Abstract
BackgroundIn Brazil, both the Civil Registry (CR) and Ministry of Health (MoH) Mortality Information System (SIM) are sources of routine mortality data, but neither is 100% complete. Deaths from these two sources can be linked to facilitate estimation of completeness of mortality reporting and measurement of adjusted mortality indicators using generalized linear modeling (GLM).MethodsThe 2015 and 2016 CR and SIM data were linked using deterministic methods. GLM with covariates of the deceased’s sex, age, state of residence, cause of death and place of death, and municipality-level education decile and population density decile, was used to estimate total deaths and completeness nationally, subnationally and by population sub-group, and to identify the characteristics of unreported deaths. The empirical completeness method and Global Burden of Disease (GBD) 2017 estimates were comparators at the national and state level.ResultsCompleteness was 98% for SIM and 95% for CR. The vast majority of deaths in Brazil were captured by either system and 94% were reported by both sources. For each source, completeness was lowest in the north. SIM completeness was consistently high across all sub-groups while CR completeness was lowest for deaths at younger ages, outside facilities, and in the lowest deciles of municipality education and population density. There was no clear municipality-level relationship in SIM and CR completeness, suggesting minimal dependence between sources. The empirical completeness method model 1 and GBD completeness estimates were each, on average, less than three percentage points different from GLM estimates at the state level. Life expectancy was lowest in the northeast and 7.5 years higher in females than males.ConclusionsGLM using socio-economic and demographic covariates is a valuable tool to accurately estimate completeness from linked data sources. Close scrutiny of the quality of variables used to link deaths, targeted identification of unreported deaths in poorer, northern states, and closer coordination of the two systems will help Brazil achieve 100% death reporting completeness. The results also confirm the validity of the empirical completeness method.
Highlights
Routine, accurate, and timely data on deaths are an essential source of evidence for national and subnational governments to monitor population health and develop programs to reduce disease and injury burden [1]
Two parallel death reporting systems exist: (1) the Civil Registry (CR), created by Law in 1874 under the control of the National Justice Council at the national level and justice courts at state level, for which the Brazilian Institute of Geography and Statistics (IBGE) has had responsibility for collating statistics since 1973, and (2) the Mortality Information System (SIM), created in 1975 and which is the responsibility of Ministry of Health (MoH)
An increase in completeness from 2015 to 2016 was observed for each system, which demonstrates the Notably, the generalized linear modeling (GLM) estimates only 1929 deaths in Brazil in 2016 were not reported by either system or only 0.1% of estimated total deaths according to this method
Summary
Accurate, and timely data on deaths are an essential source of evidence for national and subnational governments to monitor population health and develop programs to reduce disease and injury burden [1]. In Brazil, the fifth most populous country in the world, such information is especially important given its significant socio-economic and population health inequalities [2,3,4] Such evidence is best served by a complete civil registration and vital statistics (CRVS) system [1]. The two systems have different objectives: to provide inputs for the calculation of vital and epidemiological statistics (in the case of SIM), and, as required by the Public Records Act, the production of official information for the legal rights of each dying individual (in the case of the CR) Both sources commonly capture the majority of deaths in Brazil, but some events are recorded exclusively by only one of these sources [5]. Deaths from these two sources can be linked to facilitate estimation of completeness of mortality reporting and measurement of adjusted mortality indicators using generalized linear modeling (GLM)
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