Allometry of Anaerobic Performance: A Gender Comparison

Allometry of Anaerobic Performance: A Gender Comparison

Alan M. Batterham and Karen M. Birch

Catalogue Data Batterham, A.M., and Birch, K.M. (1996). Allometry of anaerobic performance: A gender comparison. Can. J. Appl. Physiol. 21(1): 48-62. O 1996 Canadian Society for Exercise Physiology.

Key words: al1omet1-ic scaling, sex different-es, peak powler- output, unthr-oponletr-y. Mots-clks: Pchelle allomPtrique, diffPrenc.es sexuelles, puissant-e de cr4te produite, unthro- pomktrie

Physiological variables must often be scsuled for body size differences to permit meaningful c.omparisons between groups. Using multivariate ullometric~ sc-aling (MAS), this study aimed to compare the anaerobic. peijormance ( f adult mules and females in 12 pair-s matched for physical activity status. Peak power- output (PPO) ulas assessed viu a 30-s suprama.uima1 cyc-le ergometer test. Fat-fr-ee mass (FFM) and thigh mu.sc*le and b o n ~ cross-sec.tiona1 area (CSA) were determined anthropometric*ally and served as indicator-s ofac-tive musculature. The MAS revealed power. func-tions of the for-m PPO = a . xencier'

FFMb (or CSAb). Common b exponents of 0.1 were identified for- both FFM and CSA (negative allometry). Sex differences were found in absolute PPO ( I ,252 11s. hHl W , p < .05). Comparison of scaled PPO data via ANCOVA (FFMO.' and CSAO' entered as c*o\'ari- ates) did not eliminate the sex difference (adjusted means 1,243 vs. 690 W , p < .05). The results suggest that the superior anaerobic performance cf males in this sample is independent of size of the involved musculature.

Pour une meilleure comparaison entre di~vers groupes, les variahles physiologiques doi~lent souvent 6tre ajustkes aux diffkrences de gabarit. Le but de cette Ptude est de c-omparer, au moyen d'une kchelle allomktrique multivarike (MAS), la performance anakr-obie [ / 'a- dultes (12 hommes et I2 femmes) appariks selon leur condition physique. La puissanc.e

A.M. Batterham and K.M. Birch: Division of Sport Science, the Manchester Metro- politan University, Crewe and Alsager Faculty, Hassall Road, Alsager, Stoke-on-Trent, ST7 2HL, England.

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Anaerobic Performance 49

de crPte (PPO) est hvuluhe au moyen d'une hpr-eve suprumaximale de 30 s sur- c)r~oc.yc.le. Deux indicuter-us de Iu musse musculuir-e active, la masse m u i ~ r e (FFM) et Iu sur:fuc.e de coupe de la cuisse, muscle et os inc-(us (CSA), sont hvuluhs uu moyen d'une mPthode anthr-opomhtr-iyue. Le MAS r-P\@le I'Pyuution allomhtr-iyue suivante: PPO = a . se.xeC . FFMb (ou CSAb). L'e.~posant de FFM et (le CSA est de 0 , l (u1lotnc;tr-ie rlh,quti\~e). La diff2renc.e de PPO ahsolue (1252 \IS. 681 W ) entr-e les deux ,qr-oupes est .si,qnlficuti\ve ( p < ,051. La compc~ruison des lluleur-s de PPO ajusthes au.1 difle'r-c.nc.c>s de ,quhur.it pur- une ANCOVA (c*ovar-iahles: FFM" ' et C,YAO') n'enleve pas le diflPr.erlc*es entr-e les de1l.u sexes (moyennes ajusthes: 1243 vs. 690 W , p < ,05). Les rhsultuts luissent c.roi1.e yue la meilleur-e pet-for-mancte anahr.ohie donnhe par les hommes est indhpendante de I'inrpol-tunc.e de la musse musc.ulair-e sollic.ithe.

