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BMC Public Health ; 15: 96, 2015 Feb 07.
Artigo em Inglês | MEDLINE | ID: mdl-25886146

RESUMO

BACKGROUND: Breast cancer is the most common cause of death from cancer in women in less developed regions. Therefore, the objective of this study was to provide data on the temporal trends in female breast cancer mortality between 1990 and 2011 and to evaluate its association with the social inequalities present in Brazil. METHODS: Breast cancer mortality data and estimates for the resident population were obtained from the Brazilian National Health Service database for the 1990-2011 period. Age-standardized mortality rates were calculated (20-39, 40-49, 50-69 and ≥70 years) by direct standardization using the 1960 standard world population. Trends were modeled using joinpoint regression model and linear regression. The Social Exclusion Index and the Human Development Index were used to classify the 27 Brazilian states. Pearson's correlation was used to describe the association between the Social Exclusion Index and the Human DeveIopment and the variations in mortality rates in each state. RESULTS: Age-standardized mortality rates in Brazil were found to be stable (annual percent change [APC] = 0.3; 95% CI: -0.1 - 0.7) between 1994 and 2011. Considering the Brazilian states, significant decreases in mortality rates were found in Rio Grande do Sul, Rio de Janeiro and São Paulo. Increases in mortality rates were most notable in the states of Maranhão (APC = 11.2; 95 %CI: 5.8 - 16.9), Piauí (APC = 9.8; 95% CI: 7.6 - 12.1) and Paraíba (APC = 9.3; 95% CI: 6.0 - 12.8). There was a statistically significant correlation between Social Exclusion Index and a change in female breast cancer mortality rates in the Brazilian states between 1990 and 2011 and between Human Development Index and mortality between 2001 and 2011. CONCLUSIONS: Female breast cancer mortality rates are stable in Brazil. Reductions in these rates were found in the more developed states, possibly reflecting better healthcare.


Assuntos
Neoplasias da Mama/mortalidade , Disparidades em Assistência à Saúde/estatística & dados numéricos , Meio Social , Adulto , Fatores Etários , Idoso , Brasil/epidemiologia , Feminino , Humanos , Modelos Lineares , Pessoa de Meia-Idade , Fatores Socioeconômicos , Adulto Jovem
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