Predicting Recreational Runners' Marathon Performance Time During Their Training Preparation.

ABSTRACT: Esteve-Lanao, J, Del Rosso, S, Larumbe-Zabala, E, Cardona, C, Alcocer-Gamboa, A, and Boullosa, DA. Predicting marathon performance time throughout the training preparation in recreational runners. J Strength Cond Res 35(11): 3218-3224, 2021-The objective of this study was to predict marathon performance at different time points along the season using different speeds derived from ventilatory thresholds and running economy (RE). Sixteen recreational runners (8 women and 8 men) completed a 16-week marathon training macrocycle. Aerobic threshold (AeT), anaerobic threshold (AnT), and maximal oxygen uptake were assessed at the beginning of the season, whereas speeds eliciting training zones at AeT and AnT, and RE were evaluated at 5-time points during the season (M1-M5). Analyses of variance and hierarchical regression analyses were conducted. Training improved AeT and AnT speeds at M2 vs. M1 (p = 0.001) and remained significantly higher at M3, M4, and M5 (p = 0.001). There was a significant effect of time (p = 0.003) for RE, being higher at M4 and M5 compared with M1 and M3. Significant correlations were found between marathon performance and speeds at AeT and AnT at every time point (r = 0.81-0.94; p < 0.05). Speed at AnT represented the main influence (65.9 and 71.41%) in the final time prediction at M1 and M2, whereas speed at AeT took its place toward the end of the macrocycle (76.0, 80.4, and 85.0% for M3, M4, and M5, respectively). In conclusion, assessment of speeds at AeT and AnT permits for reasonable performance prediction during the training preparation, therefore avoiding maximal testing while monitoring 2 fundamental training speeds. Future research should verify if these findings are applicable to runners of different levels and other periodization models.

Muscle Activation in Middle-Distance Athletes with Compression Stockings.

The aim of this study was to evaluate changes in electromyographic activity with the use of gradual compression stockings (GCSs) on middle-distance endurance athletes' performance, based on surface electromyography measurement techniques. Sixteen well-trained athletes were recruited (mean ± SD: age 33.4 ± 6.3 years, VO2max 63.7 ± 6.3 mL·kg-1·min-1, maximal aerobic speed 19.7 ± 1.5 km·h). The athletes were divided into two groups and were assigned in a randomized order to their respective groups according to their experience with the use of GCSs. Initially, a maximum oxygen consumption (VO2max) test was performed to standardize the athletes' running speeds for subsequent tests. Afterward, electromyographic activity, metabolic, and performance variables for each group were measured with surface electromyography. In addition, blood lactate concentration was measured, both with and without GCSs, during 10 min at 3% above VT2 (second ventilatory threshold), all of which were performed on the track. Next, surface electromyography activity was measured during a 1 km run at maximum speed. No significant changes were found in electromyography activity, metabolic and performance variables with GCSs use (p > 0.164) in any of the variables measured. Overall, there were no performance benefits when using compression garments against a control condition.

Intake of Animal Protein Blend Plus Carbohydrate Improves Body Composition With no Impact on Performance in Endurance Athletes.

The impact of animal protein blend supplements in endurance athletes is scarcely researched. The authors investigated the effect of ingesting an admixture providing orange juice and protein (PRO) from beef and whey versus carbohydrate alone on body composition and performance over a 10-week training period in male endurance athletes. Participants were randomly assigned to a protein (CHO + PRO, n = 15) or a nonprotein isoenergetic carbohydrate (CHO, n = 15) group. Twenty grams of supplement mixed with orange juice was ingested postworkout or before breakfast on nontraining days. Measurements were performed pre- and postintervention on body composition (by dual-energy X-ray absorptiometry), peak oxygen consumption (V˙O2peak), and maximal aerobic speed. Twenty-five participants (CHO + PRO, n = 12; CHO, n = 13) completed the study. Only the CHO + PRO group significantly (p < .05) reduced whole-body fat (mean ± SD) (-1.02 ± 0.6 kg), total trunk fat (-0.81 ± 0.9 kg), and increased total lower body lean mass (+0.52 ± 0.7 kg), showing close to statistically significant increases of whole-body lean mass (+0.57 ± 0.8 kg, p = .055). Both groups reduced (p < .05) visceral fat (CHO + PRO, -0.03 ± 0.1 kg; CHO, -0.03 ± 0.5 kg) and improved the speed at maximal aerobic speed (CHO + PRO, +0.56 ± 0.5 km/hr; CHO, +0.35 ± 0.5 km/hr). Although consuming animal protein blend mixed with orange juice over 10 weeks helped to reduce fat mass and to increase lean mass, no additional performance benefits in endurance runners were observed.

