Aerobic Cost in Elite Female Adolescent Swimmers
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1 194 Training Testing Aerobic Cost in Elite Female Adolescent Swimmers Authors V. Unnithan 1, J. Holohan, B. Fernhall 3, J. Wylegala 4, T. Rowland 5, D. R. Pendergast 6 Affiliations Affiliation addresses are listed at the end of the article Key words swimming economy elite female athletes Abstract Maximal performance in swimming depends on metabolic power and the economy of swimming. Thus, the energy cost of swimming (economy = V O /V, C s ) and maximal aerobic power ( V O max ) in elite young female swimmers (n = 10, age: 15.3 ± 1.5 years) and their relationships to race times ( m) and national ranking were examined. V O increased exponentially with velocity (V), ( V O = ( 0.58 V) V ) to a maximal V O of.71 ± 0.50 L min (46.7 ± 8. ml kg min ) at a free swimming velocity of 1.37 ± 0.07 m s. Cs was constant up to 1. m s (1.5 ml m ), however was significantly higher at 1.36 m s (7.3 ml m ). Peak [La] was 5.34 ±.6 mm. Cs expressed as a percentage of Cs at maximal swimming velocity was significantly correlated with race times and ranking across a number of distances. The data for these elite females demonstrate that the energy cost of swimming is a good predictor of performance across a range of distances. However, as swimming performance is determined by a combination of factors, these findings warrant further examination. accepted after revision August 8, 008 Bibliography DOI /s Published online: February 6, 009 Int J Sports Med 009; 30: Georg Thieme Verlag KG Stuttgart New York ISSN Correspondence Prof. V. Unnithan Department of Sport Liverpool Hope University Hope Park Liverpool United Kingdom Tel.: /91 /0 45 Fax: / 91 / unnithv@hope.ac.uk Introduction Maximal performance in swimming depends on metabolic power and the economy of the swimmer [6]. There are few studies of metabolic power or economy in young elite female swimmers. Data on the relationship between peak V O and swimming have been equivocal. Ogita et al. [16] demonstrated a positive correlation between V O max and swimming performance over the m freestyle races. Weiss et al. [5], in elite adult female swimmers, found that aerobic capacity played an important role in swimming technique at high stroke rates and velocities. However, Costill et al. [6] suggested that a high peak V O does not correlate with improved swimming performance. A complex inter-play exists between peak V O and swimming economy in high caliber swimmers [3]. High level swimming performance can be achieved with either low economy and high peak V O or high economy and lower peak V O. Furthermore, evidence exists to suggest that the submaximal energy cost of swimming (C s ) is dependent, in part, on underwater torque which in turn has been shown to increase with age [15, 6, 7, 8]. Age group swimmers vary in size and shape, even in homogeneous elite groups of the same age grouping. The effect of body length, surface area, cross-sectional area, and weight have an effect on friction, form and wave drag and thus correcting C s for these variables may explain some of the differences among swimmers, even in an elite age group. Therefore, examining C s after correction for some of these variables would demonstrate their role in C s and performance. Determining the importance of maximal aerobic power and C s in the performance of young female elite swimmers, could ultimately help guide the coaching strategy in these swimmers. Consequently, the purpose of this study was to determine these variables in elite young female swimmers and examine their relationship to their race times and ranking nationally. It was hypothesized that maximal aerobic power and C s would act as significant predictors of race time and national ranking in elite, adolescent female swimmers.
