Sleep quality and injury risk in adolescent football players
An amplified effect for high-risk athletes revealed by quantile regression
Bibliographic Data
| ID | 22080893 |
|---|---|
| Authors | Nanhu Li (Kookmin University), Zhengri Quan (Changchun Normal University), Dan Pang (China Three Gorges University), Donghui Jin (0000-0003-3391-3124, Kookmin University, corresponding author) |
| Year | 2026 |
| Volume | 14 |
| Pages | 1799229-1799229 |
| Publication date | 2026-05-28 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2026.1799229 |
| PMID | 42293645 |
| OpenAlex | W7162665543 |
| Language | EN |
| References cited | 45 |
Background Sleep quality is a key regulatory factor in sports injury, but it is not clear whether its association with injury risk is homogeneous or varies among athletes with different baseline risks. This study explored the heterogeneous and non-linear associations between sleep quality and risk of impairment. Methods We conducted a cross-sectional analysis of 478 young football players from 12 Chinese clubs. Sample size was determined based on the need to provide stable estimates across multiple conditional quantiles, exceeding the general rule of thumb for complex multivariate models. Sleep quality was assessed using the Pittsburgh Sleep Quality Index while recording its subcomponents, such as sleep duration. Injuries, including time lost and severity, were recorded during the past season. Using quantile regression, we analyzed the association between total PSQI score and the number of impairments across the conditional distribution ( τ = 0.25, 0.50, 0.75, 0.90) after controlling for team-level fixed effects and covariates. Results We observed a strong positive correlation between the PSQI score and the incidence of injury. Quantile regression revealed significant heterogeneity: this adverse association was greatly amplified at higher quantiles of injury risk. The PSQI coefficient increased from 0.07 (95% confidence interval: 0.01, 0.13) in the 25th quantile to 0.33 (95% confidence interval: 0.23, 0.43) in the 90th quantile, indicating that the strength of the association was enhanced about fivefold for high-risk athletes. Separate analysis for severe injuries corroborated this finding. A nonlinear J-type dose–response relationship was also identified, with the risk accelerating when the PSQI score exceeded 6. Conclusion The association between poor sleep and injury risk was not uniform but showed a clear gradient, with the most significant adverse associations concentrated in high-risk athletes. This quantile-dependent effect highlights the potential of sleep intervention as a precision strategy. While sleep quality remains important for all adolescent football players, targeted sleep health promotion for high-risk individuals can maximize the injury prevention benefits of adolescent athletes, but prospective studies are still needed to establish causality
Athletes · Confidence interval · Football · Pittsburgh Sleep Quality Index · Quantile · Quantile regression · Physical Activity and Health · Sleep and related disorders · Sports Performance and Training
| Citation velocity | historical |
|---|---|
| Highly cited | No |