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Objective: In healthy adults, it is generally accepted that women have less upper body muscle mass compared to men. However, it is unknown whether there are sex differences in skeletal muscle distribution in highly trained large‐sized athletes. Our aim was to compare the skeletal muscle size distribution between large‐sized male and female athletes. Methods: Ten female athletes (>80 kg body mass) and twenty‐one male athletes (>100 kg body mass) had muscle thickness (MT) and subcutaneous adipose tissue thickness measured by ultrasound at nine sites on the anterior and posterior aspects of the body. Total muscle mass (SM) was estimated from an ultrasound‐derived prediction equation. Body fat percentage and fat‐free mass were calculated from ultrasound measured subcutaneous fat thickness. Results: The average SM in female athletes (30.0 kg) was approximately 70% of the mean value of the male athletes (45.3 kg).With respect to MT, the relative values of femaleto male athletes were 68% to 78% in the upper body and 85% to 92% in the lower body. Similar results were observed when analyzing data for male and female athletes (n = 5 each) who were pair matched for height. Conclusion: The relative values of MT for female/male athletes were higher in the lower body compared to the upper body. This is similar to that observed in healthy non‐athletes indicating that this difference is not due to resistance training. The lower muscle mass in the arms and trunk of females appears to be a true sex difference but the cause of this difference is unknown. [ABSTRACT FROM AUTHOR]

Narrow cuffs cause less discomfort than wide cuffs immediately following elbow flexion exercise in combination with blood flow restriction, possibly due to a balling up effect of the bicep underneath the cuff. In this study, we sought to examine the impact of cuff width, sex, and pressure on perceived discomfort in the quadriceps, following knee extensions. One hundred participants completed three separate experiments. In Experiment 1, we compared participants' discomfort at rest after using a 5 and a 12 cm cuff. In Experiment 2, we compared the discomfort from these two cuffs after four sets of exercise. In Experiment 3, we used the same exercise protocol as in Experiment 2, but we compared the discomfort between a 12 cm cuff inflated to an inappropriate pressure and a 12 cm cuff inflated to the recommended pressure. We found no sex differences in Experiments 1 and 3. In Experiment 1, the narrow cuff had higher discomfort (16 vs 12 AU). In Experiment 2, men reported higher discomfort than women, with no discomfort differences related to cuff width, though narrow cuffs were most preferred. In Experiment 3, cuffs inflated to a pressure intended for narrow cuffs were associated with higher discomfort, and participants preferred to use it less. In summary, we found no strong evidence for discomfort differences due to cuff width. There was some indication that participants preferred narrow cuffs with pressures inflated to the recommended relative pressure. Muscle shape may influence how cuff width affects discomfort. [ABSTRACT FROM AUTHOR]

Objectives: To examine the absolute and relative skeletal muscle mass (SM) in female athletes and to discuss the potential upper limit of whole‐body muscle mass between large sized female and male athletes. Methods: Forty‐five female athletes and forty‐five recreationally active females (control) had muscle thickness measured by ultrasound at nine sites on the anterior and posterior aspects of the body. SM was estimated from an ultrasound‐derived prediction equation. Body fat percentage and fat‐free mass (FFM) were calculated from ultrasound measured subcutaneous fat thickness. To eliminate fat‐free component of adipose tissue (FFAT), we calculated FFM minus FFAT (FFM‐FFAT). Results: FFM, FFM‐FFAT, and muscle mass were markedly higher in athletes. Fat Mass was similar (Athlete: 14.9 kg vs Control: 12.9 kg [median value]). The large‐sized female athletes had approximately 9 to 11 kg FFAT which corresponds to about 10% to 15% of FFM. Seven of the female athletes had more than 60 kg of FFM‐FFAT, the largest of whom had 77.0 kg of FFM‐FFAT. SM increased in a parabolic fashion reaching a value of 35 kg SM beyond 100 kg body mass. Only one of the athletes had a SM index of more than 13 kg/m2. Conclusions: Female athletes had much greater muscle mass than controls. In large‐sized female athletes, the influence of FFAT needs to be considered when interpreting their FFM. In addition, the largest SM index in female athletes was 13.2 kg/m2, which was approximately 77% of that observed with the largest male athlete ever recorded. This difference appears similar to that observed in nonathletes. [ABSTRACT FROM AUTHOR]

