Department of Nutrition and Food Science, Faculty of Medicine, Valladolid University, Valladolid, Spain.
Department of Pediatrics, Hospital Clínico Universitario, University of Valladolid, Valladolid, Spain.
PLoS One. 2019 Jan 24;14(1):e0211148. doi: 10.1371/journal.pone.0211148. eCollection 2019.
BMI is the most commonly used indicator to evaluate overweight and obesity, but it cannot distinguish changes in body composition. Over recent years, it has been demonstrated that bioelectrical impedance analysis (BIA) is a more accurate method for analyzing body composition. Bioelectrical impedance vector analysis (BIVA) has revealed its effectiveness as an indicator of nutritional status and hydration.
To assess the usefulness of bioimpedance analysis on the study of body composition in a group of children with overweight and obesity.
Cross-sectional observational study. The anthropometric parameters of 167 (79 were older than 12 years) overweight and obese children were recorded. Their body composition was analyzed using BIA and BIVA, and was classified based on different criteria. Concordance was analyzed (intraclass correlation coefficient, Bland-Altman analysis and weighted Kappa coefficient). The BIVA of the subgroups was compared using the Mahalanobis distance and Hotelling's T2. Statistical significance was considered for p<0.05.
The BMI revealed that the majority of the assessed subjects were obese, although 12% had a normal percentage of fat mass (%FM). The classification by Z-BMI and Z-%FM significantly discriminate between subjects with different levels of adiposity. In children over the age of 12, the classification of fat mass index also discriminates significantly between obesity and non-obesity. As anticipated, in the tolerance ellipses, most of the individual vectors were situated in the left lower quadrant.
BIVA reflects differences in the bioelectric patterns of children who are classified as being overweight or obese (BMI) and who have different levels of %FM and FMI. BIVA permits a fast and easy monitoring of the evolution of the nutritional state and changes associated with body composition, and it identifies those children whose body compartments may be precisely estimated using traditional BIA methods.
BMI 是评估超重和肥胖最常用的指标，但它无法区分身体成分的变化。近年来，已经证明生物电阻抗分析（BIA）是分析身体成分更准确的方法。生物电阻抗矢量分析（BIVA）已被证明是一种评估营养状况和水合状态的有效指标。
评估生物阻抗分析在一组超重和肥胖儿童身体成分研究中的有用性。
横断面观察性研究。记录了 167 名（79 名年龄大于 12 岁）超重和肥胖儿童的人体测量参数。使用 BIA 和 BIVA 分析他们的身体成分，并根据不同的标准进行分类。分析一致性（组内相关系数、Bland-Altman 分析和加权 Kappa 系数）。使用 Mahalanobis 距离和 Hotelling's T2 比较亚组的 BIVA。p<0.05 为统计学意义。
BMI 显示，大多数受评估的受试者肥胖，尽管 12%的受试者体脂百分比（%FM）正常。Z-BMI 和 Z-%FM 的分类可显著区分不同肥胖程度的受试者。在 12 岁以上的儿童中，脂肪质量指数的分类也可显著区分肥胖和非肥胖。正如预期的那样，在容忍椭圆中，大多数个体向量位于左下方。
BIVA 反映了被归类为超重或肥胖（BMI）且具有不同 %FM 和 FMI 水平的儿童的生物电阻抗模式的差异。BIVA 允许快速轻松地监测营养状态的演变和与身体成分相关的变化，并识别出那些身体成分可以使用传统 BIA 方法精确估计的儿童。
