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Forecasting the burden of type 2 diabetes in Singapore using a demographic epidemiological model of Singapore
  1. Thao P Phan1,
  2. Leontine Alkema1,2,
  3. E Shyong Tai1,3,4,
  4. Kristin H X Tan1,
  5. Qian Yang1,
  6. Wei-Yen Lim1,5,
  7. Yik Ying Teo1,2,6,
  8. Ching-Yu Cheng1,7,8,9,
  9. Xu Wang1,
  10. Tien Yin Wong7,8,
  11. Kee Seng Chia1,
  12. Alex R Cook1,2,10,11
  1. 1Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
  2. 2Department of Statistics and Applied Probability, Faculty of Science, National University of Singapore, Singapore
  3. 3Division of Endocrinology, National University Hospital and National University Health System, Singapore
  4. 4Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  5. 5Ministry of Health, Singapore
  6. 6Life Sciences Institute, National University of Singapore, Singapore
  7. 7Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
  8. 8Singapore Eye Research Institute, Singapore
  9. 9Center for Quantitative Medicine, Duke-NUS Graduate Medical School, Singapore
  10. 10Program in Health Services and Systems Research, Duke-NUS Graduate Medical School, Singapore
  11. 11Yale-NUS College, Singapore
  1. Correspondence to Dr Alex R Cook; alex.richard.cook{at}gmail.com

Abstract

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.

  • Adult Diabetes
  • Statistical Methods
  • Demographics
  • Simulation

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/

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