ORIGINAL ARTICLE

Allometric scaling of 6-min walking distance by body massas a standardized measure of exercise capacity in healthy adults

Victor Zuniga Dourado • Mary Ann McBurnie

Received: 12 April 2011 / Accepted: 24 October 2011 / Published online: 11 November 2011

� Springer-Verlag 2011

Abstract Body mass (BM) is a confounding variable in

human performance. We hypothesized that adjusting 6-min

walk distance (6MWD) for BM differences using allome-

tric scaling would allow meaningful individual and group

comparisons. We aimed to use allometric scaling of

6MWD to BM to provide an index for comparing walking

performance in middle-aged and older adults. One hundred

and twenty subjects (40–87 years) participated. Anthro-

pometry, spirometry, and two walk tests were evaluated.

We adjusted 6MWD to BM, gender, and age using an

allometric procedure. The allometric exponents were pro-

spectively applied in a validation sample of 44 healthy

subjects. Body mass presented significant negative corre-

lation (p \ 0.01) with 6MWD � BM-1 in middle-aged and

older adults (r = -0.70 and -0.46, respectively). The

allometric exponent (b) for 6MWD was significantly higher

for older than middle-aged adults (0.35 ± 0.20 vs.

0.11 ± 0.08, respectively). The resulting BM exponents

were similar in male and female subjects (0.22 ± 0.13 and

0.17 ± 0.09, respectively). The correlation between

6MWD � BM-b and BM using the exponents (0.11 or 0.35)

was not statistically different from zero (r = 0.00) in the

validation sample, suggesting that allometric analysis did

not penalize the subjects based on BM. Allometric scaling

of 6MWD in middle-aged and older adults may be useful

for evaluating walking performance free of the confound-

ing effect of BM, even in the absence of a table of norms.

Keywords Allometry � Exercise � Healthy adults

Introduction

The six-minute walk test (6MWT) has been widely used to

assess exercise capacity in patients with cardiopulmonary

disease (ATS 2002). The 6MWT has also been adminis-

tered to healthy, asymptomatic individuals, and different

demographic, anthropometric, clinical and physiological

aspects have been identified as determinants of the 6-min

walk distance (6MWD) (ATS 2002; Enright et al. 2003).

For example, correlations between height and 6MWD are

often significant in healthy individuals in linear models

(Camarri et al. 2006; Enright and Sherrill 1998; Troosters

et al. 1999). The consistent correlation between height and

distance traveled may be attributed to the longer stride of

taller individuals (Callisaya et al. 2008). On the other hand,

Enright et al. (2003) found that the association between the

body mass index (BMI) and 6MWD is non-linear. More

recently, Lammers et al. (2008) found that the association

between body mass (BM) and 6MWD in 328 children

between 4 and 11 years of age exhibited a positive linear

relationship until approximately 30 kg, at which point the

slope nears zero, indicating that the increase in BM did not

result in a subsequent significant increase in 6MWD. In

obese children and adolescents, BMI z-score is the most

dominant predictor of the variability in the 6MWD (Cal-

ders et al. 2008). These results show the strong influence of

BM on walking performance, although the association

between BM and 6MWD is generally weak or non-existent

Communicated by Susan A. Ward.

V. Z. Dourado (&)

Department of Human Movement Sciences,

Laboratory of Human Motricity, Federal University of Sao Paulo

(UNIFESP), Av. Ana Costa, 95, Santos,

Sao Paulo 11060-001, Brazil

e-mail: vzdourado@yahoo.com.br; victor.dourado@unifesp.br

M. A. McBurnie

Kaiser Permanente Center for Health Research, Portland, USA

123

Eur J Appl Physiol (2012) 112:2503–2510

DOI 10.1007/s00421-011-2222-7

when linear approach is used (Chetta et al. 2006; Enright

and Sherrill 1998; Gibbons et al. 2001).

