Related Experiment Video
Updated: Jan 9, 2026

Sampling Soils in a Heterogeneous Research Plot
Published on: January 7, 2019
Characterizing rurality using the All of Us Research Program data
Michael Bradfield1, Toluwanimi Olorunnisola2, Vignesh Subbian2
1Department of Family Medicine, Banner Health North Colorado Medical Center, Greeley, Colorado, United States of America.
None:
Rural communities experience disproportionately higher rates of chronic diseases, less access to healthcare services, and poorer health outcomes compared to their urban counterparts in the United States. However, inconsistencies in how rurality is defined across biomedical research, including limitations in geographic detail within large-scale datasets, present significant challenges for reliably studying rural health outcomes. This study aimed to develop and apply an operational rurality scale using 3-digit ZIP codes to characterize rural participation in the All of Us Research Program and to examine associations between rurality, delayed care, and healthcare affordability. Publicly available information from the Federal Office of Rural Health Policy and the Environmental Systems Research Institute was integrated to generate a continuous rurality scale at the 3-digit ZIP code level. A Kolmogorov-Smirnov test identified statistically significant differences in the geographic distribution of those who had delayed access to care (P < 0.001) and those with difficulties affording care (P < 0.001). The proposed continuous rurality scale is reproducible and extensible in several ways within the All of Us Workbench, as it provides a framework for categorizing participants by geolocation and facilitates standardized analyses of rurality-related research questions.
Related Concept Videos
Levels of Use of a GIS
Selected Data About Geographic Locations
Cross-Sectional Research
Stratified Sampling Method
To choose a stratified sample, divide the population into groups called strata and then take a...
Data Collection by Observations
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Longitudinal Research

