Previous research shows the addition of a carbon-fiber plate (CFP) may improve running economy approximately 4% (Nike VaporFly 4% shoes). Consequently, other running shoe companies have developed similar products, but more research is needed focusing on these newer carbon-fiber plate (CFP) shoes. PURPOSE: This pilot study investigated the biomechanical and physiological effects of wearing Brooks CFP Hyperion Elite (BHE) shoe compared to a runners preferred race shoe (PRS). METHODS: Three men (Age: 25 ± 0 yrs; VO2 max: 58.9 ± 9.8 mls.min-1.kg-1) participated. Participants performed a VO2 max & two VO2 sub-max trials. Each shoe was tested in duplicate with the sub-max shoe order randomized (Day 1: PRS vs BHE or Day 2: BHE vs PRS). Sub-max stage workloads were determined from the VO2 max trial with each runner wearing their PRS. Using linear regression modeling, sub-max speed was set at 55%, 70%, and 85% of VO2 max for each 5 min stage. A standardized warm-up was done prior to testing and 30-min rest was provided in-between each shoe’s data collection trial. Metabolic data was collected using a COSMED B X B metabolic system, a Stryd power meter collected running power data, and LEOMO Type-S biomechanical wireless sensors collected ground contact time, landing pattern, lateral sway, smoothness, and cadence. Paired T-tests (summary data) and a repeated-measures ANOVA (Individual stages) using Tukey Post-Hoc analyses when appropriate (p ≤ 0.05). RESULTS: BHE shoes significantly improved running efficiency (p ≤ 0.05) looking at all stages combined (Running Pace: 8:43 mins/mi @ 70% VO2 max) comparing shoes: RunPower (watts) lower 5.1%; VO2 (mls/kg) lower 4.0%; VE (L) lower 4.8%, and energy expenditure (Kcals/min) lower by 4.8%. Biomechanically, the BHE shoe significantly enhanced mid-foot strike patterns 21.7% and running smoothness patterns by 16.7%. Across stages, starting at ≥70% of VO2 max, the BHE shoe enhanced running efficiency for the same variables mentioned above. CONCLUSION: These data indicate the BHE shoe enhanced performance efficiency to a similar degree as the Nike CFP running shoes. Future research should directly compare various CFP shoes in a larger group of runners (n = 20-30 with each runner tested across all shoes). Currently, there are many CFP available shoes plus several CFP insoles available.

The present investigation examined the ability of two threshold detection analyses (maximum distance, Dmax; modified maximum distance, mDmax) in identifying the near-infrared spectroscopy (NIRS) threshold, a lactate threshold (LT) estimate, from exercising tissue oxygen saturation (StO2) responses. Additionally, the test-retest reliability of exercising StO2 and total hemoglobin concentration (THC) responses were examined at moderate and peak cycling intensities. Fourteen healthy, recreationally active participants performed maximal incremental step cycling tests (+25 W / 3 minutes) to volitional fatigue on two separate occasions while StO2 and THC of the vastus lateralis were monitored. Exercising blood [lactate] was collected during Session One. LT and NIRS thresholds (NIRS1, NIRS2) were then determined using Dmax and mDmax threshold analyses. Significant (p < 0.05), moderate correlations were detected between LT and NIRS1 when using Dmax (LT = 130 ± 49 W, NIRS1 = 136 ± 34 W, r = 0.690), but not for mDmax (r = 0.487). No significant test-retest reliability for the NIRS thresholds were observed for Dmax (ICC = 0.351) or mDmax (ICC = 0.385). Exercising StO2 responses demonstrated good reliability (ICC = 0.841-0.873) while exercising THC responses demonstrated moderate-good reliability (ICC = 0.720-0.873) at moderate and peak exercise intensities. The results of this study suggest that neither the Dmax nor mDmax threshold analyses should be used to estimate the LT due to the unreliable detection of the NIRS threshold from session to session.

