Services on Demand
Print version ISSN 1517-8692
On-line version ISSN 1806-9940
Rev Bras Med Esporte vol.13 no.4 Niterói July/Aug. 2007
Juliana Melo AltimariI, II; Leandro Ricardo AltimariI, II; Andréia GulakI; Mara Patricia Traina Chacon-MikahilI
de Educação Física UNICAMP, Campinas, Brazil
IIGrupo de Estudo e Pesquisa em Metabolismo, Nutrição e Exercício UEL, Londrina, Brazil
The purpose of this study was to correlate the anaerobic threshold speeds (ATS) obtained from fixed lactate blood concentration (ATS 4 e ATS 3.5 mM), lactate minimum speed (LacminS) and the critical speed (CS) determined from different distances and number of coordinates: CS1 (50/100/200 m), CS2 (100/200/400 m), CS3 (50/100/200/400 m) and CS4 (200/400 m) with the performance in 400 meters (s) in adolescent swimmers. The sample was constituted by 15 swimmers (10 boys and five girls = 14.7 ± 0.7 years; 61.9 ± 8.5 kg; 171.1 ± 8.8 cm) of national level, with five to seven years of experience in competitive swimming. The correlation between the indexes and the performance in 400 m (s) was made using Pearson correlation coefficients. Significance was set at p < 0.01. The correlations between ATS 4 mM, ATS 3.5 mM, LacminS and the performance in 400 m (s) were: r = -0.63, r = -0.90 e r = 0.91, respectively (p < 0.01). The correlations between CS1 (50/100/200 m), CS2 (100/200/400 m), CS3 (50/100/200/400 m), CS4 (200/400 m) and the performance in 400 m (s) were: r = -0.62, r = -0.97, r = -0.98 e r = -0.94, respectively (p < 0.01). We suggest that ATS obtained from fixed lactate blood concentration of 3.5 mM, as well as LacminS and the CS obtained through larger distances seem to be the most fitted indexes of prediction of the aerobic performance in the studied adolescent swimmers. Additionally, the number of coordinates seems no influencing the relation between CS and aerobic performance.
Keywords: Anaerobic threshold. Lactate minimum. Critical speed. Aerobic performance. Adolescent swimmers.
It has been sometime that indices which are able to evaluate aerobic capacity and simultaneously make the suitable prescription of training intensity in athletes are searched for. Within this context, over the years, the oxygen maximal uptake (O2max) has been considered the gold standard parameter for evaluation of aerobic capacity in active and sedentary individuals as well as athletes, considering its important relationship with performance, especially in prolonged physical exertions under moderate intensity(1).
In swimming, especially in events which involve longer distances, the existence of significant correlation between O2max and performance has not been reported in the literature. Riberio et al.(2) have investigated a group of trained swimmers and did not find significant correlation between O2max and performance in 400 m crawl. These findings corroborate the results obtained in posterior studies which used the same distance(3-5). Similar results were reported in studies involving children, although different levels of correlation with aerobic performance have been observed(6-7). Moreover, reports in the literature show that the O2max, besides being influenced by the maximal cardiac debt(8), is also dependent on genetic factors(9-10).
Concerning the limitations imposed by the use of the O2max, the blood lactate response to exercise has been widely applied from the determination of the anaerobic threshold (LAn), once it is considered an extremely interesting referential for prescription of training intensity, control of the training effects, prediction of aerobic performance, as well as evaluation of the aerobic capacity of active and sedentary subjects and athletes(11).
Among the methodologies applied for determination of LAn, there are the ones which use protocols which directly measure the blood lactate concentration, making use of steady(12-15) or variable concentrations(16-17). It is highlighted though, that currently the minimum lactate methodology (Lacmin) initially proposed by Tegtbur et al.(17) and adapted for swimming, has been on the spotlight, especially due to its possibility to individually identify the maximum lactate steady state (MLSS)(18-19).
