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Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore

OBJECTIVE: Singapore is a microcosm of Asia as a whole, and its rapidly ageing, increasingly sedentary population heralds the chronic health problems other Asian countries are starting to face and will likely face in the decades ahead. Forecasting the changing burden of chronic diseases such as type...

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Autores principales: Phan, Thao P, Alkema, Leontine, Tai, E Shyong, Tan, Kristin H X, Yang, Qian, Lim, Wei-Yen, Teo, Yik Ying, Cheng, Ching-Yu, Wang, Xu, Wong, Tien Yin, Chia, Kee Seng, Cook, Alex R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212579/
https://www.ncbi.nlm.nih.gov/pubmed/25452860
http://dx.doi.org/10.1136/bmjdrc-2013-000012
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author Phan, Thao P
Alkema, Leontine
Tai, E Shyong
Tan, Kristin H X
Yang, Qian
Lim, Wei-Yen
Teo, Yik Ying
Cheng, Ching-Yu
Wang, Xu
Wong, Tien Yin
Chia, Kee Seng
Cook, Alex R
author_facet Phan, Thao P
Alkema, Leontine
Tai, E Shyong
Tan, Kristin H X
Yang, Qian
Lim, Wei-Yen
Teo, Yik Ying
Cheng, Ching-Yu
Wang, Xu
Wong, Tien Yin
Chia, Kee Seng
Cook, Alex R
author_sort Phan, Thao P
collection PubMed
description OBJECTIVE: Singapore is a microcosm of Asia as a whole, and its rapidly ageing, increasingly sedentary population heralds the chronic health problems other Asian countries are starting to face and will likely face in the decades ahead. Forecasting the changing burden of chronic diseases such as type 2 diabetes in Singapore is vital to plan the resources needed and motivate preventive efforts. METHODS: This paper describes an individual-level simulation model that uses evidence synthesis from multiple data streams—national statistics, national health surveys, and four cohort studies, and known risk factors—aging, obesity, ethnicity, and genetics—to forecast the prevalence of type 2 diabetes in Singapore. This comprises submodels for mortality, fertility, migration, body mass index trajectories, genetics, and workforce participation, parameterized using Markov chain Monte Carlo methods, and permits forecasts by ethnicity and employment status. RESULTS: We forecast that the obesity prevalence will quadruple from 4.3% in 1990 to 15.9% in 2050, while the prevalence of type 2 diabetes (diagnosed and undiagnosed) among Singapore adults aged 18–69 will double from 7.3% in 1990 to 15% in 2050, that ethnic Indians and Malays will bear a disproportionate burden compared with the Chinese majority, and that the number of patients with diabetes in the workforce will grow markedly. CONCLUSIONS: If the recent rise in obesity prevalence continues, the lifetime risk of type 2 diabetes in Singapore will be one in two by 2050 with concomitant implications for greater healthcare expenditure, productivity losses, and the targeting of health promotion programmes.
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spelling pubmed-42125792014-12-01 Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore Phan, Thao P Alkema, Leontine Tai, E Shyong Tan, Kristin H X Yang, Qian Lim, Wei-Yen Teo, Yik Ying Cheng, Ching-Yu Wang, Xu Wong, Tien Yin Chia, Kee Seng Cook, Alex R BMJ Open Diabetes Res Care Epidemiology/Health service research OBJECTIVE: Singapore is a microcosm of Asia as a whole, and its rapidly ageing, increasingly sedentary population heralds the chronic health problems other Asian countries are starting to face and will likely face in the decades ahead. Forecasting the changing burden of chronic diseases such as type 2 diabetes in Singapore is vital to plan the resources needed and motivate preventive efforts. METHODS: This paper describes an individual-level simulation model that uses evidence synthesis from multiple data streams—national statistics, national health surveys, and four cohort studies, and known risk factors—aging, obesity, ethnicity, and genetics—to forecast the prevalence of type 2 diabetes in Singapore. This comprises submodels for mortality, fertility, migration, body mass index trajectories, genetics, and workforce participation, parameterized using Markov chain Monte Carlo methods, and permits forecasts by ethnicity and employment status. RESULTS: We forecast that the obesity prevalence will quadruple from 4.3% in 1990 to 15.9% in 2050, while the prevalence of type 2 diabetes (diagnosed and undiagnosed) among Singapore adults aged 18–69 will double from 7.3% in 1990 to 15% in 2050, that ethnic Indians and Malays will bear a disproportionate burden compared with the Chinese majority, and that the number of patients with diabetes in the workforce will grow markedly. CONCLUSIONS: If the recent rise in obesity prevalence continues, the lifetime risk of type 2 diabetes in Singapore will be one in two by 2050 with concomitant implications for greater healthcare expenditure, productivity losses, and the targeting of health promotion programmes. BMJ Publishing Group 2014-06-11 /pmc/articles/PMC4212579/ /pubmed/25452860 http://dx.doi.org/10.1136/bmjdrc-2013-000012 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 3.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Epidemiology/Health service research
Phan, Thao P
Alkema, Leontine
Tai, E Shyong
Tan, Kristin H X
Yang, Qian
Lim, Wei-Yen
Teo, Yik Ying
Cheng, Ching-Yu
Wang, Xu
Wong, Tien Yin
Chia, Kee Seng
Cook, Alex R
Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title_full Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title_fullStr Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title_full_unstemmed Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title_short Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
title_sort forecasting the burden of type 2 diabetes in singapore using a demographic epidemiological model of singapore
topic Epidemiology/Health service research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4212579/
https://www.ncbi.nlm.nih.gov/pubmed/25452860
http://dx.doi.org/10.1136/bmjdrc-2013-000012
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