysis published recently in the Criminal Justice Policy Review offers new insights and raises new questions about the national public health crisis of missing and murdered Indigenous women in the U.S. — and the news media’s role in helping authorities solve these cases.

When found deceased, Native American women’s bodies are 135% more likely to be unidentified than the bodies of women of other racial or ethnic groups in the U.S., according to the analysis, which examines cases reported to the National Missing and Unidentified Persons System from 2009 to 2018.

Researchers also find that women, regardless of their race or ethnicity, are much more likely to be found dead and unidentified in urban areas than in rural ones.

Nikolay Anguelov , one of the authors of the paper, says the findings underscore the need to correct the myth that Indigenous women tend to live in remote parts of the country such as Alaska or on tribal lands, including reservations such as the Navajo Nation reservation , which spreads across 27,000-plus square miles of Arizona, New Mexico and Utah.

Of the estimated 9.7 million people in the U.S. who identify as American Indian or Alaska Native, 13% live on tribal lands , data from the 2020 U.S. Census shows.

Most Native American women live in urban areas, which is where they are most often reported missing and their remains, when discovered, are most often unidentified, says Anguelov, a political economist and associate professor of public policy at the University of Massachusetts, Dartmouth.

“This is the story you never hear,” he says. “There seems to be a migration out of Native lands that’s making women vulnerable.”

Anguelov and coauthors Morgan Hawes , of Bridgewater State University, and Danielle Slakoff , of Sacramento State University, examined 7,454 cases of women of various demographic backgrounds who had been reported missing or whose remains had not yet been identified.

White women comprised 65% of those two types of cases in the National Missing and Unidentified Persons System, or NamUs. About 2% involved Native American women aged 18 years and older, the researchers write in their paper, “ Understanding the Missing and Murdered Indigenous Women Crisis: An Analysis of the NamUs Database ,” published in March 2023.

Some of the other main takeaways:

• Regardless of race, women were 250% more likely to be found dead and categorized as unidentified in states with relatively high population densities than in states with lower population densities.
• About 48% of all unidentified women’s remains were found in the Northeast, and about 28% were in New England. Meanwhile, about 5% of cases came from the Mountain West, a region that includes Colorado, Montana, North Dakota, South Dakota, Utah and Wyoming and is home to multiple reservations.
• There is “a lack of consistent and reliable information about missing persons at the local, state, and national level,” the researchers write. Ten states require authorities to input data on missing people into NamUs. Other states do so on a voluntary basis.
• Journalists play a key role in spurring change. “The media set the agenda with regard to important societal issues, and the media have the power to make an issue important by deeming it important,” the researchers write.

It’s unclear what exactly has driven Native American women into densely populated areas, although many of those who left their tribal communities probably sought independence, better job opportunities or a place to hide from abusive partners, Anguelov says.

Another unanswered question: Why are Native American women’s bodies least likely to be identified?

One of the many possible reasons: “Maybe they’re starting new far away and don’t keep in touch or they’re estranged, or their family isn’t alive,” Anguelov says.

How news outlets cover female crime victims

News coverage of missing and murdered Indigenous women has been long criticized as spotty and superficial. The news media “largely ignore the victimizations of Native American females,” writes Slakoff, an assistant professor of criminal justice at Sacramento State University, in her 2020 paper, “The Representation of Women and Girls of Color in United States Crime News.”

A growing body of research demonstrates that missing white women typically draw significantly more media attention than missing minority women. The late PBS news anchor Gwen Ifill first used the term “Missing White Woman Syndrome” to describe this disparity in 2004.

Slakoff has written several papers investigating racial bias in news coverage.

In “ The Differential Representation of Latina and Black Female Victims in Front-Page News Stories: A Qualitative Document Analysis ,” published in Feminist Criminology in 2019, Slakoff and coauthor Pauline Brennan examine front-page stories that ran in four major newspapers — the New York Times, Los Angeles Times, Chicago Tribune and Houston Chronicle —  in 2006.

They studied a total of 131 crime stories about female victims who were either white, Black or Hispanic. Seventy-five stories focused on white females, 35 were about Black female victims and 21 were about Hispanic female victims. There were too few front-page stories about females from other minority groups, including Indigenous women and girls, for analysis.

Slakoff and Brennan learned that in addition to publishing more front-page stories about white female victims, news coverage of white female victims was more likely to feature “sympathetic narratives.”

“In the stories about Latina and Black women and girls, we commonly saw themes around them being in an unsafe environment, essentially telling the audience that these Latina and Black women and girl victims were in environments that were unsafe. It’s essentially normalizing their victimization,” Slakoff told The Objective , a nonprofit newsroom that reports on inequity in journalism, in a 2021 interview .

“On the flip side,” she added, “in the stories about white women and girl victims, we were seeing mentions of the fact that they were in safe environments, that nothing like this ever happened in this area. So we argue that this really fosters sympathy for the white women and girls. ‘How could they protect themselves if they were already in the safe area? It’s so unexpected.’”

3 tips for journalists

While Slakoff and Hawes, an assistant director at Bridgewater State University’s Office of Institutional Research, could not be reached for interviews, Anguelov shared these three tips for improving coverage of missing and murdered Indigenous women.

