It is not clear whether or not recreational runners can recover aerobic fitness and performance within one week after marathon running. This study aimed to investigate the effects of running a marathon race on aerobic fitness and performance one week later. Eleven recreational runners (six men, five women) completed the race in 3 h 36 min 20 s ± 41 min 34 s (mean ± standard deviation). Before and 7 days after the race, they performed a treadmill running test. Perceived muscle soreness was assessed before the race and for the following 7 days. The magnitude of changes in the treadmill running test was considered possibly trivial for maximal oxygen uptake (V˙O2max) (mean difference −1.2 ml/kg/min; ±90% confidence limits 2 ml/kg/min), unclear for %V˙O2max at anaerobic threshold (AT) (−0.5; ±4.1%) and RE (0.2; ±3.5 ml/kg/km), and likely trivial for both velocity at AT and peak (−0.2; ±0.49 km/h and −0.3; ±0.28 km/h). Perceived muscle soreness increased until 3 days after the race, but there were no clear differences between the values before the race and 4–7 days after it. These results show that physiological capacity associated with marathon running performance is recovered within 7 days after a marathon run.

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The purpose of this study was to investigate the relationship between classic physiological variables [maximal oxygen uptake (_VO 2 max), z _VO 2 max at anaerobic threshold (AT), and running economy (RE)] and running performance in recreational runners. 39 recreational runners (24 males and 15 females) underwent a treadmill running test to determine the classic physiological variables and velocity at AT (vAT). AT was deˆned as the point at which the respiratory exchange ratio stabilized above 1.0, and it was used as an indirect performance variable. Multiple regression analysis showed that 94z of vAT values were explained by all classic physiological variables (p＜0.001). In addition, all variables were signiˆcantly explanatory (_VO 2 max, p＜ 0.001; z _VO 2 max at AT, p＜0.001; and RE, p＜0.001). In total, 35 subjects had completed a marathon within the past year. For these subjects, single regression analysis was performed, which showed that 67z of recent marathon times was explained by vAT (r＝0.82, p＜0.05). This study indicated that during a treadmill running test, _VO 2 max, z _VO 2 max at AT, and RE can precisely explain vAT, which is highly correlated with recent marathon times.

PurposeIndividual variations in response of C-reactive protein (CRP) to acute strenuous exercise are less well known. The purpose of this study was to investigate the relationship between running economy and systemic inflammation following a marathon.Materials and methodsSixteen college recreational runners participated in this study. To measure maximal oxygen uptake and running economy, the treadmill running test was performed 1–2 weeks before the marathon race. Running economy was defined as oxygen cost (mL/kg/km) at submaximal running. CRP and muscle damage markers (creatine kinase and lactate dehydrogenase) were measured before and 1, 2, and 3 days after the race.ResultsAll subjects completed the race in 4 hours 7 minutes 43 seconds±44 minute 29 seconds [mean±SD]. The marathon running significantly increased CRP and muscle damage markers. The levels of inflammation and muscle damage peaked after 1 day and remained high throughout the 3-day recovery period compared to that before the race. Spearman correlation analysis showed that the change in CRP level was significantly positively correlated with oxygen cost (r=0.619, P=0.011) but not maximal oxygen uptake. There was no significant relationship in responses between muscle damage markers and CRP.ConclusionThese findings suggest that running economy is related to postmarathon race CRP response. Further study to clarify the cause of the relationship and clinical significance of transient increase in CRP is necessary.

Heart rate (HR) monitoring, which reflects exercise intensity and environmental factors, is often used as the basis for pacing strategies in a marathon race. However, it is difficult to obtain appropriate feedback for only the HR value since cardiovascular drift (CV drift) occurs during prolonged exercise. Recently, cardiac cost (CC, which is HR divided by running velocity) has been shown to be a potential index for evaluati ng CV drift during a marathon race. The aim of this study was to clarify the relationship between CV drift and performance in a marathon race.Fourteen male university student runners participated. Each took part in incremental tests on a treadmill and subsequently ran a marathon. CV drift was evaluated using differences between CC in the 0-5 km segment of the race and every 5 km segment (ΔCC) thereafter. Marathon performance was examined from two viewpoints: absolute performance (average running velocity during the race, Vmar), and relative performance (Vmar against velocity corresponding to the ventilatory threshold, vVT achv). Significant correlations were found between ΔCC and vVT achv in the 25-30 km, 30-35 km and 35-40 km race segments (r = −0.672, −0.671 and −0.661, respectively), suggesting that excessive CV drift had a negative impact on relative performance. Based on our results, we conclude that suppression of CV drift after 25 km is an important factor for improving relative performance in a marathon race.

Marathon running performance closely related to the several physiological and performance variables such as maximal oxygen uptake, running economy, and peak velocity. It is well known that muscle damage has a negative impact on the physiological and performance variables. Thus, restarting training or participating in the race in a state where recovery is inadequate may cause injury and loss of race performance. The aims of this review article are to (1) summarize the previous studies that investigated effects of a marathon race on muscle damage and physiological and performance variables, (2) discuss the middle and long term effects of marathon races on physical condition, (3) suggest the practical strategy for some runners that participate in consecutive races within a short period.

Some recreational runners participate in consecutive races within a short period. A high frequency of participation may not allow for su‹cient recovery time, leading to overreaching. This case study reports on the training load, physiological variables, performance, and psychological state of a male recreational runner during a 16-week marathon season. The runner completed four marathon races over a period of eight weeks. Training load was quantiˆed based on the cumulative time spent in three intensity zones (zone 1:＜the ventilatory threshold; zone 2: between the ventilatory threshold and respiratory compensation point; zone 3:＞the respiratory compensation point) using heart rate monitoring. The Hooper questionnaire was completed every morning to quantify sleep, stress, fatigue, and muscle soreness. The runner performed four identical treadmill running tests throughout the season. The coe‹cient of variation for maximal velocity and the physiological variables was 1.0 and 1.8-5.2, respectively. Pearson correlation showed signiˆcant relationships between training load and stress, fatigue, and muscle soreness. There was no signiˆcant relationship between training load and sleep. In conclusion, it appeared that the subject runner was able to complete four marathon races without overreaching. Theseˆndings suggest that the training load and Hooper questionnaire are practical tools for monitoring recreational runners during the marathon season.

Background: The effects of the use of continuous glucose monitoring (CGM) in elite endurance athletes are unclear. This case study reported the blood glucose (BG) levels of a female national-level marathon runner during a real-world marathon race. Methods: Heart rate and BG levels were monitored throughout the race. Results: The runner completed the race in 2:46 h:min, which was an improvement from her previous personal record by just under one min. Her BG levels were stable from approximately 5–40 km of the race at a mean concentration of 7.13 mmol/L, with a standard deviation of 0.20 mmol/L and a coefficient of variation of 2.8%. Increases in BG levels and heart rate were observed 6 min after the race and during the 40–42.195 km section, respectively. Conclusions: The runner broke her own record and exhibited stable BG levels throughout the race, with the highest BG value detected immediately after the race. Considering that quantity, content, and timing of pre-race meals and supplementation during the race can affect BG levels, future studies should assess additional detailed parameters in more detail and monitor multiple races with the same elite endurance athletes to acquire more definitive evidence on CGM usefulness among elite endurance athletes.