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Training, Prevention, and Rehabilitation/Section Articles

Sleep and Injury Risk

Huang, Kevin DO; Ihm, Joseph MD

Author Information
Current Sports Medicine Reports: June 2021 - Volume 20 - Issue 6 - p 286-290
doi: 10.1249/JSR.0000000000000849

Abstract

Introduction

There is an increasing body of evidence indicating that sleep plays a role in performance and recovery, as well as risk of injury in athletes. Although studies conflict on the effects of sleep, the literature overall suggests that deficient sleep may have multiple negative effects. Suboptimal sleep affects a variety of cognitive factors ranging from executive function, attention, learning, mental performance, and mental health. Suboptimal sleep also affects a variety of performance parameters, such as strength, speed, and endurance (1). Acute sleep disturbances impact athletic performance with greater effects seen on tasks requiring precision, with lesser effects seen in endurance (e.g., ultracycling) and anaerobic (e.g., weightlifting) activities. Sleep interventions among athletes have been shown to improve performance in precision tasks and also have been shown to improve strength, speed, cognitive performance, reaction time, and mental health (1). Sleep disorders are common in youth athletes, potentially because of sleep requirements for adolescents and the physical demands of and time commitment to sport (2,3). Sleep in the athlete is influenced by sport-specific factors, such as the volume of training, travel, and competition, and nonsport factors, such as sex and psychological stress (including anxiety) (3). Athletes have been found to have lower-quality sleep than their nonathlete peers (1,2), with an estimated 22% to 30% having highly disturbed sleep (3,4). Although there have been multiple investigations evaluating the wide-ranging effects of sleep on sports performance and overall well-being, the role that sleep plays in injury risk is unclear and evidence is conflicting. A recent 2020 article by Riederer (5) evaluated the impact of sleep on performance in youth athletes but did not focus on the relationship between sleep and injury risk. The primary aim of this article is to review the available evidence and examine the relationship between sleep and musculoskeletal injury risk. We also will provide recommendations on interventions to assess sleep and injury risk in the athletic population.

The Effects of Sleep Duration and Sleep Quality

There are multiple studies evaluating adolescent and adult athletes that associate decreased sleep duration with an increased risk of injury. While there is no clear optimal number of hours of sleep required to decrease risk of injury, multiple studies have shown similar findings. Several studies have found that individuals who reported ≤7 h of sleep per night were found to have increased rates of injury (6–11), with some showing up to 1.7 times greater likelihood of injury (1,7). Conversely, those who reported >8 h of sleep a night had their injury risk reduced by 61% (odds ratio, 0.39) as compared with those who had ≤8 h of sleep (9,12). A separate study suggests that increased injury risk is not seen until there is nightly sleep loss for several days. This study found increased injury rates in those who had suboptimal sleep for approximately 14 d and did not find the same association in those who had suboptimal sleep for up to 7 d. In this study, there also was increased injury risk in those with ≤7 h of reported sleep, consistent with prior studies (8).

These findings are consistent with the American Academy of Sleep Medicine and Sleep Research Society consensus statement recommending that adults (ages, 18 to 60 years) obtain ≥7 h of sleep on a regular basis (13) and further supported by a systematic review, concluding that a chronic lack of sleep is associated with greater risk of sports and musculoskeletal injuries in athletes. The effect of sleep on injury risk in adults was evaluated in a study of the military population, which found that soldiers obtaining ≤4 h of sleep as compared with those obtaining ≥8 h of sleep were 2.35 times more likely to experience a musculoskeletal injury (14). One prospective study evaluated 496 adolescent athletes (ages 15 to 19 years) across 16 sports for 52 wk. In a regression analysis assessing multiple parameters, it was found that increasing training load and intensity combined with decreased sleep volume resulted in a greater risk of injury (hazard ratio [HR], 2.25) (10). A real-life correlate would be when athletes return from the offseason to training camp, which is a period where injury incidence typically increases and may be due to increased frequency and intensity of workouts (15,16), with greater effects occurring earlier in training camp (17). This greater incidence of injury is not solely attributable to an increase in training load but occurs with concomitant sleep disturbances. These data suggest that it is important to maintain good sleep hygiene when increasing training loads across all sports, especially when transitioning from the offseason to training camp.