Effects of gradual-elastic compression stockings on running economy, kinematics, and performance in runners.

We investigated the effect of gradual-elastic compression stockings (GCSs) on running economy (RE), kinematics, and performance in endurance runners. Sixteen endurance trained athletes (age: 34.73 ± 6.27 years; VO2max: 62.83 ± 9.03 ml·kg(-1)·min(-1); 38 minutes in 10 km; 1 hour 24 minutes in half marathon) performed in random order 4 bouts of 6 minutes at a recent half-marathon pace on a treadmill to evaluate RE with or without GCSs. Subsequently, 12 athletes were divided into 2 equal groups matched by their VO2max, and they performed a time limit test (T(lim)) on a treadmill at 105% of a recent 10-km pace with or without GCSs for evaluation of physiological responses and running kinematics. There were no significant differences in the RE test in all of the variables analyzed for the conditions, but a moderate reproducibility for some physiological responses was detected in the condition with GCSs. In the T(lim), the group that wore GCSs reached a lower % of maximum heart rate (HRmax) compared with the control group (96.00 ± 2.94 vs. 99.83 ± 0.40) (p = 0.01). Kinematics did not differ between conditions during the T(lim) (p > 0.05). There were improvement trends for time to fatigue (337 vs. 387 seconds; d = 0.32) and a lower VO2peak (≈53 vs. 62 ml·kg(-1)·min(-1); d = 1.19) that were detected with GCSs during the T(lim). These results indicate that GCSs reduce the % of HRmax reached during a test at competition pace. The lower reproducibility of the condition with GCSs perhaps suggests that athletes may possibly need an accommodation period for systematically experiencing the benefits of this garment, but this hypothesis should be further investigated.

Longitudinal Analysis of Marathon Runners' Psychological State and Its Relationship With Running Speed at Ventilatory Thresholds.

Psychological variables such as motivation, self-efficacy, and anxiety have been widely studied in marathon runners, usually within the framework of Bandura's theory of self-efficacy. It is also assumed a link between self-perceived fitness and physiological performance parameters such as speed at ventilatory thresholds and running economy. The purpose of this paper is to describe longitudinal trends of self-perceptions and examine their link to physiological performance parameters over time. Sixteen healthy recreational marathoners (8 males and 8 females), aged M = 37.6 (SD = 3.9) who were about to participate in a major marathon agreed to participate. After 3 months of regular training and competition in shorter distances, all participants trained during a 16-week macrocycle under the supervision of the same coaching staff. At 4-week intervals, the participants responded five times the Podium questionnaire, measuring self-perceived psychological state relative to the upcoming race, and performed five exercise performance parameters tests. Linear mixed-effects models were used to analyze the trends and associations. In general, Podium questionnaire scores were within the standard range, with the lowest values at the beginning and the highest values closer to race day. Although only perceived fitness (p < 0.001, Cohen's f 2 = 1.19) and somatic anxiety (p < 0.001, f 2 = 0.32) showed large effect sizes for the whole longitudinal period, other partial increases were found between time points. All physiological performance parameters presented significant improvements over time (Aerobic Threshold speed, p < 0.001, f 2 = 1.04; Anaerobic Threshold speed, p < 0.001, f 2 = 0.498; Running Economy in VO2, p < 0.001, f 2 = 0.349; Running Economy in energy, p = 0.024, f 2 = 0.197). The analysis of changes between consecutive time points revealed that improving perceived physical condition predicted improving self-efficacy (p < 0.001, f 2 = 1.33), and improvements in motivation were predicted by improvements in either self-efficacy (p < 0.001, f 2 = 0.36) or perceived physical condition (p = 0.003, f 2 = 0.17). Improvements in perceived fitness, self-efficacy and motivation were associated with small effect-size improvements (decreases) in anxiety. None of the physiological performance parameters was shown to predict changes in psychological variables, although their general trends over time correlated. The results have practical implications for sport psychologists and running coaches, supporting the need for integrated working.

