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Background/Objectives: Firefighters, tactical police officers, and warriors often engage in periodic, intermittent, high-intensity physical work in austere environmental conditions and have a heightened risk of premature mortality. In addition, tough decision-making challenges, routine sleep deprivation, and trauma exacerbate this risk. Therefore, identifying strategies to bolster these personnel's health and occupational performance is critical. Creatine monohydrate (CrM) supplementation may offer several benefits to firefighters and tactical athletes (e.g., police, security, and soldiers) due to its efficacy regarding physical performance, muscle, cardiovascular health, mental health, and cognitive performance. Methods: We conducted a narrative review of the literature with a focus on the benefits and application of creatine monohydrate among firefighters. Results: Recent evidence demonstrates that CrM can improve anaerobic exercise capacity and muscular fitness performance outcomes and aid in thermoregulation, decision-making, sleep, recovery from traumatic brain injuries (TBIs), and mental health. Emerging evidence also suggests that CrM may confer an antioxidant/anti-inflammatory effect, which may be particularly important for firefighters and those performing tactical occupations exposed to oxidative and physiological stress, which can elicit systemic inflammation and increase the risk of chronic diseases. Conclusions: This narrative review highlights the potential applications of CrM for related tactical occupations, with a particular focus on firefighters, and calls for further research into these populations.

Abstract: Jagim, AR, Harty, PS, Jones, MT, Fields, JB, Magee, M, Smith-Ryan, AE, Luedke, J, and Kerksick, CM. Fat-free mass index in sport: normative profiles and applications for collegiate athletes. J Strength Cond Res 38(9): 1687-1693, 2024-Recent concerns have been raised regarding the ethical considerations of conducting body composition assessments in sports. Specific apprehensions pertain to the inappropriate use of percent body fat and the limited application of the results to performance and recovery. Fat-free mass index (FFMI), a height-adjusted assessment of FFM, can serve as an alternative body composition metric to focus on in sports. Fat-free mass index provides valuable context regarding an optimal amount of FFM, accounting for skeletal frame and height while helping to qualify an athlete's FFM as low, moderate, or high. This review posits that shifting the focus of body composition measures to FFM can support more ideal targets across athletic seasons, careers, and the return to play after injury. In addition, a FFM focus may help change the perception of body composition assessment and how athletes perceive their current body because of the increased focus on the FFM compartment and the goal of maximizing tissue accrual, rather than focusing on fat loss. Fat-free mass index is calculated by dividing FFM (kg) by height (m 2 ) and can serve to normalize FFM, relative to height, and enable comparisons across athletes, sport types, and sex. Previous research has identified differences in FFMI across sex and among sport categories. Still, there is a need for more published data to develop optimal ranges for FFMI across sex, sports, and positions. As more data become available, FFMI has the potential to provide normative guidelines for optimal FFM development, performance, and injury risk reduction. The purpose of the current review was to summarize FFMI values across collegiate sport categories and competitive status to provide normative profiles, according to sex and sport type., (Copyright © 2024 National Strength and Conditioning Association.)

Abstract: Jagim, AR, Luedke, J, Erickson, JL, Fields, JB, and Jones, MT. Validation of bioelectrical impedance devices for the determination of body fat percentage in firefighters. J Strength Cond Res 38(8): e448-e453, 2024-To cross-validate bioelectrical impedance devices for the determination of body fat percentage (BF%) in firefighters. Twenty-eight structural firefighters were evaluated (female, n = 2; male, n = 26 [mean ± SD] age: 38.2 ± 8.3 years; height: 180.2 ± 7.5 cm; body mass: 86.7 ± 20.8 kg; body mass index: 25.8 ± 7.8 kg·m-2) using multifrequency bioelectrical impedance analysis (MFBIA) hand-to-foot device, and single-frequency BIA foot scale (F2FBIA), and a single-frequency handheld BIA device (HHBIA). Dual X-ray absorptiometry served as the criterion. Validity metrics were examined to establish each method's performance. Body fat % values produced by MFBIA (r = 0.913), F2FBIA (r = 0.695), and HHBIA (r = 0.876) were strongly associated (p < 0.001) with criterion BF% measures. However, MFBIA, F2FBIA, and HHBIA all significantly (p < 0.001) underestimated BF% when compared with the criterion measure. Constant error ranged between 4.0 and 5.5% across all BIA devices. Despite strong associations between the BIA devices included in the current study and the criterion measure, all BIA devices underestimated BF%, which resulted in an overestimation of fat-free mass. In addition, proportional bias was observed in which BF% was overestimated at lower values and underestimated at higher values., (Copyright © 2024 National Strength and Conditioning Association.)

