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刘景新, 朱琳, 徐佶, 苏煜, 孙越鹏, 廖晶, 胡水, 刘晓光. 肥胖儿童青少年运动强度的多指标联合诊断标准及价值[J]. 上海体育学院学报 , 2021, 45(10): 54-61. DOI: 10.16099/j.sus.2021.10.005
引用本文: 刘景新, 朱琳, 徐佶, 苏煜, 孙越鹏, 廖晶, 胡水, 刘晓光. 肥胖儿童青少年运动强度的多指标联合诊断标准及价值[J]. 上海体育学院学报 , 2021, 45(10): 54-61. DOI: 10.16099/j.sus.2021.10.005
LIU Jingxin, ZHU Lin, XU Ji, SU Yu, SUN Yuepeng, LIAO Jing, HU Shui, LIU Xiaoguang. Diagnostic Criteria and Value of Multiple-index Joint Diagnosis of Exercise Intensity in Obese Children and Adolescents[J]. Journal of Shanghai University of Sport, 2021, 45(10): 54-61. DOI: 10.16099/j.sus.2021.10.005
Citation: LIU Jingxin, ZHU Lin, XU Ji, SU Yu, SUN Yuepeng, LIAO Jing, HU Shui, LIU Xiaoguang. Diagnostic Criteria and Value of Multiple-index Joint Diagnosis of Exercise Intensity in Obese Children and Adolescents[J]. Journal of Shanghai University of Sport, 2021, 45(10): 54-61. DOI: 10.16099/j.sus.2021.10.005

肥胖儿童青少年运动强度的多指标联合诊断标准及价值

Diagnostic Criteria and Value of Multiple-index Joint Diagnosis of Exercise Intensity in Obese Children and Adolescents

  • 摘要:
      目的  建立多指标联合诊断肥胖儿童青少年运动强度的标准,为诊断肥胖儿童青少年运动强度提供方法学参考。
      方法  招募160名10~17岁肥胖儿童青少年(训练集120人,验证集40人),测试3~7 km/h自由走、跑运动的代谢当量(MET)、心率储备百分比(% HRR)和综合矢量计数(VM3);采用Logistic回归建立多指标联合诊断模型,以多指标联合预测概率值(P3METsP6METs)绘制ROC曲线,以最大约登指数确定适宜切点;通过ROC曲线下面积评价诊断价值,通过准确率和加权Kappa值检验准确性和一致性。
      结果  多指标联合诊断模型为Logist(P3METs)=10.666-9.760×10-2×% HRR-1.035×10-3×VM3-0.290×年龄;Logist(P6METs)=-15.337+0.127×% HRR+6.316×10-4×VM3+0.176×年龄。P3METs诊断运动强度的切点是0.315,ROC曲线下面积为0.891;P6METs诊断运动强度的切点是0.248,ROC曲线下面积为0.956。多指标联合的诊断准确率为79.62%,加权Kappa值为0.686。
      结论  多指标联合诊断模型可用于诊断肥胖儿童青少年运动强度,具有较高的诊断价值。诊断标准是低强度P3METs>0.315,中等强度P3METs≤0.315且P6METs < 0.248,高强度P6METs≥0.248。

     

    Abstract:
      Objective  To establish a multi-index method for the diagnosis of exercise intensity, and provide a methodological reference for accurately diagnosing exercise intensity of obese children and adolescents.
      Methods  160 obese children and adolescents aged 10~17 were randomly divided into training group (n=120) and validation group (n=40). The METs, %HRR and vector magnitudes (VM3) were measured for all participants during free walking and running at 3~7 km/h. Logistic regression was used to establish the multi-index joint diagnosis model, and the ROC curve was conducted with the prediction probability values (P3METs and P6METs), and the cut-off point of intensity was determined by the maximum Youden index. The area under the ROC curve was evaluated for diagnostic value, accuracy and weighted Kappa values were tested for accuracy and consistency.
      Results  The 3METs multi-index joint diagnosis model was Logist(P3METs)=10.666-9.760×10-2×%HRR-1.035×10-3×VM3-0.290×Age, while the 6METs was Logist(P6METs)=-15.34+0.127×%HRR+6.316×10-4×VM3+0.176×Age. The cut-off point of 3METs for P3METswas 0.315, and the area under curve of ROC was 0.891.The cut-off point of 6METs for P6METswas 0.248, and the area under curve of ROC was 0.956. The accuracy of multiple-index joint diagosis was 79.62%, and the weighted Kappa value was 0.686.
      Conclusion  Multiple-index joint diagnosis model can be used to diagnose the exercise intensity of obese children and adolescents, which has high diagnostic value.The diagnostic criteria of light-intensity was P3METs>0.315, moderate-intensity P3METs ≤ 0.315 and P6METs < 0.248, and high-intensity P6METs ≥ 0.248.

     

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