Factors Affecting Training and Physical Performance in Recreational Endurance Runners.

Endurance running has become an immensely popular sporting activity, with millions of recreational runners around the world. Despite the great popularity of endurance running as a recreational activity during leisure time, there is no consensus on the best practice for recreational runners to effectively train to reach their individual objectives and improve physical performance in a healthy manner. Moreover, there are lots of anecdotal data without scientific support, while most scientific evidence on endurance running was developed from studies observing both recreational and professional athletes of different levels. Further, the transference of all this information to only recreational runners is difficult due to differences in the genetic predisposition for endurance running, the time available for training, and physical, psychological, and physiological characteristics. Therefore, the aim of this review is to present a selection of scientific evidence regarding endurance running to provide training guidelines to be used by recreational runners and their coaches. The review will focus on some key aspects of the training process, such as periodization, training methods and monitoring, performance prediction, running technique, and prevention and management of injuries associated with endurance running.

Metabolic conditioning among soccer players.

To reduce the risk of overuse injuries, yet obtain optimal fitness development among soccer players, research comparing different training strategies is required. This study compared conventional group conditioning (GRP) to individualized training (IT) during the preseason among female college soccer players. Both groups participated in soccer practices; however, players were randomly assigned to supplemental conditioning differentiated by the use of player-specific heart rate training in the IT group. Changes in maximal oxygen consumption, anaerobic threshold, and rate of recovery were analyzed before and after 12 weeks of conditioning. Data analysis identified significantly (p < 0.05) greater improvements in the IT group in all 3 variables, despite considerably less training volume. Based on these data, it is apparent that catering training to the fitness level of each individual player can have a positive impact on training adaptations.

Changes in Triathletes' Performance and Body Composition During a Specific Training Period for a Half-Ironman Race.

The number of recreational athletes completing a Half-Ironman triathlon has increased exponentially in recent years. However, there is a lack of research on how to train for this kind of an event. The purpose of this study was thus to analyse triathletes' changes in performance and body composition following a triathlon-specific training period. Fourteen male amateur triathletes completed a 7-week period of general training and a 13-week period of specific training for a Half-Ironman triathlon. Anthropometric measures and performance tests were carried out to assess the effects of the specific training program. Results showed that the pre-test value of VO2max for cycling was inversely correlated not only with the percentage of change in cycling performance, but also with the percentage change in several variables of running performance. In swimming, inverse correlations were observed between the time of the first 800 m test and the time percentage change for this test, but not with the percentage change in the performance of other segments of the race. Moreover, the somatotype component of endomorphy and the fat mass percentage of the first anthropometry were highly correlated with the percentage change in VO2max in the run segment. These results highlight the importance of providing individualised training, considering that the same training program had a different impact on recreational triathletes belonging to the same group. Amateur athletes with higher initial performance levels probably need a greater amount of training to achieve improved adaptation.

Running-specific, periodized strength training attenuates loss of stride length during intense endurance running.

The purpose of this study was to determine the effects of a running-specific, periodized strength training program (performed over the specific period [8 weeks] of a 16-week macrocycle) on endurance-trained runners' capacity to maintain stride length during running bouts at competitive speeds. Eighteen well-trained middle-distance runners completed the study (personal bests for 1500 and 5000 m of 3 minutes 57 seconds +/- 12 seconds and 15 minutes 24 seconds +/- 36 seconds). They were randomly assigned to each of the following groups (6 per group): periodized strength group, performing a periodized strength training program over the 8-week specific (intervention) period (2 sessions per week); nonperiodized strength group, performing the same strength training exercises as the periodized group over the specific period but with no week-to-week variations; and a control group, performing no strength training at all during the specific period. The percentage of loss in the stride length (cm)/speed (m.s) (SLS) ratio was measured by comparing the mean SLS during the first and third (last) group of the total repetitions, respectively, included in each of the interval training sessions performed at race speeds during the competition period that followed the specific period. Significant differences (p < 0.05) were found in mean percentage of SLS loss between the 3 study groups, with the periodized strength group showing no significant SLS change (0.36 +/- 0.95%) and the 2 other groups showing a moderate or high SLS loss (-1.22 +/- 1.5% and -3.05 +/- 1.2% for the nonperiodized strength and control groups, respectively). In conclusion, periodized, running-specific strength training minimizes the loss of stride length that typically occurs in endurance runners during fatiguing running bouts.

