Measuring multidimensional structural racism as a driver of racial inequities in birth outcomes

PROJECT SUMMARY
The objective of the proposed study is to determine the linkages between multidimensional structural racism
and preterm birth, low birthweight, and small-for-gestational-age birth among infants of US-born Black, foreign-
born Black, and white pregnant people. The study team published an innovative, theory-driven approach to
measuring structural racism as a multidimensional determinant of health called the Multidimensional Measure
of Structural Racism (MMSR) in 2022. Unlike previous measures of structural racism, which focus on separate
domains of structural racism (e.g., Black-white racial residential segregation, Black-white inequities in
education, employment, income, homeownership, criminal justice), the MMSR uses Latent Class Analysis—a
method commonly used by psychometricians to identify complex constructs (e.g., personality types)—to
identify multidimensional structural racism (referred to as “structural racism typologies”). The MMSR captures
the interconnection between structural racism domains and their combined health effects. The proposed study
will calculate the MMSR using the data from the American Community Survey and the Vera Institute of Justice
databases. First, we will create measures of (1) racial residential segregation, (2) education inequity, (3)
employment inequity, (4) income inequity, (5) homeownership inequity, and (6) criminal justice inequity. Next,
we will identify the structural racism typologies with Latent Class Analysis and link the typologies to birth
records using the residential address of the pregnant people at the time of delivery. For Aim 1, we will use
Vermunt's “3-step approach” to relate the structural racism typologies to the risks of preterm birth, low
birthweight, and small-for-gestational-age birth for infants born to US-born Black, foreign-born Black, and white
pregnant people in Minnesota during 2014-2021. This aim is an expansion of our pilot project, in which we
focused only on births that occurred in 2018 in Minnesota. We will calculate period-specific, age-adjusted
predicted risks, and 95% confidence interval for each group and compare them. For Aim 2, we will use the
same analytical approach as in Aim 1; however, we will use birth records from Louisiana, Michigan,
Washington, California, Pennsylvania, and New York City (i.e., one state/city from all US regions). We will
calculate state-specific estimates to examine regional heterogeneity. Additionally, we will calculate multi-state
estimates and compare them to the state-specific estimates to assess their consistency. Results of the
proposed project will (1) elucidate the linkages between structural racism and birth outcomes and answer
whether effect heterogeneity exists across time and place, (2) inform whether the MMSR needs further
refinement before expanding its use to study other health outcomes in which racial inequities exist, and (3)
make the MMSR methodology and the measure calculated for the proposed project available for public use.

Grant Number: 1R03HD111802-01A1
NIH Institute/Center: NIH
Principal Investigator: Tongtan Chantarat