Effect of income on the cumulative incidence of COVID-19: an ecological study

Rafael, Ricardo de Mattos Russo; Neto, Mercedes; Depret, Davi Gomes; Gil, Adriana Costa; Fonseca, Mary Hellem Silva; Souza-Santos, Reinaldo

doi:10.1590/1518-8345.4475.3344

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Revista Latino-Americana de Enfermagem

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Sumário

Original Article • Rev. Latino-Am. Enfermagem 28 • 2020 • https://doi.org/10.1590/1518-8345.4475.3344 copy

Effect of income on the cumulative incidence of COVID-19: an ecological study^* * This article refers to the call “COVID-19 in the Global Health Context”.

Authorship SCIMAGO INSTITUTIONS RANKINGS

Objective

to analyze the relationship between per capita income and the cumulative incidence of COVID-19 in the neighborhoods of the city of Rio de Janeiro, RJ, Brazil.

Method

an ecological study using neighborhoods as units of analysis. The cumulative incidence rate per 100,000 inhabitants and the median of potential confounding variables (sex, race, and age) were calculated. Multiple analysis included quantile regression, estimating the regression coefficients of the variable income for every five percentiles from the 10^th to 90^th percentiles to verify the relationship between income and incidence.

Results

the city’s rate was 36.58 new cases per 100,000 inhabitants. In general, the highest rates were observed in the wealthiest regions. Multiple analysis was consistent with this observation since the per capita income affected all percentiles analyzed, with a median regression coefficient of 0.02 (p-value <0.001; R² 32.93). That is, there is an increase of R$ 0.02 in the neighborhood’s per capita income for every unit of incidence.

Conclusion

cumulative incident rates of COVID-19 are influenced by one’s neighborhood of residency, suggesting that access to testing is uneven.

Coronavirus; Pandemics; Uses of Epidemiology; Income; Socioeconomic Factors; Incidence

Administrative region	Number of neighborhoods	% Women	% ≥ 60 year- old individuals	% Afro-descendent individuals	Per capita income(R$)*
Anchieta	4	52.92	14.28	58.64	672.29
Bangu	4	52.47	12.10	63.60	653.26
Barra da Tijuca	8	50.85	7.89	51.97	1387.77
Botafogo	8	55.63	22.36	18.69	3886.05
Campo Grande	5	51.86	10.76	54.37	613.97
Centro	1	53.12	21.02	40.37	1533.38
Cidade de Deus	1	52.93	10.41	72.14	517.99
Comp. do Alemão	1	51.12	8.04	65.85	390.93
Copacabana	2	56.60	27.48	15.89	3821.18
Guaratiba	3	51.15	14.43	59.54	556.62
Ilha do Governador	15	53.26	15.23	48.25	1232.26
Inhaúma	7	53.86	15.26	48.05	1090.60
Irajá	6	54.77	16.36	41.56	993.62
Jacarepaguá	10	53.25	14.87	51.33	1154.20
Lagoa	7	55.47	22.04	46.82	6098.88
Madureira	13	54.13	15.38	52.71	788.18
Maré	1	50.88	6.96	19.96	456.72
Méier	15	54.51	17.97	41.43	1122.58
Paquetá	1	51.53	23.15	56.04	1011.52
Pavuna	6	52.23	11.35	62.13	560.38
Penha	6	52.41	14.60	52.80	774.89
Portuária	4	51.62	11.38	56.47	505.50
Ramos	4	53.86	17.96	42.69	995.38
Realengo	6	52.95	13.07	49.65	1279.35
Rio Comprido	4	53.39	14.76	54.42	869.69
Rocinha	1	50.67	5.62	55.60	455.67
Santa Cruz	3	51.96	10.07	53.87	509.71
Santa Teresa	1	52.97	13.13	65.69	1281.08
São Cristóvão	4	51.99	13.01	49.99	577.60
Tijuca	3	56.31	22.44	36.94	3023.42
Vigário Geral	1	52.25	11.00	63.26	508.27
Vila Isabel	4	55.77	20.81	33.54	2362.79

