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VO2 max and training indices as determinants of competitive running performance

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The importance of the maximal oxygen uptake (VO2 max) for competitive running performance is established. Although of clear importance, the quantitative association between the volume and intensity of training, and running performance has not been established. The purpose of this investigation was to quantify the relative importance of VO2 max, training volume (miles/week) and intensity for running performance at distances ranging from 1.0 to 26.2 miles. Seventy‐eight well‐trained runners of widely varying ability were studied during uphill treadmill running to determine VO2 max. They provided training records to determine training volume and intensity, and participated in races of 1.0 (n = 31), 2.0 (n = 55), 3.0 (n = 28), 6.0 (n= 17), 10.0 (n = 20) and 26.2 (n = 25) miles. The relationship of VO2 max and training volume and intensity to performance was determined using multiple regression. Performance (running time) was highly correlated with VO2 max (r= ‐0.91, ‐0.92, ‐0.94, ‐0.96, ‐0.95 and ‐0.96 for 1.0, 2.0, 3.0, 6.0, 10.0 and 26.2 miles, respectively). The addition of training measures improved the multiple correlations in some (1.0, 2.0, 3.0 and 6.0 miles) but not all (10.0 and 26.2 miles) events. However, even when addition of one or both training indices improved the multiple correlation, the net reduction in the standard error of estimate was small. The results imply that the volume and intensity of training, per se, are relatively minor determinants of cross‐sectional differences in competitive running performance.
... The variables included in such prediction equations might be roughly classified into three distinct groups: anthropometry, physiology and training (Foster, 1983;Tanda, 2011). Body mass index (BMI; Doherty et al., 2020), body fat percentage (BF; Salinero et al., 2017), skinfold thickness (Arrese and Ostáriz, 2006), and somatotype (Bale et al., 1985) have been used among anthropometric-related variables, where high scores in BMI or fat indices were associated with a slower race speed. ...
... Therefore, the aim of the present study was to (a) profile anthropometric, physiological, and training characteristics of men recreational marathon runners by performance level and (b) develop and validate a prediction equation of race speed in the "Athens Authentic Marathon." It was hypothesized that runners with a faster running speed would present better scores in the characteristics associated with performance (e.g., VO 2 max, body composition, and training) than their slower counterparts (Foster, 1983;Tanda, 2011). It was also assumed that these characteristics could be used to predict race speed in the particular marathon race. ...
... The best predictor of race speed was VO 2 max, explaining a large portion of variance (∼40%). This finding was in agreement with previous research including VO 2 max in prediction equations of race speed or time (Foster, 1983). Moreover, it was in line with a comparative study of recreational marathon runners of different performance levels showing that the faster runners had higher VO 2 max than the slower ones (Gordon et al., 2017). ...
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Aim: The aim of the present study was to examine (a) the role of training and physiological characteristics on the performance of recreational marathon runners, and (b) to develop a prediction equation of men’s race time in the 'Athens Authentic Marathon'. Methods: Recreational male marathon runners (n=130, age 44.1±8.6 years) - who finished the 'Athens Authentic Marathon' 2017 - performed a series of anthropometry and physical fitness tests including body mass index (BMI), body fat percentage (BF), maximal oxygen uptake (VO2max), anaerobic power, squat and countermovement jump. The variation of these characteristics was examined by quintiles (i.e., five groups consisting of 26 participants in each) of the race speed. An experimental group (EXP, n=65) was used to develop a prediction equation of the race time, which was verified in a control group (CON, n=65). Results: In the overall sample, a one-way ANOVA showed a main effect of quintiles on race speed on weekly training days and distance, age, body weight, BMI, BF and VO2max (p≤0.003, η2≥0.121), where the faster groups outscored the slower groups. Running speed during the race correlated moderately with age (r=-0.36, p<0.001), and largely with the number of weekly training days (r=0.52, p<0.001) and weekly running distance (r=0.58, p<0.001), but not with the number of previously finished marathons (r=0.08, p=0.369). With regards to physiological characteristics, running speed correlated largely with body mass (r=-0.52, p<0.001), BMI (r=-0.60, p<0.001), BF (r=-0.65, p<0.001), VO2max (r=0.67, p<0.001), moderately with isometric muscle strength (r=0.42, p<0.001), and small with anaerobic muscle power (r=0.20, p=0.021). In EXP, race speed could be predicted (R2=0.61, standard error of the estimate=1.19) using the formula ‘8.804+0.111×VO2max +0.029×weekly training distance in km-0.218×BMI’. Applying this equation in CON, no bias was observed (difference between observed and predicted value 0.12±1.09 km/h, 95% confidence intervals -0.15, 0.40, p=0.122). Conclusion: These findings highlighted the role of aerobic capacity, training and body mass status for the performance of recreational male runners in a marathon race. The findings would be of great practical importance for coaches and trainers to predict the average marathon race time in a specific group of runners.
