The COVID-19 pandemic has exposed many vulnerabilities in health care, including how structural racism created the pandemic’s outsize impact on marginalized groups. Age-adjusted infection, hospitalization, and death rates for people of color in the United States were higher than those of white Americans, for example.
One big question for health researchers is how to measure structural racism—the racism built into societal systems including housing, work, and health care—in different places and systems. Epidemiologist Paris “AJ” Adkins-Jackson of Columbia University is among the growing number of scientists working on this.
Adkins-Jackson and her colleagues published a guide in 2021 to measuring structural racism for epidemiologists and other researchers. The authors call on researchers to use variables that capture the multiple dimensions of structural racism. For example, instead of just measuring the segregation in residential housing, researchers could include how local governments and banks implement zoning laws and mortgage policies that discriminate against marginalized communities; those variables in turn influence access to quality public education and healthy food. To capture the spectrum of how racism may play a role in health disparities—and in a departure from traditional epidemiological research—the guide recommends collecting qualitative data, reviewing work in the humanities and social sciences, and partnering with marginalized communities.
“I think science is like tofu,” Adkins-Jackson says. “Whatever seasonings you put in it, it will just sop it right up. So, if you season it with racism, it will become racist. It’s incumbent upon me as a scientist to choose my marinade differently… to season it with multiplicity, season it with different thoughts, season it with change.”
Last month, Adkins-Jackson gave a talk during a 2-day National Academies of Sciences, Engineering, and Medicine workshop on structural racism and social inequity, and showed how methodologies from anthropology and social sciences can inform research on health. This conversation has been edited for length and clarity.
Q: What is structural racism?
A: ace [epidemiologists] Camara Jones and Zinzi Bailey teach us, structural racism is … institutional policies and practices that unfairly minoritize and disadvantage certain groups while unfairly advantaging persons racialized as white. Such a system was historically meant to create white privilege and cannot be disentangled from the foundations of European colonization.
Q: What was your path to studying it with a heath angle?
A: I’m a Black woman raised by Salvadorians in south Los Angeles, and I remember asking my mom why our neighborhood had a curfew during the 1992 Los Angeles riots. No one really talked to me about what racism meant. So, it started from this curious place of, “Why are we in the circumstances that we live in?”
In high school, journalism gave me a home. I thought, “I could be Khadijah James,” the character from the TV show Living Single who is a journalist and started a magazine to give a voice for the unheard people. I needed more history and more context, so I took all those journalistic skills straight into anthropology. But cultures and communities cannot thrive without life: If I want to enjoy all that culture, eat all the food, study all the books, learn all the languages, then I have to preserve their life and that’s why I got into health. I did two postdocs in health. … I really just spent time studying and understanding how structures behave and how do they project onto people.
Q: To study structural racism, you advocate for a “mixed-methods” approach. What exactly are these mixed methods and what do they add?
A: Mixed methods is using qualitative tools—like interviews and focus groups—and marrying them with quantitative methods—such as a survey that allows you to ask a very specific question and have a very specific, finite answer—that we then can translate into a number .
Qualitative research like narratives, ethnography, interviews, and photovoice [are] rich forms of knowledge that challenge us to consider multiple ways of knowing beyond numbers. You won’t find them in top journals because of discrimination against methods that challenge this [quantitative] standard.
People like to use quantitative methods because they like to look at large-scale findings. But those methods can be limited … [and have] bias.
[For example,] clinical trials are one way in which structural racism works. You have five Black people in the study; you’ve got three Latinos, maybe you’ve got some Asians, and there’s 100-plus white people in your study. When you use probability, those few people from marginalized backgrounds who have suffered racism—which caused hypertension, which caused asthma, which changed their blood glucose—don’t get recorded into the study because the stories of the 100-plus white people cover the people of color because of the way we use averages.
That’s why qualitative methods become important. The way we do population analyses, [such as averaging heath measurements], is conflating the experiences of these few people. We still need to hear their stories because they’re exposed to something the 100-plus white people aren’t exposed to.
Q: What’s wrong with the idea of only using statistical methods to correct for potential biases?
A: Our systems teach us that standardization will fix bias. Researchers create all these sensitivity tests to weed out error and bias, when all it took in the beginning was adding more people to the research team to be more inclusive step by step. Why would you standardize an approach as opposed to add more interdisciplinary people to the table? Why isn’t the social worker there? Why isn’t a community advocate there? Let’s bounce ideas off of each other and decide to deal with the bias up front and account for it, instead of creating a statistical test to weed it out later. It’s crazy! Some things require a more personal touch.
Q: What’s an example of using mixed methods to measure structural racism?
A: [Social epidemiologist] Lorraine Dean, for example, used indicators reflecting education, housing, employment, criminal justice, and health care by county to show that structural racism was associated with lower body mass index in white people and higher BMI in Black people, especially in Black men.
I study adverse community-level policing across the life course, where quantitative data like racial disparities in number of arrests, police-involved killings, and incarceration rates don’t quite capture the constant pressure my elders have endured since their childhoods when police-sanctioned lynchings were precious. However, together both the statistics we use and the stories we collect—as the great Ida B. Wells did in A Red Record[: Tabulated Statistics and Alleged Causes of Lynchings in the United States]—illuminate a clear path for science to influence social change and health justice.
Q: What are some suggestions you would give to an incoming researcher doing this type of research?
A: Take control over you as the scientist, as opposed to you being a tool. Practice the science the way you want, not the way somebody told you to or how you saw it done by other researchers in a previous publication. Rethink using a method simply because someone told [you] to do so. Be your person, be what’s in your gut.
So, read! People just don’t read. We have been studying racism calling it different names—such as disparities—for a long time; it is disrespectful to act as if what you’re bringing to the table is novel. Frederick Douglass was writing about this and wasn’t even calling it the same terms.
Q: How do you explain the importance of studying structural racism and going about doing that?
A: Now, when I give presentations, I remind my colleagues of the impact of structural racism on me and those I love. It is a tangible example of how those impacted by us are not mere cases in a study. We are loved ones, colleagues, and friends that are drowning in a sea of stress and strain that can be changed if you do more.
If you have an idea, you need to be running it by communities. Will my research serve you? Will this benefit you? Is this interesting to you? Do you have the capacity to join me on this? If not, how can I best serve you through this work? I’m going to publish my scientific publications but I’m also going to build rapport, I’m going to reach out to your legislators. Science is just not for the academy, it’s just not for knowledge … it’s for change.