New public health tool keeps score on social determinants of health

Loren Saulsberry and colleagues at UChicago developed a new Social Vulnerability Metric (SVM) that measures how social factors impact health.

A person’s health is not determined just by biology. Things like living conditions, financial situation, and social environment also have an enormous impact on well-being. This set of social, economic, and demographic conditions are known as social determinants of health (SDoH), and can include things like place of residence, education, work opportunities, healthcare access, housing, transportation, exposure to racism, language and literacy, and access to healthy foods and community resources.

One study found that 80-90% of these factors that contribute to health can be changed by public health interventions targeted to socioeconomics, health-related behaviors, and environmental factors. It's important for medical providers, public health officials, and policymakers to have an accurate understanding of how social determinants shape the health of communities to decide where and how to intervene, and what kind of programs can get help to those who need it most, ideally prior to poor health outcomes.

“In the era of precision medicine, clinical and biological factors are only part of what contributes to an individual’s health,” said Loren Saulsberry, PhD, Assistant Professor of Public Health Sciences at the University of Chicago. “Some of the most influential factors are really in the realm of social determinants of health, but there aren’t good measurement tools to incorporate these into assessing risk, clinical decision making, and health policy development.”

In a new study published in the journal Health Services Research, Saulsberry and her colleagues developed a new measure called the Social Vulnerability Metric (SVM) that pulls in more than 200 SDoH variables from 17 publicly available, nationally representative databases. Their analysis focused on five key areas of SDoH: demographics like age and race, education, employment status, housing and transportation, and health insurance coverage. The resulting model produces a score that summarizes a person’s vulnerability due to social risk factors. The key word is “vulnerability,” Saulsberry said.

“Baseline level of social vulnerability can impact an individual’s ability to manage chronic conditions like cancer or diabetes, for example, or it can impact resilience to various shocks or trauma, such as a global pandemic like COVID-19,” she said. “The SVM provides a measure of how able one might be to weather different events or cope with long-term challenges.”

The team evaluated the relationship between the SVM and different health outcomes at a national, state, and local level. The SVM is highly correlated with national mortality rates at the county level, meaning that social vulnerability tends to move up and down in the same direction as death rates. The metric also tracked with zip code level health outcomes like COVID-19 mortality and vaccination rates as well as emergency department visits for asthma. It proved to be much more accurate in predicting all-cause, age-adjusted mortality than the Centers for Disease Control and Prevention’s current standard metric, accounting for 46% of the variation of county-level mortality rates, vs 12% for the CDC measure.

“This is giving us a much better understanding of the extent to which social determinants are associated with health outcomes,” Saulsberry said.

This new metric can be plugged into the decision-making process at various levels to guide clinical care and public health practice and policy. Its applications range from being displayed in electronic medical records so physicians can determine how to direct individualized care to mapping SVM scores across the city to see which neighborhoods are most at risk for experiencing health disparities during the next pandemic or economic recession. Then, officials could direct public outreach to those communities, such as vaccine campaigns or social work resources, aimed at giving individuals extra support to protect their health.

“The exciting part is that because the SVM is designed to evolve alongside emerging data sources at multiple geographic levels, it can provide insights about how to target health interventions most appropriately,” Saulsberry said. “If we know certain areas have a high SVM to begin with, we can target policies to those areas both preemptively and in real-time. It’s about knowing who’s most at risk and stepping in before it’s too late.”

The study, “The Social Vulnerability Metric (SVM) As A New Tool for Public Health Policy and Practice,” was supported by the National Human Genome Research Institute, Grant/Award Number: K08 HG011505 and the National Institute on Aging, Grant/Award Number: R56 AG066127. Additional authors include Ankur Bhargava, Sharon Zeng, Cody Brannan, Diane S. Lauderdale, and Robert D. Gibbons from the University of Chicago, and Jason B. Gibbons from Johns Hopkins University.

Loren Saulsberry, PhD

Assistant Professor of Public Health Sciences

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