Introduction

The past two decades have seen a dramatic increase in the involvement of women in high-intensity sport, exercise, and vocational activities. Such trends have raised important research questions regarding the nature of observed male-female differences in performance. It is well documented that, in absolute terms, men exhibit significantly greater anaerobic performance capability than women (Wells and Plowman, 1983). However, findings are equivocal when data are expressed relative to body size, composition, or size of involved musculature. Using anaerobic performance indices derived from supramaximal cycle ergometer tests, several authors have reported that significant sex differences remained even after normali- sation for body dimensions (Froese and Houston, 1987; Serresse et al., 1989; Winter et al., 1991). Such findings suggest that there may be true physiological or biochemical differences between male and female muscle tissue. In addition, sex or gender differences in myoneural factors should not be discounted, espe- cially activation of high-threshold motor units (Milner-Brown et al., 1973) and electromechanical delay and rate of force development (Bell and Jacobs, 1986). In contrast, other studies have demonstrated that sex differences in anaerobic performance are eliminated when data is scaled to remove the influence of body size and composition (Gleim et al., 1984; Maud and Schultz, 1986).

In England, the Allied Dunbar National Fitness Survey ( 1992) investigated the physical activity status of a sample of 6,000 adults. All types of physical activity were recorded, with the frequency and intensity of 20-min sessions in the previous 4 weeks documented via personal interviews. Males were found to be significantly more active than females, with 14% reporting an average of three or more 20-min sessions per week at a "vigorous" (7.5 kcal . min-') intensity, compared to only 4% of females. More frequent and intense levels of physical activity may positively influence the determinants of anaerobic performance. Bouchard et al. (1 99 1 ) reported that exercise training can lead to enhanced activities of muscle phosphofructokinase, phosphorylase, and Mg" stimulated adenosinetriphosphatase (ATPase), increased maximal muscle lactate and muscle buffer capacity, and increases in creatine phosphate and adenosine triphosphate (ATP) stores. Myoneural adaptation further to strength or power training is also well documented, resulting in increased activation and recruitment of motor units (Sale, 1992). Therefore, a potentially confounding factor in gender comparisons of physiological response is the failure to adequately quantify the training status and physical activity history of the test subjects. Without rigorously matching

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50 Batterham and Birch

male and female samples for habitual physical activity, it is impossible to separate true biological sex differences in anaerobic performance from those due to sociali- sation, environmental and cultural influences, and selection bias in group sampling.

The controversy in the extant literature may also result, in part, from the use of diverse statistical approaches to scaling or normalising the data. The most commonly adopted method has been the use of ratio scaling (RS), involving the division of the absolute performance variable by a body size variable to construct an index. This index is allegedly size-independent, thus permitting meaningful intergroup or intersubject comparisons. The theoretical and mathematical flaws in RS were recognised over 40 years ago (Tanner, 1949). In short, RS assumes a proportional, linear relationship between the physiological and body size variables with the line of identity passing through the origin. Violation of these assumptions may lead to erroneous conclusions in research employing RS. It has been shown that when simple ratio standards such as anaerobic power (W . kg-') are correlated with body mass (BM) (kilograms), a neguti\le relationship results (Nevill et al., 1992). This reveals that RS does not produce a size-independent index, but overcorrects the absolute data for the influence of body dimensions. In such cases, comparisons via RS would penalise larger, heavier sub-jects.

An extension of RS involves the use of regression standards of the general form y = a + h . x, where y is the physiological variable of interest, u is the y- intercept, h represents the gradient of the trend line, and s is the body size variable. Unfortunately, although often providing a better fit to the data with less residual error, positive intercepts are common, indicating that someone of zero body mass would exhibit a physiological response (Armstrong and Welsman, 1 994).

Research in comparative physiology (Schmidt-Nielsen, 1984) has revealed that a multitude of physiological variables relate to body size according to an allometric or power function relationship of the general form y = u . A', where y is the physiological dependent variable, u is the proportionality coefficient, .u is the body dimension variable, and h is the exponent. Nevill et a!. (1992) reported mass exponents (h) for anaerobic performance indices of 0.68, which is significantly less than the power of 1 that RS supporters would advocate. In this instance, the physiological variable increases with increments in body mass, but by less than the simple RS approach would predict. Use of the ratio index for these anaerobic variables would thus over-scale the data, disadvantaging heavier subjects in comparisons. Allometric models are generally more successful in providing a dimensionless physiological index, with correlations between the scaled physiological variable (ylxb) and the body size variable (1) not significantly different from zero (Nevill et al., 1992).

