the pace of life - reanalysed
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8/17/2019 The Pace of Life - Reanalysed
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The Pace of Life - Reanalysed: Why Does Walking Speed of Pedestrians Correlate with City
Size?Author(s): Peter Wirtz and Gregor RiesSource: Behaviour, Vol. 123, No. 1/2 (Nov., 1992), pp. 77-83Published by: BRILLStable URL: http://www.jstor.org/stable/4535062 .
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Behaviour23
(1-2)
1992,
E.
J.
Brill,
Leiden
THE PACE OF LIFE
-
REANALYSED: WHY DOES WALKING
SPEED OF PEDESTRIANS
CORRELATE
WITH
CITY
SIZE?
by
PETER
WIRTZ')
and
GREGOR
RIES2)
(Institut
fur
Biologic
der
Universitat
Freiburg
and
Forschungsstelle
fur
Humanethologie
in der Max
Planck
Gesellschaft)1
(With
3
Figures)
(Acc. 29-X-1992)
Summary
In a
much
quoted study,
BORNSTEIN
BORNSTEIN
1976)
showed that the
walking speed
of
pedestrians
is
positively
correlated
with the
size of the
city.
They interpreted
the
higher
walking speed
of
people
in
larger
cities
as a
psychological response
to
stimulatory
overload.
We also found a
positive
correlation between
walking
speed
and
city
size.
In
addition,
we
showed that
-
at
least
in
our
sample
-
larger
cities
had
higher proportions
of
young
males
and lower
proportions
of
people
older than 60
years.
Walking
speed
and
momentary
density
did
not correlate
positively.
Because
walking speed
is
age-
and
sex-dependent (Fig.
2),
differences in
population
structure are
likely
to cause
differences
in
average walking speed.
The
average walking
speed predicted
for each
city according
to its
age-
and
sex-composition
correlated
positively
with
city
size. The
regressions
of
observed
walking
speed
on
population
size
and of
walking
speed
predicted
from
age
structure
on
population
size
did no differ
significantly
in their
slopes (p
>
0.95).
It
therefore seems
unnecessary
to invoke
other factors
in
addition to
age
composition
to
explain
differences
in
average
walking
speeds
of
pedestrians.
Introduction
With the
catching
titel
The
pace
of life
BORNSTEIN
BORNSTEIN
(1976)
published
the
results of a
much
quoted study
showing
that
the
walking
speed
of
pedestrians
is
positively
correlated
with the
size of
the
city.
The
measurements
of the
walking speed
of,
on
average,
20
people per city
were
taken on the main
roads
of
15 towns
or cities in
the
USA, Ireland,
Germany,
Israel,
Greece and
Czechoslowakia,
ranging
in
size
from 365
to
2.6 million inhabitants. Later,
BORNSTEIN
(1979) published additional
1)
Address
for
correspondence:
Dr. P.
WIRTZ,
Universidade da
Madeira,
Largo
do
Colegio,
P-9000
Funchal,
Portugal,
Madeira.
2)
Many
thanks
for
helpful
discussions
to
colleagues
at
the
Forschungsstelle
fur
Human-
ethologie
der
Max
Planck
Gesellschaft
and in
the
Wickler
department
of the
Max
Planck
Institut fur
Verhaltensphysiologie.
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WIRTZ
& RIES
measurements
from six
further
cities,
confirming
the
initial result.
The
psychologists
M.
& H.
BORNSTEIN
interpreted
the
higher walking speed
of
people in larger cities as a response to stimulatory overload: increased
walking
speeds
serve to minimize
environmental
stimulation .
In
our
study,
which
measured
the
walking speeds
of
people
at
14
different
places
in
Germany,
France,
Switzerland and
Italy,
we also
found
a
positive
correlation between
walking speed
of
pedestrians
and
city
size.
In
addition,
we
attempted
to find
the
proximate
reason that
directly
determines
walking
speed
and
apparently
somehow correlates
with
city
size.