Considering that the obtained LAn from descriptive methods is invasive, requires blood samples collection, is pricy and has specific analyses equipment, it is important to search for more viable alternative methods to be applied. Within this context, the critical velocity (CV) which corresponds to the swimming velocity which theoretically can be kept for a longer period of time with no exhaustion, has been pointed out as one of the non-invasive indices of highest potential for evaluation of aerobic performance and LAn prediction of adult(3-5,20-21), children and adolescent swimmers(22-30), regardless the performance level(25).
It is worth mentioning that the combination of shorter distances in the CV prediction in young swimmers, determines significantly higher CV values when compared with combinations which involve longer distances(29), which could mainly contribute for differences in the relationship between CV and swimming performance and consequently in its prediction. Another relevant factor for CV is associated with the number of coordinates used in its determination, which represents the number of distances or workloads and their respective reached times(31). Some studies have suggested that the number of coordinates does not seem to change the CV values(32-33) and critical power (CP)(31) at least when longer distances or lighter loads which enable longer effort time are applied. However, these studies do not report influence of the number of coordinates used in CV determination in the relationship with physical performance.
Considering that few studies have tried to investigate the physiological indices which are able to determine performance in events with aerobic predominance in swimming, the aim of the present study was to correlate the LAn velocity obtained from the lactate steady concentrations (LAn 4 and LAn 3.5 mM), at Lacmin velocity and CV determined from different distances and number of coordinates with performance obtained in 400 meters (s) in swimming, in adolescent swimmers.
The sample consisted of fifteen swimmers (10 boys and 5 girls) from national level, with experience between 5 and 7 years in competitive swimming. Eleven subjects were specialists in free style (short and medium distances: n = 7, and long distance: n = 4), three in back stroke (short and medium distances) and one in breast stroke (short and medium distances).
All subjects were involved in a systematized training program of six weekly sessions and weekly mean volume between 36.000 and 40.000 m before the beginning of the data collection, with the purpose to improve the swimming main physical capacities. During collection the subjects were in the polishing phase, which is the final preparation process of a swimmer for the main competition season and consists of gradual reduction of the training volume-intensity ratio(34). The responsible ones for the subjects, after having been informed about the aims of the study and the procedures to which the athletes were going to be submitted, signed a free and clarified consent form. This study was approved by the Ethics Committee in Research from the Medical Sciences College of UNICAMP.
All tests were performed in the same semi-Olympic swimming pool (25 m) with water temperature ranging between 26 and 27°C, where the subjects, always using the free style, participated in seven or eight evaluations with 24 to 48 hour-interval between them. Warm-up was freely performed prior to each experimental session. In all tests the swimmers have received visual instructions from the researcher positioned at the side edge of the pool along the 25 m which have been set at each 5 m by cones in order to keep the pre-set velocities for the 25 m distance. The time of the evaluation sessions were the same during the entire experimental protocol. The volunteers were submitted to a pilot test for familiarization with the protocols as well as the used equipments.
Weight and height measurement
Body weight was measured in a digital platform scale, Urano®, model PS 180, with 0.1 kg precision, and height was determined in wooden stadiometers with 0.1 cm precision. All individuals were measured and weighted bare feet, only wearing a swimming suit. These measurements were performed with the purpose to characterize the subjects involved in the experiment.
Anaerobic threshold velocity
The anaerobic threshold velocity (VLAn) was determined through methodology similar to the one proposed by Mader et al.(12) using steady concentrations of 4 mM (VLAn 4 mM) and 3.5 mM (VLAn 3.5 mM) of blood lactate(15). Therefore, two 200 m submaximal swimming repetitions were performed, being the first at 85% and the second at 95% of maximal velocity for the 200 m distance, with interval of 20 minutes between repetitions at passive recovery. After the first, third and fifth minutes of performance of each sprint, 25 µL of artery blood from the earlobe were collected, with the aid of a heparinized and calibrated capillary for blood lactate dosing. Mean velocities corresponding to VLAn 4 mM and VLAn 3.5 mM were determined by linear interpolation between the highest lactate concentration of each sprint and its respective velocities.
