J Acad Nutr Diet. 2019 Sep;119(9):1533-1540. doi: 10.1016/j.jand.2019.02.017. Epub 2019 May 2.
Adiposity is a major risk factor for metabolic and cardiovascular diseases. Initial prediction equations to estimate adiposity are complex, requiring skinfold measurements that cannot be obtained conveniently by the general population.
To develop simplified prediction equations to estimate body fat percentage (%BF) in Asian Chinese adults, evaluate the validity of the simplified %BF prediction equations, compare the simplified %BF prediction equations with an existing equation, and create visual charts to enable easy assessment of adiposity by the general public.
Simplified prediction equations were developed and evaluated for validity using anthropometric measurements obtained from a cross-sectional study.
Healthy participants with no major diseases and not taking long-term medications were recruited in a cross-sectional study conducted at Clinical Nutrition Research Centre, Singapore, between June 2014 and October 2017. A total of 439 participants were used for model building (269 women and 170 men) and another 107 participants were used for evaluating validity (62 women and 45 men).
Simplified but acceptable prediction models and generation of user-friendly charts.
Simplified sex-specific %BF prediction equations were developed using stepwise regression and the model-building dataset. The best models were selected using the Akaike information criterion. The models were further simplified and their performance was compared using the validation dataset before choosing the final prediction equations.
The final selected models for women and men included waist circumference and height with nonsignificant prediction bias in %BF of 0.84%±3.94% (P=0.098, Cohen's d=0.21) and -0.98%±3.65% (P=0.079, Cohen's d=0.27), respectively. The final equations were split into three height categories from which the sex-specific prediction charts were generated.
The sex-specific prediction charts provide a good visual guide for estimating %BF using height and waist circumference values that are easy to obtain by the general public.
肥胖是代谢和心血管疾病的主要危险因素。最初的预测肥胖的方程很复杂，需要进行皮褶厚度测量，但一般人群无法方便地进行这种测量。
制定用于估计亚洲华裔成年人体脂百分比（%BF）的简化预测方程，评估简化 %BF 预测方程的有效性，比较简化的 %BF 预测方程与现有方程，并创建可视化图表，以便普通大众能够轻松评估肥胖程度。
使用横断面研究中获得的人体测量数据，制定并评估简化预测方程的有效性。
在 2014 年 6 月至 2017 年 10 月期间，在新加坡临床营养研究中心进行的横断面研究中，招募了没有重大疾病且不长期服用药物的健康参与者。共有 439 名参与者用于模型构建（269 名女性和 170 名男性），另有 107 名参与者用于评估有效性（62 名女性和 45 名男性）。
建立简单但可接受的预测模型，并生成易于使用的图表。
使用逐步回归和模型构建数据集，为女性和男性分别建立了简化的特定性别 %BF 预测方程。使用赤池信息量准则（Akaike information criterion）选择最佳模型。在选择最终预测方程之前，使用验证数据集进一步简化模型并比较其性能。
最终选择的女性和男性模型分别包括腰围和身高，%BF 的预测偏差无统计学意义，分别为 0.84%±3.94%（P=0.098，Cohen's d=0.21）和-0.98%±3.65%（P=0.079，Cohen's d=0.27）。最终方程分为三个身高类别，由此生成了特定性别预测图表。
这些特定性别预测图表提供了一个很好的直观指南，可使用一般人群容易获得的身高和腰围值来估计 %BF。
