Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030

The objective of this study is to predict the volume of the elderly in different health status categories in Thailand in the next ten years (2020–2030). Multistate modelling was performed. We defined four states of elderly patients (aged ≥ 60 years) according to four different levels of Activities o...

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Main Authors: Panupong Tantirat, Repeepong Suphanchaimat, Thanit Rattanathumsakul, Thinakorn Noree
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:International Journal of Environmental Research and Public Health
Subjects:
Online Access:https://www.mdpi.com/1660-4601/17/22/8703
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spelling doaj-ea33e8b89bbb4efe81aac3285de5ff782020-11-25T04:11:55ZengMDPI AGInternational Journal of Environmental Research and Public Health1661-78271660-46012020-11-01178703870310.3390/ijerph17228703Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030Panupong Tantirat0Repeepong Suphanchaimat1Thanit Rattanathumsakul2Thinakorn Noree3Division of Epidemiology, Disease Control, Ministry of Public Health, Nonthaburi 11000, ThailandDivision of Epidemiology, Disease Control, Ministry of Public Health, Nonthaburi 11000, ThailandDivision of Epidemiology, Disease Control, Ministry of Public Health, Nonthaburi 11000, ThailandInternational Health Policy Program (IHPP), Ministry of Public Health, Nonthaburi 11000, ThailandThe objective of this study is to predict the volume of the elderly in different health status categories in Thailand in the next ten years (2020–2030). Multistate modelling was performed. We defined four states of elderly patients (aged ≥ 60 years) according to four different levels of Activities of Daily Living (ADL): social group; home group; bedridden group; and dead group. The volume of newcomers was projected by trend extrapolation methods with exponential growth. The transition probabilities from one state to another was obtained by literature review and model optimization. The mortality rate was obtained by literature review. Sensitivity analysis was conducted. By 2030, the number of social, home, and bedridden groups was 15,593,054, 321,511, and 152,749, respectively. The model prediction error was 1.75%. Sensitivity analysis with the change of transition probabilities by 20% caused the number of bedridden patients to vary from between 150,249 and 155,596. In conclusion, the number of bedridden elders will reach 153,000 in the next decade (3 times larger than the status quo). Policy makers may consider using this finding as an input for future resource planning and allocation. Further studies should be conducted to identify the parameters that better reflect the transition of people from one health state to another.https://www.mdpi.com/1660-4601/17/22/8703bedriddenlong-term caremulti-state modellingelderlyThailand
collection DOAJ
language English
format Article
sources DOAJ
author Panupong Tantirat
Repeepong Suphanchaimat
Thanit Rattanathumsakul
Thinakorn Noree
spellingShingle Panupong Tantirat
Repeepong Suphanchaimat
Thanit Rattanathumsakul
Thinakorn Noree
Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
International Journal of Environmental Research and Public Health
bedridden
long-term care
multi-state modelling
elderly
Thailand
author_facet Panupong Tantirat
Repeepong Suphanchaimat
Thanit Rattanathumsakul
Thinakorn Noree
author_sort Panupong Tantirat
title Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
title_short Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
title_full Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
title_fullStr Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
title_full_unstemmed Projection of the Number of Elderly in Different Health States in Thailand in the Next Ten Years, 2020–2030
title_sort projection of the number of elderly in different health states in thailand in the next ten years, 2020–2030
publisher MDPI AG
series International Journal of Environmental Research and Public Health
issn 1661-7827
1660-4601
publishDate 2020-11-01
description The objective of this study is to predict the volume of the elderly in different health status categories in Thailand in the next ten years (2020–2030). Multistate modelling was performed. We defined four states of elderly patients (aged ≥ 60 years) according to four different levels of Activities of Daily Living (ADL): social group; home group; bedridden group; and dead group. The volume of newcomers was projected by trend extrapolation methods with exponential growth. The transition probabilities from one state to another was obtained by literature review and model optimization. The mortality rate was obtained by literature review. Sensitivity analysis was conducted. By 2030, the number of social, home, and bedridden groups was 15,593,054, 321,511, and 152,749, respectively. The model prediction error was 1.75%. Sensitivity analysis with the change of transition probabilities by 20% caused the number of bedridden patients to vary from between 150,249 and 155,596. In conclusion, the number of bedridden elders will reach 153,000 in the next decade (3 times larger than the status quo). Policy makers may consider using this finding as an input for future resource planning and allocation. Further studies should be conducted to identify the parameters that better reflect the transition of people from one health state to another.
topic bedridden
long-term care
multi-state modelling
elderly
Thailand
url https://www.mdpi.com/1660-4601/17/22/8703
work_keys_str_mv AT panupongtantirat projectionofthenumberofelderlyindifferenthealthstatesinthailandinthenexttenyears20202030
AT repeepongsuphanchaimat projectionofthenumberofelderlyindifferenthealthstatesinthailandinthenexttenyears20202030
AT thanitrattanathumsakul projectionofthenumberofelderlyindifferenthealthstatesinthailandinthenexttenyears20202030
AT thinakornnoree projectionofthenumberofelderlyindifferenthealthstatesinthailandinthenexttenyears20202030
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