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Lima EECD, Costa LCCD, Souza RF, Rocha CODE, Ichihara MYT. Presidential election results in 2018-2022 and its association with excess mortality during the 2020-2021 COVID-19 pandemic in Brazilian municipalities. CAD SAUDE PUBLICA 2024; 40:e00194723. [PMID: 38896596 PMCID: PMC11178372 DOI: 10.1590/0102-311xen194723] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/12/2023] [Accepted: 12/15/2023] [Indexed: 06/21/2024] Open
Abstract
We evaluated the hypothesis of an association between excess mortality and political partisanship in Brazil using municipal death certificates registered in the Brazilian Ministry of Health database and first-round electoral results of Presidential elections in 2018 and 2022. Considering the former Brazilian President's stance of discrediting and neglecting the severity of the pandemic, we expect a possible relationship between excessive mortality rates during the COVID-19 health crisis and the number of municipal votes for Bolsonaro. Our results showed that, in both elections, the first-round percentage of municipal votes for Bolsonaro was positively associated with the peaks of excess deaths across Brazilian municipalities in 2020 and 2021. Despite the excess mortality during the pandemic, the political loyalty to Bolsonaro remained the same during the electoral period of 2022. A possible explanation for this is linked to the Brazilian political scenario, which presents an environment of tribal politics and affective polarization.
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Affiliation(s)
| | | | - Rafael F Souza
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brasil
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2
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Gonzaga MR, Queiroz BL, Freire FHMA, Monteiro-da-Silva JHC, Lima EEC, Silva-Júnior WP, Diógenes VHD, Flores-Ortiz R, da Costa LCC, Pinto-Junior EP, Ichihara MY, Teixeira CSS, Alves FJO, Rocha AS, Ferreira AJF, Barreto ML, Katikireddi SV, Dundas R, Leyland AH. Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030. Popul Health Metr 2024; 22:9. [PMID: 38802870 PMCID: PMC11129360 DOI: 10.1186/s12963-024-00329-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 05/07/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND Mortality rate estimation in small areas can be difficult due the low number of events/exposure (i.e. stochastic error). If the death records are not completed, it adds a systematic uncertainty on the mortality estimates. Previous studies in Brazil have combined demographic and statistical methods to partially overcome these issues. We estimated age- and sex-specific mortality rates for all 5,565 Brazilian municipalities in 2010 and forecasted probabilistic mortality rates and life expectancy between 2010 and 2030. METHODS We used a combination of the Tool for Projecting Age-Specific Rates Using Linear Splines (TOPALS), Bayesian Model, Spatial Smoothing Model and an ad-hoc procedure to estimate age- and sex-specific mortality rates for all Brazilian municipalities for 2010. Then we adapted the Lee-Carter model to forecast mortality rates by age and sex in all municipalities between 2010 and 2030. RESULTS The adjusted sex- and age-specific mortality rates for all Brazilian municipalities in 2010 reveal a distinct regional pattern, showcasing a decrease in life expectancy in less socioeconomically developed municipalities when compared to estimates without adjustments. The forecasted mortality rates indicate varying regional improvements, leading to a convergence in life expectancy at birth among small areas in Brazil. Consequently, a reduction in the variability of age at death across Brazil's municipalities was observed, with a persistent sex differential. CONCLUSION Mortality rates at a small-area level were successfully estimated and forecasted, with associated uncertainty estimates also generated for future life tables. Our approach could be applied across countries with data quality issues to improve public policy planning.
