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EFFECTS OF SODIUM BICARBONATE ON MARKERS OF KIDNEY INJURY DURING REPEATED SPRINTS IN THE HEAT
No full textPURPOSE: To investigate if sodium bicarbonate (SB) supplementation reduces markers of acute kidney injury (AKI) after maximal repeated sprints in the heat. METHODS: Using a randomized, crossover, double-blind design, 10 endurance athletes (4 female) ingested capsules containing 0.2 g/kg of SB or placebo 1 hr before exercise. Participants completed a 22 min cycling warm-up followed by 4 sets of 5x6-sec maximal sprints (24 sec rest between sprints, 5 min rest between sets) on a cycle ergometer in a heat chamber (40 °C, 20% RH). Core temperature (Tc) was recorded at baseline and post-exercise. Urine samples were collected pre-capsule ingestion and pre-, post-, and 1 hr post-exercise to measure urine flow rate (UFR), specific gravity (USG), and pH. Urine samples from pre-ingestion and 1 hr post-exercise were analyzed for the product of insulin-like growth factor-binding protein 7 and tissue inhibitor of metalloproteinase 2 (IGFBP7•TIMP2), a biomarker of AKI risk. Blood was collected pre-ingestion, pre-, and post-exercise to estimate bicarbonate (HCO3). RESULTS: Blood HCO3 was higher in the SB post-ingestion (SB: 26 ± 2 mmol/L, Placebo: 22 ± 2 mmol/L; p = 0.03) but not different pre-ingestion or post-exercise (p \u3e 0.05). There were no differences between conditions for USG or UFR (p \u3e 0.05). Tc increased from pre- to post-exercise (p \u3c 0.01), with no differences in post-Tc between SB (38.1 ± 0.4 °C) and placebo (38.0 ± 0.4 °C) (p = 0.25). SB increased urine pH at pre- (6.9 ± 0.9 vs 6.1 ± 0.2; p \u3c 0.01), post- (7.6 ± 0.8 vs 6.0 ± 0.2; p \u3c 0.01), and 1 hr post-exercise (8.1 ± 1.1 vs 6.0 ± 0.2; p \u3c 0.01) versus placebo, respectively. IGFBP7•TIMP2 increased from pre- to 1 hr post-exercise (p = 0.01), but there was no condition effect (p = 0.06). Although not statistically significant, concentrations at 1 hr post were 2.5x lower on average in the SB (0.30 ± 0.30 ng/mL2/1000 vs 0.74 ± 0.79 ng/mL2/1000), which may have clinical relevance. Additionally, 6 participants in the placebo exceeded the 0.3 ng/mL2/1000 threshold for increased risk of AKI, while only 4 participants passed this threshold in the SB. Notably, a negative correlation was observed between post-exercise blood HCO3 and ΔIGFBP7•TIMP-2 (R = -0.64, p \u3c 0.01). CONCLUSION: SB supplementation before repeated maximal sprints in the heat may attenuate the risk of AKI, but further research is needed
RELIABILITY AND VARIABILITY OF FIELD-BASED SWEAT ASSESSMENT TOOLS
No full textMonitoring sweat rate and composition helps develop individualized athlete hydration strategies to prevent dehydration and its physiological effects. PURPOSE: This study evaluated the variability and reliability of four low-cost, field-based sweat assessment tools for measuring sweat rate and sweat sodium concentration. METHODS: A 28-year-old endurance-trained female completed 10 trials. Each 60-minute cycling trial was conducted at 145 watts in an 80°F, 30% humidity chamber. Sweat rate and sodium concentration were assessed via Whole Body Displacement Method (WBDM, sweat rate only), GX Patch, Nix Biosensor, Hdrop Sensor, and Horiba Laqua Twin (sodium only). Measurements were analyzed for inter-device variability and test-retest reliability using Bland-Altman plots, Intraclass Correlation Coefficients (ICC), and Coefficient of Variation (CV). RESULTS: Fluid loss CV was lowest with the GX patch (3.9%), while WBDM (23.9%), Nix (18.4%), and Hdrop (13.7%) had higher variability. For sodium, Horiba was the most reliable (10.1%), while Nix (27.9%), Hdrop (20.7%), and GX (14.1%) showed greater variability. Bland-Altman analysis showed GX best agreed with Horiba (mean diff: -32.8, LOA: -204.5 to 138.8). Hdrop showed the largest sodium discrepancies vs. Nix (-1498.6, LOA: -2298.9 to -698.2) and Horiba (-1571.9, LOA: -2471.4 to -672.4). The best fluid agreement was Nix vs. Hdrop (mean diff: -182.2, LOA: -758.3 to 393.9), while the weakest was WBDM vs. Hdrop (-762.4, LOA: -1168.6 to -356.3). ICC showed poor agreement overall, with WBDM and Nix highest for fluid (0.47), and GX and Horiba for sodium (0.28), though not statistically significant. CONCLUSION: Some tools offer more consistent, reliable measurements. GX showed the best consistency for fluid (CV 3.9%), and Horiba for sodium (CV 10.1%). ICC results suggest limited agreement between tools. This study highlights the need to understand the accuracy of low-cost sweat assessment tools used in athlete hydration planning
