Abstract

We propose a series of methods and models in order to explore the Global Burden of Disease Study and the provided healthy life expectancy (HALE) estimates from the World Health Organization (WHO) based on the mortality μ x of a population provided in a classical life table and a mortality diagram. Our estimates are compared with the HALE estimates for the World territories and the WHO regions along with providing comparative results with to findings of Chang et al (J Public Health 37(3):470–9, 2015. doi:10.1093/pubmed/fdu059. Epub 2014) on the Differences in healthy life expectancy for the US population by sex, race/ethnicity and geographic region: 2008 for USA and from Yong and Saito (Demogr Res 20:467–494, 2009) regarding Trends in healthy life expectancy in Japan. From the mortality point of view we have developed a simple model for the estimation of a characteristic parameter b related to the healthy life years lost to disability and providing full application details along with characteristic parameter selection and stability of the coefficients. We also provide a direct estimation method of the parameter b from the life tables. We straighten the importance of our methodology by proposing and applying estimates of the parameter b by using the Gompertz and the Weibull models. From the Health State point of view we summarize the main points of the first exit time theory to life table data and present the basic models starting from the first related model published by Janssen and Skiadas (Appl Stoch Models Data Anal 11(1):35–49, 1995). Even more we develop the simpler 2-parameter health state model and an extension of a model expressing the infant mortality to a 4-parameter model which is the simpler model providing very good fitting on the logarithm of the force of mortality, ln(μ x ). More important is the use of the Health State Function and the relative impact on mortality to find an estimate for the healthy life years lost to disability. We have developed simple programs in Excel providing immediately the Life Expectancy, the Loss of Healthy Life Years and the Healthy Life Expectancy estimate.

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