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TEORÍA Y METODOLOGÍA DEL DEPORTE ADAPTADO Prof. Ciro Winckler

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la Salud Pedagogía

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Velocidad

ACTN3 and ACE Genotypes in Elite Jamaican and US Sprinters

ROBERT A. SCOTT 1 , R A C H A E L IRVING 2 , L A U R A IRWIN 1 , ERROL MORRISON 3 , V I L M A C H A R L T O N 2 , KRISTA AUSTIN 4 , D A W N T L A D I 5 , M I C H A E L D E A S O N 1 , S A M U E L A. H E A D L E Y 6 , FRED W. K O L K H O R S T 7 , N A N Y A N G 8 , K A T H R Y N N O R T H 8 , and YANNIS P. PITSILADIS 1

1University of Glasgow, Glasgow, UNITED KINGDOM; 2University of West Indies Kingston, JAMAICA; 3University of Technology, Kingston, JAMAICA; 4United States Olympic Committee, Colorado Springs, CO; 5Georgia Southwestern State University, Americus, GA;6 Springfield College, Springfield, MA; 7San Diego State University, San Diego, CA; and 8Institute for Neuromuscular Research, Children's Hospital at Westmead, Sydney, AUSTRALIA

ABSTRACT

SCOTT, R. Α., R. IRVING, L . IRWIN, E. MORRISON, V . C H A R L T O N , K. A U S T I N, D. T L A D I , M . D E A S O N , S. A . H E A D L E Y , F. W. K O L K H O R S T , N . Y A N G , K. N O R T H , and Y . P. PITSILADIS. ACTN3 and ACE Genotypes in Elite Jamaican and US Sprinters. Med. Sci. Sports Exerc., Vol . 42, No. 1, pp. 107-112, 2010. The angiotensin-converting enzyme (ACE) and the α-actinin-3 (ACTN3) genes are two of the most studied "performance genes" and both have been associated with sprint/power phenotypes and elite performance. Purpose: To investigate the association between the ACE and the ACTN3 genotypes and sprint athlete status in elite Jamaican and US African American sprinters. Methods: The ACTN3 R577X and the ACE I/D and A22982G (rs4363) genotype distributions of elite Jamaican (J-A; Ν = 116) and US sprinters (US-Α; Ν = 114) were compared with controls from the Jamaican (J-C; Ν = 311) and US African American (US-C; Ν = 191) populations. Frequency differences between groups were assessed by exact test. Results: For ACTN3, the X X genotype was found to be at very low frequency in both athlete and control cohorts (J-C = 2%, J-A = 3%, US-C = 4%, US-A = 2%). Athletes did not differ from controls in ACTN3 genotype distribution (J, Ρ = 0.87: US. Ρ = 0.58). Similarly, neither US nor Jamaican athletes differed from controls in genotype at ACE I/D (J, Ρ = 0.44; US, Ρ = 0.37). Jamaican athletes did not differ from controls for A22982G genotype (P = 0.28), although US sprinters did (P = 0.029). displaying an excess of heterozygotes relative to controls but no excess of GG homozygotes (US-C = 22%, US-A = 18%). Conclusions: Given that ACTN3 X X genotype is negatively associated with elite sprint athlete status, the underlying low frequency in these populations eliminates the possibility of replicating this association in Jamaican and US African American sprinters. The finding of no excess in ACE DD or G G genotypes in elite sprint athletes relative to controls suggests that ACE genotype is not a determinant of elite sprint athlete status. Key Words: GENETICS, A F R I C A N , A T H L E T E , SPRINT, POWER

The recent Beijing Olympics was a phenomenal success for Jamaican sprinters, where they won 7 of the 12 available medals in the men's and

women's 100- and 200-m events as well as medals in the 400-m and the sprint relays. The United States took four of the five remaining medals. This, of course, prompts questions over why these athletes were so successful rel¬ative to those of other nations. Although training and environmental factors are certainly acknowledged as key components, there remains a belief that there is a genetic component to their success. However, no genetic studies have been undertaken in sprint athletes of this standard to

date. Elite athletic performance is a complex phenotype determined by several environmental factors such as diet, physical training, and sociocultural factors (19). Early fam¬ily studies indicated that genetic factors may also contribute to the interindividual differences in athletic performance (3,15), and a recent review has identified in excess of 200 gene variants associated with fitness-related phenotypes (4), although few of these variants have been associated with elite-level athletic performance.

Variants in the angiotensin-converting enzyme (ACE) gene have been associated with elite-level performance. The most frequently studied variant in the ACE gene is the I/D polymorphism: a 287-bp Alu insert into intron 16 of the gene. Generally, the D allele is associated with power phenotypes (20,21,37) and the I allele with endurance performance (2,7,13,20,21,30) in Caucasian populations, although findings have been equivocal (25,35). In addition, positive findings have not been replicated in other ethnic groups because a large study of east African distance runners did not find any association between ACE genotype and elite endurance athlete status (31). In Caucasians, the I/D polymorphism has been estimated to explain up to 47% of the variance in circulating A C E levels (28), with the I allele

Address for correspondence: Yannis P. Pitsiladis, Ph.D., Integrative and Systems Biology, Faculty of Biomedical and Life Sciences (IBLS). University of Glasgow, Glasgow G l 2 8QQ, United Kingdom: E-mail: [email protected]. Submitted for publication January 2009. Accepted for publication May 2009.

0195-9131/10/4201-0107/0 MEDICINE & SCIENCE IN SPORTS & EXERCISE® Copyright © 2009 by the American College of Sports Medicine

DOI:10.1249/MSS.0b013e3181 ae2bc0

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Periodization

tenet of a taper (discussed later in thisarticle) (56). According to this para-digm, athlete preparedness may beevaluated based on the principle after-effects of training: fitness and fatigue(87). Unlike the GAS and SFRAconcepts, which assume that fitnessand fatigue share a cause and effectrelationship, the Fit-Fat model suggeststhat they demonstrate an inverse re-lationship. This, therefore, implies thatstrategies that maximize fitness andminimize fatigue will have the greatestpotential to optimize athlete prepared-ness (74). The Fit-Fat concept isillustrated in Figure 8.

An additional key difference betweenthe Fit-Fat concept and the aforemen-tioned models is that it differentiatesbetween the actions of various stres-sors, such as neuromuscular and met-abolic stress (7) and therefore impliesthat the aftereffects of fitness andfatigue are exercise specific (74,87).This suggests that if the athlete is tootired to repeat the same exercise withan acceptable quality (as measured bypower output or form for example),theymay still be able to perform anotherexercise to satisfaction (Figure 9). This,for example, provides the basic tenet tohypertrophy programs incorporating3- to 5-day splits and concurrenttraining involving both aerobic andresistance workouts.

THE PRINCIPLE OF DIMINISHINGRETURNSMonotonous volume loads and train-ing methods can predispose an athleteto accommodation and stagnation(70,74). Zatsiorsky and Kraemer (87)refer to this as the principle ofdiminishing returns, whereby the ner-vous system is no longer challenged toadapt. It is therefore of the upmostimportance to incorporate variabilitywithin the design of periodized S&Cplans. This ideology serves as therationale for the regular application ofnovel and seminovel tasks (exercisedeletion and re-presentation) (74).Additional methods of incorporatingvariability other than exercise selectioninclude changes in volume, intensity,and frequency (5) or any combination

Figure 4. The GAS paradigm that suggests that the body’s response to stress isalways the same despite the stressor. Here, the body undergoes an alarmphase and a resistance phase before supercompensation is experienced.P = performance; T = time.

Figure 5. The stimulus-fatigue-recovery-adaptation theory concept suggests thatfatigue accumulates in proportion to the strength and duration ofa stimulus, and then after rest, fatigue is dissipated and supercompensationoccurs. P = performance; T = time.

Figure 6. The fitness-fatigue paradigm suggests that fitness (top curve) and fatigue(bottom curve) occur concurrently, and only when fatigue has dissipated,does fitness gains become apparent and athlete preparedness (blue line)becomes apparent and optimized (x-axis, time).

Strength and Conditioning Journal | www.nsca-lift.org 37

Fonte: Turner, 2011

PrincipiosyDiferenças

DiscapacidadAmputación

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UsuáriosdeSilladeRuedas• LesionMedular,Amputacion yotros

Respuestafisiológica 10-20%menos eficiente

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BC1 Classificatória individual BC1. Na foto o atleta, José Carlos Chagas. ©Alaor Filho/MPIX/CPB








Fonte: Turner, 2011

• Elvolumensistólico• Elgastocardíaco•Metabolismomuscular

Respuestasfisiológicasalejercicio

• Rendimientodelashabilidadesfísicasendiversosprotocolosdeentrenamientovariade20a50%

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Respuestas de la Persona con Discapacidad Intelectual al Ejercicio

Original article

Br J Sports Med 2010;44:215–220. doi:10.1136/bjsm.2009.067249 215

Correspondence to Dr Brendan Burkett, School of Health and Sport Sciences, Faculty of Science, Health and Education, University of the Sunshine Coast, Maroochydore DC, Queensland 4558, Australia; [email protected]

Accepted 9 October 2009

Technology in Paralympic sport: performance enhancement or essential for performance?Brendan Burkett

ABSTRACTBackground People with disabilities often depend on assistive devices to enable activities of daily living as well as to compete in sport. Technological developments in sport can be controversial.Objectives To review, identify and describe current technological developments in assistive devices used in the summer Paralympic Games; and to prepare for the London 2012 Games, the future challenges and the role of technology are debated.Methods A systematic review of the peer-reviewed literature and personal observations of technological developments at the Athens (2004) and Beijing (2008) Paralympic Games was conducted.Results Standard assistive devices can inhibit the Paralympians’ abilities to perform the strenuous activities of their sports. Although many Paralympic sports only require technology similar to their Olympic counterparts, several unique technological modifi cations have been made in prosthetic and wheelchair devices. Technology is essential for the Paralympic athlete, and the potential technological advantage for a Paralympian, when competing against an Olympian, is unclear.Conclusion Technology must match the individual requirements of the athlete with the sport in order for Paralympians to safely maximise their performance. Within the ‘performance enhancement or essential for performance?’ debate, any potential increase in mechanical performance from an assistive device must be considered holistically with the compensatory consequences the disability creates. To avoid potential technology controversies at the 2012 London Olympic and Paralympic Games, the role of technology in sport must be clarifi ed.