Allometric scaling is a more appropriate mathematical

procedure for clarifying the relation between anthropo-

metric measures (e.g., BM and stature) and physical fitness

variables, such as muscle strength, aerobic capacity, and

running speed (McArdle et al. 2003). This approach

assumes that the real relation between a physical fitness

variable of interest and an anthropometric variable is cur-

vilinear and results in the following equation:

y ¼ axb ð1Þ

in which y is the physical fitness variable of interest, x is

the scale (i.e., anthropometric variable), a is a constant

multiplier, and b is the allometric correction exponent

(Vanderburgh et al. 1995).

There are advantages of allometric scaling in relation to

other procedures for performance analysis. The ratio

standards between body size and performance remove the

effect of body size in only some statistical situations, which

rarely occur in practice. Linear procedures result in y-

intercepts different from zero, which is physiologically

impossible, indicating that extrapolation beyond the origi-

nal data are problematic in these models. In contrast, the

allometric procedure results in y-intercepts passing through

the origin. Furthermore, the allometric scaling is the result

of an exponential function, which can provide better

modeling than linear models. Statistically, heteroscedas-

ticity is often present in linear models involving variables

of body size, while the logarithmic transformations related

to allometric procedure tend to correct the heteroscedastic

nature of the data (Nevill and Holder 2000). Due to these

advantages, we chose to use allometric scaling to re-

examine the relationships between BM, 6MWD, and age in

healthy adults.

As the relation between the 6MWD and BM is non-

linear, we hypothesize that, despite the inconsistent linear

correlation between these variables, BM alone may explain

an important part of the 6MWD in healthy individuals. In

this case, the 6MWD, which is directly linked to walking

speed and total energy expenditure during exercise (ATS

2002), may be a physical fitness variable of interest and

BM, which has a non-linear association with 6MWD

(Lammers et al. 2008), would be an anthropometric vari-

able resulting in the following equation:

6MWDm ¼ a BMkg

� �b ð2Þ

The identification of the allometric exponent (b) of this

relation (i.e., 6MWD � BM-b) will allow a more adequate

comparison of performance on the 6MWT by individuals

with substantially different anthropometrics. Accordingly,

the primary aim of the present study was to use allometric

scaling for assessing normal values of an index of walking

performance (i.e., 6MWD � BM-b) in healthy middle-age

and older adults, which is free of the confounding effect of

BM, and to assess the reliability of our allometric exponents

in a validation sample of 44 participants prospectively

evaluated. Since height is a body size variable and has been

identified as an important determinant of 6MWD in linear

models, we provided alternate multivariate allometric

models also including stature.

Methods

Individuals

One hundred and twenty healthy individuals between 40

and 87 years of age (55 men) were evaluated. Participants

were recruited from among employees of the Federal

University of Sao Paulo and from among employees of the

Santa Casa Hospital, both located in Santos, Brazil, as well

as from residents of the surrounding community. All

individuals reported having no musculoskeletal injuries,

hospitalization or chronic illnesses that would impede

physical exercise. They were free of cardiopulmonary,

skeletal muscle, or metabolic disturbances and were non-

trained as self related through a questionnaire.

To determine the reliability of our allometric exponents, a

prospective evaluation of the 6MWD was carried out on 44

healthy individuals (20 men). We applied the allometric

exponents and verified the association between 6MWD �BM-b and BM in these individuals. The same approach was

performed for models including stature. These participants

were recruited from the employees of the university and

adjacent community, fulfilled the eligibility criteria and did

not participate in the initial sample.

The individuals were informed about the procedures,

discomfort and possible risks involved and signed terms of

informed consent. The present study meets the ethical

standards and received approval from the Ethics Commit-

tee of the Federal University of Sao Paulo (UNIFESP).

Anthropometrics and spirometry

Stature (cm) and BM (kg) were measured according to

standard techniques, with the subjects wearing light

clothing and no shoes. Measurements were made with a

calibrated Filizola scale (0.1 kg of precision) and with a

stadiometer (0.5 cm of precision), and the BMI (BMkg/

staturem2 ) was calculated. The following variables were

determined through spirometry (Spirodoc; MIR, Italy)

based on the criteria of the American Thoracic Society

(ATS 1995): forced expiratory volume in the first second

(FEV1), forced vital capacity (FVC), and the FEV1/FVC

2504 Eur J Appl Physiol (2012) 112:2503–2510

123

ratio. The spirometric indices are expressed in percentage

of the reference values for the Brazilian population (Pereira

et al. 2007).

