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

Author:

Ichihara Maria Yury1ORCID,Ferreira Andrêa J.F.2ORCID,Teixeira Camila S. S.1ORCID,Alves Flávia Jôse O.1ORCID,Rocha Aline Santos3ORCID,Diógenes Victor Hugo Dias4ORCID,Ramos Dandara Oliveira1ORCID,Pinto Júnior Elzo Pereira1ORCID,Flores-Ortiz Renzo1ORCID,Rameh Leila1ORCID,Costa Lilia Carolina C. da5ORCID,Gonzaga Marcos Roberto4ORCID,Lima Everton E. C.6ORCID,Dundas Ruth7ORCID,Leyland Alastair7ORCID,Barreto Maurício L.2ORCID

Affiliation:

1. Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil

2. Universidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil

3. Universidade Federal da Bahia. Escola de Nutrição. Salvador, BA, Brasil

4. Universidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Demografia. Natal, RN, Brasil

5. Universidade Federal da Bahia. Instituto de Matemática e Estatística. Salvador, BA, Brasil

6. Universidade Estadual de Campinas. Departamento de Demografia. Campinas, SP, Brasil

7. Medical Research Council. University of Glasgow, Glasgow, Scotland

Abstract

OBJECTIVE Summarize the literature on the relationship between composite socioeconomic indicators and mortality in different geographical areas of Brazil. METHODS This 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. RESULTS Of 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. CONCLUSIONS Studies 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.

Publisher

Universidade de Sao Paulo, Agencia USP de Gestao da Informacao Academica (AGUIA)

Subject

Public Health, Environmental and Occupational Health

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