2 Training Testing 195 Materials and Methods Study design At an introductory meeting, each subject s verbal assent was obtained privately and written informed consent was subsequently obtained from the subjects parent / guardian. Institutional Review Board approval from a University committee was obtained. Recent (within months) swimming records were collected and verified from the US Swimming web site. Participation required 3 visits to the laboratory. At the initial session (Visit 1), anthropometric data were obtained. Prior to the start of the swimming data collection (Visit ), all subjects participated in a 1 h habituation session at the annular pool to acclimate themselves to the equipment and environment used to obtain the energy cost data. At the third visit (Visit 3), all swimming energy cost data was collected. Participants The subjects for this study were recruited from local US Swimming community swimming clubs. Ten elite female swimmers (ages with a mean of 15.3 ± 1.5 years) participated, nine of the ten swimmers had at least one verified meet race time in the 50, 100, 00, 500 or m freestyle events that ranked them in the top 15 % in the country ( The USA Swimming National Motivational Times Table [4] ). The subjects had trained and competed on average for 6.4 ± 1.9 years, 6.9 ± 1.1 times per week for 10.9 ± 0.8 months per year. The subjects trained during the study, and for 46 of the last 5 weeks, for at least twelve hours per week. Maturity status was determined by Tanner s five stages of self-assessment for breast development [], which was previously validated [13]. Tanner stages for the group were: stage 3 (n = 3), stage 4 (n = 4) and stage 5 (n = 3). Anthropometric measurements for stature (cm) were obtained using a standard physician s scale (Health-O- Meter, Continental Scale Corporation, Bridgeview, Illinois). Body mass (kg) and body composition were obtained with the BodPod using the standard guidelines (Life Measurement, Inc., Concord, CA, USA). The stature and body mass of the subjects were ± 6 cm (mean ± SD) and 48.7 ± 3. kg in mass, with a body surface area [7] of 1.64 ± 0.07 m. The mean percentage body fat measurement for the subjects was 0.6 ± 3.3 %. Performance data Times and national rankings for 50 m to m swims are listed in Table 1. National rank was taken from a current comparison of the swimmers time in each event compared to USA Swimming s Quadrenium National Age Group Motivational Time Standards. Each subject s personal best time was obtained within months of the peak VO testing in the laboratory. All race times were from sanctioned USA swimming competitions. Electronic timing was used with a back-up system and water temperature was regulated following USA swimming requirements. The mean percentile for national rank ranged from 87.9 in the 100 m freestyle to 47 in the m freestyle. The mode was the 85th percentile and the median 80th percentile. Procedures Measurement of the energy cost of swimming ( V O ), including peak V O, was determined in an annular pool (58.6 m in circumference,.5 m wide and.5 m deep). [19, 8]. A motorized bridge circulated over the pool and was used to set the velocity of the swimmer using a turbine flow meter (PT-301, MEAD Inst. Corp., Riverdale, N.Y., USA) 1.5 m in front of the swimmer. The swimmer swam directly over a tape that was attached to a rod that was in turn attached to the bridge. The rod extended two feet below the water surface and the tape streamed back three feet. As the swimmers breathed from a mouth piece they could look directly down on the tape. Subjects swam with a nose clip, swimming goggles and mouthpiece that was attached to inspiratory and expiratory hoses that were brought around the swimmers head, fastened near the back of the neck and then brought straight up to a proboscis that was extended from the bridge and allowed adjustment of the breathing system. Swimming was stopped if the swimmer could not maintain a position over the tape so as not to put tension on the breathing system. C s and peak V O uptake were determined by a protocol that consisted of a three-minute warm-up at a set speed (0.9 m s ). The velocity of the platform was increased every three minutes by (0.1 m s ) for the first three stages, and then increased every two minutes until the swimmer was unable to keep pace with the platform. C s was determined from the initial (3 3 min) stages of the progressive velocity test, while maximal aerobic power was determined during the last minute [6, 19]. Oxygen uptake ( V O ) was determined by a standard open circuit method (STPD). Expired gases were collected in aerostatic balloons through a waterproof inspiratory and expiratory valve and hose system. Expired gas volume was determined by a calibrated dry gas meter (Harvard Apparatus, South Natick Mass., USA) and O and CO fractions by a previously calibrated mass spectrometer (MGA1100, Perkin-Elmer, Pomona, CA). Serial fingertip lactate measurements were taken at the completion of the maximal swimming test, at three-minute intervals for nine minutes post exercise [19] (Accusport Lactate Analyzer, Boehringer, Mannheim, Germany). Table 1 Individual and mean ( ± SD) values for competitive freestyle swimming times (t) and national ranking (nr) for distance from 50 m to m. Subject t50 (s) nr50 t100 (s) nr100 t00 (s) nr00 t500 (s) nr500 t1 000 (s) nr Mean SD
