Magdalena M Muszyńska-Spielauer, T. Riffe, M. Spielauer
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Our empirical demonstration is based on the prevalence of chronic diseases in selected European countries in 2017 from the Survey of Health, Ageing and Retirement in Europe (SHARE), as well as on life tables from EUROSTAT.\nWe find that the Sullivan method, when considered as an extension of the stationary population model to health, allows for the estimation of a healthy survival distribution and its statistics, beyond HE, for health characteristics with no recovery from the state of decreased health. We show that for such health conditions, the method requires that the number of persons in full health in a stationary population does not increase with age. We argue that for such health dimensions, HE conditional on being in good health at the life table radix age is of relevance for health policy interventions.\nIn our empirical application, we show that the conditional and unconditional measures of HE can give substantially different pictures of population health. Furthermore, we show that across European countries, in contrast to the negative relationship between LE and lifespan inequality, higher HE is associated with greater inequality in healthy years lived when conditional on being healthy at age 50.\nOverall, the Sullivan method, when considered as an extension of the stationary population model, proves to be a valuable tool for deriving summary statistics of population health beyond HE, which are highly relevant to public policy.\n* This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.","PeriodicalId":44592,"journal":{"name":"Comparative Population Studies","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Healthy Lifespan Statistics Derived From Cross-Sectional Prevalence Data Using the Sullivan Method are Informative Summary Measures of Population Health\",\"authors\":\"Magdalena M Muszyńska-Spielauer, T. 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引用次数: 0
摘要
健康预期寿命(Health expectancy,HE)通常是利用沙利文法从横断面流行率数据中推算出来的,是最常用的人口健康概括衡量指标。在人口学研究中,寿命分布统计通常与预期寿命(LE)一起讨论,健康寿命的类似统计也能提供有关人口健康的宝贵信息。我们研究了是否可以根据沙利文方法的数据输入--横截面流行率数据和生命表来估算 HE 以外的健康寿命分布统计数据。为此,我们将沙利文方法视为静态人口模型在健康方面的延伸,并区分了健康状况有无从健康下降状态恢复的情况。我们的实证论证基于欧洲健康、老龄和退休调查(SHARE)中 2017 年部分欧洲国家的慢性病患病率,以及欧盟统计局(EUROSTAT)的生命表。我们发现,当把沙利文方法视为静态人口模型在健康领域的扩展时,对于健康状况没有从下降状态恢复的健康特征,沙利文方法可以估算出健康的生存分布及其统计数据,而不是 HE。我们表明,对于此类健康状况,该方法要求静态人口中完全健康的人数不随年龄增长而增加。在实证应用中,我们发现,有条件和无条件的健康状况衡量方法对人口健康状况的描述大相径庭。此外,我们还表明,在欧洲各国,LE 与寿命不平等之间存在负相关关系,与此相反,当以 50 岁时健康为条件时,较高的 HE 与较高的健康寿命不平等相关联:本文属于 "预期健康水平和趋势:了解其测量和估计的敏感性 "特刊。
Healthy Lifespan Statistics Derived From Cross-Sectional Prevalence Data Using the Sullivan Method are Informative Summary Measures of Population Health
Health expectancy (HE), commonly derived from cross-sectional prevalence data using the Sullivan method, serves as the most frequently used summary measure of population health. Like lifespan distribution statistics, which are often discussed alongside life expectancy (LE) in demographic studies, analogous statistics on healthy lifespans can provide valuable information on population health. We examine whether healthy lifespan distribution statistics beyond HE can be estimated based on cross-sectional prevalence data and the life table, the data inputs of the Sullivan method. To do so, we treat the Sullivan method as an extension of the stationary population model to health and distinguish between health conditions with and without recovery from the state of decreased health. Our empirical demonstration is based on the prevalence of chronic diseases in selected European countries in 2017 from the Survey of Health, Ageing and Retirement in Europe (SHARE), as well as on life tables from EUROSTAT.
We find that the Sullivan method, when considered as an extension of the stationary population model to health, allows for the estimation of a healthy survival distribution and its statistics, beyond HE, for health characteristics with no recovery from the state of decreased health. We show that for such health conditions, the method requires that the number of persons in full health in a stationary population does not increase with age. We argue that for such health dimensions, HE conditional on being in good health at the life table radix age is of relevance for health policy interventions.
In our empirical application, we show that the conditional and unconditional measures of HE can give substantially different pictures of population health. Furthermore, we show that across European countries, in contrast to the negative relationship between LE and lifespan inequality, higher HE is associated with greater inequality in healthy years lived when conditional on being healthy at age 50.
Overall, the Sullivan method, when considered as an extension of the stationary population model, proves to be a valuable tool for deriving summary statistics of population health beyond HE, which are highly relevant to public policy.
* This article belongs to a special issue on “Levels and Trends of Health Expectancy: Understanding its Measurement and Estimation Sensitivity”.