生物电阻抗法与双能X线吸收法测量儿童青少年骨矿物含量的比较

  目的  评价生物电阻抗法(BIA)与双能X线吸收法(DXA)测量儿童青少年的骨矿物含量(BMC)的一致性，为BIA准确测量儿童青少年BMC提供依据。  方法  采用方便抽样法，于2019年4—5月在广州市某区招募1 469名7~17岁儿童青少年，采用DXA和BIA技术分别测量BMC。采用组内相关系数(ICC)、Bland-Altman分析评价一致性。Bland-Altman分析在对数转换的数据中进行。将BMC按性别年龄别三分位数分类，计算Kappa值评价一致性。以DXA测量值为因变量，建立BIA校正预测模型。  结果  男、女生的ICC分别为0.93和0.94。在Bland-Altman分析中，男、女生的BIA与DXA比值的一致性限范围均较宽，分别为0.27~0.76和0.17~0.72。男、女生中两方法判断BMC三分类水平的Kappa值分别为0.57和0.45，呈中高度一致。按BMI分组，各体重状态男生及超重女生的Kappa值均在0.75以上，一致性程度极好。构建的男、女生BIA校正预测模型分别为:BMC_DXA=-0.51+0.44×BMC_BIA+0.06×Age+0.02×BMI; BMC_DXA=-0.55+0.43×BMC_BIA+0.06×Age+0.02×BMI。模型的R2值分别为0.87和0.87。  结论  BIA与DXA所测BMC值一致性较差，但在判断分类BMC水平方面一致性尚可，研究建立的BIA测量BMC校正模型拟合效果好，提示BIA可能适用于评估儿童群体的BMC发育水平。

Comparative analysis of bone mineral content measured by bioelectrical impedance analysis and dual-energy X-ray absorption among children and adolescents

  Objective  To compare bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) for measuring body mineral content (BMC) of children and adolescents, and to provide a basis for BIA to accurately measure BMC in children and adolescents.  Methods  By using the convenience sampling method, among 1 469 children and adolescents aged 7-17 were recruited in Guangzhou from April to May 2019, the BMC was measured by DXA and BIA. The intraclass correlation coefficient (ICC) and Bland-Altman analysis were used to evaluate the agreement between BIA and DXA. Bland-Altman analysis was performed on log-transformed data. The BMC was categorized into age-and specific-tertiles, and the agreement between methods was evaluated based on the kappa coefficients. Treating the BMC with DXA as the dependent variable, a prediction model was constructed for correcting the BIA measure.  Results  The ICCs were 0.93 and 0.94 for boys and girls, respectively. In Bland-Altman analysis, the limits of agreements for the BIA-to-DXA ratio were wide in boys and girls, ranging from 0.27-0.76 and 0.17-0.72, respectively. The kappa coefficients for categorized BMC levels were 0.57 and 0.45 for boys and girls, respectively, showing a fair-to-good degree of agreement. When sub-grouped by BMI, the kappa coefficients for all BMI groups of boys and overweight girls were all >0.75, with an excellent agreement. The prediction models for boys and girls were as follows: BMC_DXA=-0.51+0.44×BMC_BIA+0.06×Age+0.02×BMI; and BMC_DXA=-0.55+0.43×BMC_BIA+0.06×Age+0.02×BMI, respectively. The R2 for models of boys and girls were 0.87 and 0.87, respectively.  Conclusion  The agreement between BIA and DXA was poor for measuring BMC, but acceptable when evaluating the categorized BMC levels, suggesting the BIA may be applied in assessment of the BMC levels when compared to the age-and gender-specific population. Additionally, the prediction model for correcting BMC by BIA fis well to the measurement by DXA.