Tendência da incompletude das estatísticas vitais no período neonatal, estado do Rio de Janeiro, 1999-2014*

Abstract

Objective: to analyze the incompleteness of variables retrieved from the Live Birth Information System (SINASC) and the Mortality Information System (SIM), in the State of Rio de Janeiro, in the time series 1999 to 2014. Methods: this was a time series study of SINASC and SIM; the Romero & Cunha score was used to analyze incompleteness; Joinpoint regression was used to analyze temporal trend; in 2014, deaths were evaluated separately according to investigation. Results: regarding SINASC variables, in 1999 marital status (37.40%), number of stillborn children (31.30%), and race/skin color (24.63%) had the highest incompleteness percentages; in 2014, no variable exceeded 5% incompleteness, except occupation; regarding SIM variables, in 1999 five variables exceeded 20%, and missing data for previous stillborn children was over 60%; in 2014, only one variable exceeded 20% incompleteness; investigated deaths had better completeness. Conclusion: both systems were found to have improved; the quality of SINASC completeness remained superior to that of SIM.

Necropolítica e reflexões acerca da população negra no contexto da pandemia da COVID-19 no Brasil: uma revisão bibliográfica

“…These data are important to develop indicators 35 . Nevertheless, some researchers 30,31,36 have pointed out that in several health information systems in Brazil, this field has not been filled in.…”

“…According to the Brazilian Decree 344/2017, filling in the race/color field is mandatory. However, recent studies have shown that most of the health information system forms lack information about race/color 12,30,31 . During the COVID-19 pandemic, epidemiologic vigilance has become one of the foundations of public health policies.…”

Incompleteness and inaccuracies in Certificates of Live Birth in a city in Southern Brazil

“…In the incompleteness analysis, the variable schooling presented rates from 2012 to 2015, but remained classified as excellent and showed no inaccuracies. A large study conducted in Rio de Janeiro 11 presented a high proportion of incompleteness in the system, mainly in the variables ethnicity, maternal schooling, living and dead children, maternal age, and pregnancy duration. Compared to this study, all these variables showed some level of incompleteness, except for maternal age, which showed no incompleteness or inaccuracies in the period.…”

“…In another analysis, ethnicity was classified as poor in most cities, particularly in São Luís, where incompleteness reached 36.8% 12 . Research developed in Rio de Janeiro considered this variable poor in 1999, with gradual incompleteness improvement, achieving an excellent rating in 2014 11 . Taking into account the potential role that ethnicity might have in determining maternal health outcomes, a study revealed that obtaining this information is a challenge, as this variable is difficult to collect and interpret given the extensive miscegenation in a population, such as that of Brazil 17 .…”

Iniquidade social e câncer de mama feminino: análise da mortalidade

“…Por exemplo, pode ter havido sub-registro de óbitos no período estudado, especialmente nas microrregiões mais pobres do estado. No entanto, estudos recentes têm mostrado melhora na qualidade das informações do SIM 33,34 . Uma outra limitação está relacionada ao desenho do estudo, pois, como os dados analisados são agregados por populações, todas as inferências feitas são para o nível ecológico, não havendo inferência direta para o nível individual, sob pena de incorrer na falácia ecológica.…”