1. Respirology (2006) 11, 211–216
Blackwell Science, LtdOxford, UKRESRespirology1323-77992005 Blackwell Publishing Asia Pty Ltd112211216Original ArticleSix-minute walk distance in SingaporeansH Poh
et al.
Correspondence: Sue Jenkins, School of Physiother-
apy, Curtin University of Technology, GPO Box U1987,
Perth, WA, Australia. Email: s.jenkins@curtin.edu.au
Received 17 June 2005; invited to revise 17 August
2005; revised 13 October 2005; accepted 13 October
2005 (Associate Editor: YC Gary Lee).
ORIGINAL ARTICLE
Six-minute walk distance in healthy Singaporean adults
cannot be predicted using reference equations derived from
Caucasian populations
Hermione POH,1
Peter R. EASTWOOD,1,2,4
Nola M. CECINS,1,3,5
Kheng Thye HO6
AND Sue C. JENKINS1,3,5
1
School of Physiotherapy, Curtin University of Technology, 2
Department of Pulmonary Physiology and
3
Department of Physiotherapy Sir Charles Gairdner Hospital, 4
School of Anatomy and Human Biology and
5
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.
INTRODUCTION
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
and
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

2. 212 H Poh et al.
Despite the popularity of the 6MWT in the clinical
setting, there is a paucity of 6MWD reference values
obtained in healthy subjects. This limits the interpre-
tation of 6MWD in patients and poses problems for
clinicians wishing to provide patients with a measure
of their expected 6MWD in the absence of disease.
The published regression equations for estimating
6MWD in healthy subjects explain between 40% and
66% of the variance in 6MWD using variables such as
age, height, weight, sex and health status.8–10
However,
the equations produce distances that differ by as
much as 100 m for the same individual, most likely
because of the use of different test protocols, that is,
different track lengths, test instructions, frequency of
encouragement during the test and number of repe-
titions of the 6MWT.8–10
It is likely that reference values for 6MWD may need
to be specifically determined for various ethnic
groups. There is some evidence of differences in
6MWD among different ethnic groups with healthy
African-Americans walking on average 40 m less than
white Americans after correcting for age, sex, height
and weight.11
Such differences in 6MWD may also
exist for the Singaporean population as, compared
with Caucasians, Asians are generally shorter in stat-
ure and Singaporean Asians have a higher percentage
of body fat for an equivalent BMI when compared
with Caucasians.12
Thus, is it possible that measures
of 6MWD collected in Caucasian populations may be
inappropriate for use in the Singaporean population.
This study sought to (i) determine 6MWD in a
healthy sample of Singaporeans aged between 45 and
85 years; (ii) identify factors contributing to 6MWD;
and (iii) compare measured 6MWD with predicted
6MWD from existing reference equations derived
from Caucasian subjects.
METHODS
Healthy Singaporean male and female volunteers
performed three 6MWTs on a single occasion with
each test separated by a 20-min rest period. Before
performing the tests measurements were obtained of
age, height, weight, leg length, smoking history,
medical history, medication usage, spirometry and
self-reported habitual physical activity. The subject’s
preferred language was used in all interactions with
the subject.
Written, informed consent was obtained before
participation in the study, which was approved by
the Domain Specific Review Board of the National
Healthcare Group, Singapore and the Human
Research Ethics Committee of Curtin University of
Technology, Perth, WA, Australia.
Subjects
Thirty-five asymptomatic healthy Singaporean vol-
unteers, aged between 45 and 85 years, were
recruited from activity centres for the elderly and in
response to flyers distributed in the local community.
Exclusion criteria comprised: a history of symptom-
atic cardiovascular disease; a family history of arte-
riosclerosis; diagnosed hyperlipidaemia; resting
blood pressure >150/100 mm Hg; resting heart rate
(HR) >100 beats per minute (b.p.m.); abnormal lung
function (FEV1 < 80% predicted or FEV1/FVC < 70%);
blood or metabolic disorders; current illness, includ-
ing upper respiratory tract infection in the past
4 weeks; use of ambulatory aids; leg length discrep-
ancy >3 cm; severe, disabling pain of musculoskeletal
origin and answering ‘yes’ to any of the questions on
the Physical Activity Readiness Questionnaire (PAR-
Q).13,14
An affirmative response on the PAR-Q indi-
cates that consultation with a physician is necessary
before participating in physical activity. Subjects
were also excluded if they had performed the 6MWT
previously.