Material and
methods
Following
the
procedure
described
by
BORNSTEIN
BORNSTEIN
(1976)
we
measured the
walking
speed
(the
time
taken to cover a
distance of
15 to
20
m)
of
123
to
1258
pedestrians
on
the main
shopping
roads of 14 cities
varying
in
population
size
from
5200
to more than
2
million
(Table 1).
As
the measurements
were taken between
November and
April,
tempera-
tures were lower than in
BORNSTEIN'S
study
(between
0 and
10°C
versus
24°C).
To
avoid
observer
bias,
the
first
single
unobstructed
person entering
the
measuring
strip
was
chosen
as a
subject
in
every
case.
In
addition,
we noted
the
follwing
variables:
-
number of
people walking
in
the
opposite
direction and
passing
the
observed
subject
while that
person
was
crossing
the
measurement
strip,
TABLE
1.
Population
size,
sample
size,
walking speed
and
sample
composition
towns
and
cities
place
population
N
subjects
V
%20-30 males %>60
VD
Berlin
2157695 1033
1.36
8.02 23.15
1.37
Hannover
505875
985
1.46
24.99
6.22
1.44
Karlsruhe
268309
291
1.46
25.78
14.10
1.43
Freiburg
185669
1258 1.39
12.71 16.89
1.40
Basel
175000
904
1.44
9.49
14.95
1.39
Varese
89146
253
1.36
10.68
9.90 1.41
Colmar
66694
326
1.35
8.88
17.78
1.40
Lahr
34566
293
1.40
12.28
12.60
1.42
Emmendingen
23653
502 1.41
7.76
17.73
1.39
Waldkirch
18879
489
1.35
4.70
22.53
1.37
Bad
Krozingen
12084 275
1.33
1.10 40.37
1.32
Breisach
10021 274
1.48
5.73
23.00
1.38
Laveno
8830
123
1.28 5.68
28.47
1.36
PonteTresa
5200 253
1.22
4.32 29.66
1.37
V
=
average
walking
speed
of
pedestrians
ms-1)
%20-30 males
=
percent
20-30
year
old
males
in
the
population;
%>60
=
percent
of
people
older
than 60
years
n
the
population;
VD
=
walking
peedpredicted
from
age-
and
sex-composition.
78
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79
-
number of
people
on the measurement
strip
immediately
after the
subject
had left
it,
-
sex
of the
subject,
-
estimated
age
of the
subject
in
the
classes
15-20, 21-30, 31-40,
41-50, 51-60,
older than
60 years (persons estimated to be younger than 15 years were not counted).
Results
Walking
speed
and
city
size.
Average
walking speed
(V)
correlated
positively
with the
logarithmic
value
of
city
size
(logpop),
following
the
equation
V = 0.043
x
logpop
+ 1.169
(r
=
0.461, p
<
0.05, one-tailed).
Figure
1
shows the
relation between
walking speed
and
city
size for all
36 cities for
which
data
are
available
(BORNSTEIN
&
BORNSTEIN, 1976;
BORNSTEIN,
979,
this
study,
plus
a value for the German
city Offenburg
1.8- ·
1.6
-
E
14
IC
E 1.4--
V0
_
.
1.2-
.' 1.0
-
/
*
·
.0
-
0.8-
0.6
-
i
I
I I I
I
I
I
100 1000 10000 100000 1000000
population
size
Fig.
1.
The relation between
average walking speed
of
pedestrians
and
city
size.
based on
the
walking speed
of
1232
pedestrians
measured
by
S.
KoPKA
during
a student's
practical:
V
=
1.52
m/s,
logpop
=
4.7).
The
equation
for the total
sample
is
V = 0.19 x logpop + 0.42
(r
=
0.76,
p
<
0.0001,
two-tailed).
Walking speed
and
momentary
density
of
people.