This study investigated the effects of a beet nitric oxide enhancing (NOE) supplement comprised of nitrite and nitrate on cycling performance indices in trained cyclists. METHODS:Subjects completed a lactate threshold test and a high-intensity interval (HIIT) protocol at 50% above functional threshold power with or without oral NOE supplement. RESULTS:NOE supplementation enhanced lactate threshold by 7.2% (Placebo = 191.6 ± 37.3 W, NOE = 205.3 ± 39.9; p = 0.01; Effect Size (ES) = 0.40). During the HIIT protocol, NOE supplementation improved time to exhaustion 18% (Placebo = 1251 ± 562s, NOE = 1474 ± 504s; p = 0.02; ES = 0.42) and total energy expended 22.3% (Placebo = 251 ± 48.6 kJ, NOE = 306.6 ± 55.2 kJ; p = 0.01; ES = 1.079). NOE supplementation increased the intervals completed (Placebo = 7.00 ± 2.5, NOE = 8.14 ± 2.4; p = 0.03; ES = 0.42) and distance cycled (Placebo = 10.9 ± 4.0 km, NOE = 13.5 ± 3.9 km; p = 0.01; ES = 0.65). Also, target power was achieved at a higher cadence during the HIIT work and rest periods (p = 0.02), which enhanced muscle oxygen saturation (SmO2) recovery. Time-to-fatigue was negatively correlated with the degree of SmO2, desaturation during the HIIT work interval segment (r = -0.67; p 0.008), while both SmO2 desaturation and the SmO2 starting work segment saturation level correlated with a cyclist's kJ expended (SmO2 desaturation: r = -0.51, p = 0.06; SmO2 starting saturation: r = 0.59, p = 0.03). CONCLUSION:NOE supplementation containing beet nitrite and nitrate enhanced submaximal (lactate threshold) and HIIT maximal effort work. The NOE supplementation resulted in a cyclist riding at higher cadence rates with lower absolute torque values at the same power during both the work and rest periods, which in-turn delayed over-all fatigue and improved total work output.

Exercise may prevent changes in body composition and provide an effective means of improving the side effects of treatment without causing lymphedema. Test the effectiveness of a 12-week water aerobics program on body composition and lymphedema risk in breast cancer survivors. Body composition analysis was completed at weeks 0, 6, and 12 weeks. Ten females completed all testing. Baseline subject characteristics were as follows: age (59.40 ± 8.22 years), weight (169.91 ± 41.70 lbs), body fat percent (%BF) (40.15 ± 9.84%), body fat mass (BFM) (71.27 ± 31.50 lbs), lean body mass (LBM) (98.66 ± 13.24 lbs), skeletal muscle mass (SMM) (53.17 ± 8.09 lbs), intracellular water (ICW) (44.24 ± 6.18 lbs), and extracellular water (ECW) (28.91 ± 3.62 lbs). One-way ANOVA showed no statistically significant differences over time as determined for weight (F(2.27) = 0.002, P = 0.96), %BF (F(2.27) = 0.004, P = 0.97), BFM (F(2.27) = 0.001, P = 0.97), LBM (F(2.27) = 0.013, P = 0.95), SMM (F(2.27) = 0.027, P = 0.91), ICW (F(2.27) = 0.021, P = 0.93), and ECW (F(2.27) = 0.01, P = 0.94) across the 12 weeks. A water aerobics program for 12 weeks was not enough to observe changes in body composition nor did it increase the risk for lymphedema and may be a safe exercise method for breast cancer survivors.

PURPOSE: Six pro endurance athletes (3 men, 3 female) participated in a study investigating the effects of cycling at high altitude on physiological & neuro-muscular systems. METHODS: Athletes were tested in three locations using identical procedures and equipment. Baseline testing took place in Santa Monica, CA. Then, the entire lab’s equipment was transported to two additional study locations (Death Valley and Mammoth Mountain, CA). Each athlete completed a 5-stage, 3-min/stage ramp exercise trial. Athletes performed the ramp test in duplicate at each test site (morning and afternoon). Respiratory-metabolic measurements, regional oxygen saturation (SMO2), substrate oxidation rates, and EMG activity were recorded continuously. Blood samples were taken the last 15-secs of each stage. Data were analyzed using repeated-measures ANOVA models and Turkey Post-Hoc test to identify specific areas of significance when appropriate. RESULTS: The mean workload across all 5 stages was 227 ± 60 watts (Stage 1 = 117 watts; Stage 5 = 287 watts). Compared to sea level, the over-all mean SMO2 saturation at the 227 watts mean was 24.5% lower at altitude (p = 0.04) while deoxy hemoglobin was 18.5% higher (p=0.04). Correspondingly, lactate concentrations were 27.2% greater, but this difference did not reach significance. However, lactate concentrations during stage 5 were 34% greater at altitude compared to see level (p = 0.035). At sea level, quadricep (Quad) muscle activation accounted for 58% of the total force produced while cycling at altitude quad work was reduced to 51%. Lactate concentrations had an inverse relationship with EMG Quad activity (p= 0.03) and direct relationship with hamstring force activation (p = 0.03). RER values indicated greater CHO oxidation rates at altitude across all stages combined (Sea level: 2.127 gm/min; Altitude: 2.954 gm/min, p = 0.01). For stages 4 & 5, despite greater respiration rates, over-all ventilation volumes declined cycling at altitude lowering oxygen uptake by 10.2% and 19.4% respectively despite being at the same workload compared to sea level. CONCLUSIONS: These results indicate cycling at altitude requires greater physiological-metabolic response to maintain neuro-muscular function cycling at work rates up to 80% of max effort.

