Energy Availability, Mental Health, and Sleep Patterns of Athletic Trainers
Engaging in exercise and appropriate nutritional intake improves mental health by reducing anxiety, depression, and sleep disturbances. However, few researchers have examined energy availability (EA), mental health, and sleep patterns in athletic trainers (ATs). To examine ATs’ EA, mental health risk (ie, depression, anxiety), and sleep disturbances by sex (male, female), job status (part time [PT AT], full time [FT AT]), and occupational setting (college or university, high school, or nontraditional). Cross-sectional study. Free living in occupational settings. A total of 47 ATs (male PT ATs = 12, male FT ATs = 12; female PT ATs = 11, female FT ATs = 12) in the southeastern United States. Anthropometric measurements consisted of age, height, weight, and body composition. Energy availability was measured through energy intake and exercise energy expenditure. We used surveys to assess the depression risk, anxiety (state or trait) risk, and sleep quality. Thirty-nine ATs engaged in exercise, and 8 did not exercise. Overall, 61.5% (n = 24/39) reported low EA (LEA); 14.9% (n = 7/47) displayed a risk for depression; 25.5% (n = 12/47) indicated a high risk for state anxiety; 25.5% (n = 12/47) were at high risk for trait anxiety, and 89.4% (n = 42/47) described sleep disturbances. No differences were found by sex and job status for LEA, depression risk, state or trait anxiety, or sleep disturbances. Those ATs not engaged in exercise had a greater risk for depression (risk ratio [RR] = 1.950), state anxiety (RR = 2.438), trait anxiety (RR = 1.625), and sleep disturbances (RR = 1.147), whereas ATs with LEA had an RR of 0.156 for depression, 0.375 for state anxiety, 0.500 for trait anxiety, and 1.146 for sleep disturbances. Although most ATs engaged in exercise, their dietary intake was inadequate, they were at increased risk for depression and anxiety, and they experienced sleep disturbances. Those who did not exercise were at an increased risk for depression and anxiety. Energy availability, mental health, and sleep affect overall quality of life and can affect ATs’ ability to provide optimal health care.Context
Objective
Design
Setting
Patients or Other Participants
Main Outcome Measure(s)
Results
Conclusions
Health care professionals may not be meeting health-related recommendations (eg, for nutritional intake, exercise, and sleep) and may be at risk for physical and mental health conditions. For example, athletic trainers (ATs), who are often advocates for health and wellness, have been shown to have inadequate nutritional intake,1 high levels of burnout,2 and elevated levels of role strain.3 Athletic trainers share similar job duties, irregular hours, and high role strain with other health care professionals (eg, nurses, physicians).4,5 Researchers have also indicated that nurses and physicians had a higher prevalence of depression (32.4% and 20.9%–43.2%, respectively) than the general population (16.6%).4–6 To date, the prevalence of and contributing factors to depression and anxiety in ATs have not been examined. Furthermore, physicians with suboptimal mental and physical health provided lower-quality care with less patient satisfaction.7 Therefore, exploring the health and well-being of ATs is warranted to better understand the potential implications for patient care and the profession’s workforce.
Lifestyle factors such as diet, exercise, and stress may influence the risk for psychopathology, including depression and anxiety.8 Previous investigators1 determined ATs were not meeting dietary recommendations, and 80% displayed negative energy balance (EB; a measure of energy intake [EI] minus total daily energy expended [TDEE]). Failure to meet dietary needs places the individual in a state of negative EB or low energy availability (LEA).9Energy availability (EA) is the amount of energy available to perform the body’s physiological functions after exercise has been accounted for.9 Low EA can occur when an individual reduces EI but maintains the same exercise habits or when exercise is increased but EI is not. Adequate EI and lifestyle behaviors, such as proper nutrition, adequate sleep, less alcohol consumption, and stress management, may prevent negative EB and LEA. However, if left untreated, individuals in negative EB or with LEA can experience severe injury and illness9,10; for instance, LEA can occur with or without an eating disorder (ED) and increased risk for pathogenic behaviors (eg, dieting, excessive exercise, use of diuretics). Torres-McGehee et al1 revealed that 84.8% of ATs presented with an ED risk, and 86.9% engaged in ≥1 pathogenic eating behavior.1 Athletic trainers also showed psychological characteristics associated with EDs (ie, interpersonal insecurity, interpersonal alienation, emotional dysregulation).1 Psychological characteristics such as interpersonal regulation, interpersonal alienation, and emotional dysregulation affect both depression and anxiety11–14 and may result in increasing alcohol consumption. Approximately 91.3% of ATs self-reported consumption of alcohol, with the majority (37.2%) consuming alcohol at least 1 d/wk, 14% at least 4 d/wk, and 4.7% more than 4 d/wk.1 Depression and anxiety are well-known comorbid conditions with EDs.15 Given previous research connecting EDs and EB,1 a further examination of EA in this population is needed.
