Six-minute walk distance in healthy Singaporean adults
1. Respirology (2006) 11, 211–216
Blackwell Science, LtdOxford, UKRESRespirology1323-77992005 Blackwell Publishing Asia Pty Ltd112211216Original ArticleSix-minute walk distance in SingaporeansH Poh
Correspondence: Sue Jenkins, School of Physiother-
apy, Curtin University of Technology, GPO Box U1987,
Perth, WA, Australia. Email: email@example.com
Received 17 June 2005; invited to revise 17 August
2005; revised 13 October 2005; accepted 13 October
2005 (Associate Editor: YC Gary Lee).
Six-minute walk distance in healthy Singaporean adults
cannot be predicted using reference equations derived from
Peter R. EASTWOOD,1,2,4
Nola M. CECINS,1,3,5
Kheng Thye HO6
AND Sue C. JENKINS1,3,5
School of Physiotherapy, Curtin University of Technology, 2
Department of Pulmonary Physiology and
Department of Physiotherapy Sir Charles Gairdner Hospital, 4
School of Anatomy and Human Biology and
Asthma and Allergy Research Institute, Perth, Western Australia, Australia, and 6
The Heart Institute,
National Healthcare Group, Singapore
Six-minute walk distance in healthy Singaporean adults cannot be predicted using reference
equations derived from Caucasian populations
POH H, EASTWOOD PR, CECINS NM, HO KT, JENKINS SC. Respirology 2006; 11: 211–216
Objectives: The 6-min walk test (6MWT) is commonly used to assess the functional exercise capac-
ity of individuals with cardiopulmonary disease. Recent studies have established regression equa-
tions to predict the 6-min walk distance (6MWD) in healthy Caucasian populations; however,
regression equations have yet to be established for the Singaporean population.The aim of this study
was to determine 6MWD in healthy Singaporeans and identify contributors to 6MWD in this popu-
lation. We also compared measured 6MWD with predicted 6MWD from two regression equations
derived in Caucasian subjects.
Methodology: Thirty-ﬁve healthy subjects (32 Chinese, 16 men) aged between 45 and 85 years per-
formed three walking tests using a standardized protocol. 6MWD was deﬁned as the greatest distance
achieved from the three tests. Heart rate (HR) was recorded each minute during the 6MWT. Other
measurements included age, height, leg length, smoking history and self-reported physical activity.
Results: 6MWD was 560 ± 105 m and was not signiﬁcantly different between men and women (P =
0.19). 6MWD was related to age (r = −0.36, P = 0.03), height (r = 0.35, P = 0.04), leg length (r = 0.38,
P = 0.02) and the maximum HR achieved on the 6MWT when expressed as a percentage of the
predicted maximum HR (%predHRmax, r = 0.73, P < 0.001). Stepwise multiple regression analysis
showed that age, height, weight and %predHRmax were independent contributors (P < 0.01) to
6MWD, explaining 78% of the variance. Predicted 6MWD using regression equations derived from
Caucasian subjects exceeded measured 6MWD by more than 75 m (P < 0.001).
Conclusions: This is the ﬁrst study to report 6MWD for healthy Singaporeans aged 45–85 years.The
regression equation developed in this study explained 78% of the variance in 6MWD. Published
equations derived from Caucasian subjects overestimate 6MWD in Singaporean Chinese.
Key words: exercise test, healthy subjects, 6-min walk distance, 6-min walk test, walk test.
The 6-min walk test (6MWT) is a widely used measure
of functional exercise capacity in individuals with car-
diopulmonary disease. It has advantages over labora-
tory based tests of exercise tolerance as it more closely
resembles the ability to perform activities of daily liv-
ing and does not require sophisticated equipment.1
The distance walked during the 6MWT, the 6-min
walk distance (6MWD), shows moderate to good
correlation with the peak oxygen uptake measured
during an incremental cycle ergometry test in
patients with moderate to severe COPD2–4
congestive heart failure (CHF).5,6
It is frequently used
as an outcome measure in cardiopulmonary rehabil-
itation and as an assessment tool in the selection of
patients for lung surgery.2,7
3. Six-minute walk distance in Singaporeans 213
of the calcaneum. The average of right and left leg
lengths was used in all analyses.
