December 8, 2025

The Urban Health Collaborative’s (UHC) Research & Data Core has developed a resource to help researchers better understand measurement options for measuring the clustering and concentration of different groups of residents (“residential segregation”). The resource presents several measures related to residential segregation, their formulas (with key references), and examples of existing empirical evidence that uses each measure.  

Measuring residential segregation can be an important tool in helping to address the effects of structural racism on health. The lasting impacts of redlining and other discriminatory housing policies can be seen today and have significant ties to health outcomes like cancer, asthma, hypertension, preterm birth, and cardiovascular health.  

However, the application of quantitative residential segregation measures in public health research has varied. As a guide to students and researchers, the UHC created the resource document with information on the Dissimilarity Index, the Gini Index, the Index of Concentration at the Extremes, and the 𝐺𝑖∗ statistic. A brief overview can be found here: 

The Dissimilarity Index 

• A segregation measure of evenness that represents the percentage of the minority population that would need to move for the populations of the minority and majority groups to be evenly distributed in the neighborhood. 
• The index has been associated with health and social outcomes like mortality, pregnancy, self-rated health, firearm homicides, air pollution, and COVID-19. 

• A measure initially developed to show income distribution and inequality.  
• It has also been shown to be associated with a number of health and social outcomes like mortality, suicide, cancer, and COVID-19. 

• A measure initially developed to better understand concentrations (as opposed to distribution) of affluence and poverty in a neighborhood.  
• It has since been extended to capture multiple social constructs like race/ethnicity and income combined when measuring segregation in a neighborhood. 
• It has also been shown to be associated with a number of health and social outcomes like police-related deaths, fatal and non-fatal assaults, and COVID-19. 

• Aka the Getis-Ord Gi-star, this statistic is a measure that shows how a neighborhood and its surrounding neighboring areas’ racial/ethnic composition can deviate from that of its larger region. 
• It can be mapped to show areas of higher than expected residential segregation (hot spots) and areas of lower than expected segregation (cold spots). It has been shown to be associated with a number of health and social outcomes, like cardiovascular health, BMI, spatial epidemiology broadly, and COVID-19. 

View The Resource Sheet