CHICAGO (PRWEB)
January 12, 2023

A new research study published in Health Services Research presents the development and validation of a new metric for social vulnerability. The breakthrough development of the social vulnerability metric (SVM) opens the door to a new approach to the estimation of social vulnerability from the ecological perspective. The SVM can serve as a tool for public health policy and practice, significantly impacting the understanding of an individual’s risk based solely on their zip code.

According to the US Department of Health and Human Services, social vulnerability refers to the potential negative effects on communities caused by external stresses on human health1. Social Determinants of Health (SDoH) are environmental conditions such as economic stability, access to healthcare, or place of residence, that impact an individual’s health and well-being, often contributing to health disparities and inequities.2,3 When SDoH is accurately measured, it can help public health departments and policymakers appropriately target interventions for communities with the greatest needs.

The SVM was developed using 2018 data obtained from the Federal and publicly available Agency for Healthcare Research and Quality (AHRQ) Social Determinants of Health (SDoH) Database, a dataset of SDoH variables from data sources spanning 2009 to 2018, measured at the Zip Code Tabulation Area (ZCTA).4 ZCTAs differ from zip codes because they only include populated areas; for example zip codes that only include PO boxes are not included in ZCTAs. From these data, researchers fit a bifactor MIRT model to the reviewed set of 94 different SDoH variables to provide a single-value SVM score.5 The bifactor model was applied to data representative of 33,120 zip codes without missing data, which includes 99% of all U.S. zip codes.

The SVM was validated against several health indicators at the national, state and city level. First, the SVM was validated against nationwide age-adjusted all-cause mortality rates provided by the CDC at the county level. The SVM accounted for 46% of the nationwide variability in mortality rates (r=0.68), whereas CDC’s measure, the Social Vulnerability Index (SVI) only accounted for 12% of the variability in mortality rates (r=0.34). Second, it was validated against State of California zip-code level COVID-19 vaccination rates (r=-0.68) and emergency department visits for asthma (r=0.62 for youth and r=0.60 for adults). The negative correlations with COVID-19 vaccination rates indicate that more socially vulnerable populations had less access to COVID-19 vaccines early in the pandemic. Third, it was validated using the Chicago Department of Public Health COVID-19 mortality and vaccination rates. The associations between the SVM scores and COVID mortality and vaccination rates. The correlations across the 58 zip codes were r=0.71 for COVID mortality and r=-0.85 for first vaccination rates. Socially vulnerable communities experienced six times the rate of COVID-19 mortality compared to less socially vulnerable communities (300/100,000 versus 50/100,000 respectively) and a much lower first vaccination rate (32% versus 79% respectively).

Lead author of the study, Lauren Saulsberry, PhD, Department of Public Health Sciences, The University of Chicago along with colleagues Robert Gibbons, Ph.D., Blum-Riese Professor at the University of Chicago; Ankur Bhargava, MD, MPH, Department of Pediatrics, The University of Chicago; Sharon Zeng, BA, Pritzker School of Medicine, University of Chicago; Jason B. Gibbons, PhD, Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health; Cody Brannan, MS, University of Chicago; and Diane S. Lauderdale, PhD, University of Chicago, also developed an interactive web application.

Visitors to the SVM web application can:

• 
  View interactive national county and zip-code level heat maps that visualize SVM percentiles
• View the relationship between county and zip-code SVM scores and 24 health indicators (such as asthma, diabetes, and stroke) nationally or by state
• View or download the county or zip-code level SVM data

“Social determinants of health not only impact people’s health and wellbeing, but it can also contribute to health disparities and inequities,” said Lauren Saulsberry, PhD. “With this study, the SVM was derived from various SDoH variables from multiple nationally representative public databases using multidimensional item response theory (MIRT), ultimately providing a higher level of precision than any existing SDoH metric. The SVM offers a measurement tool improving upon the performance of existing SDoH composite measures and has broad applicability to public health that may help in directing future policies and interventions.”

Researchers also have an exciting addition to this already forward-thinking work. Adaptive Testing Technologies, developer of the CAT-MH® assessment tools, has been collecting data using the CAT-SDoH, a measure of an individual’s personal perspective of their life satisfaction. Together with the SVM, the ability to measure SDoH accurately and precisely in a population has never been greater. When combined, the SVM and CAT-SDoH further improves the adaptive assessment of an individual’s true social vulnerability, reflected as a synthesis of both their ecological and personal perspective.

“The breakthrough developments of the CAT-SDoH and SVM open the door to a new approach to the measurement of SDoH,” said Robert Gibbons, Ph.D., Blum-Riese Professor at the University of Chicago.” “The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.

We now have the technology to adaptively measure SDoH from both ecological and personal perspectives. If we know a person’s zip code, the SVM items for that person’s environment can be immediately determined.”

About the Study

The objective of this study was to derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level. The SVM was constructed from U.S. zip-code tabulation area level measures from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality, COVID-19 vaccination and mortality rates, and emergency department visits for asthma. The SVM was also compared with the CDC/ATSDR Social Vulnerability Index (SVI) to determine convergent validity and differential predictive accuracy.

About Adaptive Testing Technologies

Adaptive Testing Technologies (ATT) is the leader in the design, testing, and implementation of large-scale, cloud-based mental health assessment tools based on Computerized Adaptive Testing (CAT) and Computerized Adaptive Diagnostic (CAD) technologies. These tools are utilized by health professionals to assess a variety of mental health conditions – including depression, anxiety, mania, psychosis, PTSD, substance use disorder, suicide risk, ADHD, and assess Social Determinants of Health. The CAT-MH® and K-CAT® represent the first and only validated, comprehensive, multidimensional item-response-theory-based adaptive screening and measurement systems in the world. They provide levels of precision and accuracy that is far beyond what can be achieved using traditional fixed-length mental health assessment scales and can be administered anywhere at any

frequency, in or out of the clinic, to any sized population. ATT’s tools are currently being utilized in emergency departments, psychiatric and primary care clinics, telemedicine, student health clinics, perinatal medicine clinics, child welfare settings, substance use disorder programs, federal and state mental health programs, employee assistance programs, and the judicial system. The tools are available and are currently being used worldwide.

###

1. https://health.gov/healthypeople/priority-areas/social-determinants-health

2. World Health Organization. Social determinants of health. 2022. Accessed April 21, 2022.

3. US Department of Health and Human Services, Healthy People 2030. Social Determinants of Health. Accessed April 21, 2022.

4.Agency for Healthcare Research and Quality (AHRQ), Rockville, MD. Social Determinants Content last reviewed June 2021. Accessed April 21, 2022.

5. Gibbons RD, Bock RD, Hedeker D, et al. Full-Information Item Bifactor Analysis of Graded Response Data. Applied Psychological Measurement. 2007;31(1):4-19.

6. United States Postal Service (USPS). Postal Facts. Available at: https://facts.usps.com/42000-zip-codes/ Accessed April 21, 2022

MEDIA CONTACT:

Hannah Wulczyn, MPA

Adaptive Testing Technologies

media@adaptivetestingtechnologies.com

312.878.6490, Ext. 505