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Testing as Teaching: A Model for Fitness Assessment Practice and Service-Learning in Exercise Physiology Laboratory Education
Get PDFThis resource is intended to provide a model for fitness assessment practice to promote student learning in an undergraduate exercise physiology laboratory course. The goal is for students to gain practical experience in fitness assessment procedures, both through skills practice and service-learning opportunities. The inclusion of an assignment requiring a specified number of assessments to be completed within the term requires additional student practice opportunities. Instruction, demonstration, and initial practice of tests associated with health-related physical fitness components must occur early in the course, so as to permit sufficient opportunities, in class or outside of class, over the remainder of the course term. Fitness assessments involving individual tests of minimal complexity require approximately 30 minutes to complete, amounting to two total hours of practice time accrued if four assessments were required, and thus adequate time must be budgeted in course planning. Students must recruit volunteers outside the course, and preferably the major, for the assessments. If subjects are required to come from the campus or local community, the opportunity for service learning can exist. Fitness assessments can be graded on the basis of completion, and the inclusion of a practical examination at the end of the course creates motivation to develop greater proficiency. Benefits to students come in the form of both enhanced learning and testing skill, which contributes to professional development, as well as an opportunity to provide a service to the community by offering health information and exercise counseling based upon the results of the fitness assessments
Sex Differences in Perceptual Adaptations During Heat Acclimation in Endurance Runners
Get PDFExercising in the heat negatively impacts performance. To combat this, heat acclimation (HA) is used to mitigate performance decrements through various physiological and perceptual adaptations. However, perceptual adaptations may differ during HA due to physiological differences between females and males. PURPOSE: To investigate perceptual adaptations between sexes during 7-day HA in endurance runners. METHODS: Seven female and four male endurance runners (age: 22 ± 5 years, body mass: 64.30 ± 7.97 kg, height: 168.00 ± 6.43 cm, maximal oxygen uptake [VO2max]: 58.30 ± 4.28 mL/kg/min; age: 21 ± 4 years, body mass: 78.63 ± 9.01 kg, height: 182.55 ± 3.97 cm, VO2max: 73.93 ± 9.69 mL/kg/min, respectively) participated in this study. Participants completed a 7-day HA protocol consisting of running at 50% velocity at VO2max for 60 minutes in a hot condition (ambient temperature, 40℃; relative humidity, 35%). Perceptual variables, including rating of perceived exertion (RPE), fatigue, thirst level, and thermal sensation, were assessed every 10 minutes to investigate perceptual adaptations with HA. Two-way repeated measures ANOVAs were conducted to investigate perceptual adaptations between sexes during 7-day HA. RESULTS: There were no significant differences in maximum RPE, fatigue, thirst level, and thermal sensation between females and males (p \u3e 0.05). Independent of sex, RPE on day 5 (14 ± 4, p=0.036), day 6 (13 ± 4, p=0.012), and day 7 (14 ± 4, p=0.034), were significantly lower than day 1 (16 ± 4). Fatigue on day 2 (6 ± 2, p = 0.036), day 4 (6 ± 2, p = 0.024), day 5 (5 ± 2, p = 0.011), day 6 (5 ± 2, p = 0.006), and day 7 (5 ± 3, p = 0.009) were significantly lower than day 1 (7 ± 2). Thirst levels on day 2 (5 ± 2, p = 0.001), day 4 (5 ± 2, p = 0.035), and day 6 (5 ± 2, p = 0.012) were significantly lower than day 1 (6 ± 2). Thermal sensation on day 4 (7 ± 1, p = 0.03) and day 6 (7 ± 1, p = 0.012) were significantly lower than day 1 (7 ± 1). CONCLUSION: Endurance male and female runners exhibited beneficial perceptual adaptations following 7-day HA. However, no significant sex differences were observed. Ultimately, HA shows to be beneficial in endurance male and female runners alike and should be an integral part of preparing for competing in hot environments
Impact of Age on Firefighter Health and Fitness Outcomes
