Your browser doesn't support javascript.

Portal de Búsqueda de la BVS Colombia

Información y Conocimiento para la Salud

Home > Búsqueda > ()
XML
Imprimir Exportar

Formato de exportación:

Exportar

Email
Adicionar mas contactos
| |

Maternal mortality and social vulnerability in a Northeast State in Brazil: a spatial-temporal approach / Mortalidade materna e vulnerabilidade social no Estado de Alagoas no Nordeste brasileiro: uma abordagem espaço-temporal

Duarte, Elena Maria da Silva; Alencar, Érika Tenório dos Santos; Fonseca, Laura Gabriele Alves da; Silva, Sylvia Marques da; Machado, Michael Ferreira; Araújo, Maria Deysiane Porto de; Correia, Divanise Suruagy; Souza, Carlos Dornels Freire de.
Rev. Bras. Saúde Mater. Infant. (Online) ; 20(2): 575-586, Apr.-June 2020. tab, graf
Artículo en Inglés | SES-SP, LILACS | ID: biblio-1136433
Abstract

Objectives:

to analyze the epidemiological profile and the spatial-temporal dynamics on maternal mortality in Alagoas and its relationship with social vulnerability and income inequality.

Methods:

a mixed ecological study involving maternal deaths who resided in Alagoas from 1996 to 2016. Sociodemographic variables (age, race/color, education, marital status), clinical (type of obstetric cause, death by category and ICD group) were analyzed, besides the indicators (Maternal Mortality Ratio-MMR, Social Vulnerability Index and Gini Index). For the temporal analysis, we used the inflection point regression model and for the spatial analysis, the local empirical Bayesian model, Moran Global and Local statistics, and the bivariate local spatial autocorrelation analysis.

Results:

a total of 586 deaths (47.63/100 thousand live births) were registered, with a trend of MMR growth (APC 2.8%), with a heterogeneous distribution between health regions and cities. The profile was characterized by the predominance of young, black / mixed skin color women with low schooling. Eight cities were considered priority. There was spatial correlation with the Social Vulnerability Index and income inequality.

Conclusions:

identifying priority areas may contribute to planning and targeting interventions.
Biblioteca responsable: BR663.1