The strength of the shoulder musculature involved with internal rotation and arm extension plays an important role in the overhead throwing motion for baseball athletes, both for throwing-related performance and injury risk. The maintenance of shoulder strength is a high priority for baseball athletes throughout a season; however, little is known in regards to the expected changes in strength throughout a season. To examine pre-post changes in shoulder strength, lower body power, and body composition among collegiate baseball players after the completion of a summer baseball league season. Amateur baseball players ( n = 12; age: 20.9 ± 1.0 years.; height: 181.6 ± 5.6 cm; body mass: 86.4 ± 11.1 kg; BMI: 26.0 ± 2.6 kg/m 2 ) participated in the current study. Pre- and post-competitive season, the participants completed shoulder strength assessments and body composition and countermovement vertical jump (CMJ) tests. An upper-body isometric test (athletic shoulder [ASH] test) was used to evaluate shoulder strength for each arm. Each subject completed maximal isometric contractions for both the throwing and non-throwing arms at four separate angles of abduction (180°, 'I'; 135°, 'Y'; 90°, 'T'; and -180°, 'A') while lying in a prone position. For shoulder strength, the primary dependent variable of interest was a composite measure that represented the average of the forces produced across all four positions of the ASH test (I, Y, T, A). For the ASH test composite measure, there was a trend toward a significant arm-by-time interaction effect ( p = 0.08), as shoulder strength decreased by 9.03% for the throwing arm (ES = 0.72; 95% CI = [-0.27, -0.01]), compared to only 2.03% for the non-throwing arm (ES = 0.15; 95% CI = [-0.16, 0.09]), over the course of the season. The main effects of time ( p = 0.16) and arm ( p = 0.58) were not significant for the ASH test composite measure. There was no relationship between lower body power and throwing arm strength at baseline (r = 0.20, p = 0.56), and only a non-significant weak relationship at post-test (r = 0.28, p = 0.41). Throughout a season, baseball players may experience reductions in shoulder strength of the throwing arm with minimal changes in shoulder strength in the non-throwing arm.

Background: The purpose of this study was to assess the effects of protein and carbohydrate supplementation, with and without creatine, on occupational performance in firefighters., Methods: Using a randomized, double-blind approach, thirty male firefighters (age: 34.4 ± 8.4 yrs., height: 1.82 ± 0.07 m; weight: 88.6 ± 12.5 kg; BF%: 17.2 ± 5.8%) were randomized to receive either (A.) 25 g of whey protein isolate + 25 g of carbohydrate powder (ProCarb group); or (B.) ProCarb + 5 g of creatine (Creatine group) in a double-blind fashion over a period of 21-26 days (depending on shift rotations) to evaluate the impact of supplementation on occupation-specific performance. At baseline and following supplementation, firefighters completed a battery of tests. These tests included an aerobic speed test on an air-braked cycle ergometer followed by the hose carry, body drag, stair climb, and Keiser sled hammer for time., Results: No significant differences in measures of performance were observed at baseline ( p > 0.05). There was a significant main effect for time observed for rescue, stair climb, total time to completion, and time trial performance ( p < 0.05). There was a significant group × time ( p < 0.05) interaction for rescue and forcible entry. Independent sample t -tests indicated that the Creatine group experienced a greater reduction (from baseline) in completion time for the rescue (1.78 ± 0.57 s, 95% CI: 0.61, 2.95 s, p = 0.004) and forcible entry (2.66 ± 0.97 s, 95% CI: 0.68, 4.65 s, p = 0.01) tests compared to the ProCarb group. No significant group × time interactions were observed for the hose line advance, stair climb, total time to completion, and time trial performance ( p > 0.05)., Conclusions: The addition of supplemental creatine to a protein and carbohydrate supplement to the diet of career firefighters throughout a three week period improves occupational performance in firefighters in specific areas of high-intensity, repetitive actions., Competing Interests: The authors declare no conflicts of interest.

Background: Kinetic asymmetries during sit-to-stand have been consistently observed early after total knee arthroplasty; however, the longer-term outcomes are less clear. The purpose of this systematic review and meta-analysis was to analyze the results of studies examining inter-limb kinetic symmetry during sit-to-stand performance among individuals who were at least one-year post unilateral total knee arthroplasty., Methods: PubMed, SPORTDiscus, CINAHL, and Health Source databases were searched. Studies were included if they were published in a peer-reviewed journal, included subjects who had undergone unilateral total knee arthroplasty at least one-year prior, and examined vertical ground reaction forces and/or knee extension moments for the involved and uninvolved limbs during sit-to-stand performance. Data were transformed into a limb symmetry index, which expressed the ratio of the peak forces/moments for the involved limb, relative to the uninvolved limb (1.0 reflects perfect symmetry). These ratios were meta-analyzed using the ratio of means method., Findings: Seven studies were deemed eligible for inclusion. Ground reaction force data was pooled from seven studies and knee extension moment data was pooled from two studies. For the peak vertical ground reaction forces, the pooled limb symmetry index was 0.96 (CI 95%  = [0.93, 0.99]). For the peak knee extension moments, the pooled limb symmetry index was 0.91 (CI 95%  = [0.84, 0.98]). In both cases this reflects greater limb/knee loading for the uninvolved limb, relative to the involved limb., Interpretation: Asymmetries in limb/knee loading persist beyond the one-year post-operative period following total knee arthroplasty, potentially contributing to degenerative changes for the uninvolved limb., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier Ltd.)

Predictive resting metabolic rate (RMR) equations are widely used to determine total daily energy expenditure (TDEE). However, it remains unclear whether these predictive RMR equations accurately predict TDEE in the athletic populations. The purpose of this study was to examine the accuracy of 10 commonly used RMR prediction equations (Cunningham, De Lorenzo, Freire, Harris-Benedict, Mifflin St. Jeor, Nelson, Owen, Tinsley, Watson, Schofield) in collegiate men and women athletes. One-hundred eighty-seven National Collegiate Athletic Association Division III men ( n  = 97) and women ( n  = 90) athletes were recruited to participate in one day of metabolic testing. RMR was measured using indirect calorimetry and body composition was analyzed using air displacement plethysmography. A repeated measures ANOVA with Bonferroni post hoc analyses was selected to determine mean differences between measured and predicted RMR. Linear regression analysis was used to assess the accuracy of each RMR prediction method ( p <0.05). All prediction equations significantly underestimated RMR ( p <0.001), although there was no difference between the De Lorenzo and Watson equations and measured RMR ( p  = 1.00) for women, only. In men, the Tinsley and Freire equations were the most agreeable formulas with the lowest root-mean-square prediction error value of 404 and 412 kcals, respectively. In women, the De Lorenzo and Watson equations were the most agreeable equations with the lowest root-mean-squared error value of 171 and 211 kcals, respectively. The results demonstrate that such RMR equations may underestimate actual energy requirements of athletes and thus, practitioners should interpret such values with caution. Highlights All prediction equations significantly underestimated RMR in men athletes.All prediction equations, except for the De Lorenzo and Watson equations, significantly underestimated RMR in women athletes.Although a significant underestimation of RMR in men athletes, the Freire and Tinsley equations were the most agreeable prediction equations.In women athletes, the De Lorenzo and Watson equations were the most agreeable prediction equations.

Intoduction: To cross-validate skinfold (SKF) equations, impedance devices, and air-displacement plethysmography (ADP) for the determination of fat-free mass (FFM)., Methods: Male and female youth athletes were evaluated ( n  = 91[mean ± SD] age: 18.19 ± 2.37 year; height: 172.1 ± 9.8 cm; body mass: 68.9 ± 14.5 kg; BMI: 23.15 ± 3.2 kg m -2 ; body fat: 19.59 ± 6.9%) using underwater weighing (UWW), ADP, and SKF assessments. A 3-compartment (3C) model (i.e., UWW and total body water) served as the criterion, and alternate body density (Db) estimates from ADP and multiple SKF equations were obtained. Validity metrics were examined to establish each method's performance. Bioelectrical impedance analysis (BIA), bioimpedance spectroscopy (BIS), and the SKF equations of Devrim-Lanpir, Durnin and Womersley, Jackson and Pollock (7-site), Katch, Loftin, Lohman, Slaughter, and Thorland differed from criterion., Results: For females, Pearson's correlations between the 3C model and alternate methods ranged from 0.51 to 0.92, the Lin's concordance correlation coefficient (CCC) ranged from 0.41 to 0.89, with standard error of the estimate (SEE) ranges of 1.9-4.6 kg. For SKF, the Evans 7-site and J&P 3 Site equations performed best with CCC and SEE values of 0.82, 2.01 kg and 0.78, 2.21 kg, respectively. For males, Pearson's correlations between the 3C model and alternate methods ranged from 0.50 to 0.95, CCC ranges of 0.46-0.94, and SEE ranges of 3.3-7.6 kg. For SKF, the Evans 3-site equation performed best with a mean difference of 1.8 (3.56) kg and a CCC of 0.93., Discussion: The Evans 7-site and 3-site SKF equations performed best for female and male athletes, respectively. The field 3C model can provide an alternative measure of FFM when necessary., Competing Interests: GT has received support for his research laboratory, in the form of research grants or equipment loan or donation, from manufacturers of body composition assessment devices, including Size Stream LLC; Naked Labs Inc.; Prism Labs Inc.; RJL Systems; MuscleSound; and Biospace, Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Jagim, Tinsley, Merfeld, Ambrosius, Khurelbaatar, Dodge, Carpenter, Luedke, Erickson, Fields and Jones.)

The purpose of this study was to examine sex differences in resting metabolic rate (RMR) and associations between measured RMR and body composition parameters in athletes. One-hundred and ninety collegiate men (n = 98; age: 20.1 ± 1.6 yr.; body mass: 92.7 ± 17.5 kg; height: 181.6 ± 6.2 cm, body mass index: 28.0 ± 4.7 kg/m 2 ) and women (n = 92; age: 19.4 ± 1.1 yr.; body mass: 65.2 ± 11.0 kg; height: 168.0 ± 6.6 cm, body mass index: 23.0 ± 3.6 kg/m 2 ) athletes volunteered to participate in this study. Athletes completed a body composition assessment using air displacement plethysmography and RMR using indirect calorimetry. Assessments were completed in a fasted state and after refraining from intense physical activity > 24 h prior to testing. Data were collected during the 2016-2019 seasons. Men had a higher RMR compared to women (2595 ± 433 vs. 1709 ± 308 kcals; p < 0.001); however, when adjusted for body mass ( p = 0.064) and fat-free mass ( p = 0.084), the observed differences were not significant. Height, body mass, body mass index, fat-free mass, and fat mass were positively associated with RMR in both men and women athletes (r = 0.4-0.8; p < 0.001). Body mass (men: β = 0.784; women: β = 0.832)) was the strongest predictor of RMR. Men athletes have a higher absolute RMR compared to their women counterparts, which is influenced by greater body mass and fat-free mass. Body mass is the strongest predictor of RMR in both men and women athletes.

Early morning training sessions may affect sleep quantity in athletes. The purpose of this study is to examine differences in total sleep time of collegiate athletes on nights prior to early morning training sessions relative to non-training nights. Wristwatch monitors equipped with photoplethysmography and accelerometer technology were worn by 18 NCAA Division III collegiate athletes (Age: 20.1 ± 1.6 years, Height: 1.81 ± 0.02 m, Body Mass: 91.2 ± 6.5 kg, Body Fat %: 20.8 ± 1.6%) during a two-week period of training to monitor total sleep times. Athletes recorded time in and out of bed using a sleep diary, anxiety levels due to having to wake up in the morning, and perceived recovery status (PRS) upon waking the next day. The data were divided into: nights before non-training days (NT) and Training days (TD). Data were analyzed using univariate analysis. All athletes obtained significantly less total sleep on nights before TD relative to NT (NT: 8:15 ± 1:03 vs. TD: 6:08 ± 0:59 hh:mm; p < 0.05). There was a positive relationship between total sleep time and recovery status ( p < 0.01). Anxiety scores were inversely related to total sleep time ( p < 0.01). Next-day recovery status was inversely related to anxiety scores ( p < 0.001). College athletes obtained significantly less total sleep time on nights before early morning training sessions (< 0700) during the off-season, regardless of sex and sport. Coaches should consider later training sessions or promote optimal sleep quantity in order to minimize the risks associated to early morning training sessions.