PURPOSE: This study investigated how high-intensity interval training (HIIT) at altitude (ALT) versus sea level (SL) with and without supplemental oxygen recovery (SRO2) affected cardiac function and skeletal muscle %O2 saturation (SMO2). METHODS: Eight cyclists aged 42.4 ± 7.7 (HT: 68.9 ± 4.6; WT: 177.9 ± 26.6; Body Fat: 19.3% ± 7.5%; VO2 max L/min 4.38 ± 1.01) performed a baseline cycling VO2max test and four treatment trials (TRA - ALTHIIT/SRO2; TRB - SLHIIT/SLrecovery; TRC - ALTHIIT/ SLrecovery; TRD - steady-state (SS) cycling). Each HIIT work period (n=3) was 75s with 120s recovery at 75% and 50% of VO2max, respectively. For TRD, subjects cycled at a workload equal to the mean O2 uptake equal of TRB (Control-Trial). O2 uptake was measured using a breath X breath metabolic cart for VO2 max and TRB. Cardiac function (HR, Cardiac Output (Q), Stroke Volume (SV)) was assessed using impedance cardiography. SMO2 was measured in the vastus-intermedius quadricep muscles using Moxy NIR devices. Data was analyzed using a w/in repeated measures design (Treatment (4) X 3 HIIT/Recovery Periods). RESULTS: Despite identical workloads, HR was significantly lower during SS cycling compared to the HIIT trials by 7.6% (SS: 118.0 ± 3.4; Mean HIIT TR HRs: 127.0 ± 3.7, p=0.002). ALTHIIT/SRO2 (TRA: 141.8 ± 9.2) showed a lower SV by 8.4% compared to the ALTHIIT/SLrecovery trial (TRC: 154.3 ± 9.2). Q was significantly lower during the HIITw/SRO2 (TRA:17.7 ± 1.1) compared to SLHIIT/SLrecovery & ALTHIIT/SLrecovery (TRB: 19.8 ± 1.1; TRC:19.8 ± 1.1) by 12% (P=0.04). SMO2 data showed a trend for ALTHIIT/SRO2 & SS cycling to have higher SMO2 values compared to the both HIIT trials without SRO2 (p=0.09). During recovery, ALTHIIT/SRO2 showed improved HR recovery 5.2% (p=0.01), increased SMO2 re- saturation rate 12.6% (p=0.01), and lowered Q 11.9% (p=0.01) compared to the altitude-sea level recovery trial. CONCLUSION: These results suggested that supplemental O2 recovery lowered cardiac demand (Q) at the same HIIT workload by maintaining HIIT SMO2 better by enhancing the overall recovery process. Supported by a grant from LiveO2 and Exercising Nutritionally, LLC