Habitual physical activity
Habitual physical activity for the previous week
and over the past 6 months, was obtained using a
The total number of min-
utes spent in moderate physical activity was
recorded and subjects were classiﬁed as ‘inactive’
if they spent <30 min per week on moderate phys-
ical activities, ‘insufﬁciently active’ if they spent 30–
150 min per week on moderate physical activities
and ‘sufﬁciently active’ for achieving health bene-
ﬁts if they spent >150 min per week on moderate
Where subjects were unable to
read or understand the questions, the question-
naire was conducted verbally by one investigator
Unpaired t-tests were used to compare subject
characteristics (age, height, BMI, leg length) and
maximum 6MWD between men and women.
Measurements obtained before (i.e. HR) or at the
end of each of the three tests (i.e. 6MWD, peak HR)
were compared using one-way repeated measures
anova. Where data were not normally distributed a
Friedman repeated measures anova on ranks was
applied. Post hoc analyses were performed with the
Dunn’s multiple comparison procedure. Repeata-
bility of the 6MWD was examined using intraclass
correlation coefﬁcient (ICC) and coefﬁcient of
The relationships between maximum 6MWD (best
of the three tests), subject characteristics and peak
HR were examined using Pearson’s univariate corre-
lation coefﬁcients (r). Forward stepwise multiple
regression analysis was performed on the following
variables: age, height, weight, sex and peak HR,
expressed as a percentage of the predicted maximum
HR (%predHRmax, with predHRmax calculated as
220 − age) to determine their contribution to maxi-
The 6MWD measured in our study was compared
with predicted 6MWD derived from the studies of
Troosters et al.9
and Gibbons et al.10
plots and paired t-tests. Comparisons were made of
6MWD obtained from an equivalent number of tests.
Speciﬁcally, when comparing our data to that of
Troosters et al.9
we used the 6MWD from the best of
the ﬁrst two tests. When comparing our data to that
of Gibbons et al.10
we used the 6MWD from the best of
three tests. No comparison was made between mea-
sured 6MWD and predicted 6MWD derived from the
study of Enright and Sherill8
as subjects in their study
performed only one 6MWT and the magnitude of the
HR response suggests the subjects’ effort level was
All analyses were performed using SigmaStat (ver-
sion 3.0.1, Systat Software, Richmond, CA, USA). Data
are reported as mean ± SD. An alpha value of 0.05 was
used to determine signiﬁcance.
Data from the 35 subjects are presented in Table 1 and
91% of the subjects were Chinese. Height, leg length
and weight were signiﬁcantly greater in men than
women (163.0 ± 7.7 cm vs. 152.5 ± 7.0 cm, P < 0.001;
83.0 ± 4.8 cm vs. 77.7 ± 5.2 cm, P = 0.004 and
63.9 ± 11.7 kg vs. 54.8 ± 13.3 kg, P = 0.041, respec-
tively). Height and leg length were strongly correlated
in both men (r = 0.80, P < 0.001) and women (r = 0.81,
P < 0.001). There were no sex differences in age, BMI,
smoking history, physical activity levels or minutes
walked in the last week. The majority of the subjects
(86%) reported taking sufﬁcient activity for health
beneﬁts and none were inactive.20
Six-minute walk distance
There were no signiﬁcant differences in HR recorded
before commencing successive tests (79 ± 11, 82 ± 10
and 83 ± 10 b.p.m., respectively). No 6MWT was ter-
minated prematurely, and no subject required a rest
during any test.
The maximum 6MWD was 560 ± 105 m (range 405–
796 m) for the group overall and was 586 ± 126 m
(range 450–796 m) for men and 538 ± 82 m (range
405–650 m) for women. Maximum 6MWD was not
signiﬁcantly different between men and women
(P = 0.19).
Six-minute walk distance increased signiﬁcantly
between test 1 and test 2 (524 ± 95 m vs. 540 ± 100 m,
P < 0.05) but not between test 2 and test 3
(540 ± 100 m vs. 557 ± 106 m). Seventy-nine per cent
of subjects walked their maximum 6MWD after the
ﬁrst walk. The ICC for the three tests was 0.99 and the
CV was 3.8 (range 0.63–13)%.
Table 1 Characteristics of the study population (n = 35)
Mean ± SD or
number of subjects
Age (years) 61.0 ± 8.3
Height (cm) 157.3 ± 9.0
Weight (kg) 58.9 ± 13.3
) 23.6 ± 3.9
Never 25 (71%)
Ex-smoker 9 (26%)
Smoker 1 (3%)
4. 214 H Poh et al.
Peak HR was 122 ± 25 b.p.m. (77 ± 15%predHRmax)
on the best of the three tests. Twelve subjects reported
leg fatigue (score >0) at the end of the 6MWT.