Background : The purpose of this study was to examine the relationship between training load and next-day recovery in collegiate American football (AF) players during pre-season. Methods : Seventeen athletes (Linemen, n = 6; Non-linemen, n = 11) participated in the 14-day study wearing monitoring (accelerometer + heart rate) sensors during on-field practice sessions throughout pre-season to assess the physiological (PL), mechanical load (ML) and recording of session RPE (sRPE load) immediately post-practice. Prior to practice, participants completed a drop-jump reactive strength index (RSI) test and reported perceived recovery status (PRS). Loaded counter movement vertical jump was assessed before and after pre-season. Results : For every one unit increase in sRPE load, RSI declined by 0.03. Non-linemen had a lower RSI value of 73.1 units compared to linemen. For every one unit increase in ML, the PRS decreased by 0.01. Non-linemen recorded higher average ML during week 2 (ES = 1.17) compared to linemen. Non-linemen recorded higher RSI values in weeks 1 (ES = -1.41) and 2 (ES = -1.72) compared to linemen. All training load and recovery parameters were lower week 2 compared to week 1 (p < 0.05) for all players. Conclusions : Next-day RSI values were influenced by sRPE load while next-day PRS appears to be more influenced by ML. No difference in PL or sRPE load was observed been groups despite non-linemen completing a higher ML throughout the preseason. A combination of training load and recovery metrics may be needed to monitor the fatigue and state of readiness of each player.

Sport nutrition knowledge has been shown to influence dietary habits of athletes. The purpose of the current study was to examine relationships between sport nutrition knowledge and body composition and examine potential predictors of body weight goals in collegiate athletes. Participants included National Collegiate Athletic Association Division III women ( n = 42, height: 169.9 ± 6.9 cm; body mass: 67.1 ± 8.6 kg; fat-free mass: 51.3 ± 6.6 kg; body fat per cent: 24.2 ± 5.3%) and men ( n = 25, height: 180.8 ± 7.2 cm; body mass: 89.2 ± 20.5 kg; fat-free mass: 75.9 ± 12.2 kg; body fat per cent: 13.5 ± 8.9%) athletes. Body composition was assessed via air displacement plethysmography. Athletes completed a validated questionnaire designed to assess sport nutrition knowledge and were asked questions about their perceived dietary energy and macronutrient requirements, as well as their body weight goal (i.e., lose, maintain, gain weight). Athletes answered 47.98 ± 11.29% of questions correctly on the nutrition questionnaire with no differences observed between sexes (men: 49.52 ± 11.76% vs. women: 47.03 ± 11.04%; p = 0.40). An inverse relationship between sport nutrition knowledge scores and body fat percentage (BF%) ( r = -0.330; p = 0.008), and fat mass ( r = -0.268; p = 0.032) was observed for all athletes. Fat mass (β = 0.224), BF% (β = 0.217), and body mass index (BMI) (β = 0.421) were all significant ( p < 0.05) predictors of body weight goal in women. All athletes significantly ( p < 0.001) underestimated daily energy (-1360 ± 610.2 kcal/day), carbohydrate (-301.6 ± 149.2 grams/day [g/day]), and fat (-41.4 ± 34.5 g/day) requirements. Division III collegiate athletes have a low level of sport nutrition knowledge, which was associated with a higher BF%. Women athletes with a higher body weight, BF% and BMI were more likely to select weight loss as a body weight goal. Athletes also significantly underestimated their energy and carbohydrate requirements based upon the demands of their sport, independent of sex.

Objective: To quantify the occurrence rate of abnormal electrocardiographic (ECG) findings and symptoms following coronavirus disease 2019 (COVID-19) infection., Patients and Methods: In this retrospective analysis, we studied adult patients (>18 years old) who were participating in collegiate athletics and previously tested positive for COVID-19 between August 1, 2020, and December 30, 2020. The athletes underwent general examinations and ECG screening prior to being medically cleared for a return to sports following their COVID-19 diagnosis. Predetermined predictors were grouped into categorical variables including (1) sex, (2) symptom severity, and (3) body mass index (normal vs overweight [≥24 kg/m 2 ]). These variables were used to examine differences of abnormal rates that occurred between different predictor categories., Results: Of the 170 athletes screened, 6 (3.5%) presented with abnormal ECG findings and were referred to cardiologists. We found no evidence that sex, symptom severity, and body mass index category were associated with a higher rate of abnormal ECG findings (all P >.05). Greater severity of COVID-19 symptoms was associated with a higher percentage of ST depression, T-wave inversion, ST-T changes, and the presence of fragmented QRS complex. Loss of smell, loss of taste, headache, and fatigue were the most prevalent symptoms, with 38.8% (66), 36.5% (62), 32.9% (56), and 25.3% (43), respectively, of the 170 athletes reporting each symptom., Conclusion: Preliminary findings indicate a low risk of myocardial injury secondary to COVID-19 infection, with less than 4% of the 170 patients in our study presenting with abnormal ECG findings and a total of 16 patients (9.4%) requiring referral to a cardiologist. Although viral myocarditis was not detected in any athlete referred for cardiological assessment, 2 patients experienced effusive viral pericarditis., (© 2021 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc.)

The purpose of the current study was to examine the impact of COVID-19 government-enforced shutdown measures on the training habits and perceptions of athletes. A web-based electronic survey was developed and distributed online to athletes. The survey contained questions regarding currently available resources, changes in weekly training habits, and perceptions of training such as intensity, motivation, and enjoyment. A total of 105 (males: n = 31; females: n = 74) athletes completed the survey (mean ± SD age = 19.86 ± 2.13 years). Ninety-nine (94.3%) athletes continued to receive guidance from their primary sport coach or strength training staff. There was a significant ( p < 0.001) decrease (mean ± SD ) in self-reported participation time for strength training (-1.65 ± 4.32 h. week -1 ), endurance (-1.47 ± 3.93 h. week -1 ), and mobility (-1.09 ± 2.24 h. week -1 ), with the largest reduction coming from participation time in sport-specific activities (-6.44 ± 6.28 h. week -1 ) pre- to post-shutdown. When asked to rate their current state of emotional well-being using a visual analog scale of 0-100, with 100 being exceptional, the mean score was 51.6 ± 19.6 AU. Athletes experienced notable reductions in training frequency and time spent completing various training related activities. In the future, practitioners should have preparations in place in the event of another lockdown period or future pandemic to avoid or minimize significant disruptions in training. Special considerations may be needed when athletes are allowed to return to sport in the event of significant levels of detraining that may have occurred., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Jagim, Luedke, Fitzpatrick, Winkelman, Erickson, Askow and Camic.)

Jagim, AR, Camic, CL, Askow, A, Luedke, J, Erickson, J, Kerksick, CM, Jones, MT, and Oliver, JM. Sex differences in resting metabolic rate among athletes. J Strength Cond Res 33(11): 3008-3014, 2019-The purpose of this study was to compare differences in resting metabolic rate (RMR) between sexes in Division III National Collegiate Athletic Association (NCAA) collegiate athletes and to identify predictors of RMR. Sixty-eight male (M) (age: 20.1 ± 1.5 years; height: 181.8 ± 5.9 cm; body mass (BM): 93.7 ± 16.3 kg; and body fat%: 16.3 ± 8.6%) and 48 female (F) athletes (age: 19.4 ± 1.3 years; height: 166.5 ± 6.0 cm; BM: 63.4 ± 12.7 kg; and body fat%: 21.5 ± 6.3%) participated in a single day of testing, which included determination of RMR using indirect calorimetry and air displacement plethysmography to measure fat mass and fat-free mass (FFM). An independent-samples t-test was used to compare differences in body composition and RMR between sexes, and regression analysis was used to identify predictors of RMR. Men had a significantly higher absolute RMR (M: 2,481 ± 209 vs. F: 1,553 ± 193 kcals·d; p < 0.001), but when adjusted for BM (M: 25.6 ± 8.3 vs. F: 25.9 ± 2.5 kcals·kg BM per day; p = 0.82) and FFM (M: 31.1 ± 10.6 vs. F: 33.6 ± 3.8 kcals·kg FFM per day; p = 0.12), these differences became nonsignificant. Regression analysis indicated that BM in both men (β = 0.73) and women (β = 0.88) was the strongest predictor of RMR. The results of the current study indicate minimal differences in RMR between sexes among athletic populations when adjusted for BM and FFM. In the current group of athletes, BM seems to account for the largest variability in RMR.

