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Enregistrement W2928744918 · doi:10.1177/2325967119s00132

CHRONIC LACK OF SLEEP IS ASSOCIATED WITH INCREASED SPORTS INJURY IN ADOLESCENTS: A SYSTEMATIC REVIEW AND META-ANALYSIS

2019· review· en· W2928744918 sur OpenAlexaboutno aff
Burke Gao, Shashank Dwivedi, Matthew D. Milewski, Aristides I. Cruz

Notice bibliographique

RevueOrthopaedic Journal of Sports Medicine · 2019
Typereview
Langueen
DomaineMedicine
ThématiqueInjury Epidemiology and Prevention
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineMeta-analysisPhysical therapyInjury preventionSleep (system call)Sports medicinePoison controlInternal medicineEmergency medicine

Résumé

récupéré en direct d'OpenAlex

Background: Although sleep has been identified as an important modifiable risk factor for sports injury, the effect of decreased sleep on sports injuries in adolescents is poorly studied. Purpose: To systematically review published literature to examine if a lack of sleep is associated with sports injuries in adolescents and to delineate the effects of chronic versus acute lack of sleep. Methods: PubMed and EMBASE databases were systematically searched for studies reporting statistics regarding the relationship between sleep and sports injury in adolescents aged <19 years published between 1/1/1997 and 12/21/2017. From included studies, the following information was extracted: bibliographic and demographic information, reported outcomes related to injury and sleep, and definitions of injury and decreased sleep. Additionally, a NOS (Newcastle-Ottawa Scale) assessment and an evaluation of the OCEM (Oxford Center for Evidence-Based Medicine) level of evidence for each study was conducted to assess each study’s individual risk of bias, and the risk of bias across all studies. Results: Of 907 identified articles, 7 met inclusion criteria. Five studies reported that adolescents who chronically slept poorly were at a significantly increased likelihood of experiencing a sports or musculoskeletal injury. Two studies reported on acute sleep behaviors. One reported a significant positive correlation between acutely poor sleep and injury, while the other study reported no significant correlation. In our random effects model, adolescents who chronically slept poorly were more likely to be injured than those who slept well (OR 1.58, 95% CI 1.05 to 2.37, p = 0.03). OCEM criteria assessment showed that all but one study (a case-series) were of 2b level of evidence—which is the highest level of evidence possible for studies which were not randomized control trials or systematic reviews. NOS assessment was conducted for all six cohort studies to investigate each study’s individual risk of bias. Five out of six of these studies received between 4 to 6 stars, categorizing them as having a moderate risk of bias. One study received 7 stars, categorizing it as having a low risk of bias. NOS assessment revealed that the most consistent source of bias was in ascertainment of exposure: all studies relied on self-reported data regarding sleep hours rather than a medical or lab record of sleep hours. Conclusions: Chronic lack of sleep in adolescents is associated with greater risk of sports and musculoskeletal injuries. Current evidence cannot yet definitively determine the effect of acute lack of sleep on injury rates. Our results thus suggest that adolescents who either chronically sleep less than 8 hours per night, or have frequent night time awakenings, are more likely to experience sports or musculoskeletal injuries. [Figure: see text][Figure: see text][Table: see text][Table: see text][Table: see text] References used in tables and full manuscript Barber Foss KD, Myer GD, Hewett TE. Epidemiology of basketball, soccer, and volleyball injuries in middle-school female athletes. Phys Sportsmed. 2014;42(2):146-153. Adirim TA, Cheng TL. Overview of injuries in the young athlete. Sports Med. 2003;33(1):75-81. Valovich McLeod TC, Decoster LC, Loud KJ, et al. National Athletic Trainers’ Association position statement: prevention of pediatric overuse injuries. J Athl Train. 2011;46(2):206-220. Milewski MD, Skaggs DL, Bishop GA, et al. Chronic lack of sleep is associated with increased sports injuries in adolescent athletes. J Pediatr Orthop. 2014;34(2):129-133. Wheaton AG, Olsen EO, Miller GF, Croft JB. Sleep Duration and Injury-Related Risk Behaviors Among High School Students--United States, 2007-2013. MMWR Morb Mortal Wkly Rep. 2016;65(13):337-341. Paruthi S, Brooks LJ, D’Ambrosio C, et al. Consensus Statement of the American Academy of Sleep Medicine on the Recommended Amount of Sleep for Healthy Children: Methodology and Discussion. Journal of clinical sleep medicine: JCSM: official publication of the American Academy of Sleep Medicine. 2016;12(11):1549-1561. Watson NF, Badr MS, Belenky G, et al. Joint Consensus Statement of the American Academy of Sleep Medicine and Sleep Research Society on the Recommended Amount of Sleep for a Healthy Adult: Methodology and Discussion. Sleep. 