Efeitos da idade-período e coorte na mortalidade por câncer do ovário no Brasil e suas grandes regiões

• Autor(a) principal: Karina Cardoso Meira
• Data de Publicação: 2019
• Outros Autores: Juliano dos Santos, Cosme Marcelo Furtado Passos da Silva, Aline Alves Ferreira, Raphael Mendonça Guimarães, Taynãna César Simões
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Cadernos de Saúde Pública
• Texto Completo: https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/7060
• topic: Neoplasias Ovarianas; Mortalidade; Estudos de Séries Temporais

This article sought to evaluate the effects of age, period and birth cohort (APC) on the temporal evolution of mortality due to ovarian cancer in Brazil and its regions from 1980 to 2014. This is an ecological, time-trend study using APC models with a Baysean approach and INLA (Integrated Nested Laplace Approximations) deterministic method for parameter inference. Mortality data and population data were obtained from the Brazilian Health Informatics Department. Rates of mortality due to ovarian cancer, according to geographical region, were standardized using the direct method, after correcting deaths for undefined causes and incomplete cancer diagnosis. In the period we studied, Brazil had 4.91 deaths due to ovarian cancer per 100,000 women, the Southern (5.66) and Southeastern regions (5.70) had higher rates per 100,000 women and the Northern region had the lowest rate (3.13/100,000 women). In all regions, there was a progressive increase in mortality as ages advanced. The multivariate best fit APC model showed positive risk of death in the Central and Northeast between 2010-2014 and, beginning in 1995-1999, in the South. We also observed a positive and significant risk of death for older cohorts in the South and Southeast and a reduced risk for younger cohorts. The inverse was opposed in the Northern and Northeastern regions. The data shows a heterogeneous pattern in the temporal evolution of mortality due to ovarian cancer in the Brazilian geographical regions, which may be related to the distinct demographic and epidemiological transition processes experienced in these regions.