1. Call attention to data problems .

Records from the FBI’s National Crime Information Center show that 5,491 Indigenous women were missing as of Dec. 31. According to NamUs, a project of the U.S. Department of Justice, there are currently 261 missing Indigenous women.

Both numbers likely represent a significant undercount. The total number of missing or murdered Indigenous women is unknown, in part because federal databases do not contain comprehensive national data, the U.S. Government Accountability Office reported in 2021 . Also, federal law requires federal, state and local law enforcement agencies — but not tribal law enforcement agencies — to report missing people under the age of 21, but not those over 21.

Anguelov urges journalists to call attention to data discrepancies and problems in how data is collected and made available to the public.

“Just reporting on the fact we need better data is very helpful,”he says.

2. Include advocacy organizations in news stories about missing and murdered women .

“Oftentimes, folks who are in vulnerable situations get information on where to find help from news stories,” Anguelov explains.

He notes that some people might prefer to seek help from a nonprofit organization that’s doing work in the community than a law enforcement agency, especially if the person needing help abuses drugs or lacks authorization to be in the U.S.

He recommends journalists report more often on the efforts of nonprofit groups that assist and advocate on behalf of female crime victims and Indigenous women and girls.

“Raise the visibility of those nonprofits that are out to help marginalized populations,” he says.

3. Report on solved cases of missing and murdered Indigenous women.

It’s difficult for researchers to determine which actions, conditions or other factors are most likely to help authorities solve cases of missing and murdered Indigenous women without more information about cases that already have been solved or otherwise closed.

Once a case is closed, it is removed from NamUs, Anguelov says. Without contacting individual law enforcement agencies and collecting information about each solved case, it’s difficult to know what led investigators to find a missing woman, identify previously unidentified remains or solve a murder.

Journalists, he says, can help fill that gap in information by reporting on successfully resolved cases.

“Right now, we have no data on women who returned, women who survived and solved cases,” he says. “Can someone tell us some of the things that helped?”

Other resources

• The Columbia Journalism Review created AreYouPressworthy.com to raise awareness of racial bias in news coverage of missing people. The tool allows you to estimate how many news stories you’d be worth if you went missing, based on factors such as your race and where you live.
• The National Indigenous Women’s Resource Center in Montana, Coalition to Stop Violence Against Native Women in New Mexico, and Missing Murdered Indigenous Women of North Carolina are some of the organizations working to end violence against Native American women.
• The Journalist’s Resource created an explainer to help journalists understand the importance of tribal sovereignty to Native Americans in the U.S.

The image above was obtained from the Flickr account of  Heather D  and is being used under a  Creative Commons license . No changes were made.

About The Author

Denise-Marie Ordway

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Health Equity Among Black Women in the United States

Juanita j. chinn.

1 Population Dynamics Branch, Division of Extramural Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.

Iman K. Martin

2 Blood Epidemiology and Clinical Therapeutics Branch, Division of Blood Diseases and Resources, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.

Nicole Redmond

3 Clinical Applications and Prevention Branch, Division of Cardiovascular Sciences, National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA.

Black women in the United States have experienced substantial improvements in health during the last century, yet health disparities persist. These health disparities are in large part a reflection of the inequalities experienced by Black women on a host of social and economic measures. In this paper, we examine the structural contributors to social and economic conditions that create the landscape for persistent health inequities among Black women. Demographic measures related to the health status and health (in)equity of Black women are reviewed. Current rates of specific physical and mental health outcomes are examined in more depth, including maternal mortality and chronic conditions associated with maternal morbidity. We conclude by highlighting the necessity of social and economic equity among Black women for health equity to be achieved.

Black women in the United States experienced substantial improvements in health during the last century, yet health disparities persist. Black women continue to experience excess mortality relative to other U.S. women, including—despite overall improvements among Black women—shorter life expectancies 1 and higher rates of maternal mortality. 2 Moreover, Black women are disproportionately burdened by chronic conditions, such as anemia, cardiovascular disease (CVD), and obesity. Health outcomes do not occur independent of the social conditions in which they exist. The higher burden of these chronic conditions reflects the structural inequities within and outside the health system that Black women experience throughout the life course and contributes to the current crisis of maternal morbidity and mortality. The health inequities experienced by Black women are not merely a cross section of time or the result of a singular incident.

Historical Context for the Current Health Experience of Black Women

Race and ethnicity are sociocultural constructs that reflect common geographic origins, cultures, and social histories of groups that are defined by societies in time-dependent contexts. 3–6 Given the social construction of race and ethnicity, racial groups and identity are fluid; they can, and do, change over time and vary across place. 7

No discussion of health equity among Black women is complete unless it considers the impacts of institutional- and individual-level forms of racism and discrimination against Black people. Nor is a review of health equity among Black women complete without an understanding of the intersectionality of gender and race and the historical contexts that have accumulated to influence Black women's health in the United States.

Research consistently has documented the continued impacts of systematic oppression, bias, and unequal treatment of Black women, 5 , 8 , 9 Substantial evidence exists that racial differences in socioeconomic ( e.g. , education and employment) and housing outcomes among women are the result of segregation, discrimination, and historical laws purposed to oppress Blacks and women in the United States.