To our knowledge, no study to date has assessed male and female anaerobic performance using objective matching for physical activity status, together with allometric scaling (AS) to remove the influence of disparate body'dimensions. The purpose of the present study therefore, was to compare (using AS) lower body anaerobic performance in an all-out 30-s cycle ergometer test, in male and female samples matched via a validated leisure-time physical activity questionnaire. Ratio-adjusted anaerobic performance data is also presented for comparing scaling techniques.

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Anaerobic Performance 5 1

Methods

SUBJECTS AND DESIGN

Written informed consent was obtained from all subjects in accordance with the guidelines of the bioethics committee of the institution. Initially, 40 male and 40 female undergraduate students, ages 18-24 years, were surveyed using the Baecke short questionnaire for the measurement of physical activity (Baecke et al., 1982). This self-report instrument provides activity indices for "work," "leisure," and "sport" using a recall period of one year (usual activity). The questionnaire was originally validated on 20- to 32-year-old males and females, with 3-month test-retest reliability coefficients ranging from 0.74-0.88. From the obtained data, it was possible to closely match 12 pairs of males and females (30% of sample), such that group means for physical activity indices were not different (p > .05). Descriptive characteristics of the subjects are shown in Table 1.

ANTHROPOMETRY

Percent body fat was estimated using the sum of bicep, tricep, subscapular, and suprailiac skinfolds (Durnin and Womersley, 1974). The mean skinfold of three rotations that agreed within 10% was used for subsequent analyses. Total body mass (BM f 0.1 kg) and fat percent were used to partition BM into its fat mass and fat-free mass (FFM) components. Midthigh circumference was measured with a nonstretch metal tape halfway between the inguinal crease and the proximal border of the patella. This girth was corrected for subcutaneous adipose tissue by means of anterior, posterior, medial, and lateral skinfolds taken with Harpenden calipers at the same anatomical level as the circumference measure. Tissue boundaries were assumed to be circular and concentric. Four skinfolds were used in an attempt to adjust to some extent for uneven distribution of subcutaneous fat. Thigh muscle and bone cross-sectional area (CSA) was then estimated according to the formula of Moritani and DeVries (1979): CSA = n (C/2n - CSKFI 4)', where CSA = muscle and bone cross-sectional area in cm', C = thigh girth in cm, and CSKF = sum of four thigh skinfolds in cm.

Thigh muscle and bone CSA derived via anthropometry has been found to correlate well with criterion nuclear magnetic resonance (NMR) imaging

Table 1 Physical Characteristics of Male and Female Subjects

Males (n = 12) M SD

Females ( n = 12) M SD

Body mass (kg) Fat-free mass (kg) Thigh CSA (cm')

Note. CSA = muscle and bone cross-sectional area. "Male values greater than female values, p < .05.

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techniques (Narici and Roi, 1992). However, random errors in thigh circumference measures or in skinfold measuring technique may reduce accuracy. Therefore, an evaluation of technical error of measurement (TEM) and reliability (R) is essential (Ulijaszek and Lourie, 1994). For the midthigh girth, TEM was 0.3 cm with an R of .97. Mean TEM for the thigh skinfolds was 1.2 mm, with a reliability coefficient of .94. These errors are comparable to reference values (Malina, 1995), and indicate that 88-94% of the between-subject variance was free from random measurement error.

ALL-OUT SUPRAMAXIMAL CYCLE ERGOMETER TEST

A Monark 864 friction-braked, drop loaded, basket ergometer was used to assess peak power output (PPO) in a 30-s test. The traditional calculation of PPO, the simple product of applied load and flywheel velocity, ignores the work done in transferring kinetic energy to, and thus accelerating, the flywheel. Lakomy (1 994) recommended that this work be calculated and credited to the subject. The specific procedures adopted in the current study to assess this "corrected" PPO are detailed in another source (Lakomy, 1986). A rolling start at 60 RPM was employed, against a resistive load of 0. I kg - kg-' BM for males and 0.08 kg . kg-' BM for females. Corrected PPO was calculated for each one-second interval of the test. The PPO values derived from this method are on average 30-35% higher than uncorrected values, with PPO attained within the first 2-3 s of the test (Lakomy, 1986). This accounts for the seemingly high PPO values in the current study compared to those cited in the extant literature.

