Cortés-Castell Ernesto, Juste Mercedes, Palazón-Bru Antonio, Monge Laura, Sánchez-Ferrer Francisco, Rizo-Baeza María Mercedes
Pharmacology, Pediatrics and Organic Chemistry Department, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
Clinical Medicine Department, Miguel Hernández University, San Juan de Alicante, Alicante, Spain.
PeerJ. 2017 Apr 27;5:e3238. doi: 10.7717/peerj.3238. eCollection 2017.
Dual-energy X-ray absorptiometry (DXA) provides separate measurements of fat mass, fat-free mass and bone mass, and is a quick, accurate, and safe technique, yet one that is not readily available in routine clinical practice. Consequently, we aimed to develop statistical formulas to predict fat mass (%) and fat mass index (FMI) with simple parameters (age, sex, weight and height).
We conducted a retrospective observational cross-sectional study in 416 overweight or obese patients aged 4-18 years that involved assessing adiposity by DXA (fat mass percentage and FMI), body mass index (BMI), sex and age. We randomly divided the sample into two parts (construction and validation). In the construction sample, we developed formulas to predict fat mass and FMI using linear multiple regression models. The formulas were validated in the other sample, calculating the intraclass correlation coefficient via bootstrapping.
The fat mass percentage formula had a coefficient of determination of 0.65. This value was 0.86 for FMI. In the validation, the constructed formulas had an intraclass correlation coefficient of 0.77 for fat mass percentage and 0.92 for FMI.
Our predictive formulas accurately predicted fat mass and FMI with simple parameters (BMI, sex and age) in children with overweight and obesity. The proposed methodology could be applied in other fields. Further studies are needed to externally validate these formulas.
双能X线吸收法(DXA)可分别测量脂肪量、去脂体重和骨量,是一种快速、准确且安全的技术,但在常规临床实践中不易获得。因此,我们旨在开发统计公式,以利用简单参数(年龄、性别、体重和身高)预测脂肪量(%)和脂肪量指数(FMI)。
我们对416名4至18岁的超重或肥胖患者进行了一项回顾性观察性横断面研究,通过DXA评估肥胖程度(脂肪量百分比和FMI)、体重指数(BMI)、性别和年龄。我们将样本随机分为两部分(构建和验证)。在构建样本中,我们使用线性多元回归模型开发预测脂肪量和FMI的公式。这些公式在另一个样本中进行验证,通过自抽样计算组内相关系数。
脂肪量百分比公式的决定系数为0.65。FMI的该值为0.86。在验证中,构建的公式对于脂肪量百分比的组内相关系数为0.77,对于FMI为0.92。
我们的预测公式能够利用超重和肥胖儿童的简单参数(BMI、性别和年龄)准确预测脂肪量和FMI。所提出的方法可应用于其他领域。需要进一步研究对这些公式进行外部验证。