The majority of the discussed studies are limited by their reliance on self-reported outcome measures, which when related to recall of sleep lack reliability and/or validity and are subject to bias. Common questionnaires, such as the Pittsburgh Sleep Quality Index, Sleep Hygiene Index, and Epworth Sleepiness Scale, have not been validated in athletes (3). One case study of an elite 31-year-old soccer athlete used wrist actigraphy, a noninvasive objective way of monitoring activity and sleep, and found that sleep onset latency and sleep efficiency were altered on the night and in the week before an injury occurred (18). However, this has not been replicated in larger prospective studies or in other sports. Other prospective studies evaluating sleep and injury risk among adolescent dancers, collegiate D1 football players, soccer players, and amateur rugby players did not find a relationship between sleep and injury risk (19–22). The approximate age of the cohorts in these studies ranged from 13 to 25 years. Furthermore, while there are studies showing that sleep interventions can improve sports performance (23–25), to our knowledge, there are not any prospective studies evaluating sleep as an intervention for injury prevention.

Although chronic sleep loss appears to be associated with an increased risk of musculoskeletal injury, it is unknown if sleep loss predisposes an individual to specific types of injury. Many of the aforementioned studies do not describe injuries as acute or overuse and do not differentiate injuries by tissue type, such as tendinous, ligamentous, bony, or muscular. Other athletic injuries have been associated with suboptimal sleep. There is at least one study that found a link between decreased sleep and concussion risk. The authors found that moderate-to-severe insomnia (relative risk, 3.13) and excessive daytime sleepiness two or more times a month (relative risk, 2.856) were independently associated with increased concussion risk. In individuals who reported both moderate to severe insomnia and excessive daytime sleepiness two or more times per month the risk was exponentially greater, being 14.6 times higher (26). However, although concussion is not strictly a musculoskeletal injury as a majority of symptoms are of neurologic etiology, a systematic review found that concussed athletes are at two times greater risk of suffering musculoskeletal injury as compared with nonconcussed athletes (27). In addition, suboptimal sleep has been found to exacerbate anxiety and depression, which has separately been found to increase musculoskeletal injury risk (26). Clearly, injury risk is affected by multiple related factors, with sleep being just one of the parameters that is associated with an increased risk of a musculoskeletal injury.

Although there are data demonstrating the impact of sleep on one's general health, it is important to keep in mind that sleep may be a symptom of a broader issue and probably should not be viewed solely as an independent factor of injury risk. An example illustrating this complexity is the concept of overtraining syndrome, which is defined as the decline in athletic performance despite continued or increased training. Sleep disturbance has been reported as one of the presenting symptoms of overtraining (3). For an individual to optimize athletic performance and readiness for competition, both sufficient training stimulus and adequate recovery periods are necessary. Overtraining syndrome is thought to occur when the balance between training stress and adequate recovery is disrupted (3). Although sleep is thought to be an essential part of the recovery process because of its physiological and psychological restorative effects, sleep also can be disturbed when training volume is increased by greater than 30% (e.g., a 1-h run of eight repetitions of 400 m is converted into an 80-min run of 11 repetitions of 400 m) (28) and may even serve as an indicator of overtraining syndrome (28,29).

Sleep Disorders and Injury Risk

Although there are studies that suggest sleep loss as measured subjectively and objectively is associated with increased injury risk, it is unclear if specific sleep disorders are associated with injury risk. Although it would be reasonable to think that relatively prevalent sleep disorders, such as sleep apnea, insomnia, or even narcolepsy, would be associated with increased musculoskeletal injury risk, to our knowledge, this has not been investigated.