2015;38(8):1161-1183. Juliff LE, Halson SL, Hebert JJ, Forsyth PL, Peiffer JJ. Longer Sleep Durations Are Positively Associated With Finishing Place During a National Multiday Netball Competition. J Strength Cond Res. 2018;32(1):189-194. Beedie CJ, Terry PC, Lane AM. The profile of mood states and athletic performance: Two meta- analyses. Journal of Applied Sport Psychology. 2000;12(1):49-68. Panic N, Leoncini E, de Belvis G, Ricciardi W, Boccia S. Evaluation of the endorsement of the preferred reporting items for systematic reviews and meta-analysis (PRISMA) statement on the quality of published systematic review and meta-analyses. PLoS One. 2013;8(12): e83138. Liberati A, Altman DG, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS medicine. 2009;6(7): e1000100. Watson A, Brickson S, Brooks A, Dunn W. Subjective well-being and training load predict in- season injury and illness risk in female youth soccer players. Br J Sports Med. 2016. Alricsson M, Domalewski D, Romild U, Asplund R. Physical activity, health, body mass index, sleeping habits and body complaints in Australian senior high school students. Int J Adolesc Med Health. 2008;20(4):501-512. Wells G, Shea B, O’Connell D, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp . Luke A, Lazaro RM, Bergeron MF, et al. Sports-related injuries in youth athletes: is overscheduling a risk factor? Clin J Sport Med. 2011;21(4):307-314. University of Oxford Center for Evidence-Based Medicine. Oxford Centre for Evidence-based Medicine – Levels of Evidence. 2009; https://www.cebm.net/2009/06/oxford-centre-evidence-based-medicine-levels-evidence-march-2009/ . von Rosen P, Frohm A, Kottorp A, Friden C, Heijne A. Too little sleep and an unhealthy diet could increase the risk of sustaining a new injury in adolescent elite athletes. Scand J Med Sci Sports. 2017;27(11):1364-1371. von Rosen P, Frohm A, Kottorp A, Friden C, Heijne A. Multiple factors explain injury risk in adolescent elite athletes: Applying a biopsychosocial perspective. Scand J Med Sci Sports. 2017;27(12):2059-2069. Picavet HS, Berentzen N, Scheuer N, et al. Musculoskeletal complaints while growing up from age 11 to age 14: the PIAMA birth cohort study. Pain. 2016;157(12):2826-2833. Kim SY, Sim S, Kim SG, Choi HG. Sleep Deprivation Is Associated with Bicycle Accidents and Slip and Fall Injuries in Korean Adolescents. PLoS One. 2015;10(8): e0135753. Stare J, Maucort-Boulch D. Odds Ratio, Hazard Ratio and Relative Risk. Metodoloski Zvezki. 2016;13(1):59-67. Watson AM. Sleep and Athletic Performance. Curr Sports Med Rep. 2017;16(6):413-418. Stracciolini A, Stein CJ, Kinney S, McCrystal T, Pepin MJ, Meehan Iii WP. Associations Between Sedentary Behaviors, Sleep Patterns, and BMI in Young Dancers Attending a Summer Intensive Dance Training Program. J Dance Med Sci. 2017;21(3):102-108. Stracciolini A, Shore BJ, Pepin MJ, Eisenberg K, Meehan WP, 3 rd. Television or unrestricted, unmonitored internet access in the bedroom and body mass index in youth athletes. Acta Paediatr. 2017;106(8):1331-1335. Snyder Valier AR, Welch Bacon CE, Bay RC, Molzen E, Lam KC, Valovich McLeod TC. Reference Values for the Pediatric Quality of Life Inventory and the Multidimensional Fatigue Scale in Adolescent Athletes by Sport and Sex. Am J Sports Med. 2017;45(12):2723-2729. Simpson NS, Gibbs EL, Matheson GO. Optimizing sleep to maximize performance: implications and recommendations for elite athletes. Scand J Med Sci Sports. 2017;27(3):266-274. Liiv H, Jurimae T, Klonova A, Cicchella A. Performance and recovery: stress profiles in professional ballroom dancers. Med Probl Perform Art. 2013;28(2):65-69. Van Der Werf YD, Van Der Helm E, Schoonheim MM, Ridderikhoff A, Van Someren EJ. Learning by observation requires an early sleep window. Proc Natl Acad Sci U S A. 2009;106(45):18926- 18930. Lee AJ, Lin WH. Association between sleep quality and physical fitness in female young adults. J Sports Med Phys Fitness. 2007;47(4):462-467. Mejri MA, Yousfi N, Hammouda O, et al. One night of partial sleep deprivation increased biomarkers of muscle and cardiac injuries during acute intermittent exercise. J Sports Med Phys Fitness. 2017;57(5):643-651. Mejri MA, Yousfi N, Mhenni T, et al. Does one night of partial sleep deprivation affect the evening performance during intermittent exercise in Taekwondo players? Journal of exercise rehabilitation. 2016;12(1):47-53. Hirshkowitz M, Whiton K, Albert SM, et al. National Sleep Foundation’s updated sleep duration recommendations: final report. Sleep health. 2015;1(4):233-243. Dennis J, Dawson B, Heasman J, Rogalski B, Robey E. Sleep pattern

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,013
score de la tête « metaresearch » (Gemma)0,002
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Méta-épidémiologie (sens large), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,458
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0130,002
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0250,003
Bibliométrie0,0020,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,062
Tête enseignante GPT0,369
Écart entre enseignants0,307 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations20
Publié2019
Routes d'admission1
Résumé présentoui

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