It is generally believed that more muscle mass in the lower body reflects more muscular strength and power. If true, greater ground reaction forces may be facilitated from increasing muscle mass, which may result in higher maximal running speeds. One method to assess the potential contributions of body composition (i.e. muscle mass and fat mass) to sprint performance is to examine the associations between those variables within each sprinter across time. The present study examined the relationships between longitudinal changes in body composition and sprint performance. Twelve elite female sprinters (9 of whom participated in the Olympics and/or the World Championships) had total body muscle mass, leg muscle mass, and body fat estimated using ultrasound. For each participant, these measurements lasted at least 5 consecutive years and the longest was 10 consecutive years (average 7 ± 1.5 years). The best sprint time in each season was used for evaluating sprint performance. Our unadjusted model indicated that muscle mass, and body fat correlated favourably with sprint performance over time. After adjusting for the error variance attributable to body fat, the relationship muscle mass with sprint performance is largely eliminated. In the first adjusted model, the partial correlations were r = −0.20 for leg muscle mass and r = 0.46 for body fat. In the second, the partial correlations were r = −0.20 for total muscle mass and r = 0.50 for body fat. In conclusion, these findings may suggest that reducing fat mass may have a greater impact on sprint performance than increasing muscle mass. [ABSTRACT FROM AUTHOR]

Training one limb with a high-load has been shown to augment strength changes in the opposite limb training with a low-load (via cross-education of strength), indicating that within-subject models can be problematic when investigating strength changes. This study examined if the cross-education of strength from unilateral high-load training could augment the strength changes in the opposite arm undergoing the same unilateral high-load training. 160 participants were randomized to one of four groups: (1) training on the dominant arm followed by the non-dominant arm (D + ND), (2) training on the dominant arm only (D-Only), (3) training on the non-dominant arm only (ND-Only), and (4) a non-exercise control. All exercise groups performed 18 sessions of unilateral high-load elbow flexion exercise over 6 weeks. Participants were compared for changes in 1RM strength and muscle thickness. Changes in strength of the non-dominant arm were greater in D + ND (2.7 kg) and ND-Only (2.6 kg) compared to D-Only (1.5 kg) and control (-0.2 kg), while the changes were greater in D-Only compared to control. The same finding was observed in the dominant arm. Only the arms being directly trained observed increases in muscle thickness. Unilateral high-load resistance training increased strength in the opposite untrained arm, without changes in muscle thickness. This cross-education of strength did not augment the strength changes in the contralateral arm undergoing the same unilateral high-load training. However, it does not necessarily indicate that within-subject models are methodologically sound to investigate strength change if both limbs are trained with a high-load., (© 2024 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Abstract: Changes in skeletal muscle size may be affected by resting blood flow (e.g., nutrient delivery) and this change in size is a hypothesized mechanism for changes in strength., Purpose: To determine: 1) whether the relationship between isometric training and muscle growth depends on baseline blood flow or is mediated by a change in blood flow and 2) whether muscle growth mediates changes in maximal isometric strength., Methods: 179 participants were randomized into: low-intensity isometric handgrip exercise (LI), low-intensity isometric handgrip exercise with blood flow restriction (LI-BFR), maximal handgrip exercise (MAX), and a non-exercise control (CONTROL). Muscle thickness, strength, and resting limb blood flow were measured before and after the six-week intervention., Results: Baseline blood flow did not moderate training effects on muscle thickness changes (MTHchg) (p = 0.666), and moderated mediation tests were non-significant. Although the LI-BFR group showed a significant effect on MTHchg (p = 0.018), MTHchg was not significantly related to handgrip strength change (HGchg) (p = 0.281), suggesting no mediation of the training-to-strength effect by MTHchg. Both the LI-BFR (p = 0.004) and MAX (p < 0.001) groups exhibited positive direct effects on HGchg compared to CONTROL. Furthermore, there were no differences between training groups and CONTROL on blood flow change (BFchg), BFchg and MTHchg were not significantly related, and neither BFchg nor MTHchg predicted HGchg, providing no evidence for mediated pathways., Conclusions: Muscle growth may not have occurred to an extent that would require vascular adaptation. Training maximally induced the greatest strength adaptations but was seemingly not driven by muscle growth., Competing Interests: Conflict of Interest and Funding Source: This study received no funding. The authors declare that there is no conflict of interest related to the content of this article., (Copyright © 2024 by the American College of Sports Medicine.)

