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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
Author(s) -
Kasajima Megumi,
Hashimoto Hideki,
Suen SzeChuan,
Chen Brian,
Jalal Hawre,
Eggleston Karen,
Bhattacharya Jay
Publication year - 2021
Publication title -
health economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.55
H-Index - 109
eISSN - 1099-1050
pISSN - 1057-9230
DOI - 10.1002/hec.3986
Subject(s) - microsimulation , population , projections of population growth , medicine , population projection , representativeness heuristic , demography , population ageing , comorbidity , epidemiology , gerontology , environmental health , statistics , population growth , mathematics , pathology , sociology , transport engineering , engineering
Abstract 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.