INTRODUCTIONEquipment such as prostheses and wheelchairs is fundamental in allowing some people with dis-abilities to carry out the tasks of daily living.1 2 Advances in technology underpin such assistive devices—for example, the development of the energy-storing prosthetic foot, can make a lower-limb amputee’s gait more effi cient and ambula-tion faster.3 4 When this revolutionary prosthetic technology was specifi cally applied to sprinters, studies showed that running velocity was signif-icantly increased.5 6 However, the application of this technology has been controversial, as clearly demonstrated by the much-publicised Oscar Pistorius or ‘Blade Runner’ debate before the 2008 Beijing Olympic and Paralympic Games.7–11 The skill of the athlete, coupled with this new pros-thetic technology, enabled Oscar to potentially qualify in the men’s 400 m sprint in both the 2008 Olympic and Paralympic Games. In the best

interest of the athlete, and to avoid potential legal problems and unwarranted issues for the next Olympic Games in London 2012, the role of tech-nology needs to be clarifi ed.

Under rule 144.2, the International Amateur Athletics Federation (IAAF) forbids ‘the use of any technical device incorporating springs …that provides the user with an advantage over another athlete not using such a device.’12 This raises the question: Does the technology create an unfair advantage for the Paralympian when competing against able-bodied Olympic athletes? When we debate whether certain sports technologies pro-vide an advantage over another athlete, the issue becomes clouded, as we must also consider equita-ble access to the technology. Consider, for exam-ple, that the Olympic marathon was won in 1960 by Abebe Bikila, an athlete from Ethiopia who ran barefoot. How much faster could Abebe have run with contemporary technology to absorb the jar-ring ground reaction forces and improve friction at the foot-ground interface? At the 2008 Beijing Games, some track and fi eld athletes wore clothing that incorporate threads of Vectran fi bre which, the manufacturer, Nike, claimed ‘reduce drag by 7% when compared with the 2004 outfi ts.’13

Although not discussed in peer-reviewed lit-erature, it is well documented in the press and sports communities that both the Olympic and Paralympic movements struggle with the role of technology in the sporting arena. For example, in 2008, Speedo launched their new LZR Racer suit amid much debate about the performance-enhancement characteristics of these new suits. The suit’s technology included strategically placed polyurethane panels to reduce drag and a corset-like structure that may help to streamline the body, although this effect is yet to be con-fi rmed in scientifi c literature. At the 2008 Beijing Games, 94% of all swimming races were won by swimmers wearing the suit. A total of 108 world records were broken in 2008, and at the 2009 World Swimming Championships in Rome, another 43 world records tumbled, mostly with swimmers wearing the new controversial poly-urethane suits. It is speculated that the suits create a greater advantage than the best performance-en-hancing drugs, which raises the comment: ‘Who’s going to win the gold medal, the swimmer or the technician?’13

Paralympic sports evolved from medical rehabil-itation programmes in the 1950s.14–16 The objec-tive of a rehabilitation programme is to regain a level of function for the client; for an athlete with a disability, the highest expression of this return to function is to compete at an elite level in the

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MICRO-CICLOS, MÉTODOS DE TRABAJO Y DESARROLLO DE LAS CARGAS DE ENTRENAMIENTO PARA PERSONAS CON DISCAPACIDAD

and where sport-specific biomotors areperfected (5). During the competitivephase, Nadori and Granek (59) suggestthat as a minimum objective, the workcapacity developed during the SSPTshould be maintained (Table 1).

The importance of the preparatoryphase is highlighted by Zatsiorsky andKraemer (87) who use the analogy‘‘soon ripe, soon rotten.’’ This, alongwith data by Fry et al. (19) and work byStone et al. (74), suggests that theaverage training intensity is inversely

correlated with the time a performancepeak can be maintained and the heightof that performance peak (Figure 3).

As a final note into defining the essenceof periodization, the S&C coachshould be cognizant of the fact thatthe science and practice of periodiza-tion is largely based on the hypothesis-generating studies, anecdotal evidence,and related research (8,16,21,64,72). Inaddition, most studies involved onlyshort-term experimental periods (e.g.,5–16 weeks) and subjects with limited

training experience (8,16,21,64,72).These contentious issues have beenraised in a review paper by Cissik et al.(8), and readers are recommended tothis for further analysis. However,and despite these challenges to anevidence-based ideology, it should benoted that enough anecdotal evidence,case study reports, and empiricallysimilar research exist to advocate itsuse across all population groups.

RECOVERY AND ADAPTATIONMesocycle blocks are usually arrangedin a 3:1 loading paradigm (Figure 4),whereby the load gradually increasesfor the first 3 microcycles (weeks)before an unloading phase in the fourth(creating the typical undulating ap-pearance of periodized programs). Theunloading phase reduces fatigue,thereby allowing adaptations to takeplace (26,27,64). The significance ofappropriately planned work to restratios (with respect to training ses-sions) may be evidenced by the articlesof Nadori and Granek (59) and Pliskand Stone (64) who suggest that thegreater the number of progressiveloading steps, the greater the numberof unloading steps required, for exam-ple, a 4:2 paradigm. It should also benoted that because training adaptationstake place during recovery periods(27), the need to reduce accumulatedfatigue cannot be understated. As ananecdotal example, one of the majordifferences between professional andsemiprofessional athletes is that aftertraining, the professional athlete re-turns home and rests, whereas thesemiprofessional athletes goes off towork. This, of course, has implicationsfor the recovery–adaptation relation-ship, especially if the work is of aphysical nature.

The importance of recovery phases forthe purposes of adaptation is wellestablished (26,27). The S&C coachmust therefore ensure that work to restratios are appropriately planned (e.g.,using the 3:1 step loading paradigm) toavoid excessive fatigue and a reducedstimulus for adaptation. According toStone et al. (74), this trade-off isdescribed by 3 principle theories: (a)

Figure 1. The inverse relationship between volume and intensity. In general, as theperiodized program advances and competition nears, intensity increases,whereas volume decreases. VOL = volume; INT = intensity; TECH = technique;GPT = general physical training; SSPT = sport-specific physical training;COMP = competition.

Figure 2. Training intensity is inversely correlated with the time a performance peakcan be maintained and the height of that performance peak. (informationattained from Stone et al. (74)) P = performance; T = time.


Estrutura General de Periodización

Fonte: Turner, 2011The Science and Practiceof Periodization: A BriefReviewAnthony Turner, MSc, CSCSLondon Sport Institute, Middlesex University, London, England

S U M M A R Y

PERIODIZATION REPRESENTS ANOPTIMAL STRATEGY FOR ORGA-NIZING STRENGTH AND CONDI-TIONING PROGRAMS. THESELECTED STRATEGY, HOWEVER,SHOULD BE BASED ON THE LEVELOF THE ATHLETE AND THE CON-STRAINTS OF THE COMPETITIVESEASON. A COMMON THEMETHROUGHOUT ALL THE PERIODI-ZATION PROTOCOLS IS THE NEEDTO MANIPULATE VOLUME LOADS,PROGRESS FROM GENERAL TOSPORT-SPECIFIC TRAINING, ANDDISSIPATE FATIGUE. SIGNIFICANTTO THE LATTER, THE USE OFPRECOMPETITION TAPERS AP-PEARS EVIDENTLY BENEFICIAL.ALTHOUGH ENOUGH ANECDOTALEVIDENCE EXISTS TO VALIDATETHE USE OF PERIODIZATION, FUR-THER SCIENTIFIC INVESTIGATIONIS REQUIRED TO UNDERSTAND ITSUSE AND LIMITATIONS TO ELITELEVEL ATHLETES ACROSS EX-TENDED PERIODS (E.G., .4YEARS). UNTIL SUCH TIME, HOW-EVER, ITS USE IS RECOMMENDEDAND ADVOCATED BY THE RE-SEARCH HEREIN.

INTRODUCTION

Periodization is regarded as asuperior method for developingan athlete’s peak performance

(16,26,71–73). However, because anathlete’s peak performance can onlybe maintained for 2–3 weeks (74), the

ability to coordinate this with a com-petition date long into the future (e.g.,the Olympics) is a fundamental skill toall strength and conditioning (S&C)coaches and the one that may only beattained after competency of the sci-ence and practice of periodization.Furthermore, and despite an apparentlack of scientific rigor to govern itsapplication (8,16,21,64,71), periodiza-tion is widely practiced (11–13,67) andrecommended (26,27,64). The aim ofthis article, therefore, was to providethe S&C coach with a brief overview ofperiodization so as they may be cog-nizant of its theory and methodology.It is hoped that this will furtherfacilitate its implementation and suc-cessful application.

DEFINING PERIODIZATIONPeriodization may be defined as a train-ing plan, whereby peak performance isbrought about through the potentia-tion of biomotors and the managementof fatigue and accommodation. This isprincipally achieved through the logi-cal yet creative variation of trainingmethods and volume loads (50). Sig-nificant to the latter point, and often-times the landmark of periodization,volume and intensity (volume loads)share an inverse relationship (Figure 1)with the only notable exceptions beingduring periods of planned overreach-ing (Figure 2).

Plisk and Stone (64) suggest thatperiodization is applied on a cyclic orperiodic basis, structured into macro-,meso-, and microcycles, which prog-ress from extensive to intensive (or

from high volume to high intensity)workloads (Figure 1). These cycles areoften defined by their allotted period,with a macrocycle typically referring toa year, a mesocycle to a month, anda microcycle to a week. There is,however, large variability in the timecourse of each, with, for example,macrocycles running $4 years in thecase of Olympic S&C programs.Moreover, mesocycles are often di-vided into 4 6 2-week blocks, as thisappears to provide the optimal timeframe for adaptation (51,64,74,84,87).

Periodization is also often defined byits progression from general to specialtasks (Figure 1, note the incorporationof technique-/sport-specific biomotorsas the program progresses and com-petition nears) (64). This is furthersupported by Bompa and Haff (5) whoreported 2 major phases of periodiza-tion: the preparatory phase and thecompetitive phase (Figure 1). In addi-tion, the preparatory phase has 2subphases: general physical training(GPT) and sport-specific physicaltraining (SSPT). The objective of theGPT is to improve the athlete’s workcapacity and maximize adaptations inpreparation for future workloads (5).The SSPT serves as a transition intothe competitive phase, whereby phys-ical capacity is developed specific tothe physiological profile of the sport

KEY WORDS :

periodization; fitness; fatigue; recovery;preparedness; summated; undulating;conjugate; taper

VOLUME 33 | NUMBER 1 | FEBRUARY 2011 Copyright ! National Strength and Conditioning Association34

the Selye general adaptation syndrome(GAS), (b) the stimulus-fatigue-recov-ery-adaptation theory (SFRA), and (c)the fitness-fatigue theory (Fit-Fat).

