ArticleFrontiers in physiology2026
Anatomical spatial-temporal distribution and multivariate risk of acute injuries in elite rugby: a cohort based on prospective surveillance.
Article in Frontiers in physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Acute injuries are common in rugby and threaten both player health and career longevity. Previous studies often focused on isolated risk factors, while limited research has comprehensively examined the interplay of physiological, environmental, and situational variables. Methods: Study conducted A cohort study of 40 elite male players from the Tianjin Rugby Team was conducted, monitoring 575 match exposures across 2.5 consecutive seasons (2022-2025). Acute injuries were defined according to international consensus criteria and verified by medical staff. Spatiotemporal distributions (seasonal variation, match stage, playing position, and body site) were analyzed using chi-square and logistic regression. Multivariate models were applied to identify independent risk factors, including demographic, training, and environmental variables. Results: A total of 143 acute injury events were recorded, with bone and joint injuries most prevalent (48.2%), and the majority classified as moderate-to-severe (78.3%). Injury incidence rate rose significantly across seasons (127.9 per 1,000 player-hours in 2024/25 vs. 43.3 in 2022/23, representing a 1.83-fold increase), and advanced competition stages showed higher risks (OR for finals = 7.06 vs. group stage, p<0.001). GEE analysis demonstrated that the 2023/24 season, semi-finals and finals, forward position, no previous injury history, and higher training load were associated with elevated acute injury risk among rugby players (all P<0.05), while higher temperature served as a protective factor (P<0.001); age, BMI, exercise level, fatigue, and training years showed no significant effects. Conclusions: Acute injury risk in rugby demonstrates clear spatiotemporal patterns and is strongly influenced by both individual and environmental factors. The model developed provides a practical basis for targeted prevention strategies, including load management, environmental adaptation, and individualized recovery protocols. These findings can serve as a reference for coaches and medical teams at elite Chinese rugby clubs-particularly those adopting training-competition models-to optimize training and competition management.
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