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Applying the Critical Power Model to a Full-Body Resistance-Training Movement

Purpose: To determine if the mathematical model used to derive critical power could be used to identify the critical resistance (CR) for the deadlift; compare predicted and actual repetitions to failure at 50%, 60%, 70%, and 80% 1-repetition maximum (1RM); and compare the CR with the estimated sustainable resistance for 30 repetitions (ESR30). Methods: Twelve subjects completed 1RM testing for the deadlift followed by 4 visits to determine the number of repetitions to failure at 50%, 60%, 70%, and 80% 1RM. The CR was calculated as the slope of the line of the total work completed (repetitions × weight [in kilograms] × distance [in meters]) vs the total distance (in meters) the barbell traveled. The actual and predicted repetitions to failure were determined from the CR model and compared using paired-samples t tests and simple linear regression. The ESR30 was determined from the power-curve analysis and compared with the CR using paired-samples t tests and simple linear regression. Results: The weight and repetitions completed at CR were 56 (11) kg and 49 (14) repetitions. The actual repetitions to failure were less than predicted at 50% 1RM (P < .001) and 80% 1RM (P < .001) and greater at 60% 1RM (P = .004), but there was no difference at 70% 1RM (P = .084). The ESR30 (75 [14] kg) was greater (P < .001) than the CR. Conclusions: The total work-vs-distance relationship can be used to identify the CR for the deadlift, which reflected a sustainable resistance that may be useful in the design of resistance-based exercise programs.

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Basal Serum Cortisol and Testosterone/Cortisol Ratio Are Related to Rate of Na+ Lost During Exercise in Elite Soccer Players

During exercise, the human body maintains optimal body temperature through thermoregulatory sweating, which implies the loss of water, sodium (Na+), and other electrolytes. Sweat rate and sweat Na+ concentration show high interindividual variability, even in individuals exercising under similar conditions. Testosterone and cortisol may regulate sweat Na+ loss by modifying the expression/activity of the cystic fibrosis transmembrane conductance regulator. This has not been tested. As a first approximation, the authors aimed to determine whether basal serum concentrations of testosterone or cortisol, or the testosterone/cortisol ratio relate to sweat Na+ loss during exercise. A total of 22 male elite soccer players participated in the study. Testosterone and cortisol were measured in blood samples before exercise (basal). Sweat samples were collected during a training session, and sweat Na+ concentration was determined. The basal serum concentrations of testosterone and cortisol and their ratio were (mean [SD]) 13.6 (3.3) pg/ml, 228.9 (41.4) ng/ml, and 0.06 (0.02), respectively. During exercise, the rate of Na+ loss was related to cortisol (r = .43; p < .05) and to the testosterone/cortisol ratio (r = −.46; p < .01), independently of the sweating rate. The results suggest that cortisol and the testosterone/cortisol ratio may influence Na+ loss during exercise. It is unknown whether this regulation depends on the cystic fibrosis transmembrane conductance regulator.

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Blood-Flow-Restriction Training: Validity of Pulse Oximetry to Assess Arterial Occlusion Pressure

Purpose: Setting the optimal cuff pressure is a crucial part of prescribing blood-flow-restriction training. It is currently recommended to use percentages of each individual’s arterial occlusion pressure, which is most accurately determined by Doppler ultrasound (DU). However, the practicality of this gold-standard method in daily training routine is limited due to high costs. An alternative solution is pulse oximetry (PO). The main purpose of this study was to evaluate validity between PO and DU measurements and to investigate whether sex has a potential influence on these variables. Methods: A total of 94 subjects were enrolled in the study. Participants were positioned in a supine position, and a 12-cm-wide cuff was applied in a counterbalanced order at the most proximal portion of the right upper and lower limbs. The cuff pressure was successively increased until pulse was no longer detected by DU and PO. Results: There were no significant differences between the DU and PO methods when measuring arterial occlusion pressure at the upper limb (P = .308). However, both methods showed considerable disagreement for the lower limbs (P = .001), which was evident in both men (P = .028) and women (P = .008). No sex differences were detected. Conclusions: PO is reasonably accurate to determine arterial occlusion pressure of the upper limbs. For lower limbs, PO does not seem to be a valid instrument when assessing the optimal cuff pressure for blood-flow-restriction interventions compared with DU.

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Changes of Hydration Measures in Elite National Collegiate Athletic Association Division I Wrestlers

Purpose: To evaluate the changes in the state of hydration in elite National Collegiate Athletic Association (NCAA) Division I college wrestlers during and after a season. Methods: Ohio State University wrestling team members (N = 6; mean [SD] age = 19.6 [1.1] y; height = 171.6 [2.9] cm; body mass = 69.5 [8.1] kg) gave informed consent to participate in the investigation with measurements (ie, body mass, urine-specific gravity [USG; 2 methods], Visual Analog Scale thirst scale, plasma osmolality) obtained during and after the season. Results: Measurements for USG, regardless of methods, were not significantly different between visits, but plasma osmolality was significantly (P = .001) higher at the beginning of the season—295.5 (4.9) mOsm·kg−1 compared with 279.6 (6.1) mOsm·kg−1 after the season. No changes in thirst ratings were observed, and the 2 measures of USG were highly correlated (r > .9, P = .000) at each time point, but USG and plasma osmolality were not related. Conclusions: A paradox in the clinical interpretation of euhydration in the beginning of the season was observed with the USG, indicating that the wrestlers were properly hydrated, while the plasma osmolality showed they were not. Thus, the tracking of hydration status during the season is a concern when using only NCAA policies and procedures. The wrestlers did return to normal euhydration levels after the season on both biomarkers, which is remarkable, as previous studies have indicated that this may not happen because of the reregulation of the osmol-regulatory center in the brain.

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Characterization of Risk Quantification Differences Using Female Athlete Triad Cumulative Risk Assessment and Relative Energy Deficiency in Sport Clinical Assessment Tool

This study’s objective was to identify differences in risk for low energy availability and athletic clearance level by comparing scores on Female Athlete Triad Cumulative Risk Assessment (Triad CRA) and Relative Energy Deficiency in Sport Clinical Assessment Tool (RED-S CAT). A total of 1,000 female athletes aged 15–30 years participating in ≥4 hr of physical activity/week for the previous ≥6 months completed an extensive survey assessing health, athletic history, family disease history, and specific Triad/RED-S risk factors. Retrospective chart review ascertained laboratory and bone mineral density measures. Triad CRA and RED-S CAT were used to assign each athlete’s risk level (low, moderate, and high), and case-by-case comparison measured the level of agreement between the tools. We hypothesized that the tools would generally agree on low-risk athletes and that the tools would be less aligned in the specific elevated risk level (moderate or high). Most of the sample was assigned moderate or high risk for Triad CRA and RED-S CAT (Triad: 54.7% moderate and 7.9% high; RED-S: 63.2% moderate and 33.0% high). The tools agreed on risk for 55.5% of athletes. Agreement increased to 64.3% when only athletes with bone mineral density measurements were considered. In conclusion, Triad CRA and RED-S CAT provide consensus on the majority of athletes at elevated (moderate or high) risk for low energy availability, but have less agreement on the specific risk level assigned.

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Combining Plant Sterols With Walking Lowers Postprandial Triacylglycerol More Than Walking Only in Chinese Men With Elevated Body Mass Index

This study examined if plant sterols and walking reduce postprandial triacylglycerol (TAG) concentrations in Chinese men with elevated body mass index (≥ 23.5 kg/m2). Fifteen Chinese men (mean [SD]: age = 25 [3] years and body mass index = 26.2 [1.5] kg/m2] completed four 10-day trials in random order with a 7- to 10-day washout between trials: (a) daily consumption of a control margarine while sedentary (C-S), (b) daily consumption of margarine containing 2 g/day of plant sterols while sedentary (PS-S), (c) daily consumption of a control margarine with 30-min daily walking (C-W), and (d) daily consumption of margarine containing 2 g/day of plant sterols with 30-min daily walking (PS-W). On Day 11 of each trial, postprandial TAG was measured after a high-fat milkshake. The 5-hr total area under the TAG curve was 22%, 25%, and 12% lower on PS-W (mean [SD]: 8.9 [4.3] mmol·5 hr/L) than C-S (11.4 [4.5] mmol·5 hr/L; p = .005; d = 0.56), PS-S (11.9 [4.9] mmol·5 hr/L; p = .004; d = 0.67), and C-W (10.1 [4.4] mmol·5 hr/L; p = .044; d = 0.27) trials, respectively. Similarly, 5-hr incremental area for PS-W (4.5 [2.7] mmol·5 hr/L) was 31%, 32%, and 18% lower than C-S (6.6 [3.3] mmol·5 hr/L; p = .005; d = 0.62), PS-S (6.6 [3.4] mmol·5 hr/L; p = .004; d = 0.64), and C-W (5.5 [2.8] mmol·5 hr/L; p = .032; d = 0.29). Ten days of daily plant sterol intake combined with walking presents an intervention strategy to lower postprandial TAG in Chinese men with elevated body mass index.

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Development of a New Tool for Managing Performance Nutrition: The Athlete Food Choice Questionnaire

This study aimed to develop and refine an Athlete Food Choice Questionnaire (AFCQ) to determine the key factors influencing food choice in an international cohort of athletes. A questionnaire that contained 84 items on a 5-point frequency scale was developed for this study. Athletes at the 2017 Universiade, in Taiwan, were invited to participate. Principal component analysis was utilized to identify key factors and to refine the questionnaire. Completed questionnaires were received from 156 athletes from 31 countries and 17 sports. The principal component analysis extracted 36 items organized into nine factors explaining 68.0% of variation. The nine factors were as follows: nutritional attributes of the food, emotional influences, food and health awareness, influence of others, usual eating practices, weight control, food values and beliefs, sensory appeal, and performance. The overall Kaiser–Meyer–Olkin measure was 0.75, the Bartlett test of sphericity was statistically significant, χ2(666) =2,536.50, p < .001, and all of the communalities remained >0.5. Intercorrelations were detected between performance and both nutritional attributes of the food and weight control. The price of food, convenience, and situational influences did not form part of the factorial structure. This research resulted in an AFCQ that includes factors specific to athletic performance and the sporting environment. The AFCQ will enable researchers and sports dietitians to better tailor nutrition education and dietary interventions to suit the individual or team. The next phase will test the accuracy and reliability of the AFCQ both during and outside of competition. The AFCQ is a useful tool to assist with management of performance nutrition for athletes.