Subjects were required to remain in contact with the saddle and to grip the handlebars throughout the test. As body configuration was similar for all subjects, possible contribution of the upper body musculature to lower body external power output within the person*rgometer system was controlled. The test was repeated on a second occasion separated by 7 days. Bland-Altman plots (Bland and Altman, 1986) at 95% confidence agreement limits revealed a coefficient of repeatability of 70 W. This compares well to the cited errors for supramaximal ergometer tests of +5% (Lakomy, 1994).

ALLOMETRY

In order to properly scale anaerobic performance data, fat free mass (FFM), and thigh CSA were selected as variables representative of active musculature. Body mass was excluded as a body size variable because it has been demonstrated that large group differences in body fat percentage may confound power function analyses (Vandenburgh et al., 1995). Clearly, excess fat mass would increase BM, but would not greatly influence peak power output in leg ergometry.

Technically, power function equations of the form PPO = u . FFMh, and PPO = u . CSAh should be computed for males and females separately to examine the proper gender-specific relationships between PPO and body size. However, if significant gender differences are found in the h exponents, intergender comparison is problematic, as the units of the scaled variable would not be equivalent. Moreover, it is likely that the combined frequency distribution of absolute PPO for males and females is bimodal. In this case, linear regression analysis is inappropriate unless "group" is entered as a separate independent variable. The

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solution involves the derivation of a common "best compromise" h exponent via multivariate allometric scaling (MAS), entering gender as a predictor variable alongside FFM or CSA (males coded as 0, females as I): PPO = u . gender' . FFMb (or CSAb). Using the common h exponent generated to scale the absolute PPO data (PPO/FFMb or PPO/CSAb) allegedly removes the influence of body dimension, permitting meaningful comparisons between genders. Best compromise FFM and CSA h exponents derived using MAS, were computed by means of a spreadsheet specially written on Microsoft Excel 5.0, providing 95%) confidence limits.

STATISTICAL ANALYSIS

Male-female comparisons of PPO were computed via analysis of covariance (SPSS 6.0 for Windows) with FFMb and CSAb entered as covariates (using the best compromise h exponents). Strong linear relationships between the covariates and the dependent variable (PPO) were confirmed (rZ = .64-39). These correlations were not different between groups O, > .05). Gender comparison of absolute and ratio-adjusted data (PPO/FFM and PPO/CSA) was conducted via paired t

test. The alpha level adopted for statistical significance was p < .05.

Results

The descriptive data for BM, FFM, and thigh CSA are presented in Table I . On average, males were 16.3 kg heavier, with 20.7 kg greater FFM, and 63 cm' (55%) greater thigh CSA, than females.

ALLOMETRY AND RATIO SCALING

The results of the multivariate allometric scaling (MAS) are presented separately for FFM and thigh CSA. Correlations between the scaled physiological variable (PPO by FFM or PPO by CSA) and the relevant body size variable (FFM or CSA) are also provided for males and females, for both allometric and ratio- adjusted data. If the scaled variable is to be independent of body size, correlations should not be significantly different from zero. Therefore, if the allometric models provide correlations closer to zero than does the ratio approach, this result represents superior scaling of the data.

PEAK POWER OUTPUT BY FAT-FREE MASS

Figures 1 and 2 illus'trate the simple, linear correlations between FFM and PPO, for males and females. Relationships were not significant for either gender (p > .05). The small variances for FFM and PPO within each group (Tables 1 and 2) demonstrate that male and female samples were essentially homogeneous. Pooling the data increases the sample size, heterogeneity, and the strength of the relationship (r' = .68; Figure 3). However, the men and women were clearly from two separate populations. Gender must therefore be entered as a separate independent variable in a multivariate allometric model. The MAS revealed the following relationships: PPO = 8 10 . gender-056 F 0 2 5 . FFMO ' ' 0 4 ( r = .86, r' = .74).