Reported Relationships: C.E. Broeder:Contracted Research - Including Principle Investigator; Corporate grant. PURPOSE: This study investigated the effects beet nitrate supplementation had on cycling performance (power, force, cadence (Cad) speed (Spd), distance, time to fatigue, kJ expended) during repeated high intensity intervals (HIIT). METHODS: Eight cyclists participated (Age: 41.4 ± 9.1; WT: 83.3 ± 9.6 kg; BF%: 21.7 ± 0.1; VO2 max: 4.20 ± 0.58 L/min, functional threshold power (FTP): 245.4 ± 43.6 watts). This study was a randomized, double-blind, crossover, matched pair design. Prior to the HIIT sessions, subjects consumed for 7-days placebo (PL) or an oral beet nitrate (BN) supplement. On the day of testing, after completing baseline measurements & 45-mins prior to the HIIT session, 10g of the treatment week’s supplement was consumed by each rider. The HIIT workload was set at a wattage 1.5 times greater than a cyclist’s baseline FTP, e.g., FTP = 200 watts; HIIT work interval = 300 watts. Each HIIT segment was 75-secs and followed by a 2-min recovery at 50% of FTP. Cyclists were instructed to do as many intervals as possible. A matched paired t-test was used to compare each treatment for the summary data (i.e., total secs completed under the placebo versus beet supplementation conditions), HIIT trial total work data, and HIIT trial total recovery data. When a significant difference was observed, Cohen’s d effect size (ES) procedures were used to determine the magnitude. RESULTS: BN supplementation improved time to exhaustion (PL: 1,251 ± 562 secs, BN: 1,475 ± 504 secs; p = 0.02; ES = 0.423) and total energy expended (PL: 251.3 ± 48.6 secs, BN: 306.6 ± 55.2 kJ; p = 0.01; ES = 1.079) compared to PL. Subjects during the BN trials completed more intervals (BN = 8.14 ± 2.4, PL = 7.00 ± 2.5, p = 0.03, ES = 0.42) and cycled 23.9% further (BN = 13.5 ± 3.9 km, PL = 10.9 ± 4.0 km, p = 0.01, ES = 0.65). During the work segments, BN enhanced cadence and speed by 2.0% at the same force compared to PL (Cad: p = 0.02; ES = 0.20; Spd; p = 0.02; ES = 0.20). During recovery, comparing BN to PL, force was lower (PL: 68.2 ± 15.6 N, BN: 65.5 ± 13.7 N, p = 0.01, ES = 0.23), Cad was higher (PL: 91.8 ± 10.9 rpm, BN: 93.9 ± 7.4 rpm, p = 0.01, ES = 0.23), Spd was greater (PL: 30.7 ± 3.3 kph, BN: 31.4 ± 1.9 kph, p = 0.02, ES = 0.27). CONCLUSIONS: BN enhanced HIIT work and recovery performance allowing a more efficient maintenance of Cad, force, & Spd.

Surface Electrical Muscle Stimulation (EMS) is the excitation of muscle through electrodes directly placed on the skin of a given target muscle or muscle groups. Past studies have investigated the effects of EMS in healthy subjects or special populations, e.g., spinal cord injury, diabetic or heart failure patients. Additionally, other studies have focused on muscle strength, speed, power, co-contraction effects, abdominal strength, body composition, and Energy Expenditure (EE)

Lactate threshold (LT) is an important variable to consider for aerobic training programs and has traditionally been analyzed by measuring blood lactate concentration ([La]) during maximal exercise tests. Previously, near-infrared spectroscopy (NIRS) techniques have been used to non-invasively estimate the LT during maximal exercise tests by assessing the microvascular oxygenation (SmO2) response. PURPOSE: To determine the validity and reliability of a new wireless NIRS system in estimating the LT during a maximal exercise test. METHODS: 10 subjects with minimal cycling experience (29 ± 3 yrs, 1.8 ± 0.1 m, 79.1 ± 12.6 kg, 35.8 ± 5.6 mL/kg/min) performed two exercise sessions, separated by 7 d, of a step protocol (+25 W / 3 min) to volitional fatigue on a Monark 839E cycle ergometer. During session 1, arterialized venous blood samples were collected during the last 15 s of each stage to assess [La]. Additionally, the SmO2 response (NIRS1) was continuously recorded at a sampling rate of 2 Hz using a wireless NIRS sensor placed on the vastus lateralis. To assess reliability of the NIRS system, the SmO2 response was measured again during session 2 (NIRS2) as the subjects repeated the same cycling step protocol from session 1. All SmO2 data were averaged over the last 15 s of each stage. Thresholds based upon the [La], NIRS1, and NIRS2 responses to the increasing work rate were detected via visual inspection, by 3 experienced investigators blinded to the subjects and conditions, and computer modeling (Dmax, Modified Dmax). One-way, repeated measures ANOVA was used to test for significant differences (p < 0.05) between threshold detection methods ([La], NIRS1, NIRS2). RESULTS: Moderate-good inter-rater reliability between visual inspection raters was observed (ICC = 0.58-0.80). Visual inspection of the thresholds displayed no difference between threshold detection methods ([La] = 114 ± 12W, NIRS1 = 114 ± 21W, NIRS2 = 109 ± 26W). No difference was detected between threshold detection methods when analyzed using the Dmax ([La] = 130 ± 44W, NIRS1 = 120 ± 28W, NIRS2 = 138 ± 32W) or modified Dmax ([La] = 130 ± 44W, NIRS1 = 119 ± 28W, NIRS2 = 136 ± 32W). CONCLUSIONS: The new wireless NIRS system may be able to accurately and reliably estimate the LT during maximal exercise tests performed on a cycle ergometer in a healthy, adult population.

