OBJECTIVE: To assess ecological models to describe infant mortality rate in Ceara (Northeastern Brazil) in two different periods of time. METHODS: This was a cross-sectional ecologic study of two years, 1991 and 2000, using non-matching information per municipalities. Estimates on the infant mortality rate of the Instituto de Pesquisas Econômicas Aplicadas (Institute of Applied Economic Research) have been used. For the remaining indicators different sources of the System of Health Information were used. The main risk factors were assessed using multiple linear regression. RESULTS: In 1991, the variables that predicted infant mortality rate (R2=0.3575) were: small houses (beta=0.0043; rho=0.010), proportion of inhabitants with tap water in the household (beta=-0.0029; rho=0.024), urbanization rate (beta=0.0032; rho=0.004), fecundity rate (beta=0.0351; rho=0.024), the proportion of children working at 10-14 years (beta=0.0049; rho=0.017), proportion of families with income < ½ minimum wage (beta=0.0056; rho=0.000), that can read and write (beta=-0.0062; rho=0.031). In the year 2000, the following possible determinants were identified (R2=0.3236): the proportion of children <2 years of age with malnutrition (beta=0.0064; rho=0.024), proportion of households with adequate sanitation (beta=-0.0024; rho=0.010), proportion of women who could read and write (beta=-0.0068; rho=0.044), expenses on health human resources regarding total health expenses (beta=-0.0024; rho=0.027), proportion of the value of the vegetal production in relation to the total of the state (beta=-0.1090; rho=0.001), intensity of poverty (beta=0.0065; rho=0.002), and ageing index (beta=-0.0100; rho=0.006). CONCLUSIONS: Although the variables have not been exactly the same for the evaluated period, determiners of infant mortality have been changing, except for indicators of education, income and sanitation. The overall decrease in fecundity led to a reduction in its discriminating power, and it was replaced by the ageing index. Another tendency observed was the replace of several demographic variables by health care indicators.
Infant mortality; Socioeconomic factors; Risk factors; Linear models