Minimum lactate velocity
In order to determine the minimum lactate velocity (VLacmin) an adaptation of the protocol proposed by Tegtbur et al.(17) for runners was used, according to what was suggested by Ribeiro et al.(19) Initially, the individuals performed two maximal efforts of 50 m, with 1 minute-interval between them, for induction of considerable accumulation of lactate in the blood stream (lactic acidosis). After a period of 8 minutes of passive recovery, the volunteers initiated an incremental exercise protocol with 300 m stages, with initial velocity ranging from 1.10 to 1.25 m.s-1 and increments of 0.05 m.s-1 at every repetition until exhaustion(19). The initial velocity was chosen by each individual so that they could perform from four to six efforts. In the seventh minute after lactic acidosis induction and immediately after each repetition during the incremental phase, approximately 25 µl of artery blood from the earlobe were collected, through a heparinized and calibrated capillary, for blood lactate dosing. VLacmin was considered that in which the lowest blood lactate concentration during the progressive phase of the test was observed(19).
For the critical velocity determination (CV) maximal sprints were performed in the 50, 100, 200 and 400 m distances, being the respective times registered, with sprints exit from the pool, next to the edge. The sprints were randomly performed during the training sessions, with one try per session. CV was determined through the inclination (b) of the linear regression line between the distances and their respective times obtained at each repetition(3). In order to determine CV1, 50, 100 and 200 m distances were used; for CV2, 100, 200 and 400 m distances were used; for CV3, 50, 100, 200 and 400 m were used and, for CV4, 200 and 400 m distances were used. The athletes were evaluated in groups to motivate them to get their best performance. The time was registered with a hand digital time watch (SEIKO S140, JAPAN) with milliseconds precision.
Blood lactate analysis
Blood samples collected for lactate dosing were immediately placed in polyethylene microtubes with 1.0 ml Eppendorff lid, containing 50 µl of haemolysing solution (sodium fluoride, 1%) and then stored at 70ºC. Lactate analysis was performed by an electrochemical analyzer (YSL 2300 STAT Yellow Spring Co., USA).
Data statistical treatment was performed by StatisticaTM computer package for Windows 6.0® (STATSOFT INC., USA). After data normality was stated (Shapiro-Wilk test), descriptive statistics procedures were used and, later, simple regression analysis as well as the Pearson simple coefficient correlation for analysis of the correlations among VLAn 4 mM, VLAn 3.5 mM, VLAcmin, CV1, CV2, CV3, CV4 and performance in 400 m (s). Significance level adopted was of p < 0.01.
In table 1, the anthropometric characteristics of the studied subjects are found.
In table 2, the mean values for VLAn 4 mM, VLAn 3.5 mM, VLacmin, CV1, CV2, CV3 and CV4 are found.
In figure 1 the correlations (r) in VLAn 4 mM, VLAn 3.5 mM, VLacmin and performance in 400 m (s) (r = -0.63, r = -0.90 and r = -0.91, p < 0.01, respectively) are presented.
In figure 2 (r) correlations among CV1 (50/100/200 m), CV2 (100/200/400 m), CV3 (50/100/200/400 m), CV4 (200/400 m) and performance in 400 m (s) (r = -0.62, r = -0.97, r = -0.98 and r = -0.94, p < 0.01, respectively) are presented.
Since there is a need to analyze indices able to predict performance in swimming which allow a more suitable training prescription, the aim of the present investigation was to correlate the LAn velocity obtained from lactate steady concentrations (LAn 4 and LAn 3.5 mM), Lacmin velocity and CV determined from different distances and number of coordinates with performance in 400 meters (m) in adolescent swimmers. Thus, the findings of the present study show that: 1) the correlation values obtained among VLAn 3.5 mM, VLacmin, CV2, CV3 and CV4 and performance in 400 m (s) were highly significant; 2) VLAn 4 mM and CV1 presented low correlation values with performance in 400 m (s).
