The social vulnerability metric (SVM) as a new tool for public health

Abstract

Objective: To derive and validate a new ecological measure of the social determinants of health (SDoH), calculable at the zip code or county level.

Data sources and study setting: The most recent releases of secondary, publicly available data were collected from national U.S. health agencies as well as state and city public health departments.

Study design: The Social Vulnerability Metric (SVM) was constructed from U.S. zip-code level measures (2018) from survey data using multidimensional Item Response Theory and validated using outcomes including all-cause mortality (2016), COVID-19 vaccination (2021), and emergency department visits for asthma (2018). The SVM was also compared with the existing Centers for Disease Control and Prevention's Social Vulnerability Index (SVI) to determine convergent validity and differential predictive validity.

Data collection/extraction methods: The data were collected directly from published files available to the public online from national U.S. health agencies as well as state and city public health departments.

Principal findings: The correlation between SVM scores and national age-adjusted county all-cause mortality was r = 0.68. This correlation demonstrated the SVM's robust validity and outperformed the SVI with an almost four-fold increase in explained variance (46% vs. 12%). The SVM was also highly correlated (r ≥ 0.60) to zip-code level health outcomes for the state of California and city of Chicago.

Conclusions: 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. The SVM provides a single measure of SDoH that better quantifies associations with health outcomes.

Keywords: biostatistical methods; determinants of health/population health/socioeconomic causes of health; health care disparities; health equity; health policy; social determinants of health.

FIGURE 1

Social Vulnerability Metric (SVM) and the Center for Disease Control and Prevention Social Vulnerability Index correlations with all‐cause age‐adjusted mortality. r, correlation coefficient; SVI, Social Vulnerability Index; SVM, Social Vulnerability Metric. Centers for Disease Control and Prevention Wide‐ranging Online Data for Epidemiologic Research data all‐cause age‐adjusted mortality. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 2

SVM versus COVID‐19 vaccinations (Panel A) and age‐adjusted emergency department visits for asthma (Panel B) in the state of California (USA). Lowess plots of the proportion of ≥1 and full COVID vaccination (Panel A) and the rate of age‐adjusted emergency department visits for asthma in the state of California (Panel B). Data analyzed on COVID vaccinations extended through June 19, 2021. Data from 2018 were analyzed for emergency department visits for asthma. Panel B represents the visit rate per 10,000 individuals for age groups 0–17 years and adults 18+ years. r, correlation coefficient; SVM, Social Vulnerability Metric. Authors' analysis of zip‐code level data from the California Health and Human Services on ≥1 and full COVID vaccinations and age‐adjusted emergency department visits for asthma. [Color figure can be viewed at wileyonlinelibrary.com]

FIGURE 3

SVM versus COVID mortality rate (Panel A) and COVID first vaccination rate (Panel B) in the city of Chicago. Lowess plots of COVID mortality (Panel A) and proportion of COVID first vaccinations (Panel B). r, correlation coefficient, SVM, Social Vulnerability Metric. Authors' analysis of zip‐code level data from the Chicago Department of Health on COVID mortality and vaccine initiation through June 19, 2021. Data are reflective of 58 Chicago, Illinois (USA) zip codes. [Color figure can be viewed at wileyonlinelibrary.com]