Associations with 6-min walk distance
There was a signiﬁcant inverse relationship between
age and 6MWD (r = −0.36, P = 0.03). Signiﬁcant direct
relationships were found between 6MWD and height
(r = 0.35, P = 0.04), leg length (r = 0.38, P = 0.02) and
%predHRmax (r = 0.73, P < 0.001). Age, height, weight
and %predHRmax were identiﬁed as independent
contributors to 6MWD (P < 0.01) in stepwise multiple
regression and together explained 78% of the variance
in 6MWD. %PredHRmax alone explained 53% of the
variance in 6MWD with height, age and weight con-
tributing 11%, 6% and 9%, respectively. The regres-
sion equation for estimating 6MWD is as follows:
6MWD (m) = 5.50 (%predHRmax) + 6.94 (height,
cm) − 4.49 (age, year) − 3.51 (weight, kg) − 473.27
Comparison with published regression
Comparisons between the 6MWD measured in our
Singaporean subjects with 6MWD derived from pub-
are illustrated in Figures 1 and 2.
Both previously derived equations signiﬁcantly over-
estimate 6MWD for our Singaporean subjects. Group
mean 6MWD was overestimated by 76 ± 89 m
(95% conﬁdence interval (CI): 47–108 m)9
(P < 0.001) and 86 ± 95 m (95% CI: 53–119 m)10
(P < 0.001).
This study demonstrated that the average 6MWD
in healthy Singaporeans aged 45–85 years was
560 ± 105 m. This age range is representative of indi-
viduals undergoing cardiopulmonary rehabilitation
in Singapore. The study also demonstrated that exist-
ing regression equations overestimate 6MWD in our
Comparison with published regression equations
The 6MWD measured in our subjects was signiﬁ-
cantly less than the predicted 6MWD from regression
equations derived in Caucasian populations. The
implications of this for patients with COPD or CHF
may be considerable, and include an overestimation
of the level of a patient’s disability as well as the
potential for setting unrealistic outcomes from inter-
ventions aimed at improving 6MWD.
One possible explanation for the lower 6MWD in
Singaporeans may be the differences in body compo-
sition with Singaporean Asians having a higher per-
centage of body fat for a given BMI when compared
Lean body mass is a predictor of
exercise capacity in healthy subjects.21
may include differences in the speed of habitual walk-
ing and walking efﬁciency between Caucasians and
Singaporean Asians. The Caucasian subjects in previ-
were on average 10–12 cm taller than
our cohort and the derived regression equation for
predicting 6MWD may be less accurate when applied
to individuals of shorter stature.
Limitations of our study include the small sample
size and the overrepresentation of Chinese individu-
als in our sample (91%) when compared with the
Singaporean population (77% Chinese). A recom-
Figure 1 Scatter plot of best of the ﬁrst two 6MWD and
predicted 6MWD from Troosters et al.9
Line of identity is
Predicted 6MWD (m)
400 500 600 700 800 900
Figure 2 Scatter plot of best of three 6MWD and predicted
6MWD from Gibbons et al.10
Line of identity is shown.
Predicted 6MWD (m)
400 500 600 700 800 900
5. Six-minute walk distance in Singaporeans 215
mendation arising from our study is the need for a
prospective validation of our equation in a larger
sample of Singaporeans that would also allow com-
parison of 6MWD among Singaporean Chinese,
Malays and Indians.
Sources of variability in 6MWD
Our equation included age, height, weight and
%predHRmax and explained 78% of the variance in
6MWD. Both external sources and subject-related
sources of variability are likely to exist.