Black women earn on average $5,500 less per year and experience higher unemployment and poverty rates than the U.S. average for women ( Table 1 ). 10 Moreover, Black women are more likely to be the head of household than their White counterparts, effectively supporting more dependents with fewer resources. 10 Black women live in neighborhoods that are more racially segregated and have lower property values than their White counterparts. 10 , 11 Mortgage lending discrimination (“redlining”), a legal practice in which lenders deny mortgage loans to communities and individuals based on race, resulted in community disinvestment residential segregation. 11 Residential segregation, as Williams and Collins argued, 12 is a fundamental cause of racial disparities in health, operating through many social institutions (including labor markets and education) to affect health.

Descriptive Demographic Statistics for Black Women in the United States, 2018

Data are collected by sex (female).

Data source: https://blackdemographics.com/population/black-women-statistics 10

The intersectionality of gender and race and its impact on the health of Black women also is important. This intersection of race and gender for Black women is more than the sum of being Black or being a woman: It is the synergy of the two. Black women are subjected to high levels of racism, sexism, and discrimination at levels not experienced by Black men or White women. 13–15

In contrast to Black women, White women in the United States have benefited from living in a politically, culturally, and socioeconomically White-dominated society. 1 These benefits accumulate across generations, creating a cycle of overt and covert privileges 16 , 17 not afforded to Black women, such as wage gap differentials 18 and the invisibility of whiteness ( i.e. , not having to think about one's race). 19 , 20 These privileges do not mean that all White women are similarly advantaged nor are all Black women similarly disadvantaged.

These social conditions create the environment for health disparities to exist and persist. They are the social determinants of health, the “conditions in the environments in which people are born, live, learn, work, play, worship, and age that affect a wide range of health, functioning, and quality-of-life outcomes and risks.” 21 Disparities in Black women's health are particular types of health differences “that are closely linked with social, economic, and/or environmental disadvantage.” 21

The history of Black women's access to health care and treatment by the U.S. medical establishment, particularly in gynecology, contributes to the present-day health disadvantages of Black women. Health inequality among Black women is rooted in slavery. White slave holders viewed enslaved Black women as a means of economic gain, resulting in the abuse of Black women's bodies and a disregard for their reproductive health. Black women were forced to procreate, with little or no self-agency and limited access to medical care. 22 The development of gynecology as a medical specialty in the 1850s 23 ushered in a particularly dark period for the health of Black women. With no regulations for the protection of human subjects in research, Black women were subjected to unethical experimentation without consent. 22–24 Even in more contemporary times, these abuses continue. 25 , 26

As a result of this history and the accumulation of disadvantages across generations, Black women are at the center of a public health emergency. Maternal mortality rates for non-Hispanic Black women are three to four times the maternal mortality rates of non-Hispanic White women. 2 In the next section of this article, we highlight some of the physical and mental health disparities that contribute to the current maternal mortality rates. Although discussed separately, physical health and mental health are inextricably linked.

Physical Health

Demographic characteristics.

Black women are diverse in both nativity and ethnicity. 27 They are not a monolithic group; instead, they comprise multiple cultures and languages. For the purposes of this article, “Black women” refers to the collective identities of Black women, including women of different ethnicities. In the data cited here, “Black women” refers to the women included in the original study population.

Black women currently make up ∼7.0% of the U.S. population and 13.6% of all U.S. women. 10 Although, on average, Black women are younger (36.1 years) than U.S. women overall (39.6 years) ( Table 1 ), 10 they have a higher prevalence of many health conditions, including heart disease, stroke, cancers, diabetes, maternal morbidities, obesity, and stress. Life expectancy at birth is 3 years longer for non-Hispanic White females than for non-Hispanic Black females. Infant mortality rates for children born to non-Hispanic Black women are twice as high as those for children born to non-Hispanic White women 1 ( Table 2 ).

Descriptive Health Statistics for Women

Maternal mortality and pregnancy-related mortality are per 100,000 live births.

Infant mortality rates are per 1,000 live births.

Data sources:

As adults age, their health declines. Aging is affected not only by chronological age but also by biological, behavioral, sociocultural, and environmental factors. 31 Stress, an important factor in aging, is affected strongly by exposure to the built and social environments. Geronimus et al. posit the weathering hypothesis , that is differential exposures to stressful environments are a major factor in widening health disparities as individuals age. They suggest that Black–White disparities in health widen with age because of the accumulation of socioeconomic disadvantages and experiences with racism among Black women throughout the life course. 31–35 Evidence for the weathering hypothesis includes the finding that babies born to Black women in their teens are at lower risk of infant mortality than babies born to older non-Hispanic Black women, the reverse of what is observed for non-Hispanic White women. 31 More recently, Geronimus et al. found that among women aged 49–55 years, telomere length (a biomarker of aging) indicates that Black women are 7.5 years biologically “older” than White women. Perceived stress and poverty account for 27% of this difference. 33