Get PDFResearch indicates that cardiovascular disease (CVD) risk among firefighters (FF) may be influenced by factors like oxidative stress, inflammation, low fitness levels, and body composition, with age potentially playing a role in risk variation. It is well established that age is an independent CVD risk factor, but limited data exist concerning the impact of age on FF health and fitness. PURPOSE: This study assessed the impact of CRF on the stress response to a live-fire training evolution (LFTE). METHODS: 144 FF completed an annual clinical health assessment. Shapiro-Wilk Test was used to assess normality. One-way ANOVA or Kruskal-Wallis tests (if normality was violated) assessed differences in CVD risk biomarkers and fitness and body composition metrics (determined via a dual-energy X-ray absorptiometry scan) between age groups (i.e., 20-29, 30-39, 40-49, 50+). Partial Eta squared (ηₚ²) values were used to determine effect sizes. RESULTS: Significant differences were found across age groups in low-density lipoprotein concentrations (p=0.002, ηₚ²=0.102), triglycerides (p\u3c0.001, ηₚ²=0.122), VO₂max (p\u3c0.001, ηₚ²=0.222), push-ups (p\u3c0.001, ηₚ²=0.191) and fat mass (p=0.027, ηₚ²=0.063). Higher fasting insulin levels (p=0.000, ηₚ²=0.163) were observed in the 50+ age group. Notable values were observed for Framingham risk score (p\u3c0.001, ηₚ²=0.805) and visceral adipose tissue (VAT; p\u3c0.001, ηₚ²=0.301) across all age groups. Compared to firefighters aged 20-29, 10-year CVD risk (p\u3c0.001, ηₚ²=0.519) was higher for those aged 40-49 and 50+. Overall, firefighters aged 20-29 demonstrate better health and fitness profiles than their older counterparts. CONCLUSION: These data suggest significant differences in CVD risk biomarkers, physical fitness levels, and body composition metrics across age groups among FF, an occupation whose number one cause of line-of-duty death is sudden cardiac death. The high effect sizes for Framingham risk score, 10-year CVD risk, and VAT highlight their potential as CVD risk predictors. Age-specific health interventions are recommended to manage and mitigate CVD risk effectively over time in this population
Effects of Acute Lower Body Resistance Exercise on Body Composition Parameters Assessed by DXA
Get PDFDual-energy X-ray-absorptiometry (DXA) analysis has the capability to measure bone mineral content (BMC), fat mass (FM), and lean mass (LM), also known as a 3-compartment model. Various factors such as exercise, hydration status, glycogen status, and others are thought to influence the accuracy of DXA estimated body composition. PURPOSE: The purpose of this study is to investigate acute changes in DXA LM and FM results pre-and-post prescribed lower body exercise compared to a non-exercise treatment. METHODS: Participants (n = 14; 22.71 ± 1.63 years; 169.42 ± 13.23 cm; 80.79 ± 17.71 kg) completed each trial that consisted of two treatments in a randomly assigned crossover experimental design: resting conditions (REST) or a prescribed lower body workout (LBRE) consisting of 4 sets of 12 repetitions on leg press, leg curls, leg extension, and kettlebell squat. At each visit, height, weight, and urine specific gravity were measured. DXA scans were performed before and 60 mins after REST or immediately after LBRE. Linear mixed-effects models were used to evaluate each outcome variable. The fixed effects included time, condition, and their interaction. Random intercepts were included to account for between-participant variability. The model was fitted using restricted maximum likelihood estimation. Data was analyzed using R software. RESULTS: DXA total mass, total LM, total FM, and total body fat percentage were unaffected by the lower-body exercise session (p\u3e0.05 for all model coefficients). Similarly, no segmental LM or FM variables were influenced by the exercise session (p\u3e0.05 for all model coefficients). CONCLUSIONS: An acute bout of lower body resistance exercise does not meaningfully influence DXA estimates of body composition parameters in a recreationally active population. Thus, guidelines suggesting to abstain from resistance exercise prior to a DXA might not be essential, which could allow for greater flexibility in scheduling of body composition assessments
Pilot Study: Effects of Resistance Training on DEXA and DARI Metrics in NCAA Division I Cross-Country Athletes
