Método de estimação de grau de cobertura em pequenas áreas: uma aplicação nas microrregiões mineiras

Abstract

O artigo tem como objetivo principal apresentar uma metodologia simples para estimar o grau de cobertura dos registros de óbitos e obter estimativas de mortalidade para pequenas áreas, usando Minas Gerais como exemplo. A metodologia proposta combina a padronização indireta da estrutura de mortalidade de áreas menores com base nas funções de mortalidade de áreas maiores, e depois a aplicação dos métodos de distribuição de mortes para obter estimativas mais robustas de mortalidade para áreas menores. Os resultados obtidos são robustos e adequados quando comparados com estimativas oficiais e usando outros métodos. As estimativas em dois estágios foram tão robustas que elas reduziram o sobre-registro de óbitos em alguns casos e melhorou as estimativas de mortalidade adulta em algumas áreas onde os dados são menos confiáveis.

Estimating age- and sex-specific mortality rates for small areas with TOPALS regression: an application to Brazil in 2010

“…Previous studies have identified many areas in Brazil with poor vital registration coverage (PAES; ALBUQUERQUE, 1999;QUEIROZ, 2011;JUSTINO;LUCIO, 2012;SAWYER, 2014;FREIRE et al, 2015). Current approaches for estimating mortality rates in such areas (e.g., HORTA et al, 1998;SAWYER, 2014) use a two-step process: (1) IS to smooth small-area rates and estimate expected numbers of deaths by age group, followed by (2) correction for under-registration by applying Death Distribution Methods to the smoothed data.…”

“…For small areas in regions with reliable death registration, researchers have applied IS smoothing to estimate mortality rates directly (CURTIN; KLEIN, 1995;UNDP, 2013;RAM et al, 2015). Death registration is incomplete in many regions of Brazil, however (VASCONCELOS, 1998;PAES;ALBUQUERQUE, 1999;SZWARCWALD et al, 2002;LAURENTI;GOTLIEB, 2007;QUEIROZ, 2011;JUSTINO;LUCIO, 2012;FRIAS et al, 2013;SAWYER, 2014;. In regions with problematic vital records, IS smoothing produces estimates of (uncorrected) mortality schedules, which then serve as inputs to procedures that estimate the degree and age pattern of under-registration (e.g., HORTA et al, 1998;UNDP, 2013;QUEIROZ et al, 2013;SAWYER, 2014;FREIRE et al, 2014;FREIRE et al, 2015).…”

“…Death registration is incomplete in many regions of Brazil, however (VASCONCELOS, 1998;PAES;ALBUQUERQUE, 1999;SZWARCWALD et al, 2002;LAURENTI;GOTLIEB, 2007;QUEIROZ, 2011;JUSTINO;LUCIO, 2012;FRIAS et al, 2013;SAWYER, 2014;. In regions with problematic vital records, IS smoothing produces estimates of (uncorrected) mortality schedules, which then serve as inputs to procedures that estimate the degree and age pattern of under-registration (e.g., HORTA et al, 1998;UNDP, 2013;QUEIROZ et al, 2013;SAWYER, 2014;FREIRE et al, 2014;FREIRE et al, 2015). In both cases, the quality of mortality estimates depends on the fundamental IS assumption -namely, that a specific pattern of relative mortality rates by age is correct.…”

“…IS methods use the mortality pattern in a large region as a standard shape for the patterns in component subregions (HORTA et al, 1998;SAWYER, 2014), which imposes a strong homogeneity assumption. In contrast, TOPALS regression allows estimation and smoothing of age-specific mortality rates for small areas without assuming homogeneity.…”

“…Despite these advances, accurate estimation of age-specific rates for subnational populations in developing countries remains a challenge for demographers and public health researchers (HORTA et al, 1998;JUSTINO;LUCIO, 2012;UNDP, 2013;SAWYER, 2014;FREIRE et al, 2014;. In particular, there is still value in developing robust estimation methods for complete mortality schedules, which could then serve as building blocks for more complex models.…”