Impact of sociodemographic factors on COVID-19 survival: a nationwide 2,000,000 in-patients’ cohort in Brazil

Guimarães, Raphael Mendonça; Pastura, Danielle Cristina Lourenço dos Santos

doi:10.1590/1980-549720230050

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Revista Brasileira de Epidemiologia

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Sumário

Brief Communication • Rev. bras. Epidemiol. 26 • 2023 • https://doi.org/10.1590/1980-549720230050 copy

Impact of sociodemographic factors on COVID-19 survival: a nationwide 2,000,000 in-patients’ cohort in Brazil

Impacto de fatores sociodemográficos na sobrevida da COVID-19: uma coorte nacional de 2 milhões de pacientes internados no Brasil

Authorship SCIMAGO INSTITUTIONS RANKINGS

ABSTRACT

Objective:

To estimate the impact of sociodemographic factors on survival from COVID-19 in Brazil.

Methods:

Longitudinal data from a retrospective cohort of 2,000,000 hospitalizations due to COVID-19 in Brazil between March 2020 and May 2022, enrolled in SIVEP-Gripe, were analyzed.

Results:

The adjusted Cox model showed a 7% higher probability of death for men. 9% and 13% for the brown population compared to white and 16% for those living in the rural region. Long-lived elderly has a 301% higher probability when compared to young people.

Conclusion:

Sociodemographic factors interfere with survival from COVID-19 and should gain prominence in theoretical models and clinical aspects, and should be considered when formulating public policies, especially in countries with greater social inequality, such as Brazil.

Keywords:
Covid-19; Social determinants of health; Mortality; Survival analysis

Characteristics	Categories	Descriptive			Cox Model
		Kaplan-Meyer			Crude		Adjusted
		Mean	SE	p-value (LogRank)	HR (95%CI)	p-value	HR (95%CI)	p-value
Sex	Female	17.01	0.01	<0.001	1	<0.001	1	<0.001
Sex	Male	16.98	0.01	<0.001	1.05 (1.04–1.06)	<0.001	1.04 (1.03–1.05)	<0.001
Age (years)	0 to 19	24.63	0.09	<0.001	1	<0.001	1	<0.001
	20 to 39	21.12	0.04		1.23 (1.13–1.34)		1.22 (1.12–1.32)
	40 to 59	18.99	0.02		1.51 (1.40–1.64)		1.47 (1.36–1.59)
	60 to 79s	15.92	0.01		2.30 (2.12–2.49)		2.17 (2.00–2.35)
	80+	12.85	0.02		3.75 (3.46–4.06)		3.59 (3.31–3.89)
Skin color/race	White	17.07	0.01	<0.001	1	<0.001	1	<0.001
	Brown	16.42	0.01		1.09 (1.08–1.11)		1.10 (1.09–1.12)
	Black	15.78	0.04		1.18 (1.16–1.21)		1.17 (1.15–1.20)
Zone	Urban	17.04	0.01	<0.001	1	0.002	1	0.008
	Peri urban	16.27	0.17		1.14 (1.05–1.25)		1.14 (1.05–1.25)
	Rural	15.87	0.04		1.16 (1.12–1.19)		1.15 (1.12–1.17)
County of hospitalization	Inhabitant	17.01	0.01	0.005	1	0.006	1	0.018
County of hospitalization	Outsider	16.99	0.02	0.005	1.08 (1.06–1.09)	0.006	1.01 (1.00–1.02)	0.018
ICU care	No				1	<0.001	1	<0.001
ICU care	Yes				0.57 (0.56–0.58)		0.57 (0.56–0.58)
Major symptoms	No	19.72	0.07	<0.001	1	<0.001	1	<0.001
Major symptoms	Yes	16.99	0,07	<0.001	1.19 (1.16–1.23)	<0.001	1.19 (1.15–1.23)	<0.001
Multimorbidity	No	17.20	0.03	<0.001	1	<0.001	1	<0.001
Multimorbidity	Yes	15.73	0.02	<0.001	1.16 (1.14–1.17)	<0.001	1.15 (1.14–1.17)	<0.001

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[1] CORRESPONDING AUTHOR: Raphael Mendonça Guimarães. Rua Leopoldo Bulhões, 1480, apto 916, CEP: 21041-210 – Rio de Janeiro (RJ) Brazil. E-mail: raphael.guimaraes@fiocruz.br