... Analysis: Table 2 presents 12 studies from 1983 to 2015 [12,13,[22][23][24][25][26][28][29][30][31][32]. The most notable are the physiological variables such as VO2max [12,23,25,32] and vVO2max, [13,22,28,31] and RE measurements [12,29,30,33]. ...
... Analysis: Table 2 presents 12 studies from 1983 to 2015 [12,13,[22][23][24][25][26][28][29][30][31][32]. The most notable are the physiological variables such as VO2max [12,23,25,32] and vVO2max, [13,22,28,31] and RE measurements [12,29,30,33]. Table 2. Multiple regression models associated with performance in 5000 m races. ...
... Analysis: Table 3 presents 13 studies from 1983 to 2014 [13,23,[26][27][28][33][34][35][36][37][38][39][40][41][42][43][44][45][46]. Physiological variables such as VO2max [23,[32][33][34]38] and vVO2max continue to be prominent [27,28,33]. Of the 13 studies, seven have a prediction equation [7,23,26,28,34,37,44]. ...
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Physiological variables such as maximal oxygen uptake (VO2max), velocity at maximal oxygen uptake (vVO2max), running economy (RE) and changes in lactate levels are considered the main factors determining performance in long-distance races. The aim of this review was to present the mathematical models available in the literature to estimate performance in the 5000 m, 10,000 m, half-marathon and marathon events. Eighty-eight articles were identified, selections were made based on the inclusion criteria and the full text of the articles were obtained. The articles were reviewed and categorized according to demographic, anthropometric, exercise physiology and field test variables were also included by athletic specialty. A total of 58 studies were included, from 1983 to the present, distributed in the following categories: 12 in the 5000 m, 13 in the 10,000 m, 12 in the half-marathon and 21 in the marathon. A total of 136 independent variables associated with performance in long-distance races were considered, 43.4% of which pertained to variables derived from the evaluation of aerobic metabolism, 26.5% to variables associated with training load and 20.6% to anthropometric variables, body composition and somatotype components. The most closely associated variables in the prediction models for the half and full marathon specialties were the variables obtained from the laboratory tests (VO2max, vVO2max), training variables (training pace, training load) and anthropometric variables (fat mass, skinfolds). A large gap exists in predicting time in long-distance races, based on field tests. Physiological effort assessments are almost exclusive to shorter specialties (5000 m and 10,000 m). The predictor variables of the half-marathon are mainly anthropometric, but with moderate coefficients of determination. The variables of note in the marathon category are fundamentally those associated with training and those derived from physiological evaluation and anthropometric parameters.
... Some of the more notable measures that have been examined are VO 2max , time-toexhaustion (TTE) tests, and time-trial (TT) tests. VO 2max is highly correlated with race performance [17] but has limitations because it does not account for additional physiological differences [18,19]. The reliability of TTE tests has been shown to be lower than TT tests [20]. ...
... In addition to TT performance, the studies all measured change in VO 2max and once again there was no response difference between men and women. The similarity in responses between changes in TT performance and VO 2max is an important finding because it demonstrates consistency between two outcome measures that have been shown to be highly correlated [17]. ...
