Análise espacial das condições do nascimento nas macrorregiões de saúde no Estado de Santa Catarina

Abstract

To verify spatial differences pattern of birth conditions in health macroregions to the Santa Catarina's state. Methods: This is an ecological and exploratory study that applied geoprocessing techniques on data collected from SINASC and IBGE from 2013 to 2017. The data that were treated are HDI, Childbirth Type, Maternal Education, Gestational age, Apgar Index at the fifth minute, Number Prenatal Consultations and Birth Weight. The Q-Gis and GeoDa programs were used to produce maps and estimate spatial autocorrelation of the data cited. Excel was used too. The correlation between the variables was estimated by calculating the Pearson correlation coefficient. For spatial autocorrelation, the Moran index statistic was used. Results: Autocorrelation was found for most variables, especially cesarean child-birth, apgar score, number of prenatal consultations. For Pearson there is a positive correlation between: HDI and Schooling (r = 0.55); between underweight and prematurity (r = 0.45); and between HDI and Apgar (<7) (r = 0.33). Negative correlation was also found between: Age below 20 years and Apgar (<7) (r = -0.30); HDI and Apgar (≤7) (r = -0.39); between prenatal care (more than 6 appointments) and age under 20 years (r = -0.44); and between HDI and Age below 20 years (r = -0.63). Conclusions: There are differences between birth conditions between the different health macroregions of the state of Santa Catarina, and Serra Catarinense's Health Region has the worst socioeconomic and health data.