GENERAL ADAPTATIONSYNDROMEThe GAS paradigm describes thebody’s physiological response to stress,which, according to Selye (66), is thesame despite the stressor. The GASassumes 3 distinct phases during stress,which, for the following example, willbe an exercise training session. Thealarm phase (phase 1) represents therecognition and initial response tothe session. This may be in the formof fatigue, stiffness, or delayed onset ofmuscle soreness for example. Theresistance phase (phase 2) is theninitiated in which the body is returnedto either its pre-exercise session

homeostasis or its new adapted higherstate (i.e., supercompensation occurs).Finally, and assuming that the accu-mulation of stress is too great (e.g., theabsence of an unloading week), theexhaustion phase (phase 3) occurs, andthis may be considered synonymouswith overtraining (74). The GAS isdepicted in Figure 5.

STIMULUS-FATIGUE-RECOVERY-ADAPTATION THEORYThe SFRA concept (80,81,83) suggeststhat fatigue accumulates in proportionto the strength and duration of a stim-ulus. Then, after the stimulus, forexample, an exercise session, the bodyis rested, enabling fatigue to dissipateand adaptations (often referred to assupercompensation) to occur. Thisconcept also suggests that if the stressis not applied with sufficient frequency

(also known as density), detraining(also known as involution) will occur.Moreover, involution time is influ-enced by the length of the preparationperiod (74), with the greater theduration of a training program, thegreater the residual effects (Figure 3)(87). In addition, and by virtue of this,the subsequent preparation phases in-herent to bi- and tricycles can pro-gressively decrease. The significance ofpreparation has been previously dis-cussed within this article. The SFRAconcept is illustrated in Figure 6.

The SFRA concept is also used todescribe the supercompensationobserved after periods of planned over-reaching (81,83). For example, theaccumulation of fatigue from the se-quential execution of similar trainingsessions (i.e., a concentrated primarilyunidirectional loading of strength/power training) is superimposed onone another (Figure 7). This, therefore,leads to excessive fatigue and acutely(almost equal to 4 weeks) diminishedstrength and power capabilities. How-ever, after the return to normal training(and by virtue of a delayed trainingeffect phenomenon), they then reboundbeyond their initial values (20,69). Thisstrategy, however, is reserved for elitelevel athletes, whose window for adap-tation is small, and therefore requiresmore intense interventions to bringabout a supercompensation response(5). Planned overreaching strategies arebriefly discussed later in this article.

FITNESS-FATIGUE PARADIGMCurrently, this is the most prevailingtheory of training and adaptation(7,64,74) and is considered the basic

Table 1The principle phases and subphases of periodization

Training phase

Preparatory phase

Competitive phaseGPT SSPT

Phase objective [ aerobic and anaerobic capacity;[ neuromuscular functioning

Develop and perfect sport-specificbiomotors

Maintain biomotorconditioning

Information attained from Bompa and Haff (5).

GPT = general physical training; SSPT = sport-specific physical training; [ = increase.

Figure 3. A 3:1 loading paradigm (information attained from Bompa and Haff (5) andStone et al. (74)) VL = volume load.

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Fonte: Turner, 2011

of these. As a final word of caution,however, the reader should note thattoo much variability could reduce theopportunity for the body to adapt tothe given stimulus and reduce thedevelopment of skill acquisition (5).

APPLICATION OF PERIODIZATION

BASIC MODEL OF PERIODIZATIONThe type of periodized model usedshould reflect the S&C training age ofthe athlete and not their competitionage or rank. It is considered prudent

therefore to initiate S&C programswith basic periodized models. Thesegenerally entail little variation andrelatively flat workloads (74) with themain emphasis being on the logical andtherefore potentiated progression ofbiomotors (e.g., strength endurance !strength ! power). Figure 7 illustratesa basic model.

As an example of this basic strategy,the athlete essentially completes a hy-pertrophy/strength endurance phasefor 4 microcycles (or 1 mesocycle),a strength phase for 4 microcycles, andthen a power phase for 4 microcycles(Table 2). Each phase (dependent onthe prescribed volume loads) may befurther separated by an unloadingweek, as may also happen after thepower phase and before the competi-tion. In addition, heavy and light daysmay still be prescribed. This strategy,considered appropriate for athleteswith an S&C age of zero, introducesthem to S&C (i.e., the merits of and therequired discipline) and periodization(i.e., the need to systematically alter theemphasized biomotors and a qualityover quantity approach) and enablesthem to get a ‘‘feel’’ for gym-basedtraining interventions and developingtheir associated technique. As a finalnote on this basic model (which isapplicable to all models), to ensure theathlete gets the most out of each phase,the S&C coach should ensure that theyare technically sound to perform theexercise of each phase before progress-ing onto it. For example, power cleansand snatches may be part of the powerphase; however, the athlete shouldstart practicing and developing themin the strength endurance phase toensure effective training by the timethey are called into use.

INTERMEDIATE MODEL OFPERIODIZATIONAs the athlete’s S&C age advances andadaptations begin to plateau, greatervariability becomes paramount. In addi-tion, because of the enhanced workcapacity of the athlete, greater volumeloads are required and thus the need forplanned recovery sessions. The perio-dized program therefore begins to evolve

Figure 7. Athlete preparedness based on the specific form of fatigue. In this scenario,while the athlete is too fatigued to effectively undertake any additionalstrength training sessions so acutely, they are able to work and adapt theiraerobic system with relatively less recovery (information attained fromZatsiorsky and Kraemer (87)).

Figure 8. Basic model of periodization entailing little variation and relatively flatworkloads within each mesocycle.

Figure 9. The traditional approach to the design of periodized training, which isattributed to the work of Matveyev (50), (y axis, volume load; x axis, week).

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into wavelike increases in volume loads(50,51) that typically fluctuate at themicrocyclic level (71,72). This is referredto as summated microcycles and isusually represented as the 3:1 paradigmpreviously discussed. In addition, andbecause of the need to incorporatevariability, each microcycle can possesmultiple biomotors (e.g., strength, power,and speed work), some for the purposeof maintenance and potentiation andothers for the purpose of developmentand adaptation. Additional methods ofincorporating variability and thus adap-tation include intersession variability(e.g., heavy and light days and exercisedeletion and re-presentation methods)and intrasession variability (e.g., clustertraining and postactivation potentiationprotocols). Figure 10 illustrates thistraditional approach for designing perio-dized programs, which is attributed toMatveyev (50,51). An example of in-termediate periodized program is illus-trated in Table 3.

ADVANCED MODEL OFPERIODIZATIONAgain, as the athlete’s S&C age advancesand the windows of adaptation begin todiminish, more advanced strategies arerequired, which incorporate yet morevariability and greater volume loads. Themajority of the emphasis, however, isnow placed on the prescription ofvolume loads through advanced strate-gies such as the conjugated system (alsoknown as the coupled successive system;Figure 10) (82). Because this places theathlete dangerously close to the over-training syndrome, athletes undertak-ing this system must be able to tolerate

very-high–volume loads (64), and theS&C coaches applying these interven-tions must be highly skilled.

The conjugate system involves periods ofplanned overreaching followed by peri-ods of restitution (64). Plisk and Stone(64) suggest that this is best implementedin the blocks of 4 microcycles with onlyone primary emphasis (e.g., strength),with maintenance loads allocated toother abilities (e.g., speed). This systemaims to saturate the emphasized trainingstress, causing significant fatigue andconcurrent decreases in performance.Then, during the following restitutionblocks, the emphasis is reversed (Figure2). For example, the volume load forstrength training markedly drops,whereas that for speed work is moder-ately increased. By virtue of a delayedtraining effect phenomenon, the athlete’sstrength capabilities undergo supercom-pensation. A practical example of theconjugate system, adapted from the

work of Plisk and Stone (64) and Stoneet al. (74), is illustrated in Table 4. Here, itcan be seen that volume load ismanipulated by simply increasing (accu-mulation) or decreasing (restitution) thenumber of sessions in each block.

Significant support for the conjugatesystem may be gleaned from studiesinvestigating the response of the endo-crine system to prolonged ($3 week)and severe increases in volume load(20,28,30,61,65). In general, these studiesreport significant decreases in resting/pre-exercise testosterone concentrationand the testosterone to cortisol ratio,followed by supernormal levels andcorresponding performance improve-ments upon returning to normal volumeloads with a subsequent taper. Thesefindings are considered significant asthe testosterone concentration and thetestosterone to cortisol ratio are consid-ered indices of the anabolic/catabolicstate of the body (19,64).

Table 2Example sessions used as part of a basic periodized model

Example hypertrophy session Example strength session Example power session

Intensity: 3 3 10 at 10–12 RM, ,2 minsbetween sets and exercises

Intensity: 4 3 4 at 4–6 RM, .2 minsbetween sets and exercises

Intensity: 5 3 3 at variable loads,.3 mins between sets and exercises

Exercises: Squats, SLDL, bench press,lat pull-down, shoulder press(note: weightlifting may have tobe developed within the warm-up)

Exercises: Squats, SLDL, bench press,weighted chins (note: weightliftingmay have to be developed withinthe warm-up)

Exercises: Snatch, jump squats

SLDL = stiff leg deadlift.

Figure 10. The conjugate sequence system pioneered by Verkhoshansky (82). Thissystem involves periods of planned overreaching followed by periods ofrestitution.


in actual competition or field-basedcriterion performance of competitiveathletes after a taper. Table 7 summa-rizes their findings (measured as effectsizes [an effect size is an objective wayof identifying the meaningfulness ofresults and is commonly used withina meta-analysis because their values arestandardized. The formula subtractsthe mean of one group from the meanof another and divides the difference bythe SD)], for which the scale proposedby Cohen (9) was used for their inter-pretation. Accordingly, the magnitudeof the difference was considered small(0.2), moderate (0.5), or large (0.8).