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800 I

59 61 63 65 67 69 71 73

Fat Free Mass (kg)

Figure 1. Relationship between fat-free mass and lower body peak power output in males ( n = 12).

Fat Free Mass (kg)

Figure 2. Relationship between fat-free mass and lower body peak power output in females (n = 12).

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Table 2 Lower Body Peak Power Output (PPO) for Men and Women

Males ( n = 12) Females ( 17 = 12) M SD M sn

Absolute PPO (W) 1,252 270 68 1 96" PPO/FFM (W . kg-') 18.7 4.2 14.7 2.2" PPOICSA (W . cm-') 7.1 2.0 6.0 1.1-F Adjusted means via ANCOVA (W) 1,243 690"

- -

Note. FFM = fat-free mass; CSA = muscle and bone cross-sectional area. Adjusted means derived from ANCOVA with FFM" ' and CSA" ' as covariates. "Male PPO greater than female, p < .05. +No difference between male and female value, p > .05.

Fat Free Mass (kg) - -

Figure 3. Power function relationship between fat-free mass and lower body peak power output for pooled data set (N = 24). Peak power output was proportional to fat- free mass to the raised power of 1.5.

The negative exponent isolated for gender indicates the anticipated relationship: As gender tends toward zero (males), PPO increases. The gender-independent h exponent for FFM of 0.1 provides the best compromise allometric solution for intersubject and intergroup comparisons of PPO nonnalised for FFM differences. The correlation checks between allometrically scaled PPO and FFM ~lithin each gender are presented below:

Male: r FFM, PPO/FFMO.' = .05 Female: r FFM, PPO/FFMO.' = -.01

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The above correlations are not different from zero ( p > .05), indicating that the expression of PPO/FFMo.' did not penalise males or females based on FFM. Figures 4 and 5 illustrate that normalised PPO essentially remains constant as FFM increases within group, revealing that the scaled variable is size independent, thus permitting meaningful comparisons. In contrast, the correlation checks for ratio-adjusted PPO (by FFM) demonstrated that the ratio index failed to correctly remove the influence of FFM in either group. Correlations between FFM and PPO/FFM were negative (-.22 and -.37 for males and females, respectively). Ratio scaling appears to overcorrect the absolute data and, thus, effects a penalty on larger subjects with greater FFM.

PEAK POWER OUTPUT BY THIGH CSA

The MAS for PPO by gender and CSA revealed the following relationships: PPO = 706 gender4," "' ' . CSAO ' ' 0 2 (r = 37, r2 = .76). The size-independent negative gender exponent again suggests that males produce greater PPO than females. The correlation checks revealed that the expression of PPO/CSA0 ' did not penalise males or females, with relationships between CSA and the power function ratio not significantly different from zero 0, > .05). For ratio-adjusted data however, strong negative correlations were found between CSA and PPO/ CSA (-.65 and -.69 for males and females, respectively). Clearly, the ratio standard PPOICSA overscales the absolute data and, thus, penalises larger subjects in this sample.

GENDER COMPARISONS OF PPO

The results presented in Table 2 reveal significant gender differences for absolute PPO, and the ratio standard PPO/FFM. No significant gender difference was found

63 68 Fat Free Mass (kg)

Figure 4. Relationship between allometrically scaled peak power output (PPO . FFM-" ') and fat-free mass in males.

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Fat Free Mass (kg)

Figure 5. Relationship between allometrically scaled peak power output (PPO FFM-"I) and fat-free mass in females.

for PPO expressed per unit thigh CSA. However, as it has been demonstrated that the ratio index PPOICSA overscales the absolute data, this method of gender comparison is deeply problematic. The overcorrection for CSA would penalise the larger (generally male) subjects, possibly leading to a Type I1 error and spurious conclusions. The moderate to large effect size for PPOICSA of 0.71 [(male mean - female mean)/pooled standard deviation] further supports this contention, suggesting a meaningful gender difference. In contrast to the ratio scaling by CSA, the ANCOVA with FFMO' and CSA"' entered as covariates revealed significant gender differerices 0, < .05) in PPO, independent of body dimension.

