Spatial patterns of preventable perinatal mortality in Salvador, Bahia, Brazil

• Autor(a) principal: Nascimento,Rita de Cássia de Sousa
• Data de Publicação: 2017
• Outros Autores: Costa,Maria da Conceição Nascimento, Braga,José Uéleres, Natividade,Márcio Santos da
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Revista de Saúde Pública
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0034-89102017000100269
• topic: Perinatal Death, prevention & control; Perinatal Mortality; Risk Factors; Spatial Analysis

ABSTRACT OBJECTIVE To identify the spatial distribution patterns and areas of higher risk of preventable perinatal mortality in the city of Salvador, State of Bahia, Brazil. METHODS We carried out a spatial aggregated study in 2007, considering the weighting areas (census tracts contiguous sets) of Salvador, of which the center and north present low life conditions. Data were obtained from national vital statistics systems and the 2010 Census. Addresses of live births and stillbirths were geocoded by weighting area. The spatial distribution of the perinatal mortality rate was analyzed from thematic maps. Spatial dependence was evaluated by the Global and Local Geary’s and Moran’s Indexes. RESULTS Crude and smoothed perinatal mortality rates were high in areas situated to the north, west, and in center of Salvador. The smoothed rates in weighting areas ranged from 4.9/1,000 to 22.3/1,000 births. Of all perinatal deaths, 92.1% could have been prevented. We identified spatial dependence for preventable perinatal mortality for care in pregnancy, with neighboring areas with high risk in the north of the city. CONCLUSIONS The preventability potential of perinatal mortality was high in Salvador, in 2007. The spatial distribution pattern with higher rates in disadvantaged areas of the city suggests the existence of social inequalities in health. The characteristics of the process of urban development of Salvador, which has inadequate prenatal care, possibly influenced the magnitude and spatial distribution pattern of this mortality.