For the
city
of
Freiburg
(the
place
with
the
highest
sample size),
we
correlated the
walking
speed
of
pedestrians
with
two
measures of
momen-
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WIRTZ & RIES
tary density,
namely
number of
people
walking
in the
opposite
direction
and
passing
the observed
subject
while
that
person
crossed the
measure-
ment strip and number of people on the measurement strip imme-
diately
after the
subject
had left
it ;
we also correlated
walking speed
with
the
logarithmic
values of these two measures. The
walking
speed
of
neither
male nor female
subjects
correlated
with
these
variables;
the
resulting eight
correlation coefficients
ranged
between -0.003 and
-0.19,
none
of
them
approachig
significance
level.
Walking speed
and
age
or sex
of
subject.
It
is,
of
course,
well known that males tend to walk faster than females and
that older
people
tend to
walk
slower than
younger people
(references
in
WALMSLEY
LEWIS,
1989). Higher
walking
speed
of males is due to
larger
stride
length
and not to
higher
stride
frequency
(S.
KOPKA& C.
KRAMER,
unpublished
students'
report).
The
average
walking speed
of
males and
females of
each
age
class was calculated
separately
for
every city.
The
mean of these
means
gives
a
walking
speed
typical
for each
age-
and
sex-
class and
independent
of
city
size.
The
relation between
walking
speed
and
age
or
sex is shown
in
Fig.
2.
City
size and
population composition.
Because
walking speed
was found to be
age-
and
sex-dependent,
we
tested
whether cities of different sizes
differed
in
their
population composition.
In
our
sample, population composition
covaried with
city
size
in a
system-
atic
way:
larger
cities tended to have
higher proportions
of
20
to
30
year-
old
males,
i.e.
higher
proportions
of the fastest
walking
class
(r
=
0.62,
p
<
0.02,
two-tailed)
and
larger
cities tended
to
have lower
proportions
of
people
older
than
60
years,
i.e.
lower
proportions
of the two slowest
walking
classes
(r
=
-0.56,
p
=
0.03,
two-tailed):
Table 1.
Walking speed
and
population composition.
Because
larger
cities have
higher
proportions
of
people
that
walk
fast and
lower proportions of people that walk slowly, differences in age- and sex-
composition
could
perhaps already
explain
the faster
walking speeds
observed in
larger
cities.
Using
the data on
age
and
sex of the
people
measured in
each
city,
and
using
the
average age-
and
sex-specific
walk-
ing
speeds
calculated
previously,
a
demographic walking
speed
VD
was
calculated;
this is
the
average
walking
speed predicted
for each
city
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81
1.6
-
male
w
1.5_
*
female
E
1.4
-
U
1.3-
'
1.2-
o
1.1-
i
I I I
60
age (years)
Fig.
2.
Average walking
speed
of
men and women
of different
age
classes.
*
observed
o
expected
1.5
-
@ 0
0
o obs.
lo·
_
_ ,
__
exp.
Q.
'
1.3-
100
100
1 0 1
1000 10000 100000
1000000
population
size
Fig.
3.
Walkingspeed
observed and
predicted
from
age-
and
sex-composition.
according
to its
age-
and
sex-composition
and
independent
of
its size
(Table
1).
Demographic
walking
speed
was
positively
correlated with
population
size,
indicating
that
differences
in
the
age
and sex
composition
of
the
cities do
already
explain higher
walkings
speed
in
larger
cities. The
regression
equation
was
VD
=
0.02
x
logpop
+
1.29
(r = 0.502, p = 0.07, two-tailed).
The
unexpectedly
low
walking
speed
at the
city
of Berlin
apparently
is
caused
by
an
atypically
high
proportion
of
older
people
and an
atypically
low
proportion
of
younger
people
(see
Table
1).
Observed
walking
speed
V and
demographic
walking
speed
VD
were
positively
correlated with r
=
0.572
and
p
=
0.032,
two-tailed.