Discussion

RELATIONSHIPS BETWEEN BODY DIMENSIONS AND PPO

The findings demonstrated that allometric scaling (AS) was superior to the ratio scaling (RS) approach in partitioning out the influence of body dimensions. For AS (Figures 4 and 5), correlations between scaled PPO (PPOlxb) and the relevant body size variable (x) were not significant 0, > .05). The equivalent correlation checks for RS ( I - between x and PPOIx) revealed that this approach allel-.scaleti the absolute PPO data, thus penalising heavier subjects in intersubject or intergroup comparisons. Clearly, the adoption of RS for the data gathered in the current study, may have led to spurious conclusions.

Multivariate allometric scaling (MAS) enabled identification of gender independent power function ratios (PPOIxb). The proper value of h was found to be 0.1 for both FFM and thigh cross-sectional area (CSA). It is of theoretical

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and practical interest to compare this exponent with those predicted from the theory of dimensionality (Schmidt-Nielsen, 1984). This theory assumes that growth is isometric; that is, geometric similarity is maintained with increases in body dimensions. The criteria for testing isometry in the relationship y = u . ,ub require consideration of the dimensions of y and x. For example, if y is proportional to an area (L'), and x to a length (L), then h = 2 wo~lld indicate isometry. By definition, anaerobic power is work divided by time (W/T). Work is proportional to the cube of the linear body dimension (L3), whereas time is assumed to be proportional to the first power of L (Astrand and Rodahl, 1986, pp. 391-41 1). Anaerobic power is thus proportional to L3/L, or L'. Body mass and FFM are proportional to L3.

Dimensionality theory therefore, predicts that anaerobic power should be proportional to FFM raised to the 213 power (Schmidt-Nielsen, 1984). For thigh CSA, a h exponent of 1 would indicate isometry, as both anaerobic power and CSA are proportional to L2. The relationships between PPO and body dimensions (FFM and CSA) in the current study revealed negative allometry: h exponents much lower than those predicted from geometric similarity theory. Subjects in this sample did not therefore conform to an isometric pattern. This finding underlines the caveat issued by Gould (1966) that the applicability of power functions in scaling physiological data must be determined empirically. Normali- sation of physiological variables through use of a theoretical mass exponent of 213 is a dangerous practice in the absence of sample-specific empirical confirmation.

Scaling of PPO within gender was rendered difficult due to the relatively small sample sizes and homogeneity of variables evident (Figures 1 and 2: Table 2). This problem has been recognised previously (Rogers et al., 1995) and may lead to a wide variety of h exponents reported in different studies, for the same physiological and body size variables. This again underlines the need for conducting sample-specific allometric scaling, rather than adopting assumed scaling indices.

GENDER COMPARISON OF ANAEROBIC PERFORMANCE

As expected, absolute PPO was greater in men than in women (1,252 vs. 68 1 W; p < .05). Scaling the data using the ratio index approach demonstrated that this sex difference was eliminated when PPO was expressed per unit CSA. The failure of RS to correctly remove the influence of body dimension in the current study, however, precludes its use for valid group comparisons. The ANCOVA (Table 2), entering FFMO ' and CSAO ' as covariates, demonstrated that correctly accounting for disparate body dimensions reduced the sex difference in PPO, but did not eliminate it (adjusted means for men and women 1,243 vs. 690 W; p < .05). It would seem that men and women are not physiologically equal. A comparison of body-size corrected external PPO in male and female samples matched for physical activity level revealed a significant sex difference in performance. If i t is assumed that the matching tool adopted was sufficiently rigorous, the results are indicative of a true, biological difference between men and women. Winter et al. ( 199 1) also reported significant sex differences in lower body PPO normalised for lean limb volume. This finding was questionable, however, as the authors adopted a linear, regression standards analysis. The current study

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supports the results of Winter et al. by using a more appropriate allometric scaling model.