3 196 Training Testing Statistical analysis A test for normality was conducted on all data and this confirmed that all data was normally distributed, consequently, parametric statistics were used. Descriptive statistics (mean ± SD) were computed for each variable. A repeated measures ANOVA was performed for V O and C s as a function of swimming velocity. The V O data were fitted with the form V O, = a + bv + bv using the least squares technique (SigmaPlot 9, SSPS). This statistical model was selected as it is related to the relationship of drag and velocity, namely D = kv [3]. Pearson Product Moment correlation coefficients were calculated for the following variables (peak V O vs m race time, C s at 1. m s vs m race time and C s at 1.1 m s vs m race time) and with these same variables and national rank. Furthermore, V O expressed as a percentage of peak V O was correlated for swimming velocities from 0.9 to 1. m s for race distances from m. C s when expressed as a percentage of the C s at maximal speed was correlated with both national rank and race time. Post peak V O serial lactate concentrations were correlated with national rank and race time. V O adjusted for body surface area SA(m ) and C s SA(m ) were regressed to competitive times and national rankings at distances from m. Statistical significance was set at P < 0.05 and SigmaStat software was (Version 3.0, SSPS) used to analyze the data. Fig. 1 Mean ± SD for oxygen consumption swimming ( V O, L min ) the freestyle is plotted as a function of free swimming velocity (m s ). The data were fit with the expression kv and are shown in the upper left corner of the figure. * denotes statistically significant differences between the swimming velocities of 1. and 1.4 m s and 0.9, 1.0 and 1.1 m s respectively. Results Subjects The subjects for this study were elite female age group swimmers. The subjects had trained and competed for more than 6 years and for nine out of the 10 swimmers were performing in the top 15 % nationally of swimmers of similar ages for at least one event. The one swimmer that did not achieve this criteria was still ranked in the top 5 % nationally. The mean ranking was 87 % for the distances up to 00 m, after which it declined to 68 % and 47 % for 500 m and m, respectively. Peak V O Peak V O values were:.71 ± 0.50 L min, 46.7 ± 8. ml kg m in and 1.66 ± 0.9 L min m respectively and were achieved at a speed of 1.36 ± 0.07 m s. V O at 0.9, 1, 1.1, and 1. were 53 ± 10, 61 ± 1, 68 ± 16, and 80 ± 15 % respectively of V O peak. The mean blood [La] values for 3, 6 and 9 min post-exercise were 5.3 ±.3 mm, 4.9 ± 1.8 mm and 4. ± 1.5 mm, respectively. Energy cost of swimming The mean ± SD data for V O are shown in Fig. 1 and the C s in Fig.. V O, increased significantly and exponentially (kv ) as a function of velocity (m s ), while the C s was not significantly different among lower velocities (1.5 ml m ), at velocities above 1. m s C s significantly (p < 0.05) increased (7.3 ml m ). The averaged r values for the fitted model ranged from 0.9 to There was very little variability in the surface area (SA) of the subjects in this study (4 % coefficient of variability) and they averaged 1.64 ± 0.07 m. After correction for SA, the C s values for velocities below 1. m s were independent of velocity and were 1.4 ±.05 ml m m, and increased significantly to 14.3 ±.3 at 1. m s and 16.7 ± 3.00 at maximal (1.3 ± 0.1 m s ). Fig. The mean ± SD. data for the energy cost of swimming (Cs) as a function of velocity ( V O / v, ml m ) is plotted as a function of velocity. * denotes statistically significant differences between the swimming velocities of 1. and 1.4 m s and 0.9, 1.0 and 1.1 m s respectively. Correlation analyses The measured variables were correlated with the competitive performance data ( Tables,3, respectively). Absolute peak V O (L min ) was not significantly correlated to either competitive time or the swimmer s national rank ( Table ). Relative V O (ml kg mi n ) was significantly correlated with national ranking, but only at 00 m (r = 0.67, p <.05). All the remaining correlations between peak V O and time or national rank were not significant. The C s did not significantly correlate with either race time or national ranking ( m), ( Table ). C s at 1.1 m s when expressed as a percentage of the C s at maximal speed was significantly negatively correlated with national ranking at 50 ( 0.66, p = 0.038), 100 ( 0.83, p = 0.003), 00 ( 0.73, p = 0.017), 500 ( 0.811, p = 0.004) and m ( 0.678, p = 0.031) and positively for race time at 00 m (0.783, p = 0.007). None of
4 Training Testing 197 Table Correlation coefficients for Peak V O and C s as a function of competitive times from 50 to m and national ranking from m, n = m 100 m 00 m 500 m m V O Peak (L min ) vs time vs nat rank C s (ml m )at 1. m s vs time vs nat rank C s (ml m ) at 1.1 m s vs time vs nat. rank Table 3 Shared variances (R ) for V O, expressed as a percentage of Peak V O regressed as a function of race time for m and the national ranking (nr) for the m. Race time Distance Velocity (m s ) 50 m 100 m 00 m 500 m m National rank Distance Velocity (m s ) 50 m 100 m 00 m 500 m m the correlation coefficients between lactate concentration and performance were significant (data not shown). The V O at speeds of 0.9, 1.0, 1.1, and 1. m s, when expressed as a function of the peak aerobic power ( % ), were significantly associated (r = ) to race times and national rank at 00 and 500 m ( Table 3 ). Eighty-eight percent (p < 0.05) of the variability in national rank at m could be explained by the ratio of V O at 1.0 m s expressed as a percentage of peak V O. Previously, swimming data have been corrected for surface area () so the values for SA, V O SA(m ) and C s SA(m ) were regressed to competitive times and national rakings at distances from meters. There were no significant (p > 0.05) relationships between: SA vs. time and national ranking, V O SA (m ) vs. time and national ranking and, C s SA(m ) vs. time and national ranking. Discussion The hypothesis stated at the outset of the study was partially accepted. Peak V O was not a significant determinant of race time or performance, however, C s was. The specific findings from this study were: 1) Peak V O was not correlated with time or national ranking, ) V O increased exponentially as a function of velocity, while the energy cost per unit distance was constant up to a speed of 1.1 m s, after which speed it increased, 3) The energy cost of swimming (C s ), when expressed as a percentage of peak C s was significantly correlated with national rank and race time over a range of distances, 4) Submaximal V O expressed as a percentage of peak V O explained a proportion of the variability in race time and national rank at 00, 500 and m, 5) There were no significant correlations between peak lactate measures and competitive time or national rank for all race distances. As swimming performance is determined by a combination of factors [, 5, 6, 8, 10, 1, 15, 17, 18, 7] these findings warrant further examination. Aerobic power There was no significant correlation between peak V O and competitive time or national ranking in this study. This finding is similar to that reported in other swimming studies conducted with both children and adult subjects [6, 0, 17]. Pendergast et al. [17] demonstrated that the energy cost of swimming at a given velocity was directly related to the body surface area of the swimmer. When the peak V O data from the present study was expressed per unit body surface area, there were still no significant associations with time or national rank. It should be noted, however, that the lack of variability in age, race times, national ranking, and surface area, as well as V O may be the basis of the weak correlations seen in this study, but reflects the association in elite swimmers. Pendergast et al. [17] suggested that peak V O measures do not correlate with race time in swimming because of the great variability in the energy cost of swimming at a given velocity among different swimmers. This variability could be a product of other factors (i.e. anaerobic power, stroke mechanics or torque) and these parameters might obscure the importance of aerobic energy production during swimming [0]. Although peak V O was not the discriminating variable for elite swimming performance, it is undoubtedly a prerequisite for elite swimming success [3]. Maximal swimming velocity is a product of the