Tracking daily energy expenditure via wearable devices has become very popular. However, few in-lab and field studies validating these devices have been published. PURPOSE: To determine the accuracy of a wrist-based activity tracking device in a lab setting and during a NCAA style golf tournament. METHODS: Eight NCAA golfers [4 males; 4 females; Age: 19.3±2.0 yrs; WT: 149.5±13.4 lbs; Bag WT: 22.3±2.0 lbs; Bag Wt./Body Wt.: 15.0±1.8%; HT: 67.7±3.6 in; % BF: 20.0±7.3%] were tested. In-lab testing consisted of a VO2max test with golf bag wt. simulation and two 6-min run/walk steady-steady (SS) tests (one with bag wt., one without). The golf tournament consisted of completing two, 18-hole rounds while carrying their own golf clubs. Variables collected during tournament play were HR, distance, time, speed, device kcals, kcals from the metabolic cart (MET kcals), pace, and score. Unpaired, paired t-test, and a repeated measures ANOVA were used to determine significant differences. Correlation and step-wise multiple regression were used to determine which variables had the largest influence on determining kcals expended. RESULTS: During the in-lab testing, the device overestimated kcals expended compared to the actual MET kcals (+22.4%; p=0.01) for the 6-min SS tests. Step-wise regression showed that HR had the largest impact on kcal expenditure (p=0.04) during the SS tests. During the golf tournament, males had lower mean HRs (males: 111.00 ± 4.31 bpm; females: 121.99 ± 15.26 bpm). The device showed females burned more tournament kcals (1,642.33 ± 442.98 kcals), but less kcals per hour (348.59 ± 78.09 cal/hour) than males (1,583.13 ± 145.80 kcals; 357.13 ± 30.21 cal/hour). Comparing MET kcals and device kcals, the device underestimated females by 6.22% (not significant, NS) and overestimated males by 5.3% (NS). Looking at the device kcals for all golfers across all rounds, step-wise regression showed that calories/hour and playing duration time (p ≤ 0.01, p ≤ 0.01; r-squared=0.99) were the primary independent device kcal determinants. CONCLUSION: The in-lab tests showed the device overestimated kcals expended. During the golf tournament, the device overestimated males and underestimated the female kcals expended showing a possible golf tournament wearable kcal gender measurement tracking bias.

Deer antler velvet (Dav) supplementation purportedly increases athletic performance; however, little data support this claim. the primary aim of our study is to examine Dav and exercise performance. We randomized 32 men (18–35 y) participating exclusively in resistance training (>4 y) to 10-weeks of randomly assigned, double blind, Dav (1350 mg, 2×/day) or placebo treatments. Primary outcomes included maximal aerobic capacity (vo2max), maximal strength (1rM; bench press and squat) and anaerobic cycling power. Secondary outcomes included comprehensive blood profiles and body composition. We used general linear models to determine changes following treatment. Eighteen participants (n = 9) completed the study with Dav participants showing significant improvements in vo2max (4.30 ±0.45 to 4.72 ±0.60 l/min, P < 0.04). the placebo and Dav groups increased bench press and squat 1rM (both, P < 0.04); yet, when expressed relative to body mass, only the Dav group showed significant bench press (4%) and squat (10%; both, P < 0.02). Neither group improved cycling performance or showed adverse changes in blood chemistries. We did observe a significant reduction in lDl-C (12%) accompanying Dav supplementation and both groups significantly reduced percent body fat (P < 0.05). our results suggest that Dav may have ergogenic effects in men participating solely in resistance training.