Jagim, AR, Camic, CL, Kisiolek, J, Luedke, J, Erickson, J, Jones, MT, and Oliver, JM. Accuracy of resting metabolic rate prediction equations in athletes. J Strength Cond Res 32(7): 1875-1881, 2018-The purpose of this study was to determine the accuracy of 5 different resting metabolic rate (RMR) prediction equations in male and female athletes. Twenty-two female (19.7 ± 1.4 years; 166.2 ± 5.5 cm; 63.5 ± 7.3 kg; 49.2 ± 4.3 kg of fat-free mass (FFM); 23.4 ± 4.4 body fat (BF) percent) and 28 male (20.2 ± 1.6 years; 181.9 ± 6.1 cm; 94.5 ± 16.2 kg; 79.1 ± 7.2 kg of FFM; 15.1 ± 8.5% BF) athletes were recruited to participate in 1 day of metabolic testing. Assessments comprised RMR measurements using indirect calorimetry, and body composition analyses using air displacement plethysmography. One-way repeated-measures analysis of variance with follow-up paired t tests were selected to determine differences between indirect calorimetry and 5 RMR prediction equations. Linear regression analysis was used to assess the accuracy of each RMR prediction method. An alpha level of p ≤ 0.05 was used to determine statistical significance. All the prediction equations significantly underestimated RMR while the Cunningham equation had the smallest mean difference (-165 kcals). In men, the Harris-Benedict equation was found to be the best prediction formula with the lowest root-mean-square prediction error value of 284 kcals. In women, the Cunningham equation was found to be the best prediction equation with the lowest root-mean-squared error value of 110 kcals. Resting metabolic rate prediction equations consistently seem to underestimate RMR in male and female athletes. The Harris-Benedict equation seems to be most accurate for male athletes, whereas the Cunningham equation may be better suited for female athletes.

We report the role of a gene (rpoH) from the facultative phototroph Rhodobacter sphaeroides that encodes a protein (sigma37) similar to Escherichia coli sigma32 and other members of the heat shock family of eubacterial sigma factors. R. sphaeroides sigma37 controls genes that function during environmental stress, since an R. sphaeroides deltaRpoH mutant is approximately 30-fold more sensitive to the toxic oxyanion tellurite than wild-type cells. However, the deltaRpoH mutant lacks several phenotypes characteristic of E. coli cells lacking sigma32. For example, an R. sphaeroides deltaRpoH mutant is not generally defective in phage morphogenesis, since it plates the lytic virus RS1, as well as its wild-type parent. In characterizing the response of R. sphaeroides to heat, we found that its growth temperature profile is different when cells generate energy by aerobic respiration, anaerobic respiration, or photosynthesis. However, growth of the deltaRpoH mutant is comparable to that of a wild-type strain under each of these conditions. The deltaRpoH mutant mounted a heat shock response when aerobically grown cells were shifted from 30 to 42 degrees C, but it exhibited altered induction kinetics of approximately 120-, 85-, 75-, and 65-kDa proteins. There was also reduced accumulation of several presumed heat shock transcripts (rpoD P(HS), groESL1, etc.) when aerobically grown deltaRpoH cells were placed at 42 degrees C. Under aerobic conditions, it appears that another sigma factor enables the deltaRpoH mutant to mount a heat shock response, since either RNA polymerase preparations from an deltaRpoH mutant, reconstituted Esigma37, or a holoenzyme containing a 38-kDa protein (sigma38) each transcribed E. coli Esigma32-dependent promoters. The lower growth temperature profile of photosynthetic cells is correlated with a difference in heat-inducible gene expression, since neither wild-type cells or the deltaRpoH mutant mount a typical heat shock response after such cultures were shifted from 30 to 37 degrees C.