The relatively high levels of morbidity and mortality among Black populations in the United States are, in large part, caused by obesity, which increases the risk of stroke and various CVDs. 36–38 Obesity is a major source of morbidity and mortality for all U.S. populations, but non-Hispanic Blacks have a higher age-adjusted prevalence of obesity than any other racial/ethnic group, with estimates ranging from 34% to 50%. 39 Patterns of obesity vary by many factors across and within races, including location, gender, and educational attainment. 40 Unlike other demographic groups, higher levels of income are not protective against obesity among non-Hispanic Black women. 39 This difference in the prevalence of obesity as reflected in national adiposity data on Black women is the result of the complex multilevel interplay of the measurable and difficult-to-measure social determinants that affect health disparities. Furthermore, Black women lose less weight than other subpopulations do in behavioral weight loss intervention research, 41 and they have a positive body self-image at higher weight levels, which may be psychologically healthy, but also diminishes their motivation to lose weight. 42 These findings support the need for interventions that integrate biological, sociocultural, and environmental factors that influence obesity. 41 The high prevalence of obesity among Black women 36 , 37 impacts the prevalence rates of stroke and various CVDs. 38

Cardiovascular disease

After 50 years of declines in CVD mortality, declines stalled in 2011, with CVD mortality increasing starting in 2015. 43–45 Despite changes in the overall CVD mortality rates, racial and sex disparities persist. Compared with White women, Black women have higher rates of CVD mortality, which have been attributed to poorer cardiovascular (CV) health and a higher burden of modifiable risk factors and clinical comorbidities. 46 , 47 Furthermore, the accumulation of both clinical and behavioral CV risk factors and the manifestation of CVD at younger ages for Black women compared with other racial and ethnic groups—that is, during young adulthood and middle adulthood—have significant implications for maternal and infant health. 48 Understanding the drivers of disparities in CVD among Black women requires examining the intersection of sex as a biological variable 49 and multi-omic influences ( e.g. , genetic ancestry 50 and epigenetic characterization) with multilevel 51 ( e.g. , biological ancestry characterization, individual, interpersonal, community, and society) social constructs ( e.g. , race, ethnicity, and gender).

Although differences in CVD incidence, prevalence, morbidity, and mortality by sex and race/ethnicity are well documented, research on the contributions of genetic factors is limited. People of African ancestry have been underrepresented in genomic research. 52 Furthermore, in genomic studies, analyses of sex chromosomes and the interaction between sex hormones and genetic characteristics are rarely included. 53 Therefore, significant concerns exist about the potential for precision medicine efforts, such as polygenic risk scores, to exacerbate CVD health disparities when using precision medicine research that relies on genetic studies that had inadequate participation from populations with African ancestry. 54

Optimizing such behavioral factors as diet, physical activity, sleep, smoking, alcohol use, emotional health, and stress management is important to maintaining CV health (primordial prevention) and reducing CVD risk (primary and secondary prevention). 55–59 Compared with non-Hispanic White women, non-Hispanic Black women aged 20 years and older have a higher prevalence of several clinical risk factors for CVD, including obesity, high blood pressure, and diabetes. 60

Sleep disparities may contribute to racial/ethnic disparities in CVD. 61 , 62 Blacks have a higher likelihood of short or prolonged sleep durations, obstructive sleep apnea, insomnia, and other measures of poor sleep quality. A study of women of childbearing age showed that, despite Black women having poorer self-reported sleep quality, they were less likely than other women to report their sleep disturbances to a physician. 63 Sleep disturbances may be a manifestation of altered stress reactivity resulting in activation of the chronic stress response and resultant elevations in cardiometabolic disease. 64

Bleeding and blood disorders

Diseases of the blood are as numerous and complex as the fields of hematological physiology and pathophysiology. Benign blood disease include anemia (iron deficiencies), sickle cell anemia (SCD), glucose-6-phosphate dehydrogenase disorders, and hemophilia, among others. Malignant blood diseases (cancers of the blood) include acute myeloid leukemia, acute lymphocytic leukemia, multiple myeloma, non-Hodgkin lymphoma, Hodgkin lymphoma, myeloproliferative neoplasms, and myelodysplastic syndrome. Well-documented differences exist in the prevalence, treatment experiences, and outcomes across races and ethnicities for most benign blood diseases, 65 , 66 and interest in observed disparities in malignancies of the blood is emerging. 67 , 68 Black women are disproportionately impacted by SCD and its complications, as well as by anemia (almost all forms), and they have poor outcomes associated with ancestrally linked disorders, such as G6PD. 69 , 70

Maternal morbidity and mortality

It is estimated that non-Hispanic Black women are three to almost four times more likely to die while pregnant or within 1 year postpartum than their non-Hispanic White and Latina counterparts. 2 The racial disparity in mortality persists at every education level 2 and has persisted or increased over time. 71 As detailed in the sections above, Black women have elevated prevalence rates of chronic conditions associated with higher risk of severe maternal morbidity and mortality. 72 Some of the leading causes of maternal morbidities resulting in pregnancy-associated death occur more in non-Hispanic Black women ( e.g. , hemorrhage, infection [sepsis], thrombotic pulmonary/other embolism, and pregnancy-associated hypertensive disorders). 72 However, changes in the prevalence of these risk factors do not fully account for the increasing trends in severe maternal morbidity 73 and subsequent mortality among non-Hispanic Black women over time. 73

