Yang Guang, Cao Jianhua, Li Yingke, Cheng Peng, Liu Bin, Hao Zongji, Yao Hui, Shi Dongzhe, Peng Li, Guo Liya, Ren Zhongyu
School of Physical Education, Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun, China.
College of Physical Education, Key Laboratory of Physical Fitness Evaluation and Motor Function Monitoring, General Administration of Sport of China, Institute of Sports Science, Southwest University, Chongqing, China.
Front Psychol. 2019 Sep 3;10:1959. doi: 10.3389/fpsyg.2019.01959. eCollection 2019.
It is well established that increased internet use is related to an increased risk of musculoskeletal pain among adolescents. The relationship between internet addiction (IA), a unique condition involving severe internet overuse, and musculoskeletal pain has, however, not been reported. This study aimed to investigate the association between IA and the risk of musculoskeletal pain among Chinese college students.
A cross-sectional study was conducted among 4211 Chinese college freshmen. IA status was evaluated using the 20-item Young's Internet Addiction Test (IAT). IA was defined as internet addiction score ≥50 points. Musculoskeletal pain was assessed using a self-reported questionnaire. Multiple logistic regression analysis was performed to determine association between IA categories (normal, mild, and moderate-to-severe) and musculoskeletal pain.
Among all participants; neck, shoulder, elbow, wrist/hand, and low back and waist pain was reported by 29.2, 33.9, 3.8, 7.9, and 27.9%, respectively. The prevalence of IA was 17.4%. After adjusting for potential confounders, the results showed significant differences in the risk of musculoskeletal pain among different IA categories. The odds ratios (ORs) and 95% confidence intervals (CI) for neck pain with IA categories were 1.000 (reference), 1.451 (1.221, 1.725), and 1.994 (1.608, 2.473), respectively ( for trends: < 0.001). For shoulder pain, these were 1.000 (reference), 1.520 (1.287, 1.795), and 2.057 (1.664, 2.542), respectively ( for trends: < 0.001). For elbow pain, ORs (95% CIs) were 1.000 (reference), 1.627 (1.016, 2.605), and 2.341 (1.382, 3.968), respectively ( for trends: 0.001). Those for wrist/hand pain were 1.000 (reference), 1.508 (1.104, 2.060), and 2.236 (1.561, 3.202), respectively ( for trends: < 0.001). For low back and waist pain with severe IA categories, these were 1.000 (reference), 1.635 (1.368, 1.955), and 2.261 (1.813, 2.819), respectively ( for trends: < 0.001).
This cross-sectional study showed that severe IA was associated with a higher risk of musculoskeletal pain in Chinese college freshmen. In future research, it will be necessary to explore causality regarding this relationship using interventional studies.
已有充分证据表明，青少年上网时间增加与肌肉骨骼疼痛风险增加有关。然而，网络成瘾（IA）这一涉及严重网络过度使用的独特状况与肌肉骨骼疼痛之间的关系尚未见报道。本研究旨在调查中国大学生中IA与肌肉骨骼疼痛风险之间的关联。
对4211名中国大学新生进行了一项横断面研究。使用20项杨氏网络成瘾测试（IAT）评估IA状态。IA被定义为网络成瘾得分≥50分。使用自我报告问卷评估肌肉骨骼疼痛。进行多因素逻辑回归分析以确定IA类别（正常、轻度和中度至重度）与肌肉骨骼疼痛之间的关联。
在所有参与者中，分别有29.2%、33.9%、3.8%、7.9%和27.9%的人报告有颈部、肩部、肘部、手腕/手部以及下背部和腰部疼痛。IA的患病率为17.4%。在调整潜在混杂因素后，结果显示不同IA类别之间肌肉骨骼疼痛风险存在显著差异。IA类别与颈部疼痛的比值比（OR）和95%置信区间（CI）分别为1.000（参考值）、1.451（1.221，1.725）和1.994（1.608，2.473）（趋势：<0.001）。对于肩部疼痛，这些值分别为1.000（参考值）、1.520（1.287，1.795）和2.057（1.664，2.542）（趋势：<0.001）。对于肘部疼痛，OR（95%CI）分别为1.000（参考值）、1.627（1.016，2.605）和2.341（1.382，3.968）（趋势：0.001）。手腕/手部疼痛的OR值分别为1.000（参考值）、1.508（1.104，2.060）和2.236（1.561，3.202）（趋势：<0.001）。对于重度IA类别下的下背部和腰部疼痛，这些值分别为1.000（参考值）、1.635（1.368，1.955）和2.261（1.813，2.819）（趋势：<0.001）。
这项横断面研究表明，重度IA与中国大学新生中较高的肌肉骨骼疼痛风险相关。在未来的研究中，有必要使用干预性研究来探索这种关系的因果性。
