• Siyu Liang, Zhongyu Ren, and Guang Yang.
• School of Physical Education and Chinese Center of Exercise Epidemiology, Northeast Normal University, Changchun, PR China.
• Medicine (Baltimore). 2022 Aug 19; 101 (33): e30034e30034.

AbstractSevere internet addiction (IA) is associated with a higher risk of musculoskeletal pain, but whether there is a significant prospective association between IA and fatigue is unclear. This study aimed to examine the association between IA and fatigue level among Chinese college students. A cross-sectional (n = 1011) and prospective study (n = 653) was conducted to examine the association between IA and risk of fatigue. IA was measured using Young internet addiction test. Fatigue level was evaluated using the Chalder fatigue scale. Multivariate logistic regression analyses showed a cross-sectional association between IA and the risk of fatigue. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.88 (1.20, 2.95), and 5.60 (3.33, 9.42), respectively (P for trend: <0.001). Similarly, multivariate logistic regression analyses also revealed a significant prospective relationship between IA and the risk of fatigue during the 1-year follow-up period. The odds ratios (95% CIs) of fatigue for normal, mild, and moderate to severe groups were 1.00 (reference), 1.56 (0.67, 3.67), and 3.29 (1.08, 10.04), respectively (P for trend: 0.046). Our findings indicate that IA is positively related to risk of fatigue among Chinese college students. Further interventional studies are needed to explore the causality underlying the effects of IA on fatigue.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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