Geographic Variation in Racial Disparities in Health and Coronavirus Disease-2019 (COVID-19) Mortality

Parcha, Vibhu; Malla, Gargya; Suri, Sarabjeet Singh; Kalra, Rajat; Heindl, Brittain; Fouad, Mona N.; Arora, Garima; Arora, Pankaj

doi:10.1016/j.mayocpiqo.2020.09.005

Cited by 26 publications

(29 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The COVID-19 pandemic has placed a disproportionate burden of morbidity and mortality on the Black and Hispanic populations [ 21 ], which is similar to previous viral pandemics [ 22 – 24 ]. Parcha et al [ 25 ] studied geographic variation and racial disparities in COVID-19 and demonstrated a threefold higher cumulative incidence rate (per 100,000) in Blacks compared with Whites, with a twofold higher crude mortality rate. In both the ICH-COVID and SAH-COVID comparisons, we found higher proportions of Blacks, Asians, and Hispanics than in the control groups.…”

Section: Discussionmentioning

confidence: 99%

Impact of COVID-19 on the hospitalization, treatment, and outcomes of intracerebral and subarachnoid hemorrhage in the United States

et al. 2021

View full text Add to dashboard Cite

Objective To examine the outcomes of adult patients with spontaneous intracranial and subarachnoid hemorrhage diagnosed with comorbid COVID-19 infection in a large, geographically diverse cohort. Methods We performed a retrospective analysis using the Vizient Clinical Data Base. We separately compared two cohorts of patients with COVID-19 admitted April 1–October 31, 2020—patients with intracerebral hemorrhage (ICH) and those with subarachnoid hemorrhage (SAH)—with control patients with ICH or SAH who did not have COVID-19 admitted at the same hospitals in 2019. The primary outcome was in-hospital death. Favorable discharge and length of hospital and intensive-care stay were the secondary outcomes. We fit multivariate mixed-effects logistic regression models to our outcomes. Results There were 559 ICH-COVID patients and 23,378 ICH controls from 194 hospitals. In the ICH-COVID cohort versus controls, there was a significantly higher proportion of Hispanic patients (24.5% vs. 8.9%), Black patients (23.3% vs. 20.9%), nonsmokers (11.5% vs. 3.2%), obesity (31.3% vs. 13.5%), and diabetes (43.4% vs. 28.5%), and patients had a longer hospital stay (21.6 vs. 10.5 days), a longer intensive-care stay (16.5 vs. 6.0 days), and a higher in-hospital death rate (46.5% vs. 18.0%). Patients with ICH-COVID had an adjusted odds ratio (aOR) of 2.43 [1.96–3.00] for the outcome of death and an aOR of 0.55 [0.44–0.68] for favorable discharge. There were 212 SAH-COVID patients and 5,029 controls from 119 hospitals. The hospital (26.9 vs. 13.4 days) and intensive-care (21.9 vs. 9.6 days) length of stays and in-hospital death rate (42.9% vs. 14.8%) were higher in the SAH-COVID cohort compared with controls. Patients with SAH-COVID had an aOR of 1.81 [1.26–2.59] for an outcome of death and an aOR of 0.54 [0.37–0.78] for favorable discharge. Conclusions Patients with spontaneous ICH or SAH and comorbid COVID infection were more likely to be a racial or ethnic minority, diabetic, and obese and to have higher rates of death and longer hospital length of stay when compared with controls.

show abstract

Section: Discussionmentioning

confidence: 99%

Impact of COVID-19 on the hospitalization, treatment, and outcomes of intracerebral and subarachnoid hemorrhage in the United States

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Racial and ethnic disparities in outcomes associated with COVID-19 in the U.S. have been the subject of widespread concern and societal discourse. Characterizing racial/ethnic disparities in COVID-19 outcomes is an active area of scientific research [ 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 ], and quantifying racial/ethnic disparities in the COVID-19 mortality burden has been a particular area of focus. For example, the Color of Coronavirus project of the American Public Media Research Lab [ 32 ] tracks COVID-19 death counts by race/ethnicity in each state, providing analyses and extended commentary on mortality rates by race/ethnicity and comparisons between the percentage of total deaths and the percent population share by race/ethnicity.…”

