Rethinking Vulnerability: Using Factor Analysis to Assess Census Tract–Level Vulnerability

Abstract

Objectives:

The Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Social Vulnerability Index (SVI) is used to guide policy making and resource allocation for emergency responses. However, limited research has explored the extent to which each variable contributes to the overall calculation of the SVI. We used a factor analysis approach to determine whether specific drivers of vulnerability exist at the state and national levels.

Methods:

We used the 2020 CDC/ATSDR SVI dataset to perform factor analysis separately for each state and nationally. We determined factor weights and scores and conducted a comparative analysis with CDC/ATSDR SVI. The final SVI for each census tract ranged from 0 to 1, with higher values indicating greater vulnerability.

Results:

At the national level, our factor analysis approach identified 4 primary variables that affected vulnerability the most: the percentage of the population below 150% of the federal poverty level (weight, 0.262), with housing cost burden (ie, households that spend >30% of their income on housing-related costs; weight, 0.226), in a racial and ethnic minority group (weight, 0.232), and without a high school diploma (weight, 0.138). However, at the state level, some analyses assigned low weights to the primary national-level drivers.

Conclusions:

Our study highlights the need to consider context-specific vulnerability measures when characterizing community social vulnerability. The factor analysis SVI provides nuanced insight into vulnerability drivers at the national and state levels, laying the groundwork for more precise disaster response planning, resource allocation, and community resilience initiatives.