Nutrimetry: BMI assessment as a function of development. / Nutrimetría: evaluando el IMC en función del desarrollo.

BACKGROUND AND OBJECTIVE: Adequate nutritional assessment is required to fight malnutrition (undernutrition and overfeeding) in children and adolescents. For this, joint interpretation of certain indicators (body mass index [BMI], height, weight, etc.) is recommended. This is done clinically, but not epidemiologically. The aim of this paper is to present "nutrimetry", a simple method that crosses anthropometric information allowing for bivariate interpretation at both levels (clinical and epidemiological). MATERIALS AND METHODS: Data from 41,001 children and adolescents aged 0-19 years, taken from Mexico's National Health and Nutrition Survey 2012, were analyzed. Data crossed were BMI-for-age z-scores (BAZ) with height-for-age z-scores (HAZ) according to the World Health Organization (WHO) standards. Conditional prevalences were calculated in a 3×3 grid and were compared with expected values. RESULTS: This method identified subgroups in each BAZ category showing heterogeneity of the sample with regard to WHO standards for HAZ and nutritional status. According to the method, nutritional status patterns differed among Mexican states and age and sex groups. CONCLUSION: Nutrimetry is a helpful and accessible tool to be used in epidemiology. It allows for detecting unexpected distributions of conditional prevalences, its graphical representation facilitates communication of results by geographic areas, and enriched interpretation of BAZ helps guide intervention actions according to their codes.

Is Marathon Training Harder than the Ironman Training? An ECO-method Comparison.

Purpose: To compare the absolute and relative training load of the Marathon (42k) and the Ironman (IM) training in recreational trained athletes. Methods: Fifteen Marathoners and Fifteen Triathletes participated in the study. Their performance level was the same relative to the sex's absolute winner at the race. No differences were presented neither in age, nor in body weight, height, BMI, running VO2max max, or endurance training experience (p > 0.05). They all trained systematically for their respective event (IM or 42k). Daily training load was recorded in a training log, and the last 16 weeks were compared. Before this, gas exchange and lactate metabolic tests were conducted in order to set individual training zones. The Objective Load Scale (ECOs) training load quantification method was applied. Differences between IM and 42k athletes' outcomes were assessed using Student's test and significance level was set at p < 0.05. Results: As expected, Competition Time was significantly different (IM 11 h 45 min ± 1 h 54 min vs. 42k 3 h 6 min ± 28 min, p < 0.001). Similarly, Training Weekly Avg Time (IM 12.9 h ± 2.6 vs. 42k 5.2 ± 0.9), and Average Weekly ECOs (IM 834 ± 171 vs. 42k 526 ± 118) were significantly higher in IM (p < 0.001). However, the Ratio between Training Load and Training Time was superior for 42k runners when comparing ECOs (IM 65.8 ± 11.8 vs. 42k 99.3 ± 6.8) (p < 0.001). Finally, all ratios between training time or load vs. Competition Time were superior for 42k (p < 0.001) (Training Time/Race Time: IM 1.1 ± 0.3 vs. 42k 1.7 ± 0.5), (ECOs Training Load/Race Time: IM 1.2 ± 0.3 vs. 42k 2.9 ± 1.0). Conclusions: In spite of IM athletes' superior training time and total or weekly training load, when comparing the ratios between training load and training time, and training time or training load vs. competition time, the preparation of a 42k showed to be harder.

Metabolic, cardiorespiratory, and neuromuscular fitness performance in children with cerebral palsy: A comparison with healthy youth.

