Measures & Applications for Relating Historical Structural Racism with Contemporary Health Outcomes

Sowmya Rao Chair
Boston University School of Public Health
Philimon Gona Organizer
University of Massachusetts
Sunday, Aug 6: 4:00 PM - 5:50 PM
Topic-Contributed Paper Session 
Metro Toronto Convention Centre 
Room: CC-206F 



Main Sponsor

Health Policy Statistics Section

Co Sponsors

Committee on Minorities in Statistics
Justice Equity Diversity and Inclusion Outreach Group


A Novel Residential Segregation Measure that Incorporates the Impact of Historical Redlining on Contemporary Residential Segregation

Structural racism in the form of contemporary and historical residential segregation have been linked to the persistence of many racial/ethnic health disparities within the United States. Contemporary residential segregation measures used in current research ignore the impact of historical residential segregation, which is likely to have influenced present day racial residential segregation. We propose a new segregation measure that combines the prior information of the historical context defined by Home Owners Loan Corporation designations along with the contemporary residential segregation landscape for a given neighborhood. We further examine its impact on hypertension prevalence among three different cities using data from PLACES and the ACS 5-year estimates. Utilizing Bayesian spatial methods, we assessed if our new measure explains additional variation in hypertension prevalence at the census tract level, then what contemporary or historical residential segregation already explain separately. The purpose of our new measure is to provide a way of determining the degree of influence that historical residential segregation may have on contemporary residential segregation. 


Loni Tabb, Drexel University, Dornsife School of Public Health
Harrison Quick
Sharrelle Barber, Dornsife School of Public Health, Drexel University


Ruby Bayliss, Drexel University, Dornsife School of Public Health

A Two-stage Bayesian Model for Assessing the Geography of Racialized Economic Segregation and Premature Mortality Across US Counties

Racialized economic segregation, a key metric that simultaneously accounts for spatial, social and income polarization, has been linked to adverse health outcomes, including morbidity and mortality; however, statistical methods for measuring the association between racialized economic segregation and health outcomes are not well-developed and are usually studied at the individual level. In this paper we propose a two-stage Bayesian statistical framework that provides a broad, flexible approach to studying the spatially varying association between premature mortality and racialized economic segregation, while accounting for neighborhood-level latent health factors across US counties. We apply our method by using data from three sources: (1) the CDC WONDER, (2) the County Health Rankings, and (3) the Public Health Disparities Geocoding Project. Findings from our study show that the posterior estimates of latent health factors clearly demonstrate geographical patterning across US counties. Additionally, our results highlight the importance of accounting for the presence of spatial autocorrelation in racialized economic segregation measures, in health equity focused settings. 


Yang Xu
Loni Tabb, Drexel University, Dornsife School of Public Health


Loni Tabb, Drexel University, Dornsife School of Public Health

Racial Disparity in TB Mortality Between and Within States With and Without History of Jim Crow Laws

Tuberculosis deaths declined at an annualized rate of change (AROC) of -4.78% over 30 years in the US (GBD 2019). Country-level estimates, however, mask geographic and racial heterogeneity. In 16 southern states health inequities engendered by Jim Crow laws have not been evaluated for TB. We compared TB mortality in former Jim Crow vs non-Jim Crow states from 1990 to 2019 (GBD 2019). We defined a proxy for racialized segregation by identifying the county with the highest proportion of the White population vs the county with highest proportion of the Black. We compared mortality across states and counties within states using GBD Study data. From 1990 to 2019, most former Jim Crow states had highest TB mortality, non-Jim Crow states had the lowest. Mortality declined in all states. Steepest decline was Washington DC, with a 6-fold decline, i.e., AROC -2.68%. Of the 17 states in the top third in 1990, 11 states had a history of Jim Crow laws, whereas of the 17 in the bottom third none had such history. Even though the Civil Act of 1964 dismantled Jim Crow laws, our results suggest that inequities experienced in the past may be felt in future generations via "intergenerational drag". 


Lorena Lorena Estrada-Martinez, University of Massachusetts Boston
Lingling Zhang, University of Massachusetts Boston
Clara Gona, MGH Institute of Health Professions
Aaloke Mody, Washington University School of Medicine in St. Louis
Sowmya Rao, Boston University School of Public Health
Joseph Cooper, University of Massachusetts Boston
Kibibi Mack-Shelton, University of South Florida
Suzanne Leveille, College of Nursing and Health Sciences
Ali Mokdad, University of Washington


Philimon Gona, University of Massachusetts

The measurement of racism in health inequities research

There is limited knowledge on the best measures and methods to examine the impact of racism (institutionalized, personally mediated, and internalized) on health inequities. In this review, we conduct a descriptive examination of the measurement of racism in the health inequities epidemiological literature. We examine the study design, methods used for analysis, types of measures used (e.g., composite, absolute, relative), number of measures used, phase of research (detect, understand, solutions), viewpoint (oppressor, oppressed) and components of structural racism measures (historical context, geographical context, multi-faceted nature). We discuss potential methods (e.g., Peters-Belson, Latent Class Analysis, Difference in Differences) that have demonstrated potential for future work. The articles reviewed were limited to the detect (25%) and understand (75%) phases. Although the majority (56%) of studies had cross-sectional designs, many authors point to the need for longitudinal and multi-level data for further exploration. We examined study design features as independent elements but racism is a multifaceted system and these categories are not mutually exclusive or exhaustive. 


Melody Goodman, New York University