The
partial
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WIRTZ
& RIES
correlation coefficient between
city
size and
observed
walking
speed
was
0.346
(p
>
0.10,
two-tailed),
i.e.
considerably
smaller
than
the
partial
correlation coefficient of 0.579 (p <.05, two-tailed) between demo-
graphic
walking speed
and observed
walking speed.
Figure
3
compares
the
walking
speeds
measured
in
the
14
cities and the
demographic
walking speeds
calculated
for
these
places.
The
slopes
of
the two
regression
lines were
compared
by analysis
of covariance.
They
do
not differ
significantly (p
>
0.95).
Discussion
BORNSTEIN & BORNSTEIN
(1976)
measured the
walking speeds
of,
on aver-
age, only
20
people per
city.
Even had
they
thought
of
it,
they
would have
been unable to test for the influence
of
the
age
composition
of the
population
on
walking speed
in
their data.
We
have shown
that
-
in
our
data
set,
at least
-
the
populations
sampled
in
different cities did
not
have
the same
age
structure.
Apparently, systematic
differerences
in
the
age
structure of the
14
cities observed
by
us
already
explain higher walking
speed in larger cities.
The variance
in
measured
walking
speed
is much
greater
than that in
demographic walking speed. Clearly,
other
factors
than
age
and sex
influence
walking
speed.
In
the towns of
Varese,
Colmar, Laveno,
and
Ponte
Tresa
walking speed
was
much lower
than
that
predicted
from
population
composition.
A
more leasure life
style
in Latin
towns than
in German
ones is
one
of
several
speculations
one
might
put
foreward as a
possible
reason.
Another factor whose
influence would
have to be consid-
ered in future studies is body size: in the northern hemisphere, southern
populations
of
Homo
sapiens
tend to
be smaller than
northern
ones and
therefore
probably
have shorter
stride
lengths.
In
the
study
by
BORNSTEIN
& BORNSTEIN
(1976),
small
towns
were
predominantly
from
southern
areas
and
large
cities
predominantly
from
northern areas
-
the
possible
reason for a much
larger
regression
coefficient
in
the
equation
found
by
BORNSTEIN& BORNSTEIN
(1976).
In
addition to
differences
in
age
structure,
sex
composition,
and
aver-
age body size, psychological phenomena such as the one envisioned by
BORNSTEIN & BORNSTEIN
(1976)
could
influence the
average
walking speed
of
pedestrians.
The
observation
that there was no
positive
correlation
between
walking speed
and
momentary density (if any,
the trend was a
negative correlation)
argues against
the
particular
explanation
offered
by
BORNSTEIN
&
BORNSTEIN.
If
increased
walking speed
served
to
reduce
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83
stimulatory
overload we
would
expect higher
walking speeds
at
higher
densities.
The regression of observed walking speed on population size and the
regression
of
walking
speed predicted
from
age
and
sex
composition
on
population
size
resulted
in
two
slightly
different lines
(Fig.
3).
The
slope
of
the curve
with the observed
walking
speed
is the
steeper
of the
two,
indicating
that there
might
be an
additional factor
correlating
positively
with
population
size.
The statistical
comparison
of
the
two
lines,
however,
showed that there is
a
97%
probability
of the
difference
between the
lines
being
a
chance
product.
At
present,
it
therefore seems
unnecessary
to
invoke additional factors other than age composition to explain the
differences
in
average walking
speeds
of
pedestrians.
References
BORNSTEIN,
. H.
(1979).
The
pace
of
life:
revisited.
-
Int.
J.
Psychol.
14,
p.
83-90.
-&
BORNSTEIN,
. G.
(1976).
The
pace
of
life.
-
Nature
259,
p.
557-559.
WALMSLEY,
.J.
&
LEWIS,
G.J. (1989).
The
pace
of
pedestrian
flows
in
cities.
-
Environ-
ment
and Behaviour
21,
p.
123-150.
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