Appendix C

Multiracial Analysis Schemes

To assist in their information gathering, the committee commissioned the following piece. Opinions and statements included in the paper are solely those of the individual author and are not necessarily adopted, endorsed, or verified as accurate by the Committee on the Use of Race and Ethnicity in Biomedical Research or the National Academies of Sciences, Engineering, and Medicine.

A MECHANISM-DRIVEN APPROACH TO CATEGORIZING MULTIRACIAL PARTICIPANTS IN BIOMEDICAL RESEARCH

Sarah Forthal, M.Phil., M.P.H.

In 2000, the US Census allowed Americans to officially self-identify with more than one racial group for the first time (1). Two decades later, the self-identified Multiracial population is measured at 33.8 million—nearly a 500% increase – and represents over 10% of the US population (1–3). In parallel, several prominent biomedical research organizations have initiated programs to understand and eliminate long-standing and unjust racial health disparities (e.g., 4–8). Multiracial people are exposed to systemic racism, both on the basis of their Multiracial and specific racial backgrounds, that increases their risk of several health conditions (9–14). Yet, most of these disparities programs have struggled to incorporate the growing Multiracial population into their research and intervention development.

A critical challenge preventing greater inclusion of Multiracial populations in biomedical research is uncertainty around how to define and categorize Multiracial identity. Studies seeking to identify racial disparities in health routinely exclude or erase Multiracial participants, leaving significant gaps in our understanding of Multiracial health risks and consequentially, underinvestment in addressing them (12). The few studies that do include a Multiracial category in analysis operationalize it differently, creating challenges for interpreting results (12).

Compounding the issue, how studies define, include, or exclude their Multiracial participants can significantly change outcome estimates for other racial groups as well (15–18). For example, a study of men living with HIV found that the approach to categorizing Multiracial participants determined whether a Black-White disparity in experiences of stigma was observed (15).

So how should studies categorize Multiracial participants? Multiracial people have different experiences with racism based on their phenotypes and racial backgrounds (11,19). In addition, Multiracial identity is characterized by the complex interplay of ancestral background, self-identification, societal norms, and external perceptions (20,21), which do not always converge and can be situationally and developmentally fluid (22). Thus, this experience is not easily captured by traditional research methods for racial categorization, which rely on fixed and discrete lines to be drawn between groups for comparisons and are essentialist in nature (23,24).

In this paper, I describe an approach to categorizing the Multiracial population in biomedical research that honors the diversity of this population and improves methodological rigor by employing theoretically grounded measures of race. Echoing foundational work on operationalizing race in sociology (25–27) and the consensus that racial disparities in health are driven by underlying (28) racially-patterned social mechanisms for which race is a proxy (29,30), I argue that there exists no single “best” Multiracial categorization scheme for all biomedical research purposes. Instead, the most appropriate Multiracial categorization scheme should be determined by the hypothesized mechanism linking race and racism to health.

Assumptions Implicit in Categorization of Race

Categorization of race in research is often determined by standard practice and data availability (31), but each choice in fact encodes certain assumptions. First, racial categories assume a shared within-group social identity (32). However, this is particularly challenging to assume for Multiracial individuals, who share identities with multiple groups and may primarily identify with one, all, or none of their component monoracial (i.e., single-race) groups (28,33,34). Further, different racial identities may be more salient for Multiracial people in different contexts (35). For example, some Multiracial people primarily identify as members of their most minoritized monoracial group due to historical or political reasons (33,34). Ultimately, researchers cannot simply assume that all Multiracial people identify with a separate “Multiracial” identity, nor that they identify with any monoracial identity.

Second, racial categorization makes the statistical assumption that outcome risk is similar for participants categorized into the same group and meaningfully different from participants categorized into the other groups (36). For example, comparing risk of asthma between study participants identifying as monoracial Black and monoracial White assumes that risk of asthma is similar within the Black and White groups and meaningfully different between them. This is a reasonable assumption given that Black Americans are on average more likely than White Americans to experience environmental and social stressor exposures associated with asthma, due to historic and current

systemic racism in the US (37). Yet, making this assumption is less straightforward when considering Multiracial populations, who carry with them the experiences of multiple racial groups. Is the risk of a Multiracial Black and White individual more like other Multiracial individuals, other Black, or other White individuals? Or is it a combination of these? A unique experience on its own? Answering these questions necessitates a clear understanding of the underlying mechanisms driving asthma risk and its relationship to the individual’s racial identity. Failure to engage critically with these assumptions may result in under-theorized and unjustified categorization of race.