Protocol and measurements
Subjects attended one testing session and were asked
to avoid caffeine, alcohol and consumption of a heavy
meal for at least 2 h before testing and strenuous exer-
cise in the previous 24 h.
Six-minute walk tests
The 6MWT protocol used was based on published
guidelines,15
and a straight 45 m indoor track along a
hospital corridor was used. The same investigator
(H.P.) supervised all tests. Standard pretest instruc-
tions were provided. Subjects were told to ‘walk as
quickly as you can for 6 min so that you cover as
much ground as possible’. Subjects were informed
that they could slow down or rest if necessary. At the
end of each minute subjects were given feedback on
the elapsed time and standardised encouragement
in the form of statements such as ‘you’re doing well,
keep it up’ and ‘do your best’. HR was measured 5
min before the initial test, at 1 min before the start
of each test and at the end of each min during all
tests using a telemetric HR monitor (Polar Favor,
Electro Oy, Kempele, Finland).16
Leg fatigue was
rated at the end of each test using a modified Borg
0–10 scale.17
Spirometry
FEV1 and FVC were measured using a portable
spirometer; (SpiroPro® Handheld Spirometer by
SensorMedics©, Bilthoven and in accordance with
recommended guidelines).18
Predicted FEV1 and FVC
were calculated from regression equations developed
for the local ethnic groups.19
Anthropometric data
Height and weight were measured using a calibrated
stadiometer. BMI (weight/height2
) was calculated.
Leg length on both right and left sides was measured
while standing and was taken as the distance from the
greater trochanter of the femur to the lateral border

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
standard questionnaire.20
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
physical activities.20
Where subjects were unable to
read or understand the questions, the question-
naire was conducted verbally by one investigator
(H.P.).
Data analysis
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
variation (CV).
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-
mum 6MWD.
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
using scatter
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
submaximal.
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.
RESULTS
Subject characteristics
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)
Characteristic
Mean ± SD or
number of subjects
Man/women 16/19
Age (years) 61.0 ± 8.3
Ethnicity
Chinese 32
Indian 2
Eurasian 1
Height (cm) 157.3 ± 9.0
Weight (kg) 58.9 ± 13.3
BMI (kg/m2
) 23.6 ± 3.9
Smoking history
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
(R2
= 0.78).
Comparison with published regression
equations
Comparisons between the 6MWD measured in our
Singaporean subjects with 6MWD derived from pub-
lished equations9,10
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
(Fig. 1)
(P < 0.001) and 86 ± 95 m (95% CI: 53–119 m)10
(Fig. 2)
(P < 0.001).
DISCUSSION
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
Singaporean cohort.
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
with Caucasians.12
Lean body mass is a predictor of
exercise capacity in healthy subjects.21
Other causes
may include differences in the speed of habitual walk-
ing and walking efficiency between Caucasians and
Singaporean Asians. The Caucasian subjects in previ-
ous studies9,10
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
shown.
Predicted 6MWD (m)
400 500 600 700 800 900
Measured6MWD(m)
Bestfromtest1and2
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
Measured6MWD(m)
Bestof3tests
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
Our 6MWT
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
6MWT9,10,24
and in this study the magnitude of the
learning effect was similar to previous reports in
healthy subjects.9,10,24,25
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
previous studies.9,10
Consistent with Troosters et al.,9
an inverse relationship between weight and 6MWD
was found; however, in contrast to Gibbons et al.,10
we
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-
sian subjects.11
When adjusting this threshold to 27,
the value used to identify Singaporean Chinese as
obese only six subjects were classified as obese.29
The
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
6MWD.11
Including an assessment of mood may also
be valuable as high levels of depression exist in
COPD30
and CHF,31
patient populations frequently
assessed using the 6MWT.
ACKNOWLEDGEMENTS
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
(No. 294404).
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