LAn has been considered an extremely interesting index for prediction of aerobic performance of athletes(11). Studies with adult swimmers conducted by Wakayoshi et al.(3-5) found significantly high correlations between LAn of 4 mM and performance in 400 m (r = 0.76, r = 0.90 and r = 0.93, respectively). Likewise, Bonifazi et al.(35) when investigating trained athletes of both genders have verified high levels of correlation between LAn of 4 mM and performance in 400 m (r = 0.86) and 800 m (r = 0.84) distances in female swimmers, and in 200 m (r = 0.72), 400 m (r = 0.87) and 1500 m (r = 0.91) distances in male swimmers. In addition to that, Guglielmo and Denadai(36) when investigating a group of trained swimmers and triathletes observed high and significant correlation between LAn of 4 mM and performance in 400 m (s) (r = -0.90). In this same study, when LAn was determined in an arm egometer, significant correlation with performance in 400 m (s) (r = -0.74) was also found.
As seen before, the present study shows different correlation values between VLAn 4 mM and VLAn 3.5 mM with performance in 400 m (s) (r = -0.63 and r = -0.90, respectively), showing that the lactate concentration used in LAn determination interferes in the relationship with swimming performance of the studied group. A study by Greco et al.(29) involving male and female swimmers aged 13-15 years found correlation values significantly high between LAn 4 mM and performance in 400 m (s) (r = -0.89 at r = -0.92, respectively). Still in this study, when younger swimmers were analyzed (10 and 12 years) the boys presented correlation values of r = -0.88 and the girls of r = -0.97, between LAn 4 mM and performance in 400 m (s).
In another study also involving swimmers of both genders aged 10-12 years, Denadai and Greco(23) found correlation values significantly high between LAn 4 mM and performance in 200 m (r = 0.93). Similarly, Freitas et al.(27) when studying a group of young swimmers of both genders (10-12 years) found correlation values significantly high between LAn 4 mM and performance in 200 m (r = 0.88) and 400 m (r = 0.94).
It is worth mentioning that VLAn determination in our study was composed of two submaximal repetitions of 200 m, according to what has been used in other studies with young swimmers(24-25,29,37), with intensities of 85% and 95% of maximal velocity for 200 m distance, which corresponded to approximately 120 and 135 seconds of duration, respectively. Moreover, one should consider that incremental and continuous protocols with stages lower than five minutes, should use lactate steady concentration of 3.5 mM in the determination of VLAn instead of 4 mM, once the use of the latter may overestimate LAn intensity, which limits the use potential of this method both for performance prediction and determination of aerobic capacity(15). These observations may partly explain the highest correlation values found between performance in 400 m (s) and LAn determined by the 3.5 mM blood lactate concentration.
Despite being widely used, LAn determination by results interpolation has been criticized since it does not consider the lactate kinetics individually(16), and its results do not suffer influence of previous availability of muscular glycogen(38). Therefore, some authors have suggested the application of the minimum lactate test (Lacmin) for individual evaluation of LAn, since besides not having its results affected by the previous depletion of glycogen, Lacmin test presents objectivity in its estimation(17).
Few studies have applied the Lacmin test in swimming for LAn determination, especially in adolescent populations. A study by Simões et al.(18) which had as aim to investigate the relationship between Lacmin and performance in 200 and 700 m distances in a group of trained swimmers, mean age of 16.0 ± 0.8 years, stated significant correlations between VLacmin and performance in 200 m and 700 m (r = 0.97 and r = 0.96, respectively). More recently, Santos et al.(39) when studying swimmers of both genders, mean age of 15.3 ± 1.1 years, did not find significant correlations between VLacmin and performance in 200 m and 400 m (r = 0.94 and r = 0.94, respectively). Our results corroborate these previous findings where the correlation between VLacmin and performance in 400 m (s) was significantly high (r = -0.91). As already mentioned, the highest correlation values found between VLacmin and performance in 400 m (s) compared with the ones observed for VLAn 4 mM and performance in 400 m (s) may be explained by the overestimation of the swimming velocities obtained from the LAn 4 mM method(15).
