Effects of an Acute Strength and Conditioning Training Session on Dual-Energy X-Ray Absorptiometry Results.

Lytle, JR, Stanelle, ST, Kravits, DM, Ellsworth, RL, Martin, SE, Green, JS, and Crouse, SF. Effects of an acute strength and conditioning training session on dual-energy x-ray absorptiometry results. J Strength Cond Res 34(4): 901-904, 2020-The purpose of this study was to determine whether an athletic strength and conditioning (S&C) session will alter body composition estimates of a dual-energy x-ray absorptiometry (DXA) scan. Twenty-two strength-trained individuals (15 men, 7 women, 24 ± 2 years, 174.2 ± 8.5 cm, 83.5 ± 15.0 kg) volunteered to participate in the study. Each subject underwent 2 DXA scans, before and after completion of the S&C session, which consisted of upper- and lower-body resistance exercises and interval running. Subjects consumed a free-living meal before the first scan, after which only ad libitum water intake was consumed until completing the second scan. Results were analyzed through sex by time repeated-measures analysis of variance. If no interaction effect was observed, results were next analyzed through correlated t-test (α = 0.05). Significant sex by time interactions were observed for arm total and lean mass, as well as a significant main effect of time showing a decrease in arm lean mass after the S&C session. Values before and after the S&C session that resulted in significant differences via correlated t-test are displayed in Table 1. Results revealed a significant decrease in total mass, arm and leg percent fat, and trunk lean mass, and an increase in leg lean mass.

Predicting V[Combining Dot Above]O2max From Treadmill Performance in American-Style Football Athletes.

Crouse, SF, Tolson, H, Lytle, J, Johnson, KA, Martin, SE, Green, JS, Oliver, J, Carbuhn, A, Lambert, B, and Bramhall, JP. Predicting V[Combining Dot Above]O2max from treadmill performance in American-style football athletes. J Strength Cond Res 33(4): 1028-1034, 2019-Prediction equations are often used to estimate V[Combining Dot Above]O2max in the general population but are lacking for American-style football (ASF) athletes. We sought to develop a regression model to estimate V[Combining Dot Above]O2max from treadmill exercise time in ASF athletes and compare our football V[Combining Dot Above]O2max model with 2 published prediction equations (Foster et al., 1984, and Bruce, 1973). American-style football athletes (N = 472, age = 18 ± 1 year, height = 186.1 ± 8.2 cm, and body mass = 101.8 ± 20.4 kg) underwent treadmill exercise to voluntary exhaustion (Bruce protocol). Maximal exercise time was recorded in minutes (Tmin), and V[Combining Dot Above]O2max was simultaneously measured (M-V[Combining Dot Above]O2max, mlO2·kg·min) by an automated gas-analysis system. Athletes were then randomly divided into validation and cross-validation groups (n = 236). Linear regression yielded estimates of V[Combining Dot Above]O2max from Tmin as follows: validation V[Combining Dot Above]O2max = 4.012 × Tmin - 4.628 (r = 0.678, p < 0.001, and SEE = 4.07); cross-validation V[Combining Dot Above]O2max = 4.025 × Tmin - 4.693 (r = 0.661, p < 0.001, and SEE = -4.16). These equations had a cross-validation coefficient of 0.813 and a double cross-validation coefficient of 0.823. Differences between the slopes of the 2 equations were not significant (t-test, p = 0.9603). Because validation and cross-validation groups were not statistically different on any variables measured (multivariate analysis of variance, p > 0.05), all athletes were combined to yield our final prediction equation: football V[Combining Dot Above]O2max = 4.017 × Tmin - 4.644 (r = 0.670, p < 0.001, and SEE = 4.11). Repeated-measures analysis of variance demonstrated significant differences (p < 0.001) in estimates of V[Combining Dot Above]O2max among Foster (44.1 ± 6.1), Bruce (47.1 ± 5.5), and our football (45.1 ± 5.8) equations. Foster and Bruce V[Combining Dot Above]O2max estimates were also significantly different from M-V[Combining Dot Above]O2max ((Equation is included in full-text article.)diff = -0.975 and 1.995, respectively, p < 0.001). V[Combining Dot Above]O2max of ASF athletes can be reasonably estimated by our football prediction equation using maximal treadmill time as the predictor.

Physiological Stress Responses to a Live-Fire Training Evolution in Career Structural Firefighters.

OBJECTIVE: This study assessed firefighters' physiological stress response to a live fire training evolution (LFTE). METHODS: Seventy-six ( n = 76) firefighters completed an LFTE. Salivary samples were collected pre-, immediately post, and 30-min post-LFTE and analyzed for α-amylase (AA), cortisol (CORT), and secretory immunoglobulin-A (SIgA). RESULTS: Concentrations of AA, CORT, and SIgA were elevated immediately post LFTE versus pre (P<0.001) and 30-min post (P<0.001). Cohen's d effect size comparing pre and immediately-post means were 0.83, 0.77, and 0.61 for AA, CORT, and SIgA and were 0.54, 0.44, and 0.69 for AA, CORT, and SIgA, comparing immediately-post and 30-min post, respectively. CONCLUSIONS: These data demonstrate the stress response and activation of the hypothalamic-pituitary-adrenal/sympathetic-adreno-medullar axis and immune system immediately after real-world firefighting operations. Future work is needed to understand the impact of elevated stress biomarkers on firefighter performance and disease risk.

Firefighter Health: A Narrative Review of Occupational Threats and Countermeasures.

Structural firefighters are responsible for protecting properties and saving lives during emergency operations. Despite efforts to prepare firefighters for these hazardous occupational demands, the unfortunate reality is that the incidence of health morbidities is increasing within the fire service. Specifically, cardiovascular disease, cancer, and mental health disorders are among the most documented morbidities in firefighters. Pubmed and Google Scholar search engines were used to identify peer-reviewed English language manuscripts that evaluated firefighters' occupational health threats, allostatic factors associated with their occurrence, and evidence-based strategies to mitigate their impact. This narrative review provides fire departments, practitioners, and researchers with evidence-based practices to enhance firefighters' health.

Oral creatine supplementation's decrease of blood lactate during exhaustive, incremental cycling.

PURPOSE: To determine the effects of creatine supplementation on blood lactate during incremental cycling exercise. METHODS: Thirteen male subjects (M ± SD 23 ± 2 yr, 178.0 ± 8.1 cm, 86.3 ± 16.0 kg, 24% ± 9% body fat) performed a maximal, incremental cycling test to exhaustion before (Pre) and after (Post) 6 d of creatine supplementation (4 doses/d of 5 g creatine + 15 g glucose). Blood lactate was measured at the end of each exercise stage during the protocol, and the lactate threshold was determined as the stage before achieving 4 mmol/L. Lactate concentrations during the incremental test were analyzed using a 2 (condition) × 6 (exercise stage) repeated-measures ANOVA. Differences in power at lactate threshold, power at exhaustion, and total exercise time were determined by paired t tests and are presented as M ± SD. RESULTS: Lactate concentrations were reduced during exercise after supplementation, demonstrating a significant condition effect (p = .041). There was a tendency for increased power at the lactate threshold (Pre 128 ± 45 W, Post 143 ± 26 W; p = .11). Total time to fatigue approached significant increases (Pre 22.6 ± 3.2 min, Post 23.3 ± 3.3 min; p = .056), as did maximal power output (Pre 212.5 ± 32.5 W, Post 220 ± 34.6 W; p = .082). CONCLUSIONS: Our findings demonstrate that creatine supplementation decreases lactate during incremental cycling exercise and tends to raise lactate threshold. Therefore, creatine supplementation could potentially benefit endurance athletes.

Risk Factors for Cardiometabolic Disease in Professional Firefighters.

OBJECTIVE: Firefighters are plagued with cardiometabolic disease (CMD). Obesity, poor cardiorespiratory and muscular fitness, and blood lipids (low-density lipoprotein cholesterol, triglycerides, low high-density lipoprotein cholesterol) are risk factors for CMD. However, markers of oxidative stress, inflammation, and insulin resistance can provide further insight regarding CMD risk. METHODS: This study investigated the relationships between fitness metrics (cardiorespiratory and muscular fitness, percent body fat, waist circumference), blood lipids, blood pressure, and years of experience as a firefighter to blood markers of insulin resistance: Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), oxidative stress: advanced oxidation protein products (AOPPs), and inflammation: C-reactive protein. RESULTS: Waist circumference and blood concentrations of triglycerides were significantly related to AOPPs and HOMA-IR. Cardiorespiratory fitness was inversely related to AOPPs, HOMA-IR and C-reactive protein. CONCLUSION: These findings demonstrate the importance of high cardiorespiratory fitness and low waist circumference to reduce markers of CMD.

Assessment of Vascular Function in Response to High-Fat and Low-Fat Ground Beef Consumption in Men.

Red meat is stigmatized as an unhealthy protein choice; however, its impacts on vascular function have not been evaluated. We aimed to measure the vascular impact of adding either low-fat (~5% fat) ground beef (LFB) or high-fat (~25% fat) ground beef (HFB) to a habitual diet in free-living men. Twenty-three males (39.9 ± 10.8 years, 177.5 ± 6.7 cm, 97.3 ± 25.0 kg) participated in this double-blind crossover study. Assessment of vascular function and aerobic capacity were measured at entry and in the last week of each intervention and washout period. Participants then completed two 5-week dietary interventions (LFB or HFB; 5 patties/week) in a randomized order with a 4-week washout. Data were analyzed via 2 × 2 repeated-measures ANOVA (p < 0.05). The HFB intervention improved FMD relative to all other time points, while lowering systolic (SBP) and diastolic blood pressure (DBP) relative to entry. Neither the HFB nor the LFB altered pulse wave velocity. The addition of either low- or high-fat ground beef did not negatively alter vascular function. In fact, consuming HFB improved FMD and BP values, which may be mediated by lowering LDL-C concentrations.

DEXA or BMI: clinical considerations for evaluating obesity in collegiate division I-A American football athletes.

OBJECTIVE: To evaluate the relationship between body mass index (BMI) and %body fat (%Fat) in collegiate football athletes (FBA) compared with age-matched/gender-matched general population volunteers (comparison group, CG) and compare body composition and overweight/obese frequencies by BMI between FBA and CG. DESIGN: Cross-sectional. SETTING: Two Division I-A (D-IA) universities in Texas. Integrative Health Technologies (San Antonio, Texas) laboratory. PARTICIPANTS: Football athletes (n = 156, 20.0 ± 1.3 years, 185.6 ± 6.5cm, 103.3 ± 20.4 kg). Comparison group (n = 260, 21.5 ± 2.7 years, 179.0 ± 7.6 cm, 86.3 ± 20.9 kg). STATISTICAL ANALYSIS: Body mass index and bone densitrometry (DEXA) body composition were assessed. Regression was used to predict %Fat from BMI in CG and FBA. To compare %Fat, fat mass (FM), fat-free mass (FFM), and weight (WT) between CG, FBA, linemen, and non-linemen, 1 × 4 analysis of variance was used. Chi-square analysis was used to compare the frequency of BMI ≥25 between groups. RESULTS: Body mass index differently predicted %Fat for CG (r = 0.643, SE = 6.258) and FBA (r =0.769, SE = 4.416). Body mass index cutoffs for overweight/obese corresponded to the following %Fat in each group [BMI ≥25 = 19.9% (CG) and 11.1% (FBA); BMI ≥30 = 27.3% (CG) and 20.2% (FBA)]. Football athletes had significantly higher WT, BMI, FFM, and frequency of BMI ≥25 with lower %Fat and FM than CG (α < 0.05). Linemen had the highest WT, BMI, FFM, %Fat, and frequency of BMI ≥25. CONCLUSIONS: The relationship between BMI and %Fat differed between CG and FBA. Using current BMI thresholds for obesity in FBA may result in misleading inferences about health risk.

Firefighters With Higher Cardiorespiratory Fitness Demonstrate Lower Markers of Cardiovascular Disease Risk.

OBJECTIVE: High cardiorespiratory fitness (CRF) is associated with reduced markers of oxidative stress and cardiovascular disease (CVD) risk factors; however, this relationship has not been elucidated in firefighters. The purpose of this study was to examine differences in markers of CVD risk between firefighters who have either high or low levels of CRF. METHODS: Forty-six firefighters participated in a maximal graded exercise test and a dual-energy x-ray absorptiometry scan and provided a fasted blood sample. V˙O 2max values were categorized based on American College of Sports Medicine guidelines to establish high- and low-fitness groups. RESULTS: High fitness firefighters demonstrated significantly higher high-density lipoprotein cholesterol and lower markers of CVD risk: cholesterol, triglycerides, low-density lipoprotein cholesterol, insulin, homeostatic model assessment for insulin resistance, C-reactive protein, and advanced oxidation protein products concentrations. CONCLUSION: Firefighters are encouraged to maintain high CRF to reduce risk of CVD.

Electrocardiograms of collegiate football athletes.

BACKGROUND: The prevalence of electrocardiogram (ECG) abnormalities in American collegiate football athletes is virtually unknown. PURPOSE: The purpose of this study was to characterize the type and frequency of ECG abnormalities in a sample of football athletes entering National Collegiate Athletic Association (NCAA) Division I Football Bowl Subdivision university program. METHODS: Over a 4-y period, resting and exercise 12-lead ECG recordings were analyzed by a cardiologist from 68 freshmen and 9 transfer football athletes (n=77; 54 African-Americans and 23 Caucasians, aged 18 +/- 1 y, height=1.89 +/- 0.06 m, weight= 104.4 +/- 19.8 kg) as part of their entry physical examination. RESULTS: A total of 79% of the athletes demonstrated at least 1 abnormal ECG finnding, and significantly more African-America athletes (85%) than Caucasian (65%) athletes. Wolff-Parkinson-White (WPW) syndrome was found in 1 African-American player. Frequencies of various ECG abnormal findings in all athletes were: left ventricular hypertrophy = 64.5%, ST-T wave = 6.5%, interventricular conduction delay = 2.6%, sinus bradycardia = 9.1%, sinus arrhythmia = 15.6%, first-degree atrioventricular (AV) block = 11.7%, left atrial enlargement = 48.1%, early repolarization = 33.8%, and right axis deviation = 20.8%. Average values for the PR (0.17 +/- 0.03 s), QRS (0.08 +/- 0.02 s), and QT intervals (0.38 +/- 0.05 s), P-wave duration (0.10 +/- 0.02 s), and QRS axis (79.1 +/- 18.2 degrees) were normal. The ECG responses to maximal treadmill exercise stress tests were evaluated as normal without ischemia or arrhythmias. CONCLUSION: Abnormal resting ECG findings are common in a sample of collegiate football athletes, exceeding the rate expected for their age, and are more frequent in African-American athletes as compared with Caucasian athletes.

Predicting Energy Expenditure of an Acute Resistance Exercise Bout in Men and Women.

The energy expenditure of resistance exercise (RE) is an important consideration for exercise prescription and weight management, yet prediction models are lacking. PURPOSE: This study aimed to develop regression equations to predict energy expenditure (kcal) for RE involving each major muscle group using commonly measured demographic and exercise variables as predictors. METHODS: Fifty-two healthy, active subjects (27 men, 25 women, age 20-58 yr, height 174.1 ± 10.5 cm, weight 188.7 ± 42.6 kg, V˙O2max 36.8 ± 9.2 mL·kg⋅min) were strength tested to estimate their one-repetition maximum 1 wk before their experimental RE bout. The experimental RE bout consisted of a warm-up set followed by 2-3 sets (2-min turnover) of 8-12 reps at 60%-70% of predicted one-repetition maximum for leg press, chest press, leg curl, lat pull, leg extension, triceps push down, and biceps curl. Kilocalories were estimated from V˙O2 measured continuously throughout the RE bout via an automated metabolic cart. Total exercise volume (TV) was calculated as sets × reps × weight lifted. Multiple linear regression (stepwise removal) was used to determine the best model (highest adjusted R) to predict the kilocalorie consumption of the total workout and of the individual RE lifts. RESULTS: The derived regression equation for the net kilocalorie consumption of an RE bout was as follows: total net kilocalorie = 0.874 (height, cm) - 0.596 (age, yr) - 1.016 (fat mass, kg) + 1.638 (lean mass, kg) + 2.461 (TV × 10) - 110.742 (R = 0.773, SEE = 28.5 kcal). Significant equations were also derived for individual lifts (R = 0.62 to 0.83). CONCLUSIONS: Net energy expenditure for a total RE bout and for individual RE can be reasonably estimated in adult men and women using commonly measured demographic and RE variables.

Echocardiographic and Blood Pressure Characteristics of First-Year Collegiate American-Style Football Players.

Echocardiographic (echo) and blood pressure (BP) reference values may help identify athletes at cardiovascular risk, yet benchmarks are inadequate for collegiate American-style football (ASF) players. Our purpose was to describe echo characteristics and BP values in collegiate ASF athletes compared with normal. First-year players (n = 80, age = 18 ± 1 years, height = 186 ± 7 cm, weight = 100.1 ± 22.0 kg, body mass index = 28.7 ± 5.0), body surface area [BSA] = 2.24 ± 0.25; percentage fat = 16.5 ± 9.7%) were measured for systolic and diastolic BP, and underwent echo procedures by a certified sonographer. Data analyses included simple statistics, Pearson r, frequencies in normal ranges, and t test; α = 0.05. Selected echo measurements (and indexed by BSA) were: left ventricular (LV) internal diameter diastole = 5.3 ± 0.5 cm (2.4 ± 0.3); left atrial diameter = 3.9 ± 0.5 cm (1.8 ± 0.2): LV end-diastolic volume = 138 ± 30 ml (62 ± 11); septal wall thickness = 1.0 ± 0.2 cm (0.5 ± 0.1); LV posterior wall thickness = 1.0 ± 0.1 cm (0.5 ± 0.1), LV mass = 212 ± 46 g (95 ± 18); and relative wall thickness = 0.39 ± 0.07. Correlations between BSA and echo variables were significant (r = 0.26 to 0.50). Indexing by BSA reduced percentages above reference ranges from 36% to 7%. Septal wall thickness index was significantly greater in black (0.5 ± 0.1) than nonblack (0.4 ± 0.1) athletes. Fifty-nine athletes were hypertensive or prehypertensive, and diastolic BP was significantly greater in black (76 ± 10 mm Hg) compared with nonblack athletes (71 ± 8 mm Hg). ASF athletes demonstrated LV wall thicknesses and cavity sizes consistent with sport-training hypertrophy but which were unremarkable when indexed by BSA. Ethnicity generally did not influence echo variables. No ASF players were identified with cardiac dysfunction or disease.

Effects of resistance, endurance, and concurrent exercise on training outcomes in men.

UNLABELLED: The specificity of training principle predicts that combining resistance and endurance training (concurrent training) could interfere with the maximum development of strength and endurance capacity that results from either type of training alone. PURPOSE: To determine whether endurance and resistance training performed concurrently produces different performance and physiologic responses compared with each type of training alone. METHODS: Untrained male volunteers were randomly assigned to one of three groups: endurance training (ET, N = 12); resistance training (RT, N = 13); and concurrent training (CT, N = 16). The following measurements were made on all subjects before and after 12 wk of training: weight, percent body fat, peak oxygen consumption (VO(2peak)), isokinetic peak torque and average power produced during single-leg flexion and extension at 60 and 180 degrees.s, one-repetition maximum (1RM) leg press, 1RM bench press, vertical jump height, and calculated jump power. RESULTS: Weight and lean body mass (LBM) increased significantly in the RT and CT groups (P < 0.05). Percent body fat was significantly decreased in the ET and CT groups. VO(2peak) was significantly improved only in the ET group. Peak torque during flexion and extension at 180 degrees.s(-1) increased in the RT group. Improvements in 1RM leg press and bench press were significant in all groups, but were significantly greater in the RT and CT compared to the ET group. Jump power improved significantly only in the RT group, and no group showed a significant change in vertical jump height. CONCLUSIONS: Concurrent training performed by young, healthy men does not interfere with strength development, but may hinder development of maximal aerobic capacity.

Acute exercise and training alter blood lipid and lipoprotein profiles differently in overweight and obese men and women.

Our purpose was to elucidate effects of acute exercise and training on blood lipids-lipoproteins, and high-sensitivity C-reactive protein (hsCRP) in overweight/obese men (n = 10) and women (n = 8); age, BMI, body fat percentage, and VO(2)max were (mean ± SEM): 45 ± 2.5 years, 31.9 ± 1.4 kg·m(-2), 41.1 ± 1.5%, and 25.2 ± 1.3 mlO(2)·kg(-1)·min(-1). Before exercise training subjects performed an acute exercise session on a treadmill (70% VO(2)max, 400 kcal energy expenditure), followed by 12 weeks of endurance exercise training (land-based or aquatic-based treadmill): 3 sessions·week(-1), progressing to 500 kcal·session(-1) during which subjects maintained accustomed dietary habits. After training, the acute exercise session was repeated. Blood samples, obtained immediately before and 24 h after acute exercise sessions, were analyzed for serum lipids, lipoproteins, and hsCRP adjusted for plasma volume shifts. Exercise training increased VO(2)max (+3.67 mlO(2)·kg(-1)·min(-1), P < 0.001) and reduced body weight (-2.7 kg, P < 0.01). Training increased high-density lipoprotein (HDL) and HDL(2b)-cholesterol (HDL-C) concentrations (+3.7 and +2.4 mg·dl(-1), P < 0.05) and particle numbers (+588 and +206 nmol·l(-1), P < 0.05) in men. In women despite no change in total HDL-C, subfractions shifted from HDL(3)-C (-3.2, P < 0.01) to HDL(2b)-C (+3.5, P < 0.05) and HDL(2a)-C (+2.2 mg·dl(-1), P < 0.05), with increased HDL(2b) particle number (+313 nmol·l(-1), P < 0.05). Training reduced LDL(3) concentration and particle number in women (-1.6 mg·dl(-1) and -16 nmol·l(-1), P < 0.05). Acute exercise reduced the total cholesterol (TC): HDL-C ratio in men (-0.16, P < 0.01) and increased hsCRP in all subjects (+0.05 mg·dl(-1), P < 0.05), regardless of training. Training did not affect acute exercise responses. Our data support the efficacy of endurance training, without dietary intervention, to elicit beneficial changes in blood lipids-lipoproteins in obese men and women.

Predicting football players' dual-energy x-ray absorptiometry body composition using standard anthropometric measures.

CONTEXT: The recent increase in athlete size, particularly in football athletes of all levels, coupled with the increased health risk associated with obesity warrants continued monitoring of body composition from a health perspective in this population. Equations developed to predict percentage of body fat (%Fat) have been shown to be population specific and might not be accurate for football athletes. OBJECTIVE: To develop multiple regression equations using standard anthropometric measurements to estimate dual-energy x-ray absorptiometry %Fat (DEXA%Fat) in collegiate football players. DESIGN: Controlled laboratory study. PATIENTS AND OTHER PARTICIPANTS: One hundred fifty-seven National Collegiate Athletic Association Division IA football athletes (age = 20 ± 1 years, height = 185.6 ± 6.5 cm, mass = 103.1 ± 20.4 kg, DEXA%Fat = 19.5 ± 9.1%) participated. MAIN OUTCOME MEASURE(S): Participants had the following measures: (1) body composition testing with dual-energy x-ray absorptiometry; (2) skinfold measurements in millimeters, including chest, triceps, subscapular, midaxillary, suprailiac, abdominal (SFAB), and thigh; and (3) standard circumference measurements in centimeters, including ankle, calf, thigh, hip (AHIP), waist, umbilical (AUMB), chest, wrist, forearm, arm, and neck. Regression analysis and fit statistics were used to determine the relationship between DEXA%Fat and each skinfold thickness, sum of all skinfold measures (SFSUM), and individual circumference measures. RESULTS: Statistical analysis resulted in the development of 3 equations to predict DEXA%Fat: model 1, (0.178 · AHIP) + (0.097 · AUMB) + (0.089 · SFSUM) - 19.641; model 2, (0.193 · AHIP) + (0.133 · AUMB) + (0.371 · SFAB) - 23.0523; and model 3, (0.132 · SFSUM) + 3.530. The R(2) values were 0.94 for model 1, 0.93 for model 2, and 0.91 for model 3 (for all, P < .001). CONCLUSIONS: The equations developed provide an accurate way to assess DEXA%Fat in collegiate football players using standard anthropometric measures so athletic trainers and coaches can monitor these athletes at increased health risk due to increased size.