Social Science Meets Neuroscience

Race is not a biological construct but a social one.¹ It is a social construct which has become a surrogate measure for a person's likely lived experiences, culture, ancestral heritage, and environmental exposures predisposed to certain medical conditions or socioeconomic risk factors. Race is commonly used as a marker of social drivers of health (SDOH) both in clinical practice and research. In these settings, race seems to correlate with the SDOH, but these 2 concepts are not equivalent,² and work is being performed to better delineate the real SDOH outcomes.

Structural racism is increasingly being recognized as a SDOH and refers to those systems—or remnants of systems—that unintentionally or intentionally disadvantage certain races or ethnic groups in society. For example, in modern-day Columbus, OH, historically redlined areas carry a deleterious legacy effect through a heightened prevalence of stroke for the current residents.³ Structural racism (aka systemic or institutionalized racism) is distinct from individualized or interpersonal racism. Although it is classically thought of as impacting African Americans, it does affect other racial minority groups, though how it does so is less often studied or defined.

Although documenting a social history is commonly used in medical practice, it often fails to capture all the SDOH, including housing, schooling, health care access, and insurance status. It is difficult to document the generational effect of “Jim Crow” laws, or the smoldering distrust of medical institutions that has been fueled by events such as the Tuskegee syphilis study, the Henrietta Lacks cells, the Havasupai Tribe DNA research, the Puerto Rican birth control trials, or the killing of George Floyd. The latter, while not a medical event, sparked wide distrust of all structural systems. Because the medical record is simply not able to capture these nuances, both clinical practice and research using SDOH are often hampered by insufficient information. To combat this, researchers have had to design new studies with a separate tool administered prospectively to patients to capture proxies of these missing elements.⁴ There are a limited number of SDOH screening tools that have been validated in populations with neurologic disease. In addition, comparison across studies and populations is constrained by the lack of standardized common data elements.⁵

However, designing new studies with common data elements for SDOH is expensive in time, talent, and capital, and these studies may be limited when performed on existing data sets or cohorts because they are seldom well characterized. To address the challenge of measuring SDOH, researchers have sought to use existing indirect measures of SDOH (social vulnerability index, area deprivation index, and historic redlining), cross-tabulating them with existing data sets.

In this issue of Neurology®, Polineni et al.⁶ publish a study in which they address the challenge of defining and measuring structural racism in a quantifiable way, allowing for replication in future studies. In their article entitled “Associations Between Measures of Structural Racism and Acute Ischemic Stroke Incidence in the United States,” they introduce us to a new lexicon of valuable social science concepts, including the delta index (the proportion of [minority] members residing in areal units with above average density of [minority] members), dissimilarity index (the percentage of Black people who would have to move to achieve an equal distribution of White and Black people across all blocks within a geographic area), Gini index (a measure of the distribution of minority populations within a geographic area), and isolation index (the extent to which Black members of a block are exposed only to 1 another).⁷ They effectively combined these measures along with 4 other county-level SDOH^8-10 into a novel and concise composite structural racism score with writing that is clear, straightforward, and accessible. They analyzed census population data combined with Medicare fee for service data using this composite score and identified significant geographic variations in structural racism and a direct association between this score and an increased incidence of acute ischemic stroke regardless of race.

Figure compares several tools used to measure structural racism, highlighting their overlapping concepts and features. The composite structural racism score allows for an in-depth analysis of structural racism by incorporating more than the traditional neighborhood-level socioeconomic factors. Still, it does not account for medical distrust or criminal justice indicators. Scores provide a practical way to measure and track interventions, offering insight into changes over time. However, relying on a single measure carries the risk of oversimplifying complex issues such as structural racism, which requires multidimensional approaches to uncover hidden nuances. This study's composite score effectively highlights disparities among Medicare beneficiaries, widening our lens from a social science perspective, but lacks generalizability to younger populations or other minority groups.

Figure. A Comparison of Structural Racism Tools and Their Features.

We designed an original figure to compare several structural racism tools and their features. The sources for the indices included in the figure are cited in the references).^11,12

This article suggests a new path of integrating social science into neuroscience research. It sheds light on key social mechanisms and their interplay with health outcomes, providing a foundation for actionable insights and underscoring the importance of interdisciplinary collaboration in addressing health inequities. Ultimately, we hope everyone—regardless of race—receives the care they need and deserve.

Author Contributions

K. Johnson: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. G.L. Gordon Perue: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design.

Study Funding

The authors report no targeted funding.

Disclosure

The authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.