The CV which corresponds to the swimming velocity which theoretically may be kept for a long period of time with no exhaustion, has been shown as one of the non-invasive methods with the most potential for aerobic performance evaluation and LAn prediction of adult swimmers(3-5,20-21). A study by Wakayoshi et al.(3) with a group of well-trained adult swimmers using swimming-flume, has observed significantly high correlation between CV and performance in 400 m (r = 0.86). Still in swimming-flume, Wakayoshi et al.(4) found significant correlation value between CV and performance in 400 m (r = 0.82). In the same study, when the CV determined by the 50, 100, 200 and 400 meters distances were obtained in a pool (25 m), the correlation between CV and performance 400 m was of r = 0.99.
In addition to that, studies performed in a pool by Wakayoshi et al.(5) who used 200 and 400 meters distances, Kokubun(20) who used 100, 200 and 400 meters distances and Rodriguez et al.(21) who used 100 and 400 m distances in the determination of CV in trained adult swimmers, also found significant correlations between CV and performance in 400 m (r = 0.97, r = 0.95 and r = 0.94, respectively). Moreover, it is worth highlighting that Kokubun(20) in a study observed significant correlation between CV and performance in 800 m (r = 0.99).
Hill et al.(22) suggest the use of CV in evaluation of aerobic performance in young swimmers (8 to 18 years). These authors, after having analyzed the relationship between CV and performance in two groups of swimmers, found for the younger group (mean of 11 years) a significant correlation between CV and performance in 457 m (r = 0.92), and for the older group (mean of 15 years) found a correlation of r = 0.92 between CV and performance in 1509 m.
In our study significantly high correlations have been found between CV2, CV3 and CV4 and performance in 400 m (s) (r = -0.97, r = -0.98 and r = -0.94, respectively). However, when the relationship between CV1 and performance in 400 m (s) was analyzed, it was low (r = -0.62). These findings suggest that the combination of different distances in CV determination, especially involving shorter distances, and, consequently, with lower times of execution, influences in the relationship between CV and performance in young swimmers, which can limit the use of this method for performance prediction. Corroborating these findings, Greco et al.(29) demonstrated that the combination of shorter distances (25/50/100 m) in CV prediction, with exhaustion times between 14 and 121 seconds, determined significantly higher values of CV in young swimmers of both genders, aged between 10-15 years, than when the combinations involved longer distances (50/100/400 m and 100/200/400 m).
A study by Barsa et al.(26) in swimmers of both genders aged between 13-15 years found significantly high correlation values between CV determined by the 100, 200 distances and 400 m and performance in 100 m (r = 0.87), 200 m (r = 0.97) and 400 m (r = 1.00). In this same study, when the younger swimmers (10 and 12 years) were analyzed, the correlations values between CV and performance in 100, 200 and 400 m were of r = 0.91, r = 0.92 and r = 1.00, respectively. Likewise, a study by Greco et al.(29) involving male and female swimmers aged between 13-15 years, found significantly high correlation values between CV determined by 50, 100 and 200 m distances and performance in 400 m (s) (r = -0.95 at r = -0.88, respectively). Still in this study, when younger swimmers (10 and 12 years) were analyzed, the boys presented correlation values of r = -0.88 and the girls of r = -0.96, between CV and performance in 400 m (s).
Similarly, Denadai and Greco(23) when studying swimmers of both genders aged between 10-12 year found significantly high correlation values between CV determined by the same distances (50/100/200 m) and performance in 200 m (r = 0.98). In addition, Freitas et al.(27) when studying a group of young (10-12 years) swimmers of both genders found significantly high correlation values between CV determined by 100, 200 and 400 m distances and performance in 200 m (r = 0.95) and 400 m (r = 1.00). More recently, Bartholomeu-Neto et al.(40) when studying swimmers of both genders, mean age of 14.3 ± 1.2 years found significantly high correlation values between CV determined by the same distances (100/200/400 m) and performance in 200 m (r = 0.95) and 400 m (r = 0.98).
It can also be observed in our study that the number of coordinates used to determine CV does not seem to influence the relationship between CV and performance of young swimmers, at least when distances which allow longer time of effort until exhaustion are used. Such fact became evident from the correlation values observed between CV2, CV3 and CV4 determined by three, four, and two distances, respectively, and performance in 400 m (s), which were very close (r = -0.97, r = -0.98 and r = -0.94, respectively).