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Background Interval training has become an essential component of endurance training programs because it can facilitate a substantial improvement in endurance sport performance. Two forms of interval training that are commonly used to improve endurance sport performance are high-intensity interval training (HIIT) and sprint interval training (SIT). Despite extensive research, there is no consensus concerning the optimal method to manipulate the interval training programming variables to maximize endurance performance for differing individuals.Objective The objective of this manuscript was to perform a systematic review and meta-analysis of interval training studies to determine the influence that individual characteristics and training variables have on time-trial (TT) performance.Data SourcesSPORTDiscus and Medline with Full Text were explored to conduct a systematic literature search.Study SelectionThe following criteria were used to select studies appropriate for the review: 1. the studies were prospective in nature; 2. included individuals between the ages of 18 and 65 years; 3. included an interval training (HIIT or SIT) program at least 2 weeks in duration; 4. included a TT test that required participants to complete a set distance; 5. and programmed HIIT by power or velocity.ResultsTwenty-nine studies met the inclusion criteria for the quantitative analysis with a total of 67 separate groups. The participants included males (n = 400) and females (n = 91) with a mean group age of 25 (range 19–45) years and mean \(V{\text{O}}_{{2{\text{max}}}}\) of 52 (range 32–70) mL·kg−1·min−1. The training status of the participants comprised of inactive (n = 75), active (n = 146) and trained (n = 258) individuals. Training status played a significant role in improvements in TT performance with trained individuals only seeing improvements of approximately 2% whereas individuals of lower training status demonstrated improvements as high as 6%. The change in TT performance with HIIT depended on the duration but not the intensity of the interval work-bout. There was a dose–response relationship with the number of HIIT sessions, training weeks and total work with changes in TT performance. However, the dose–response was not present with SIT.Conclusion Optimization of interval training programs to produce TT performance improvements should be done according to training status. Our analysis suggests that increasing interval training dose beyond minimal requirements may not augment the training response. In addition, optimal dosing differs between high intensity and sprint interval programs.
... Maximal aerobic exercise capacity is an important predictor of health, as reflected by the associations between maximal oxygen consumption (VO 2 max), an established indicator of cardiorespiratory fitness, and life expectancy [2,3]. A number of factors can improve cardiorespiratory fitness [4], including regular exercise training. However, some studies have proposed that an individual's maximal exercise capacity could be limited as a result of premature birth. ...
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Background A negative impact of premature birth on health in adulthood is well established. However, it is not clear whether healthy adults who were born prematurely but have similar physical activity levels compared to adults born at term have a reduced maximal aerobic exercise capacity (maximum oxygen consumption [VO2max]). Objective We aimed to determine the effect of premature birth on aerobic exercise capacity and lung function in otherwise healthy, physically active individuals. Methods A broad literature search was conducted in the PubMed database. Search terms included ‘preterm/premature birth’ and ‘aerobic exercise capacity’. Maximal oxygen consumption (mL/kg/min) was the main variable required for inclusion, and amongst those investigations forced expiratory volume in 1 s (FEV1, % predicted) was evaluated as a secondary parameter. For the systematic review, 29 eligible articles were identified. Importantly, for the meta-analysis, only studies which reported similar activity levels between healthy controls and the preterm group/s were included, resulting in 11 articles for the VO2max analysis (total n = 688, n = 333 preterm and n = 355 controls) and six articles for the FEV1 analysis (total n = 296, n = 147 preterm and n = 149 controls). Data were analysed using Review Manager ( Review Manager. RevMan version 5.4 software. The Cochrane Collaboration; 2020.). Results The systematic review highlighted the broad biological impact of premature birth. While the current literature tends to suggest that there may be a negative impact of premature birth on both VO2max and FEV1, several studies did not control for the potential influence of differing physical activity levels between study groups, thus justifying a focused meta-analysis of selected studies. Our meta-analysis strongly suggests that prematurely born humans who are otherwise healthy do have a reduced VO2max (mean difference: − 4.40 [95% confidence interval − 6.02, − 2.78] mL/kg/min, p < 0.00001, test for overall effect: Z = 5.32) and FEV1 (mean difference − 9.22 [95% confidence interval − 13.54, − 4.89] % predicted, p < 0.0001, test for overall effect: Z = 4.18) independent of physical activity levels. Conclusions Whilst the current literature contains mixed findings on the effects of premature birth on VO2max and FEV1, our focused meta-analysis suggests that even when physical activity levels are similar, there is a clear reduction in VO2max and FEV1 in adults born prematurely. Therefore, future studies should carefully investigate the underlying determinants of the reduced VO2max and FEV1 in humans born preterm, and develop strategies to improve their maximal aerobic capacity and lung function beyond physical activity interventions.
