Mortality rates due to diseases of the circulatory system (DCS) in Ribeirão Preto - SP, from 1980 to 2004.
BACKGROUND
In terms of epidemiologic transition, century-long trend studies may act as subsidies for health management hypotheses.


OBJECTIVE
Identify mortality rate pattern for diseases of the circulatory system (DCS) in Ribeirão Preto, SP (RP-SP), in the period between 1980 and 2004.


METHODS
The number of deaths due to DCS were obtained from the Mortality Information System (SIM). Populational estimates for RP-SP - taking gender, age group, and calendar years into account - were obtained from the Brazilian Institute of Geography and Statistics (IBGE). Specific mortality rates were calculated on yearly basis according to gender and age group in 10-year intervals starting at 30 years of age. The trend analysis was conducted through polynomial regression models for time series. Significance level was < 0.05.


RESULTS
Specific mortality rates due to DCS increased with age both among males and females, being higher among males in the 40 to 49-year-old range. After that, figures were comparable, although at 80-year-old age groups data for females showed to be higher than that for males in some years of the series. Along the study period, significant reduction was observed for mortality rates among both males and females, and for all age ranges from those causes (p<0.001).


CONCLUSIONS
Mortality rate pattern due to DCS in RP-SP was similar to that found in developed areas, which helped formulate hypotheses on the likely protection factors that may explain the observed decline.
Moraes
Suzana Alves de
SA
Escola de Enfermagem de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, - Brasil. samoraes@usp.br
Suzuki
Cláudio Shigueki
CS
Freitas
Isabel Cristina Martins de
IC
Costa Júnior
Moacyr Lobo da
ML
D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D001938:Brazil / Q000453:epidemiology; D002318:Cardiovascular Diseases / Q000401:mortality*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009026:Mortality / Q000639:trends; D017678:Sex Distribution; D013997:Time Factors