5 198 Training Testing energy cost of swimming at that velocity and the total metabolic power. Although total metabolic power is comprised of both maximal VO and anaerobic power, previous studies have shown that VO max, or peak, is important, even at competitive speeds, and correlates with swimming performance [4]. Furthermore, changes in VO max (peak) have been associated with an increase in performance after swimming training [3]. Peak V O (ml kg mi n ) correlated strongly with national ranking in the 00 meters freestyle. It has been shown that in races 00 m and longer both maximal V O and anaerobic power contribute to the overall energetics [3], in spite of the view that the 00 m race is considered to have a high anaerobic component [3, 17]. Despite the narrow chronological age-range of the subjects, the maturity status of these individuals needed to be estimated in order to rule out any confounding effect of maturation on peak V O. Little difference exists in the mass adjusted peak V O values between Tanner stages 3 and 5, as studied in this study [1]. Consequently, it is unlikely that maturity-related differences obscured any physiological-performance relationship seen in this cohort of swimmers. Energy cost of swimming The V O of free swimming increased exponentially as a function of velocity (kv ) in these elite female swimmers, as has previously been reported for male swimmers [3, 10, 17, 19, 0, 3, 7] and female swimmers [15, 7]. The energy cost of swimming in these elite female swimmers is below what has previously been reported for less competitive female swimmers [15, 17, 7]. It is possible to speculate that the elite status of the swimmers in the present study contributed to the lower energy cost of swimming compared to less highly trained female swimmers in previous studies. In this study, the coefficient of variation of C s was 9 % at 0.9 m /s and increased to 16 % at maximal velocity. It was also found that C s at 1.1 m s, when expressed as a percentage of C s at maximal velocity (C s / C s at v max), was significantly correlated with competitive times ( + ) and national rankings ( ) in freestyle events. To understand C s, it is important to consider the influence of underwater torque (T ), one of the main determinates of C s. Although T was not measured in the present study, C s has been shown to be dependent on underwater torque (T ) [15, 17, 7, 8]. Zamparo et al. [7] demonstrated that underwater torque was highly correlated with body surface area (r = 0.866). However, a more recent study has shown that the relationship between T and C s is velocity dependent, so T may not relate to Cs in elite swimmers as studied in the present study [6]. The data from this study fits with the data of Mollendorf et al. [14], who showed at moderate speeds that drag is primarily determined by pressure drag, which in turn is proportional to surface area, while at faster speeds wave drag plays a role. In addition, although the body s torque plays a role in the frontal surface area at lower velocities, at faster speeds, torque is off-set by the hydrostatic pressure generated by velocity which pushes the body to a more horizontal position in the water. This has also to be considered in light of the swimmers technique which can also minimize the frontal surface area of a swimmer. Previous studies in adults [7] have shown a relationship between the tendency for the legs to sink (torque) when the swimmer is passive and C s, and this was confirmed in subjects of similar age to the subjects in this study [8]. In a subsequent study, torque measured in young swimmers was shown to relate to C s at lower speeds (1.4 m sec, similar to the lower speeds from the present study), however not at faster speeds which would include the fastest speed in the present study [6]. In addition to torque, other factors such as strength and power may play a role. Studying a wide range of swimmers with varying technique, a relationship between power and sprint swimming was shown [8, 9, 1]. However, when swimmers of similar ages and abilities are compared this relationship is not significant [3]. One could conclude that as children grow and their strength and power increase there is also an increase in swimming velocity due to a combination of factors, however strength or power alone do not determine velocity, which is dominated by metabolic power and C s [5, 3]. Kjendlie et al. [11] has reported that children have lower C s than adults when expressed in absolute values, however when corrected for BSA or BM, but not body length, children have higher values. The data from the present study did not demonstrate a relationship between BSA, BM or body length and Cs or performance. The discrepancy between these two studies most likely has to do with the heterogeneous sample in the Kjendlie et al. [11] study and the homogeneous sample in the present study, and in the latter case the dominance of factors other than BSA or BM, namely swimming technique and metabolic power. The complex interaction of other variables, such as swimming technique maybe one of the reasons why trying to isolate the energy cost contribution to swimming can be challenging. The relationship noted between C s and free swimming velocity ( Figs. 1, ) appears to demonstrate a swimming velocity threshold, beyond which any further increase in swimming velocity requires a disproportionate increase in the energy cost. These findings suggest that even at distances that could be considered sprint or middle-distance events, the capacity to