Potential Mechanisms Linking Race to Health

Race, a socially constructed classification system based on essentialist interpretations of physical traits, has no biological basis and is not a cause of differential health risk in itself (38). Instead, racial disparities in health are caused by several mechanisms rooted in contemporary and historic systemic racism (39). These include racial patterning in exposure to discrimination, unmet treatment needs, other chronic illness, adverse childhood experiences, other traumatic events, including criminal justice system involvement and exposure to violence, and life stressors, including economic disadvantage (40–46). Some of these mechanisms are highly prevalent in Multiracial populations (9,14,43), while others are more highly prevalent in Black, Indigenous, and Latine populations, sometimes including their Multiracial members (47–50).

Racial disparities in health may also be driven by patterning of protective factors such as racial identity affirmation and belonging (i.e., self-identifying as, being in community with, having a sense of belonging in, and having positive attitudes towards one’s racial group(s)) (51). Though relevant to all racial groups (52,53), racial identity affirmation and belonging is particularly prevalent in the Multiracial health literature given common experiences of identity denial and questioning in this population (32,54–59). Researchers investigating racial disparities should always explicitly name the mechanism they hypothesize links race to the health outcome of interest (29).

Outlining a More Theoretically Motivated Approach

Despite its fraught nature, careful categorization of race is critical to identify and act on racial health disparities (60). At the same time, it is clear that traditional research methods for racial categorization become increasingly problematic when applied to Multiracial populations. An alternative approach suggests that the most informative way to categorize Multiracial participants differs based on the mechanism hypothesized to drive the health disparity of interest.

This approach acknowledges that Multiracial individuals experience racialized exposures both on the basis of their Multiracial and specific racial backgrounds, and that different aspects of their identities may be more salient to different mechanisms linking race to health. For example, a study investigating contemporary racial discrimination as the mechanism of interest for a health disparity might consider the categorization scheme that best reflects the diversity of experiences faced by Multiracial people of

different racial backgrounds (11,57,61). On the other hand, a study investigating racial identity affirmation and belonging might group all Multiracial individuals together, regardless of racial background, because threats to this are similarly experienced by Multiracial individuals (32,54–59).

I conducted a review of methodological research on Multiracial categorization approaches and applied research on health disparities in depression (which is my area of expertise and tends to be more inclusive of Multiracial participants) to identify how Multiracial participants have been categorized in the literature to date. Of note, I focus on schemes that can be coded using the 1997 updated Office of Management and Budget’s Statistical Policy Directive No. 15 (SPD 15) self-reported racial and ethnic categories: American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White for race and Hispanic or Latino for ethnicity (62), as studies using these categories have to date been most commonly used to support national health equity programs. However, the principle of mechanism-driven categorization can be applied to any other survey structure, including the 2024 updated SPD 15 which uses a combined race/ethnicity question and includes a new Middle Eastern or North African category (63). The Multiracial categorization schemes identified from the literature are as follows:

1. Grouping all who identify with more than one race, but not Hispanic or Latino ethnicity, into one Multiracial category (16,64–67) This is how the 2020 US Census categorized Multiracial respondents (68) and is very commonly seen in the disparities literature. I refer to this as the “non-Hispanic Multiracial” scheme.

   ➩ Variations:

   1. Grouping all who identify with more than one race, regardless of their Hispanic origin response, in the Multiracial category (58) “Hispanic-inclusive Multiracial” scheme.
   2. Considering Hispanic or Latino ethnicity as a race option when determining who to include in the Multiracial category (15,33,67,69) “Hispanic-as-race Multiracial” scheme.
2. Grouping Multiracial participants into subcategories defined by specific racial identities (e.g., Asian-White; American Indian or Alaska Native-Black) “disaggregated Multiracial” scheme.