Heart-rate variability characterizes cardiac autonomic balance, and provides a useful index of training load exposure, and hence an estimate of cumulative physical fatigue. However, the interaction between HRV and performance is less understood. PURPOSE: To determine the predictive value of the Root Mean Square of Successive Differences (RMSSD) and Low to High Frequency Ratio (LF/HF) on cycling 4km TT performance following high-intensity (HI) exercise. METHODS: Four elite cyclists (mountain bike (F), cyclocross (M), triathlon (M), BMX (M)) performed three successive days of 4x5 min HI cycling bouts at 260W (F), and 375 ± 21.8W (M) separated by 5-7 min of recovery between each bout. Following completion of the HI protocol, athletes rested for 30 min and then performed a 4km TT on a Cyclus 2 ergometer. HRV was recorded the evening before the TT’s between 22:00h and 23:59h using a HealthPatch (Vital Connect, Campbell CA), and areas under the curve were computed for RMSSD and LF/HF ratio. Linear regression was performed to determine the relationship between RMSSD, LF/HF ratio and TT time. RESULTS: 4x5 min HI exercise bouts were sustained in all athletes except BMX where workload was reduced by 14% from day 1 to day 2. Progressive fatigue was evidenced by RPE’s increasing from 1km to 4km by 12.5±3.6% (Day 1) to 20.6±4.5% (Day 3). Day 1 to Day 3 data is shown in the table below;Table: No title available.RMSSD v. TT time R2 for day 1-3 respectively was, -0.39, -0.29, and -0.60 (p=0.03 for grouped days). LF/HF v. TT time R2 for day 1-3 respectively was, 0.09, 0.59, and 0.18 (p=0.06 for grouped days). CONCLUSION: Early sleep cycle HRV data prior to HI fatiguing cycling explains partially TT cycling performance in elite athletes.

Understanding the factors influencing students’ choices of what college to attend and what academic major to pursue holds important implications for academic programmers and university stakeholders. While several studies have examined the factors impacting the school choice decisions of student-athletes, little to no research has been done to explore the factors influencing school-choice decision-making among the general student population. PURPOSE: To examine the factors that impact student decisions to pursue a graduate degree in exercise physiology. METHODS: 31 students currently enrolled in an exercise physiology graduate program at a midsized university located in the Midwestern United States (13 females, 18 males; Mage = 23.8 years) volunteered to participate in the study. Data were collected using semi-structured, one-on-one interviews (referred to as laddering) which focuses on eliciting responses that climb the “ladder” of abstraction (i.e., from relatively concrete attributes, to more abstract consequences, and finally to highly abstract personal values). In the laddering interviews, respondents were first asked to identify the attributes of the selected school and graduate sport management program. Follow-up questions (in the form of “why is that good or beneficial” or “why is that important to you”) were then asked to identify the consequence(s) provided by each attribute; and finally the value(s) associated with each consequence. RESULTS: A number of representative ladders and means-end chains were obtained. One means-end chain example linked the attribute of a graduate assistantship, with the consequence of not having to take out a student loan, to finally the value of increased financial security after graduation. The set of means-end chains obtained are summarized across the study sample in the form of a Hierarchical Value Map (HVM). The final means-end chain values were security, achievement, comfortability, and enjoyment. CONCLUSION: Findings provide university stakeholders and graduate-level programs with a clearer understanding of the different factors contributing to graduate students’ school-choice decisions. More specifically, students appear to place the most value on financial and job-related security.

Obesity has been established as a risk factor for multiple diseases and is an increasing problem throughout the world. Advances in technology have enabled health professionals to use many devices to diagnose individuals as healthy, overweight, or obese. However, there are discrepancies between the validity of the devices. PURPOSE: The purpose of this study is to validate InBody 520 and InBody S10 against the Hologic dual-energy X-ray absorptiometry (DXA) system. METHODS: 50 male and female subjects performed body composition testing on an InBody 520, InBody S10, and a Hologic DXA, followed by repeat measurements on the InBody 520 and S10. RESULTS: JMP Statistical Discovery Software Version 12.2.0 (Cary, NC) was used to run a matched pairs T-test and one-way analysis of variance (ANOVA) statistical analysis on all data collected. The significance level was set as p<.05 with a confidence interval of 95%. Subjects were (31 males, 19 females) mean weight was 87.8 ± 19.6kg (male) and 63.9 ± 10.7 kg (female), mean height was 178.7 ± 6.6cm (male) and 161.9 + 7.1cm (female), mean age was 23.1 ± 2.7 years (male) and 22.9 ± 2.0 years (female). Body fat percentage was significantly greater for the DXA (28.9 ± 8.2) when compared to the InBody 520 (20.4 ± 9.6), p<.001, and significantly greater when compared to the the InBody S10 (21.8 ± 9.8), p = .001. Lean body mass was significantly less for the DXA (54.7 ± 14.4) when compared to InBody 520 (62.2 ± 15.1), p = .036, but not significant when compared to the InBody S10 (61.0 ± 15.6), p = .096. Body fat mass was significantly greater for the DXA (22.3 ± 9.4) compared to the InBody 520 (16.5 ± 10.6), p = .0156, but not significant when compared to the InBody S10 (17.9 ± 10.9), p = .091. CONCLUSION: The overall conclusion of this project is significant differences existed when measuring body composition variables between the DXA and the InBody devices. The InBody devices however, were not significantly different to each other when measuring body fat mass, lean body mass, and percent body fat, but again, they were significantly different when compared to the DXA.