Get PDFINTRODUCTION: Cross-country athletes often prioritize endurance training, which, while crucial for performance, can lead to overlooked aspects of athletic development such as muscular strength, mobility, and bone health. Resistance training (RT) is a recognized strategy to address these potential deficits and enhance overall athletic performance. PURPOSE: The study aimed to evaluate the effects of incorporating RT on body fat percentage (%BF), bone mineral density (BMD), and dynamic performance metrics in NCAA Division I cross-country athletes. METHODS: Thirteen collegiate athletes (11 males/2 females; mean age = 19.6 yrs) participated in this pilot study. Pre-season (August) and in-season (November) assessments included dual energy x-ray absorptiometry scans (DEXA, Hologic) to measure %BF and BMD, as well as DARI®motion analysis to evaluate dynamic performance metrics such as shoulder mobility, rotational mobility, single-leg squats, squat depth, vertical jump, and balance. Athletes completed twice-weekly resistance training (RT) sessions focused on compound movements performed at 65–80% of 1RM, including exercises like squats, trap bar deadlifts, and hip thrusts. Sessions also incorporated mobility work to enhance movement quality and progressed to muscle endurance exercises as the competitive season approached. During the in-season phase, a deload phase was implemented prior to competition to prioritize recovery and ensure peak performance. Due to the demands of the competitive season, no control group was included. Paired t-tests were used to analyze changes in from pre- to in-season measures. RESULTS: No significant difference was observed in motion analysis scores (644 ± 234 vs 686 ± 114, t(11) = 0.88, p = 0.396). Changes in BMD were also not significant (1.20 ± 0.10 vs 1.21 ± 0.11, t(11) = -0.48, p = 0.644); variability ranged from -1.1% to +2.9%, with most athletes maintaining or improving their BMD. Similarly, changes in %BF were not significant (14.1 ± 2.7 vs 14.8 ± 2.9, t(11) = -1.64, p = 0.131); %BF changes ranged from -0.5% to +3.7%. CONCLUSION: Resistance training may support athletic performance and bone health in endurance athletes, though changes in DARI® scores, BMD, and %BF were not statistically significant. Training adherence, fatigue, and individual variability likely impacted these results. Future research with larger samples, control groups, and detailed monitoring is needed to better understand resistance training’s effects on performance, body composition, and bone health in cross-country athletes
Validity of a Portable Metabolic Analyzer for Estimating Resting Metabolic Rate in Muscular Resistance-trained Adults
Get PDFAn individual’s resting metabolic rate (RMR) is commonly the largest contributor to total daily energy expenditure. The accepted reference method for in vivo measurement of RMR is indirect calorimetry (IC). However, the accessibility of traditional IC analyzers is limited to select settings; therefore, portable indirect calorimeters are also applied to estimate RMR. Limited data are available to inform the validity of the VO2 Master for estimating RMR in muscular resistance-trained adults. PURPOSE: The purpose of this study was to determine the validity of the VO2 Master portable metabolic analyzer for estimating RMR in muscular resistance-trained adults. METHODS: A sample of 38 resistance-trained adults (15 F, 23 M; [mean ± SD] age 28.0 ± 7.9 y, height 172.0 ± 9.6 cm, weight 77.6 ± 12.9 kg, body fat% 17.5 ± 5.2, fat-free mass index 21.5 ± 2.9 kg/m2) underwent metabolic assessment via a metabolic cart (IC) and a portable metabolic analyzer (VO2 Master) in a single visit. RMR estimates obtained from IC were considered the reference values. Equivalence testing was used to evaluate whether the VO2 Master demonstrated equivalence with IC. Null hypothesis significance testing was also performed, and Bland-Altman analysis was used alongside linear regression to assess the degree of proportional bias. Constant error (CE), mean absolute error (MAE), and 95% limits of agreement (LOA) were also calculated. RESULTS: The mean ± SD RMR estimates for IC and the VO2 Master were 2192.7 ± 408.8 kcal/d and 1798.2 ± 418.8 kcal/d, respectively. The CE and MAE were -394.6 kcal/d and 419.1 kcal/d, respectively. Additionally, no proportional bias was observed, but wide LOA were present, and the VO2 Master did not demonstrate equivalence with IC. CONCLUSION: Given these findings, the consistent underestimation by the VO2 Master indicates that it may not be suitable for application in muscular resistance-trained adults. While noteworthy, fat-free mass contributes to a considerable portion of variance within RMR, and it has been suggested that the relationship between underprediction bias and RMR is likely a result of greater fat-free mass
Does Probe Positioning and Pressure Effect the Reliability of M-wave Max?