... In general, carrying a higher body weight makes it more difficult to sustain maximal speed (Mori et al., 2016). The LBM was also found to be an essential attribute that affects oxygen consumption and the maximum running speed (Foster, 2015). The mean LBM was 59.24 ± 6.09 kg, which was expected to be the highest values achieved by cross-country athletes. ...
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In recent years, there has been an increasing interest in the morphological and physiological characteristics for many sporting codes. Morphological and physiological testing is an important tool for cross-country athletes and coaches and assists in the training intensity prescription, monitoring of training adaptation and profiling athletes for specific competitions. So far, however, there has been few reports on senior male cross-country athletes. The aim of this research was to determine the relationship between morphological and physiological characteristics of senior male cross-country athletes in Gauteng province, South Africa. Forty males (age: 20-35 years; height: 173.09 cm; weight: 63.05 kg) who competed in the Central Gauteng Senior Cross-Country Championships competition were invited to participate in this study. Parameters tested included stature, body weight, seven skinfolds, body fat percentage, lean body mass, somatotype and 10km time measured. The maximal oxygen consumption, running economy and two ventilatory thresholds (VT1 and VT2) were calculated using online assessments of each participant as explained in the methods of this study. Data were analysed using descriptive statistics (SPSS, v.21) and Pearson coefficient of correlation procedures. A significant difference was observed between athletes who trained for <45 minutes and those who trained for >45 minutes per day by an independent t-test. An independent t-test was used to determine significant differences between the two groups. The data were collected experimentally by using a self-administered questionnaire for the medical and sporting status of the runners. The results of this study indicated mean values of body weight (63.05 kg), body fat percentage (8.04 %), sum of seven skinfolds (34.12 mm), lean body mass (59.24 kg) and somatotype (i.e., endomorph, mesomorph, and ectomorph ratios) (1.80, 1.40. and 2.80) respectively. The mean values for maximum oxygen consumption (V̇ O2max) (63.50 mlO2 . kg˗1.min-1 ), running economy (at 12 km·hr -1 32.8 L/min, 14.5 km·hr -1 41.70 L/min, 16 km·hr -1 56 L/min, 19.2 km·hr -1 30.60 L/min), ventilatory threshold (2.95 L/min-1 ), maximum heart rate (191.00 bpm), respiratory exchange ratio (1.23) and average 10 km running speed (16.24 km·hr -1 ) were also determined. The VT1 and VT2 were calculated and at the intensities corresponding to the last point before a first non-linear increase in both VT1 and VT2. The senior male cross-country athletes showed higher values for O2 expressed relative to morphological and physiological factor. The above measurements were captured in Johannesburg at the following altitude (1753 m), barometric pressure (82.54 kPa), air density (0.98 kg/m2 at 20 ºC/ (293 k). These characteristics are generally associated with cross-country iii runners, suggesting that senior male cross-country athletes in Gauteng province, South Africa, are professional athletes. There were no significant V̇ O2max, RE and personal best 10 km time differences between participants who trained <45 minutes and those who trained >45 minutes per day during training sessions (p > 0.05). However, there were significant body weight (p = 0.028) and BF% (p = 0.030) differences between the two groups. It can thus suggest that the duration of the daily training session has a direct effect on some morphological characteristics of athletes, but no effect on others. The analysis showed that athletes of various endurance events statistically differ in morphological measures, especially in dimensions of BW and BF%. Further, highlight the importance of morphological and physiological factors in cross�country running. This research will serve as a basis for future studies and will provide information on senior male cross-country athletes, which can be referred to by coaches and sports scientists who train athletes during the competition preparation phase. KEY WORDS: anthropometry, V̇ O2max, running economy, ventilatory threshold
... In general, carrying a higher body weight makes it more difficult to sustain maximal speed (Mori et al., 2016). The LBM was also found to be an essential attribute that affects oxygen consumption and the maximum running speed (Foster, 2015). The mean LBM was 59.24 ± 6.09 kg, which was expected to be the highest values achieved by cross-country athletes. ...
