Hayes A J, Lung T W C, Bauman A, Howard K
Sydney School of Public Health, University of Sydney, Sydney, New South Wales, Australia.
Office of the Chief Scientist, The George Institute for Global Health, Sydney Medical School, University of Sydney, New South Wales, Australia.
Int J Obes (Lond). 2017 Jan;41(1):178-185. doi: 10.1038/ijo.2016.165. Epub 2016 Sep 27.
BACKGROUND/OBJECTIVES: Modelling is increasingly being used to predict the epidemiology of obesity progression and its consequences. The aims of this study were: (a) to present and validate a model for prediction of obesity among Australian adults and (b) to use the model to project the prevalence of obesity and severe obesity by 2025.
SUBJECTS/METHODS: Individual level simulation combined with survey estimation techniques to model changing population body mass index (BMI) distribution over time. The model input population was derived from a nationally representative survey in 1995, representing over 12 million adults. Simulations were run for 30 years. The model was validated retrospectively and then used to predict obesity and severe obesity by 2025 among different aged cohorts and at a whole population level.
The changing BMI distribution over time was well predicted by the model and projected prevalence of weight status groups agreed with population level data in 2008, 2012 and 2014.The model predicts more growth in obesity among younger than older adult cohorts. Projections at a whole population level, were that healthy weight will decline, overweight will remain steady, but obesity and severe obesity prevalence will continue to increase beyond 2016. Adult obesity prevalence was projected to increase from 19% in 1995 to 35% by 2025. Severe obesity (BMI>35), which was only around 5% in 1995, was projected to be 13% by 2025, two to three times the 1995 levels.
The projected rise in obesity severe obesity will have more substantial cost and healthcare system implications than in previous decades. Having a robust epidemiological model is key to predicting these long-term costs and health outcomes into the future.
背景/目的：建模越来越多地用于预测肥胖进展及其后果的流行病学情况。本研究的目的是：（a）提出并验证一个用于预测澳大利亚成年人肥胖情况的模型；（b）使用该模型预测到2025年肥胖和重度肥胖的患病率。
对象/方法：采用个体水平模拟结合调查估计技术，对随时间变化的人群体重指数（BMI）分布进行建模。模型输入人群来自1995年的一项全国代表性调查，代表了超过1200万成年人。模拟运行30年。该模型进行了回顾性验证，然后用于预测到2025年不同年龄队列以及全人群水平的肥胖和重度肥胖情况。
该模型很好地预测了BMI随时间的变化情况，并且预测的体重状况组患病率与2008年、2012年和2014年的人群水平数据相符。该模型预测，与老年成年队列相比，年轻成年队列中的肥胖增长更多。在全人群水平上的预测是，健康体重将下降，超重将保持稳定，但肥胖和重度肥胖患病率在2016年之后将继续上升。预计成年肥胖患病率将从1995年的19%上升到2025年的35%。重度肥胖（BMI>35）在1995年仅约为5%，预计到2025年将达到13%，是1995年水平的两到三倍。
预计肥胖和重度肥胖的上升将比前几十年产生更巨大的成本和对医疗保健系统的影响。拥有一个强大的流行病学模型是预测未来这些长期成本和健康结果的关键。