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Affiliation(s)
- Marcos R Gonzaga
- Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
| | - Bernardo L Queiroz
- Graduate Program in Demography, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil
| | - Flávio H M A Freire
- Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | | | - Everton E C Lima
- Graduate Program in Demography, Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, Brazil
| | - Walter P Silva-Júnior
- Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | - Victor H D Diógenes
- Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil
| | - Renzo Flores-Ortiz
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | | | - Elzo P Pinto-Junior
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | - Maria Yury Ichihara
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | - Camila S S Teixeira
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | - Flávia J O Alves
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | - Aline S Rocha
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
- School of Nutrition, Universidade Federal da Bahia (UFBA), Salvador, Brazil
| | - Andrêa J F Ferreira
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | - Maurício L Barreto
- Centro de Integração de Dados e Conhecimentos para a Saúde (Center of Data and Knowledge Integration for Health) - CIDACS/ Gonçalo Moniz Institute - Fiocruz/Bahia, Salvador, Brazil
| | | | - Ruth Dundas
- MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland
| | - Alastair H Leyland
- MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland
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Azevedo Lemos D, de Araújo Fonseca LG, Bento Florêncio R, Barbosa de Almeida JA, Dantas Florentino Lima IN, Peroni Gualdi L. Hospitalisations and fatality due to respiratory diseases according to a national database in Brazil: a longitudinal study. BMJ Open Respir Res 2024; 11:e002103. [PMID: 38387997 PMCID: PMC10882403 DOI: 10.1136/bmjresp-2023-002103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/19/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Respiratory diseases (RDs) cause millions of hospitalisations and deaths worldwide, resulting in economic and social impacts. Strategies for health promotion and disease prevention based on the epidemiological profile of the population may reduce hospital costs. AIM To characterise hospitalisations and deaths due to RDs in Brazilian adults above 20 years old between 2008 and 2021. METHODS This ecological study used secondary data of hospitalisations and deaths due to RDs from the Hospital Information System of the Brazilian Unified Health System between 2008 and 2021. Data were grouped according to region, age group and sex. The period was divided into first (2008-2011), second (2012-2015) and third (2016-2019) quadrennia and one biennium (2020-2021), and all data were analysed using the GraphPad Prism; statistical significance was set at p<0.05. RESULTS A total of 9 502 378 hospitalisations due to RDs were registered between 2008 and 2021. The south and southeast regions presented the highest hospitalisation and fatality rate, respectively, in the age group ≥80 years with no significant differences between sexes. Also, RDs caused 1 170 504 deaths, with a national fatality rate of 12.32%. CONCLUSION RDs affected the Brazilian population and impaired the health system, especially the hospital environment. The south/southeast regions were the most affected, and the ageing process contributed to the increased incidence of RDs.
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Affiliation(s)
- Darllane Azevedo Lemos
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
| | - Luiza Gabriela de Araújo Fonseca
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
| | - Rencio Bento Florêncio
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
| | - José Alexandre Barbosa de Almeida
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
| | - Illia Nadinne Dantas Florentino Lima
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
| | - Lucien Peroni Gualdi
- Programa de Pós-Graduação em Ciências da Reabilitação/Faculdade de Ciências da Saúde do Trairi, Universidade Federal do Rio Grande do Norte, Santa Cruz, Rio Grande do Norte, Brazil
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Zimeo Morais GA, Miraglia JL, de Oliveira BZ, Mistro S, Hisatugu WH, Greffin D, Marques CB, Reis EP, de Lima HM, Szlejf C. Factors associated with the quality of death certification in Brazilian municipalities: A data-driven non-linear model. PLoS One 2023; 18:e0290814. [PMID: 37651355 PMCID: PMC10470916 DOI: 10.1371/journal.pone.0290814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 08/16/2023] [Indexed: 09/02/2023] Open
Abstract
Studies evaluating the local quality of death certification in Brazil focused on completeness of death reporting or inappropriate coding of causes of death, with few investigating missing data. We aimed to use missing and unexpected values in core topics to assess the quality of death certification in Brazilian municipalities, to evaluate its correlation with the percentage of garbage codes, and to employ a data-driven approach with non-linear models to investigate the association of the socioeconomic and health infrastructure context with quality of death statistics among municipalities. This retrospective study used data from the Mortality Information System (2010-2017), and municipal data regarding healthcare infrastructure, socioeconomic characteristics, and death rates. Quality of death certification was assessed by missing or unexpected values in the following core topics: dates of occurrence, registration, and birth, place of occurrence, certifier, sex, and marital status. Models were fit to classify municipalities according to the quality of death certification (poor quality defined as death records with missing or unexpected values in core topics ≥ 80%). Municipalities with poor quality of death certification (43.9%) presented larger populations, lower death rates, lower socioeconomic index, healthcare infrastructure with fewer beds and physicians, and higher proportion of public healthcare facilities. The correlation coefficients between quality of death certification assessed by missing or unexpected values and the proportion of garbage codes were weak (0.11-0.49), but stronger for municipalities with lower socioeconomic scores. The model that best fitted the data was the random forest classifier (ROC AUC = 0.76; precision-recall AUC = 0.78). This innovative way of assessing the quality of death certification could help quality improvement initiatives to include the correctness of essential fields, in addition to garbage coding or completeness of records, especially in municipalities with lower socioeconomic status where garbage coding and the correctness of core topics appear to be related issues.