It is a great honor to be asked to write a memoriam for Dr. Jack H. Wilmore. Dr. Wilmore was my doctoral mentor, my friend, and most importantly, my brother in Christ. Dr. Wilmore's impact on both exercise physiology and clinical exercise physiology over his long career was extensive and far reaching. Dr. Wilmore was a past-president of the American College of Sports Medicine (ACSM; 1978–79). Based on an extensive career (317 peer-reviewed research articles; 55 chapters in edited books; 15 authored/co-authored books; research grants from the National Institutes of Health, National Aeronautics and Space Administration (NASA), and the United States Air Force), Dr. Wilmore was a recipient of the ACSM Citation Award in 1984 and the ACSM Honor Award in 2006. He was also editor-in-chief of Exercise and Sport Sciences Reviews from 1972 to 1975. Dr. Wilmore's textbook in collaboration with Dr. David Costill, Physiology of Sport and Exercise, has set the standard for exercise physiology textbooks since it was first published. In a similar light, in collaboration with Dr. Michael Pollock and Dr. Samuel Fox, Dr. Wilmore's Exercise in Health and Disease: Evaluation and Prescription for Prevention and Rehabilitation was often considered required reading for clinical exercise physiology students.Dr. Wilmore's extensive work in clinical exercise physiology included landmark studies that contributed to understanding that obesity was becoming an epidemic several decades before it was officially recognized by most health and medical institutions. Dr. Wilmore lead the way in developing preventive health adult fitness programs that continue to be an important part of the kinesiology program at the University of Texas at Austin, where Dr. Wilmore was the first endowed chair in exercise physiology awarded at a major research institute in United States. In addition, his research and consultation with the Beckman Corporation helped pave the way for today's automated metabolic carts. And his research on body composition, human performance, thermoregulation, betablockers and exercise, obesity, gender and exercise effects on resting metabolic rate, and genetic adaptations to training are some of the most influential studies in clinical and sports performance exercise physiology.While Dr. Wilmore's professional accomplishments were exceptional, when I look back at my time with him, I can tell you first-hand, Dr. Wilmore's day-to-day life always honored God, family, and caring for others before his own personal goals and desired accomplishments. For many years, he helped organize and contribute to the Christian Fellowship Breakfast held each year during ACSM's annual scientific meeting. In the 31 years I had the honor of knowing and working with Dr. Wilmore, not once did he ever stop showing us that those principles were always at the core of his being. While I was his doctoral student, Dr. Wilmore played a critical role in two major events in my life. In 1985, directly as a result of my wife and Dr. Wilmore, I accepted Christ in my life as my Lord and Savior. I remember Dr. Wilmore and Dottie, his wife, coming to my baptism. I remember him giving me the biggest hug and congratulating me on my decision. Suddenly, I was not simply his student and he my doctoral mentor; we were now brothers in Christ. The second major event was in 1989 when my wife was diagnosed with a rare and very deadly disease called clear cell ovarian cancer while I was a doctoral student. Dr. Wilmore as department head, our UT faculty, and my fellow students supported us in ways that were family-like. Dr. Wilmore's examples led the way because that is how his lab and exercise science program always felt—like family!I am sure that each and every person who had the opportunity to work with and get to know Dr. Wilmore feel as I do when I say that his professional career was nothing less than exceptional, but the life he lived and shared with all of us is why he will always be one of the most respected people in our profession. To close, I believe it is most fitting to finish with Dr. Wilmore's own words from his acceptance speech when he was honored with the 2010 Hetherington Award from the National Academy of Kinesiology: