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Hugh Trenchard, Andrew Renfree and Derek M. Peters

Purpose:

Drafting in cycling influences collective behavior of pelotons. Although evidence for collective behavior in competitive running events exists, it is not clear if this results from energetic savings conferred by drafting. This study modeled the effects of drafting on behavior in elite 10,000-m runners.

Methods:

Using performance data from a men’s elite 10,000-m track running event, computer simulations were constructed using Netlogo 5.1 to test the effects of 3 different drafting quantities on collective behavior: no drafting, drafting to 3 m behind with up to ~8% energy savings (a realistic running draft), and drafting up to 3 m behind with up to 38% energy savings (a realistic cycling draft). Three measures of collective behavior were analyzed in each condition: mean speed, mean group stretch (distance between first- and last-placed runner), and runner-convergence ratio (RCR), which represents the degree of drafting benefit obtained by the follower in a pair of coupled runners.

Results:

Mean speeds were 6.32 ± 0.28, 5.57 ± 0.18, and 5.51 ± 0.13 m/s in the cycling-draft, runner-draft, and no-draft conditions, respectively (all P < .001). RCR was lower in the cycling-draft condition but did not differ between the other 2. Mean stretch did not differ between conditions.

Conclusions:

Collective behaviors observed in running events cannot be fully explained through energetic savings conferred by realistic drafting benefits. They may therefore result from other, possibly psychological, processes. The benefits or otherwise of engaging in such behavior are as yet unclear.

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Marc Sim, Brian Dawson, Grant Landers, Dorine W. Swinkels, Harold Tjalsma, Debbie Trinder and Peter Peeling

The effect of exercise modality and intensity on Interleukin-6 (IL-6), iron status, and hepcidin levels was investigated. Ten trained male triathletes performed 4 exercise trials including low-intensity continuous running (L-R), low-intensity continuous cycling (L-C), high-intensity interval running (H-R), and high-intensity interval cycling (H-C). Both L-R and L-C consisted of 40 min continuous exercise performed at 65% of peak running velocity (vVO2peak) and cycling power output (pVO2peak), while H-R and H-C consisted of 8 × 3-min intervals performed at 85% vVO2peak and pVO2peak. Venous blood samples were drawn pre-, post-, and 3 hr postexercise. Significant increases in postexercise IL-6 were seen within each trial (p < .05) and were significantly greater in H-R than L-R (p < .05). Hepcidin levels were significantly elevated at 3 hr postexercise within each trial (p < .05). Serum iron levels were significantly elevated (p < .05) immediately postexercise in all trials except L-C. These results suggest that, regardless of exercise mode or intensity, postexercise increases in IL-6 may be expected, likely influencing a subsequent elevation in hepcidin. Regardless, the lack of change in postexercise serum iron levels in L-C may indicate that reduced hemolysis occurs during weight-supported, low-intensity activity.

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Nicola Giovanelli, Filippo Vaccari, Mirco Floreani, Enrico Rejc, Jasmine Copetti, Marco Garra, Lea Biasutti and Stefano Lazzer

to the best of our knowledge the effects of SMFR on running performance have not been investigated yet. The energy cost of running (Cr) plays a relevant role in determining performance among middle- and long-distance runners along with the maximal oxygen uptake and the fraction of it that is

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Everton C. do Carmo, Renato Barroso, Andrew Renfree, Natalia R. da Silva, Saulo Gil and Valmor Tricoli

head-to-head (HTH) running race situation and compare them with time trial running. Methods Participants A total of 14 trained male runners (33.3 [6.1] y, 69.5 [9.1] kg, 172 [8] cm, 56.7 [6.2] mL·kg −1 ·min −1 ), with at least 2 years’ of experience and able to run 10 km in <45 minutes, participated in

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Joanne L. Fallowfield, Clyde Williams and Rabindar Singh

Recovery from prolonged exercise involves both rehydration and replenishment of endogenous carbohydrate stores. The present study examined the influence of ingesting a carbohydrate-electrolyte (CE) solution following prolonged running, on exercise capacity 4 hr later. Twelve men and 4 women were divided into two matched groups, which were randomly assigned to either a control (P) or a carbohydrate (CHO) condition. Both groups ran at 70% of maximal oxygen uptake (VO2max) on a level treadmill for 90 min or until volitional fatigue (R,), and they ran at the same %VO2max to exhaustion 4 hr later to assess endurance capacity (R2). The CHO group ingested a 6.9% CE solution providing 1.0 g CHO · kg body weight−1 immediately post-R, and again 2 hr later. The P group ingested equal volumes of a placebo solution. Run times (mean ± SEM) for Rj did not differ between the groups (P 86.3 ± 3.8 min; CHO 87.5 ± 2.5 min). The CHO group ran 22.2 (±3.5) min longer than the P group during R2 (P 39.8 ± 6.1 min; CHO 62.0 ± 6.2 min) (p < .05). Thus, ingesting a 6.9% carbohydrate-electrolyte beverage following prolonged, constant-pace running improves endurance capacity 4 hr later.

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Konstantinos Tsintzas, Raymond Liu, Clyde Williams, Ian Campbell and George Gaitanos

Seven experienced endurance runners completed a 30-km road race on two occasions separated by 10 days. On each occasion the subjects consumed 250 ml of either a 5% carbohydrate (CHO) solution or nonflavored tap water (W) immediately prior to the start of the race, and 150 ml of the assigned fluid every 5 km thereafter. Performance time for the CHO trial was faster compared with the time recorded for the W trial (128.3 ± 19.9 min vs. 131.2 ± 18.7 min [p<0.01] respectively). Running speed was maintained throughout the race in the CHO trial, whereas a decrease in the running speed occurred after 25 km (p<0.05) in the W trial. No difference was found between the two trials in blood glucose concentration, plasma electrolyte concentrations, body weight loss, change in plasma volume, and rating of perceived exertion. Blood lactate concentration was higher at 25 km during the CHO trial compared with the W trial (p<0.01), but plasma FFA and glycerol concentrations were lower at 30 km during the CHO trial than during the W trial (p<0.05). In conclusion, this study shows that performance time for a 30-km road race is improved after ingesting a 5% CHO solution.

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Thibault Lussiana, Cyrille Gindre, Kim Hébert-Losier, Yoshimasa Sagawa, Philippe Gimenez and Laurent Mourot

Purpose:

No unique or ideal running pattern is the most economical for all runners. Classifying the global running patterns of individuals into 2 categories (aerial and terrestrial) using the Volodalen method could permit a better understanding of the relationship between running economy (RE) and biomechanics. The main purpose was to compare the RE of aerial and terrestrial runners.

Methods:

Two coaches classified 58 runners into aerial (n = 29) or terrestrial (n = 29) running patterns on the basis of visual observations. RE, muscle activity, kinematics, and spatiotemporal parameters of both groups were measured during a 5-min run at 12 km/h on a treadmill. Maximal oxygen uptake (V̇O2max) and peak treadmill speed (PTS) were assessed during an incremental running test.

Results:

No differences were observed between aerial and terrestrial patterns for RE, V̇O2max, and PTS. However, at 12 km/h, aerial runners exhibited earlier gastrocnemius lateralis activation in preparation for contact, less dorsiflexion at ground contact, higher coactivation indexes, and greater leg stiffness during stance phase than terrestrial runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of the running cycle, shorter flight time, greater leg compression, and a more rear-foot strike.

Conclusions:

Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forward rather than upward to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

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Martin Buchheit, Bachar Haydar, Karim Hader, Pierre Ufland and Said Ahmaidi

Purpose:

To examine physiological responses to submaximal feld running with changes of direction (COD), and to compare two approaches to assess running economy (RE) with COD, ie, during square-wave (SW) and incremental (INC) exercises.

Methods:

Ten male team-sport athletes performed, in straight-line or over 20 m shuttles, one maximal INC and four submaximal SW (45, 60, 75 and 90% of the velocity associated with maximal pulmonary O2 uptake [vVO2pmax]). Pulmonary (VO2p) and gastrocnemius (VO2m) O2 uptake were computed for all tests. For both running mode, RE was estimated as the O2 cost per kilogram of bodyweight, per meter of running during all SW and INC.

Results:

Compared with straight-line runs, shuttle runs were associated with higher VO2p (eg, 33 ± 6 vs 37 ± 5 mL O2·min–1·kg–1 at 60%, P < .01) and VO2m (eg, 1.1 ± 0.5 vs 1.3 ± 0.8 mL O2·min–1·100 g–1 at 60%, P = .18, Cohen’s d = 0.32). With COD, RE was impaired during SW (0.26 ± 0.02 vs 0.24 ± 0.03 mL O2·kg–1·m–1, P < .01) and INC (0.23 ± 0.04 vs 0.16 ± 0.03 mL O2·kg–1·m–1, P < .001). For both SW and INC tests, the changes in RE with COD were related to height (eg, r = .56 [90%CL, 0.01;0.85] for SW) and weekly training/competitive volume (eg, r = –0.58 [–0.86;–0.04] for SW). For both running modes, RE calculated from INC was better than that from SW (both P < .001).

Conclusion:

Although RE is impaired during feld running with COD, team-sport players of shorter stature and/or presenting greater training/competitive volumes may present a lower RE deterioration with COD. Present results do not support the use of INC to assess RE in the feld, irrespective of running mode.

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Patrick B. Wilson, Stacy J. Ingraham, Chris Lundstrom and Gregory Rhodes

Background:

The effects of dietary factors such as carbohydrate (CHO) on endurance-running performance have been extensively studied under laboratory-based and simulated field conditions. Evidence from “reallife” events, however, is poorly characterized. The purpose of this observational study was to examine the associations between prerace and in-race nutrition tendencies and performance in a sample of novice marathoners.

Methods:

Forty-six college students (36 women and 10 men) age 21.3 ± 3.3 yr recorded diet for 3 d before, the morning of, and during a 26.2-mile marathon. Anthropometric, physiological, and performance measurements were assessed before the marathon so the associations between diet and marathon time could be included as part of a stepwise-regression model.

Results:

Mean marathon time was 266 ± 42 min. A premarathon 2-mile time trial explained 73% of the variability in marathon time (adjusted R 2 = .73, p < .001). Day-before + morning-of CHO (DBMC) was the only other significant predictor of marathon time, explaining an additional 4% of the variability in marathon time (adjusted R 2 = .77, p = .006). Other factors such as age, body-mass index, gender, day-before + morning-of energy, and in-race CHO were not significant independent predictors of marathon time.

Conclusions:

In this sample of primarily novice marathoners, DBMC intake was associated with faster marathon time, independent of other known predictors. These results suggest that novice and recreational marathoners should consider consuming a moderate to high amount of CHO in the 24–36 hr before a marathon.

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Eric K. O’Neal, Brett A. Davis, Lauren K. Thigpen, Christina R. Caufield, Anthony D. Horton and Joyce R. McIntosh

The purpose of this study was to determine how accurately runners estimate their sweat losses. Male (n = 19) and female (n = 20) runners (41 ± 10 yr, VO2max 57 ± 9 ml · kg−1 · min−1) from the southeastern U.S. completed an ~1-hr run during late summer on a challenging outdoor road course (wet bulb globe temperature 24.1 ± 1.5 °C). Runs began at ~6:45 a.m. or p.m. Before and after running, participants filled race-aid-station paper cups with a volume of fluid they felt would be equivalent to their sweat losses. Total sweat losses and losses by percent body weight differed (p < .01) between men (1,797 ± 449 ml, 2.3% ± 0.6%) and women (1,155 ± 258 ml, 1.9% ± 0.4%). Postrun estimates (738 ± 470 ml) were lower (p < .001) than sweat losses (1,468 ± 484 ml), equaling underestimations of 50% ± 23%, with no differences in estimation accuracy by percentage between genders. Runners who reported measuring changes in pre- and postrun weight to assess sweat losses within the previous month (n = 9, –54% ± 18%) were no more accurate (p = .55) than runners who had not (n = 30, –48% ± 24%). These results suggest that inadequate fluid intake during runs or between runs may stem from underestimations of sweat losses and that runners who do assess sweat-loss changes may be making sweat-loss calculation errors or do not accurately translate changes in body weight to physical volumes of water.