Your browser doesn't support javascript.
loading
Estimation and probabilistic projection of age- and sex-specific mortality rates across Brazilian municipalities between 2010 and 2030.
Gonzaga, Marcos R; Queiroz, Bernardo L; Freire, Flávio H M A; Monteiro-da-Silva, José H C; Lima, Everton E C; Silva-Júnior, Walter P; Diógenes, Victor H D; Flores-Ortiz, Renzo; da Costa, Lilia C C; Pinto-Junior, Elzo P; Ichihara, Maria Yury; Teixeira, Camila S S; Alves, Flávia J O; Rocha, Aline S; Ferreira, Andrêa J F; Barreto, Maurício L; Katikireddi, Srinivasa Vittal; Dundas, Ruth; Leyland, Alastair H.
Afiliação
  • Gonzaga MR; Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil. marcos.gonzaga@ufrn.br.
  • Queiroz BL; Graduate Program in Demography, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil.
  • Freire FHMA; Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  • Monteiro-da-Silva JHC; Graduate Group in Demography, University of Pennsylvania, Philadelphia, PA, USA.
  • Lima EEC; Graduate Program in Demography, Universidade Estadual de Campinas (UNICAMP), Campinas, São Paulo, Brazil.
  • Silva-Júnior WP; Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  • Diógenes VHD; Graduate Program in Demography, Universidade Federal do Rio Grande do Norte (UFRN), Natal, Rio Grande do Norte, Brazil.
  • Flores-Ortiz R; 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.
  • da Costa LCC; Universidade Federal da Bahia (UFBA), Salvador, Bahia, Brazil.
  • Pinto-Junior EP; 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.
  • Ichihara MY; 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.
  • Teixeira CSS; 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.
  • Alves FJO; 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.
  • Rocha AS; 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.
  • Ferreira AJF; School of Nutrition, Universidade Federal da Bahia (UFBA), Salvador, Brazil.
  • Barreto ML; 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.
  • Katikireddi SV; 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.
  • Dundas R; MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland.
  • Leyland AH; MRC/CSO Social and Public Health Sciences, Unit University of Glasgow, Glasgow, Scotland.
Popul Health Metr ; 22(1): 9, 2024 May 27.
Article em En | MEDLINE | ID: mdl-38802870
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.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Expectativa de Vida / Mortalidade / Teorema de Bayes / Cidades Limite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Expectativa de Vida / Mortalidade / Teorema de Bayes / Cidades Limite: Adolescent / Adult / Aged / Aged80 / Child / Child, preschool / Female / Humans / Infant / Male País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2024 Tipo de documento: Article