Article
Full-text available
In recent years, there has been an increasing interest in the morphological and physiological characteristics for many sporting codes. Morphological and physiological testing is an important tool for cross-country athletes and coaches and assists in the training intensity prescription, monitoring of training adaptation and profiling athletes for specific competitions. So far, however, there has been few reports on senior male cross-country athletes. The aim of this research was to determine the relationship between morphological and physiological characteristics of senior male cross-country athletes in Gauteng province, South Africa. Forty males (age: 20-35 years; height: 173.09 cm; weight: 63.05 kg) who competed in the Central Gauteng Senior Cross-Country Championships competition were invited to participate in this study. Parameters tested included stature, body weight, seven skinfolds, body fat percentage, lean body mass, somatotype and 10km time measured. The maximal oxygen consumption, running economy and two ventilatory thresholds (VT1 and VT2) were calculated using online assessments of each participant as explained in the methods of this study. Data were analysed using descriptive statistics (SPSS, v.21) and Pearson coefficient of correlation procedures. A significant difference was observed between athletes who trained for <45 minutes and those who trained for >45 minutes per day by an independent t-test. An independent t-test was used to determine significant differences between the two groups. The data were collected experimentally by using a self-administered questionnaire for the medical and sporting status of the runners. The results of this study indicated mean values of body weight (63.05 kg), body fat percentage (8.04 %), sum of seven skinfolds (34.12 mm), lean body mass (59.24 kg) and somatotype (i.e., endomorph, mesomorph, and ectomorph ratios) (1.80, 1.40. and 2.80) respectively. The mean values for maximum oxygen consumption (V̇ O2max) (63.50 mlO2 . kg˗1.min-1 ), running economy (at 12 km·hr -1 32.8 L/min, 14.5 km·hr -1 41.70 L/min, 16 km·hr -1 56 L/min, 19.2 km·hr -1 30.60 L/min), ventilatory threshold (2.95 L/min-1 ), maximum heart rate (191.00 bpm), respiratory exchange ratio (1.23) and average 10 km running speed (16.24 km·hr -1 ) were also determined. The VT1 and VT2 were calculated and at the intensities corresponding to the last point before a first non-linear increase in both VT1 and VT2. The senior male cross-country athletes showed higher values for O2 expressed relative to morphological and physiological factor. The above measurements were captured in Johannesburg at the following altitude (1753 m), barometric pressure (82.54 kPa), air density (0.98 kg/m2 at 20 ºC/ (293 k). These characteristics are generally associated with cross-country iii runners, suggesting that senior male cross-country athletes in Gauteng province, South Africa, are professional athletes. There were no significant V̇ O2max, RE and personal best 10 km time differences between participants who trained <45 minutes and those who trained >45 minutes per day during training sessions (p > 0.05). However, there were significant body weight (p = 0.028) and BF% (p = 0.030) differences between the two groups. It can thus suggest that the duration of the daily training session has a direct effect on some morphological characteristics of athletes, but no effect on others. The analysis showed that athletes of various endurance events statistically differ in morphological measures, especially in dimensions of BW and BF%. Further, highlight the importance of morphological and physiological factors in cross�country running. This research will serve as a basis for future studies and will provide information on senior male cross-country athletes, which can be referred to by coaches and sports scientists who train athletes during the competition preparation phase. KEY WORDS: anthropometry, V̇ O2max, running economy, ventilatory threshold.
... Pacing, described as the work or effort distribution over a race, has been extensively studied over the last 40 years in endurance sports [1]. There is consensus that pacing is a prerequisite to achieve successful endurance performance, and that depends on several internal (i.e., muscle fatigue [2], and psychophysiological variables [3]) and external (i.e., tactics [4], and ambient conditions, such as wind resistance [5]) factors [6]. ...
