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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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 |
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