External sources of variability
External sources of variability include track length,
test instructions and encouragement.22,23
protocol aimed to achieve the subject’s best possible
6MWD by using a sufﬁcient length track (45 m) to
avoid excessive turning, standard instructions, and
standard encouragement given every minute.22
Subject-related sources of variability
A learning effect has been demonstrated for the
and in this study the magnitude of the
learning effect was similar to previous reports in
Based on our ﬁndings, when
standardised instructions and encouragement are
given, one practice walk appears sufﬁcient to obtain a
reliable 6MWD in healthy subjects. This is consistent
with studies in patients with COPD and CHF where a
plateau in 6MWD occurs after the ﬁrst test.26–28
Other factors inﬂuencing 6MWD include age,
anthropometric data and psychological factors. Age
and height have been found to be major sources of
variability in 6MWD and in our study the correlations
between these variables and 6MWD were similar to
Consistent with Troosters et al.,9
an inverse relationship between weight and 6MWD
was found; however, in contrast to Gibbons et al.,10
failed to show an inverse relationship between BMI
and 6MWD. This is most likely because only three
subjects had a BMI >30, a value identiﬁed as the
upper threshold for a low 6MWD in healthy Cauca-
When adjusting this threshold to 27,
the value used to identify Singaporean Chinese as
obese only six subjects were classiﬁed as obese.29
absence of sex as a contributor to 6MWD is consistent
with other studies in which no signiﬁcant difference
in 6MWD between men and women was found after
correcting for height.11
In an attempt to explain a greater proportion of
the variability in 6MWD we examined relationships
between 6MWD and %predHRmax achieved on the
6MWT, leg length, number of minutes spent on mod-
erate activity and time spent walking for ﬁtness in the
previous week. The mean %predHRmax achieved on
the maximum 6MWD was identical to that reported
by Troosters et al.9
(77 ± 15%predHRmax); however, in
both studies considerable variability was observed. As
the 6MWT is self-paced, subjects have the freedom to
choose the speed at which they walk during the test.
The overall intensity of the test is therefore subject
selected despite the use of standardised instructions
and encouragement that aim to maximize perfor-
mance. The maximum HR attained on the 6MWT,
expressed as a %predHRmax, was more strongly cor-
related with 6MWD (r = 0.73) than any other variable
measured. Previous authors have not reported the
relationship between %predHRmax and 6MWD. The
inclusion of %predHRmax as a variable in the regres-
sion equation does, however, have limitations when
measuring 6MWD in individuals with disease or med-
ications that inﬂuence the HR response to exercise.
The correlations between 6MWD with height and
leg length were similar and the strong correlation
between height and leg length precluded the inclu-
sion of both variables in the regression equation.
Height was therefore used in preference to leg length
as it is more easily measured in the clinical setting.
The majority of subjects were physically active and no
signiﬁcant correlations were found between habitual
physical activity and 6MWD, a ﬁnding consistent with
Gibbons et al.10
In future studies the inclusion of other
factors such as mood, attitude and motivation may
explain a greater proportion of the variability in
Including an assessment of mood may also
be valuable as high levels of depression exist in
patient populations frequently
assessed using the 6MWT.
The authors thank the Department of Rehabilitation,
National University Hospital of Singapore for provid-
ing a test venue and each subject for their participa-
tion in this research. We also thank Dr Ritu Gupta for
statistical advice. This study was funded, in part, by
the National Health and Medical Research Council
(Australia) Grant no. 212016. Dr Peter Eastwood was
supported by a NHMRC R Douglas Wright Fellowship
1 Solway S, Brooks D, Lacasse Y, Thomas S. A qualitative
systematic overview of the measurement properties of
functional walk tests using in the cardiorespiratory
domain. Chest 2001; 119: 256–70.
2 Cahalin L, Pappagianopoulos P, Prevost S, Wain J, Ginns
L. The relationship of the 6-min walk test to maximal
oxygen consumption in transplant candidates with end-
stage lung disease. Chest 1995; 108: 452–9.
3 Carter R, Holiday DB, Stocks J, Grothues C, Tiep B. Pre-
dicting oxygen uptake for men and women with moder-
ate to severe chronic obstructive pulmonary disease.
Arch. Phys. Med. Rehabil. 2003; 84: 1158–64.
4 Turner SE, Eastwood PR, Cecins NM, Hillman DR, Jen-
kins SC. Physiologic responses to incremental and self-
paced exercise in COPD. A comparison of three tests.
Chest 2004; 126: 766–73.
6. 216 H Poh et al.
5 Roul G, Germain P, Bareiss P. Does the 6-minute walk
test predict the prognosis in patients with NYHA class
II or III chronic heart failure? Am. Heart J. 1998; 36:
6 Zugck C, Kruger C, Dure S et al. Is the 6-minute walk test
a reliable substitute for peak oxygen uptake in patients
with dilated cardiomyopathy? Eur. Heart J. 2000; 21:
7 Kadikar A, Maurer J, Kesten S. The six-minute walk test:
a guide to assessment for lung transplantation. J. Heart
Lung Transplant. 1997; 16: 313–19.
8 Enright PL, Sherill DL. Reference equations for the six-
minute walk in healthy adults. Am. J. Respir. Crit. Care
Med. 1998; 158: 1384–7.