A study by Housh et al.(31) verified that the CP estimated from two coordinates, was significantly correlated (r = 0.96) with the values found when it was estimated by four coordinates, when the time difference between the two coordinates was higher than 2.7 minutes. However, when this difference was higher than 5 minutes, the correlation index was increased (r = 0.98). Therefore, the findings show the possibility of use of only two coordinates for swimming performance prediction, as long as they present longer effort time until exhaustion, which could contribute in the decrease in the number of sessions applied in the CV estimation. The results of this study are according to others conducted in cyclic modalities such as canoeing(32) and swimming(33).
It is important to highlight that the present study has a relative limitation concerning the generalization of results and should be analyzed only in the swimming context; besides being applied only in the reality of an adolescent swimming team of national level. Despite the reduced number of athletes used in the sample of the present study, it is verified that it is part of a restricted population, of difficult use in an investigation, since they are athletes of national level. In swimming, a club hardly ever has an athletic team of national level in the age group investigated. Additionally, coaches are usually resistant about making the athletes available for studies of this nature during the preparation phase for competitions. Stone et al.(41) highlight that the majority of the studies in Sports Science, differently from Exercise Science, involve multiple test sessions and a relatively low number of subjects. Nevertheless, in the authors' opinion, they are the most valuable for the training development and manipulation, due to the inherent analysis of a specific population as well as the lack of publications in this context. Therefore, the present study is very relevant, once it has been integrally and trustworthily conducted concerning the proposed experiments, as well as the control of the tests to which the subjects were submitted.
According to the findings of the present study, it is suggested that the choice of the lactate concentration for LAn determination interferes in the relationship with aerobic performance for the studied adolescents. Moreover, the combination of different distances in CV determination, especially concerning lower distances, influences the relationship between CV and aerobic performance. It is also suggested that, the number of coordinates does not seem to influence the relationship between CV and performance of young swimmers, at least when longer distances are applied in its determination. Therefore, it would be possible to use only two coordinates in the performance prediction. Finally, we may conclude that LAn determined from 3.5 mM, at VLacmin and CV obtained through longer distances seem to be the most suitable predictors of aerobic performance in the adolescent swimmers studied.
The authors thank Prof. Dr. Benedito S. Denadai from the Laboratory of Human Performance UNESP/Rio Claro-SP for making this analysis of blood lactate possible, as well as CNPq and FAPESP for the scholarships offered. To CPG-FEF/UNICAMP for the financial aid.
1. Basset Jr DR, Howley ET. Limiting factors for maximum oxygen uptake and determinants of endurance performance. Med Sci Sports Exerc. 2000;32:70-84. [ Links ]
2. Ribeiro JP, Sadavid E, Baena J, Monsalvet E, Barna A, De Rose, EH. Metabolic predictions of middle-distance swimming performance. Br J Sports Med. 1990; 24:196-200. [ Links ]
3. Wakayoshi K, Ilkuta K, Yoshida T, Udo M, Moritani T, Mutoh Y, et al. Determination and validity of critical velocity speed as an index of swimming performance in the competitive swimmer. Eur J Appl Physiol. 1992;64:153-7. [ Links ]