The results of the study by Bosquetet al. (6) revealed that the optimal taperis 2 weeks in duration and consists ofexponentially reducing the volume oftraining by 41–61%, while maintainingboth the intensity and the frequency ofsessions. This outcome is in agreementwith the previous investigations (56)and confirmed the reports of others,which suggest that volume is theoptimal variable to manipulate (34,56).

The reader should also note the largevariability between studies, as suggestedby 95% confidence intervals (Table 7). Itis therefore likely that not all athleteswill respond favorably to this taperprescription. For example, based ontheir review of research, Wilson andWilson (85) concluded that the re-duction in volume should be dependenton the accumulated fatigue gainedthrough the preceding training pro-gram, that is, greater volume reductionsare necessary when previous trainingdurations are longer and more intense.For example, in trained athletes, Mujikaand Padilla (56) found benefits fromreducing the volume by 50–90% foraerobic events (49,60) and 50–70% foranaerobic events (55,77). However,Thomas and Busso (75) suggested anoptimal volume reduction in the rangeof 30–40% for untrained athletes. Thelatter investigators attributed this lowerpercentage to the reduced capacity ofuntrained athletes to sustain greatervolume loads (and therefore fatigue)during the preceding training program.

Figure 12. The 2-phase taper (Information attained from Thomas et al. (76)) VL =volume load.

Table 7Effect of training variables on the effect size of taper-induced performance

adaptations

Variable Effect size 95% CI p

Y in volume

#20% 20.02 20.32, 0.27 0.88

21–40% 0.27 0.04, 0.49 0.02

41–60% 0.72 0.036, 1.09 0.0001

$60% 0.27 20.03, 0.057 0.07

Y in intensity

Yes 20.02 20.037, 0.33 0.91

No 0.33 0.19, 0.47 0.0001

Y in frequency

Yes 0.24 20.03, 0.52 0.08

No 0.35 0.18, 0.51 0.0001

Duration of taper, d

#7 0.17 20.05, 0.38 0.14

8–14 0.59 0.26, 0.92 0.0005

15–21 0.28 20.02, 0.59 0.07

$22 0.31 0.14, 0.75 0.18

Pattern of taper

Step 0.42 20.11, 0.95 0.12

Progressive 0.30 0.16, 0.45 0.0001

Information attained from Bosquet et al. (6).

CI = confidence intervals; d = days; p = significance value; Y = decrease.

Strength and Conditioning Journal | www.nsca-lift.org 43 Fonte: Turner, 2011

– Written by Irineu Loturco and Fabio Y. Nakamura, Brazil

TRAINING PERIODISATIONAN OBSOLETE METHODOLOGY?

Table 1

Event Number of athletes

WC better than season PB % EFF

All throws (finalists)

Men 48 8 17

Women 36 9 25

High jump

Men 33 6 18

Women 35 9 26

Triple jump

Men 43 7 16

Women 32 8 25

110m and 100m hurdles

Men 47 13 28

Women 32 8 25

Table 1: Effectiveness of the preparation for the World Track and Field Championships, 1995 in specific events: Championship results versus the best performance in the season. WC = World Championships result. PB = Personal best. EFF = Effectiveness.

Indicações

Baja tasa de éxito de la periodización

Pruebas y controles asociados con la especificidad

Control de los efectos a escala de volumen y intensidad

Controlar las cargas internas

medidas simples

¿QUE HACER?

¿Qué datos nos proporcionan?

Zancadas

10

0

15

30

45

60

Petrucio Derus Yohanson

Olímpicos 41-49

Zancadas

¿Qué datos nos proporcionan?

Tempos

10

0

1,25

2,5

3,75

5

Petrucio Derus Yohanson

¿Lo que se observa en esta carrera?

Rendimiento deportivo

Efectos agudos

Efectoscrónico

Cargas Internas

Cargas Externas

Como hacer el Controle

0 REPOSO/NADA

1 MUY, MUY LIGERO

2

3 LIGERO

4 MODERADO

5 ALGO DURO

6 Duro7

8 MUY DURO

9

10 EXTREMADAMENTE DURO

CR10 Borg

4 Nakamura et al.

R. da Educação Física/UEM Maringá, v. 21, n. 1, p. 1-11, 1. trim. 2010

representaria uma carga de treinamento equivalente a 240 unidades arbitrárias (Figura 2).

Figura 2 - Exemplo de quantificação das cargas

pelo método da PSE da sessão

De acordo com Foster et al. (1996; 2001), a PSE da sessão pode ser utilizada para a construção de curvas/gráficos de periodização do treinamento (Figura 2). Isso permitiria a visualização do padrão de alternância e distribuição das cargas de treinamento. Estes gráficos de distribuição das cargas têm sido, frequentemente, reportados em livros didáticos (BOMPA, 1999; MATVEEV, 1997), porém, nos mesmos não há explicação de como as cargas podem ser quantificadas. O método da PSE da sessão combina a duração e a intensidade da unidade de treinamento, fornecendo a magnitude da carga interna.

Outros índices úteis e práticos também podem ser obtidos a partir da quantificação das cargas de treinamento pela PSE da sessão. Além da magnitude da carga, a monotonia das cargas entre dias consecutivos parece influenciar as respostas adaptativas. A baixa variabilidade pode levar a adaptações negativas, potencializando a chance de overtraining. Uma forma simples de acessar a monotonia das sessões é o cálculo da média das cargas de treinamento das sessões de um determinado período (por exemplo, uma semana) dividido pelo seu desvio padrão (FOSTER, 1998). Por exemplo, na figura 2 pode-se observar a organização das cargas de treinamento da semana (Seg: 0 U.A.; Ter: 600 U.A.; Qua: 240 U.A.; Qui: 300 U.A. Sex: 450 U.A.; Sab: 200 U.A. e Dom: 700 U.A. – Total 2490 U.A.). A média da semana (2490 U.A. ÷ 7 dias = 356

U.A.) dividida pelo seu desvio padrão (225) determina o nível de monotonia do treino (1,58). Logo, quanto menos as cargas variarem, maior será a monotonia. Além disso, Foster (1998) propôs também uma medida de training strain, calculada por meio da multiplicação da monotonia pelo somatório das cargas de treinamento acumuladas no período (Training strain = 2490 x 1,58 = 3934 U.A.). Essa medida também está associada ao nível de adaptação ao treinamento. Em períodos de cargas elevadas e alto nível de monotonia, observa-se aumento da incidência de doenças infecciosas e lesões (FOSTER, 1998). Por esta razão, recomenda-se o cálculo e o acompanhamento frequente desses índices, bem como o estabelecimento de sua relação com o desempenho competitivo.

UTILIZAÇÃO DA PSE DA SESSÃO NAS MODALIDADES ESPORTIVAS

A PSE da sessão apresenta forte relação com outros indicadores internos de intensidade de exercício, como, por exemplo, o consumo de oxigênio e a frequência cardíaca (FC) mantidos no fase estável de exercícios contínuos (HERMAN et al., 2006). Dessa forma, este método pode auxiliar na quantificação da carga de sessões de treinamento de modalidades esportivas com características aeróbias e cíclicas, em que a variação nos parâmetros fisiológicos durante o esforço não é grande (exemplo: corridas de fundo).

Diversos métodos de quantificação do treinamento baseados nas respostas de frequência cardíaca, nas respostas ventilatórias e na concentração de lactato têm sido utilizados para validar o método da PSE da sessão (BANISTER, 1991; EDWARDS 1993; LUCÍA et al., 2003; SEILER; KJERLAND, 2006). Os métodos propostos por Banister (1991), Edwards (1993), Lucía et al. (2003) e Seiler e Kjerland (2006) têm sido, frequentemente, adotados para validação da PSE da sessão, sendo todos aceitos como critério para esta validação.

Em nadadores, as médias das correlações intraindividuais entre as cargas de treinamento determinadas pela PSE da sessão e pelos impulsos de treinamento (TRIMPs) pelo método de Banister (1991), Edwards (1993) e Lucía et al. (2003) foram, respectivamente, de 0,74, 0,75

PSE = Borg X Tiempo

Fonte: Nakamura, 2010

Magnitud de carga

Carga Prescrita XPercepción de carga

My Jump app

Olímpicos r2= .92 Atletas r2= .82 Guias

r2= .36

Testes Simples com Grande Associação aos

Gestos Técnicos

.54

ORIGINAL RESEARCHpublished: 06 November 2015

doi: 10.3389/fphys.2015.00323

Frontiers in Physiology | www.frontiersin.org 1 November 2015 | Volume 6 | Article 323

Edited by:

Thomas Janssen,

VU University Amsterdam,

Netherlands

Reviewed by:

Naoto Fujii,

University of Ottawa, Canada

Alvaro N. Gurovich,

Indiana State University, USA

*Correspondence:

Irineu Loturco

[email protected]

Specialty section:

This article was submitted to

Exercise Physiology,

a section of the journal

Frontiers in Physiology

Received: 28 August 2015

Accepted: 26 October 2015

Published: 06 November 2015

Citation:

Loturco I, Winckler C, Kobal R, Cal

Abad CC, Kitamura K, Veríssimo AW,

Pereira LA and Nakamura FY (2015)

Performance changes and relationship

between vertical jump measures and

actual sprint performance in elite

sprinters with visual impairment

throughout a Parapan American

games training season.

Front. Physiol. 6:323.

doi: 10.3389/fphys.2015.00323

Performance changes andrelationship between vertical jumpmeasures and actual sprintperformance in elite sprinters withvisual impairment throughout aParapan American games trainingseasonIrineu Loturco 1*, Ciro Winckler 2, Ronaldo Kobal 1, Cesar C. Cal Abad1, Katia Kitamura 1,Amaury W. Veríssimo2, Lucas A. Pereira 1 and Fábio Y. Nakamura 1, 3

1 Nucleus of High Performance in Sport, São Paulo, Brazil, 2 Brazilian Paralympic Committee, Brasília, Brazil, 3 Department of

Physical Education, State University of Londrina, Londrina, Brazil

The aims of this study were to estimate the magnitude of variability and progression in

actual competitive and field vertical jump test performances in elite Paralympic sprinters

with visual impairment in the year leading up to the 2015 Parapan American Games,

and to investigate the relationships between loaded and unloaded vertical jumping

test results and actual competitive sprinting performance. Fifteen Brazilian Paralympic

sprinters with visual impairment attended seven official competitions (four national, two

international and the Parapan American Games 2015) between April 2014 and August

2015, in the 100- and 200-m dash. In addition, they were tested in five different periods

using loaded (mean propulsive power [MPP] in jump squat [JS] exercise) and unloaded

(squat jump [SJ] height) vertical jumps within the 3 weeks immediately prior to the main

competitions. The smallest important effect on performances was calculated as half

of the within-athlete race-to-race (or test-to-test) variability and a multiple regression

analysis was performed to predict the 100- and 200-m dash performances using the

vertical jump test results. Competitive performance was enhanced during the Parapan

American Games in comparison to the previous competition averages, overcoming the

smallest worthwhile enhancement in both the 100- (0.9%) and 200-m dash (1.43%). In

addition, The SJ and JS explained 66% of the performance variance in the competitive

results. This study showed that vertical jump tests, in loaded and unloaded conditions,

could be good predictors of the athletes’ sprinting performance, and that during the

Parapan American Games the Brazilian team reached its peak competitive performance.