Six-minute walk test

The 6MWT consisted of walking as fast as possible for

6 min on a flat, covered 30 m course delimited by two

traffic cones with demarcations every 3 m on the ground.

The volunteers performed two tests, with standardized

verbal encouragement from the examiners. Phrases such as,

‘‘you are doing well. You have 5 min to go’’ and ‘‘keep up

the good work. You have 4 min to go’’ were used every

minute with fairness and appropriate voice and with no

body language following the recommendations of the

American Thoracic Society (ATS 2002). The tests were

performed with 30-min interval between then. Heart rate,

blood pressure, and lower limb fatigue (using the Borg

Perceived Exertion scale) (Borg 2000) were determined

prior to and at the end of each test. The 6MWD on the

second test was used in the data analysis.

Statistical analysis

The data are expressed as mean ± standard deviation. The

student’s t test was used for the comparisons between mean

values. Pearson’s correlation coefficient was used to assess

linear associations between the continuous values. The

Kolmogorov–Smirnov test was used to assess the normality

of 6MWD. The probability of a type I error was set at 5%

(p \ 0.05).

Ratio standards between 6MWD and BM (6MWD �BM-1) were calculated. The same relation was assessed by

means of allometric scaling. This method takes the curvi-

linear relation between the variables into account and

mathematically defines the relation described in Eq. 1.

Applying log-linear regression, this equation can be

linearized:

log yð Þ ¼ bð Þ log xð Þ þ log að Þ; ð3Þ

in which a is derived from the antilog of the intercept at

y and the slope b is equal to the allometric exponent of the

function y = axb (Vanderburgh et al. 1995).

Linear regressions were carried out for male and

females separately. Different a values between men and

women reflect the influence of gender and equal exponents

indicate that the performance of males and females

undergoes the same influence from BM. The Kolmogorov–

Smirnov test was used to assess the normality of the

residual distribution. Homoscedasticity was assessed

through the absence of a correlation between the residuals

and the anthropometric measures. The exponents were

considered similar between males and females if Pearson’s

correlation coefficient between 6MWD � BM-b and BM

was not different from zero when the allometric exponent

from the males was used for the females and vice versa

(Vanderburgh et al. 1995). If males and females presented

similar exponent, only one log-linear regression was

applied for the total sample with sex added to the regres-

sion model (Nevill and Holder 2000). In all statistical

approaches, sex was incorporated as a dummy variable

(women = 0; men = 1). The procedures were repeated

within the age groups with sex as separate independent

variable added to the regression model. This allowed us to

estimate one value of b but different values of a, indicating

difference in 6MWD due only to sex.

To investigate the influence of age, we chose to stratify

the sample into two age groups applying linear regressions

separately for middle-age (40–59 years) and older adults

(C60 years). The same approach described above was used

for this comparison. The influence of age and BM on

6MWD was investigated using the allometric model

described elsewhere (Johnson et al. 2000; Nevill and

Holder 2000). In each age group, age was incorporated into

the model as exponential term using the following form:

6MWD ¼ BMb exp aþ c � ageð Þ þ d � sexð Þ½ �e; ð4Þ

where e represents a random multiplicative error term. Age

was not selected as a determinant. For this reason, we re-

examined the influence of BM in each age group using only

sex.

Since health-related performance first increases as BM

increases in the lower range of normal values (‘‘muscle

effect’’), but then decreases as BM increases further

(‘‘obesity effect’’), we solved this limitation using the

following three approaches.

First, the ‘‘obesity effect’’ was investigated by the fol-

lowing form within each age group:

6MWD¼BMb exp�aþ c� ageð Þþ d� sexð Þþ e� BMð Þ

�e

ð5Þ

The model was linearized by taking the natural logarithm

as described above. Incorporating BM in the multiplicative

model (Eq. 5) as an allometric term as well as within the

exponential function, the model is able to describe an initial

growth in the response variable with increasing BM

(‘‘muscle effect’’) that will eventually peak and then

subsequently decline with excessive BM (‘‘obesity

effect’’). The BM as well as age were not selected as

determinants as exponential terms. For this reason, we re-

examined the influence of BM considering only sex.