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Affiliation(s)
| | - João Luiz Miraglia
- Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil
| | - Bruno Zoca de Oliveira
- Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil
| | - Sóstenes Mistro
- Multidisciplinary Institute of Health, Federal University of Bahia, Vitoria da Conquista, Bahia, Brazil
| | - Wilian Hiroshi Hisatugu
- Department of Computing and Electronics, Federal University of Espirito Santo, Vitoria, Espírito Santo, Brazil
| | | | | | - Eduardo Pontes Reis
- Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil
| | | | - Claudia Szlejf
- Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil
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Queiroz BL. Challenges related to records and quality of information in the Amazon. CAD SAUDE PUBLICA 2023; 39:e00098323. [PMID: 37585905 PMCID: PMC10494665 DOI: 10.1590/0102-311xpt098323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 06/19/2023] [Accepted: 06/23/2023] [Indexed: 08/18/2023] Open
Affiliation(s)
- Bernardo Lanza Queiroz
- Departamento de Demografia, Universidade Federal de Minas Gerais, Belo Horizonte, Brasil
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6
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Diógenes VHD, Pinto EP, Gonzaga MR, Queiroz BL, Lima EEC, da Costa LCC, Rocha AS, Ferreira AJF, Teixeira CSS, Alves FJO, Rameh L, Flores-Ortiz R, Leyland A, Dundas R, Barreto ML, Ichihara MYT. Differentials in death count records by databases in Brazil in 2010. Rev Saude Publica 2022; 56:92. [PMID: 36287489 PMCID: PMC9586519 DOI: 10.11606/s1518-8787.2022056004282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 12/07/2021] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE To compare the death counts from three sources of information on mortality available in Brazil in 2010, the Mortality Information System (SIM - Sistema de Informações sobre Mortalidade ), Civil Registration Statistic System (RC - Sistema de Estatísticas de Resgistro Civil ), and the 2010 Demographic Census at various geographical levels, and to confirm the association between municipal socioeconomic characteristics and the source which showed the highest death count. METHODS This is a descriptive and comparative study of raw data on deaths in the SIM, RC and 2010 Census databases, the latter held in Brazilian states and municipalities between August 2009 and July 2010. The percentage of municipalities was confirmed by the database showing the highest death count. The association between the source of the highest death count and socioeconomic indicators - the Índice de Privação Brasileiro (IBP - Brazilian Deprivation Index) and Índice de Desenvolvimento Humano Municipal (IHDM - Municipal Human Development Index) - was performed by bivariate choropleth and Moran Local Index of Spatial Association (LISA) cluster maps. RESULTS Confirmed that the SIM is the database with the highest number of deaths counted for all Brazilian macroregions, except the North, in which the highest coverage was from the 2010 Census. Based on the indicators proposed, in general, the Census showed a higher coverage of deaths than the SIM and the RC in the most deprived (highest IBP values) and less developed municipalities (lowest IDHM values) in the country. CONCLUSION The results highlight regional inequalities in how the databases chosen for this study cover death records, and the importance of maintaining the issue of mortality on the basic census questionnaire.
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Affiliation(s)
- Victor Hugo Dias Diógenes
- Universidade Federal do Rio Grande do NorteCentro de Ciências Exatas e da TerraPrograma de Pós-Graduação em DemografiaNatalRNBrasil Universidade Federal do Rio Grande do Norte . Centro de Ciências Exatas e da Terra . Programa de Pós-Graduação em Demografia . Natal , RN , Brasil ,Universidade Federal da ParaíbaCentro de Ciências Sociais AplicadasDepartamento de Finanças e ContabilidadeJoão PessoaPBBrasil Universidade Federal da Paraíba . Centro de Ciências Sociais Aplicadas . Departamento de Finanças e Contabilidade . João Pessoa , PB , Brasil
| | - Elzo Pereira Pinto
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil
| | - Marcos Roberto Gonzaga