   ➩ Variations:

   1. Grouping Multiracial participants into subcategories defined by having or not having White identity (e.g., White-Nonwhite; Nonwhite-Nonwhite) (19) “disaggregated White/non-White Multiracial” scheme.
3. Recategorizing Multiracial respondents into their most socially disadvantaged racial group (16,21,39,40,72,73) “hypodescent” scheme; note that this reflects the legacy of hypodescent, i.e., the historical ‘one-drop rule’ that continues to shape some Multiracial identification today (73,74).
4. Recategorizing Multiracial respondents into their most socially advantaged racial group (33,34) “hyperdescent” scheme.

5. Recategorizing Multiracial respondents into their least populous racial group (24) “rarest” scheme; note that some researchers recommend this to improve precision in estimates for smaller groups that include many Multiracial members, such as Native Hawaiian or Other Pacific Islander and American Indian or Alaska Native (12,24).
6. Recategorizing Multiracial respondents into the single race that they identify best with (24,25,75,76) “best race” scheme.
7. Categorizing Multiracial respondents into all of their component monoracial groups (77) “additive” scheme.

   ➩ Variations:

   1. Categorizing Multiracial respondents into all of their component monoracial groups, plus a Multiracial group (16) “additive + Multiracial” scheme.

Researchers seeking to apply a mechanism-driven approach to categorizing Multiracial participants would first identify the primary mechanism they hypothesize is driving the racial disparity of interest. Then, based on existing evidence and social theory, they would determine which aspect of the Multiracial participants’ racial identity may be most salient to this mechanism, and consequentially, which racial (or Multiracial) category their outcome risk is most likely to be similar to. To illustrate this process, some examples matching Multiracial categorization schemes with the potential mechanisms linking race to health are described below. The mechanisms and categorization schemes listed are not exhaustive and should be only used as a starting point for one’s own research.

Examples: Potential mechanisms driving racial disparities in health and suggested Multiracial categorization schemes

• Racial identity affirmation and belonging (mechanism) Hispanic-inclusive Multiracial (categorization). Individuals identifying with more than one race, regardless of their Hispanic origin response, report relatively low levels of racial identity affirmation and belonging and systematic exclusion from racial identity-affirming communities (32,54–59,78,79). However, because the relationship between race and ethnicity among Hispanic and Latino individuals can be complex (80,81), the “non-Hispanic Multiracial” and “Hispanic-as-race Multiracial” schemes should also be considered plausible. Note that the 2024 revision to SPD 15 mirrors the “Hispanic-as-race Multiracial” scheme in its use of a combined race/ethnicity question.
• Racial discrimination (mechanism) Additive (categorization). Multiracial individuals can experience discrimination directed at their Multiracial or component racial backgrounds (11,57,61). However, because most existing measures of racial discrimination do not include Multiracial-specific forms such as identity denial or questioning, I recommend using “additive” without the Multiracial indicator. If using a measure that includes Multiracial-specific forms of discrimination alongside more traditionally measured ones, consider the “additive + Multiracial” scheme or one of the “disaggregated Multiracial”

• schemes. The “best race” scheme may also be useful here, as it can reflect socially assigned race (12). However, use this with caution as many Multiracial people do not identify with a single race and may refuse to do so (82).
• Unmet psychiatric treatment needs (mechanism) Hyperdescent (categorization). Multiracial Americans access psychiatric treatment at rates similar to White Americans (83,84).
• Chronic illness (mechanism) Additive + Multiracial (categorization). Multiracial Americans have both distinct and shared chronic illness risk profiles with their component monoracial groups (85,86). However, note that the relationship between Multiracial and monoracial risk profiles may differ for specific illnesses. Choose the categorization scheme that best reflects this relationship in each case.
• Adverse childhood experiences, other traumatic experiences, life stressors (mechanism) Hypodescent (categorization). Risk factors include poverty, community violence, and caregiver trauma, all which stem from historical, cumulative, and intergenerational traumas that are more likely to be experienced by less socially advantaged groups (43,87–89).

Conclusion

As the Multiracial population continues to grow, it is critical that the biomedical field adapt its research tools to ensure rigorous inclusion in health equity efforts. In service of this goal, this paper outlined a novel approach to categorizing Multiracial study participants based on the hypothesized mechanism linking race and racism to health. It additionally provided examples of existing Multiracial categorization schemes and their applicability to different potential health disparity-driving mechanisms. By addressing the weaknesses of traditional racial categorization approaches, this mechanism-driven approach has the potential to improve measurement of health disparities and inform more effective interventions to improve the health of Multiracial and monoracial populations alike.

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