Second, we tested the influence of BMI. The entire

cohort was divided by BMI in ‘‘normal weight’’ BMI

\25 kg/m2 versus ‘‘overweight’’/obese BMI C25 kg/m2

and new models were developed and tested.

Eur J Appl Physiol (2012) 112:2503–2510 2505

123

Third, we used the same above-mentioned procedure for

providing alternative multivariate allometric models

including BM as well as stature. A multiple regression was

employed, resulting in a log-linear model as follows:

log yð Þ ¼ log að Þ þ b1 log x1ð Þ þ b2 log x2ð Þ ð6Þ

This equation, as well as described for Eq. 3, is

equivalent to the following equation were x2 represents

stature:

y ¼ a � xb1

1 � xb2

2 ð7Þ

The reliability of our index of walking performance was

evaluated using the allometric exponents obtained in

the initial sample in a validation sample of 44 healthy

middle-age and older adults. The gender factor was defined as

men = 1 and women = 0. Statistical analysis was performed

using the statistical package SPSS 12 (SPSS, Chicago, IL,

USA).

Results

All individuals presented normal lung function (FEV1

= 93 ± 8%; FVC = 91 ± 8%; FEV1/FVC = 90 ± 12%).

According to reference cutoff points, 42 participants were

classified as normal weight, 66 as over weight, and 12 as

obese. There were no significant differences between the

initial sample and validation sample regarding age, BM,

stature, BMI, 6MWD, and proportion of male and female

(Table 1). Six-minute walk distance was normally distrib-

uted both in the initial (K–S dist. = 0.068; p = 0.180) and

validation sample (K–S dist. = 0.118; p = 0.128). There

were significant correlations between 6MWD and age

(r = -0.30; p \ 0.001), stature (r = 0.40; p \ 0.001), and

BM (r = 0.23; p \ 0.05). Six-minute walk distance was

greater among the males (600 ± 82 vs. 538 ± 72 m;

p \ 0.001). There was a significant negative correlation

between 6MWD � BM-1 and BM in middle-age and older

adults (r = -0.70; p \ 0.001 and r = -0.46; p \ 0.01,

respectively), indicating that the ratio standards penalize

individuals with a greater BM.

When allometric scaling was applied separately for males

and females, the exponents for BM were 0.22 ± 0.13 and

0.17 ± 0.09, respectively. There was no significant differ-

ence between the exponents, as the Pearson correlation

coefficients between 6MWD � BM-b and BM were not

significant when the exponent from the males (b = 0.22)

was used for the females and when the exponent from the

females (b = 0.17) was used for the males (r = -0.09) and

vice versa (r = 0.03). Similarly, the exponents obtained for

normal and overweight/obese subjects were not statistically

different (0.31 ± 0.20 vs. 0.25 ± 0.1, respectively). On the

other hand, the allometric exponent was significantly higher

for older than for middle-age adults (0.35 ± 0.20 vs.

0.11 ± 0.08, respectively), i.e., there were significant cor-

relation coefficients between 6MWD � BM-b and BM,

when the exponent of older was used for middle-age adults

and vice versa (r = 0.31 and -0.23, p \ 0.05). The corre-

lation coefficient between 6MWD � BM-b and BM was not

statistically different from zero in the initial sample (r =

-0.02), thereby demonstrating the individuals with a greater

BM were not penalized by the allometric correction. Thus,

we could calculate percentiles of 6MWD � BM-0.11 for

middle-age and of 6MWD � BM-0.35 for older adults

(Table 2). Nevertheless, we used these allometric exponents

in the validation sample and the coefficient of correlation

between 6MWD � BM-b and BM was not statistically dif-

ferent from zero (Fig. 1, left side). The R2 values were 0.347

and 0.304 for middle-aged and older participants,

respectively.