Keywords: Paralympics, track and field, muscle power, physical disability, blind athletes

9 Moss, B. M., Refsnes, P. E., Abildgaard, A., Nicolaysen, K., Jensen, J. (1997). Effects of maximal 413 effort strength training with different loads on dynamic strength, cross-sectional area, load-power 414 and load-velocity relationships. Eur J Appl Physiol Occup Physiol. 75, 193-9. 415 Nilsson, J., Thorstensson, A. (1989). Ground reaction forces at different speeds of human walking 416 and running. Acta Physiol Scand. 136, 217-27. 417 Pyne, D., Trewin, C., Hopkins, W. (2004). Progression and variability of competitive performance 418 of Olympic swimmers. J Sports Sci. 22, 613-20. 419 Sanchez-Medina, L., Perez, C. E., Gonzalez-Badillo, J. J. (2010). Importance of the propulsive 420 phase in strength assessment. Int J Sports Med. 31, 123-9. 421 Sleivert, G., Taingahue, M. (2004). The relationship between maximal jump-squat power and sprint 422 acceleration in athletes. Eur J Appl Physiol. 91, 46-52. 423 Stone, M. H., O'Bryant, H. S., McCoy, L., Coglianese, R., Lehmkuhl, M., Schilling, B. (2003). 424 Power and maximum strength relationships during performance of dynamic and static weighted 425 jumps. J Strength Cond Res. 17, 140-7. 426 Wisloff, U., Castagna, C., Helgerud, J., Jones, R., Hoff, J. (2004). Strong correlation of maximal 427 squat strength with sprint performance and vertical jump height in elite soccer players. Br J Sports 428 Med. 38, 285-8. 429 Young, W., Benton, D., Pryor, J. M. (2001). Resistance training for short sprints and maximum-430 speed sprints. Strength Cond J. 23, 7. 431 432 FIGURES AND TABLE LEGENDS 433 434 Figure 1. Variation in 100- (Panel A) and 200-m (Panel B) dash performances across seven official 435 competitions. The black line represent the mean individual performances, and the gray area 436 represent the smallest important effect on performances (i.e., calculated as half of the within-athlete 437 race-to-race variability). National corresponds to competitions organized by the local Paralympic 438 Committee; IPC corresponds to international competitions organized by the International 439 Paralympic Committee; ParaPan corresponds to the ParaPan American Games. 440 441 Figure 2. Variation in squat jump (SJ) (Panel A) and relative mean propulsive power in jump squat 442 exercise (MPP REL JS) (Panel B) test results across the five periods. The black line represents the 443 mean individual performances, and the gray area represents the smallest important effect on 444 performances (i.e., calculated as half of the within-athlete test-to-test variability). 445 446 Figure 3. Linear regression between 100-m (panels A and C) and 200-m (panels B and D) dash 447 performances and the squat jump (SJ) height and relative mean propulsive power (MPP REL) in 448 the jump squat (JS) exercise. 449 450 Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis. 451 452 453 TABLE 1 454 455 Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis. 456 457

R2 Equation 100-m 0.66* y = 15.558 - (0.063 x SJ) - (0.061 x JS) 200-m 0.66* y = 32.918 - (0.167 x SJ) - (0.098 x JS)

458 Note: SJ = squat jump; JS = jump squat; P < 0.01. 459

In review

Loturco et al. Performance of Paralympic sprinters

FIGURE 3 | Linear regression between 100 (A,C) and 200-m (B,D) dash performances and the squat jump (SJ) height and relative mean propulsive

power (MPP REL) in the jump squat (JS) exercise; *P < 0.01.

regression models have increased only (on average) ∼1.2% ofthe explained variance between dependent (actual sprint times)and independent variables (SJ and JS), we considered relevantto carry out this calculation, since slight differences betweenindividuals in 100- and 200-m dash events might significantlyaffect their competitive results. Observing the data reported here,from this point on, Paralympic coaches can better estimate theactual performance of their top-level athletes in official sprintcompetitions. Furthermore, by understanding the importanceof this specific “mechanical combination” (i.e., SJ and JS) insprinting performance, they will be able to develop more effectiveand specific training programs.

Concerning the within-subject variability, the smallestworthwhile enhancements in the 100- (0.9%) and 200-m dash(1.43%) were comparable to those reported in Olympic andParalympic swimmers (Pyne et al., 2004). However, these valueswere higher than the estimates provided by elite track athleteswithout disabilities (Hopkins, 2005). The greater variabilityin athletes with visual impairment’s performances may beassociated with their disabilities (Fulton et al., 2009) and thepossible influence of their respective guides on the individuals’sprinting mechanics (unpublished data). Importantly, thesmallest worthwhile enhancement provides the coach with anidea of the meaningfulness of a given change in an athlete’sperformance. In general, an enhancement needs to be higherthan the smallest worthwhile enhancement to affect the results

TABLE 2 | Predictions of 100- and 200-m dash performances using

multiple regression analysis.

R2 Equation

100-m 0.66* y = 15.558 – (0.063 × SJ) – (0.061 × JS)

200-m 0.66* y = 32.918 – (0.167 × SJ) – (0.098 × JS)

SJ, squat jump; JS, jump squat; *P < 0.01.

(i.e., medal prospects; Fulton et al., 2009). Curiously, in the100-m dash, the athletes presented worse sprinting times thantheir mean times during the period of observation, but duringthe Parapan American Games they achieved their “performancepeak.” Although in the 200-m the times were close to the meanperformance throughout the observation, during the ParapanAmerican Games, they reached a meaningful performancechange (in comparison to the previous analyzed competitions).To some extent, this explains the outstanding results obtained bythe Brazilian team during the 2015 Pan American Games (threegold, six silver, and two bronze medals in the 100- and 200-mraces).

The jumping test results were substantially more variable thanthe actual competitive performances in the 100- and 200-m dash(CV of SJ = 5.58% and JS = 7.97%), which implies the needfor larger improvements in jumping tests, in order to considerthese enhancements as meaningful. The general dynamics of

Frontiers in Physiology | www.frontiersin.org 6 November 2015 | Volume 6 | Article 323

[email protected]

[email protected]


Relationship between aerobic and anaerobic parameters andfunctional classification in wheelchair basketball players

C. A. B. de Lira, R. L. Vancini, F. C. Minozzo, B. S. Sousa, J. P. Dubas, M. S. Andrade, L. L. Steinberg, A. C. da Silva

Department of Physiology, Universidade Federal de Sao Paulo (UNIFESP), Sao Paulo, BrazilCorresponding author: Claudio Andre Barbosa de Lira, Department of Physiology, Universidade Federal de Sao Paulo(UNIFESP), Rua Botucatu, 862, 51 andar, 04023-062, Sao Paulo, SP, Brazil. Tel: 155 11 5576 4513, Fax: 155 11 55710171, E-mail: [email protected]

Accepted for publication 15 January 2009

Participation in sports for individuals with disabilitiescontinues to gain popularity. In order to provide fair andequitable competition among persons with different disabil-ities and functional capacity, a separate functional classifi-cation system has been devised for each sport. The aims ofthe present study were to evaluate aerobic and anaerobicperformance of wheelchair basketball athletes and verify acorrelation with the International Wheelchair BasketballFederation functional classification system. For this, 17highly trained male Brazilian basketball wheelchair athletes(25.4! 4.4 years) from the national team who had takenpart in the Athens 2004 Paralympic Games were assessed.These athletes were submitted to cardiopulmonary exercise

testing and Wingate-like 30-s sprint test using upper limbs.The present study demonstrated that the functional classi-fication score correlated with relative (r5 0.90; Po0.0001)and absolute peak power (r5 0.50; P5 0.0353) and abso-lute mean power (r5 0.93; Po0.0001) obtained from theWingate-like 30-s sprint test and also correlated withabsolute

.VO2 peak (r5 0.68; P5 0.0026) and

.VO2 at

ventilatory threshold (r5 0.71; P5 0.0014), measured oncardiopulmonary exercise testing. Therefore, our findingssupport the functional classification created to classifyathletes’ functional capability on the court, which alsocorrelated with aerobic and anaerobic performance para-meters of the elite wheelchair basketball players.