4. Wakayoshi K, Yoshida T, Udo M, Kasai T, Moritani T, Mutoh Y, et al. A simple method for determining critical speed as swimming fatigue threshold in competitive swimming. Int J Sports Med. 1992;13:367-71. [ Links ]
5. Wakayoshi K, Yoshida T, Udo M, Harada T, Moritani T, Mutoh Y, et al. Does critical swimming velocity represent exercise intensity at maximal lactate steady state? Eur J Appl Physiol. 1993;66:90-5. [ Links ]
6. Cyrino ES, Okano AH, Silva KES, Altimari LR, Dórea VR, Zucas SM, et al. Aptidão aeróbia e sua relação com os processos de crescimento e maturação. Revista de Educação Física da Uem. 2002;13:17-26. [ Links ]
7. Tomkinson GR, Leger LA, Olds TS, Cazorla G. Secular trends in the performance of children and adolescents (1980-2000): an analysis of 55 studies of the 20 m shuttle run test in 11 countries. Sports Med. 2003;33:285-300. [ Links ]
8. Saltin B, Strange S. Maximal oxygen uptake: old and new arguments for a cardiovascular limitation. Med Sci Sports Exerc. 1992;24:30-7. [ Links ]
9. Klissouras V. Heritability of adaptive variation. J Appl Physiol. 1971;31:338-44. [ Links ]
10. Klissouras V, Pirnay F, Petit JM. Adaptation to maximal effort: genetics and age. J Appl Physiol. 1973;35:288-93. [ Links ]
11. Svedahl K, Macintosh BR. Anaerobic threshold: the concept and methods of measurement. Can J Appl Physiol. 2003;28:299-323. [ Links ]
12. Mader A, Liesen H, Heck H, Philippi H, Schürch PM, Hollmann W. Zur Beurteilung der sportartspezifischen Ausdauerleistungsfähigkeit. Sportarzt Sportmed. 1976;27:80-8. [ Links ]
13. Kinderman W, Simon G, Keul J. The significance of the aerobic-anaerobic transitions for determination of workload intensities during endurance training. Eur J Appl Physiol. 1979;42:25-34. [ Links ]
14. Sjodin B, Jacobs I. Onset of blood lactate accumulation and marathon running performance. Int J Sports Med. 1981;2:23-6. [ Links ]
15. Heck H, Mader A, Hess G, Mücke S, Müller R, Hollmann W. Justification of the 4-mmol/l lactate threshold. Int J Sports Med. 1985;6:117-30. [ Links ]
16. Stegmann H, Kindermann W, Schinabel A. Lactate kinetics and individual anaerobic threshold. Int J Sports Med. 1981;2:160-5. [ Links ]
17. Tegtbur U, Busse MW, Braumann KM. Estimation of an individual equilibrium between lactate production and catabolism during exercise. Med Sci Sports Exerc. 1993;25:620-7. [ Links ]
18. Simões HG, Campbell CSG, Tango MLL, Mello F, Maziero DC, Baldissera V. Lactate minimum test in swimming: relationship to performance and maximal lactate steady state. Med Sci Sports Exerc. 2000;32(suppl 1):161. [ Links ]
19. Ribeiro L, Balakian P, Malachias P, Baldissera V. Stage length, spline function and lactate minimum swimming speed. J Sports Med Phys Fitness. 2003;43: 312-8. [ Links ]
20. Kokubun, E. Velocidade crítica como estimador do limiar anaeróbio na natação. Rev Paul Educ Fís. 1996;10:5-20. [ Links ]
21. Rodriguez FA, Moreno D, Keskinen KL. Validity of a two-distance simplified testing method for determining critical swimming velocity. In: Chatard JC, editor. Biomechanics and medicine in swimming IX. Saint-Etienne: University of Saint Etienne, 2003;385-90. [ Links ]
22. Hill DW, Steward RP, Lane CJ. Application of the critical power concept to young swimmers. Pediatr Exerc Sci. 1995;7:281-93. [ Links ]
23. Denadai BS, Greco CC. Correlação entre a velocidade crítica e a velocidade de limiar anaeróbio com as performances nos 50, 100, 200 metros, em nadadores de 10 a 12 anos. Revista da Associação dos Professores de Educação Física de Londrina. 1997;12:33-41. [ Links ]
24. Denadai BS, Greco CC, Donega MR. Comparação entre a velocidade de limiar anaeróbio e a velocidade crítica em nadadores com idade de 10 a 15 anos. Rev Paul Educ Fis. 1997;11:128-33. [ Links ]