CHANGES TO PHYSICAL ACTIVITY LEVELS WITH IMPLEMENTATION OF AN EMPLOYEE WELLNESS PROGRAM
No full textINTRODUCTION: Employee wellness programs impact physical activity (PA) levels which can lead to increased overall activity and improved health. These programs provide a supportive framework for regular PA and motivate participants to engage in autonomous workouts. METHODS: University employees (N=23) participated in a 10-week wellness program. The International Physical Activity Questionnaire (IPAQ) measured exercise volume in walking, moderate, vigorous, and total MVPA categories. Participants were grouped based on total volume: inactive (n=9; IA=/min/wk-1), minimally active (n=11; MA=600-3000 MET/min/wk-1 ), very active (n=3; VA=\u3e3,000 MET/min/wk-1). Participants also responded to questions about exercise habits. Dependent t-tests analyzed changes within each group from pre- to post-test. RESULTS: Dependent t-tests revealed no significant difference within groups (p\u3e.05). Moderate to large effects were seen in all groups. Crosstabs revealed 8 of 9 IA individuals moved to a higher PA category, as well as 7 of 11 MA participants. Two individuals (8.7%) reported they would not continue exercising autonomously. Lack of accountability or creation of a habit were cited as reasons. Two primary reasons for continuing exercise autonomously were enhanced exercise knowledge and creation of a routine. CONCLUSIONS: PA was most effectively increased in the MA group. Providing education to master exercise and creating an accountable routine are important for modifying PA behavior
CAN LEADING A PHYSICALLY ACTIVE AND HEALTHY LIFESTYLE PREVENT GAINING THE FRESHMAN 15?
No full textPURPOSE: The purpose of this study is to investigate if leading a physically active and healthy lifestyle can prevent the weight gain typically experienced during the freshman year of college – the ‘Freshman 15.’ METHODS: Study participants (N = 525) were from three cohorts of incoming students (2018–2020) at a mid-sized university in the West South-Central United States. The weight of each study participant was measured at three points over a year: beginning of their first semester, beginning of their second semester, and beginning of their third semester. During the study, students were encouraged to lead physically active and healthy lifestyles and to exercise daily. Weight changes at six-month and one-year intervals were recorded as percentages. RESULTS: Freshmen weight gain/loss depended upon initial weight, with freshmen who arrived on campus with relatively lower weights (\u3c 100 kg) tending to gain weight, especially males, while freshmen who arrived on campus with relatively higher weights (\u3e 100 kg) tended to lose weight. This finding was both more apparent and more statistically significant at the 1-year mark than at the 6-month mark. CONCLUSIONS: Several previous studies have linked freshmen weight gain to initial weight, with students with higher initial weights gaining the most. However, our results show that maintaining a physically active and healthy lifestyle when entering college reverses this trend – with students with high initial weights losing weight. Thus, living a physically active and healthy lifestyle, which includes aerobic exercise, can prevent the fat mass weight gain often experienced by college freshmen
EFFECTS OF LEFT FOREARM MUSCLE METABOREFLEX ACTIVATION ON RIGHT VASTUS LATERALIS MOTOR UNIT BEHAVIOR
