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Observational Study
. 2022 Jul 25:12:05027.
doi: 10.7189/jogh.12.05027.

Characterization of demographic data, clinical signs, comorbidities, and outcomes according to the race in hospitalized individuals with COVID-19 in Brazil: An observational study

Affiliations
Observational Study

Characterization of demographic data, clinical signs, comorbidities, and outcomes according to the race in hospitalized individuals with COVID-19 in Brazil: An observational study

Nathália Ms Sansone et al. J Glob Health. .

Abstract

Background: Brazil is a multiracial country with five major official races: White, Black, individuals with multiracial backgrounds, Asian, and Indigenous. Brazil is also one of the epicentres of the Coronavirus Disease (COVID)-19 pandemic. Thus, we evaluated how the races of the Brazilian population contribute to the outcomes in hospitalized individuals with COVID-19, and we also described the clinical profile of the five official Brazilian races.

Methods: We performed an epidemiological analysis for the first 67 epidemiological weeks of the COVID-19 pandemic in Brazil (from February 22, 2020, to April 04, 2021) using the data available at OpenDataSUS of the Brazilian Ministry of Health, a data set containing data from Brazilian hospitalized individuals. We evaluated more than 30 characteristics, including demographic data, clinical symptoms, comorbidities, need for intensive care unit and mechanical ventilation, and outcomes.

Results: In our data, 585 655 hospitalized individuals with a positive result in SARS-CoV-2 real-time chain reaction (RT-PCR) were included. Of these total, 309 646 (52.9%) identified as White, 31 872 (5.4%) identified as Black, 7108 (1.2%) identified as Asian, 235 108 (40.1%) identified as individuals with multiracial background, and 1921 (0.3%) identified as Indigenous. The multivariate analysis demonstrated that race was significative to predict the death being that Black (OR = 1.43; 95% CI = 1.39-1.48), individuals with multiracial background (OR = 1.36; 95% CI = 1.34-1.38), and Indigenous (OR = 1.91; 95% CI = 1.70-2.15) races were more prone to die compared to the White race. The Asian individuals did not have a higher chance of dying due to SARS-CoV-2 infection compared to White individuals (OR = 0.99; 95% CI = 0.94-1.06). In addition, other characteristics contributed as such as being male (OR = 1.17; 95% CI = 1.16-1.19), age (mainly, +85 years old - OR = 23.02; 95% CI = 20.05-26.42) compared to 1-year-old individuals, living in rural areas (OR = 1.22; 95% CI = 1.18-1.26) or in peri-urban places (OR = 1.25; 95% CI = 1.11-1.40), and the presence of nosocomial infection (OR = 1.91; 95% CI = 1.82-2.01). Among the clinical symptoms, the main predictors were dyspnoea (OR = 1.25; 95% CI = 1.23-1.28), respiratory discomfort (OR = 1.30; 95% CI = 1.28-1.32), oxygen saturation <95% (OR = 1.40; 95% CI = 1.38-1.43). Also, among the comorbidities, the main predictors were the presence of immunosuppressive disorder (OR = 1.44; 95% CI = 1.39-1.49), neurological disorder (OR = 1.21; 95% CI = 1.17-1.25), hepatic disorder (OR = 1.41; 95% CI = 1.34-1.50), diabetes mellitus (OR = 1.40; 95% CI = 1.37-1.42), cardiopathy (OR = 1.13; 95%CI = 1.11-1.14), hematologic disorder (OR = 1.34; 95% CI = 1.24-1.43), Down syndrome (OR = 1.61; 95% CI = 1.43-1.81), renal disease (OR = 1.15; 95% CI = 1.11-1.18), and obesity (OR = 1.18; 95% CI = 1.15-1.21). Individuals on intensive care unit (OR = 2.25; 95% CI = 2.22-2.29) and on invasive (OR = 10.92; 95% CI = 10.66-11.18) or non-invasive (OR = 1.33; 95% CI = 1.30-1.35) mechanical ventilation were more prone to die.

Conclusions: Alongside several clinical symptoms and comorbidities, we associated race with an enhanced risk of death in Black individuals, individuals with multiracial backgrounds, and Indigenous peoples.

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Conflict of interest statement

Disclosure of interest: The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author), and declare no relevant interest.

Figures

Figure 1
Figure 1
Hospitalization due to severe acute respiratory syndrome (SARS) individuals due to Coronavirus Disease (COVID)-19 in Brazil. A) Number of hospitalized SARS individuals due to COVID-19 according to the epidemiologic week of filling out the notification form and the outcomes. B) Number of hospitalized SARS individuals due to COVID-19 according to the epidemiologic week of the first symptoms and the outcomes. We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021).
Figure 2
Figure 2
Distribution of the individuals with Coronavirus Disease (COVID)-19 according to the Brazilian States and Federal district. We presented the data as a percentage. We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021).
Figure 3
Figure 3
Percentage of the total hospitalized individuals due to Coronavirus Disease (COVID)-19 according to demographic data, clinical signs, comorbidities, and outcomes in all the five Brazilian official races. We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021). We presented the complete information in Supplementary Material.
Figure 4
Figure 4
Percentage of the total hospitalized individuals who died due to Coronavirus Disease (COVID)-19 according to demographic data, clinical signs, comorbidities, and outcomes in all the five Brazilian official races. We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021). We presented the complete information in Supplementary Material.
Figure 5
Figure 5
Bivariate analyses to determine the individuals’ characteristics that contributed to the risk of death. We presented the races as colours: A) all individuals hospitalized due to Coronavirus Disease (COVID)-19 in Brazil; B) White individuals hospitalized due to COVID-19 in Brazil; C) Black individuals hospitalized due to COVID-19 in Brazil. We presented the data as odds ratio (OR) and 95% confidence interval (95% CI). We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021). We presented the complete information in Supplementary Material.
Figure 6
Figure 6
Bivariate analyses to determine the individuals’ characteristics that contributed to the risk of death. We presented the races as colours: A) Asian individuals hospitalized due to COVID-19 in Brazil; B) multiracial backgrounds (Pardos) individuals hospitalized due to COVID-19 in Brazil; and C) Indigenous peoples hospitalized due to COVID-19 in Brazil. We presented the data as odds ratio (OR) and 95% confidence interval (95% CI). We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021). We presented the complete information in Supplementary Material.
Figure 7
Figure 7
Length of hospital stay (days) and length of stay in the intensive care unit ICU (days) according to the races of hospitalized individuals due to severe acute respiratory syndrome (SARS) due to Coronavirus Disease (COVID)-19 in Brazil. *, P was significative (<0.05). We presented the data as mean and 95% confidence interval (95%CI). We retrieved the individuals’ data from the Brazilian Ministry of Health (https://opendatasus.saude.gov.br/) platform and corresponded to one year of the pandemic (from February 22, 2020, to April 04, 2021). We presented the complete information in Supplementary Material.

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