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Laboratory of Systems Physiology

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1 Laboratory of Systems Physiology
Examination of Risk for Sleep Disordered Breathing Among College Football Players LSP Laboratory of Systems Physiology Bailey Peck1, Timothy Renzi1, Hannah Peach2, Jane F. Gaultney2, Joseph S. Marino1 The University of North Carolina-Charlotte, Charlotte, NC 1Kinesiology, 2Psychology & Health Psychology ABSTRACT RESULTS TABLE 2 Purpose: Professional football linemen are at greater risk for sleep disordered breathing (SDB) due to the physical characteristics favored by the sport. This may increase current or later risk for metabolic and cardiovascular disease. It is currently unknown whether collegiate football linemen also display signs of SDB. The purpose of this study was to determine whether collegiate linemen have risk factors for SDB. Methods: Male football linemen and track Division I athletes participated in this study. Participants completed the Multivariable Apnea Prediction (MAP) Index and Epworth Sleepiness Scale (ESS) questionnaires, validated measures of symptoms of sleep apnea and daytime sleepiness, respectively. This was followed by measurement of neck and waist circumferences, blood pressure, Mallampati Index (MMPI) and Tonsil Size, and body composition assessment using DEXA. Results: Self-reported survey data demonstrated a deficiency in sleep quality and efficiency, which coincided with increased self-reported symptoms of apnea (MAP index=0.79) in college linemen relative to age-matched track athletes. As expected, neck circumference (45cm), waist circumference (107.07cm), body mass index (36.64kg/m2) and body fat % (30.19%), all of which exceeded the clinical predictors of risk for obstructive sleep apnea, were significantly greater in linemen compared to track athletes. MAP variables were significantly correlated with MMPI, neck circumference, body fat %, body mass index, and systolic blood pressure (r ≥ .31, p < 0.05), indicating that college football linemen are at an increased risk for SDB. Conclusions: Our data demonstrate that the risk factors for SDB previously recognized in professional football linemen are also present at the collegiate level. Early detection and intervention may improve academic and athletic performance and minimize the effect of SDB on overall health later in life. Team differences for both self-reported and physiological risk factors were significant. Football players had larger necks and waists, higher body mass index, larger tonsils, and higher systolic blood pressure. Measures generated by the MAP (roughly indicating risk for apnea and potential severity of apnea) were significantly higher among football players. Football (Mean±SD) Track (Mean±SD) N 21 19 Age 20.57± 1.08 20.53±1.22 Time to fall asleep 2.24±1.18* 1.53±0.77 Trouble Falling Asleep 0.90±1.26 0.37±0.68 Feel Rested in Morning 2.90±1.55 2.68±1.11 Epworth Sleepiness Scale 7.57±3.6 7.42±2.87 MAP Index 0.78±0.93* 0.21±0.39 MAP Likelihood RDI > 10 -0.05±0.60* -2.33±0.47 Body fat (%) 30.19±5.49* 13.10±2.95 Neck Circumference 45±2.42* 36.92±2.08 Waist-Hip Ratio 107.07±6.22 76.29±3.75 MMPI 126.02±7.02 101.76±22.68* Tonsil Size 0.85±0.04* 0.77±0.10 Body Mass Index 36.64±3.44* 23.07±2.34 Systolic Blood Pressure2 131.5±10.85* 123.68±8.61 Diastolic Blood Pressure2 75.19±7.43 74.47±7.63 INTRODUCTION TABLE 1 Despite their young age and physical fitness, professional football players are at greater risk for sleep disordered breathing (SDB) than the general population due to greater upper body mass. Although larger upper body mass is valuable to these athletes (linemen, in particular), this often includes greater neck mass and upper body bulk, which increase risk of developing SDB. This may subsequently increase downstream risk for cardiovascular and metabolic disease. In order to explore whether these risk factors are also evident among college athletes, the present study examined subjective and objective risk factors for SDB in college level football players relative to athletes with lower body mass. Multivariate Analysis of Variance of a Set of Outcomes Predictive of Sleep Apnea Followed by Univariate Analysis of Variance for Each Outcome _______________________________________________________ Multivariate F(8,31) = 41.11, p<.001, η2partial = .91 F(1,38) p η2partial MAP Index MAP RDI> < Neck Circumference (cm) < Modified Mallampati Index < Tonsil Size < % Body Fat < Avg. Systolic Blood Pressure Avg. Diastolic Blood Pressure ___________________________________________________________________ MAP; Multivariate Apnea Risk index (an index >1 associated with greater likelihood of diagnosis of apnea), MMPI; Modified Mallampati Index, MAP RDI>10= the likelihood that a given participant would have a respiratory index (indicative of severity of apnea) >10; Avg. Sys. BP and Avg. Dias. BP is the average (across two readings) systolic and diastolic blood pressure, respectively METHODS EXPERIMENTAL DESIGN: Participants. The study included 21 male Division I linemen and 22 Division I track and cross-country athletes (18 to 22 years old). Since exercise may reduce risk for SDB, we wanted to include a comparison group of athletes who also experienced the rigorous training of a university sports team. See Table 1 for descriptive data of the sample. Materials. Subjective risk factors for SDB were assessed using the Multivariable Apnea Prediction (MAP) index. Participants rated how frequently they experienced a list of sleep disorder symptoms. The MAP index (risk for SDB) included average frequency of loud snoring, breathing cessation, and snorting/gasping. In addition, the survey generated a score that indicated the likelihood of severity, defined as a respiratory disturbance index (RDI) of ≥10 disturbances per hour. Objective measures of physiological characteristics associated with SDB were collected, including height, weight, blood pressure, waist and neck circumference, the modified Mallampati index, and tonsil size. Body composition was measured using Dual Energy X-ray absorptiometry (DEXA). Statistical Analyses. Following inspection of descriptive data and bivariate correlations, the hypothesis that football linemen would have more risk factors for OSA than did members of the track team was tested with two multivariate analyses of variance (MANOVAs). Separate analyses were run for self-reported data (the Epworth Sleepiness Scale, the MAP Index 1, and the MAP RDI>10 variable) and objectively measured physiological data. Use of MANOVAs allowed examination of multiple outcomes when simultaneously entered into the model. Each MANOVA was followed by univariate analyses of variance (ANOVA) to compare sport differences in the individual measures. Notes: *significant effect of sport, p<.05. MAP; Multivariate Apnea scale, RDI; Respiratory Distress Index; MMPI=modified Mallampati index. Blood pressure values are average of two blood pressure readings. CONCLUSION College level football players demonstrated significantly more self-reported and objectively measured risk factors associated with SDB than did track team members. These data suggest that the body characteristics valued among linemen that may predispose them to SDB are evident in college athletes. Our data suggest that simple assessments could be incorporated into the screening process of collegiate athletes to identify those at risk for developing SDB, which would allow early awareness of risk and intervention. *manuscript under review, Journal of American College Health Contact information: Joseph S. Marino,


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