Factors associated with preventable infant death: a multiple logistic regression

ABSTRACT OBJECTIVE To identify and analyze factors associated with preventable child deaths. METHODS This analytical cross-sectional study had preventable child mortality as dependent variable. From a population of 34,284 live births, we have selected a systematic sample of 4,402 children who did not die compared to 272 children who died from preventable causes during the period studied. The independent variables were analyzed in four hierarchical blocks: sociodemographic factors, the characteristics of the mother, prenatal and delivery care, and health conditions of the patient and neonatal care. We performed a descriptive statistical analysis and estimated multiple hierarchical logistic regression models. RESULTS Approximatelly 35.3% of the deaths could have been prevented with the early diagnosis and treatment of diseases during pregnancy and 26.8% of them could have been prevented with better care conditions for pregnant women. CONCLUSIONS The following characteristics of the mother are determinant for the higher mortality of children before the first year of life: living in neighborhoods with an average family income lower than four minimum wages, being aged ≤ 19 years, having one or more alive children, having a child with low APGAR level at the fifth minute of life, and having a child with low birth weight.

Variáveis de impacto na queda da mortalidade infantil no Estado de São Paulo, Brasil, no período de 1998 a 2008 / Impact variables on the decline in infant mortality in the state of São Paulo, Brazil: 1998-2008

Trata-se de estudo ecológico analítico, retrospectivo, composto pelos 645 municípios do Estado de São Paulo, cujo objetivo foi verificar a relação entre variáveis socioeconômicas, demográficas e modelo de atenção, em relação ao coeficiente de mortalidade infantil, no período de 1998 a 2008. Foi calculada a proporção de variação média anual para cada indicador por estrato de cobertura. A mortalidade infantil foi analisada segundo modelo de medidas repetidas no tempo, ajustado para as variáveis de correção: população do município, proporção de PSF implantado, proporção de PACS implantado, PIB per capita e IPRS (índice paulista de responsabilidade social). A análise foi realizada por modelos lineares generalizados, considerando a distribuição gama. Comparações múltiplas foram realizadas pela razão de verossimilhança com distribuição aproximada qui-quadrado, considerando-se nível de significância de 5%. Houve diminuição da mortalidade infantil no decorrer dos anos (p < 0,05), não havendo diferença significativa de 2004 a 2008 (p > 0,05). A proporção de PSF implantado (p < 0,0001) e o PIB per capita (p < 0,0001) foram significativos no modelo. A queda da mortalidade infantil no período analisado foi influenciada pelo crescimento do PIB per capita e pelo modelo Saúde da Família.

This is an ecological, analytical and retrospective study comprising the 645 municipalities in the State of São Paulo, the scope of which was to determine the relationship between socioeconomic, demographic variables and the model of care in relation to infant mortality rates in the period from 1998 to 2008. The ratio of average annual change for each indicator per stratum coverage was calculated. Infant mortality was analyzed according to the model for repeated measures over time, adjusted for the following correction variables: the city's population, proportion of Family Health Programs (PSFs) deployed, proportion of Growth Acceleration Programs (PACs) deployed, per capita GDP and SPSRI (São Paulo social responsibility index). The analysis was performed by generalized linear models, considering the gamma distribution. Multiple comparisons were performed with the likelihood ratio with chi-square approximate distribution, considering a significance level of 5%. There was a decrease in infant mortality over the years (p < 0.05), with no significant difference from 2004 to 2008 (p > 0.05). The proportion of PSFs deployed (p < 0.0001) and per capita GDP (p < 0.0001) were significant in the model. The decline of infant mortality in this period was influenced by the growth of per capita GDP and PSFs.