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1.
文章 在 中文 | WPRIM | ID: wpr-887151

摘要

With the development of social economy and improvement of people's health condition, life expectancy continues to extend and people are more concerned about the quality of life. Nowadays people's attention has shifted from living longer lives to living healthier lives. Life expectancy can only reflect the length of life, but not the health condition and quality of life. Meanwhile, healthy life expectancy contains death and disability information, which comprehensively reflects the length and quality of life and evaluates the health status of the population comprehensively. Through literature search and review, the article summarized the research on healthy life expectancy in recent years, including the concept proposal, index development, calculation, and application progress of health life expectancy. The research methods of healthy life expectancy are summarized in order to provide academic reference for further research.

2.
Cad. saúde colet., (Rio J.) ; 29(spe): 115-129, 2021. tab, graf
文章 在 英语 | LILACS-Express | LILACS | ID: biblio-1364646

摘要

Abstract Background Health expectancy indicators aim at capturing the quality dimension of total life expectancy.; however, the underlying approach, definition of health, and information source differ considerably among the indicators available. Objective (1) Review the main concepts and approaches used to estimate health expectancy focusing on two widely used European health indicators: Health-Adjusted Life Expectancy (HALE) and Healthy Life Years (HLY); (2) identify underlying differences between the results yielded by these two indicators. Method Statistical differences between the HALE and HLY indicators by sex at ages 50, 60, and 70 were tested using pairwise and global Student´s t-tests and z-scores based on standard deviation. Data for 29 European countries were collected from the European Health Expectancy Monitoring Unit (EHEMU) information system and the World Health Organization (WHO) Global Burden of Disease Study 2016 (GBD 2016). Results The HALE indicator estimates were smoother across European countries compared with those of the HLY indicator, present a narrower sex gap in morbidity, higher z-scores compared with the average distribution across Europe, and results less sensitive to cross-national variations. Conclusion The HALE estimates indicate that morbidity is more compressed for both sexes, whereas the HLY estimates suggest that morbidity is more compressed for males but more expanded for females. These contrasting results demonstrate that health expectancy indicators should be interpreted with caution.


Resumo Introdução Os indicadores de expectativa de vida saudável visam capturar uma dimensão de qualidade na expectativa de vida total. No entanto, os pressupostos, a definição de saúde e a fonte de informação diferem consideravelmente entre os indicadores. Objetivo (1) Revisar os principais conceitos e abordagens para estimar as expectativas de saúde com foco em dois indicadores de saúde usados no caso europeu (HALE e HLY); e (2) Identificar diferenças subjacentes nos resultados gerados por esses dois indicadores. Método As diferenças estatísticas entre HALE e HLY por sexo nas idades de 50, 60 e 70 são testadas através dos testes t de Student emparelhados e globais e escores z com base no desvio padrão. Os dados são de 29 países europeus do Sistema Europeu de Informação da Unidade de Monitoramento de Expectativas de Saúde (EHEMU) e do estudo OMS-GBD para o ano de 2016. Resultados As estimativas da HALE possuem menor variabilidade entre os países europeus do que a HLY, apresentam uma diferença de morbidade menor por sexo, apresentam escores-z mais altos em comparação com a distribuição média europeia e têm resultados menos sensíveis às variações entre países. Conclusão As estimativas da HALE indicam que a morbidade é mais comprimida para ambos os sexos, enquanto a HLY sugere que a morbidade para os homens é mais comprimida e para mulheres mais expandida. Esses resultados contrastantes implicam que se deve ter cuidado com os indicadores de expectativa de vida saudável e sua interpretação.

3.
Ciênc. Saúde Colet. (Impr.) ; 24(3): 737-747, mar. 2019. tab, graf
文章 在 葡萄牙语 | LILACS | ID: biblio-989596

摘要

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.


