ArticlePopulation health metrics2018
Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs.
Article in Population health metrics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Deriving and comparing healthy longevity distributions by gender and health prevalence measures: a statistical moments and maximum entropy approach.Population health metrics · 2026Article
- Global, Regional, and National Epidemiology of Postpartum Hemorrhage (1990-2021): A Statistical Analysis of Incidence, Mortality, and DALYs.Health science reports · 2026Article
- Longer healthy life, but for how many? A stochastic analysis of healthy lifespan inequality.Annals of operations research · 2026Article
- Well-Being Adjusted Health Expectancy: A New Summary Measure of Population Health.European journal of population = Revue europeenne de demographie · 2022Article
- Estimating the number and length of episodes in disability using a Markov chain approach.Population health metrics · 2020Article
- Estimating lifetime malnourished period and its statistics based on the concept of Markov chain with reward.Heliyon · 2020Article
- Variance as a life history outcome: Sensitivity analysis of the contributions of stochasticity and heterogeneity.Ecological modelling · 2020Article
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Abstract
backgroundIncreases in human longevity have made it critical to distinguish healthy longevity from longevity without regard to health. Current methods focus on expectations of healthy longevity, and are often limited to binary health outcomes (e.g., disabled vs. not disabled). We present a new matrix formulation for the statistics of healthy longevity, based on health prevalence data and Markov chain theory, applicable to any kind of health outcome and which provides variances and higher moments as well as expectations of healthy life.
methodThe model is based on a Markov chain description of the life course coupled with the moments of health outcomes ("rewards") at each age or stage. As an example, we apply the method to nine European countries using the SHARE survey data on the binary outcome of disability as measured by activities of daily living, and the continuous health outcome of hand grip strength.
resultsWe provide analytical formulas for the mean, variance, coefficient of variation, skewness and other statistical properties of healthy longevity. The analysis is applicable to binary, categorical, ordinal, or interval scale health outcomes. The results are easily evaluated in any matrix-oriented software. The SHARE results reveal familiar patterns for the expectation of life and of healthy life: women live longer than men but spend less time in a healthy condition. New results on the variance shows that the standard deviation of remaining healthy life declines with age, but the coefficient of variation is nearly constant. Remaining grip strength years decrease with age more dramatically than healthy years but their variability pattern is similar to the pattern of healthy years. Patterns are similar across nine European countries.
conclusionsThe method extends, in several directions, current calculations of health expectancy (HE) and disability-adjusted life years (DALYs). It applies to both categorical and continuous health outcomes, to combinations of multiple outcomes (e.g., death and disability in the formulation of DALYs) and to age- or stage-classified models. It reveals previously unreported patterns of variation among individuals in the outcomes of healthy longevity.
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