- Universidade Federal do Rio Grande do NorteCentro de Ciências Exatas e da TerraPrograma de Pós-Graduação em DemografiaNatalRNBrasil Universidade Federal do Rio Grande do Norte . Centro de Ciências Exatas e da Terra . Programa de Pós-Graduação em Demografia . Natal , RN , Brasil ,Universidade Federal do Rio Grande do NorteCentro de Ciências Exatas e da TerraDepartamento de Demografia e Ciências AtuariaisNatalRNBrasil Universidade Federal do Rio Grande do Norte . Centro de Ciências Exatas e da Terra . Departamento de Demografia e Ciências Atuariais . Natal , RN , Brasil
| | - Bernardo Lanza Queiroz
- Universidade Federal de Minas GeraisFaculdade de Ciências EconômicasCentro de Desenvolvimento e Planejamento RegionalBelo HorizonteMGBrasil Universidade Federal de Minas Gerais . Faculdade de Ciências Econômicas . Centro de Desenvolvimento e Planejamento Regional . Belo Horizonte , MG , Brasil
| | - Everton E. C. Lima
- Universidade Estadual de CampinasInstituto de Filosofia e Ciências HumanasNúcleo de Estudos de PopulaçãoCampinasSPBrasil Universidade Estadual de Campinas . Instituto de Filosofia e Ciências Humanas e Núcleo de Estudos de População . Campinas , SP , Brasil
| | - Lilia Carolina C. da Costa
- Universidade Federal da BahiaInstituto de Matemática e EstatísticaDepartamento de EstatísticaSalvadorBABrasil Universidade Federal da Bahia . Instituto de Matemática e Estatística . Departamento de Estatística . Salvador , BA , Brasil
| | - Aline S. Rocha
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil ,Universidade Federal da BahiaEscola de NutriçãoPrograma de Pós-Graduação em Alimento, Nutrição e SaúdeSalvadorBABrasil Universidade Federal da Bahia . Escola de Nutrição . Programa de Pós-Graduação em Alimento, Nutrição e Saúde . Salvador , BA , Brasil
| | - Andrêa J. F. Ferreira
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil ,Universidade Federal da BahiaInstituto de Saúde ColetivaPrograma de Pós-Graduação em Saúde ColetivaSalvadorBABrasil Universidade Federal da Bahia . Instituto de Saúde Coletiva . Programa de Pós-Graduação em Saúde Coletiva . Salvador , BA , Brasil
| | - Camila S. S. Teixeira
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil ,Universidade Federal da BahiaInstituto de Saúde ColetivaPrograma de Pós-Graduação em Saúde ColetivaSalvadorBABrasil Universidade Federal da Bahia . Instituto de Saúde Coletiva . Programa de Pós-Graduação em Saúde Coletiva . Salvador , BA , Brasil
| | - Flávia Jôse O Alves
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil ,Universidade Federal da BahiaInstituto de Saúde ColetivaPrograma de Pós-Graduação em Saúde ColetivaSalvadorBABrasil Universidade Federal da Bahia . Instituto de Saúde Coletiva . Programa de Pós-Graduação em Saúde Coletiva . Salvador , BA , Brasil
| | - Leila Rameh
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil
| | - Renzo Flores-Ortiz
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil
| | - Alastair Leyland
- University of GlasgowMedical Research CouncilGlasgowScotland University of Glasgow . Medical Research Council . Glasgow , Scotland
| | - Ruth Dundas
- University of GlasgowMedical Research CouncilGlasgowScotland University of Glasgow . Medical Research Council . Glasgow , Scotland
| | - Maurício L. Barreto
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil ,Universidade Federal da BahiaInstituto de Saúde ColetivaPrograma de Pós-Graduação em Saúde ColetivaSalvadorBABrasil Universidade Federal da Bahia . Instituto de Saúde Coletiva . Programa de Pós-Graduação em Saúde Coletiva . Salvador , BA , Brasil
| | - Maria Yury Travassos Ichihara
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz . Centro de Integração de Dados e Conhecimentos para Saúde . Salvador , BA , Brasil
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Ichihara MY, Ferreira AJ, Teixeira CSS, Alves FJO, Rocha AS, Diógenes VHD, Ramos DO, Pinto EP, Flores-Ortiz R, Rameh L, da Costa LCC, Gonzaga MR, Lima EEC, Dundas R, Leyland A, Barreto ML. Mortality inequalities measured by socioeconomic indicators in Brazil: a scoping review. Rev Saude Publica 2022; 56:85. [PMID: 36228230 PMCID: PMC9529207 DOI: 10.11606/s1518-8787.2022056004178] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 11/10/2021] [Indexed: 11/17/2022] Open
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.