Another lifestyle factor is physical activity (PA) and exercise, which may prevent chronic diseases and protect against depression and anxiety.16 More specifically, authors17–19 noted that exercise resulted in improvements in mood state and self-esteem and lower stress, depression, and anxiety levels. However, exercise can also place the person in an LEA state if nutritional intake is inadequate, as demonstrated by Torres-McGehee et al1 in a study on ATs. Yet research on PA and exercise among ATs is limited. In an exploration of ATs and burnout, ATs increased PA in their daily lives to improve their health and wellness, including minimizing symptoms of depression and anxiety.20 The concept of burnout is important because, similar to EDs, depression, and anxiety, burnout may be the cause or result of depression and anxiety21; nonetheless, it is important to note that burnout, depression, and anxiety are not mutually exclusive conditions.2,22 To date, exercise and mental health (ie, depression, anxiety) in ATs have not been addressed. The authors1 of only 1 study provided general information on exercise, stating that 84.8% of ATs engaged in exercise ≥1 time per week. They assessed the ED risk and EB but did not specifically link these to LEA.
Depression and anxiety may also result directly from role strain before the onset of burnout. Role strain, or an individual’s inability to complete the requirements of a job, is regarded as 1 cause of burnout.2 Burnout, along with stressors such as role strain and poor sleep quality, may also cause or result from depression and anxiety.2Burnout consists of emotional exhaustion, depersonalization of patients, decreased perceptions of personal accomplishment, and unresolvable stress.2 Many of the same aspects of burnout are causes of depression and anxiety.2,5,22 Emotional exhaustion is recognized as a depression symptom,15,21 and anxiety contributes to burnout in health care.22 Role strain can be subdivided into role conflict, overload, incongruity, incompetence, and ambiguity.2Role overload occurs when job requirements exceed the available time and the individual’s EA,2 suggesting that role strain may affect ATs’ ability to provide self-care, including eating, exercising, and sleeping, all of which are important for holistic health and wellness. Although many factors affect a person’s sleep quality, poor sleep is associated with anxiety, depression,23 and decreased quality of life.24 In a cohort of medical students, inadequate sleep and not exercising independently contributed to burnout onset and depression.25
Health care professionals are not meeting personal health-related requirements, resulting in negative consequences to their physical and mental health and decreasing the quality of care they provide to patients. Research is warranted specifically on depression and anxiety in ATs, along with contributing factors (eg, sleep, nutrition). Our purpose was to examine ATs’ EA, depression and anxiety risk, and sleep quality. Secondly, we sought to determine whether exercising or having LEA increased ATs’ risk for mental health and sleep disturbance. We hypothesized that individuals who exercised would display a lower risk for depression and anxiety and exhibit a lower prevalence of sleep disturbances. Additionally, we proposed that those who did not exercise and those with LEA would have increased risks for depression and anxiety and poor sleep quality.