The best fit curves of the 6MWD and BM relationships

were as follows:

6MWDm ¼ 317:66 � BMkg

� �0:11middle-age femalesð Þ

ð8Þ

6MWDm ¼ 343:64 � BMkg

� �0:11middle-age malesð Þ ð9Þ

6MWDm ¼ 118:39 � BMkg

� �0:35older femalesð Þ ð10Þ

6MWDm ¼ 144:02 � BMkg

� �0:35older malesð Þ ð11Þ

As was found for BM, stature was influenced by age in the

allometric approach, but not by sex. When the exponents

were used in the validation sample, the correlation between

6MWD � BM�b1 � stature�b2 and BM was not significantly

different from zero (Fig. 1, right side). The R2 values were

0.406 and 0.398 for middle-aged and older participants,

respectively. Therefore, alternative multivariate models

including stature were developed as follows:

Table 1 General characteristics of the participants

Initial sample

(n = 120)

Validation

(n = 44)

Age (years) 58 ± 10 57 ± 8

BM (kg) 69 ± 11 67 ± 11

Stature (cm) 161 ± 9 163 ± 8

BMI (kg/m2) 26 ± 4 27 ± 5

6MWD (m) 563 ± 82 564 ± 55

Values are expressed as mean ± standard deviation

BM body mass, BMI body mass index, 6MWD distance traveled on

six-minute walk test

2506 Eur J Appl Physiol (2012) 112:2503–2510

123

6MWDm ¼ 76:40 � BMkg

� �0:08

� staturecmð Þ0:31middle-age femalesð Þ ð12Þ

6MWDm ¼ 80:82 � BMkg

� �0:08

� staturecmð Þ0:31middle-age malesð Þ ð13Þ

6MWDm ¼ 7:46 � BMkg

� �0:26

� staturecmð Þ0:62middle-age femalesð Þ ð14Þ

6MWDm ¼ 8:67 � BMkg

� �0:26

� staturecmð Þ0:62middle-age malesð Þ ð15Þ

Discussion

We are unaware of previous studies that clarify the rela-

tionship between the 6MWD and BM using allometric

scaling. It was determined that BM alone is capable of

Table 2 6-min walking

distance (6MWD) adjusted for

body mass (BM) using the

allometric correction exponents

Percentiles (%) Middle-aged adults

6MWD � BM-0.11 (m kg-0.11)

Older adults

6MWD � BM-0.35 (m kg-0.35)

Males

(n = 39)

Females

(n = 41)

Males

(n = 19)

Females

(n = 21)

5 284.62 288.57 102.44 92.31

10 309.85 293.68 122.45 99.07

25 341.52 310.01 129.72 106.93

50 373.34 344.19 147.27 121.53

75 411.97 372.77 159.95 134.22

90 433.80 404.07 176.40 146.98

95 453.94 412.13 195.38 152.16

BW(kg)50 55 60 65 70 75 80 85 90

6MW

D x

BM

-0.1

1 (m x

kg-0

.11 )

300

320

340

360

380

400

420

440

460

480

BW (kg)50 55 60 65 70 75 80 85 90

6MW

D x

BM

-0.0

8 x s

tatu

re-0

.31

(m x

kg-0

.08 x

cm

-0.3

1 )

1600

1800

2000

2200

2400

2600

2800

BW (kg)50 60 70 80 90 100

6MW

D x

BM

-0.3

5 (m x

kg-0

.35 )

90

100

110

120

130

140

150

160

BW (kg)50 60 70 80 90 100

6MW

D x

BM

-0.2

6 x s

tatu

re-0

.62

(m x

kg-0

.26 x

cm

-0.6

2 )

3000

3500

4000

4500

5000

5500

6000

Fig. 1 Scatter plots of 6-min walk distance (6MWD) corrected by body mass (BM) and stature using allometric scaling in middle-aged (toppanel) and older (bottom panel) healthy participants

Eur J Appl Physiol (2012) 112:2503–2510 2507

123

adequately assessing the performance on the 6MWT

among middle-age and older adults. We observed that the

allometric exponent found in the present study allows more

appropriate comparison of walking performance in these

participants, free from the confounding effect of BM and

seems to be valid for comparing walking performance in a

prospectively sample.