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Development of an Athlete Diet Index for Rapid Dietary Assessment of Athletes

Food-based diet indices provide a practical, rapid, and inexpensive way of evaluating dietary intake. Rather than nutrients, diet indices assess the intake of whole foods and dietary patterns, and compare these with nutrition guidelines. An athlete-specific diet index would offer an efficient and practical way to assess the quality of athletes’ diets, guide nutrition interventions, and focus sport nutrition support. This study describes the development and validation of an Athlete Diet Index (ADI). Item development was informed by a review of existing diet indices, relevant literature, and in-depth focus groups with 20 sports nutritionists (median of 11 years’ professional experience) from four elite athlete sporting institutes. Focus group data were analyzed (NVivo 11 Pro; QSR International Pty. Ltd., 2017, Melbourne, Australia), and key themes were identified to guide the development of athlete-relevant items. A modified Delphi survey in a subgroup of sports nutritionists (n = 9) supported item content validation. Pilot testing with athletes (n = 15) subsequently informed face validity. The final ADI (n = 68 items) was categorized into three sections. Section A (n = 45 items) evaluated usual intake, special diets or intolerances, dietary habits, and culinary skills. Section B (n = 15 items) assessed training load, nutrition supporting training, and sports supplement use. Section C (n = 8 items) captured the demographic details, sporting type, and caliber. All of the athletes reported the ADI as easy (40%) or very easy (60% of participants) to use and rated the tool as relevant (37%) or very relevant (63% of participants) to athletes. Further evaluation of the ADI, including the development of a scoring matrix and validation compared with established dietary methodology, is warranted.

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Diet Quality Profile of Track-and-Field Paralympic Athletes

This study aimed to assess the diet quality of Brazilian Paralympic track-and-field team sprinters and its variation between days. All sprinters (n = 28) were invited, and 20 (13 men and seven women) accepted the invitation consisting of 13 athletes with visual impairment, four with cerebral palsy, and three with limb deficiency. The dietary intake was recorded by photographic register on four consecutive days, and diet quality was determined using a revised version of the Healthy Eating Index for the Brazilian population. Physical activity was assessed using an accelerometer, and metabolic unit information was used to classify exercise intensity. Variance Analysis Model and Bonferroni multiple comparisons were used to assess relationships between variables. The correlations between variables used Pearson linear correlation coefficient. The results show that revised version of the Healthy Eating Index score was classified as “needs to be modified” for all athletes. The maximum score for the components “Whole fruits,” “Total vegetables,” and “Dark green and orange vegetables and legumes” was achieved by 23.1% and 14.3%, 7.7% and 14.3%, and 46.2% and 57.8% of male and female athletes, respectively. Only 38.5% of the male athletes achieved the maximum score for the “Total cereal” component. Female athletes achieved higher scores than male athletes for the “Milk and dairy products” component (p = .03). Intake of whole grain cereals, dairy products, vegetables, and whole fruits needs modifications to improve adequate intake of vitamins and antioxidants, highlighting the need of continuous actions of nutrition education for this population.

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Does Mathematical Coupling Matter to the Acute to Chronic Workload Ratio? A Case Study From Elite Sport

Purpose: Criticisms of the acute to chronic workload ratio (ACWR) have been that the mathematical coupling inherent in the traditional calculation of the ACWR results in a spurious correlation. The purposes of this commentary are (1) to examine how mathematical coupling causes spurious correlations and (2) to use a case study from actual monitoring data to determine how mathematical coupling affects the ACWR. Methods: Training and competition workload (TL) data were obtained from international-level open-skill (basketball) and closed-skill (weightlifting) athletes before their respective qualifying tournaments for the 2016 Olympic Games. Correlations between acute TL, chronic TL, and the ACWR as coupled/uncoupled variations were examined. These variables were also compared using both rolling averages and exponentially weighted moving averages to account for any potential benefits of one calculation method over another. Results: Although there were some significant differences between coupled and uncoupled chronic TL and ACWR data, the effect sizes of these differences were almost all trivial (g = 0.04–0.21). Correlations ranged from r = .55 to .76, .17 to .53, and .88 to .99 for acute to chronic TL, acute to uncoupled chronic TL, and ACWR to uncoupled ACWR, respectively. Conclusions: There may be low risk of mathematical coupling causing spurious correlations in the TL–injury-risk relationship. Varying levels of correlation seem to exist naturally between acute and chronic TL variables regardless of coupling. The trivial to small effect sizes and large to nearly perfect correlations between coupled and uncoupled AWCRs also imply that mathematical coupling may have little effect on either calculation method, if practitioners choose to apply the ACWR for TL monitoring purposes.