Examination of nonclinical factors, such as hospital quality 74 , 75 (the degree to which health services for individuals and populations increase the likelihood of desired health outcomes) and access to quality care, helps to explain some of the disparities in maternal mortality. Howell et al. 74 , 75 found that women from racial and ethnic minority groups give birth in lower quality hospitals and in hospitals with higher rates of severe maternal morbidity. Using a simulation model, they found that if non-Hispanic Black women gave birth at the same hospitals as non-Hispanic White women, the non-Hispanic Black severe maternal morbidity rate would decrease by 47.7%, from 4.2% to 2.9% (1.3 events per 100 deliveries per year). 74 , 76–79 Qualitative research reveals that many non-Hispanic Black women giving birth in low-performing hospitals experience poor patient–provider communication and difficulties in obtaining appropriate prenatal and postpartum care. 74 , 75

Additionally, homicide is a leading cause of death during pregnancy and postpartum, yet it remains understudied. Typically, homicide is not captured in examinations of pregnancy-related deaths or maternal mortality. Wallace et al. 80 argue that failure to identify and address factors underlying pregnancy-associated homicide will perpetuate racial inequity in mortality during pregnancy and the postpartum period.

Mental Health

National epidemiological surveillance systems that capture information on health risk behaviors and mental health care access—including suicide attempts/occurrence, depression, anxiety, and clinical encounters that record concerns associated with mental health and substance abuse—have notable limitations. Measurement of race and gender across mental health studies varies considerably, creating a dearth of longitudinal research on the nuances of the mental health status of Black women. Even if the experiences of Black women as a racial–gender subgroup are captured with sufficient statistical power to report stratified results of survey findings ( Table 2 ), the results must be interpreted through the lens of the full scope of Black women's experiences in the United States.

Racial discrimination is a toxic “uncontrollable or unpredictable” stressor that is associated not only with poor physical health but also with psychological stress. 76–78 , 81 – 85 Chronic stressors reduce coping resources and increase vulnerability to mental health problems. 76 , 85 Non-Hispanic Blacks with higher levels of multiple stress measures are less likely to achieve intermediate or ideal levels of overall CV health. 86 Research suggests that chronic exposure to environmental stressors, such as racism, across the life span contributes to the weathering of the health of Black women, increasing their allostatic load and, consequently, compromising their reproductive health. 76 , 77 , 81–85 Allostatic load is a measure of the physiological dysregulation that results from cumulative chronic stress on the body. 76 , 87 It is a relevant measure for health disparities research because it can be utilized to assess racial/ethnic differences in biological responses to stressors and their relationship with adverse health outcomes. 83

Maternal mental health

Perceived stress from chronic experiences of discrimination has been found to be a significant predictor of poor birth outcomes. 76 Indeed, non-Hispanic Black women are twice as likely to have a low-birth weight infant than non-Hispanic White women. 76 Non-Hispanic Black women are at a disadvantage regarding the protective factor of the early initiation of prenatal care, with 67% participating in prenatal care in the first trimester compared with 77% of non-Hispanic White women and 81% of Asian women. 76 This is problematic, given that the delivery of perinatal mental health services is critical, particularly for non-Hispanic Black and Latina women because they experience higher rates of depression and anxiety during pregnancy and are at greater risk of poor pregnancy outcomes. 76 , 77 , 81–84 , 88 , 89 Perinatal depression has been linked to risks for adverse maternal and birth outcomes, including preeclampsia, gestational diabetes, preterm birth, and low birth weight. 76 , 90–92 Specifically, it is estimated that up to 28% of non-Hispanic Black women experience perinatal depression. 89

Conclusions

The health of Black women is measured in their disproportionally poor health outcomes, but it is a result of a complex milieu of barriers to quality health care, racism, and stress associated with the distinct social experiences of Black womanhood in U.S. society. Black women are characterized by incredible resilience in the face of adversity and continue to experience improvements in health, even with the socioeconomic contexts that allow disparities to persist. Despite recent mandates by the National Institutes of Health (NIH) to enhance the inclusion of women and racial/ethnic groups that are underrepresented in biomedical research in all NIH-funded research projects, 66 Black women continue to be underrepresented, 93–96 and the resulting interventions may not reflect the unique needs of Black women. Moreover, there is a dearth of current and accessible data on Black women that examines the diversity of Black women (nativity, ethnicity, and country of ancestry). Demographic and health data at the intersection of race and gender are critical to understanding the trends and opportunities for intervention and prevention.

Racism and gender discrimination have profound impacts on the well-being of Black women. Evidence-based care models that are informed by equity and reproductive justice frameworks (reproductive rights as human rights) 76 , 84 need to be explored to address disparities throughout the life course, including the continuum of maternity care, and to ensure favorable outcomes for all women. 79 Interventions to enhance patient–health care provider interactions include raising awareness about the implicit biases that a provider may hold. 97 Black women have continued to make significant inroads in many disciplines yet remain one of few demographic groups that must advocate for themselves to receive consistent and high-quality care. We have outlined disparities in several health conditions and the dire mortality outcomes experienced by Black women. Health does not exist outside its social context. Without equity in social and economic conditions, health equity is unlikely to be achieved, 98 and one cost of health inequality has been the lives of Black women.

