학술논문
Spatial patterns of mortality in low birth weight infants at term and its determinants in the State of São Paulo, Brazil.
Document Type
Academic Journal
Author
Rodríguez EYA; Universidade Estadual de São Paulo, Postgraduate Program in Engineering - Guaratinguetá (SP), Brazil.; Rodríguez ECA; Universidade Estadual de São Paulo, Postgraduate Program in Engineering - Guaratinguetá (SP), Brazil.; Marins FAS; Universidade Estadual de São Paulo, Postgraduate Program in Engineering - Guaratinguetá (SP), Brazil.; Silva AFD; Universidade Estadual de São Paulo, Postgraduate Program in Engineering - Guaratinguetá (SP), Brazil.; Nascimento LFC; Universidade Estadual de São Paulo, Postgraduate Program in Engineering - Guaratinguetá (SP), Brazil.; Universidade de Taubaté, Postgraduate Program in Environmental Sciences - Taubaté (SP), Brazil.
Source
Publisher: Associação Brasileira de Pós-Graduação em Saúde Coletiva Country of Publication: Brazil NLM ID: 100954576 Publication Model: eCollection Cited Medium: Internet ISSN: 1980-5497 (Electronic) Linking ISSN: 1415790X NLM ISO Abbreviation: Rev Bras Epidemiol Subsets: MEDLINE
Subject
Language
English
Abstract
Objective: Low birth weight (LBW) is a public health problem strongly associated with infant mortality. This study aimed to identify the spatial distribution of infant mortality in newborns with LBW (750-2,500 g) at term (≥37 weeks of gestation), due to their being small for gestational age, analyzing its association with mother-related determinants, as well as to identify priority areas of mortality in the State of São Paulo, 2010-2019.
Methods: Infant mortality rate was analyzed in the division of neonatal mortality and postneonatal mortality of newborns with LBW at term. The empirical Bayesian method smoothed the rates, the univariate Moran index was used to measure the degree of spatial association between the municipalities, and the bivariate Moran index was employed to identify the existence of a spatial association between the rates and the selected determinants. Thematic maps of excess risk and local Moran were prepared to identify spatial clusters, adopting 5% as a significance level.
Results: The excess risk map showed that more than 30% of the municipalities had rates above the state rate. High-risk clusters were identified in the southwest, southeast, and east regions, mainly among more developed municipalities. The determinants of adolescent mothers, mothers over 34 years of age, low education, human development index, social vulnerability index, gross domestic product, physicians, and pediatric beds showed a significant association with the rates evaluated.
Conclusions: Priority areas and significant determinants associated with reduced mortality in newborns with LBW were identified, suggesting the need for intervention measures to achieve the Sustainable Development Goal.
Methods: Infant mortality rate was analyzed in the division of neonatal mortality and postneonatal mortality of newborns with LBW at term. The empirical Bayesian method smoothed the rates, the univariate Moran index was used to measure the degree of spatial association between the municipalities, and the bivariate Moran index was employed to identify the existence of a spatial association between the rates and the selected determinants. Thematic maps of excess risk and local Moran were prepared to identify spatial clusters, adopting 5% as a significance level.
Results: The excess risk map showed that more than 30% of the municipalities had rates above the state rate. High-risk clusters were identified in the southwest, southeast, and east regions, mainly among more developed municipalities. The determinants of adolescent mothers, mothers over 34 years of age, low education, human development index, social vulnerability index, gross domestic product, physicians, and pediatric beds showed a significant association with the rates evaluated.
Conclusions: Priority areas and significant determinants associated with reduced mortality in newborns with LBW were identified, suggesting the need for intervention measures to achieve the Sustainable Development Goal.