Evidence map›Paper›PMID 36228230›Full record

ArticleRevista de saude publica2022

Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review.

Maria Yury Ichihara, Andrêa J F Ferreira, Camila S S Teixeira, Flávia Jôse O Alves, Aline Santos Rocha, Victor Hugo Dias Diógenes, Dandara Oliveira Ramos, Elzo Pereira Pinto Júnior, Renzo Flores-Ortiz, Leila Rameh and 6 more

Abstract readScoping Review
In one paragraph

Article in Revista de saude publica, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

16 authors.

Maria Yury IchiharaFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-8590-6212
Andrêa J F FerreiraFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0002-6884-3624
Camila S S TeixeiraFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-6340-7957
Flávia Jôse O AlvesFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0003-1613-2270
Aline Santos RochaFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0003-3806-6446
Victor Hugo Dias DiógenesUniversidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Demografia. Natal, RN, Brasil.ORCID http://orcid.org/0000-0002-4010-2699
Dandara Oliveira RamosFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-9162-0456
Elzo Pereira Pinto JúniorFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0002-6977-2071
Renzo Flores-OrtizFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-7639-2627
Leila RamehFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-9056-2928
Lilia Carolina C da CostaUniversidade Federal da Bahia. Instituto de Matemática e Estatística. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0001-5107-2723
Marcos Roberto GonzagaUniversidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Demografia. Natal, RN, Brasil.ORCID http://orcid.org/0000-0002-6088-3453
Everton E C LimaUniversidade Estadual de Campinas, Departamento de Demografia. Campinas, SP, Brasil.ORCID http://orcid.org/0000-0001-6275-9854
Ruth DundasMedical Research Council. University of Glasgow, Glasgow, Scotland.ORCID http://orcid.org/0000-0002-3836-4286
Alastair LeylandMedical Research Council. University of Glasgow, Glasgow, Scotland.ORCID http://orcid.org/0000-0003-3741-7099
Maurício L BarretoFundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil.ORCID http://orcid.org/0000-0002-0215-4930

Funding

Chief Scientist Office SPHSU17Medical Research Council MC_UU_00022/2Wellcome Trust
6 · The paper itself

Abstract

objectiveSummarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil.

methodsThis scoping review included articles published between January 1, 2000, and August 31, 2020, retrieved by means of a bibliographic search carried out in the Medline, Scopus, Web of Science, and Lilacs databases. Studies reporting on the association between composite socioeconomic indicators and all-cause, or specific cause of death in any age group in different geographical areas were selected. The review summarized the measures constructed, their associations with the outcomes, and potential study limitations.

resultsOf the 77 full texts that met the inclusion criteria, the study reviewed 24. The area level of composite socioeconomic indicators analyzed comprised municipalities (n = 6), districts (n = 5), census tracts (n = 4), state (n = 2), country (n = 2), and other areas (n = 5). Six studies used composite socioeconomic indicators such as the Human Development Index, Gross Domestic Product, and the Gini Index; the remaining 18 papers created their own socioeconomic measures based on sociodemographic and health indicators. Socioeconomic status was inversely associated with higher rates of all-cause mortality, external cause mortality, suicide, homicide, fetal and infant mortality, respiratory and circulatory diseases, stroke, infectious and parasitic diseases, malnutrition, gastroenteritis, and oropharyngeal cancer. Higher mortality rates due to colorectal cancer, leukemia, a general group of neoplasms, traffic accident, and suicide, in turn, were observed in less deprived areas and/or those with more significant socioeconomic development. Underreporting of death and differences in mortality coverage in Brazilian areas were cited as the main limitation.

conclusionsStudies analyzed mortality inequalities in different geographical areas by means of composite socioeconomic indicators, showing that the association directions vary according to the mortality outcome. But studies on all-cause mortality and at the census tract level remain scarce. The results may guide the development of new composite socioeconomic indicators for use in mortality inequality analysis.

Indexed as

Social ClassSuicideBrazilCitiesHumansInfantMortalitySocioeconomic Factors

Identifiers

PMID36228230
PMCPMC9529207

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Registered trials

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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.