Interestingly, the prevalence of obstructive sleep apnea (OSA) may be higher in high-contact sports. An increased incidence in OSA has been specifically seen in professional football, professional hockey, and collegiate football players. These athletes require greater strength and power and, therefore, present with a larger body mass and neck circumference. However, it should be noted that the apnea in these athletes was typically mild (2). Currently, there are no studies evaluating the relationship between OSA and injury risk. Our opinion is given that chronic sleep insufficiency is associated with increased injury risk and has negative effects on mental health, general health, and cognitive performance, we recommend screening athletes who present with symptoms of chronic sleep insufficiency, such as daytime sleepiness, fatigue, and lack of energy, despite sleep hygiene education and measures. A clinically useful screening tool that can be used in an outpatient practice is the Neck, Obesity, Snoring, Age, Sex (NoSAS) score. The NoSAS score, which ranges from 0 to 17, measures neck circumference (3 points for >40 cm), BMI (3 points for BMI 25–30, 5 points for BMI >30), snoring (2 points for snorers), age (4 points if age >55 in years), and sex (2 points for being male). Studies have found that using a threshold score of ≥7 was 94.3% sensitive with a positive predictive value of 87.6% in determining if sleep-disordered breathing is present. Given the ease of administering this screening tool, we would recommend its use when concerned that a sleep disorder is present (30,31). Based on prior studies, we recommend referral to a sleep specialist for consideration of a polysomnography for those with a NoSAS ≥7. We realize that this tool has not been validated in adolescents or in athletic populations.

Association Between Sleep and Musculoskeletal Pain

Another area to explore when discussing musculoskeletal pain in the athlete is the association between suboptimal sleep and increased pain. Similar to the studies evaluating the risk of musculoskeletal injuries, many of the studies evaluated the relationship between sleep and pain with subjective self-reported measures and validated questionnaires without assessing athletic participation. A systematic review found that a decline in sleep quality and quantity is associated with two to three times increased risk of developing pain (32). Further studies have found that sleep deprivation has been shown to produce a hyperalgesic response in individuals (33,34) and that chronic sleep deprivation is associated with an increased risk of developing chronic pain. Longitudinal studies in both adults and children have found that suboptimal sleep more consistently predicts next-day pain as compared with pain predicting subsequent sleep loss (32–34). Although suboptimal sleep has been prospectively shown to be associated with greater pain, there is insufficient evidence to show a clear positive relationship between improvement in sleep and subsequent pain improvement. Improved sleep may be a predictor of chronic pain remission because there are studies showing those who reported multisite pain at baseline but not at follow-up after a sleep intervention (32,34). Furthermore, suboptimal sleep has a negative effect on mood and affect, which are known to have negative effects on pain (32,33). Considering these studies, it is reasonable to postulate that pain related to disease entities, such as chronic low back pain and tendinopathy, could be more prominent in those with impaired sleep. Given that musculoskeletal conditions such as these can present without acute tissue changes, pain from these conditions may be more likely in those who do not achieve optimal sleep.

What Is a Good Night's Sleep?

Sleep quality is a widely used concept but there is a lack of clear consensus on the definition. Various parameters such as sleep latency, nighttime awakenings, wake after sleep onset, and sleep efficiency are used to evaluate sleep quality, but these lack clear normative values across all age ranges. Sleep latency is defined as the length of time, in minutes, it takes to transition from wake to sleep, while sleep efficiency is defined as the ratio of time spent sleeping to total time in bed. It has been generally accepted that shorter sleep latencies, fewer nighttime awakenings, reduced time spent awake between sleep onset and sleep termination (i.e., wake after sleep onset), and higher sleep efficiency are indicators of better sleep quality (35). The National Sleep Foundation's consensus statement agreed that the following measures throughout all age groups indicated a good night's sleep: sleep latency ≤15 min, one or fewer awakenings per night, wake after sleep ≤20 min, and sleep efficiency ≥85%. The same panel also agreed that the following measures across all age groups indicated a poor night's sleep: sleep latency >60 min, four or more awakenings per night, wake after sleep ≥51 min, and sleep efficiency ≤64% (35). There is a lack of consensus on the importance of naps; however, it is thought that fewer naps per 24-h period indicate good sleep quality, and more naps indicate poor sleep quality (35). Recently, activity trackers, in the form of wrist actigraphy or a cellular phone application, are becoming more widely used. However, these technologies are continually evolving, and there are no studies validating their accuracy in determining sleep quality as compared with polysomnography. Clinicians need to understand these limitations when communicating with patients about the wealth of information that can be provided with these technologies.