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The aims of the current study were to compare the pacing patterns of all-time 800 m, 1500 m and mile running world records (WRs) and to determine whether differences exist between sexes, and if 800 m and 1500 m WRs were broken during championship or meet races. Overall and lap times for men and women's 800 m, 1500 m, and mile WRs from World Athletics were collected when available and subsequently compared. A fast initial 200 m segment and a decrease in speed throughout was found during 800 m WRs. Accordingly, the first 200 m and 400 m were faster than the last 200 m and 400 m, respectively (p < 0.001, 0.77 ≤ ES ≤ 1.86). The first 400 m and 409 m for 1500 m and mile WRs, respectively, were faster than the second lap (p < 0.001, 0.74 ≤ ES ≤ 1.46). The third 400 m lap was slower than the last 300 m lap and 400 m lap for 1500 m and mile WRs, respectively (p < 0.001, 0.48 ≤ ES ≤ 1.09). No relevant sex-based differences in pacing strategy were found in any event. However, the first 409 m lap was faster than the last 400 m lap for men but not for women during mile WRs. Women achieved a greater % of WRs than men during championships (80% vs. 45.83% in the 800 m, and 63.63% vs. 31.58% in the 1500 m, respectively). In conclusion, positive, reverse J-shaped and U-shaped pacing profiles were used to break 800 m, men's mile and 1500 m, and women's mile WRs, respectively. WRs are more prone to be broken during championships by women than men.
... Maximal aerobic power (VO 2max ) is an established determinant of endurance performance (Blagrove et al., 2018;Foster, 1983;JDR Bassett & Howley, 1997;Joyner, 1991;Pollock et al., 1980). Training methods to improve VO 2max are characterized in two modes: continuous training (CT) and interval training (IT) methods (Laursen & Jenkins, 2002; KS Seiler & Kjerland, 2006). ...
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Success in endurance running is primarily determined by maximal aerobic power (VO2max), fractional utilization, and running economy (RE). Within the literature, two training modalities have been identified to improve VO2max; continuous training (CT) and interval-training (IT). The efficacy of IT to improve VO2max in well-trained runners remains equivocal, as does whether a dose-response relationship exists between the IT training load performed and changes in VO2max. A keyword search was performed in five electronic databases. Seven studies met the inclusion criteria for this systematic review. The training impulse (TRIMP) was calculated to analyse relationships between training load and changes in VO2max, by calculating the time accumulated in certain intensity domains throughout a training intervention. Non-significant (P>0.05) improvements in VO2max were reported in six studies, with only one study reporting a significant (P<0.05) improvement following the IT interventions. A relationship between the training session impulse of the interval-training performed (IT STRIMP) and VO2max improvements were observed. The efficacy of IT to improve VO2max in well-trained runners remains equivocal, nevertheless, the novel method of training-load analysis demonstrates a relationship between the IT STRIMP and VO2max improvements. This provides practical application for the periodization of IT within the training regime of well-trained distance runners.
Thesis
Cette thèse avait pour objectif de présenter les différents travaux réalisés sur la prédiction de la performance en course à pied afin d’aider les athlètes et les entraîneurs à optimiser leur processus d’entraînement. Ces études, en collaboration avec la Fédération Française d’Athlétisme (FFA), se sont appuyées sur le système d’information fédéral répertoriant notamment l’ensemble des résultats athlétiques, les bilans ou encore le nombre de licenciés. La première étude avait pour objectif d’exposer l’évolution des performances françaises des courses de demi-fond et de fond chez les femmes. Les études suivantes étaient principalement destinées à tester la validité, la justesse, et la précision de différentes méthodes de prédiction (i.e., capacité à prédire les performances) sur des performances individuelles réelles d’athlètes de différents niveaux, hommes et/ou femmes. Les résultats se sont avérés valides et précis, quelle que soit la méthode de prédiction utilisée. Enfin, la dernière recherche était destinée à la prédiction du potentiel de performance. Cette étude a notamment mis en avant une analyse du taux d'amélioration des performances en demi-fond et en fond précédant la réalisation de records personnels chez les hommes et chez les femmes. Un index de progression à visée pratique, a également été proposé, afin d’évaluer l’évolution des performances et permettre une éventuelle détection et orientation des athlètes au fort potentiel.