There was an influence from age, stature, and gender on

the 6MWD. Such findings have been widely discussed in

previous studies (Ben Saad et al. 2009; Camarri et al. 2006;

Troosters et al. 1999), including on the Brazilian popula-

tion (Iwama et al. 2009), and will not be discussed here.

However, the association between 6MWD and BM has

been inconsistent in a large number of studies (Enright

et al. 2003; Gibbons et al. 2001; Troosters et al. 1999).

Gibbons et al. (2001) submitted 79 volunteers between 20

and 80 years of age to four 6MWTs and found that age and

gender were determinants of 6MWD. In a study by Poh

et al. (2006), BM was not selected as a determinant of

6MWD. Iwama et al. (2009) found that age and gender

were determinants of 6MWD in 134 Brazilians between 13

and 84 years of age. Corroborating Gibbons et al. (2001),

there was a weak correlation between 6MWD and BMI

(r = -0.24 and r = -0.27, respectively) in these studies

(Gibbons et al. 2001; Iwama et al. 2009). Lammers et al.

(2008) evaluated 328 children between 4 and 11 years of

age and found that age, BM and stature were determinants

of 6MWD, together explaining 44% of the variability;

however, age alone explained 41% of this 44% (Lammers

et al. 2008). The authors (Lammers et al. 2008) also found

a linear association between 6MWD and BM only up to

30 kg, at which point the slope leveled off. Indeed, when

significant, the correlation between 6MWD and BM is

inconsistent (e.g., r = 0.25) (Camarri et al. 2006).

The results from the aforementioned studies suggest a

limited influence of BM on 6MWD. However, the present

study demonstrates that the influence of BM is substantial.

Its limited influence in some studies is due to the fact that

its association with 6MWD is not linear. Therefore, it is not

surprising that, across studies, the impact of this variable is

inconsistent in linear regression models. The results of the

present study using allometric correction demonstrate that

appropriate comparisons among gender and age groups

independent of the confounding effect of BM were

possible.

The BM exponents found in the present study means

that the distance traveled increases at a lower proportion

than BM in these age groups. These results are in agree-

ment with those found in the literature. Among 37 species

of mammals (from the smallest to the largest), the mean

allometric exponent between walking performance and BM

was 0.35 (Alexander 1989). A number of authors evalu-

ating the relation between BM and stature or leg length in

children have described allometric exponents between 0.32

and 0.37 (Morgan et al. 2002; Rowlands et al. 1997; Vin-

cent and Pangrazi 2002). Given that, the 6MWT is a self-

paced test, the larger 6MWD represents ultimately the

walking speed on the ground. The ground speed of all

mammals depends primarily on the number of steps per

unit distance traveled and frequency of movement of the

lower limbs. Assuming geometrical similarity among the

animals, the number of steps per unit distance is related to

BM raised to one-third. The frequency of steps is also

proportional to the one-third power of BM (Schmidt-

Nielsen 1984). Pua (2006) showed an allometric exponent

of 0.07 for the timed up and go test using multivariate

regression model adjusted for BM, age, and sex. These

results are close to the exponent 0.11 found in the present

study.Thus, although the allometric exponent of the rela-

tion between 6MWD and BM has not been previously

described, the finding of the present study is similar to the

above-mentioned findings (Schmidt-Nielsen 1984; Vincent

and Pangrazi 2002). In regard to stature, the literature

demonstrates a consistent correlation between stature and

gait speed on the 6MWT (Chetta et al. 2006; Enright and

Sherrill 1998; Troosters et al. 1999), which may be

attributed to the longer stride of taller people. Stride length

and frequency are two of the main determinants of gait

speed (Callisaya et al. 2008).

