Measuring health inequities in geostatistics

Authors: Nathaniel Henry*, University of Oxford
Topics: Spatial Analysis & Modeling, Geography and Urban Health, Quantitative Methods
Keywords: Geostatistics, small-area methods, GIS, health, mortality, race, inequities, social determinants of health
Session Type: Virtual Paper
Day: 4/10/2021
Start / End Time: 3:05 PM / 4:20 PM
Room: Virtual 8
Presentation File: No File Uploaded


Geostatistics and small area methods are commonly applied to health surveillance data in order to measure local variation in disease prevalence, mortality rates, or life expectancy across a population. These methods can quantify health differences between sub-populations while preserving uncertainty: as such, they appear to be a promising tool for measuring health inequities, which the World Health Organization defines as differences in health between population subgroups that arise from underlying differences in social conditions. Despite this, relatively few small-area studies of health within the United States have explicitly measured health inequities by race and class. This study demonstrates how geographical knowledge about racial disparities in the social determinants of health can be formalized to quantify health inequities in a small-area context. These include capturing the spatial trend from macro-segregation to micro-segregation in the US; tracking differential exposure to environmental hazards across population subgroups; and expanding the concept of space-time random effects structures to include race and class groupings. These concepts are applied to measure inequities in life expectancy and all-cause mortality by census block group, sex, and racial group across the Cleveland, Ohio metro area over the past decade.

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