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Marathon running which is also known as long distance running event which is well designed and well planned in a periodical way. Its training protocols and sessions are on point where a marathon runner can work on his physical capabilities, enhance it and maintain over the period where the health and fitness of a marathon runner should be focused to complete the race on a greater note in terms of winning the long-distance running event. Training for the same should work on the aerobic endurance capacities and physiological changes for the betterment of the runners.
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Muscle biopsy samples were obtained from the gastrocnemius of 26 well-trained runners of widely varying ability. Portions of the sample were analyzed for succinate dehydrogenase (SDH) activity and for muscle fiber composition. $\dot V$ O2 max was determined during uphill treadmill running. Mean values for muscle SDH activity (14.6 U/g), fiber composition (55% slow twitch) and $\dot V$ O2 max (60.9 ml/kg×min−1) were lower than reported previously for groups of elite and sub-elite runners. The physiological data were consistent with the performance ability of the sample [5∶12, 11∶20 and 36∶40 (min∶s) for 1, 2 and 6 miles, respectively]. Within the sample, performance was most strongly related to $\dot V$ O2 max (r=−0.84, −0.87 and −0.88 for 1, 2, and 6 miles). There was little relationship between muscle SDH activity and either performance (r=−0.11, −0.14, −0.20 for 1, 2, and 6 miles) or $\dot V$ O2 max (r=0.23). The relationship between muscle fiber composition and performance was only modestly strong (r=−0.52, −0.54, −0.55 for 1, 2, and 6 miles). The results indicate that the primary determinant of cross-sectional differences in running performance is $\dot V$ O2 max. Skeletal muscle metabolism apparently contributes little to these cross-sectional differences and may be of much greater importance to variations in performance within an individual.
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This study was undertaken to determine the response of $\dot V$ O2 max and of running performance (805 and 3218 m) to the onset of training in untrained individuals and to an increase in the volume and intensity of training in well trained individuals. In series A, $\dot V$ O2 max and performances of 12 previously untrained individuals were determined before and after 4 and 8 weeks of training. In series B, performances, $\dot V$ O2 max and $\dot V$ O2 submax of 15 previously well trained runners were determined before and after 4 and 8 weeks of controlled training. In series A, $\dot V$ O2 max increased during the first 4 weeks of training but failed to increase further even in the presence of an increased training load (80 total km for the first 4 weeks, 130 total km for the second 4 weeks). Running performances improved throughout the training period. In series B, neither $\dot V$ O2 max nor $\dot V$ O2 submax changed but running performance improved throughout the experimental period. The results indicated that not all of the improvement in running performance subsequent to training is attributable to changes in $\dot V$ O2 max. Further the results indicate that changes in running economy are not a likely explanation for performance improvement among previously well trained runners. It is suggested that physiological adaptations not integrated in the test of $\dot V$ O2 max, or improvement in pacing contribute to training induced improvements in running performance.
Article
Muscle biopsies were obtained from the gastrocnemius of 14 elite distance runners, 18 middle distance runners, and 19 untrained men. The middle distance runners were all highly trained, but had significantly slower performance times than the elite runners at distances greater than 3 miles. Fiber composition and mean cross sectional areas were determined from muscle sections incubated for histochemical activity. A portion of the specimen was used to determine succinate dehydrogenase (SDH), lactate dehydrogenase (LDH) and phosphorylase activities. All subjects were tested for maximal oxygen uptake on a treadmill. As previously demonstrated by others, the elite runners' muscles were characterized by a high percentage (79%) of slow twitch (ST) fibers. On the average, the cross sectional area of their ST fibers was found to be 22% larger than the FT fibers (P<0.05). SDH activity of whole muscle homogenates from elite and middle distance runners was 3.4 and 2.8 fold greater, respectively, than that measured in the untrained men. Since the LDH and phosphorylase activities were similar for the runners and untrained men, it appears that training for distance running has little influence on the enzymes of glycogenolysis.
