Why COVID-19 May Be Disproportionately Killing African Americans: Black Overrepresentation among COVID-19 Mortality Increases with Lower Irradiance, Where Ethnicity Is More Predictive of COVID-19 Infection and Mortality Than Median Income

Author(s):  
Alex Backer

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Russ D. Kashian ◽  
Tracy Buchman ◽  
Robert Drago

PurposeThe study aims to analyze the roles of poverty and African American status in terms of vulnerability to tornado damages and barriers to recovery afterward.Design/methodology/approachUsing five decades of county-level data on tornadoes, the authors test whether economic damages from tornadoes are correlated with vulnerability (proxied by poverty and African American status) and wealth (proxied by median income and educational attainment), controlling for tornado risk. A multinomial logistic difference-in-difference (DID) estimator is used to analyze long-run effects of tornadoes in terms of displacement (reduced proportions of the poor and African Americans), abandonment (increased proportions of those groups) and neither or both.FindingsControlling for tornado risk, poverty and African American status are linked to greater tornado damages, as is wealth. Absent tornadoes, displacement and abandonment are both more likely to occur in urban settings and communities with high levels of vulnerability, while abandonment is more likely to occur in wealthy communities, consistent with on-going forces of segregation. Tornado damages significantly increase abandonment in vulnerable communities, thereby increasing the prevalence of poor African Americans in those communities. Therefore, the authors conclude that tornadoes contribute to on-going processes generating inequality by poverty/race.Originality/valueThe current paper is the first study connecting tornado damages to race and poverty. It is also the first study finding that tornadoes contribute to long-term processes of segregation and inequality.



2020 ◽  
Vol 13 (Suppl_1) ◽  
Author(s):  
Mohamed M Gad ◽  
Islam Y Elgendy ◽  
Ahmed M Mahmoud ◽  
Anas M Saad ◽  
Hani Jneid ◽  
...  

Introduction: The incidence of cardiovascular (CV) disease among pregnant women is rising in the United States (US). Data on racial disparities for the major CV events during pregnancy are limited. Methods: Pregnant women hospitalized from January 2007 to September 2015 were identified in the Nationwide Inpatient Sample. Outcomes of interest were mortality, myocardial infarction (MI), stroke, and pulmonary embolism (PE). Multivariate regression analysis was used for Odds Ratio (OR) and 95% Confidence Interval (CI). Results: Among 37,524,315 pregnant women, 17,159,400 (45.7%) were White, 4,921,574 (13.1%) were African American, and 7,111,216 (19.0%) were Hispanic. Following 2010, trends of mortality and stroke declinedsignificantly in African Americans, however, were stable in Whites (Figure). In-hospital mortality was 13.52 per 100,000 hospitalizations. The incidence of in-hospital mortality was highest among AfricanAmericans followed by White, then Hispanic patients; 29.63, 10.61, and 9.73 per 100,000 hospitalizations, respectively. The majority of African Americans (61.9%) were insured by Medicaid while the majority of White patients had private insurance (61.9%). Most of African American patients were below-median income (70.54%) while nearly half of the White patients were above the median income (47%). Compared to Whites, African Americans had the highest mortality with OR of 2.79, 95% CI (2.61-2.99), myocardial infarction with OR of 2.178, 95% CI (2.01-2.36), stroke with OR of 2.04, 95% CI (1.96-2.13), and pulmonary embolism with OR of 1.95, 95% CI (1.82-2.08). Conclusions: Significant racial disparities exist in the major CV events among pregnant women. Further efforts are needed to minimize these differences.



2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Dominique J. Monlezun ◽  
Alfred T. Samura ◽  
Ritesh S. Patel ◽  
Tariq E. Thannoun ◽  
Prakash Balan

Introduction. Social disparities in out-of-hospital cardiac arrest (OHCA) outcomes are preventable, costly, and unjust. We sought to perform the first large artificial intelligence- (AI-) guided statistical and geographic information system (GIS) analysis of a multiyear and multisite cohort for OHCA outcomes (incidence and poor neurological disposition). Method. We conducted a retrospective cohort analysis of a prospectively collected multicenter dataset of adult patients who sequentially presented to Houston metro area hospitals from 01/01/07-01/01/16. Then AI-based machine learning (backward propagation neural network) augmented multivariable regression and GIS heat mapping were performed. Results. Of 3,952 OHCA patients across 38 hospitals, African Americans were the most likely to suffer OHCA despite representing a significantly lower percentage of the population (42.6 versus 22.8%; p < 0.001 ). Compared to Caucasians, they were significantly more likely to have poor neurological disposition (OR 2.21, 95%CI 1.25–3.92; p = 0.006 ) and be discharged to a facility instead of home (OR 1.39, 95%CI 1.05–1.85; p = 0.023 ). Compared to the safety net hospital system primarily serving poorer African Americans, the university hospital serving primarily higher income commercially and Medicare insured patients had the lowest odds of death (OR 0.45, p < 0.001 ). Each additional $10,000 above median household income was associated with a decrease in the total number of cardiac arrests per zip code by 2.86 (95%CI -4.26- -1.46; p < 0.001 ); zip codes with a median income above $54,600 versus the federal poverty level had 14.62 fewer arrests ( p < 0.001 ). GIS maps showed convergence of the greater density of poor neurologic outcome cases and greater density of poorer African American residences. Conclusion. This large, longitudinal AI-guided analysis statistically and geographically identifies racial and socioeconomic disparities in OHCA outcomes in a way that may allow targeted medical and public health coordinated efforts to improve clinical, cost, and social equity outcomes.



2001 ◽  
Vol 120 (5) ◽  
pp. A571-A571
Author(s):  
J SCHWARTZ ◽  
V FISHMAN ◽  
R THOMAS ◽  
J GAUGHN ◽  
K KOWDLEY ◽  
...  




2006 ◽  
Vol 39 (5) ◽  
pp. 18
Author(s):  
ELAINE ZABLOCKI
Keyword(s):  




Sign in / Sign up

Export Citation Format

Share Document