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梅涛，李晓霞，李燕春，等.抗阻训练改善下肢肌力的个体差异性及预判模型[J].上海体育学院学报，2023，47（9）：64-74. DOI: 10.16099/j.sus.2022.06.13.0005
引用本文: 梅涛，李晓霞，李燕春，等.抗阻训练改善下肢肌力的个体差异性及预判模型[J].上海体育学院学报，2023，47（9）：64-74. DOI: 10.16099/j.sus.2022.06.13.0005
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MEI Tao, LI Xiaoxia, LI Yanchun, YANG Xiaolin, YAN Bing, LIANG Yan, LIANG Lijuan, DUAN Jiayan, ZHANG Zhihao, HE Zihong. Individual Differences and Predictive Models of Lower Limb Muscle Strength after Resistance Training[J]. Journal of Shanghai University of Sport, 2023, 47(9): 64-74. DOI: 10.16099/j.sus.2022.06.13.0005
Citation: MEI Tao, LI Xiaoxia, LI Yanchun, YANG Xiaolin, YAN Bing, LIANG Yan, LIANG Lijuan, DUAN Jiayan, ZHANG Zhihao, HE Zihong. Individual Differences and Predictive Models of Lower Limb Muscle Strength after Resistance Training[J]. Journal of Shanghai University of Sport, 2023, 47(9): 64-74. DOI: 10.16099/j.sus.2022.06.13.0005
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抗阻训练改善下肢肌力的个体差异性及预判模型

Individual Differences and Predictive Models of Lower Limb Muscle Strength after Resistance Training

    摘要
  • 摘要:
    目的  比较不同抗阻训练后下肢肌力变化的个体差异，构建抗阻训练改善下肢肌力的预判模型。
    方法  193名受试者完成12周70%1RM训练（MIST12），其中训练无效者以87%1RM完成8周（HIST8）和12周的训练（HIST12）。下肢肌力指标包括等速蹬踏屈/伸峰值力（PTf/PTe）、等长峰值力（PTi）和反向纵跳（CMJ）。采用Logistic回归构建训练效果的预判模型。
    结果  MIST12干预后，PTf、PTe、CMJ显著增加（P<0.01），PTi变化无显著性差异（P>0.05）；HIST8干预后，PTf、PTe变化无显著性差异（P>0.05），PTi、CMJ显著增加（P<0.05）；HIST12干预后，PTf、PTe、PTi、CMJ显著增加（P<0.05）。PTf、PTe低效者比例在3种方案中无显著性差异（P>0.05），PTi、CMJ低效者比例差异显著（P<0.05）。 PTf、PTe、PTi和CMJ训练效果预判模型的AUC值分别为0.609、0.602、0.684和0.719，回代检验显示预测值与真实值无差异（P>0.05）。
    结论  抗阻训练改善下肢肌力存在个体差异，肌力初始值、训练方案和肌肉厚度是下肢肌力训练效果的预判因子，在制订以提升不同肌力为目的的精准化力量健身指导方案时应将其作为重要参考因素。

     

    Abstract:
    Objective To compare the individual differences in lower limb strength changes after different resistance training programs and construct a predictive model for improving lower limb strength through resistance training.
    Methods 193 participants completed a 12-week 70% 1RM training program (MIST12), with ineffective trainees completed 8 weeks (HIST8) and 12 weeks (HIST12) of training at 87% 1RM. Lower limb strength indicators included peak force during concentric (PTf) and eccentric (PTe) knee extension/flexion, isometric peak force (PTi), and counter movement jump (CMJ). Logistic regression was used to construct a predictive model for training effectiveness.
    Results After MIST12 intervention, PTf, PTe, and CMJ significantly increased (P < 0.01), while PTi showed no significant change (P > 0.05). After HIST8 intervention, PTf and PTe showed no significant change (P > 0.05), while PTi and CMJ significantly increased (P < 0.05). After HIST12 intervention, PTf, PTe, PTi, and CMJ significantly increased (P < 0.05). No significant differences were found in the proportion of low respondents in PTf and PTe among the three programs (P > 0.05), while there was a significant difference in the proportion of low respondents in PTi and CMJ (P < 0.05). The AUC values for the predictive models of PTf, PTe, PTi, and CMJ training effectiveness were 0.609, 0.602, 0.684, and 0.719, respectively. Back testing showed no significant differences between predicted values and actual values (P > 0.05).
    Conclusion Individual differences exist in improving lower limb muscle strength through resistance training. Initial strength, training program, and muscle thickness are predictive factors for the effectiveness of lower limb strength training. They should be considered important factors in developing personalized strength training guidance for different strength goals.

     

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