METHODS
Study Procedures
The study was part of a larger study conducted by our research team.1 It is important to note that data were collected before the start of the 2020 COVID-19 pandemic, and the initial findings were published in 2021,1 with a secondary analysis occurring in 2022. We began the initial study by sending out an inquiry-for-participation email to all ATs in the surrounding area of the southeastern US region. This email included a short survey to determine if interested volunteers met the inclusion criteria. Then individual meetings were scheduled to review the study details and obtain signed consent. After consent was obtained, participants underwent anthropometric and resting metabolic rate (RMR) measurements, scheduled a dual-energy x-ray absorptiometry (DXA) scan, and completed ED surveys along with the Center for Epidemiological Studies Depression Scale Revised (CESD-R), Spielberger State-Trait Anxiety Inventory (STAI), and Pittsburgh Sleep Quality Index (PSQI) surveys. Participants were given a written and oral overview of the weekly procedures, including detailed instructions for the food and exercise logs and armband. They began self-reporting 7 consecutive days of foods, fluids, and planned and intentional exercise in the online log at the end of the information session. We emphasized that participants should continue their normal food and fluid consumption, PA, and exercise during data collection. After the 7 days, participants emailed food and exercise logs to us and returned the armband. The Instruments and Protocols section describes only the instruments and protocols used for the secondary analysis.
Participants
A convenience sample of ATs (males = 23, age = 29.8 ± 8.5 years; females = 24, age = 28.9 ± 7.9 years) from the southeastern United States were recruited from local colleges or universities (CUs), high schools (HSs), and nontraditional (NT) settings (eg, clinics, recreation centers, outreach programs). The inclusion criterion was being an AT certified by the Board of Certification. The exclusion criterion was working primarily under a different credential (eg, an individual working under both certified AT and PT credentials). Institutional review board approval was acquired, and all participants provided consent before data collection.
Instruments and Protocols
Demographic and Anthropometric Measurements
Basic demographic and anthropometric information consisted of sex (male or female), job status (part time [PT AT] or full time [FT AT]), job setting (CU, HS, or NT), and self-reported height and weight.1 In addition, we measured participants’ height, weight, and body composition in compliance with American College of Sports Medicine standards.26 Height was measured using a stadiometer (model ShorrBoard; Shorr Productions). Weight was measured to the nearest 0.1 kg (model SC331S Body Composition Scale; Tanita Corp of America, Inc). Body fat percentage was determined using a densitometer (model Lunar Prodigy; GE HealthCare), which provided fat-free mass (FFM).
Resting Metabolic Rate
Resting metabolic rate was measured using indirect calorimetry (model MedGem; Microlife Medical Home Solutions). The MedGem is clinically validated for assessing RMR and has an interclass reliability range of 0.91 to 0.97 (mean = 0.94).
Energy Availability
Energy availability is the amount of dietary intake remaining after exercise energy expenditure (EEE), expressed as kcal/kg of lean body mass (EA = [dietary intake − EEE]/kg lean body mass). Optimal EA is ≥45 kcal/kg of FFM9; LEA for females and males was ≤30 kcal/kg FFM. Specific values of LEA in males have been minimally investigated; some suggest the LEA threshold in males is lower, but not enough evidence fully supports this claim.
Energy Intake
We assessed and analyzed total kilocalories based on participants’ online daily food logs (FoodProdigy, version 8.0; ESHA Research) for 7 consecutive days to determine EI. Portion size descriptions and examples were provided to all participants to aid food log accuracy.
Total Daily Energy Expenditure and Exercise Energy Expenditure
Total daily energy expenditure is the amount of energy required for essential life processes to occur—the energy expended to digest, absorb, and convert food and the energy expended during PA and recovery.1 A SenseWear Armband (BodyMedia, Inc) with an accelerometer continuously monitored TDEE and EEE. The participant’s sex, age, height, and weight were programmed to the armband. Participants were required to wear the armband approximately 23 h/d for 7 consecutive days. The SenseWear Armband is valid for assessing TDEE in free-living conditions for adults with a reliability of 0.81. Individuals who were unable to wear the armband self-reported exercise and PA using FoodProdigy. They recorded exercise duration, mode, and intensity, and we used the compendium of PA to determine the appropriate metabolic equivalent for the exercise performed. The EEE was estimated using the following equation: EEE = duration (min) × 3.5 × weight (kg)/200.
Center for Epidemiological Studies Depression Scale Revised
The CESD-R is a self-reported measure of depressive symptoms and contains 20 questions.27 The instrument consists of statements that may reflect a person’s feelings throughout the week. The CESD-R is composed of 9 subscales: sadness (dysphoria), loss of interest (anhedonia), appetite, sleep, thinking or concentration, guilt (worthlessness), tired (fatigue), movement (agitation), and suicidal ideation. Participants selected how often during the past week they felt or behaved on a scale of 1 = rarely or none of the time to 4 = most or all the time. Scores > 16 indicate an individual is at risk for depression. Internal consistency ranges from r = 0.85 to 0.90, and the reliability for our study was r = 0.895.
