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Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data

Accurate future projections of population health are imperative to plan for the future healthcare needs of a rapidly aging population. Multistate‐transition microsimulation models, such as the U.S. Future Elderly Model, address this need but require high‐quality panel data for calibration. We develo...

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Autores principales: Kasajima, Megumi, Hashimoto, Hideki, Suen, Sze‐Chuan, Chen, Brian, Jalal, Hawre, Eggleston, Karen, Bhattacharya, Jay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032851/
https://www.ncbi.nlm.nih.gov/pubmed/32662080
http://dx.doi.org/10.1002/hec.3986
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author Kasajima, Megumi
Hashimoto, Hideki
Suen, Sze‐Chuan
Chen, Brian
Jalal, Hawre
Eggleston, Karen
Bhattacharya, Jay
author_facet Kasajima, Megumi
Hashimoto, Hideki
Suen, Sze‐Chuan
Chen, Brian
Jalal, Hawre
Eggleston, Karen
Bhattacharya, Jay
author_sort Kasajima, Megumi
collection PubMed
description Accurate future projections of population health are imperative to plan for the future healthcare needs of a rapidly aging population. Multistate‐transition microsimulation models, such as the U.S. Future Elderly Model, address this need but require high‐quality panel data for calibration. We develop an alternative method that relaxes this data requirement, using repeated cross‐sectional representative surveys to estimate multistate‐transition contingency tables applied to Japan's population. We calculate the birth cohort sex‐specific prevalence of comorbidities using five waves of the governmental health surveys. Combining estimated comorbidity prevalence with death record information, we determine the transition probabilities of health statuses. We then construct a virtual Japanese population aged 60 and older as of 2013 and perform a microsimulation to project disease distributions to 2046. Our estimates replicate governmental projections of population pyramids and match the actual prevalence trends of comorbidities and the disease incidence rates reported in epidemiological studies in the past decade. Our future projections of cardiovascular diseases indicate lower prevalence than expected from static models, reflecting recent declining trends in disease incidence and fatality.
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spelling pubmed-80328512022-10-14 Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data Kasajima, Megumi Hashimoto, Hideki Suen, Sze‐Chuan Chen, Brian Jalal, Hawre Eggleston, Karen Bhattacharya, Jay Health Econ Special Issue Papers Accurate future projections of population health are imperative to plan for the future healthcare needs of a rapidly aging population. Multistate‐transition microsimulation models, such as the U.S. Future Elderly Model, address this need but require high‐quality panel data for calibration. We develop an alternative method that relaxes this data requirement, using repeated cross‐sectional representative surveys to estimate multistate‐transition contingency tables applied to Japan's population. We calculate the birth cohort sex‐specific prevalence of comorbidities using five waves of the governmental health surveys. Combining estimated comorbidity prevalence with death record information, we determine the transition probabilities of health statuses. We then construct a virtual Japanese population aged 60 and older as of 2013 and perform a microsimulation to project disease distributions to 2046. Our estimates replicate governmental projections of population pyramids and match the actual prevalence trends of comorbidities and the disease incidence rates reported in epidemiological studies in the past decade. Our future projections of cardiovascular diseases indicate lower prevalence than expected from static models, reflecting recent declining trends in disease incidence and fatality. John Wiley and Sons Inc. 2020-07-14 2021-11 /pmc/articles/PMC8032851/ /pubmed/32662080 http://dx.doi.org/10.1002/hec.3986 Text en © 2020 The Authors. Health Economics published by John Wiley & Sons Ltd https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Special Issue Papers
Kasajima, Megumi
Hashimoto, Hideki
Suen, Sze‐Chuan
Chen, Brian
Jalal, Hawre
Eggleston, Karen
Bhattacharya, Jay
Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title_full Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title_fullStr Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title_full_unstemmed Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title_short Future projection of the health and functional status of older people in Japan: A multistate transition microsimulation model with repeated cross‐sectional data
title_sort future projection of the health and functional status of older people in japan: a multistate transition microsimulation model with repeated cross‐sectional data
topic Special Issue Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032851/
https://www.ncbi.nlm.nih.gov/pubmed/32662080
http://dx.doi.org/10.1002/hec.3986
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