Evidence map›Paper›PMID 38088714›Full record

ArticleRevista brasileira de epidemiologia = Brazilian journal of epidemiology2023

Spatial-temporal evolution of tuberculosis incidence rates in indigenous and non-indigenous people of Brazil, from 2011 to 2022.

Isabela Freitas Vaz, Natália Santana Paiva, Paulo Victor de Sousa Viana

Abstract read
In one paragraph

Article in Revista brasileira de epidemiologia = Brazilian journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 citing papers in PubMed.

  1. Article
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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

3 authors.

Isabela Freitas VazFundação Oswaldo Cruz, Escola Nacional de Saúde Pública Sergio Arouca - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0009-0005-0336-4277
Natália Santana PaivaUniversidade Federal do Rio de Janeiro, Instituto de Estudos em Saúde Coletiva - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0003-0541-4686
Paulo Victor de Sousa VianaFundação Oswaldo Cruz, Escola Nacional de Saúde Pública Sergio Arouca, Centro de Referência Professor Hélio Fraga - Rio de Janeiro (RJ), Brazil.ORCID http://orcid.org/0000-0002-8449-2705

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo describe the space-time evolution of TB incidence rates (TI) in indigenous and non-indigenous people, according to the Federative Units (UF) of Brazil, from 2011 to 2022.

methodsEcological, temporal, and spatial study on new tuberculosis cases in Brazil among indigenous and non-indigenous populations. Data from the Notifiable Diseases Information System (Sinan) were collected from 2011 to 2022 and stratified by Federal Unit, explored and statistically analyzed using R software version 4.2.3.

resultsThe mean TI among indigenous populations in Brazil was 71.7 new cases per 100,000 inhabitants, while for non-indigenous populations it was 28.6/100,000 inhabitants. The regions of the country that presented the highest (mean) incidence among indigenous populations were: Central-West (102.8/100,000 inhabitants), Southeast (99.6/100,000 inhabitants), and North (79.9/100,000 inhabitants). For non-indigenous populations the highest incidence was in the North region (36.5/100,000 inhabitants), followed by the Southeast (31.3/100,000), and the Northeast (27,4/100,000 inhabitants). The analysis showed that the highest incidence of TB cases among indigenous populations occurred in the states of: SP, RO, RJ, MS, MT e PA.

conclusionHigh incidence of the disease compared to the non-indigenous population show the need for a specific approach to address the health needs of these populations. Regional disparities in incidence indicate the need to address socioeconomic and infrastructure issues that affect the health of indigenous populations.

Indexed as

TuberculosisBrazilHumansIncidenceIndigenous PeoplesSocioeconomic Factors

Identifiers

PMID38088714
PMCPMC10715319

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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.