Spielberger State-Trait Anxiety Inventory
The STAI is a self-reported tool that assesses state and trait anxiety.28 The STAI differentiates between the temporary condition of state anxiety and the more general and longstanding quality of trait anxiety. The STAI consists of 20 statements each related to state anxiety and trait anxiety. State anxiety is assessed by examining how individuals feel “right now at this moment” on a Likert scale ranging from 1 = not at all to 4 = very much so. Trait anxiety is assessed by how individuals “generally feel” on a scale of 1 = almost never to 4 = almost always.28 To score the STAI, weighted scores were coded and added for each set of 20 items (state and trait), with scores ranging from 20 to 80.28 We used previous STAI normative data to compare our participant results. For example, normative STAI values were provided for males and females, working adults, students, and military recruits (eg, state-trait anxiety for a male working adult was 35.72 ± 10.40).28 Therefore, a male working adult whose score exceeded the upper SD was considered at risk. All scores were individualized by sex and working adult (FT AT) or student (PT AT) status. The STAI is the most widely used and validated anxiety questionnaire for adults,28 with internal consistency coefficients ranging from 0.86 to 0.95 and the test-retest reliability ranging from 0.65 to 0.75.28 The reliability for the STAI in this study was r = 0.948.
Pittsburgh Sleep Quality Index
The PSQI is a sensitive measure for detecting sleep disturbances and identifying insomnia in adults.29 It differentiates poor from good sleep by measuring 7 areas: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction over the last month.29 Answers are scored based on a Likert scale from 0 to 3, where 3 reflects the negative extreme. A global sum of ≥5 indicates a poor sleeper. The PSQI has an internal consistency and reliability of 0.83.29 The reliability for the PSQI in this study was r = 0.79.
Data Analysis
For all analyses, we applied SPSS (version 28; IBM Corp) with a priori α = .05. To calculate power, we used G*Power software (version 3.1.9.4; Franz Faul, Universität Kiel). With α = .05 and a large effect size (0.9) for the χ2 analysis of categorical variables, the power calculation indicated that 21 males and 21 females (42 participants total) were needed for an estimated power of 0.9. Basic descriptive statistics were calculated to examine demographic information (eg, height, weight, job status). Two-way analysis of variance identified differences between sexes (male or female) by job status (PT AT or FT AT) and job setting (CU, HS, or NT) with respect to all anthropometric measurements and energy needs (RMR, EA, EI, TDEE, and EEE). Frequencies and proportions with 95% CIs were computed for categorical variables along with means and SDs for continuous variables. To determine the proportion of participants classified as at risk for EA, depression, state anxiety, trait anxiety, and poor sleep, we performed χ2 analyses. Relative risks (RRs) were calculated to determine if those with no exercise and LEA displayed risks for depression, state anxiety, trait anxiety, and sleep disturbances.
RESULTS
We achieved appropriate statistical power (n = 47) and had almost equal distribution between males and females and between PT ATs and FT ATs. However, power was insufficient to examine both sex and job status (male PT ATs = 12, male FT ATs = 12; female PT ATs = 11, female FT ATs = 12) and job setting (CU = 16, HS = 20, NT = 11); therefore, our findings cannot be generalized beyond this study. All physical and self-reported demographic and anthropometric measurements are shown in Table 1.

Energy Needs
The ATs’ energy needs are presented in Table 2. Eight ATs reported they did not engage in planned and intentional exercise; thus, we could not calculate EA for those participants. Overall, 61.5% (n = 24/39) of ATs indicated LEA. No differences were observed between EA and sex–job status and sex–job setting. Low EA was identified in both sexes (male: 68.4% [13/19]. females: 55% [11/20]), job status (PT ATs = 65% [13/20], FT ATs = 57.9% [11/19]), and across all settings (CU = 46.2% [6/13], HS = 68.8% [11/16], and NT = 70.0% [7/10]). Differences were noted between sex–job status and sex–job setting for RMR (F1,45 = 17.162, P = .001), EI (F1,45 = 13.032, P = .001), TDEE (F1,45 = 42.514, P < .001), and EEE (F1,38 = 5.353, P = .026). No differences were seen within job status or job setting for EA.