The aim of this study was to assess metabolic, cardiorespiratory, and neuromuscular fitness parameters in children with spastic cerebral palsy (CP) and to compare these findings with typically developing children. 40 children with CP (21 males, 19 females; mean age, 11.0±3.3 yr; range, 6.5-17.1 yr; Gross Motor Function Classification System levels 1 or 2) and 40 healthy, age- and sex-matched children completed a test battery that consisted of 8 tests and 28 measures that assessed cardio-respiratory fitness, energy expenditure, anaerobic endurance, muscle strength, agility, stability and flexibility. Children with CP had significantly lower performance (P<0.05) on most cardiorespiratory and metabolic tests than those of healthy children, Differences in neuromuscular measures of muscular strength, speed, agility, anaerobic endurance, and flexibility between groups were most apparent. Grouped differences in cardiorespiratory variables revealed a 25% difference in performance, whereas grouped differences in metabolic and neuromuscular measures were 43% and 60%, respectively. The physical fitness of contemporary children with CP is significantly less than healthy, age-matched children. Significant differences in neuromuscular measures between groups can aid in the identification of specific fitness abilities in need of improvement in this population.

How do endurance runners actually train? Relationship with competition performance.

PURPOSE: To quantify the relationship between total training load and running performance during the most important competitions of the season (national cross-country championships, 4.175- and 10.130-km races). METHODS: Eight well-trained, subelite endurance runners (age (mean+/-SD): 23+/-2 yr; VO2max: 70.0+/-7.3 mL.kg.min) performed a maximal cardiorespiratory exercise test before the training period to determine ventilatory threshold (VT) and respiratory compensation threshold (RCT). Heart rate was continuously recorded using telemetry during each training session over a 6-month macrocycle, designed to achieve peak performance during the aforementioned cross-country races, lasting from late August to the time that these races were held, that is, mid-February. This allowed us to quantify the total cumulative time spent in three intensity zones calculated as zone 1 (low intensity, lower than the VT); zone 2 (moderate intensity, between VT and RCT); and zone 3 (high intensity, above the RCT). RESULTS: Total training time in zone 1 (4581+/-979 min) was significantly higher (P<0.001) than that accumulated in zones 2 (1354+/-583 min) and 3 (487+/-154 min). Total time in zone 2 was significantly higher than time in zone 3 (P<0.05). A correlation coefficient of r=-0.79 (P=0.06) and r=-0.97 (P=0.008) was found between the total training time spent in zone 1 and performance time during the short and long cross-country races, respectively. CONCLUSIONS: Our findings suggest that total training time spent at low intensities might be associated with improved performance during highly intense endurance events, especially if the event duration is approximately 35 min. Interventional studies (i.e., improving or reducing training time in zone 1) are needed to corroborate our findings and to elucidate the physiological mechanisms behind them.

Specific Intensity for Peaking: Is Race Pace the Best Option?

BACKGROUND: The peaking period for endurance competition is characterized for a relative increase of the intensity of training, after a longer period of training relatively dominated by lower intensity and higher volume. OBJECTIVES: The present study was designed to compare physiological and 10 km performance effects of high intensity training (HIT) versus race pace interval training (RP) during peaking for competition in well-trained runners. PATIENTS AND METHODS: 13 athletes took part in the study, they were divided into two groups: HIT and RP. HIT performed short intervals at ~105% of the maximal aerobic velocity (MAV), while RP trained longer intervals at a speed of ~90% of the MAV (a speed approximating 10 km race pace). After 12 weeks of baseline training, the athletes trained for 6 weeks under one of the two peaking regimes. Subjects performed 10 km prior to and after the intervention period. The total load of training was matched between groups during the treatment phase. Subjects completed a graded treadmill running test until volitional exhaustion prior to each 10 km race. MAV was determined as the minimal velocity eliciting maximal oxygen consumption (VO2max). RESULTS: Both groups significantly improved their 10 km time (35 minutes 29 seconds ± 1 minutes 41 seconds vs 34 minutes 53 seconds ± 1 minutes 55 seconds, P < 0.01 for HIT; 35 minutes 27 seconds ± 1 minutes 40 seconds vs 34 minutes 53 seconds ± 1 minutes 18 seconds P < 0.01 for RP). VO2max increased after HIT (69 ± 3.6 vs 71.5 ± 4.2 ml.Kg(-1).min(-1), P < 0.05); while it didn't for RP (68.4 ± 6 vs 69.8 ± 3 ml.Kg(-1).min(-1), p>0.05). In contrast, running economy decreased significantly after HIT (210 ± 6 ml.Kg(-1).km(-1) vs 218 ± 9, P < 0.05). CONCLUSIONS: A 6 week period of training at either 105% of MAV or 90% of MAV yielded similar performance gains in a 10km race performed at ~90% MAV. Therefore, the physiological impact of HIT training seems to be positive for VO2max but negative for running economy.