No full textMuscle metaboreflex is a physiological response triggered by metabolite accumulation during muscle activity, which increases sympathetic nervous system activity. Although muscle metaboreflex activation (MMA) and cardiovascular responses are well studied, less is known regarding its effect on motor unit (MU) behavior. PURPOSE: To investigate the effects of MMA on MU recruitment and firing rate patterns. METHODS: Sixteen lower-body resistance trained males (21 ± 2 yrs, 179.52 ± 7.87 cm, 84.87 ± 13.42 kg) performed isometric maximal voluntary contractions (MVCs) of the right knee extensors. Participants then completed isometric handgrip dynamometer MVCs of the left hand, followed by a 2 minute 30% MVC isometric handgrip muscle action. For the MMA treatment, arterial occlusion of the left arm at supra-systolic pressure (≥ 250 mm Hg) was initiated the last 10 secs of the 30% MVC, and remained on during a 40% MVC trapezoidal muscle action for the right knee extensors. For control (CON), blood flow was not occluded during the hand grip- or knee extensor-muscle actions. Treatments were randomized. Surface electromyographic (EMG) signals were recorded from the vastus lateralis (VL) during the knee extensor muscle actions. For the 40% MVCs, EMG was decomposed for analysis of MU: recruitment thresholds (RT), action potential amplitudes (MUAPAMPS), and mean firing rates (MFR). EMG amplitude (EMGRMS) was normalized (N-EMGRMS) to MVC EMGRMS. MMA was assessed via mean arterial pressure (MAP) changes. Y-intercepts (y-ints) and slopes were calculated for the MUAPAMP and MFR vs. RT relationships during MMA and CON. Nine paired samples t-tests were used to compare MAP, y-ints and slopes for the MUAPAMP and MFR vs. RT relationships, and N-EMGRMS between treatments. Alpha was ≤ 0.05. RESULTS: There were no significant differences for the y-ints or slopes of the MUAPAMP or MFR vs. RT relationships. However, there were significant differences for MAP (MMA = 21.75 ± 13.75 mm Hg, CON = 41.98 ± 17.73 mm Hg; p \u3c 0.001) and N-EMGRMS (MMA = 43.37 ± 7.76%, CON = 48.34 ± 11.91%; p = 0.015). CONCLUSION: MMA of the left forearm decreased N-EMGRMS of the VL, suggesting a downward shift in the N-EMGRMS–torque relationship. Therefore, less excitation to the MU pool of the VL was required to match the same submaximal torque of the knee extensors during MMA
Mission success: mastering muscle function through humanoid analysis
Get PDFKnowledge of muscle function and human movement are essential skills of all kinesiology students. In the humanoid activity, teams are challenged to determine whether a muscle is essential to the successful development of a humanoid being sent to Mars. This activity provides a significant learning experience regarding muscle anatomy, function, and movement analysis. The humanoid activity is intended for use in a face-to-face upper-level kinesiology anatomy or movement analysis course and best implemented with class sizes of 20-30 students. The total time commitment is approximately 45 minutes
Assessing Accuracy of Smartwatch-based Estimation of Maximum Oxygen Consumption Using Different Watches
Get PDFMaximal oxygen consumption (VO2max) is a predictor of overall health and a key measure of cardiovascular fitness and aerobic capacity. As wearable technology advances, smartwatches are increasingly used to track cardiovascular health metrics. PURPOSE: The purpose of this study was to evaluate the validity and reliability of maximal oxygen consumption estimates from two leading smartwatches. METHODS: 15 participants (11M, 4F), aged 19-29 (23.8±3.2) years, were recruited and met inclusion criteria for the study. VO2max for all participants was determined in a controlled laboratory environment using a metabolic gas analyzer. Subjects completed a graded exercise test on a treadmill until reaching subjective exhaustion. This value was then compared with the estimated VO2max values from two smartwatch devices (Watch A, Watch B), calculated while wearing the watches for at least 3 consecutive days and measured directly after an outdoor run. The watches were synced between runs and returned after the study period. Baseline descriptive data calculations were performed. Reliability was measured using Intraclass Correlation Coefficient (ICC). Bland-Altman analyses were utilized to explore VO2max values. RESULTS: Measured VO2max in the lab setting was significantly lower than the predicted VO2max (mL·min-1·kg-1) from Watch A (mean 45.28±6.51 vs. mean 48.68±7.03) (p=.041) and Watch B (mean 47.69±8.64 vs. mean 52.83±5.83) (p=.041) with a medium effect size. ICC average measures (2,2) for Watch A (0.836, p=.003) and for Watch B (0.856, p=.001) suggested good reliability for VO2max estimates for both watches and the lab setting measurements. Bland-Altman analyses confirmed overestimation and consistent agreement. CONCLUSION: Both smartwatches tended to overestimate VO2max compared to lab measurements but exhibited good reliability across trials. Either device may be acceptable for recreational users to track VO2max outside of a laboratory setting. However, healthcare professionals should be aware of estimation limitations when prescribing intensity for cardiorespiratory fitness