Administrative Region	General population	Women	Men	≥60-year-old individuals	<60-year-old individuals
Anchieta	15.16	18.87	11.89	4.52	14.53
Bangu	12.62	14.87	10.48	24.85	9.58
Barra da Tijuca	58.51	61.75	55.52	124.23	41.89
Botafogo	66.74	74.93	60.31	70.04	50.47
Campo Grande	13.65	18.60	9.15	25.25	10.70
Centro	58.33	51.84	64.06	127.18	31.60
Cidade de Deus	13.69	23.27	5.17	0.00	13.69
Complexo do Alemão	1.45	2.96	0.00	0.00	1.45
Copacabana	78.17	87.03	71.55	86.91	52.73
Guaratiba	4.87	8.32	1.59	0.00	4.87
Ilha de Paquetá	-	-	-	-	-
Ilha do Governador	18.82	21.01	16.87	21.62	15.52
Inhaúma	26.80	32.28	22.10	47.93	19.35
Irajá	29.56	32.38	27.20	48.28	21.19
Jacarepaguá	17.11	19.15	15.28	37.55	12.40
Jacarezinho	-	-	-	-	-
Lagoa	732.05	723.84	739.68	279.09	97.75
Madureira	37.55	54.64	23.72	26.65	12.64
Maré	1.08	1.17	1.00	11.08	2.31
Méier	69.35	83.15	56.04	43.43	14.58
Pavuna	8.55	13.83	4.15	29.63	12.93
Penha	11.01	14.18	8.18	17.91	9.69
Portuária	2.69	1.13	4.12	18.94	8.22
Ramos	51.37	55.47	47.56	16.83	13.71
Realengo	23.50	26.70	20.73	33.77	10.29
Rio Comprido	9.05	8.75	9.32	34.52	22.79
Rocinha	43.05	46.51	40.07	153.81	40.37
Santa Cruz	27.39	35.08	19.92	2.64	4.88
Santa Teresa	2.17	1.69	2.61	18.61	17.10
São Cristóvão	48.87	77.93	23.06	45.87	17.67
Tijuca	96.58	114.09	80.07	55.69	31.90
Vigário Geral	17.05	21.31	13.72	28.31	19.09
Vila Isabel	49.20	58.46	40.75	56.53	23.77

Predictors	Adjusted R²	β*	CI 95%^†		T^\|\|	p-value
Predictors	Adjusted R²	β*	LI^‡	LS^§	T^\|\|	p-value
Percentile 10	23.41
Per capita income^¶		0.01	0.01	0.02	3.6	<0.001
% 60-year-old or older individuals		0.67	-1.02	2.36	0.78	0.435
% Afro-descendent individuals		0.10	-0.17	0.38	0.76	0.448
% Women		-1.31	-5.65	3.04	-0.59	0.553
Percentile 25	26.32
Per capita income^¶		0.02	0.01	0.02	7.5	<0.001
% 60-year-old or older individuals		-0.23	-2.02	1.56	-0.26	0.798
% Afro-descendent individuals		0.06	-0.08	0.20	0.84	0.403
% Women		-0.06	-5.26	5.15	-0.02	0.983
Percentile 50	32.93
Per capita income^¶		0.02	0.01	0.03	6.09	<0.001
% 60-year-old or older individuals		1.24	-0.65	3.12	1.3	0.197
% Afro-descendent individuals		0.27	-0.01	0.56	1.88	0.062
% Women		-5.01	-10.64	0.63	-1.76	0.081
Percentile 75	41.93
Per capita income^¶		0.03	0.02	0.04	5.1	<0.001
% 60-year-old or older individuals		1.30	-1.38	3.99	0.96	0.339
% Afro-descendent individuals		0.37	-0.14	0.88	1.43	0.155
% Women		-5.61	-13.84	2.62	-1.35	0.180
Percentile 90	50.88
Per capita income^¶		0.03	0.01	0.05	3.30	0.001
% 60-year-old or older individuals		4.30	-0.75	9.35	1.68	0.094
% Afro-descendent individuals		0.29	-0.67	1.24	0.59	0.554
% Women		-19.88	-34.26	-5.50	-2.73	0.007

Escola de Enfermagem de Ribeirão Preto / Universidade de São Paulo Av. Bandeirantes, 3900, 14040-902 Ribeirão Preto SP Brazil, Tel.: +55 (16) 3315-3451 / 3315-4407 - Ribeirão Preto - SP - Brazil
E-mail: rlae@eerp.usp.br

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[1] Corresponding author: Ricardo de Mattos Russo Rafael E-mail: prof.ricardomattos@gmail.com

Brasil

Brasil

Effect of income on the cumulative incidence of COVID-19: an ecological study* * This article refers to the call “COVID-19 in the Global Health Context”.

Objective

Method

Results

Conclusion

Effect of income on the cumulative incidence of COVID-19: an ecological study^* * This article refers to the call “COVID-19 in the Global Health Context”.