Section: Introductionmentioning

confidence: 99%

Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia

Chen

Belin

et al. 2021

IJERPH

View full text Add to dashboard Cite

The coronavirus disease 2019 (COVID-19) epidemic in the United States has disproportionately impacted communities of color across the country. Focusing on COVID-19-attributable mortality, we expand upon a national comparative analysis of years of potential life lost (YPLL) attributable to COVID-19 by race/ethnicity (Bassett et al., 2020), estimating percentages of total YPLL for non-Hispanic Whites, non-Hispanic Blacks, Hispanics, non-Hispanic Asians, and non-Hispanic American Indian or Alaska Natives, contrasting them with their respective percent population shares, as well as age-adjusted YPLL rate ratios—anchoring comparisons to non-Hispanic Whites—in each of 45 states and the District of Columbia using data from the National Center for Health Statistics as of 30 December 2020. Using a novel Monte Carlo simulation procedure to perform estimation, our results reveal substantial racial/ethnic disparities in COVID-19-attributable YPLL across states, with a prevailing pattern of non-Hispanic Blacks and Hispanics experiencing disproportionately high and non-Hispanic Whites experiencing disproportionately low COVID-19-attributable YPLL. Furthermore, estimated disparities are generally more pronounced when measuring mortality in terms of YPLL compared to death counts, reflecting the greater intensity of the disparities at younger ages. We also find substantial state-to-state variability in the magnitudes of the estimated racial/ethnic disparities, suggesting that they are driven in large part by social determinants of health whose degree of association with race/ethnicity varies by state.

show abstract

“…Our findings of variation of caseload across facilities is analogous to reports of geographic heterogeneity in disease prevalence. 22 For example, a serological survey from Spain reported substantial geographical variation, with higher prevalence near Madrid (>10%) and lower prevalence in coastal areas (<3%). 23 A study from the USA reported higher COVID-19 mortality in rural versus urban communities; however, that study was limited to county-level (not patient level) data.…”

Section: Discussionmentioning

confidence: 99%

Heterogeneity in COVID-19 patient volume, characteristics and outcomes across US Department of Veterans Affairs facilities: an observational cohort study

et al. 2021

View full text Add to dashboard Cite

ObjectiveStudies describe COVID-19 patient characteristics and outcomes across populations, but reports of variation across healthcare facilities are lacking. The objectives were to examine differences in COVID-19 patient volume and mortality across facilities, and understand whether facility variation in mortality was due primarily to differences in patient versus facility characteristics.DesignObservational cohort study with multilevel mixed effects logistic regression modelling.SettingThe Veterans Health Administration (VA) is the largest healthcare system in the USA.ParticipantsPatients with COVID-19.Main outcomeAll-cause mortality within 45 days after COVID-19 testing (March–May, follow-up through 16 July 2020).ResultsAmong 13 510 patients with COVID-19, 3942 (29.2%) were admitted (2266/3942 (57.5%) ward; 1676/3942 (42.5%) intensive care unit (ICU)) and 679/3942 (17.2%) received mechanical ventilation. Marked heterogeneity was observed across facilities in median age (range: 34.3–83.9 years; facility mean: 64.7, SD 7.2 years); patient volume (range: 1–737 at 160 facilities; facility median: 48.5, IQR 14–105.5); hospital admissions (range: 1–286 at 133 facilities; facility median: 11, IQR 1–26.5); ICU caseload (range: 1–85 at 115 facilities; facility median: 4, IQR 0–12); and mechanical ventilation (range: 1–53 at 90 facilities; facility median: 1, IQR 0–5). Heterogeneity was also observed in facility mortality for all patients with COVID-19 (range: 0%–29.7%; facility median: 8.9%, IQR 2.4%–13.7%); inpatients (range: 0%–100%; facility median: 18.0%, IQR 5.6%–28.6%); ICU patients (range: 0%–100%; facility median: 28.6%, IQR 14.3%–50.0%); and mechanical ventilator patients (range: 0%–100%; facility median: 52.7%, IQR 33.3%–80.6%). The majority of variation in facility mortality was attributable to differences in patient characteristics (eg, age).ConclusionsMarked heterogeneity in COVID-19 patient volume, characteristics and mortality were observed across VA facilities nationwide. Differences in patient characteristics accounted for the majority of explained variation in mortality across sites. Variation in unadjusted COVID-19 mortality across facilities or nations should be considered with caution.

show abstract

Geographic Variation in Racial Disparities in Health and Coronavirus Disease-2019 (COVID-19) Mortality

Cited by 26 publications

References 41 publications

Impact of COVID-19 on the hospitalization, treatment, and outcomes of intracerebral and subarachnoid hemorrhage in the United States

Impact of COVID-19 on the hospitalization, treatment, and outcomes of intracerebral and subarachnoid hemorrhage in the United States

Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia

Heterogeneity in COVID-19 patient volume, characteristics and outcomes across US Department of Veterans Affairs facilities: an observational cohort study

Contact Info

Product

Resources

About