Impact of Years of Experience on The Stress Responses to Firefighting
Get PDFResearch demonstrates that firefighters (FF) experience elevated stress levels during live fire-training evolution (LFTE) scenarios, which is posited to exacerbate cardiovascular disease (CVD) risk. However, whether these occupational stress response levels differ as an FF gains experience in the field has yet to be evaluated. PURPOSE: This study assessed the differences in stress response to a LFTE between FF with greater years of experience. METHODS: Forty-four (n=44) FF completed an annual clinical health assessment. Years of experience were used to delineate between less experienced (LOW; \u3c6 years) and experienced FF (EXP). Salivary samples were collected baseline (BL), immediately post (POST), and 30- min post the LFTE and analyzed for α-amylase (AA), secretory immunoglobulin-A (SIgA), and cortisol (CORT). Data were analyzed via a general linear model (GLM) multivariate and univariate analysis. RESULTS: GLM analysis revealed an overall time effect (p\u3c0.001, ηₚ²=0.216) with no group x time effect (p=0.796, ηₚ²=0.019) for the salivary stress biomarkers. The univariate analysis revealed time effects for AA (p\u3c0.001, ηₚ²=0.244), SIgA (p\u3c0.001, ηₚ²=0.261), and CORT (p=0.003, ηₚ²=0.133); however, no group x time effects were found for AA (p=0.481, ηₚ²=0.011), SIgA (p=0.817, ηₚ²=0.003), and CORT (p=0.511, ηₚ²=0.016). Immediately post-LFTE concentrations were significantly higher for AA (p\u3c0.001), SIgA (p\u3c0.001), and CORT (p=0.004) than at baseline. A significant group effect was found for AA (p=0.049, ηₚ²=0.089), with the LOW group having lower overall AA concentrations than the EXP group, whereas there were no group effects for CORT (p=0.427, ηₚ²=0.015) or SIgA (p=0.204, ηₚ²=0.038). CONCLUSION: These data demonstrate that years of experience do not impact the stress response to an LFTE. It is plausible that years of job experience can influence one’s ability to deal with occupational stress, yet future work should elucidate the impact of stress on CVD risk and occupational performance
Examining the Relationship of E-Cigarette Vapor Exposure and Exercise Performance in Aerobically Trained Rats
Get PDFElectronic cigarettes, or e-cigarettes, are alternatives to traditional cigarettes and they are rapidly growing in popularity. These electronic nicotine delivery systems heat up nicotine and vehicle liquids to deliver nicotine to the user via vapor rather than smoke. Although they are touted as a “healthier” alternative to smoking, vape use is associated with changes in heart rate and blood pressure, increased lung inflammation, and reduced mucociliary clearance. Such physiological changes may have an effect on exercise performance and athletic ability. PURPOSE: This study’s purpose was twofold: to train rats to successfully run on a treadmill, and to evaluate the relationship of e-cigarette vapor exposure and exercise performance in rats. Exercise performance was defined as time spent running, distance run, and peak speed reached. METHODS: An encased SEDACOM two lane treadmill and its accompanying treadmill controller was used to train adult female Long-Evans Rats (n=8) in a 9 week training program. Once all rats were able to run at 40 cm/s, a pre-exposure exercise test was performed to evaluate exercise performance. The test was a graded exercise test that increased speed until exhaustion. Each rat was then randomly assigned to either the control group (n=4) or the vape group (n=4). Both groups continued training according to the training protocol, but the vape group was also exposed to 5% nicotine vapor for 10 minutes a day for 7 days using a whole-body exposure chamber. Following the week of training and vape exposure, a post-exposure exercise test was performed on