Get PDFAppropriate assessment of nerve function is vital to establish the outcomes of neuromuscular excitability, muscle activation, and the standardization of electromyographic data. Further, the determination of this measure has clinical relevance in the diagnosis of nerve disorders. However, factors such as probe orientation and pressure may lead to inconsistencies in the accurate assessment of nerve function. PURPOSE: The purpose of this study was to determine the interrater reliability of varying probe orientations and pressures on the maximal m-wave (M-wavemax). METHODS: Fourteen females and ten males (age: 20.9 ± 2.2yrs) underwent electrical stimulation to the median nerve and M-wavemax was recorded in the abductor pollicis brevis. Two raters administered five conditions on separate visits to evaluate the effects of varying probe orientations and pressures on the M-wavemax response. Measures included a 1) parallel (PAR) probe nerve orientation with a pressure of 4-6 N; 2) PAR probe nerve stimulation with a pressure of 9-11 N; 3) perpendicular (PERP) nerve orientation with a pressure of 9-11 N, 4) stimulation disc electrodes in the PAR and 5) PERP direction. The intraclass correlation coefficient (ICC) was calculated for interrater reliability. The reliability of two raters was assessed using a two-way mixed model (ICC[2,1]). RESULTS: Regarding the PERP orientation, there was moderate reliability for the 9-11 N and stimulation disc electrodes (ICC(2,1) = 0.57, p = 0.003, M = 14.77, SE = 5.02; ICC(2,1) = 0.65, p = 0.211, M = 14.88, SE = 4.30; respectively). Similarly, in the PAR orientation, there was moderate reliability for the 9-11 N and stimulation patches (ICC(2,1) = 0.53, p = 0.952, M = 14.20, SE = 5.02; ICC (2,1) = 0.56, p = 0.889, M = 14.52, SE = 5.13; respectively). Lastly, in the PAR orientation, there was poor reliability for 4-6 N (ICC(2,1) = 0.33, p = 0.821, M = 13.61, SE = 5.99). CONCLUSION: The poor and moderate reliability indicate varying levels of consistency between the measurements acquired. This is meaningful in clinical applications because measurement reliability is crucial in the effectiveness of diagnosis and treatment. These findings suggest appropriate standardization should be emphasized to increase reliability in common peripheral nerve stimulation
Impact of an Outdoor Physical Activity Intervention on Muscular Fitness in Adolescents
Get PDFPhysical inactivity among adolescents is a growing health concern. Innovative, engaging interventions are needed, such as after-school programs to promote physical activity and improve youths’ health, including muscular fitness. PURPOSE: The purpose was to evaluate the impact of an outdoor physical activity intervention on muscle strength, muscle endurance, and agility in middle school students. METHODS: The intervention included various physical activities (e.g., kayaking, orienteering/hiking, archery, disc golf, mountain biking), across 10 sessions over 5 weeks. Seven 6th and 7th graders (age: 11.7 ± 0.2 years; BMI: 24.7 ± 2.7) completed pre and post intervention assessments for muscle strength, muscle endurance, and agility. A portable isometric dynamometer (Microfet 2; Hoggan Scientific, Salt Lake City, UT) was used to measured muscular strength and muscular endurance of leg (knee extension) and arm (shoulder extension) musculature. For both muscle groups, participants pushed as hard as possible against the dynamometer for 3s, rested for 3s, and repeated this cycle for 20 repetitions. Verbal encouragement was provided. Strength was defined as the maximum force produced during the 20 contractions. Muscular endurance was calculated using fatigue index (FI), calculated by dividing the minimum force produced by the maximum force. Muscular endurance is also expressed as a percent change from the maximum contraction force to the lowest force produced during the last five contractions. Participants also performed the agility T-test, completing two trials with 30s rest between trials. The fastest time was used for analysis. T-tests were used to determine statistical significance for pre-post changes, and Cohen’s d (effect size) was calculated to determine the practical meaningfulness of these changes. Data are reported as mean ± SE. RESULTS: While t-tests were not significant, effect sizes indicated small or medium effects for 5 of 7 variables. Leg strength improved from pre (39.40 ± 4.52 lbs) to post (48.23 ± 6.79 lbs) with a medium effect (d = 0.61; p = 0.156), and arm strength also increased from pre (18.74 ± 4.32 lbs) to post (20.46 ± 3.75 lbs) with a medium effect (d = 0.56; p = 0.191). Leg muscular endurance improved from pre (FI: 0.57 ± 0.06) to post (FI: 0.64 ± 0.06) with a medium effect (d = 0.52; p = 0.217), while there was no change in muscular endurance of the arm: pre (FI: 0.67 ± 0.03) and post (FI: 0.67 ± 0.04) (d = 0.04; p = 0.912). Leg endurance expressed as percent change showed an improvement from pre (-27.44 ± 5.83%) to post (-19.61 ± 5.04%) with a small effect (d = 0.33; p = 0.420), while the percent change in arm endurance was stable pre (-20.55 ± 3.56%) and post (-21.77 ± 3.61%) (d = 0.13; p = 0.745). Agility improved from pre (16.42 ± 1.18s) to post (15.87 ± 0.78s) with a small effect size (d = 0.38; p = 0.353). CONCLUSION: Results demonstrate that the outdoor physical activity intervention had a meaningful impact on leg strength and endurance, arm strength, and agility, while the effects on arm muscular endurance remained stable. Activities involved hiking hills and biking, which likely contributed to lower extremity improvements. Future programs should focus on enhancing muscular fitness through diverse outdoor physical activities that incorporate both lower and upper extremities. Funding: Social Innovation Research Accelerator Grant, Texas State University to LK, JM, KG
