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Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs

BACKGROUND: Increases 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 mat...

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Autores principales: Caswell, Hal, Zarulli, Virginia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992869/
https://www.ncbi.nlm.nih.gov/pubmed/29879982
http://dx.doi.org/10.1186/s12963-018-0165-5
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author Caswell, Hal
Zarulli, Virginia
author_facet Caswell, Hal
Zarulli, Virginia
author_sort Caswell, Hal
collection PubMed
description BACKGROUND: Increases 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. METHOD: The 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. RESULTS: We 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. CONCLUSIONS: The 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12963-018-0165-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-59928692018-07-05 Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs Caswell, Hal Zarulli, Virginia Popul Health Metr Research BACKGROUND: Increases 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. METHOD: The 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. RESULTS: We 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. CONCLUSIONS: The 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12963-018-0165-5) contains supplementary material, which is available to authorized users. BioMed Central 2018-06-07 /pmc/articles/PMC5992869/ /pubmed/29879982 http://dx.doi.org/10.1186/s12963-018-0165-5 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Caswell, Hal
Zarulli, Virginia
Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title_full Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title_fullStr Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title_full_unstemmed Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title_short Matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and DALYs
title_sort matrix methods in health demography: a new approach to the stochastic analysis of healthy longevity and dalys
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5992869/
https://www.ncbi.nlm.nih.gov/pubmed/29879982
http://dx.doi.org/10.1186/s12963-018-0165-5
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