Caution must be exercised in interpreting the above results, as limitations exist in the anthropometric method for estimating muscle and bone thigh CSA. First, the anatomical CSA does not necessarily reflect physiological CSA, which may vary considerably among the muscles of the lower limbs (Narici et al., 1992). Second, anthropometrically determined CSA does not account for intersubject differences in intramuscular fat and connective tissue content. Burkinshaw et al. (1971) identified a larger proportion of interstitial fat in women compared to men. This would result in an overestimation of true thigh muscle and bone CSA. Moreover, De Koning et al. (1986), reported that anthropometric methods overestimated arm CSA compared to computer tomography assessments. This error was found to increase with the thickness of the subcutaneous fat layer. As women generally possess greater subcutaneous fat than men, this would lead to an overestimation of thigh CSA and would therefore penalise women in comparisons of force or power per unit of CSA. These limitations may have exaggerated the sex difference in performance in the current study. Nevertheless, high correlations have been found in adults between anthropometrically determined muscle CSA and that measured via criterion NMR imaging methods (Narici and Roi, 1992). The potential confounding impact of the limitations outlined in the CSA estimation are difficult to quantify. However, we believe that the significant sex differences found in the current study are sufficiently large to offset any errors in CSA estimation in the female sample.

Although no other measurements were secured, some reasons for the sex differences in PPO may be considered. As anthropometric indices have been discounted, attention is redirected towards hormonal, enzymatic, and neurogenic factors. Differences in muscle recruitment capability may partially explain the superior performance of men. Sex differences have been reported in electromechanical delay (the interval between the contraction stimulus and the change in electrical activity in the muscle) and subsequently in the rate of force development (Bell and Jacobs, 1986). Females may thus have experienced difficulty in the rapid expression of power, and in overcoming the inertia of the flywheel and the inherent friction of the system. Tentative evidence for this suggestion can be derived from within-subject comparisons of "uncorrected" PPO (product of load and flywheel velocity) and PPO corrected for work done in accelerating the flywheel. Data from our own laboratory (unpublished observation) demonstrate that corrected PPO is approximately 24% greater than uncorrected in males (p < .05), but only 7% greater in females (p > .05). Hence, it is possible that females in the current study may have experienced difficulty in rapidly accelerating the flywheel. The extent of the sex difference in anaerobic performance may thus partly depend upon the specific methods employed.

With reference to muscle recruitment in cycling, large intersubject differences have been found. Coyle (1995) reported that the best time trialists were better able to utilise their hip extensor muscles (gluteus maximus in particular), thus generating 22% greater peak torque during the cycling downstroke, than another group matched for FFM and V0,max. In the current study, potential intergroup differences in muscle recruitment capability could not be accounted for. A further limitation was the attempt to relate anaerobic performance to the

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involved musculature, via thigh muscle and bone CSA estimations. This represents a relatively crude index of the muscles active in supramaximal cycle ergometry. In particular, the contribution of the gluteal muscles is unaccounted for.

In addition to the potential for disparate muscle recruitment ability, sex differences have also been reported in the activity of rate-limiting enzymes in the glycolytic pathway, with males exhibiting 15-29% greater phosphofructokinase (PFK) activity than females (Green et al., 1984; Simoneau and Bouchard, 1989). These differences may be vital in the expression of PPO, as it has been shown that glycolysis makes a significant contribution to ATP turnover in the first few seconds of maximal intensity muscular contractions (Hultman and Sjoholm, 1983; Jacobs et al., 1983).

In conclusion, we have demonstrated the superiority of allometric scaling over ratio standards approaches in correctly removing the influence of body size on anaerobic performance. We recommend that sample-specific allometry be conducted in all studies where data scaling is required, as power function exponents can vary widely. After normalisalion of lower body PPO for body dimensions, significant sex differences in performance remained, in samples of males and females of comparable physical activity status. The extent of this sex difference may partly relate to the specific methods employed to assess PPO. The precise mechanisms underlying this apparent biological difference in anaerobic performance remain to be elucidated.

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Allometry of Anaerobic Performance: A Gender Comparison

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