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The author presents this book as a supplement to his Psychometric methods (see 10: 6010). This new text presupposes no previous knowledge of statistics and does not include the emphasis on measurement nor psychophysics which was contained in the previous one. There is also no description of factor analysis, for which the reader is referred to the earlier volume. Within the 14 chapters the author presents the newer work of Fisher and others, such as methods of statistical inference and analysis of variance. Two new chapters, on testing hypotheses, and on predictions and errors of prediction, have been added and include such concepts as the null hypothesis, chisquare distribution, and the use of attributes in statistical prediction. The statistical illustrations are taken from modern psychological research. Exercises are presented after each chapter. Six tables in an appendix and an author and subject index are given. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Article
The present study confirms earlier observations that the musculature of elite distance runners is characterized by a high predominance of ST fibers. Although the percent ST fibers effectively discriminates between good and elite distance runners, fiber composition alone is a poor predictor of distance running success within the group of elite runners. Muscle enzyme measurements suggest that the 11 to 20 miles (17.7 to 32.2 km) of daily training performed by the elite runners produced a significantly greater increase in muscle SDH activity than was observed in the good distance runners, who were running 7 to 11 miles (11.3 to 17.7 km) per day, Although such endurance training enhances the oxidative capacity of the muscle, it apparently has little influence on the enzymes of glycogenolysis.
The aerobic performance of thirteen male ultramarathon and nine female marathon runners were studied in the laboratory and their results were related to their times in events ranging in distance from 5 km to 84.64 km. The mean maximal aerobic power output (VO2 max) of the men was 72.5 ml/kg·min compared with 58.2 ml/kg·min (p<0.001) in the women but the O2 cost (VO2) for a given speed or distance of running was the same in both sexes. The 5 km time of the male athletes was closely related to their VO2 max (r=−0.85) during uphill running but was independent of relative power output (%VO2 max). However, with increasing distance the association of VO2 max with male athletic performance diminished (but nevertheless remained significant even at 84.64 km), and the relationship between VO2 max and time increased. Thus, using multiple regression analysis of the form: $$\begin{gathered} 42.2 km (marathon) time (h) = 7.445 - 0.0338 \dot V{\text{O}}_{{\text{2 max}}} ({\text{ml/kg }} \cdot {\text{ min}}) \hfill \\ - 0.0303\% \dot V{\text{O}}_{{\text{2 max}}} (r = 0.993) \hfill \\ \end{gathered} $$ and $$\begin{gathered} 84.64 {\text{km (London}} - {\text{Brighton) time (h) = 16}}{\text{.998 }} - {\text{ 0}}{\text{.0735 }}\dot V{\text{O}}_{{\text{2 max}}} \hfill \\ ({\text{ml/kg }} \cdot \min ) - 0.0844\% \dot V{\text{O}}_{{\text{2 max}}} (r = 0.996) \hfill \\ \end{gathered} $$ approximately 98% of the total variance of performance times could be accounted for in the marathon and ultramarathon events. This suggests that other factors such as footwear, clothing, and running technique (Costill, 1972) play a relatively minor role in this group of male distance runners. In the female athletes the intermediate times were not available and they did not compete beyond 42.2 km (marathon) distance but for this event a similar association though less in magnitude was found with VO2 max (r=−0.43) and %VO2 max (= −0.49). The male athletes were able to sustain 82% VO2 max (range 80–87%) in 42.2 km and 67% VO2 max (range 53–76%) in 84.64 km event. The comparable figure for the girls in the marathon was 79% VO2 max (ranges 68–86%). Our data suggests that success at the marathon and ultramarathon distances is crucially and (possibly) solely dependent on the development and utilisation of a large VO2 max.
Maximal oxygen uptake (max VO2) in leg and arm work, succinate dehydrogenase activity (SDH) and percentage of slow twitch fibers (%ST fibers) in M. vastus lateralis (VL), M. gastrocnemius c.l. (GL) and M. deltoideus (D) were studied in 89 athletes practising 11 different sport events. It was found that maximal oxygen uptake correlated positively with %ST fibers and SDH activity in M. VL. The SDH activity and %ST fibers in M. VL correlated also with one another. The results suggest that oxidative capacity of the muscles is not the limiting factor for maximal oxygen uptake. The role of the oxidative capacity of the muscles might be important during submaximal work of long duration and when a relatively small muscle mass is activated (long-distance running). MaxVO2 might be the most important determinant of performance when large muscle mass is activated during maximal work of a duration from several minutes up to 1 h (cross-country skiing).