Acknowledgment

The authors extend their enormous gratitude to Dr. Beda Jean-Francois for her tireless work and feedback on this article.

The views expressed in this article are those of the authors and do not necessarily represent the views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development; the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

The Woman in White

Wilkie collins, ask litcharts ai: the answer to your questions.

Walter Hartright , a young drawing teacher who lives in London, needs a job and an escape from the city for the autumn months. One night he goes to visit his mother and sister, Sarah , and is surprised to find his friend Professor Pesca , a cheerful Italian whom Walter once saved from drowning, waiting for him at the Hartright’s family home. Pesca tells Walter that he has found a job for him teaching art to a pair of young ladies in Cumberland, at a place called Limmeridge House, in the employment of a man named Mr. Fairlie . Walter is somewhat uneasy about the job but accepts.

On his last night in London, Walter visits his mother’s house to say goodbye and walks home across Hampstead Heath. On the road he meets a young woman dressed head to toe in white clothes . She asks him the way to London and walks with Walter to the city. On the way, she asks Walter if he knows many powerful men there, and mutters something about a certain Baronet. Walter tells her he is only a drawing master and does not know anyone of rank. He tells her that he has just taken a job at Limmeridge House and is surprised to learn that the woman has been there and that she speaks fondly of the late Mrs. Fairlie . The woman asks Walter if he will help her find a cab once they get to the city; Walter agrees, and he finds one quickly when they reach London. As the cab drives off, another carriage passes Walter, and the man inside leans out and shouts to a nearby policeman. He asks him if he has seen “a woman in white,” as this woman has recently “escaped from an asylum.”

Walter travels to Limmeridge House to start his job. He does not like Mr. Fairlie, who is a pretentious man, but gets on well with his pupils, Marian Halcombe and Laura Fairlie . Immediately, Walter notices that Laura reminds him of someone. He also tells Marian about the woman in white, as Marian is the late Mrs. Fairlie’s daughter, and Marian looks through her mother’s letters to see if she can find any reference to this woman. One night, when Walter and Marian are in the drawing room and Laura is outside, Marian discovers that one of her mother’s letters describes a little girl who came to the school at Limmeridge, where Mrs. Fairlie taught. Mrs. Fairlie’s letter notes that she thought this girl, Anne Catherick, was strange but very sweet and gave her some white dresses to wear. At this moment, Laura comes inside from the garden, and Walter suddenly realizes that Laura looks like the mysterious woman in white.

Walter and Laura begin to fall in love. This seems to make Laura very sad, and one day, Marian takes Walter aside and tells him that Laura is engaged to marry a Baronet named Sir Percival Glyde . She kindly tells Walter that he should leave Limmeridge because Sir Percival is expected to arrive in the next few days to make plans for the wedding. Walter is heartbroken but reluctantly agrees. While they are talking, a maid summons Marian back to the house because Laura is very upset—she has received an anonymous letter warning her not to marry Sir Percival. Marian and Walter ask around in the village to see if anyone knows who sent the note, and they discover a woman in white has been seen near Mrs. Fairlie’s grave. Knowing this must be Anne Catherick, Walter decides to hide in the churchyard that night so he can speak to her if she comes back to Mrs. Fairlie’s grave. His plan works, and he manages to speak with Anne, but she becomes extremely angry when Walter mentions Sir Percival’s name. Unable to calm her, Walter leaves Anne with her companion, an older woman named Mrs. Clements , and the next day he returns to London.

Sir Percival Glyde comes to Limmeridge House to arrange his wedding. Laura is reluctant to marry him, but she has promised her father on his deathbed and feels too guilty to break the engagement. Sir Percival seems charming and considerate, but Marian still does not like him. She finds him bad tempered with the servants, and Laura’s friendly dog always barks at him, which seems to be a measure of his character. Hoping to get out of the engagement, Laura tells Sir Percival that she does not love him, and that she loves someone else, and offers him the chance to break off the engagement; however, Sir Percival delights in her honesty, confesses his undying love for her, and the wedding goes ahead as planned. In the days that follow, Mr. Gilmore , Laura’s lawyer, arranges the marriage settlement. This settlement states that, if Laura dies without an heir, Sir Percival will receive twenty thousand pounds and Limmeridge House, while Laura’s aunt, Madame Fosco , will receive ten thousand pounds. After the wedding, Laura and Sir Percival set off on their honeymoon to Europe, where they plan to meet up with Laura’s aunt and her Italian husband, Count Fosco . Marian arranges to meet the newlyweds on their return at Sir Percival’s house at Blackwater, where she will live with them.

