Evidence map›Paper›PMID 42293645›Full record

ArticleFrontiers in public health2026

Sleep quality and injury risk in adolescent football players: an amplified effect for high-risk athletes revealed by quantile regression.

Nanhu Li, Zhengri Quan, Dan Pang, Donghui Jin

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Article in Frontiers in public health, 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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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Nanhu LiSchool of Physical Education, Kookmin University, Seoul, Republic of Korea.
Zhengri QuanSchool of Physical Education and Health, Changchun Normal University, Changchun, China.
Dan PangSchool of Sports Science, China Three George University, Yichang, China.
Donghui JinSchool of Physical Education, Kookmin University, Seoul, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 ( 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.

Indexed as

AthletesAthletic InjuriesFootballSleep QualityAdolescentChinaCross-Sectional StudiesHumansMaleRisk FactorsSleep Durationadolescentsathletic injurieseffect heterogeneityfootballprecision preventionquantile regressionsleep

Identifiers

PMID42293645
PMCPMC13253420

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