Ratings of Perceived Exertion During Walking Predicts Endurance Independent of Physiological Effort in Older Women

Hunter, GR, Neumeier, WH, Chandler-Laney, PC, Carter, SJ, Borges, JH, Hornbuckle, LM, Plaisance, EP, and Fisher, G. Ratings of perceived exertion during walking predicts endurance independent of physiological effort in older women. J Strength Cond Res 34(5): 1340-1344, 2020-This study aimed to determine whether ratings of perceived exertion (RPE) and physiological effort at different exercise intensities relate to exercise endurance. Ninety-eight sedentary women (older than 60 years) completed 3 submaximal locomotion tasks: (a) stair climbing, (b) flat walking at 2 mph, and (c) grade walking at 2 mph. Maximal treadmill endurance was measured at least 3 days before the submaximal tests. Oxygen uptake was measured during all tests, and RPE were collected for the submaximal tasks. Ratings of perceived exertion during moderate-intensity exercise (walking on the flat at 43% V[Combining Dot Above]O2max, partial R = -0.35, p < 0.01), but not higher intensity exercise (grade walk at 59% V[Combining Dot Above]O2max, p = 0.49, and stair climbing at 67% V[Combining Dot Above]O2max, p = 0.17), were related to endurance even after adjusting for aerobic capacity and physiological effort (composite of maximal heart rate, ventilation, and respiratory exchange ratio). However, physiological effort was significantly related to endurance for the higher intensity exercise (both grade walk and stair climbing partial R >-0.24, p < 0.02). Similar to previous findings that subjective ratings of fatigue at rest were related to RPE during low/moderate-intensity exercise, but not higher intensity exercise, these data further support Ekkekakis's dual-mode hypothesis that cognitive factors influence RPE during low/moderate-intensity exercise. A practical application is that the coach and personal trainer should know that physiological effort seems to play a greater role in influencing endurance than RPE as intensity of exercise increases.

Accuracy of Bioelectrical Impedance Analysis in Estimated Longitudinal Fat-Free Mass Changes in Male Army Cadets

Introduction

Bioelectrical impedance analysis (BIA) is a practical and rapid method for making a longitudinal analysis of changes in body composition. However, most BIA validation studies have been performed in a clinical population and only at one moment, or point in time (cross-sectional study). The aim of this study is to investigate the accuracy of predictive equations based on BIA with regard to the changes in fat-free mass (FFM) in Brazilian male army cadets after 7 mo of military training. The values used were determined using dual-energy X-ray absorptiometry (DXA) as a reference method.

Materials and Methods

The study included 310 male Brazilian Army cadets (aged 17-24 yr). FFM was measured using eight general predictive BIA equations, with one equation specifically applied to this population sample, and the values were compared with results obtained using DXA. The student's t-test, adjusted coefficient of determination (R2), standard error of estimation (SEE), Lin's approach, and the Bland-Altman test were used to determine the accuracy of the predictive BIA equations used to estimate FFM in this population and between the two moments (pre- and post-moment).

Results

The FFM measured using the nine predictive BIA equations, and determined using DXA at the post-moment, showed a significant increase when compared with the pre-moment (p < 0.05). All nine predictive BIA equations were able to detect FFM changes in the army cadets between the two moments in a very similar way to the reference method (DXA). However, only the one BIA equation specific to this population showed no significant differences in the FFM estimation between DXA at pre- and post-moment of military routine. All predictive BIA equations showed large limits of agreement using the Bland-Altman approach.

Conclusion

The eight general predictive BIA equations used in this study were not found to be valid for analyzing the FFM changes in the Brazilian male army cadets, after a period of approximately 7 mo of military training. Although the BIA equation specific to this population is dependent on the amount of FFM, it appears to be a good alternative to DXA for assessing FFM in Brazilian male army cadets.

Divergent Blood Pressure Response After High-Intensity Interval Exercise: A Signal of Delayed Recovery?

Hunter, GR, Fisher, G, Bryan, DR, Borges, JH, and Carter, SJ. Divergent blood pressure response after high-intensity interval exercise: a signal of delayed recovery? J Strength Cond Res 32(11): 3004-3010, 2018-The objective of this commentary is to highlight potential factors influential to the adaptation of high-intensity exercise. Herein, we present a rationale supporting the contention that elevated systolic blood pressure, after a bout of high-intensity exercise, may be indicative of delayed/incomplete recovery. Relative to type I skeletal muscle fibers, the unique cellular/vascular characteristics of type II muscle fibers may necessitate longer recovery periods, especially when exposed to repeated high-intensity efforts (i.e., intervals). In addition to the noted race disparities in cardiometabolic disease risk, including higher mean blood pressures, African Americans may have a larger percentage of type II muscle fibers, thus possibly contributing to noted differences in recovery after high-intensity exercise. Given that optimal recovery is needed to maximize physiological adaptation, high-intensity training programs should be individually-tailored and consistent with recovery profile(s). In most instances, even among those susceptible, the risk to nonfunctional overreaching can be largely mitigated if sufficient recovery is integrated into training paradigms.