Abstract Life expectancy at age 60 in Brazil has increased by around nine years in a little over 50 years. This general gain in life expectancy at national level has been heterogeneous across the country's major regions. Furthermore, little is known about how increases in life expectancy at age 60 across regions influence the number of years lived with some form of associated disability or the number of years lived free from disability. This study aimed to analyze increases in total life expectancy and its components [disability-free life expectancy (DFLE) and disability life expectancy (DLE)] at ages 60, 70, and 80 in Brazil and Major Regions in 1998 and 2013. The study used data on disability obtained from the 1998 National Household Sample Survey (PNAD - acronym in Portuguese) and 2013 National Health Survey (PNS- acronym in Portuguese) and used the Sullivan method to estimate DFLE by sex and age. The findings show that there was an increase in life expectancy and a concomitant increase in DFLE between 1998 and 2013. However, the gains in DFLE were not statistically significant in the North and Center-west regions. This means that, with the exception of the latter regions, in addition to living longer, the Brazils population aged 60 years can expect to live a greater number of healthy years.


Subject(s)
Humans , Male , Female , Aged , Aged, 80 and over , Health Status , Life Expectancy/trends , Disabled Persons/statistics & numerical data , Time Factors , Brazil , Health Surveys , Age Factors , Middle Aged
4.
Chinese Journal of Epidemiology ; (12): 1249-1254, 2018.
文章 在 中文 | WPRIM | ID: wpr-736664

摘要

Objective To estimate the health-adjusted life expectancy (HALE) of adults in Zhejiang province and evaluate the health status of the adults.Methods This study was based on the mortality data collected from Zhejiang Chronic Disease Surveillance Information and Management System,and mortality rates from the underreporting survey and self-reported health data in 2016.Hierarchical Ordered Probit (HOPIT) model was used to estimate the severity-weighted prevalence of disability.Sullivan's method was used to calculate the HALE.Results After adjustment by HOPIT model,the severity-weighted prevalence of disability increased significantly with age (x2=5 795.81,P<0.001),and it was higher in females than in males (x2=5 353.27,P<0.001).The life expectancy and self-evaluated HALE were 59.08 years and 48.68 years,respectively,in those aged ≥20 years,the difference was 10.40 years due to disability.The proportion of HALE loss due to disability in the total life expectancy was 17.61%,and it increased with age.HALE was higher in males than in females (49.21 years vs.48.14 years),and in urban residents than in rural residents (49.92 years vs.47.43 years).Conclusion The proportion of loss of HALE in the total life expectancy in adults was high in Zhejiang,and it higher in males than in females,in urban residents than rural residents.Programs on improving health care in women and rural residents should be promoted.

5.
Chinese Journal of Epidemiology ; (12): 1249-1254, 2018.
文章 在 中文 | WPRIM | ID: wpr-738132

摘要

Objective: To estimate the health-adjusted life expectancy (HALE) of adults in Zhejiang province and evaluate the health status of the adults. Methods: This study was based on the mortality data collected from Zhejiang Chronic Disease Surveillance Information and Management System, and mortality rates from the underreporting survey and self-reported health data in 2016. Hierarchical Ordered Probit (HOPIT) model was used to estimate the severity-weighted prevalence of disability. Sullivan's method was used to calculate the HALE. Results: After adjustment by HOPIT model, the severity-weighted prevalence of disability increased significantly with age (χ(2)=5 795.81,P<0.001), and it was higher in females than in males (χ(2)=5 353.27, P<0.001). The life expectancy and self-evaluated HALE were 59.08 years and 48.68 years, respectively, in those aged ≥20 years, the difference was 10.40 years due to disability. The proportion of HALE loss due to disability in the total life expectancy was 17.61%, and it increased with age. HALE was higher in males than in females (49.21 years vs. 48.14 years), and in urban residents than in rural residents (49.92 years vs. 47.43 years). Conclusion: The proportion of loss of HALE in the total life expectancy in adults was high in Zhejiang, and it higher in males than in females, in urban residents than rural residents. Programs on improving health care in women and rural residents should be promoted.


Subject(s)
Adult , Female , Humans , Male , Middle Aged , China/epidemiology , Chronic Disease/epidemiology , Disabled Persons/statistics & numerical data , Health Status , Life Expectancy/ethnology , Prevalence , Sex Distribution
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