General Health Considerations

As sleep is considered a part of one's general health, sleep quality may just be one marker of an individual's risk of pain and injury. As the American population continues to see a rise in childhood obesity and general health conditions (36), sleep may just be one more parameter that is affected. It is known that factors involved with metabolic syndrome increase the risk of tendinopathy and tendon tears (37–39) and low back pain (40). In a study by von Rosen et al. (10), which applied a biopsychosocial model to evaluating injury risk, an increase in competence-based self-esteem, defined as self-esteem based on performance and competition results, was associated with greater injury risk as compared with an athlete with a lower score. These individuals are suspected to minimize recovery time, not wear protective gear, and therefore engage in behaviors that increase injury risk throughout the season. As we consider the role of sleep in assessing the athlete's risk of injury, considering the general health of the athlete with regard to diet, general activity and exercise, body fat percentage, metabolic parameters, and other intrinsic and extrinsic risk factors is important. This is supported by the Von Rosen et al. study in which the authors noted that no single risk factor provides an adequate etiological explanation of injury and evaluated this by combining risk factors into a Risk Index. The covariates included in the Risk Index were sex, body mass index, history of severe injury, Nutrition Index (score ≤ 4), sleep ≤8 h during weekdays, competence-based self-esteem, self-perceived stress, preevent variables (e.g., increased training intensity, increased training load, increased days of competitions), and decreased sleep volume. The Risk Index was defined by having one, two, or three risk factors with increased injury risk associated with a greater number of risk factors (one risk factor: HR, 1.18; P = 0.038; two risk factors: HR, 1.35; P = 0.092; three risk factors: HR, 2.37; P < 0.001).

Conclusions and Final Recommendations

In summary, there is evidence of a relationship between chronic suboptimal sleep patterns and the risk of musculoskeletal pain and sports injury. The amount of sleep that has been consistently found to be associated with increased risk of injury is ≤7 h of sleep on a chronic basis, which increases injury risk by 1.7 times. Furthermore, the literature does not consistently associate a single night of suboptimal sleep or more acute sleep loss with increased injury risk, as there appears to be a lag time of approximately 14 d of sleep loss that needs to occur before injury risk increases. Overall, the studies in the literature are limited by subjective outcome measures where recall of one's sleep can be limited. To further elucidate these relationships, studies performed with activity trackers and wrist actigraphy may provide additional information, although this technology is rapidly evolving and has not been validated with polysomnography in rigorous studies.

While sleep quality is important to consider when assessing an athlete's injury risk, it should be considered as only one of many factors that can impact an athlete's overall health and well-being. Evaluating an athlete's injury risk will require reviewing multiple aspects of what the athlete is doing to achieve optimal health and performance. While currently it is unclear if targeting sleep with specific interventions decreases the risk of a musculoskeletal injury, it is important to educate athletes on what constitutes optimal sleep due to its association with injury risk since optimal sleep has wide-ranging positive effects on cognitive function, athletic performance, and general health. With these ideas in mind, the following are additional specific parameters that suggest the presence of suboptimal sleep: sleep latency >60 min, four or more awakenings per night, wake after sleep ≥51 min, and sleep efficiency ≤64%. Also, consider the factors involved in the Risk Index as described by Von Rosen et al: sex, body mass index, history of severe injury, Nutrition Index (score ≤ 4), sleep ≤8 h during weekdays, competence-based self-esteem, self-perceived stress, preevent variables (e.g., increased training intensity, increased training load, increased days of competitions), and decreased sleep volume. Those who have more than one of these factors should be thought to be at increased risk for injury, and targeting these specific factors should be considered as an intervention for injury prevention. For the athletes suspected to have sleep disorders not improved with sleep hygiene education, we recommend screening with the NoSAS score and referring those with a score >7 to a sleep specialist for consideration of a polysomnography. Given the complex multifactorial nature of injury risk, those with sleep disturbances in combination with other psychological or general health issues should be treated from a biopsychosocial perspective, as addressing a singular issue will likely be of less benefit in injury prevention (Table 1, https://links.lww.com/CSMR/A116, Table 2, https://links.lww.com/CSMR/A117, Table 3, https://links.lww.com/CSMR/A118).

The authors declare no conflict of interest and do not have any financial disclosures.

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