Mental Health and Sleep
All mental health and sleep data are provided in Table 3. The overall prevalence of ATs at risk for depression was 14.9% (n = 7), 16.7% (n = 4) of males and 13.0% (n = 3) of females. No differences were evident for the depression risk by sex and job status. The overall prevalence of high state anxiety was 25.5% (n = 12), 25% of males (n = 6) and 26.1% of females (n = 6). Similarly, the overall prevalence of high trait anxiety was 25.5% (n = 12), 25% of males (n = 6) and 26.1% of females (n = 6). The overall prevalence of sleep disturbances was 89.4% (n = 42), 91.7% of males (n = 22) and 87% of females (n = 20). No differences were demonstrated for sleep and sex and job status.

Exercise and Mental Health
Of the 39 ATs who engaged in exercise, 12.8% (n = 5) were at risk for depression compared with 25.0% (n = 2) of nonexercising ATs. The RR of depression if ATs did not exercise was 1.950 (95% CI = 0.456, 8.336). Of those who exercised, 20.5% (n = 8) were at risk for state anxiety compared with 50.0% (n = 4) of nonexercising ATs (RR = 2.438, 95% CI = 0.963, 6.168). Of those who exercised, 23.1% (n = 9) were at risk for trait anxiety compared with 37.5% (n = 3) of nonexercising ATs (RR = 1.625, 95% CI = 0.562, 4.701), and 87.2% (n = 34) were at risk for sleep disturbances compared with 100.0% (n = 8) of nonexercising ATs (RR = 1.147, 95% CI = 1.017, 1.294).
Energy Availability and Depression
Among the ATs classified with optimal EA (n = 15), 26.7% (n = 4) were at risk for depression compared with 4.2% (n = 1) with LEA. The RR of depression if ATs had LEA was 0.156 (95% CI = 0.019, 1.269). Of those with optimal EA, 33.3% (n = 5) were at risk for state anxiety compared with 12.5% (n = 3) with LEA (RR = 0.375, 95% CI = 0.104, 1.346), and 33.3% (n = 5) were at risk for trait anxiety compared with 16.7% (n = 4) with LEA (RR = 0.500, 95% CI = 0.159, 1.572). Among those with optimal EA, 80.0% (n = 12) were at risk for sleep disturbances compared with 91.7% (n = 22) with LEA (RR = 1.146, 95% CI = 0.866, 1.517).
DISCUSSION
We sought to examine ATs’ EA, depression and anxiety risks, and sleep quality and determine whether exercising or having LEA increased their risk for mental health concerns and sleep disturbances. We also assessed these variables across sex, job setting, and job role.
Energy Needs
Differences were found by sex for RMR, TDEE, and EEE and addressed in a previous publication.1 In the present study, males and females, on average, had LEA and consumed fewer calories than they expended. Despite differences in EI and TDEE, no differences were observed between EA and sex. Although the research on LEA in females is extensive, only recently did researchers30 report LEA in males. Due to the potentially permanent implications of chronic LEA, our identification of similar LEA prevalence between sex reinforces the need for more research on the effects of LEA in males.
Regarding job status, FT ATs often have irregular schedules and long work hours. Arguably, a PT AT who works fewer hours may have more time to eat, yet this was not shown in our data. More than half of the ATs, regardless of job status or setting, had LEA. This percentage (61.5%) was higher than the prevalence range among athletes (up to 58%).31 Underreporting and differences in EI methods account for possible inaccuracies in determining population prevalence. Regardless, understanding nutrition is a competency set forth by the Board of Certification for ATs; 71.4% of ATs had adequate nutrition knowledge and were as confident in their incorrect answers on nutrition knowledge as they were in their correct answers.32 This confidence in their nutritional knowledge, although inaccurate, could explain their poor dietary habits. Those ATs with correct nutritional knowledge may knowingly not be practicing appropriate behaviors.
