Hendrie Gilly A, Ullah Shahid, Scott Jane A, Gray John, Berry Narelle, Booth Sue, Carter Patricia, Cobiac Lynne, Coveney John
CSIRO Food and Nutrition Flagship, South Australia.
Flinders Centre for Epidemiology and Biostatistics, School of Medicine, Flinders University, South Australia.
Aust N Z J Public Health. 2015 Dec;39(6):536-43. doi: 10.1111/1753-6405.12442. Epub 2015 Sep 3.
Functional data analysis (FDA) is a forecasting approach that, to date, has not been applied to obesity, and that may provide more accurate forecasting analysis to manage uncertainty in public health. This paper uses FDA to provide projections of Body Mass Index (BMI), overweight and obesity in an Australian population through to 2019.
Data from the South Australian Monitoring and Surveillance System (January 2003 to December 2012, n=51,618 adults) were collected via telephone interview survey. FDA was conducted in four steps: 1) age-gender specific BMIs for each year were smoothed using a weighted regression; 2) the functional principal components decomposition was applied to estimate the basis functions; 3) an exponential smoothing state space model was used for forecasting the coefficient series; and 4) forecast coefficients were combined with the basis function.
The forecast models suggest that between 2012 and 2019 average BMI will increase from 27.2 kg/m(2) to 28.0 kg/m(2) in males and 26.4 kg/m(2) to 27.6 kg/m(2) in females. The prevalence of obesity is forecast to increase by 6-7 percentage points by 2019 (to 28.7% in males and 29.2% in females).
Projections identify age-gender groups at greatest risk of obesity over time. The novel approach will be useful to facilitate more accurate planning and policy development.
功能数据分析（FDA）是一种预测方法，迄今为止尚未应用于肥胖问题，它可能为管理公共卫生领域的不确定性提供更准确的预测分析。本文运用FDA对澳大利亚人群直至2019年的体重指数（BMI）、超重及肥胖情况进行预测。
通过电话访谈调查收集南澳大利亚监测与监督系统（2003年1月至2012年12月，n = 51618名成年人）的数据。FDA按四个步骤进行：1）每年的年龄 - 性别特异性BMI通过加权回归进行平滑处理；2）应用功能主成分分解来估计基函数；3）使用指数平滑状态空间模型预测系数序列；4）将预测系数与基函数相结合。
预测模型表明，在2012年至2019年期间，男性的平均BMI将从27.2kg/m²增至28.0kg/m²，女性则从26.4kg/m²增至27.6kg/m²。预计到2019年肥胖患病率将上升6 - 7个百分点（男性达到28.7%，女性达到29.2%）。
预测确定了随着时间推移肥胖风险最高的年龄 - 性别群体。这种新方法将有助于更准确的规划和政策制定。