all rats to evaluate peak speed, distance run, and time run. The post-exposure exercise test followed the same protocol as the pre-exposure exercise test. RESULTS: Peak speed, distance run, and time run were compared to each other through three separate 2 x 2 (Group x Time) Mixed Model ANOVAs. There was no main effect of Group or Time on exercise performance, nor an interaction between the two. The most notable result, though not statistically significant, was the effect of time (pre-exposure test vs post-exposure test) on time run (F(1,6)=0.182, p=0.684, ƞp2 = 0.03). The control group increased their time run from pre-exposure test (M = 1499.3 s SD = 971.6 s) to post-exposure test (M = 1579.6 s, SD = 690.3 s), compared to the vape group’s increase from pre-exposure test (M = 1442.5 s, SD = 710.0 s) to post-exposure test (M = 1478.1 s, SD = 576.3 s). Some behavioral observations in the rats, such as seeking more physical assistance while running or accumulating shocks faster than before exposure, indicate an immeasurable effect of vaping on fatigue. CONCLUSION: Ten minutes of exposure to e-cigarette vapor per day for 7 consecutive days isn’t enough to significantly affect exercise performance in rats. Further studies will investigate how much e-cigarette vapor exposure is needed to have an effect on exercise performance, as well as its ability to affect aerobic versus anaerobic exercise
Timbersports Relationship Between Upper Body Biomechanics and Accuracy
Get PDFTimbersports are relatively new in comparison to most traditional sports. Given how new of a sport this is, there have been less than 5 recorded studies across every discipline. Most of the previous studies have presented data for the individual\u27s trunk and lower body, but no study yet has examined the upper body kinematics to date. PURPOSE: Given this information, we decided to conduct a study exploring the relationship between upper body biomechanics and accuracy among a college timber sports team. METHODS: Subjects used a double-bit axe for throwing, most of the weight is in the head (1.35 kg), a bit (cutting edge) length of 15 cm, and a wooden handle that exits the head with a length of 52 cm. The axe throwers stood 5 meters from a target made of southern yellow pine planks that is 70.5 cm across. The bullseye in the middle of the target is a .25 cm dot that is 1.23 m above the ground. The only throws that counted for the study were throws in which the axe stuck in the target with only one side of the bit. If the axe did not stick in the target or had both bits stick, that throw did not count. Accuracy was measured as the distance of the nearest point of the axe bit to the bullseye. Target location was measured as the angle of the line between the bit and the bullseye on a vertical plane parallel to the target, and orientation was measured as the angle of the axe handle perpendicular to the target. Inertial measurement units on the upper body were used to compute the angles of release from the elbows and shoulders. As this study is still in progress, we have data from four axe throwers with three trials completed each. Each trial was entered into the correlation as a unique case. RESULTS: There was a moderate correlation between the axe distance to center and the angle of the shoulder (r=.33). There was a moderate correlation between the accuracy and the angle of the shoulder(r=.35). There was a large correlation between the orientation and the angle of the shoulder(r=.67). There was a small correlation between the accuracy and angle of the elbow (r=.13). There was a moderate correlation between the location and the angle of the elbow (r=.31). There was a small correlation between orientation and the angle of the elbow (r=.19). CONCLUSION: Accuracy is related to each of the shoulder and elbow angles. The angle of the axe is dependent on the shoulder and elbow angles. The greater the angle of the shoulder is, the closer the axe lands to the bullseye and the greater the angle of the axe to the bullseye will be. The orientation of the axe is dependent on the location of the shoulder. The location of the axe in regard to the bullseye is dependent on the elbow angle. This study is necessary for the improvement and further learning of axe throwing performance