Effect of Advanced Footwear Technology in Trail Running Shoes on Running Economy
Get PDFRunning economy (RE), a measure of a runner’s oxygen consumption or energy expenditure at a fixed speed, is an important endurance performance determinant. Advanced footwear technology (AFT), such as resilient and compliant midsole foams with an imbedded carbon-fiber plate, have previously been incorporated into road racing shoes to improve RE. AFT features are now being utilized in trail running shoes, but the efficacy has not been determined. PURPOSE: Determine the effect of an AFT trail running shoe on RE relative to a traditional trail shoe over trail and treadmill surfaces. METHODS: Eight runners reported for two separate visits, which included one session on a dirt/gravel trail outdoors and one session on a stiff treadmill indoors. Each visit, subjects completed 4 x 1500m trials wearing both an advanced shoe (AFT) and a control shoe (CTRL) in a duplicate, mirrored order. Thus, shoes were tested in either an ABBA or BAAB sequence, counterbalanced across subjects. Oxygen consumption (VO2) was measured with a calibrated portable metabolic cart, and the average values of the final 1000m of each 1500m trial were calculated. Subjects completed the trail running session first. They were directed to run the trials at self-selected 50k race effort. RE was calculated as VO2 expressed as cost of transport (CoT; ml/kg/km) to normalize for running speed. A high CoT is indicative of worse RE. Subjects completed the treadmill session ~1-2 weeks following the trail session. Treadmill speed was fixed to match the average speed of each individual subject’s trail trials. RE was analyzed by a 2-way (surface x shoe) repeated-measures ANOVA. RESULTS: There was a significant main effect for surface (p \u3c .001) with the treadmill (209.0 ± 14.9 ml/kg/km) offering a 5.2 ± 2.3% CoT benefit relative to the trail (220.7 ± 16.1 ml/kg/km), independent of shoe. There was no significant effect for shoe (p = .105), but CoT was on average 1.0 ± 1.5% lower with AFT (208.1 ± 14.8 ml/kg/km) compared to CTRL (210.2 ± 15.6 ml/kg/km), independent of surface. There was also no surface x shoe interaction (p = .800), as the CoT benefit of AFT was 1.0 ± 1.1% over the trail and 0.8 ± 3.1% on the treadmill. CONCLUSION: We found that running overground on the trails significantly increased energy use regardless of shoe. While we did not see a significant benefit of AFT in trail shoes with the current sample of data, there is likely a small effect that can be observed with an expanded sample size. Nonetheless the magnitude of these effects (~1%) are smaller than those observed previously with AFT in road racing shoes (~2.7-4%) at faster speeds. Since there was not a difference in our data between the AFT trail shoe benefits on the trail vs. treadmill, this reduced benefit is not likely a surface effect. Instead, it may have more to do with the slower speeds tested, as we have previously shown a reduced benefit of AFT in road racing shoes at slower paces
AI-Driven Insights from the NFL Scouting Combine: Principal Component Analysis, K-Means Clustering, and Regression for Predicting Draft Position and Status
Get PDFThe NFL Scouting Combine provides prospective professional American football players the opportunity to demonstrate physical performance abilities and position-specific skills in a series of standardized assessments, though the current understanding of the influence of these tests on draft status and position remains unclear. PURPOSE: This study evaluates the NFL Combine\u27s physical tests for explaining variance in performance within positions and predicting relative draft position (RDP) and draft status (DS). METHODS: Players (n=1234) were categorized into four position groups (PG) using k-means clustering: quarterbacks (QB), skill, linemen, and mid-size. Predictors included results of the six NFL Combine tests, height, weight, power, and momentum. Only players who completed all combine assessments were included (n=1234). Principal Component (PC) analysis with oblimin rotation and Horn’s parallel analysis reduced data dimensionality for each PG. Linear mixed models and binary logistic regression were used to predict the impact of PCs on RDP and DS for each position. RESULTS: Two to three meaningful PCs (adjusted eigenvector ≥ 1) were identified for each PG with the first PC universally representing momentum metrics, explaining 33-45% of intra-PG variance. PCs significantly associated with RDP were identified for all PGs but defensive backs and running backs, while PCs significantly associated with DS were found for all PGs except QBs and power running backs (p0.05), and 10/26 PCs showed no significant relationship with DS (p\u3e0.05), suggesting that physical performance alone does not account for most variability in RDP once underlying physical thresholds to be drafted are met. CONCLUSION: The NFL Combine physical performance tests inconsistently predict DS and RDP but should not be overlooked during draft preparation. Prospects should prioritize position-specific skills and game performance over optimizing these test results. Future research should explore the influence of these components on NFL career success and longevity