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Affiliation(s)
- Maria Yury Ichihara
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
| | - Andrêa J.F. Ferreira
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaInstituto de Saúde ColetivaSalvadorBABrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil
| | - Camila S. S. Teixeira
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaInstituto de Saúde ColetivaSalvadorBABrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil
| | - Flávia Jôse O. Alves
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaInstituto de Saúde ColetivaSalvadorBABrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil
| | - Aline Santos Rocha
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaEscola de NutriçãoSalvadorBABrasil Universidade Federal da Bahia. Escola de Nutrição. Salvador, BA, Brasil
| | - Victor Hugo Dias Diógenes
- Universidade Federal do Rio Grande do NortePrograma de Pós-Graduação em DemografiaNatalRNBrasil Universidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Demografia. Natal, RN, Brasil
- Universidade Federal da ParaíbaDepartamento de Finanças e ContabilidadeJoão PessoaPBBrasilUniversidade Federal da Paraíba. Departamento de Finanças e Contabilidade. João Pessoa, PB, Brasil
| | - Dandara Oliveira Ramos
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaInstituto de Saúde ColetivaSalvadorBABrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil
| | - Elzo Pereira Pinto
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
| | - Renzo Flores-Ortiz
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
| | - Leila Rameh
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
| | - Lilia Carolina C. da Costa
- Universidade Federal da BahiaInstituto de Matemática e EstatísticaSalvadorBABrasil Universidade Federal da Bahia. Instituto de Matemática e Estatística. Salvador, BA, Brasil
| | - Marcos Roberto Gonzaga
- Universidade Federal do Rio Grande do NortePrograma de Pós-Graduação em DemografiaNatalRNBrasil Universidade Federal do Rio Grande do Norte. Programa de Pós-Graduação em Demografia. Natal, RN, Brasil
| | - Everton E. C. Lima
- Universidade Estadual de CampinasDepartamento de DemografiaCampinasSPBrasilUniversidade Estadual de Campinas, Departamento de Demografia. Campinas, SP, Brasil
| | - Ruth Dundas
- Medical Research CouncilUniversity of GlasgowGlasgowScotlandMedical Research Council. University of Glasgow, Glasgow, Scotland
| | - Alastair Leyland
- Medical Research CouncilUniversity of GlasgowGlasgowScotlandMedical Research Council. University of Glasgow, Glasgow, Scotland
| | - Maurício L. Barreto
- Fundação Oswaldo CruzCentro de Integração de Dados e Conhecimentos para SaúdeSalvadorBABrasil Fundação Oswaldo Cruz. Centro de Integração de Dados e Conhecimentos para Saúde. Salvador, BA, Brasil
- Universidade Federal da BahiaInstituto de Saúde ColetivaSalvadorBABrasilUniversidade Federal da Bahia. Instituto de Saúde Coletiva. Salvador, BA, Brasil
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Castanheira HC, Monteiro da Silva JHC. Examining sex differences in the completeness of Peruvian CRVS data and adult mortality estimates. GENUS 2022; 78:3. [PMID: 35068495 PMCID: PMC8760572 DOI: 10.1186/s41118-021-00151-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 11/28/2021] [Indexed: 11/28/2022] Open
Abstract
The production, compilation, and publication of death registration records is complex and usually involves many institutions. Assessing available data and the evolution of the completeness of the data compiled based on demographic techniques and other available data sources is of great importance for countries and for having timely and disaggregated mortality estimates. In this paper, we assess whether it is reasonable, based on the available data, to assume that there is a sex difference in the completeness of male and female death records in Peru in the last 30 years. In addition, we assess how the gap may have evolved with time by applying two-census death distribution methods on health-related registries and analyzing the information from the Demographic and Health Surveys and civil registries. Our findings suggest that there is no significant sex difference in the completeness of male and female health-related registries and, consequently, the sex gap currently observed in adult mortality estimates might be overestimated.
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Affiliation(s)
- Helena Cruz Castanheira
- Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile
| | - José Henrique Costa Monteiro da Silva
- Latin American and Caribbean Demographic Centre (CELADE)-Population Division of the United Nations Economic Commission for Latin America and the Caribbean (ECLAC), Santiago, Chile
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Lima EEC, Vilela EA, Peralta A, Rocha M, Queiroz BL, Gonzaga MR, Piscoya-Díaz M, Martinez-Folgar K, García-Guerrero VM, Freire FHMA. Investigating regional excess mortality during 2020 COVID-19 pandemic in selected Latin American countries. GENUS 2021; 77:30. [PMID: 34744175 PMCID: PMC8564791 DOI: 10.1186/s41118-021-00139-1] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 10/11/2021] [Indexed: 11/10/2022] Open
Abstract
In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2-10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1186/s41118-021-00139-1.
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Affiliation(s)
| | | | - Andrés Peralta
- Public Health Institute, Pontifical Catholic University of Ecuador (PUCE) – Ecuador, Quito, Ecuador
| | | | | | - Marcos R. Gonzaga
- Departamento de Demografia e Ciências Atuariais, Universidade Federal do Rio Grande do Norte, Natal, Brazil
| | | | - Kevin Martinez-Folgar
- Urban Health Collaborative & Department of Epidemiology and Biostatistics, Dornsife School of Public
Health, Drexel University, Philadelphia, PA USA
| | | | - Flávio H. M. A. Freire
- Departamento de Demografia e Ciências Atuariais, Universidade Federal do Rio Grande do Norte, Natal, Brazil
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