M Z Goldani1, M A Barbieri, H Bettiol, M R Barbieri, A Tomkins. 1. Departamento de Pediatria e Puericultura, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brasil. hegold@uol.com.br
Abstract
OBJECTIVE: Data from municipal databases can be used to plan interventions aimed at reducing inequities in health care. The objective of the study was to determine the distribution of infant mortality according to an urban geoeconomic classification using routinely collected municipal data. METHODS: All live births (total of 42,381) and infant deaths (total of 731) that occurred between 1994 and 1998 in Ribeirão Preto, Brazil, were considered. Four different geoeconomic areas were defined according to the family head's income in each administrative urban zone. RESULTS: The trends for infant mortality rate and its different components, neonatal mortality rate and post-neonatal mortality rate, decreased in Ribeirão Preto from 1994 to 1998 (chi-square for trend, p<0.05). These rates were inversely correlated with the distribution of lower salaries in the geoeconomic areas (less than 5 minimum wages per family head), in particular the post-neonatal mortality rate (chi-square for trend, p<0.05). Finally, the poor area showed a steady increase in excess infant mortality. CONCLUSIONS: The results indicate that infant mortality rates are associated with social inequality and can be monitored using municipal databases. The findings also suggest an increase in the impact of social inequality on infant health in Ribeirão Preto, especially in the poor area. The monitoring of health inequalities using municipal databases may be an increasingly more useful tool given the continuous decentralization of health management at the municipal level in Brazil.
OBJECTIVE: Data from municipal databases can be used to plan interventions aimed at reducing inequities in health care. The objective of the study was to determine the distribution of infant mortality according to an urban geoeconomic classification using routinely collected municipal data. METHODS: All live births (total of 42,381) and infant deaths (total of 731) that occurred between 1994 and 1998 in Ribeirão Preto, Brazil, were considered. Four different geoeconomic areas were defined according to the family head's income in each administrative urban zone. RESULTS: The trends for infant mortality rate and its different components, neonatal mortality rate and post-neonatal mortality rate, decreased in Ribeirão Preto from 1994 to 1998 (chi-square for trend, p<0.05). These rates were inversely correlated with the distribution of lower salaries in the geoeconomic areas (less than 5 minimum wages per family head), in particular the post-neonatal mortality rate (chi-square for trend, p<0.05). Finally, the poor area showed a steady increase in excess infant mortality. CONCLUSIONS: The results indicate that infant mortality rates are associated with social inequality and can be monitored using municipal databases. The findings also suggest an increase in the impact of social inequality on infant health in Ribeirão Preto, especially in the poor area. The monitoring of health inequalities using municipal databases may be an increasingly more useful tool given the continuous decentralization of health management at the municipal level in Brazil.