Mental Health
Although individuals in this study were only analyzed for the risk of depression and not diagnosed, 16.7% of males and 13% of females were at risk, values that were similar to those in the US general population (approximately 16%).6 Depression may be exacerbated by job duties, burnout, or other external pressures. Athletic trainers often work long hours, providing patient care in a fast-paced environment, and may neglect their own needs. Depending on the setting, an AT’s specific job duties may also influence his or her own mental health (eg, emergency response versus rehabilitative care). In a survey of 34 240 emergency medical service professionals, 6.8% (n = 1589) were classified as depressed.33 Arguably, nurses have similar job responsibilities to ATs; in 1 investigation, 13% tested positive for depression and 16% for anxiety.34 In the same study, 87% had symptoms of anxiety, depression, or posttraumatic stress disorder.34 The prevalence of anxiety among health care professionals was greater than in the general US population (9.0%).35 Anxiety was identified in 6.0% to 23.7% of emergency medical service providers,33,36 which was comparable with approximately 25% of our ATs. Among a combined group of physicians, nurses, and emergency medical service providers, approximately 62% reported mild to severe anxiety symptoms.36 For ATs, increased anxiety may be due to a high patient load, emergency situations, and pressures to return athletes to play.
Consideration for mental health conditions among ATs is important to combat the widespread professional concern of burnout.2 Causes and symptoms of burnout resemble those of clinical depression,21 though individuals suffering from burnout experienced more depressive symptoms.2 Wurm et al37 found that physicians with mild, moderate, or severe burnout were 2.99, 10.14, or 46.84 times, respectively, more likely to suffer from clinical depression. Depression can proceed or precede burnout onset.2 We did not examine burnout, yet given the concern for burnout among ATs2 and the depression risk we identified, we suggest that future researchers consider the link between burnout and depression.
Sleep and Mental Health
Sleep disturbances in our study were higher (91.7% of males and 87.0% of females) than those in primary care male (25.3%) and female (40%) physicians38 and nursing staff (61.0%).39 In contrast, our results were consistent with those of shift-work resident physicians, of whom 90% reported poor sleep quality.40 This similarity may be attributed to the irregular working hours of shift workers and some ATs. For ATs, poor sleep quality may be related to job responsibilities at different times of year (eg, in-season versus off-season). Low-quality sleep was associated with adverse psychological changes, including anxiety and depression.23 Inadequate sleep may influence state anxiety levels throughout the workday. Not only was poor sleep related to decreased quality of life,24 inadequate sleep, particularly when combined with anxiety and depression, negatively affects the quality of care provided.
Exercise and Mental Health
Exercise and even minimal PA may improve overall physical health and the physiological response to stress, perhaps via a mechanism whereby exercise facilitates endorphin release. Endorphins create a sense of well-being, subsequently reducing depression and anxiety levels. Unsurprisingly, physical inactivity contributes to mental health disorders. The benefits of exercise and PA on depressive symptoms may also be independent of age, sex, and geographic region. In this sample of ATs, 83% exercised but still exhibited a higher depression risk than the general population. Most researchers16 have reported a decreased relative risk of depression in exercisers. When comparing ATs who exercised with those who did not, our results agree with those of others16 who have shown a lower relative risk for depression with exercise.
Similarly, ATs who did not exercise displayed increased risks for both state and trait anxiety. The job responsibilities of ATs can include high-stress situations that require quick decision-making, potentially predisposing them to state or trait anxiety or both. Unfortunately, the cause of anxiety as both a symptom and a syndrome is not yet understood.41 Exercise has been identified as a protective factor against anxiety disorders, but much of the research lacks methodologic congruity, and therefore, concrete conclusions cannot be drawn.18,19 However, authors18,19 have demonstrated that individuals who exercise regularly had a lower risk of experiencing symptoms of and being diagnosed with anxiety than their physically inactive colleagues. In interventional studies, state anxiety decreased immediately after a single bout of exercise.19 Given the multidimensional context, we cannot yet conclude how exercise affected anxiety in the ATs studied. The effect of exercise on anxiety (and anxiety on exercise) may be clinically relevant to an AT only as a protective factor and as an influencer in the decision to exercise. Although exercise has been beneficial in reducing state anxiety, an AT cannot stop providing patient care and exercise when he or she feels anxious. Regular exercise decreases the anxiety risk and anxiety symptoms compared with physically inactive individuals. For ATs, exercise may be beneficial in reducing or protecting against anxiety.
