Introduction: Sleep is crucial for recovery post-training in sports. However, studies have found that athletes, especially in elite level, have significantly poorer sleep quality compared to non-athletic population. To develop a comprehensive strategy for improving sleep quality for better recovery in sports, this study aims to conduct a systematic review to (1) identify the risk factors associated with sleep disorders in athletic populations, and (2) grading of recommendations for these factors that according to the strength of the evidence from the literature. Fnally, (3) synthesize the factors identified based on the workload-injury model. Methods: Four databases were searched for publications up to December 2023 using keywords grouped under "athlete", "risk factor " and "sleep disorder." The screening process follow the 2020 PRISMA guidelines. The inclusion criteria included origical studies (1) involving athletic participants, regardless the their level, (2) investigating risk factors related to sleep disorders, and (3) including sleep disorders assessments. Results: A total of 26 studies were included and the risk factors were graded using the grade practice recommendations scale, ranging from level A to D. Then based on the workload-injury aetiology model, the risk factors were categorized into modifiable intrinsic risk factor included psychological stress (level A) and anxiety (level B), physical fatigue, depressive mood, poor training adaptation, abnormal menstrual cycle, BMI <18.5 kg/m2 (all level C). Additionally, non-modifiable intrinsic factors like female gender (level A), history of concussion (level B) and sleep apnea (level C). Along with extrinsic factors such as electronic devices use before bedtime or after light off, high morning training frequency, increased training load, and athletic level (all level B) were recognized. Furthermore, post-match day, sport discipline, skipping breakfast, alcohol and caffeine consumptions, competition schedules, travel distances, training duration, long-haul flights, social media use, academic pressure, and nighttime part-time job (all level C) were also identified. These classifications were then integrated to form a dynamic recursive model of sleep disorders tailored for athletes. Discussion: While most of the included articles were cross-sectional studies providing lower quality evidence, after classifying the levels of practice recommendations, we found that female gender and psychological stress are high-risk factors for sleep disorders in athletes. Contrary to the commen belief that extrinsic factors have a more significant impact on sleep, our study highlights that intrinsic risk factors also pose substantial risks for sleep disorders. Impact/Application to the field: Our findings underscore that a multitude of factors can adversely affect sleep quality. We recommend focusing on athletes who exhibit high-risk factors with higher recommended grades when monitoring sleep and implementing strategies to mitigate both modifiable intrinsic and extrinsic risk factors. The dynamic recursive model of sleep disorders in athletes offers evidence-based guidelines that sport medicine practitioners can use to evaluate athlete`s' condition and provide individualized interventions for those at high risk. Declaration: My co-authors and I acknowledge that we have no conflict of interest of relevance to the submission of this abstract.
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