Many months later, Laura and Sir Percival arrive home at Blackwater with Sir Percival’s friend Count Fosco and his wife. Marian and Laura both deeply dislike the Count and are very afraid of him. His wife behaves suspiciously too and submissively does everything the Count says. Marian also finds that Sir Percival’s demeanor has completely changed; instead of the charming (albeit off-putting) man who sauntered around Limmeridge declaring his undying love for Laura, Sir Percival is now extremely irritable and bad tempered, especially toward his new wife. At one point, he tries to force Laura to sign a document without telling her what it is (he has folded the paper so that only the signature line is visible), and becomes aggressive when Laura refuses to sign. Sir Percival’s combative mood is made worse when he hears that Anne Catherick is in the area, and he becomes determined to find her. One day, on a walk to the boathouse near the lake in the grounds, Laura meets Anne Catherick, who tells her that she knows a secret about Sir Percival. Laura agrees to meet Anne the next day. When she tries, however, Sir Percival follows her, drags her home, and locks her in her room. He tries to force her to sign the document again but Count Fosco stops him. Meanwhile, Marian has become deeply suspicious about Sir Percival and Count Fosco’s motives towards her sister. She tries to write to Mr. Fairlie and Mr. Kyrle (the girls’ new lawyer) for help on several occasions, but Madame Fosco intercepts the letters. One night, Marian overhears Sir Percival and Count Fosco in the garden and hears them discuss plan to murder Laura for her fortune. Unfortunately, Marian gets soaked in a rain shower while crouching on the roof to listen and becomes ill with typhus.

While Marian is ill, Count Fosco and Sir Percival continue their hunt for Anne Catherick. One day, the housekeeper, Mrs. Michelson , sees Count Fosco come in from a walk and Sir Percival asks if he has found her, at which Count Fosco smiles. Sir Percival sends Mrs. Michelson away to look at seaside houses for him to rent and, when she returns, she is told that Marian has been sent to Limmeridge, and that Laura will follow suit the next day. All the servants are to be dismissed, and the house is to be shut up. Mrs. Michelson is shocked but takes Laura to the station and sees her off on the train to London. When she arrives back at Blackwater, she discovers that Marian is still at the house and that Laura has been tricked. When Laura gets to London, she is taken to stay with Count Fosco, but dies the next day from heart failure.

Several months later, Marian hears that Anne Catherick has been returned to the asylum and goes to visit her to see if she can find out about Sir Percival’s secret. When she arrives, she discovers that it is not Anne in the asylum but Laura, who has been disguised against her will as Anne. Marian breaks her sister out of the asylum, and they return to Limmeridge, but find that everyone there believes that Laura is dead. In the churchyard, where Anne has been buried in Mrs. Fairlie’s tomb, they meet Walter Hartright, who has returned to mourn for the woman he loves.

Marian and Walter move to London, and Walter decides to investigate Sir Percival Glyde to see if he can uncover his secret. He visits Mrs. Clements, and she tells him that it has something to do with his being caught “in the vestry of the church” in Welmingham with Mrs. Catherick . Walter then visits Mrs. Catherick , Anne’s mother, and, when he mentions the vestry to her, can see from her reaction that the secret is in fact hidden there. He goes to Welmingham and finds that the church marriage register has been forged: Sir Percival’s parents were never married, making him an illegitimate child, and he is not a Baronet at all. Walter runs to the nearby village to check this information in the second copy of the marriage register, and the forgery is confirmed. When he returns to the church that night, Walter is startled to find that it is on fire, and that Sir Percival, of all people, is trapped inside. He has accidentally set the church alight while trying to destroy the forgery and is killed in the blaze. After Sir Percival’s death, Mrs. Catherick writes to Walter and tells him that Anne never knew the secret, but that Sir Percival locked her in the asylum just in case she did know it. In the midst of all of this chaos, Walter and Laura marry.

Now that Sir Percival is dead, Walter goes after Count Fosco. He tracks him down one night at the opera and takes Pesca with him to see if Pesca, who was once involved in Italian politics, recognizes the Count. Pesca does not, but the Count recognizes Pesca instantly and flees the opera house in fear. He is followed by a foreign man who had been watching Walter and Pesca carefully during the opera. Walter questions Pesca and Pesca confesses that he was a member of a secret political organization in Italy in his youth and suspects that the Count is a traitor to this same organization.

That night, Walter writes Pesca a letter with Count Fosco’s address and tells him to come to this address and kill Count Fosco if he does not hear from Walter before the morning. Walter then goes to the Count’s house and blackmails him into writing a confession of the conspiracy against Laura. The Count agrees to do this if Walter will let him go and intercept the letter to Pesca. The Count then writes a confession which proves that Laura is the real Laura Fairlie, and that Anne Catherick is the woman who died at his house. The Count promptly leaves London, and Walter returns to Laura and Marian with his proof. They can now restore Laura’s identity and prove to her relatives that she is alive. Some months later, Walter gets a job which takes him to Paris. While he is there, he passes the Paris Morgue and sees Count Fosco’s body there. He has been stabbed by the foreign man who saw them at the opera, who is a member of the political organization Count Fosco betrayed. Walter and Laura have a son and, when Mr. Fairlie dies, they move back to Limmeridge House and Walter’s son becomes the heir to the property.

