Your browser doesn't support javascript.
loading
Gender bias in under-five mortality in low/middle-income countries.
Costa, Janaína Calu; da Silva, Inacio Crochemore Mohnsam; Victora, Cesar Gomes.
Afiliação
  • Costa JC; International Center for Equity in Health, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil.
  • da Silva ICM; International Center for Equity in Health, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil.
  • Victora CG; International Center for Equity in Health, Postgraduate Program in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil.
BMJ Glob Health ; 2(2): e000350, 2017.
Article em En | MEDLINE | ID: mdl-29082002
INTRODUCTION: Due to biological reasons, boys are more likely to die than girls. The detection of gender bias requires knowing the expected relation between male and female mortality rates at different levels of overall mortality, in the absence of discrimination. Our objective was to compare two approaches aimed at assessing excess female under-five mortality rate (U5MR) in low/middle-income countries. METHODS: We compared the two approaches using data from 60 Demographic and Health Surveys (2005-2014). The prescriptive approach compares observed mortality rates with historical patterns in Western societies where gender discrimination was assumed to be low or absent. The descriptive approach is derived from global estimates of all countries with available data, including those affected by gender bias. RESULTS: The prescriptive approach showed significant excess female U5MR in 20 countries, compared with only one country according to the descriptive approach. Nevertheless, both models showed similar country rankings. The 13 countries with the highest and the 10 countries with the lowest rankings were the same according to both approaches. Differences in excess female mortality among world regions were significant, but not among country income groups. CONCLUSION: Both methods are useful for monitoring time trends, detecting gender-based inequalities and identifying and addressing its causes. The prescriptive approach seems to be more sensitive in the identification of gender bias, but needs to be updated using data from populations with current-day structures of causes of death.
Palavras-chave
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Determinantes_sociais_saude / Equity_inequality Idioma: En Revista: BMJ Glob Health Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Aspecto: Determinantes_sociais_saude / Equity_inequality Idioma: En Revista: BMJ Glob Health Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Brasil País de publicação: Reino Unido