25. Denadai BS, Greco CC, Teixeira M. Blood lactate response and critical speed in swimmers aged 10-12 years of different standards. J Sports Sci. 2000;18:779-84. [ Links ]
26. Barsa E, Bianco A, Greco CC. Velocidade crítica, capacidade de trabalho anaeróbio e performance em nadadores de 10 a 15 anos. Claretiano Revista do Centro Universitário. 2001;1:164-73. [ Links ]
27. Freitas ADE, Greco CC, Gomide EBGG, Souza W. Comportamento de variáveis técnicas e metabólicas e correlação com a performance em nadadores de 10 a 12 anos. Claretiano Revista do Centro Universitário. 2002;2:171-9. [ Links ]
28. Greco CC, Bianco A, Gomide E, Denadai BS. Validity of the critical speed to determine blood lactate response and aerobic performance in swimmers aged 10-15 years. Sci Sports. 2002;17:306-8. [ Links ]
29. Greco CC, Denadai BS, Peligrinotti IL, Freitas ADB, Gomide E. Anaerobic threshold and critical speed determined with different distances in swimmers aged 10 to 15 years: relationship with the performance and blood lactate response during endurance tests. Rev Bras Med Esporte. 2003;9:1-7. [ Links ]
30. Greco CC, Denadai BS. Critical speed and endurance capacity in young swimmers: effects of gender and age. Pediatr Exerc Sci. 2005;17:353-63. [ Links ]
31. Housh DJ, Housh TJ, Bauge SM. A methodological consideration for the determination of critical power and anaerobic work capacity. Res Q Exerc Sport. 1990; 61:406-9. [ Links ]
32. Fontes EB, Borges TO, Altimari LR, Melo JC, Okano AH, Cyrino ES. Influência do número de coordenadas e da seleção de distâncias na determinação da velocidade crítica na canoagem de velocidade. Rev Bras Ciên e Mov. 2002;10(Suppl 1):161. [ Links ]
33. Melo JC, Altimari LR, Gulak A, Machado MV, Cyrino ES, Chacon-Mikahil MPT. Comparação entre protocolos de determinação do limiar anaeróbio em nadadores adolescentes. Anais do I Congresso Brasileiro de Metabolismo, Nutrição e Exercício, 2006, Londrina, Brasil. 2006. p. 28. [ Links ]
34. Verkhoshansky YV. Entrenamiento deportivo Planificacion y programacion. Barcelona: Ed. Martinez Roca; 1990. [ Links ]
35. Bonifazi M, Martelli G, Marudo L, Sardella F, Carli G. Blood lactate accumulation in top level swimmers following competition. J Sports Med Phys Fitness. 1993; 33:13-8. [ Links ]
36. Guglielmo LGA, Denadai BS. Validade do ergômetro de braço para a determinação do limiar anaeróbio e da performance aeróbia de nadadores. Rev Port Cien Desp. 2001;1:7-13. [ Links ]
37. Melo JC, Altimari LR, Machado MV, Chacon-Mikahil MPT, Cyrino ES. Velocidade crítica, limiar anaeróbio e intensidade de nado na máxima fase estável de lactato sanguíneo em nadadores juvenis. Lect Educ Fís Deportes. 2005;10:on-line. [ Links ]
38. Reilly T, Woodbridge V. Effects of moderate dietary manipulations on swim performance and on blood lactate-swimming velocity curves. Int J Sports Med. 1998; 20:93-7. [ Links ]
39. Santos ILG, Papoti M, Gobatto CA, Zagatto AM. Relações entre o lactato mínimo e performance de nado crawl. Rev Bras Ci Mov. 2005;13(Supl 1):72. [ Links ]
40. Bartholomeu-Neto JB, Pellegrinotti IL, Cielo FMBL, Luchiari R. Correlação entre os tempos obtidos na distância de 100, 200 e 400 metros e a velocidade crítica em nadadores de 13 a 16 anos. Rev Bras Ci Mov. 2005;13(supl 1):96. [ Links ]
41. Stone MH, Sands WA, Stone ME. The downfall of sports science in the United States. Strength Cond J. 2004;26:72-5. [ Links ]
Profª Mara Patricia Traína Chacon-Mikahil
Faculdade de Educação Física UNICAMP
Av. Érico Veríssimo, 701
Cidade Universitária Zeferino Vaz
Barão Geraldo Campinas, SP, Brazil
Approved in 31/1/07.
All the authors declared there is not any potential conflict of interests regarding this article.