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Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts

• METABOLOMIC EPIDEMIOLOGY
• Published: 04 May 2024

Cite this article

• Emma E. McGee   ORCID: orcid.org/0000-0002-7456-6408 1 , 2 , 3 ,
• Oana A. Zeleznik 1 ,
• Raji Balasubramanian 4 ,
• Bernard A. Rosner 1 , 5 ,
• Jean Wactawski-Wende 6 ,
• Clary B. Clish 3 ,
• Julian Avila-Pacheco 3 ,
• Walter C. Willett 1 , 2 , 7 ,
• Kathryn M. Rexrode 4 ,
• Rulla M. Tamimi 8 &
• A. Heather Eliassen 1 , 2 , 7  

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There is growing interest in incorporating metabolomics into public health practice. However, Black women are under-represented in many metabolomics studies. If metabolomic profiles differ between Black and White women, this under-representation may exacerbate existing Black-White health disparities. We therefore aimed to estimate metabolomic differences between Black and White women in the U.S. We leveraged data from two prospective cohorts: the Nurses’ Health Study (NHS; n = 2077) and Women’s Health Initiative (WHI; n = 2128). The WHI served as the replication cohort. Plasma metabolites (n = 334) were measured via liquid chromatography-tandem mass spectrometry. Observed metabolomic differences were estimated using linear regression and metabolite set enrichment analyses. Residual metabolomic differences in a hypothetical population in which the distributions of 14 risk factors were equalized across racial groups were estimated using inverse odds ratio weighting. In the NHS, Black-White differences were observed for most metabolites (75 metabolites with observed differences \(\ge \) |0.50| standard deviations). Black women had lower average levels than White women for most metabolites (e.g., for N6, N6-dimethlylysine, mean Black-White difference = − 0.98 standard deviations; 95% CI: − 1.11, − 0.84). In metabolite set enrichment analyses, Black women had lower levels of triglycerides, phosphatidylcholines, lysophosphatidylethanolamines, phosphatidylethanolamines, and organoheterocyclic compounds, but higher levels of phosphatidylethanolamine plasmalogens, phosphatidylcholine plasmalogens, cholesteryl esters, and carnitines. In a hypothetical population in which distributions of 14 risk factors were equalized, Black-White metabolomic differences persisted. Most results replicated in the WHI (88% of 272 metabolites available for replication). Substantial differences in metabolomic profiles exist between Black and White women. Future studies should prioritize racial representation.

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Data availability.

Due to participant confidentiality and privacy concerns, requests to access the NHS and WHI data must be submitted in writing and must comply with the data request procedures of the NHS and WHI. Investigators wishing to use NHS data are asked to submit a brief description of the proposed project. Go to https://www.nurseshealthstudy.org/researchers (contact email: [email protected]) for more details on accessing the NHS data. To request use of the WHI data, go to https://www.whi.org/get-started . Statistical code used in this manuscript is publicly available via GitHub: https://github.com/emma-mcgee/racial-differences-in-metabolomic-profiles

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The Nurses’ Health Study analyses were funded by the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (grants UM1 CA186107, R01 CA49449, and P01 CA87969). Census tract variables were ascertained through funding from the National Institute of Environmental Health Sciences, National Institutes of Health, U.S. Department of Health and Human Services (grants R01 ES017017 and R01 ES028033). The Women’s Health Initiative program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. Metabolomic analysis in the Women’s Health Initiative was funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contract HHSN268201300008C. A list of WHI investigators is available online at https://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short%20List.pdf . E.E. McGee was supported by funding from the Eric and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. The funders had no role in the design of the study; collection, analysis, or interpretation of data; writing of the report; or decision to submit the manuscript for publication. The content presented here is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or any other sponsors.

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Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

Emma E. McGee, Oana A. Zeleznik, Bernard A. Rosner, Walter C. Willett & A. Heather Eliassen

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Emma E. McGee, Walter C. Willett & A. Heather Eliassen

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Emma E. McGee, Clary B. Clish & Julian Avila-Pacheco

Division of Women’s Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

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Jean Wactawski-Wende

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Conceptualization and design of the study : EEM, OAZ, CBC, WCW, KMR, RMT, and AHE. Acquisition of data : CBC, JAP, WCW, KMR, RMT, and AHE. Analysis of data : EEM. Interpretation of data : EEM, OAZ, RB, JH, BAR, JWW, CBC, JAP, WCW, KMR, RMT, and AHE. Drafting of manuscript : EEM. Review and approval of final manuscript : EEM, OAZ, RB, JH, BAR, JWW, CBC, JAP, WCW, KMR, RMT, and AHE. EEM had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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The NHS study protocol was approved by the institutional review boards of Brigham and Women's Hospital and Harvard T.H. Chan School of Public Health. Institutional review board approval for the WHI was obtained at each clinical center.

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McGee, E.E., Zeleznik, O.A., Balasubramanian, R. et al. Differences in metabolomic profiles between Black and White women in the U.S.: Analyses from two prospective cohorts. Eur J Epidemiol (2024). https://doi.org/10.1007/s10654-024-01111-x

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Received : 22 November 2023

Accepted : 26 February 2024

Published : 04 May 2024

DOI : https://doi.org/10.1007/s10654-024-01111-x

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