Reis Gilson Jácome Dos, Barcellos Christovam, Pedroso Marcel de Moraes, Xavier Diego Ricardo
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil.
Instituto de Comunicação e Informação Científica e Tecnológica em Saúde, Fundação Oswaldo Cruz, Rio de Janeiro, Brasil.
Cad Saude Publica. 2018 Sep 6;34(9):e00105517. doi: 10.1590/0102-311X00105517.
The study aimed to characterize notified cases of congenital syphilis from 2011 to 2014 in the city of Rio de Janeiro and to analyze possible associations between congenital syphilis and living conditions in the city's neighborhoods. Cases of congenital syphilis were characterized according to biological and socioeconomic variables and health services use. At the aggregate level, regression tree technique was used for the data analysis, with mean incidence rate (2011-2014) of congenital syphilis as the dependent variable and housing quality, schooling, income, teenage pregnancy, poverty density, access to prenatal care, and skin color as independent variables. The dependent variable was mapped to identify spatial patterns. The SINAN, SINASC, and IBGE databases were used for notifiable diseases, live births, and census data, respectively. A total of 6,274 cases of congenital syphilis were reported, which represents an incidence rate of 17.3 cases/1,000 live births. Cases were distributed in the central, northern peripheral, and western zones of the city, with a high proportion of cases in infants of black mothers with low schooling. There was also a high proportion of pregnant women with late diagnosis of syphilis and inadequate treatment. At the aggregate level, the most relevant variable for explaining the problem was the low proportion of pregnant women with at least 7 prenatal visits. The analysis allowed the identification of marginalized population segments and can help direct public health resources more effectively.
该研究旨在描述2011年至2014年里约热内卢市先天性梅毒报告病例的特征,并分析先天性梅毒与该市各社区生活条件之间可能存在的关联。根据生物学和社会经济变量以及卫生服务利用情况对先天性梅毒病例进行了特征描述。在总体层面,采用回归树技术进行数据分析,以先天性梅毒的平均发病率(2011 - 2014年)作为因变量,住房质量、受教育程度、收入、青少年怀孕、贫困密度、获得产前护理的情况以及肤色作为自变量。对因变量进行映射以识别空间模式。分别使用SINAN、SINASC和IBGE数据库获取法定传染病、活产和人口普查数据。共报告了6274例先天性梅毒病例,发病率为17.3例/1000活产。病例分布在该市的中心、北部边缘和西部区域,母亲为黑人且受教育程度低的婴儿中病例比例较高。梅毒诊断延迟和治疗不充分的孕妇比例也很高。在总体层面,解释该问题最相关的变量是至少进行7次产前检查的孕妇比例较低。该分析有助于识别边缘化人群,并有助于更有效地分配公共卫生资源。