Participation in regular physical activity is consid-ered to be an essential part of the rehabilitationprocess among individuals with chronic disabilities(Booth & Grogono, 1998; Bhambhani, 2002) andthere has been a tremendous growth in competitivesport for those with disabilities (Bhambhani, 2002).Thus, there is an increase in the number of publica-tions involving physical exercise and the disabled(Jacobs & Nash, 2004; De Groot et al., 2008; Wrightet al., 2008).In order to provide fair and equitable competition

among persons with different disabilities and diversefunctional potential, separate functional classifica-tion systems have been devised for each sport. Inwheelchair basketball, the functional classificationsystem is based mainly on the competence of theclassifier in recognizing a player’s physical ability inexecuting fundamental movements through field test-ing and game observation. These movements includetrunk stability, sitting balance and trunk movementin the horizontal, frontal and sagittal planes, such aspushing and handling the wheelchair, dribbling andpassing, shooting and rebounding the ball. Underthis system, players are assigned a score of 1.0(minimal functional potential) to 4.5 points (maximal

functional potential) on an ordinal scale according tothe extent of their physical ability, balance andmaneuverability in the wheelchair. In addition,half-point classes, i.e., 1.5, 2.5, 3.5 and 4.5, are usedif the player functionally blends characteristics, spe-cific criteria or the volume of action of two classes(Strohkendl, 1984, 1985).The International Wheelchair Basketball Federa-

tion (IWBF) applies the four-class Player Classifica-tion System for Wheelchair Basketball at allinternational events (IWBF, 2008): a team is allowedto field players at any time with a total of points notgreater than 14 (IWBF, 2008).The validity of the player classification system has

been examined on a national level through field-testanalysis (Hedrick & Brasile, 1996; Vanlandewijck,1997) and field performance analysis (Vanlandewijcket al., 1995; Molik & Kosmol, 2001). In 2004,Vanlandewijck et al. validated the classification sys-tem on an international level, studying the classdependency of field performance in elite male wheel-chair athletes. These authors demonstrated a clearrelationship between the functional classificationattributed to elite athletes and their sport-specificperformance. It was concluded that the Player Clas-

Scand J Med Sci Sports 2010: 20: 638–643& 2009 John Wiley & Sons A/Sdoi: 10.1111/j.1600-0838.2009.00934.x

638

The second visit to the laboratory was used to applyWingate-like 30-s sprint tests. This test was performed in acalibrated, electromagnetically braked arm crank ergometer(Cybex MET-300; Cybex, Ronkonkoma, New York, USA).During the 10-min warm-up period in which participantspracticed with the ergometer, they were asked to performthree all-out 5-s sprints on the command of the investigator.Following this warm-up period, participants rested quietly for5min. The athletes were then instructed to begin unloadedpedaling 10 s before beginning the test. Again, on the com-mand of the investigator, each participant was instructed toaccelerate maximally against no load. Then, isokinetic resis-tance was applied until the end of the 30-s period test. Verbalencouragement was provided throughout the period.

The following data (average of 5 s) were obtained: absolutepeak power (PPa) and relative peak power (PPr), the highestpower obtained during the test; absolute mean power (MPa) andrelative mean power (MPr), the average power obtained duringthe test; and fatigue index (FI). PPr and MPr were expressed inWatt/kg. The FI was calculated as the absolute differencebetween the highest and the lowest power output obtained inthe sprint test and was expressed as percentage.

Statistical analysis

Results are presented as mean ! standard deviation (SD).Distribution analysis was performed using the Kolmogorov–Smirnov test. Spearman’s correlation was used to establish therelationship between variables obtained from incrementalmaximal exercise test and Wingate-like 30-s sprint test. Statis-tical analysis was conducted using the GRAPH PAD PRISM SOFT-

WARE (GraphPad Software, San Diego, California, USA). Thelevel of significance for all statistical procedures was Po5%.

Results

Data for progressive exercise testing are shown inTable 2. Table 3 summarizes data concerning per-formance during the sprint test with upper limbs.

Table 4 summarizes the data concerning the relation-ship between cardiopulmonary exercise testing re-sults and functional classification in wheelchairbasketball players. Positive correlations were de-tected with

.VO2 (L/min) in VT and maximal exercise

and with VO2/HR in VT.Table 5 shows the data concerning the relationship

between Wingate-like 30-s sprint test, with upperlimb results, and functional classification in wheel-chair basketball players. Positive correlations weredetected with PPa (W), PPr (W/kg) and MPa (W).

Table 2. Metabolic parameters obtained in cardiopulmonary exercisetesting (n 5 17)

Variable Mean SD Range

At ventilatory threshold.VO2 (L/min) 1.35 0.31 0.78–1.96.VO2 (mL/kg/min) 20.9 4.1 14.9–31.0%

.VO2 peak 68.5 10.8 50.4–91.7

HR (bpm) 144.1 20.3 98–179% HRmax 77.7 9.3 61.7–93.2% predicted HRmax 74.3 10.3 50.5–92.3.VO2/HR (mL/beat) 8.8 2.0 5.7–13.7Velocity (km/h) 10.1 1.2 8–13

Maximal exercise.VO2 (L/min) 1.92 0.37 1.25–2.62.VO2 (mL/kg/min) 30.8 6.1 23.82–46.78HR (bpm) 185.5 12.7 148–203% predicted HRmax 95.6 6.2 76.3–103.1.VO2/HR (mL/beat) 10.8 2.1 6.7–15.4Velocity (km/h) 14.2 1.5 12–17.VCO2/

.VO2 1.38 0.12 1.11–1.54

SD, standard deviation;·VO2, oxygen uptake; HR, heart rate;

·VO2/HR,

oxygen pulse;·VCO2, carbon dioxide production;

·VCO2/

·VO2, respiratory

exchange ratio.

Table 3. Wingate-like 30-s sprint test indices of wheelchair basketballplayers (n 5 17)


PPa (W) 396.5 128.2 261–651PPr (W/kg) 6.3 1.4 3.5–6.8MPa (W) 304.4 94.3 161–487MPr (W/kg) 4.8 1.1 2.7–6.4FI (%) 50 11 30–75

SD, standard deviation; PPa, absolute peak power; PPr, relative peakpower; MPa, absolute mean power; MPr, relative mean power; FI, fatigueindex.

Table 4. Correlation coefficients between metabolic parameters obtainedin cardiopulmonary exercise testing and functional classification systemscore (n 5 17)

Variables Spearman’s r P

At ventilatory threshold.VO2 (L/min) 0.71* 0.0014.VO2 (mL/kg/min) 0.10 0.7050%

.VO2 peak 0.20 0.4455

HR (bpm) 0.32 0.2066% HRmax 0.29 0.2533.VO2/HR (mL/beat) 0.45 0.0673Velocity (km/h) " 0.11 0.6750

Maximal exercise.VO2 (L/min) 0.68* 0.0026.VO2 (mL/kg/min) " 0.02 0.9473HR (bpm) " 0.07 0.7836.VO2/HR (mL/beat) 0.63* 0.0068Velocity (km/h) " 0.14 0.5885

·VO2, oxygen uptake; HR, heart rate;

·VO2/HR, oxygen pulse.

*Significant correlation.

Table 5. Correlation coefficients between Wingate-like 30-s sprint testindices and functional classification system score (n 5 17)


PPa (W) 0.90* o0.0001PPr (W/kg) 0.50* 0.0353MPa (W) 0.93* o0.0001MPr (W/kg) 0.41 0.1065FI (%) 0.20 0.4360

PPa, absolute peak power; PPr, relative peak power; MPa, absolute meanpower; MPr, relative mean power; FI, fatigue index.*Significant correlation.

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The second visit to the laboratory was used to applyWingate-like 30-s sprint tests. This test was performed in acalibrated, electromagnetically braked arm crank ergometer(Cybex MET-300; Cybex, Ronkonkoma, New York, USA).During the 10-min warm-up period in which participantspracticed with the ergometer, they were asked to performthree all-out 5-s sprints on the command of the investigator.Following this warm-up period, participants rested quietly for5min. The athletes were then instructed to begin unloadedpedaling 10 s before beginning the test. Again, on the com-mand of the investigator, each participant was instructed toaccelerate maximally against no load. Then, isokinetic resis-tance was applied until the end of the 30-s period test. Verbalencouragement was provided throughout the period.

The following data (average of 5 s) were obtained: absolutepeak power (PPa) and relative peak power (PPr), the highestpower obtained during the test; absolute mean power (MPa) andrelative mean power (MPr), the average power obtained duringthe test; and fatigue index (FI). PPr and MPr were expressed inWatt/kg. The FI was calculated as the absolute differencebetween the highest and the lowest power output obtained inthe sprint test and was expressed as percentage.

Statistical analysis

Results are presented as mean ! standard deviation (SD).Distribution analysis was performed using the Kolmogorov–Smirnov test. Spearman’s correlation was used to establish therelationship between variables obtained from incrementalmaximal exercise test and Wingate-like 30-s sprint test. Statis-tical analysis was conducted using the GRAPH PAD PRISM SOFT-

WARE (GraphPad Software, San Diego, California, USA). Thelevel of significance for all statistical procedures was Po5%.

Results

Data for progressive exercise testing are shown inTable 2. Table 3 summarizes data concerning per-formance during the sprint test with upper limbs.

Table 4 summarizes the data concerning the relation-ship between cardiopulmonary exercise testing re-sults and functional classification in wheelchairbasketball players. Positive correlations were de-tected with

.VO2 (L/min) in VT and maximal exercise

and with VO2/HR in VT.Table 5 shows the data concerning the relationship

between Wingate-like 30-s sprint test, with upperlimb results, and functional classification in wheel-chair basketball players. Positive correlations weredetected with PPa (W), PPr (W/kg) and MPa (W).

Table 2. Metabolic parameters obtained in cardiopulmonary exercisetesting (n 5 17)


At ventilatory threshold.VO2 (L/min) 1.35 0.31 0.78–1.96.VO2 (mL/kg/min) 20.9 4.1 14.9–31.0%

.VO2 peak 68.5 10.8 50.4–91.7

HR (bpm) 144.1 20.3 98–179% HRmax 77.7 9.3 61.7–93.2% predicted HRmax 74.3 10.3 50.5–92.3.VO2/HR (mL/beat) 8.8 2.0 5.7–13.7Velocity (km/h) 10.1 1.2 8–13

Maximal exercise.VO2 (L/min) 1.92 0.37 1.25–2.62.VO2 (mL/kg/min) 30.8 6.1 23.82–46.78HR (bpm) 185.5 12.7 148–203% predicted HRmax 95.6 6.2 76.3–103.1.VO2/HR (mL/beat) 10.8 2.1 6.7–15.4Velocity (km/h) 14.2 1.5 12–17.VCO2/

.VO2 1.38 0.12 1.11–1.54

SD, standard deviation;·VO2, oxygen uptake; HR, heart rate;

·VO2/HR,

oxygen pulse;·VCO2, carbon dioxide production;

·VCO2/

·VO2, respiratory

exchange ratio.

Table 3. Wingate-like 30-s sprint test indices of wheelchair basketballplayers (n 5 17)


PPa (W) 396.5 128.2 261–651PPr (W/kg) 6.3 1.4 3.5–6.8MPa (W) 304.4 94.3 161–487MPr (W/kg) 4.8 1.1 2.7–6.4FI (%) 50 11 30–75

SD, standard deviation; PPa, absolute peak power; PPr, relative peakpower; MPa, absolute mean power; MPr, relative mean power; FI, fatigueindex.

