Differences in Training and Health Characteristics Between Trail Ultrarunners and Shorter Distance Runners.

INTRODUCTION: The primary aim of the study was to compare select training and health characteristics between ultramarathon and shorter distance runners participating in a trail race series. METHODS: A questionnaire was sent to all participants who signed up for a trail race series, including distances of 10 km, half marathon, 50 km, 80.5 km (50 mi), and 100 km. There were 59 participants (27 ultramarathoners and 32 half marathon/10-km runners) who completed the questionnaire. We compared the training and health characteristics between groups using t tests and Fisher exact tests. RESULTS: There were no significant differences in reported history of stress fracture (15% vs 9%; P=0.70) or sleep quality scores (4.4 vs 5.5; P=0.15) between the ultramarathon and half marathon/10-km groups. Over half of both groups reported trying to change body weight to improve performance, without significant differences between groups (65% vs 53%; P=0.42). A significantly greater proportion of the ultramarathoners reported an episode of binge eating in the 4 wk preceding the race (38% vs 3%; P=0.001). CONCLUSIONS: Despite differences in training volume, we did not find different injury, sleep, and nutrition data between the ultramarathoners and half marathon/10-km runners, with the exception of more ultramarathoners reporting binging behaviors in the 4 wk leading up to the race. Screening for eating disorder behaviors should be considered in distance runners, particularly ultrarunners.

Training volume recommendations and psychosocial outcomes in adolescent athletes.

OBJECTIVES: Researchers have recommended that youth athletes limit their practice volume to the number of hours/week that they are old in years. We examined sport perceptions, burnout, anxiety, and depressive symptoms among youth athletes who did and did not report playing more hours/week of organized sports than their age. METHODS: Uninjured athletes aged 13-18 years old completed questionnaires documenting demographics, sport participation volume, health and injury history, depressive symptoms, anxiety, burnout, and sport perceptions during a pre-participation physical examination. We grouped participants as those who reported more hours/week in organized sports than their age (exceeds age/volume recommendation) vs. those who reported equal/less hours/week in organized sports than their age (meets age/volume recommendation). RESULTS: Of 161 participants, 21% (n = 33) were in the 'exceeds age/volume recommendation' group (age = 15.2 ± 1.3 years; 55% female; 18.7 ± 4.0 hours/week) and 79% (n = 128) were in the 'meets age/volume recommendation' group (age = 15.6 ± 1.2 years; 50% female; 10.2 ± 3.4 hours/week). A higher proportion of the 'exceeds age/volume recommendation' group agreed with the statement 'youth in my sport play too many games before college' than the 'meets age/volume recommendation' group (33% vs. 16%; p = 0.03). After adjusting for the effect of age, sport specialization level, and weight, exceeding age/volume recommendations was associated with the perception that youth in sports play too many games before college (aOR = 3.24; 95% CI = 1.26, 8.29; p = 0.01), while burnout (aOR = 0.99; 95% CI = 0.94, 1.06; p = 0.93), anxiety (aOR = 0.97; 95% CI = 0.84, 1.11; p = 0.65), and depressive symptoms (aOR = 0.90; 95% CI = 0.74, 1.10; p = 0.30) were not significantly related. CONCLUSION: Athletes who spend more hours in sport than their age appear to perceive their competition load during youth sports to be excessive. Coaches and providers should monitor athlete's training hours and perceptions of competition load to offer support and potentially prevent burnout development.

Socioeconomic status and injury history in adolescent athletes: Lower family affluence is associated with a history of concussion.

Background: While healthcare and health outcome disparities have been studied across a variety of different injuries, their relation to concussion incidence and management are relatively understudied. Aim: The aim of this study was to evaluate the association between history of concussion or musculoskeletal injury, and family affluence and/or school-level measures of socioeconomic status. Methods: We conducted a cross-sectional study of adolescent athletes in a local school district. Adolescent athletes (n = 192; mean age = 15.3, SD = 1.6 years; 49% female), who presented for a pre-participation physical evaluation reported concussion and injury history, and family affluence scale (FAS) scores. We also examined the percent of students on free/reduced lunch at each school compared to state averages. Independent variables, individual FAS score and school-based marker of socioeconomic status, were compared between those with and without a history of concussion and time-loss musculoskeletal injury. Results: Of the participants, 40 (21%) reported a history of concussion. Athletes with a concussion history had significantly lower FAS scores than athletes without a history of concussion (mean difference = 0.7, 95%CI = 0.1, 1.4; P = 0.027). There was no significant difference in FAS scores between those with and without a history of time-loss musculoskeletal injury (mean difference = 0.0, 95% CI = -0.5, 0.5; P = 0.97). Athletes with a history of concussion had a higher proportion of a prior time-loss musculoskeletal injury (68% vs. 32%; P < 0.001). After adjusting for age, school free-reduced lunch rate, and history of musculoskeletal injury, a lower FAS score was associated with concussion history (adjusted odds ratio = 0.79; 95% CI = 0.64, 0.96; P = 0.019). Concussion and musculoskeletal injury were not associated with school-level markers of socioeconomic status. Conclusion: Lower individual measures, but not school-level measures, of socioeconomic status were associated with a history of concussion in our sample of adolescent athletes. Relevance for Patients: Enhance providers' understanding of how socioeconomic factors may impact concussion history and empower providers to adequately screen for and provide concussion education to mitigate disparities.

Sport specialization, sleep, fatigue, and psychosocial ratings: do highly specialized athletes differ from their less specialized peers?

OBJECTIVES: To determine if sleep quality, fatigue, anxiety, depressive symptoms, or perceptions of sport participation differ between high-, moderate-, and low-specialized high school athletes with or without prior injuries. METHODS: During pre-participation physical examinations (PPE), high school athletes completed questionnaires on sport specialization level, history of time-loss orthopedic injury, perceptions of sport participation, as well as sleep quality (Pittsburgh Sleep Quality Index (PSQI)), fatigue, anxiety, and depressive symptoms (Patient-Reported Outcomes Measurement Information System (PROMIS®)). Athletes were grouped according to sport specialization level and history of prior time-loss orthopedic injury. RESULTS: A total of 186 athletes completed the study: 49% (n = 92; mean age = 15.3 ± 2.0 yrs; 50% female) were low specialized, 34% (n = 64; mean age = 15.3 ± 1.3 yrs; 47% female) were moderately specialized, and 16% (n = 30; mean age = 15.7 ± 1.1 yrs; 57% female) were highly specialized. Groups were similar for demographics, training volume, and injury history. Compared to the moderate-specialization group, highly specialized athletes reported higher levels of fatigue (3.1 ± 3.7 vs. 1.5 ± 2.2; p = 0.02), anxiety (3.6 ± 4.1 vs. 1.8 ± 2.6; p = 0.02), and depressive symptoms (2.4 ± 4.0 vs. 0.8 ± 2.0; p = 0.02). No differences in psychometric ratings, sleep quality, or perceptions of sport participation were observed between the low/moderate- or low/high-specialization groups. We did not observe any significant differences between groups who did and did not report a history of prior time-loss orthopedic injury. CONCLUSIONS: Highly specialized high school athletes report higher levels of fatigue, more anxiety symptoms, and more depressive symptoms than their moderately specialized peers, despite no differences in training volume or injury history. Low specialized athletes did not differ from moderately specialized or highly specialized athletes in the aforementioned domains, and there were no differences in sleep quality across specialization groups. These findings add to the current body of literature on early sport specialization by illustrating the distinctive psychosocial implications of sport specialization and demonstrating the need for further prospective research.