title: [Breast cancer mortality in women of Southern Brazil, 1980-1999].
abstract: OBJECTIVE
  To analyze time and geographical trends of breast cancer mortality.
  
  
  METHODS
  Annual mortality rates per 100,000 female inhabitants aged 20 to 59 years for the Baixada Santista metropolitan area, the city and state of São Paulo and Brazil, from 1980 to 1999, were standardized by age groups and analyzed. The analyses included regression models to estimate and compare time trends of each area.?
  
  
  RESULTS
  Increasing mortality rate trends were observed for all areas. However, intrametropolitan variations have higher baselines and time trends than the other areas. Santos had standardized mortality rates between 25 and 35 per 100,000 women, which were the highest in the study. Differences between Santos rates and the rates of other cities included in the study were statistically significant (p<0.001). The cities of São Vicente, Cubatão and Peruíbe of the Baixada Santista metropolitan area also showed increased mortality rates trends and higher rates than those for the state of São Paulo and Brazil.
  
  
  CONCLUSIONS
  A similar increasing trend in mortality rates was observed in all cities of the study area and higher rates were seen in Santos. There is a need for further studies in order to identify the determinant conditions for this trend.
authors.affiliation: Programa de Pós-Graduação em Saúde Coletiva, Universidade Católica de Santos, Santos, SP, Brasil.
authors.forename: Augusto
authors.initials: A
authors.lastname: Zago
authors.forename: Luiz A A
authors.initials: LA
authors.lastname: Pereira
authors.forename: Alfésio L F
authors.initials: AL
authors.lastname: Braga
authors.forename: Aylene
authors.initials: A
authors.lastname: Bousquat
mesh_terms: D000328:Adult; D001938:Brazil / Q000453:epidemiology; D001943:Breast Neoplasms / Q000401:mortality*; D005260:Female; D006801:Humans; D015994:Incidence; D008875:Middle Aged; D009026:Mortality / Q000639:trends; D012044:Regression Analysis; D013029:Space-Time Clustering