Table 4. Correlation coefficients between metabolic parameters obtainedin cardiopulmonary exercise testing and functional classification systemscore (n 5 17)


At ventilatory threshold.VO2 (L/min) 0.71* 0.0014.VO2 (mL/kg/min) 0.10 0.7050%

.VO2 peak 0.20 0.4455

HR (bpm) 0.32 0.2066% HRmax 0.29 0.2533.VO2/HR (mL/beat) 0.45 0.0673Velocity (km/h) " 0.11 0.6750

Maximal exercise.VO2 (L/min) 0.68* 0.0026.VO2 (mL/kg/min) " 0.02 0.9473HR (bpm) " 0.07 0.7836.VO2/HR (mL/beat) 0.63* 0.0068Velocity (km/h) " 0.14 0.5885

·VO2, oxygen uptake; HR, heart rate;

·VO2/HR, oxygen pulse.

*Significant correlation.

Table 5. Correlation coefficients between Wingate-like 30-s sprint testindices and functional classification system score (n 5 17)


PPa (W) 0.90* o0.0001PPr (W/kg) 0.50* 0.0353MPa (W) 0.93* o0.0001MPr (W/kg) 0.41 0.1065FI (%) 0.20 0.4360

PPa, absolute peak power; PPr, relative peak power; MPa, absolute meanpower; MPr, relative mean power; FI, fatigue index.*Significant correlation.

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AtletasenSillasdeRuedas

Equipamiento

ClasseFuncional

NiveldelaLesion

Fuerzade

Tronco

ManejodelaSillas

Atletas conDiscapacidad

VIsual

Guia

FuncionalidadeProtocolo

deEvaluacion

Isokinetics and Speed

192,2

98,9

251,3*

130,0*142,7

90,4

181,6*

118,0*119,191,2

148,5*112,6*

RExtensor RFlexor RExtensor RFlexor

ATHLETES GUIDES

PeakTorque60°/s 180°/s 300°/s

6,097,99 8,54

6,398,93* 9,69*

02468

1012

10m 30m 50m

Speed

Distance

SPEEDVI G

AthleteswithVisualImpairment

R.Extensor60°/s

R.Extensor180°/s

R.Extensor300°/s

0-10m 0,423 0,386 0,374

10-30m 0,786* 0,752* 0,721*

30-50m 0,792* 0,776* 0,731*

BARROS, R.A. ; Winckler, C. ; LOTURCO, I. 2013.

Baixa Complexidade

Alta Complexidade

Acompañamiento de 1 ano Associason de Lesiones con déficits en la relación

agonista/antagonista H/Q (<60%)

Table 1. H/Q ratio values at the three assessments.

1st assessment 2nd assessment 3rd assessment Right Left Right Left Right Left

H/Q 60°/s 56.3±12.7 52.5±6.9 53.1±7.1 53.2±3.4 56.0±10.1 53.9±6.7

H/Q 180º/s 68.0±11.2 66.2±8.6 65.7±8.4 65.5±6.3 66.3±9.2 64.6±7.3

H/Q 300°/s 80.8±11.6 75.9±8.4 74.4±11.2* 73.8±6.6 76.7±9.9 74.0±6.6

* p=0.01: significant difference relative to the first assessment

7DEOH

Déficit contralateral de Fuerza isocinética y Salto-Unilateral

Muscular strength, functional performances and injury risk inprofessional and junior elite soccer players

C. Lehance1, J. Binet2, T. Bury1, J. L. Croisier2

1Department of Sports Physiology, University of Liege, Liege, Belgium, 2Department of Physical Medicine and Rehabilitation,University Hospital Centre, Liege, BelgiumCorresponding author: Cedric Lehance, Department of Sports Physiology, Faculty of Medicine, ISEPK, B21, Allee des Sports4, B-4000, University of Liege , Liege, Belgium. Tel: 0032-(0)43663886, Fax: 0032-(0)43662901, E-mail: [email protected]

Accepted for publication 10 January 2008

Muscle strength and anaerobic power of the lower extre-mities are neuromuscular variables that influence perfor-mance in many sports activities, including soccer. Despitefrequent contradictions in the literature, it may be assumedthat muscle strength and balance play a key role in targetedacute muscle injuries. The purpose of the present study wasto provide and compare pre-season muscular strength andpower profiles in professional and junior elite soccer playersthroughout the developmental years of 15–21. One originalaspect of our study was that isokinetic data were consideredalongside the past history of injury in these players. Fifty-seven elite and junior elite male soccer players were assignedto three groups: PRO, n5 19; U-21, n5 20 and U-17,n5 18. Players benefited from knee flexor and extensorisokinetic testing consisting of concentric and eccentricexercises. A context of lingering muscle disorder was definedusing statistically selected cut-offs. Functional performance

was evaluated throughout a squat jump and 10m sprint. ThePRO group ran faster and jumped higher than the U-17group (Po0.05). No significant difference in isokineticmuscle strength performance was observed between the threegroups when considering normalized body mass parameters.Individual isokinetic profiles enabled the identification of 32/57 (56%) subjects presenting lower limbmuscular imbalance.Thirty-six out of 57 players were identified as havingsustained a previous major lower limb injury. Of these 36players, 23 still showed significant muscular imbalance(64%). New trends in rational training could focus more onthe risk of imbalance and implement antagonist strengtheningaimed at injury prevention. Such an intervention wouldbenefit not only athletes recovering from injury, but alsouninjured players. An interdisciplinary approach involvingtrainers, a physical coach, and medical staff would be ofinterest to consider in implementing a prevention programme.

Soccer performance depends on a myriad of factorssuch as technical, tactical, mental and physiologicalfactors (Stolen et al., 2005). Muscle strength andanaerobic power of the lower extremities are neuro-muscular variables that influence performance inmany sports activities, including soccer (Paasukeet al., 2001). Although aerobic metabolism dominatesthe energy delivery during a soccer game, the mostdecisive actions are made by means of anaerobicmetabolism. To perform short sprints, jumps, tacklesand duel play, anaerobic energy release is determi-nant with regard to who is sprinting fastest orjumping highest. This is often crucial for the matchoutcome (Stolen et al., 2005). Anaerobic power is theproduct of strength and speed and refers to theability of the neuromuscular system to produce thegreatest possible impulse in a given time period(Wisloff et al., 2004). The idea of this maximalstrength/power performance relationship is sup-ported by jump test results as well as in 30m sprintresults (Schmidtbleicher, 1992; Wisloff et al., 2004).

By increasing the available force of muscular con-traction in appropriate muscles or muscle groups,acceleration and speed may improve in skills criticalto soccer such as turning, sprinting and changingpace (Bangsbo et al., 1991). Therefore, the accelera-tion phase and predominantly the initial accelerationphase (0–10m) are of major importance to athletes(Cometti et al., 2001). The contribution of strengthqualities to sprinting performance is not clear. Sev-eral studies have reported correlations betweenstrength measurement and anaerobic power perfor-mance (Mero et al., 1981; Mero, 1985; Young et al.,1995), while others have reported low and non-significant relationships (Farrar & Thorland, 1987;Cometti et al., 2001). Such a discrepancy may resultfrom variations in the sample studies with respect toage, gender and performance level. In addition, thespecificity of strength measurements to sprinting mayhave influenced the results.Muscular strength evaluation of the lower extre-

mities in athletes has been frequently performed

Scand J Med Sci Sports 2009: 19: 243–251& 2009 John Wiley & Sons A/SPrinted in Singapore . All rights reserved

DOI: 10.1111/j.1600-0838.2008.00780.x

243

Dados Preliminares

Injuries in VI athletics

were not recorded. Where athletes suffered a recurrent injury,the injury was counted only once.

Statistical analysis. Data were collated using MicrosoftExcel 2007! and analyzed using the SPSS 14.0!. Descriptivestatistics were calculated and used to determine the total andrelative frequency of injuries. The Shapiro–Wilk test wasused to determine the normality of data distribution. Wherethe normality of data distribution could be assumed, a one-way ANOVA test for independent groups was used to assessdifferences between visual classes and track and field events,and a t-test was used to compare between sexes. Alterna-tively, the Kruskal–Wallis test was used to assess differencesbetween sexes and visual classes. The acceptance level ofsignificance was set at P G 0.05.

RESULTS

Forty athletes participated in this study and 31 suffered atotal of 77 sports injuries (Table 1), which correspond to aprevalence of 78%, a clinical incidence of 1.93 injuries perparticipating athlete (Table 1), and an average incidence rateof 0.39 injuries per athlete per competition.

Female athletes presented a slightly higher prevalenceand clinical incidence when compared to male athletes(Table 1), but this was not statistically significant (P 9 0.05).With regard to visual class, T/F11 athletes presented a

slightly higher prevalence of sports injuries, followed byT/F12 and T/F13 athletes. However, T/F12 athletes showedslightly higher clinical incidence, followed by T/F11 andT/F13 (Table 1). There were no statistically significant dif-ferences observed between classifications or groups in theseepidemiological data (P 9 0.05). When comparing the epi-demiological data between event types such as track (sprint,medium, and long distance) and field (throws and jumps), nostatistically significant differences were observed.

TABLE 1. Number of participant athletes, injured athletes, sports injuries, prevalence, and clinical incidence according to visual class, event type, and sex.

Visual Class Event Type Sex

Competitions T/F11 T/F12 T/F13 Track Field Female Male Total

ParticipantsParalympic Games 2004 4 5 2 11 — 5 6 11IBSA Para Pan-American Games 2005 8 12 8 25 3 7 21 28IBSA World Championship 2007 9 12 7 25 3 8 20 28Para Pan-American Games 2007 7 8 4 19 — 6 13 19Paralympic Games 2008 8 10 4 22 — 8 14 22Total 14 15 11 35 5 12 28 40

Injured athletesParalympic Games 2004 3 5 1 8 — 4 5 9IBSA Para Pan-American Games 2005 3 7 3 12 1 4 9 13IBSA World Championship 2007 6 7 4 14 3 6 11 17Para Pan-American Games 2007 2 4 3 9 — 4 5 9Paralympic Games 2008 2 6 1 8 — 3 5 8Total 12 12 7 27 3 11 20 31

No. sports injuriesParalympic Games 2004 3 7 1 11 — 5 6 11IBSA Para Pan-American Games 2005 5 8 3 15 1 4 12 16IBSA World Championship 2007 7 14 7 22 6 8 20 28Para Pan-American Games 2007 3 4 4 11 — 6 5 11Paralympic Games 2008 3 6 2 11 — 3 8 11Total 21 39 17 70 7 27 50 77

Prevalence (%)Paralympic Games 2004 75 100 50 73 — 80 83 82IBSA Para Pan-American Games 2005 38 58 38 48 33 57 43 46IBSA World Championship 2007 67 58 57 56 100 75 55 61Para Pan-American Games 2007 29 50 75 47 — 67 38 47Paralympic Games 2008 25 60 25 36 — 38 36 36Total 86 80 64 77 60 92 71 78

Clinical incidenceParalympic Games 2004 0.8 1.4 0.5 1.00 — 1.0 1.0 1.0IBSA Para Pan-American Games 2005 0.6 0.7 0.4 0.60 0.33 0.6 0.6 0.6IBSA World Championship 2007 0.8 1.2 1.0 0.88 2.00 1.0 1.0 1.0Para Pan-American Games 2007 0.4 0.5 1.0 0.58 — 1.0 0.4 0.6Paralympic Games 2008 0.4 0.6 0.5 0.50 — 0.4 0.6 0.5Total 1.5 2.6 1.5 2.00 1.40 2.3 1.8 1.9

FIGURE 1—Mechanism of sport injury in track and field paralympiccompetitions.

http://www.acsm-msse.org910 Official Journal of the American College of Sports Medicine

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Copyright © 2013 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.With respect to injury mechanisms (Fig. 1), overuse in-

juries were the most prevalent (82%), and traumatic injuriesconstituted the remaining smaller proportion (P G 0.05).

