O objetivo deste estudo foi analisar as diferenças nas estimativas de três variantes da expectativa de vida saudável dos idosos no Brasil de 1998 para 2008: expectativa de vida livre de incapacidade funcional, com percepção de saúde boa e livre de doenças crônicas. Empregou-se o método de Sullivan, combinando as tábuas de vida do Instituto Brasileiro de Geografia e Estatística (IBGE) para 1998 e 2008 e estimativas intervalares das prevalências de incapacidade funcional, percepção de saúde e doenças crônicas da Pesquisa Nacional por Amostra de Domicílios (PNAD 1998 e 2008). Além do aumento da expectativa de vida, observaram-se aumentos significativos e similares da expectativa de vida saudável nas dimensões de percepção do estado de saúde e incapacidade funcional em quase todas as idades. As mulheres apresentaram maiores expectativas de vida, se comparadas aos homens, porém esperaram viver por mais tempo com saúde ruim, independentemente do indicador utilizado para mensurar saúde. Mesmo que a forma de mensurar saúde possa variar entre os estudos, dificultando comparações, é notável a desvantagem feminina em relação à expectativa de vida saudável.
High sampling variability complicates estimation of demographic rates in small areas. In addition, many countries have imperfect vital registration systems, with coverage quality that varies significantly between regions. We develop a Bayesian regression model for small-area mortality schedules that simultaneously addresses the problems of small local samples and underreporting of deaths. We combine a relational model for mortality schedules with probabilistic prior information on death registration coverage derived from demographic estimation techniques, such as Death Distribution Methods, and from field audits by public health experts. We test the model on small-area data from Brazil. Incorporating external estimates of vital registration coverage though priors improves small-area mortality estimates by accounting for underregistration and automatically producing measures of uncertainty. Bayesian estimates show that when mortality levels in small areas are compared, noise often dominates signal. Differences in local point estimates of life expectancy are often small relative to uncertainty, even for relatively large areas in a populous country like Brazil.
High variability in recorded vital events creates serious problems for small-area mortality estimation by age and sex. Many existing approaches to fitting local mortality schedules, including those most often used in Brazil, estimate rates by making rigid mathematical assumptions about local age patterns. Such methods assume that all areas within a larger area (for example, microregions within a mesoregion) have identically-shaped log mortality schedules by age. We propose a more flexible statistical estimation method that combines Poisson regression with the TOPALS relational model (DE BEER, 2012). We use the new method to estimate age-specific mortality rates in Brazilian small areas (states, mesoregions, microregions, and municipalities) in 2010. Results for Minas Gerais show notable differences in the age patterns of mortality between adjacent small areas, demonstrating the advantages of using a flexible functional form in regression models.
In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2–10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems.
The observed improvements seem to be related to investments in the public health care system and administrative procedures to improve the recording of vital events.
To determine the variations and spatial patterns of adult mortality across regions, over time, and by sex for 137 small areas in Brazil, we first apply TOPALS to estimate and smooth mortality rates and then use death distribution methods to evaluate the quality of the mortality data. Lastly, we employ spatial autocorrelation statistics and cluster analysis to identify the adult mortality trends and variations in these areas between 1980 and 2010. We find not only that regions in Brazil’s South and Southeast already had complete death registration systems prior to the study period, but that the completeness of death count coverage improved over time across the entire nation—most especially in lesser developed regions—probably because of public investment in health data collection. By also comparing adult mortality by sex and by region, we document a mortality sex differential in favor of women that remains high over the entire study period, most probably as a result of increased morbidity from external causes, especially among males. This increase also explains the concentration of high male mortality levels in some areas.
Resumo A expectativa de vida aos 60 anos no Brasil aumentou cerca de 9 anos em pouco mais de meio século. Trata-se de um ganho de sobrevida generalizado, mas que também ocorre de forma heterogênica entre as Grandes Regiões do país. Por outro lado, pouco se sabe, ainda, como os aumentos da expectativa de vida aos 60 anos por região podem ser acompanhados por acréscimos ou decréscimos tanto nos anos vividos com incapacidade, quanto nos vividos livre de incapacidade. O objetivo deste artigo é analisar, para 1998 e 2013, aumentos na Expectativa de Vida Total e suas componentes: Expectativa de Vida Livre de Incapacidade Funcional (EVLI) e com Incapacidade Funcional (EVCI), aos 60, 70 e 80 anos para a população do Brasil e Grandes Regiões. O estudo utilizou informações sobre incapacidade funcional da PNAD de 1998 e PNS de 2013 e empregou o método de Sullivan para estimação da EVLI por sexo e idade. No geral, os resultados mostraram que, entre 1998 e 2013, concomitantemente aos ganhos na EV, ocorreu um crescimento na EVLI. Contudo, os ganhos na EVLI não foram estatisticamente significativos para as regiões Norte e Centro-Oeste. Ou seja, com exceção dessas regiões, além de viver mais, a população idosa de 60 anos poderia esperar viver um número maior de anos com saúde.
We develop a Bayesian regression model for small-area mortality schedules that simultaneously addresses the problems of small local samples and underreporting of deaths. We combine a relational model for mortality schedules with probabilistic prior information on death registration coverage – derived from demographic estimation techniques such as Death Distribution Methods, and from field audits done by public health experts. We test the model on small-area data from Brazil. Incorporating external estimates of vital registration coverage though priors improves small-area mortality estimates by accounting for under-registration, and by automatically producing measures of uncertainty.
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