9 Troosters T, Gosselink R, Decramer M. Six minute walk-
ing distance in healthy elderly subjects. Eur. Respir. J.
1999; 14: 270–4.
10 Gibbons WJ, Fruchter N, Sloan S, Levy RD. Reference
values for a multiple repetition 6-minute walk test in
healthy adults older than 20 years. J. Cardiopulm. Reha-
bil. 2001; 21: 87–93.
11 Enright PL, McBurnie MA, Bittner V et al. The 6-min walk
test. A quick measure of functional status in elderly
adults. Chest 2003; 123: 387–98.
12 Werkman A, Deurenberg-Yap M, Schmidt G, Durenberg
P. A comparison between composition and density of the
fat-free mass of young adult Singaporean Chinese and
Dutch Caucasians. Ann. Nut. Metabol. 2000; 44: 235–42.
13 Health Canada Fitness Unit. Physical Activity Readiness
Questionnaire. [Cited 30 January 2004.] http://www.
14 Qu NN, Li KJ. Study on the reliability and validity of inter-
national physical activity questionnaire (Chinese IPAQ).
Zhonghua Lie Xing Bing Xue Za Zhi 2004; 25: 265–8.
15 American Thoracic Society. ATS statement: guidelines
for the six-minute walk test. Am. J. Respir. Crit. Care Med.
2002; 166: 111–17.
16 Laukkanen RMT, Virtanen PK. Heart rate monitors: state
of the art. J. Sports Sci. 1998; 16: S3–S7.
17 Borg GAV. Psychophysical bases of perceived exertion.
Med. Sci. Sports Exerc. 1982; 14: 377–81.
18 American Thoracic Society. ATS standardization of spi-
rometry. Am.J.Respir.Crit.Care Med. 1994; 152: 1107–36.
19 Chin NK, Ng TP, Hui KP, Tan WC. Population based stan-
dards for pulmonary function in non-smoking adults in
Singapore. Respirology 1997; 2: 143–9.
20 Bull F, Milligan R, Rosenberg M, MacGowan H. Physical
Activity Levels of Western Australian Adults 1999. Health
Department of Western Australia and Sport and Recre-
ation Way2Go. Western Australian Government, Perth,
21 Jones NL, Makrides L, Hitchcock C, Chypchar T, McCart-
ney N. Normal standards for an incremental progressive
cycle ergometer test. Am. Rev. Respir. Dis. 1985; 131:
22 Guyatt GH, Pugsley SO, Sullivan MJ et al. Effect of
encouragement on walking test performance. Thorax
1984; 39: 818–22.
23 Sciurba F, Criner GJ, Lee SM et al. Six-minute walk
distance in chronic obstructive pulmonary disease:
reproducibility and effect of walking course layout
and length. Am. J. Respir. Crit. Care Med. 2003; 167:
24 Wu G, Sanderson B, Bittner V. The 6-minute walk test:
how important is the learning effect? Am. Heart J. 2003;
25 Kervio G, Carre F, Ville NS. Reliability and intensity of
the six-minute walk test in healthy elderly subjects. Med.
Sci. Sports Exerc. 2003; 35: 169–74.
26 Eiser N, Willsher D, Dore CJ. Reliability, repeatability
and sensitivity to change of externally and self-paced
walking tests in COPD patients. Respir. Med. 2003; 97:
27 Stevens D, Elpern E, Sharma K, Szidon P, Ankin M, Kes-
ten S. Six-minute walk tests. Am. J. Respir. Crit. Care Med.
1999; 160: 1540–3.
28 Morales FJ, Martinez A, Mendez M et al. A shuttle walk
test for assessment of functional capacity in chronic
heart failure. Am. Heart J. 1999; 138: 291–8.
29 Deurenberg-Yap M, Schmidt G, van Staveren WA,
Deurenberg P. The paradox of low body mass index and
high body fat percentage among Chinese, Malays and
Indians in Singapore. Int. J. Obes. Relat. Metab. Disord.
2000; 24: 1011–17.
30 van Manen JG, Bindels PJ, Dekker FW, IJzermans CJ, van
der Zee JS, Schade E. Risk of depression in patients with
chronic obstructive pulmonary disease and its determi-
nants. Thorax 2002; 57: 412–16.
31 Gottlieb SS, Khatta M, Friedmann E et al. The inﬂuence
of age, gender, and race on the prevalence of depression
in heart failure patients. J. Am. Coll. Cardiol. 2004; 43: