Keywords
Social Vulnerability
Abstract
This study evaluates the predictive power of four established social vulnerability models in explaining geographic variation in health outcomes, health behaviors, health status, and participation in preventive measures across the United States. While decades of research have demonstrated the importance of social determinants of health, questions remain about the comparative performance, validity, and real-world utility of widely used social vulnerability indices in forecasting public health outcomes. Using census tract level data from the Centers for Disease Control and Prevention’s PLACES database, this research examines the explanatory strength of four widely applied frameworks: the CDC’s Social Vulnerability Index (SVI), the Texas A&M HRRC SVI, the Georgetown SVI, and the original Social Vulnerability Index (SoVI). Regression analyses were conducted to evaluate how each model’s variable inputs, Thematic/Factor groupings, and final composite scores relate to a comprehensive set of outcomes across four domains: chronic disease prevalence, risk behaviors, health status, and the uptake of preventive measures/screenings. To further explore contextual influences, analyses were stratified by Urban, Urban-Intersecting, and Non-Urban geographies to assess how spatial context modifies the predictive power of each framework. Findings contribute to the growing discussion on model comparability and predictive accuracy, revealing differences in explanatory capacity that may depend on both model design and geographic setting. This study underscores the need to move beyond a single index approach toward a more nuanced understanding of how place and vulnerability interact to shape health outcomes. By identifying where and how these models perform most effectively, the research offers guidance for policymakers, planners, and health professionals seeking to use spatially informed strategies to target interventions, allocate resources, and reduce health disparities across diverse communities.
Completion Date
2025
Semester
Fall
Committee Chair
Dr. Christopher Emrich
Degree
Doctor of Philosophy (Ph.D.)
College
College of Community Innovation and Education
Department
Department of Public Affairs
Format
Release Date
12-15-2027
Document Type
Dissertation
Campus Location
UCF Downtown
Subjects
Public health--Research--Social aspects; Public health--Research--Evaluation; Health risk assessment--Research; Public health--Mathematical models; Urban health--Evaluation
STARS Citation
Russell, Olga L., "Assessing Leading Social Vulnerability Models Ability to Predict Health Risk Behaviors, Prevention Measures, Health Status, and Health Outcomes" (2025). Graduate Thesis and Dissertation post-2024. 543.
https://stars.library.ucf.edu/etd2024/543
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