On the other hand, our results are different from those

described above for the VO2max by Johnson et al. (2000)

and Welsman et al. (1996). Although the 6MWD present

consistent correlation with VO2max in the elderly (Kervio

et al. 2003), the kinetics of oxygen consumption during the

6MWT assumes an exponential pattern, similar to that

described for a constant intensity endurance test (Troosters

et al. 2002; Wasserman et al. 2005). In this regard, the

correlation between 6MWD and VO2max is non-linear,

which explains in part the differences in allometric expo-

nents found for the 6MWD in the present study and pre-

viously described for VO2max (Johnson et al. 2000;

Welsman et al. 1996). However, since we were unable to

find other studies concerning the 6MWD, no appropriate

comparisons were possible. Therefore, individuals with a

smaller body dimensions have lesser mechanical efficiency

than larger individuals, which explain partially our allo-

metric exponents (0.11 and 0.35) (Eisenmann and Wickel

2005).

The exponent observed in older adults was significantly

higher compared to middle-age adults. Older adults need

more BM for each meter walked during the 6MWT, indi-

cating their lower muscle quality (although fat free mass

was the best predictor). The negative influence of advanced

age on muscle quality and in consequence on exercise

capacity might be explained by the gradual reduction in

muscle mass, muscle strength, and maximal oxygen uptake

2508 Eur J Appl Physiol (2012) 112:2503–2510

123

that typically occurs in parallel with aging (Evans and

Campbell 1993; Fleg and Lakatta 1988).

The present study has limitations that should be con-

sidered. The population was a convenience sample. How-

ever, this type of sampling has been used in a number of

studies analyzing normal 6MWD values (Ben Saad et al.

2009; Enright and Sherrill 1998; Troosters et al. 1999).

Moreover, the exponents obtained in the present study were

validated in a second, independent sample, which reduces

the bias inherent to convenience sampling. Lean body

mass, which is a better index of muscle performance than

BM, was not evaluated in the present study. The exponents

presented here could be used to evaluate walking perfor-

mance free of the confounding effect of BM. The 6MWD

declines when BMI[30 kg/m2 (Enright et al. 2003). In the

present study, the allometric exponent obtained for the

normal weight participants did not differ from that seen in

over weight/obese participants. Our results are different

from those described previously for peripheral muscle

strength (Zoeller et al. 2008), probably due to the large

percentage of overweight participants in our sample. In

addition, only 12 participants had BMI [30 kg/m2 above

this value, which makes the allometric procedure more

reliable in relation to BM. Finally, the exponents have been

validated in a sample with BMI values similar to the ori-

ginal sample. According to the exclusion criteria of this

study, the BMI of the participants did not exceed 35 kg/m2.

Since the relationship between BMI and body fat is age and

sex dependent, it is possible that BMI is not able to dif-

ferentiate reliably lean mass and body fat. Thus, it is rea-

sonable to question whether the homogeneity of body

composition can be completely taken in our sample. We

could not observe the ‘‘obesity effect’’ on health-related

performance in the present study, since the BM as expo-

nential term was not selected as a determinant. Thus, we

recognize that the results of this study may not be suitable

in a range of BMI [35 kg/m2. In fact, very substantial

errors can result from the application of curvilinear models

to individuals outside the boundaries within which the

equation is appropriate. However, this is also a limitation

of linear models. Thus, these exponents would have to be

validated before use in obese subjects, considering their

growing proportion in the population. Although the sample

size was sufficient for the determination of the allometric

exponents, the findings should be confirmed in studies

involving a greater number of individuals.

In conclusion, the allometric scaling applied to the

6MWD in healthy middle-age and older adults allow

assessing performance on the 6MWT free of the influence

of BM. These allometric exponents may be used for

comparisons between individuals of either gender and with

different anthropometric measures, even in the absence of

the tables of the norms. The influence of BM on the 6MWD

has been underestimated in studies that have developed

reference equations based on linear regressions. These duly

validated exponents will enable a better interpretation of

performance on the 6MWT by healthy individuals, as well

as patients with diseases that affect exercise capacity.

Acknowledgments This study received financial support in the

form of a research grant from the Fundacao de Amparo a Pesquisa doEstado de Sao Paulo (FAPESP, Foundation for the Support of

Research in the State of Sao Paulo; grant no. 2007/08673-3).

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