operate at a lower proportion of their peak aerobic capacity will confer success at the elite level. Summary The energy cost of swimming is an important determinant of success of elite young female swimmers, as it is for older swimmers []. However, successful swimming performance is determined by a combination of factors and these warrant further investigation in elite adolescent female swimmers. Affiliations 1 Department of Sport, Liverpool Hope University, Liverpool, United Kingdom Physical Education and Athletics, Cornell University, Ithaca, United States 3 Kinesiology and Community Health Department, University of Illinois, Champaign, United States 4 Rehabilitation Sciences and Physiology, University of Buffalo, Buffalo, United States 5 Department of Pediatrics, Baystate Medical Center, Springfield, United States 6 Center for Research and Education in Special Environments, University of Buffalo, Buffalo, United States References 1 Armstrong N, Williams J, Balding J, Gentle P, Kirby B. The peak oxygen uptake of British children with reference to age, sex and sexual maturity. Eur J Appl Physiol 1991 ; 6 : Bar-Or O, Unnithan V, Illescas C. Physiologic consideration in age-group swimming. Med Sci Aquatic Sports 1994 ; 39 : Capelli C, Pendergast DR, Termin B. Energetics of swimming at maximal speeds in humans. 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6 Training Testing Costill DL, Kovaleski J, Porter D, Fielding R, King D. Energy expenditure during front crawl swimming: predicting performance in middle distance events. Int J Sports Med 1985 ; 6 : Dubois EF. Basal metabolism in health and disease. Philadelphia: Lea and Febiger ; 1936 ; 93 8 Hawley JA, Williams MM, Vickovic PJ, Handcock BB. Muscle power predicts freestyle swimming performance. Br J Sports Med 199 ; 6 : Hawley JA, Williams MM. Relationship between upper body anaerobic power and freestyle swimming performance. Int J Sports Med 1991 ; 1 : Holmer I. Swimming Physiology. Ann Physiol Anthropol 199 ; 11 : Kjendlie PL, Ingjer F, Madsen O, Stallman RK, Stray-Gundersen J. D ifferences in the energy cost between children and adults during front crawl swimming. Eur J Appl Physiol 004 ; 91 : Klentrou PP, Montpetit RR. Physiologic and physical correlates of swimming performance. J Swimming Research 1991 ; 7 : Matsudo S, Matsudo V. Physicians assessment of sexual maturation in Brazilian boys and girls: concordance and reproducibility. Am J Hum Biol 1994 ; 6 : Mollendorf JC, Termin AC II, Oppenheim E, Pendergast DR. Effect of swim suit design on passive drag. Med Sci Sports Exerc 004 ; 36 : Montpetit R, Cazorla G, Lavoie JM. Energy expenditure during front crawl swimming: A comparison between males and females. In: Ungerechts BE, ed. Swimming Science V. Champaign. Illinois: Human Kinetics ; 1986 ; Ogita F, Taniguchi S. The comparison of peak oxygen uptake between swim-bench exercise and arm stroke. Eur J Appl Physiol 1995 ; 71 : Pendergast DR, Prampero PE di, Craig AB Jr, Wilson DR, Rennie DW. Quantitative analysis of the front crawl in men and women. J Appl Physiol Respirat Environ 1977 ; 43 : Poujake B, Hautier CA, Rouard A. Determinates of the energy cost of front crawl swimming in children. Eur J Appl Physiol 00 ; 87 : Prampero di PE, Pendergast DR, Wilson DW, Rennie DW. Blood lactic acid concentrations in high velocity swimming. In: Eriksson B, Furberg B, eds. Swimming Medicine IV. Baltimore: University Park Press ; 1978 ; Prampero di PE, Pendergast DP, Wilson DW, Rennie DW. Energetics of swimming in man. J Appl Physiol 1974 ; 37 : Sharp RL, Troup JP, Costill DL. Relationship between power and sprint freestyle swimming. Med Sci Sports Exerc 198 ; 14 : Tanner JM. Growth at Adolescence, nd edition. Oxford, UK: Blackwell ; 196 ; Termin B, Pendergast DR. Training using the stroke frequency-velocity relationship to combine biomechanical and metabolic paradigms. J Swimming Research 001 ; 14 : USA Swimming, 00. USA Swimming Rules and Regulation. USA Swimming ; 00 ; Weiss M, Klaus R, Niels B, Gerrit S, Weicker W. Relationship of blood lactate accumulation to stroke rate and distance per stroke in top female swimmers. In: Ungerechts BE, ed. Swimming Science V. Champaign. Illinois: Human Kinetics, Zamparo P, Capelli C, Cautero M, Nino A Di. Energy cost of front crawl swimming at supra-maximal speeds and underwater torque in young swimmers. Eur J Appl Physiol 000 ; 83 : Zamparo P, Capelli C, Termin B, Pendergast DR, Prampero PE di. Effect of the underwater torque on the energy cost, drag, and efficiency of front crawl swimming. Eur J Appl Physiol 1996 ; 73 : Zamparo P, Antonutto G, Capelli C, Francescato MP, Girardis M, Sangoi R, Soule RG, Pendergast DR. Effects of body size, body density, gender and growth on underwater torque. Scand J Med Sci Sports 1996 ; 6 : 73 80
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