Data Analytics Connects COVID-19 Outcomes to Ethnicity, Socioeconomics
Researchers used data analytics to study how socioeconomic determinants are linked to race and ethnicity-based COVID-19 outcomes.
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By - University of California researchers used patient data analytics to determine if race and ethnicity-based COVID-19 outcomes disparities are associated with socioeconomic characteristics.
Since the beginning of the pandemic, COVID-19 has disproportionately impacted racial and ethnic minority groups. According to researchers, however, the association of social determinants of health, especially socioeconomic determinants, with racial disparities in COVID-19 was unclear.
To address health disparities, researchers needed to determine how and why racial COVID-19 inequalities persist.
“In this study, we examine the associations of race and ethnicity with COVID-19 positivity rates, mortality, hospitalization, and ICU admission in the United States. We then associate these outcomes with various social determinants through adjusted and unadjusted relative risk ratio (RR) and odds ratio (OR) calculations and metaregression analysis,” the research author wrote in their study.
“To our knowledge, we are the first to examine social determinants of health in racial disparities of COVID-19 outcomes through a systematic review and meta-analysis, which provides a more accurate understanding than results published in single-site studies.”
The team conducted a systematic search of studies published between Jan. 1, 2020, and Jan. 6, 2021, in PubMed, medRxiv, bioRxiv, Embase, and the World Health Organization COVID-19 databases. After reviewing the studies for terms related to COVID-19 and disparities, the team selected 68 studies and began extracting the data.
“We collected details from studies regarding study setting and type and patient demographic characteristics, comorbidities, and outcomes, using the same independent reviewer design as during study selection,” the researchers wrote.
“Following the initial data review, socioeconomic variables quantifying disparities in health, income, and geography were extracted from external sources using zip code and congressional district location.”
Data analyses were then conducted separately for each racial and ethnic group in the following cohorts: COVID-19 positivity, ICU admission, hospitalization, and mortality. A total of 4,318,929 patients from 68 studies were included in the meta-analysis.
Overall, 370,933 patients (8.6 percent) were Black, 9,082 (0.2 percent) were American Indian or Alaska Native, 101,793 (2.4 percent) were Asian American, 851,392 identified as Hispanic/Latinx (19.7 percent), 7,417 (0.2 percent) were Pacific Islander, 1,037,996 (24.0 percent) were White, and 269,040 (6.2 percent) identified as multiracial or of another racial or ethnic group.
After adjusting for sex and age, researchers found that Black and Hispanic populations were the most likely to test positive for COVID-19. Additionally, Asian Americans had the highest risk of intensive care unit admission.
“In this study, African American, Hispanic, and Asian American individuals were at considerably higher risk of COVID-19 positivity and ICU admission compared with White individuals. Adjustment for social determinants of health and socioeconomic factors decreased risks of COVID-19 positivity in racial and ethnic minority groups; however, several factors were not accounted for by these variables,” the study stated.
Additionally, the researchers found the decreased assess to clinical care was also associated with poor COVID-19 outcomes in Hispanic and Black communities. The researchers concluded that socioeconomic determinants are responsible for racial and ethnic disparities in COVID-19 outcomes for some populations, including Black, Hispanic, Asian American individuals.
