The Disproportionate Impacts of Social Determinants of Health
Exposure factors drive disparities in COVID rates
A recent study from researchers at New York University’s Grossman School of Medicine highlights how social and racial inequities are responsible for significant disparities in COVID infection rates and mortality across the United States.
Through analyzing the medical records of more than 10,000 patients in the N.Y.U. Langone Health System who tested positive for coronavirus in early spring, researchers found that once infected, Black and Hispanic patients were no more likely than white patients to be hospitalized. Furthermore, if hospitalized, Black patients were less likely than white patients to have severe illness or die.
The study found that key in explaining the disparities of overall disproportionate infection and death rates are rates of exposure. People of color are more likely to be exposed to the virus, compared to white patients. Combined with higher rates of underlying conditions and poorer access to healthcare, these communities are therefore infected at higher rates.
The Atlas Research Coalition has been tracking these disparities since the beginning of the pandemic, adding contextual community indicators, reviewing historical policies and power dynamics, and highlighting regions of legacy racism. Because data is not commonly disaggregated by race or ethnicity in a systematic way, adding these contextual factors can be helpful to track disparities at a community level where detailed data isn’t available.
Exposure explains racial disparities in COVID rates
The NYU study adds to the growing body of evidence that there is no innate biological vulnerability among minority communities. The disparities are largely due to higher rates of exposure, which are linked to social determinants of health.
Lead researcher Dr. Gbenga Ogedegbe said in a recent New York Times article about the study’s findings, “We hear this all the time — ‘Blacks are more susceptible.’ It is all about the exposure. It is all about where people live. It has nothing to do with genes.”
The CDC reports long-standing systemic health and social inequities put communities of color at increased risk of getting sick and dying from COVID-19. Inequities in social determinants of health (SDOH), or the conditions in the places that people live, work, learn, and play that affect a wide range of health risks and outcomes, disproportionately impact communities of color. These conditions include systemic racism and discrimination, poor access to healthcare, high rates of unemployment or under-employment, education gaps, and lack of affordable housing.
Exploring impact in Black Belt Counties
Earlier this year, we added features to the US COVID Atlas to highlight areas where there are significant racial and ethnic minority populations (Native American Reservation, Black Belt Counties) or cities where there are significantly higher rates of segregation (Hyper-Segregated Cities). The Atlas helps visualize how the virus has spread across different geographic regions and areas of interest over time, and incorporating community health and SDOH variables can help expose disparities in vulnerable communities.
The Black Belt Counties overlay highlights dozens of southern U.S. counties where populations were at least 40% Black, according to data from the 2000 Census. The region is still largely rural, with an economy that was once dominated by the cotton and tobacco plantations worked by Black enslaved populations, and later Black laborers and tenant farmers, on land that was largely controlled by wealthy white landowners. The region has historically ranked low in terms of SDOH indicators, including high poverty, low median incomes, and low educational attainment. Today, poverty rates remain some of the highest in the country. In 2018, the UN Special Rapporteur for Extreme Poverty, essentially the UN’s ‘point man’ on global poverty, paid a visit to the Black Belt to highlight the region’s impoverished conditions and severe economic disparities.
Using the Atlas’ most recent data, the confirmed count is currently much higher than it was for most of the previous nine months. Diving deeper with the Hotspot map, we see Black Belt counties in Georgia, Mississippi, and Alabama, in particular, emerged and remained hotspots in the spring and into summer. (Here, hotspots are composed of counties with statistically significant high rates surrounded by counties with similarly significant high rates.) Almost the entire Southeast region, including Florida, appeared to be a hotspot by July. Since the summer, rates have significantly decreased in the Black Belt — suggesting that the high rates of the summer may have prompted the policy and behavioral changes that reduced spread of the virus in the fall.
By late November, however, we see high rates beginning to emerge again, along with rates across the larger Southeastern region and across the country. As of mid-December, Clarke, Marengo, Wilcox and Greene counties in Alabama have some of the highest rates in the Black Belt, forming a high rate cluster that stretches into the northern part of the state and into Mississippi counties including Noxubee and Oktibbeha.
Pandemic responses must be informed by SDOH
The recent NYU study highlights the need for a better understanding of the impact on social determinants of health on the spread of COVID, particularly in communities of color and regions with large Black and Latinx populations. Policy responses and public health campaigns should reflect the evidence that SDOH disparities explain how and why this virus has disproportionately impacted already-vulnerable communities.
We plan to integrate additional SDOH variables and data sources in the Atlas in 2021 to deepen our collective understanding of these trends. Stay tuned for more on this critical aspect to our research in the new year.
We want to hear from you
We are excited to be working on new features and upgrades to the Atlas, to be released in early 2021. The updates are well underway, but we need your help to make sure that the changes we’ve made work with how you use or might use the new Atlas. Give it a spin here and let us know your thoughts on the feedback form. Thanks for your input!
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