Evidence map›Paper›PMID 41370476›Full record

ArticleRevista brasileira de epidemiologia = Brazilian journal of epidemiology2025

Inequities in COVID-19 morbidity in Brazil: the influence of demographic and socioeconomic characteristics and preexisting health conditions.

Célia Landmann Szwarcwald, Deborah Carvalho Malta, Wanessa da Silva Almeida, Paulo Roberto Borges de Souza Júnior, Giseli Nogueira Damacena, Crizian Saar Gomes, Euclides Ayres de Castilho

Abstract read
In one paragraph

Article in Revista brasileira de epidemiologia = Brazilian journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Impact of the COVID-19 pandemic on the health situation of the Brazilian population.The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Célia Landmann SzwarcwaldFundação Oswaldo Cruz, Institute of Scientific and Technological Communication and Information in Health, Health Information Laboratory - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0002-7798-2095
Deborah Carvalho MaltaUniversidade Federal de Minas Gerais, School of Nursing - Belo Horizonte (MG), Brazil.ORCID http://orcid.org/0000-0002-8214-5734
Wanessa da Silva AlmeidaFundação Oswaldo Cruz, Institute of Scientific and Technological Communication and Information in Health, Health Information Laboratory - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0002-5164-8603
Paulo Roberto Borges de Souza JúniorFundação Oswaldo Cruz, Institute of Scientific and Technological Communication and Information in Health, Health Information Laboratory - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0001-8677-0134
Giseli Nogueira DamacenaFundação Oswaldo Cruz, Institute of Scientific and Technological Communication and Information in Health, Health Information Laboratory - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0002-7059-3353
Crizian Saar GomesUniversidade Federal de Minas Gerais, School of Nursing - Belo Horizonte (MG), Brazil.ORCID http://orcid.org/0000-0001-6586-4561
Euclides Ayres de CastilhoUniversidade de São Paulo, School of Medicine, Department of Preventive Medicine - São Paulo (SP), Brazil.ORCID http://orcid.org/0000-0002-7352-8784

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze COVID-19 morbidity according to sociodemographic characteristics and preexisting health conditions, based on data from a survey conducted in 2023 online called "ConVid-2 Behavior Survey".

methodsThis was a cross-sectional epidemiological study using the Respondent-Driven Sampling (RDS) method. Prevalence estimates and 95% confidence intervals were calculated for five COVID-19-related indicators. Logistic regression models were applied to test the hypothesis of associations between outcomes and sociodemographic characteristics.

resultsThe sample included 3,805 individuals aged 18 years or older. Approximately 50% of participants had received four or more doses of the COVID-19 vaccine. The estimated prevalence of COVID-19 was 49.5%, with significant and increasing gradients by age and decreasing gradients by education level. Long COVID was identified in 32% of individuals with confirmed COVID-19, with the highest proportions among women (38.3%; OR=0.52; p=0.002), those with financial difficulties (38.9%; OR=1.68; p=0.02), and those with a chronic noncommunicable disease (36.3%; OR=1.58; p=0.03). The highest rate of hospitalization occurred among those with Long COVID (12.7%). Death of a household member due to COVID-19 was reported by 5.1% of participants.

conclusionThe findings revealed major socioeconomic inequalities across all indicators related to COVID-19 morbidity. Older age, preexisting health conditions, and Long COVID contributed to greater disease severity and increased hospitalization. These findings are relevant to inform public policies aimed at supporting the diagnosis and management of COVID-19-related complications within the public health system.

Indexed as

COVID-19Health Status DisparitiesAdolescentAdultAgedBrazilCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceSociodemographic FactorsSocioeconomic FactorsYoung Adult

Identifiers

PMID41370476
PMCPMC12685276

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.