Figure 2 represents the distribution of sport injuries bybody segment, where the lower limbs appeared to be mostaffected.

The frequency of injuries by body region (Fig. 3) revealedthat the thighs were most affected.

The frequency of sport injuries varied by diagnosis (Fig. 4),with the greatest frequencies reported as tendinopathy andspasm.

DISCUSSION

The results of this study demonstrate that the overall clin-ical incidence was 1.93 injuries per injured Paralympic athleteduring the period of observation, indicating that many athletessustained multiple injuries (21). Paralympic track and fieldis considered a low risk sport when compared to other Para-lympic sports modalities (10). In terms of sports injuryprevalence, we demonstrated an overall value of 78%, vary-ing from 82% to 36% across the five competitions observed

(Table 1). A previous study in track and field athletes withoutdisability observed an injury prevalence of 42.8% (17).

When comparing sports injuries by sex, female athletespresented a slightly higher prevalence (92% vs 71%) andclinical incidence (2.3 vs 1.8 injuries per athlete) of injury(Table 1) compared to males. This trend suggests that ahigher proportion of female athletes were injured and thosethat were sustained more injuries per athlete compared tomales. While these observations were not significantly dif-ferent, this may be a function of the relatively small samplesize stemming from a single nation team. There seems to bevery little difference in the pattern of injuries between menand women when comparing the same sports among able-bodied athletes (30). A review article suggests that the risk ofsports injuries is lower in female than in male athletes withoutdisability (20). Clearly, further studies should be encouragedto evaluate the risk of injury by sex in Paralympic sports. Toaddress this question fully, greater statistical power is re-quired, which may ultimately require the collection and col-lation of data, using common injury reporting methods acrossmultiple nations.

With regard to visual class, T/F11 athletes presented a higherPrevalence of injury, but B2 athletes a higher clinical incidence;this means that a larger percentage of T/F11 athletes was in-jured, but B2 athletes sustained more injuries, but no statisticalsignificance was revealed. In addition, another study with 131visually impaired athletes affirms that the prevalence of injury isgreatest among athletes with the greatest visual impairment(24). This can be related to the fact that postural stability isaffected by vision (2), and proprioception in blind individualstends to be worse than in those with partial vision resulting inabnormal gait and biomechanics, which can lead to injuries(34). These findings suggest that the implementation of pro-prioception training, as a preventive measure, may be useful toreduce the prevalence and clinical incidence of sports injuriesin athletes with visual impairment.

Overuse injuries were most frequently observed in thispopulation. This mechanism of injury is not atypical in sport

FIGURE 2—Distribution of sport injury by body segment in track andfield paralympic competitions.

FIGURE 3—Distribution of sport injury by body part in track and field paralympic competitions.

INJURIES IN VISUALLY IMPAIRED ATHLETES Medicine & Science in Sports & Exercised 911

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Sports Injuries in Paralympic Track and FieldAthletes with Visual Impairment

MARILIA PASSOS MAGNO E SILVA1, CIRO WINCKLER2, ANSELMO ATHAYDE COSTA E SILVA1,JAMES BILZON3, and EDISON DUARTE1

1Department for Adapted Physical Education, University of Campinas, BRAZIL; 2Department for Movement Science,Federal University of Sao Paulo, BRAZIL; and 3Department for Health, University of Bath, UNITED KINGDOM

ABSTRACT

MAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track

and Field Athletes with Visual Impairment.Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013. Purpose: The aims of this study

were to determine the epidemiology, nature, and pattern of sports injuries in Brazilian Paralympic track and field athletes with visual

impairment and to assess differences between visual classes and sex. Methods: Forty visually impaired elite Paralympic athletes par-

ticipated in this study (28 males and 12 females). All athletes competed in International Paralympic competitions between 2004 and

2008. According to the visual classification, 14 athletes were T/F11, 15 were T/F12, and 11 were T/F13. A standardized report form was

used to collect injury data during five competitions. Results: Thirty-one athletes reported 77 sports injuries, with a prevalence of 78%, a

clinical incidence of 1.93 injuries per athlete, and an incidence rate of 0.39 injuries per athlete per competition. Overuse injuries

accounted for 82% and traumatic injuries 18% (P G 0.05). Small variations in the prevalence and clinical incidence of injury between

sexes and visual classes were observed, but these were not statistically different (P 9 0.05). The highest distribution of injury was in

the lower limbs (87%), followed by spine (12%) and upper limbs (1%). The body regions most affected were the thighs (33.8%),

lower legs (16.9%), and knees (9.1%). The most frequent diagnoses were spasms (26%), tendinopathies (23.4%), and strains (13%).

Conclusions: Elite visually impaired track and field Paralympic athletes present a pattern of overuse injuries predominantly affect-

ing the lower limbs, particularly the thighs, lower legs, and knees. These injuries are associated with tendinopathies, muscle spasms,

and strains. There were no apparent differences in injury characteristics between visual classes or sex. Key Words: ATHLETICS,DISABILITY SPORT, INJURY EPIDEMIOLOGY, PARALYMPICS

Athletics was one of only eight sports included in thefirst Paralympic Games, held in Rome, in 1960. Inthis first Paralympiad, only throwing and pentathlon

events were performed. In the modern Paralympic Games,track and field athletics is the sport with the largest numberof participating athletes, competing in eight track events(100, 200, 400, 800, 1500, 5000, and 10,000 m and mara-thon), six field events (long jump, high jump, triple jump,javelin, discus, and shot put), and one combined event(pentathlon). They compete in male and female categoriesand are classified in 1 of the 26 sport classes, according totheir disability type and motor function (motor, physical,visual, and intellectual). Athletes who participate in trackevents use the letter T before the class number to indicate theevent type, whereas those participating in field events use

the letter F (18). This short introduction serves to highlightthe complexity and variety of Paralympic athletic events,which is also reflected in the development and understand-ing of research in the discipline.

To compete, visually impaired athletes must be submittedto a visual classification, where an ophthalmologist evalu-ates acuity and visual field. Athletes can be categorized inone of three levels: B1 are considered blind athletes (fromno light perception in either eye, up to light perception butunable to recognize the shape of a hand at any distance ordirection), B2 are considered to have severely impaired vi-sion (from ability to recognize the shape of a hand, up to avisual acuity of 20/600 or a visual field of less than 5- in thebest eye with the best practical eye correction), and B3 areconsidered to have moderate to poor vision (visual acuityabove 20/600 to 20/200, or a visual field of less than 20-and more than 5- in the best eye with the best correction)(22). In track and field athletics, these classifications aregiven sport-specific nomenclature as follows: T/F11, T/F12,and T/F13, respectively. The Track and Field ParalympicRules determine that acoustic assistance and a guide arepermitted for the classes T/F11 and T/F12. Athletes T/F11should wear opaque glasses to match the capacity of lightperception between the competitors. The T/F13 athletesfollow the same rules as the regular athletics (18).

Address for correspondence: James Bilzon, Ph.D., Department for Health, Uni-versity of Bath, Bath BA2 7AY, United Kingdom; E-mail: [email protected] for publication June 2012.Accepted for publication November 2012.

0195-9131/13/4505-0908/0MEDICINE & SCIENCE IN SPORTS & EXERCISE!Copyright " 2013 by the American College of Sports Medicine

DOI: 10.1249/MSS.0b013e31827f06f3

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Copyright © 2013 by the American College of Sports Medicine. Unauthorized reproduction of this article is prohibited.

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ReferênciasBARROS, R.A. ; Winckler, C. ; LOTURCO, I. . Analysis of Relationship between Strength and Speed in Athletes with Visual Impairment and Guides Participants of Athletics Brazil Paralympic Team. In: VISTA 2013 'Equipment and Technology in Paralympic Sports', 2013, Bonn. VISTA2013 Scientific Conference Booklet. Bonn, 2013. v. 1. p. 81-83.Nakamura, F. Y., Moreira, A., & Aoki, M. S. (2010). Monitoramento da Carga de Treinamento: A Percepção Subjetiva do Esporfço da Sessão é um Método Confiável ? R Da Educação Física, 21(1), 1–11. http://doi.org/10.4025/reveducfis.v21i1.6713

Silva A, Zanca G, Alves ES, de Aquino Lemos V, Ga´vea SA, Winckler C, Mattiello SM, Peterson R, Vital R, Tufik S, D. M. M. (2015). Isokinetic Assessment and Musculoskeletal Complaints in Paralympic Athletes: A Longitudinal Study. Am J Phys Med Rehabil, 1–7. http://doi.org/10.1097/PHM.0000000000000244

Turner, A. (2011). The Science and Practice of Periodization: A Brief Review. Strength and Conditioning Journal, 33(1), 34–46. http://doi.org/10.1519/SSC.0b013e3182079cdfMAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track and Field Athletes with Visual Impairment. Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013.

http://doi.org/10.4025/reveducfis.v21i1.6713

http://doi.org/10.1097/PHM.0000000000000244

http://doi.org/10.1097/PHM.0000000000000244

http://doi.org/10.1519/SSC.0b013e3182079cdf

[email protected]

[email protected]