Training-intensity distribution during an ironman season: relationship with competition performance.

PURPOSE: To describe training loads during an Ironman training program based on intensity zones and observe Training-performance relationships. METHODS: Nine triathletes completed a program with the same periodization model aiming at participation in the same Ironman event. Before and during the study, subjects performed ramp-protocol tests, running, and cycling to determine aerobic (AeT) and anaerobic thresholds (AnT) through gas-exchange analysis. For swimming, subjects performed a graded lactate test to determine AeT and AnT. Training was subsequently controlled by heart rate (HR) during each training session over 18 wk. Training and the competition were both quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity; AnT). RESULTS: Most of training time was spent in zone 1 (68% ± 14%), whereas the Ironman competition was primarily performed in zone 2 (59% ± 22%). Significant inverse correlations were found between both total training time and training time in zone 1 vs performance time in competition (r = -.69 and -.92, respectively). In contrast, there was a moderate positive correlation between total training time in zone 2 and performance time in competition (r = .53) and a strong positive correlation between percentage of total training time in zone 2 and performance time in competition (r = .94). CONCLUSIONS: While athletes perform with HR mainly in zone 2, better performances are associated with more training time spent in zone 1. A high amount of cycling training in zone 2 may contribute to poorer overall performance.

Does polarized training improve performance in recreational runners?

PURPOSE: To quantify the impact of training-intensity distribution on 10K performance in recreational athletes. METHODS: 30 endurance runners were randomly assigned to a training program emphasizing low-intensity, sub-ventilatory-threshold (VT), polarized endurance-training distribution (PET) or a moderately high-intensity (between-thresholds) endurance-training program (BThET). Before the study, the subjects performed a maximal exercise test to determine VT and respiratory-compensation threshold (RCT), which allowed training to be controlled based on heart rate during each training session over the 10-wk intervention period. Subjects performed a 10-km race on the same course before and after the intervention period. Training was quantified based on the cumulative time spent in 3 intensity zones: zone 1 (low intensity, RCT). The contribution of total training time in each zone was controlled to have more low-intensity training in PET (±77/3/20), whereas for BThET the distribution was higher in zone 2 and lower in zone 1 (±46/35/19). RESULTS: Both groups significantly improved their 10K time (39min18s ± 4min54s vs 37min19s ± 4min42s, P < .0001 for PET; 39min24s ± 3min54s vs 38min0s ± 4min24s, P < .001 for BThET). Improvements were 5.0% vs 3.6%, ~41 s difference at post-training-intervention. This difference was not significant. However, a subset analysis comparing the 12 runners who actually performed the most PET (n = 6) and BThET (n = 16) distributions showed greater improvement in PET by 1.29 standardized Cohen effect-size units (90% CI 0.31-2.27, P = .038). CONCLUSIONS: Polarized training can stimulate greater training effects than between-thresholds training in recreational runners.

Running world cross-country championships: a unique model for pacing.

UNLABELLED: The aim of this study was to describe the pacing distribution during 6 editions of the world cross-country championships. METHODS: Data from the 768 male runners participating from 2007 to 2013 were considered for this study. Blocks of 10 participants according to final position (eg, 1st to 10th, 11 to 20th, etc) were considered. RESULTS: Taking data from all editions together, the effect of years was found to be significant (F(5,266) = 3078.69, P < .001, ω² = 0.31), as well as the effect of blocks of runners by final position (F(4,266) = 957.62, P < .001, ω² = 0.08). A significant general decrease in speed by lap was also found (F(5,1330) = 2344.02, P < .001, ω² = 0.29). Post hoc analyses were conducted for every edition where several pacing patterns were found. All correlations between the lap times and the total time were significant. However, each lap might show different predicting capacity over the individual outcome. DISCUSSION: Top athletes seem to display different strategies, which allow them to sustain an optimal speed and/or kick as needed during the critical moments and succeed. After the first group (block) of runners, subsequent blocks always displayed a positive pacing pattern (fast to slow speed). Consequently, a much more stable pacing pattern should be considered to maximize final position. CONCLUSIONS: Top-10 finishers in the world cross-country championships tend to display a more even pace than the rest of the finishers, whose general behavior shows a positive (fast-to-slow) pattern.