Avaliação da incompletude da variável escolaridade materna nos registros das Declarações de Nascidos Vivos nas capitais brasileiras - 1996 a 2013

• Autor(a) principal: Sonia Silvestrin
• Data de Publicação: 2018
• Outros Autores: Viviane Costa de Souza Buriol, Clécio Homrich da Silva, Marcelo Zubaran Goldani
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Cadernos de Saúde Pública
• Texto Completo: https://cadernos.ensp.fiocruz.br/ojs/index.php/csp/article/view/6825
• topic: Declaração de Nascimento; Escolaridade; Sistemas de Informação

The article assessed the quality of completion of the maternal school variable in Brazilian state capitals and its regional distribution, based on the Brazilian Information System on Live Births (SINASC) with processed data from live birth certificates. A descriptive study was conducted in the time series from 1996 to 2013, with a total de 12,062,064 births, of which 11,442,494 (94.86%) had valid information on the maternal schooling variable. The results were calculated as the number of incomplete results in the variable per 1,000 live births, and the trend was assessed with the Joinpoint software, version 4.3.1. According to regional analysis, the South of Brazil showed a downward trend in incompleteness of maternal schooling throughout the study in all the state capitals of that region. Most of the country’s other state capitals also showed improvement in the variable’s completeness. However, there were different trends in some state capitals, even with greater incompleteness at the end of the period when compared to the beginning. SINASC proved to be a valuable source of data on mothers and their newborns, besides information on conditions in labor, delivery, and birth in the country. Maternal schooling, considered an important factor for obstetric and neonatal outcomes, is particularly useful for elaborating and evaluating policies and measures in maternal and child health. Thus, to achieve maximum completeness in data on this variable requires joint effort by health professionals and administrators, thereby guaranteeing the data’s trustworthiness.