Exercise and Sleep
Exercise is suggested to improve sleep quality.24 As little as 30 minutes of yoga improved sleep quality in health care professionals.23 Despite most of our participants exercising, 87% still experienced sleep disturbances. The dose threshold for exercise to improve sleep is unknown24 and is influenced by exercise duration, intensity, type, and time of day. For example, exercising > 3 hours before bedtime is related to less sleep disturbance than exercising < 3 hours before bedtime.24 The variability in PA and exercise levels among participants may have accounted for the high prevalence of poor sleep quality despite exercising. Another consideration is that exercise alone may not be enough to improve sleep quality. Numerous other factors, such as comfort in the environment, the stress level, prioritizing coursework or continuing education, or nutrition (eg, supplements, caffeine), can affect sleep quality.
Energy Availability and Mental Health
Dietary intake, a main factor in assessing EA, may be influenced by psychosocial stress and mental health conditions. However, no evidence indicates that a mental health condition in ATs is a direct cause or result of LEA. Although we hypothesized that ATs with LEA would have greater risks for mental health conditions, the results, based on RRs, were not supportive. This may reflect that, in our participants, LEA did not have a large effect on mental health. One factor is the role of exercise. An individual who exercises more expends more energy, increasing the chance for LEA. Exercise improves overall physical health and the physiological response to stress.17 Unsurprisingly, physical inactivity and poor diet have been recognized as contributors to noncommunicable chronic diseases and mental health disorders.17 Individuals can benefit from the protective factor of exercise against mental health disorders such as depression and anxiety, even with minimal amounts of PA.16 Exercise facilitates the release of endorphins; endorphins create a sense of wellbeing, which is why exercise is believed to reduce depression and anxiety levels.42 Therefore, the same exercising individual may also obtain the protective benefits of exercise on mental health, thereby experiencing a decreased risk. Another consideration is the combination of exercise and prolonged inadequate dietary intake leading to weight loss. Weight loss is associated with decreased depression and anxiety symptoms.10
Energy Availability and Sleep
Consistent with our hypothesis, most individuals with LEA experienced sleep disturbances. Nonetheless, and although they were at statistically lower risk, most of those with optimal EA had sleep disturbances. Although ATs with LEA were at statistically higher risk for sleep disturbances, the clinical relevance of this result must be determined. It is challenging to identify which variables are directly associated with sleep disturbances. As alluded to previously, an AT’s job requirements may create barriers to meeting dietary requirements and obtaining optimal sleep. Athletic trainers often work long hours and do not have a specific time allotted for eating. They may value exercise, sleep, and eating differently, choosing one over the other for personal reasons.
LIMITATION AND FUTURE RESEARCH
This study was limited to participants in 1 geographic region, at 1 time point in the year, and we did not explore individual job responsibilities. Therefore, the findings should not be generalized to the entire AT population. Assessing a free-living population limits the ability to control for confounding variables beyond the study variables. Also, inaccurate responses may occur with self-report questionnaires and dietary intake. Future researchers should continue to investigate mental health among ATs, including the factors that influence LEA, the prevalence of various mental health conditions, and sleep disturbances and how these conditions affect ATs’ quality of life and ability to perform the job. Authors of future studies should examine ATs in different geographic regions and settings at different times of the year and specifically evaluate ATs’ nutrition and exercise behaviors.
CONCLUSIONS
Health care professionals’ provision of care can be affected by factors associated with their own quality of life. We determined that ATs were not obtaining adequate dietary intake and sleep, which influenced their risks of depression, anxiety, or both. Additionally, ATs’ LEA and sleep disturbances were not influenced by sex, job status, or job setting. We recommend that ATs seek resources and implement habits aimed at improving their sleep quality and decreasing their risks for depression and anxiety. To provide optimal patient care, ATs must take care of themselves to optimize their physical and mental health and well-being. Strategies may include but are not limited to advancing their knowledge of employee benefits that support health and wellness, improving their nutritional knowledge, reevaluating their current job duties, and finding ways to achieve work-life balance.
Contributor Notes