Association between age and muscle function, architecture, and composition in long-distance master runners: a cross-sectional study

The aim of this study was to describe the muscle function, architecture, and composition of long-distance master runners, and verify the association between age and these variables. Additionally, different clusters of runners were compared based on age and training variables. Forty male runners (≥50 years) reported their training routine and had their muscle function evaluated through maximum knee extensor isometric peak torque (PT) assessed with an isokinetic dynamometer. The cross-sectional area (CSA), pennation angle (PA), fascicle length (FL), muscle thickness (MT), and echo intensity (EI) were evaluated through ultrasound (muscle architecture and composition). The participants were 58.7±6.2 years old and had been training for 18.4±10.3 years, 4 sessions/week with 298.8±164.7 min/week of training. The absolute torque was 226.92±63.44 N·m, and the specific torque (PT/CSA) was 7.29±3.78 N·m/cm2. Regarding muscle architecture, the phase angle was 17.34±4°, the fascicle angle 6.78±1.04 cm, muscle thickness 2.93±0.56 cm, and the cross-sectional area 21.24±5.88 cm2. Concerning muscle composition, the master runners showed echo intensity values of 62.05±11.68 AU. The analysis demonstrated a weak and negative association between age and some muscle architecture variables (CSA and MT) and muscle function (PT). No association was verified between age and muscle composition (EI). Age partially explained CSA, MT, and muscle function changes (13, 11, and 14%, respectively). Participants' high level of physical training might have contributed to the low association between these variables and the lack of association with muscle composition.

A influência de variáveis aeróbias e anaeróbias no teste de "sprints" repetidos / Influence of aerobic and anaerobic variables on repeated sprint tests

Resumo O objetivo deste estudo foi determinar o modo e o grau com que variáveis aeróbias e anaeróbias influenciam o desempenho e a fadiga em "sprints" repetidos (RS) na corrida. Para este fim, participaram do estudo 24 homens, sendo oito corredores velocistas, oito corredores fundistas e oito sujeitos ativos. Em uma pista sintética de atletismo estes sujeitos foram submetidos aos seguintes testes: 1) teste incremental para determinação do VO2max e da velocidade aeróbia máxima (VAM); 2) teste de velocidade constante realizado a 110%VAM para determinar a cinética do VO2 durante exercício e o máximo déficit acumulado de oxigênio (MAOD); 3) teste de "sprints" repetidos (10 "sprints" de 35 m, intercalados com 20 s de recuperação) para determinar o tempo total dos "sprints" (TT), tempo do melhor sprint (TM) e a queda do desempenho em percentual (Sdec). Para analisar a diferença entre os grupos e as relações entre as variáveis foram utilizadas a análise de variância ANOVA "one-way", complementada pelo teste de Tukey, e a correlação de Pearson, respectivamente. O TT em RS foi diferente significativamente entre todos os grupos (velocistas, 49,5 ± 0,8 s; fundistas, 52,6 ± 3,1 s; ativos, 55,5 ± 2,6 s) e Sdec foi significativamente inferior em fundistas comparado aos outros grupos (velocistas, 8,9 ± 2,1%; fundistas, 4,0 ± 2,0%; ativos, 8,4 ± 4,4%). O TT foi correlacionado significativamente com o TM (r = 0,85, p < 0,01) e com o MAOD (r = - 0,54, p < 0,01). Além disso, Sdec foi correlacionado significativamente com variáveis aeróbias (VO2max, r = - 0,58, < 0,01; VAM, r = - 0,59, p < 0,01; constante de tempo "tau", r = 0,45, p = 0,03). Portanto, conclui-se que apesar de índices aeróbios influenciarem na redução da fadiga em RS, o desempenho em RS é principalmente influenciado por características anaeróbias.(AU)

Abstract This study aimed to determine the manner and degree to which aerobic and anaerobic variables influence repeated running sprint performance and ability. Twenty four males (sprinters = 8, endurance runners = 8 and physical active subjects = 8) performed in a synthetic track the following tests: 1) incremental test to determine the VO2max and the maximum aerobic velocity (MAV); 2) constant velocity test performed at 110% of MAV to determine the VO2 kinetics and the maximum accumulated oxygen deficit (MAOD); 3) repeated sprint test (10 sprints of 35-m interspersed by 20s) to determine sprint total time (TT), best sprint time (BT) and score decrement (Sdec). Between-groups comparisons and the correlations between variables were analyzed by one-way ANOVA with a Tukey post-hoc tests and Pearson correlation, respectively. TT was significantly different among all groups (sprinters = 49.5 ± 0.8 s; endurance = 52.6 ± 3.1 s; active = 55.5 ± 2.6 s) and Sdec was significantly lower in endurance runners as compared with sprinters and physical active subjects (sprinters = 8.9 ± 2.1%; endurance = 4.0 ± 2.0%; active = 8.4 ± 4.4%). TT correlated significantly with BT (r = 0.85, p < 0.01) and MAOD (r = - 0.54, p < 0.01). Moreover, Sdec was significantly correlated with aerobic parameters (VO2max, r = - 0.58, p < 0.01; MAV, r = - 0.59, p < 0.01; time constant tau, r = 0.45, p = 0.03). In conclusion, although the aerobic parameters have an important contribution to RS ability, RS performance is mainly influenced by anaerobic parameters.(AU)

A new approach to assessment of energy expenditure during physical training / 体力科学

While the session-RPE (rating of perceived exertion) method can quantify training volume in athletes, this method is not able to evaluate energy expenditure (EE) during a training session. We developed an RPE-based activity record for assessing EE during athletic training, and we compared its results to those obtained using the flex-heart rate (flex-HR) method. The EE of nine female collegiate endurance runners was assessed by the RPE-based activity record and flex-HR methods during eight days in the normal training season. Subjects were asked to record their RPE in the record at 5-minute intervals, and to wear a HR monitor during training. All subjects also participated in an incremental treadmill exercise test, which was used to determine their RPE-EE and HR-EE regression equations. Although the RPE-based activity record significantly overestimated EE (RPE-activity record, 572 kcal/session; flex-HR method, 499 kcal/session; <i>p</i> = 0.031), it had high validity relative to the flex-HR method (intra-class correlation coefficient, 0.891; 95% confidence interval, 0.845–0.923) and there were no systematic errors in EE estimation between the two methods. Therefore, the RPE-based activity record can be used to assess EE during training in female runners. However, RPE-based activity record might overestimate EE for athletes who have more intermittent activities during training than endurance runners, because RPE takes more time for returning to the resting level than HR when the intensity of activity declines. Further research is needed to verify the validity of the RPE-based activity record for assessing EE during other sporting activities or measurement conditions, and to identify the factors affecting the degree of estimation error associated with this method.