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Assessment of sleep disturbances with the athlete sleep screening questionnaire in Chinese athletes

This study investigated the factors that are associated with sleep disturbances among Chinese athletes. Sleep quality and associated factors were assessed by the Athlete Sleep Screening Questionnaire (ASSQ, n ​= ​394, aged 18–32 years, 47.6% female). Sleep difficulty score (SDS) and level of sleep p...

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Detalles Bibliográficos
Autores principales: Zhang, Boyi, Bender, Amy, Tan, Xiao, Wang, Xiuqiang, Le, Shenglong, Cheng, Sulin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chengdu Sport University 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9219323/
https://www.ncbi.nlm.nih.gov/pubmed/35782277
http://dx.doi.org/10.1016/j.smhs.2022.02.001
Descripción
Sumario:This study investigated the factors that are associated with sleep disturbances among Chinese athletes. Sleep quality and associated factors were assessed by the Athlete Sleep Screening Questionnaire (ASSQ, n ​= ​394, aged 18–32 years, 47.6% female). Sleep difficulty score (SDS) and level of sleep problem (none, mild, moderate, or severe) were used to classify participants' sleep quality. Categorical variables were analyzed by Chi-square or fisher's exact tests. An ordinal logistic regression analysis was used to explore factors with poor sleep (SDS ≥8). Approximately 14.2% of participants had moderate to severe sleep problem (SDS ≥8). Fifty-nine percent of the athletes reported sleep disturbance during travel, while 43.3% experienced daytime dysfunction when travelling for competition. No significant difference was found in the SDS category between gender, sports level and events. Athletes with evening chronotype were more likely to report worse sleep than athletes with morning and intermediate chronotype (OR, 2.25; 95%CI, 1.44–3.52; p ​< ​0.001). For each additional year of age, there was an increase of odds ratio for poor sleep quality (OR, 1.15; 95%CI, 1.04–1.26; p ​= ​0.004), while each additional year of training reduced the odds ratio (OR, 0.95; 95%CI, 0.91–0.99; p ​= ​0.044). To improve sleep health in athletes, chronotype, travel-related issues, age and years of training should be taken into consideration.