Racial Differences in Relative Skeletal Muscle Mass Loss During Diet-Induced Weight Loss in Women

OBJECTIVE

It is unclear whether there are race-specific differences in the maintenance of skeletal muscle during energy restriction. Changes in relative skeletal muscle index (RSMI; limb lean tissue divided by height squared) were compared following (1) diet alone, (2) diet + aerobic training, or (3) diet + resistance training.

METHODS

Overweight, sedentary African American (AA; n = 72) and European American (EA; n = 68) women were provided an 800-kcal/d diet to reduce BMI < 25 kg/m² . Regional fat-free mass was measured with dual-energy x-ray absorptiometry. Steady-state VO₂ and heart rate responses during walking were measured.

RESULTS

AA women had greater RSMI and preserved RSMI during diet alone, while RSMI was significantly reduced among EA women (EA women -3.6% vs. AA women + 1.1%; P < 0.05). Diet + resistance training subjects retained RSMI (EA women + 0.2% vs. AA women + 1.4%; P = 50.05), whereas diet + aerobic training subjects decreased RSMI (EA women -1.4% vs. AA women -1.5%; P < 0.05). Maintenance of RSMI was related to delta walking ease and economy.

CONCLUSIONS

Compared with AA women, EA women are less muscular and lose more muscle during weight loss without resistance training. During diet-induced weight loss, resistance training preserves skeletal muscle, especially among premenopausal EA women. Maintenance of muscle during weight loss associates with better ease and economy of walking.

Adaptive thermogenesis and changes in body composition and physical fitness in army cadets

BACKGROUND

To analyze the association between a 34-week military training on body composition, physical fitness and compensatory changes in resting energy expenditure (REE) recognized as adaptive thermogenesis (AT). We also explored if regional body composition changes were related to AT.

METHODS

Twenty-nine male army cadets, aged 17 to 22 years were tested at baseline (T0) and after 34-weeks military training (T1). Physical training was performed 5 days/week during 90 minutes/day. Measurements included body composition by dual-energy x-ray absorptiometry; physical fitness by 3000-m running, pull-up, 50-m freestyle swimming, push-up and sit-up tests; REE measured by indirect calorimetry (REEm) and predicted from fat-free mass (FFM), fat mass (FM) and ethnicity at T0 (REEp). %AT was calculated using values at T1: 100(REEm/REEp-1); and AT (kcal/day) as %AT/100 multiplied by baseline REEm.

RESULTS

Physical training was associated with increases of lean soft tissue (LST) (∆1.2±1.3 kg), FM (∆1.4±1.3 kg), FFM (∆1.2±1.3 kg) and physical fitness (P<0.01), but no REE changes (∆59.6±168.9 kcal/day) and AT were observed (P>0.05). Though a large variability was found, AT was partially explained by trunk LST (r2=0.17, P=0.027). Individuals showing a higher AT response demonstrated a higher trunk LST increase (∆0.8±0.7 kg, P<0.05).

CONCLUSIONS

The military training increased LST, FM, FFM and physical fitness. Though no mean changes in AT occurred, a large individual variability was observed with some participants increasing REE beyond the expected body composition changes, suggesting a spendthrift phenotype. Changes of trunk LST may play an important role in the AT response observed in these individuals.

Validity of Bioelectrical Impedance Analysis to Estimation Fat-Free Mass in the Army Cadets

Background: Bioelectrical Impedance Analysis (BIA) is a fast, practical, non-invasive, and frequently used method for fat-free mass (FFM) estimation. The aims of this study were to validate predictive equations of BIA to FFM estimation in Army cadets and to develop and validate a specific BIA equation for this population. Methods: A total of 396 males, Brazilian Army cadets, aged 17–24 years were included. The study used eight published predictive BIA equations, a specific equation in FFM estimation, and dual-energy X-ray absorptiometry (DXA) as a reference method. Student’s t-test (for paired sample), linear regression analysis, and Bland–Altman method were used to test the validity of the BIA equations. Results: Predictive BIA equations showed significant differences in FFM compared to DXA (p < 0.05) and large limits of agreement by Bland–Altman. Predictive BIA equations explained 68% to 88% of FFM variance. Specific BIA equations showed no significant differences in FFM, compared to DXA values. Conclusion: Published BIA predictive equations showed poor accuracy in this sample. The specific BIA equations, developed in this study, demonstrated validity for this sample, although should be used with caution in samples with a large range of FFM.