Progressive overload describes the gradual increase of stress placed on the body during exercise training, and is often quantified (i.e. in resistance training studies) through increases in total training volume (i.e. sets × repetitions × load) from the first to final week of the exercise training intervention. Within the literature, it has become increasingly common for authors to discuss skeletal muscle growth adaptations in the context of increases in total training volume (i.e. the magnitude progression in total training volume). The present manuscript discusses a physiological rationale for progressive overload and then explains why, in our opinion, quantifying the progression of total training volume within research investigations tells very little about muscle growth adaptations to resistance training. Our opinion is based on the following research findings: (1) a noncausal connection between increases in total training volume (i.e. progressively overloading the resistance exercise stimulus) and increases in skeletal muscle size; (2) similar changes in total training volume may not always produce similar increases in muscle size; and (3) the ability to exercise more and consequently amass larger increases in total training volume may not inherently produce more skeletal muscle growth. The methodology of quantifying changes in total training volume may therefore provide a means through which researchers can mathematically determine the total amount of external 'work' performed within a resistance training study. It may not, however, always explain muscle growth adaptations., (© 2024 Institute of Physics and Engineering in Medicine. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Purpose: To 1) examine whether blood flow restriction would provide an additional exercise-induced hypoalgesic response at an upper and lower limb when it is incorporated with low-load resistance exercise until failure, and 2) examine if increases in blood pressure and discomfort, with blood flow restricted exercise, would mediate the exercise-induced hypoalgesia over exercise without blood flow restriction. Methods: Forty healthy young participants completed two trials: four sets of unilateral knee extension exercise to failure at 30% of one-repetition maximum, with and without blood flow restriction. Pressure pain thresholds were assessed before (twice) and 5-min post exercise at an upper and lower limb. Blood pressure and discomfort ratings were recorded to examine mediating effects on exercise-induced hypoalgesia with blood flow restricted exercise. Results: Pressure pain threshold increased following both exercise conditions compared to a control, without any differences between exercise conditions at the upper (exercise conditions vs. control: ~0.37 kg/cm 2 ) and lower (exercise conditions vs. control: ~0.60 kg/cm 2 ) limb. The total number of repetitions was lower for exercise with blood flow restriction compared to exercise alone [median difference (95% credible interval) of -27.0 (-29.8, -24.4) repetitions]. There were no mediating effects of changes in blood pressure, nor changes in discomfort, for the changes in pressure pain threshold at either the upper or lower limb. Conclusion: The addition of blood flow restriction to low-load exercise induces a similar hypoalgesic response to that of non-blood flow restricted exercise, with a fewer number of repetitions.

Increased plasma volume is often reported as a cause or symptom of hypertension in individuals with obesity. However, these individuals are often compared to normal weight normotensive individuals. Since higher plasma volumes have been reported in larger individuals, it is possible that plasma volume is actually lower in obese hypertensive individuals compared to normotensive obese individuals. This may be important for better understanding the clinical manifestation of hypertension between weight categories. National Health and Nutritional Examination Survey (cycles 1999-2018) data were used to examine the relationship between plasma (derived from the Straus formula), blood pressure (measured with an automated device) and body mass index. We observed an inverse relationship between estimated plasma volume and systolic (B = -1.68 (95% CI: -2.06, -1.30) mmHg), p < 0.0001), diastolic (B = -3.35 (95% CI: -3.61, -3.08) mmHg) p < 0.0001), and mean arterial pressure (B = -2.79 (95% CI: -3.05, -2.53) mmHg) p < 0.0001). The relationship between estimated plasma volume and diastolic blood pressure (interaction term: B = -0.069 (-0.10, -0.03), p < 0.0001) did depend on BMI. The "normal weight" group had the lowest slope and this slope was significantly different from the "obese" (B = -1.47 (95% CI: -1.88, -1.07)) and "overweight" (B = -1.11 (-1.55, -0.67)) groups. Plasma volume is lower in hypertensive individuals regardless of weight status, but this relationship is more pronounced among obese individuals., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Context: The perceived tightness scale is suggested to be an effective method for setting subocclusive pressures with practical blood flow restriction. However, the reliability of this scale is unknown and is important as the reliability will ultimately dictate the usefulness of this method., Objective: To determine the reliability of the perceived tightness scale and investigate if the reliability differs by sex., Design: Within-participant, repeated-measures., Setting: University laboratory., Participants: Twenty-four participants (12 men and 12 women) were tested over 3 days., Main Outcome Measures: Arterial occlusion pressure (AOP) and the pressure at which the participants rated a 7 out of 10 on the perceived tightness scale in the upper arm and upper leg., Results: The percentage coefficient of variation for the measurement was approximately 12%, with no effect of sex in the upper (median δ [95% credible interval]: 0.016 [-0.741, 0.752]) or lower body (median δ [95% credible interval]: 0.266 [-0.396, 0.999]). This would produce an overestimation/underestimation of ∼25% from the mean perceived pressure in the upper body and ∼20% in the lower body. Participants rated pressures above their AOP for the upper body and below for the lower body. At the group level, there were differences in participants' ratings for their relative AOP (7 out of 10) between day 1 and days 2 and 3 for the lower body, but no differences between sexes for the upper or lower body., Conclusions: The use of the perceived tightness scale does not provide reliable estimates of relative pressures over multiple visits. This method resulted in a wide range of relative AOPs within the same individual across days. This may preclude the use of this scale to set the pressure for those implementing practical blood flow restriction in the laboratory, gym, or clinic.