Journal of Physical Activity and Health, 2011, 8, 841 -847
© 2011 Human Kinetics, Inc.
Differences in Association of Walking for Recreation
and for Transport With Maximum Walking Speed
in an Elderly Japanese Community Population
Masamitsu Kamada, Jun Kitayuguchi, Kuninori Shiwaku, Shigeru Inoue,
Shimpei Okada, and Yoshiteru Mutoh
Background: Physical activity contributes to maintaining functional ability later in life. Specific relationships
between walking for particular purposes (eg, recreation or transport) and functional ability are not clear. It is
useful for planning health promotion strategies to clarify whether walking time for recreation, or walking time
for transport has the stronger relationship with maximum walking speed (MWS), a determinant of functional
ability later in life in the elderly. Methods: A cross-sectional survey was conducted in 2007 using a sample of
372 community-dwelling elderly people aged 60 to 87 years in Mitoya Town, Unnan City, rural Japan. Associations with MWS were examined for self-reported weekly times of walking for recreation and for transport
using multiple linear regression analyses. Results: Both in men and women, walking time for recreation was
significantly associated with MWS after controlling for age, height, weight, hip and knee pain, and a number
of chronic diseases (men: β = 0.18, P = .024; women: β = 0.17, P < .01). However, walking time for transport
was not significantly associated with MWS (men: β = –0.094, P = .24; women: β = –0.040, P = .50). Conclusions: Walking for recreation may contribute to maintaining functional abilities such as MWS in the elderly.
Keywords: physical activity, physical fitness, public health, older adults, epidemiology
Physical activity plays a role in maintaining functional ability later in life.1–4 Walking is the most common
physical activity behavior of adults and the elderly.5–7
Previous studies have shown the health benefit of walking behaviors.1,3,4,8,9 However, there has been little study
of the differences in the purposes of walking (eg, recreational vs. nonrecreational). If the intensities of walking
for recreation and for transport are different, effects of
those behaviors on health outcomes should be different,
and taking such differences into account could be useful,
in health education and the promotion of walking behaviors. Differences between specific associations of walking
for recreation or for transport with health benefits, such
as functional ability, have not been clearly identified.10
Maximum walking speed (MWS) is a good predictor of bone health11 and functional dependence12 in the
elderly and believed to be susceptible to walking behavior.13 The purpose of this study was to clarify specific
Kamada and Kitayuguchi are with the Physical Education and
Medicine Research Center UNNAN, Unnan, Japan. Shiwaku
is with the Dept of Environmental and Preventive Medicine,
Shimane University, Izumo, Japan. Inoue is with the Dept of
Preventive Medicine and Public Health, Tokyo Medical University, Tokyo, Japan. Okada is with the Physical Education
and Medicine Research Foundation, Tomi, Japan. Mutoh is
with the Graduate School of Education, University of Tokyo,
Tokyo, Japan.
relationships between walking for particular purposes and
maximum walking speed in the elderly. We hypothesized
that walking for recreation may have a greater influence
on functional ability, such as maximum walking speed,11
because this type of walking is assumed to be conducted
with higher levels of intensity compared with walking
for transport.
Methods
Study Location and Subjects
A cross-sectional survey was conducted in communitydwelling elderly in Mitoya Town (population 8241, area
82.7km2), Unnan City, Shimane Prefecture, in western
rural Japan in October 2007. This study was a part of a
Shimane study14 conducted concomitantly with an annual
health examination. All adults aged 20 years and above
then living in Mitoya were invited to participate in the
study by direct mail, local public broadcasts, cable television, circulars called kairanban, and city newsletters.
Figure 1 shows the flowchart of the recruitment. The following inclusion criteria were used for each subject: aged
60 years and over, community-dwelling, and a participant
in a Shimane study conducted concomitantly with the
subject’s annual health examination. Exclusion criteria
applied were those individuals in assisted living facilities, those requiring nursing care, and those who walked
841
842 Kamada et al
Figure 1 — Subject recruitment.
using an assistive device. Data on 372 elderly people who
qualified as subjects (132 men and 240 women) aged 60
to 87 years (70.5 ± 5.8) were used in the analyses.
Walking Behavior
We investigated average walking time for recreation
(including for both exercise and leisure) and for transport
(to or from work, shopping, to access public transportation, etc.) over a typical 7-day period (min/w), using a
self-administered questionnaire and a face-to-face interview for confirmation. Subjects were asked to address
only their walking activities lasting for at least 10 minutes
at a time. This questionnaire and interview confirmation
method had an acceptable 1-week test-retest reliability
(Spearman’s ρ = 0.79, P < .01) in 43 elderly people (22
men and 21 women) aged 75.7 ± 4.6 years in Kisuki
Town, adjacent to Mitoya, in Unnan City. A validity test
with a 1-week walking diary was also conducted in Kisuki
with another group of 44 elderly people (12 men and
32 women) aged 72.7 ± 5.2 years. These subjects were
provided with walking diaries and were asked to make
daily records of their start and finish times and purpose of
all walking activities continuing for at least 10 minutes.
This validity test showed acceptable results of walking
times for recreation (Spearman’s ρ = 0.49, P < .01) and
for transport (Spearman’s ρ = 0.38, P = .013). Results of
a validity test for total walking time with average daily
step counts recorded by a uniaxial accelerometer (Lifecorder, Suzuken Co. Ltd., Nagoya, Japan)15,16 were also
acceptable (Spearman’s ρ = 0.41, P < .01) in 93 elderly
people (35 men and 58 women) aged 73.7 ± 5.0 years in
Kisuki. The questionnaire used in this study is originally
in Japanese and available online.17
Maximum Walking Speed (MWS)
Walking speed was measured once by trained examiners
using digital stopwatches and a 10-m course set between
the 2- and 12-m marks of a 14-m straight, flat, indoor
walkway. We asked subjects to walk as fast as they safely
could without running on the walkway course. The high
reliability of walking (gait) speed measurements have
been reported previously.13
Other Measurements
Subjects underwent anthropometric measurements and
questionnaires with face-to-face interviews covering
chronic musculoskeletal pain in the hip and knee,18,19 and
chronic diseases (cerebrovascular disorder, diabetes, heart
disease, liver disease, lung disease, hypertension).2,20
Data and Statistical Analyses
Differences by gender were examined by t test for variables with normal distributions and Mann-Whitney test
for variables with nonnormal distributions. Correlations
with MWS were calculated by Pearson correlation for
age, height, weight, and body mass index and Spearman’s ρ for musculoskeletal pain, a number of chronic
diseases, walking time for recreation, and walking time
for transport with nonnormal distributions. The correlations between walking times for recreation and for transport were calculated by Spearman’s ρ. Multiple linear
regression models were used with MWS as the dependent
variable and walking times for recreation and for transport as the independent variables separately by gender.
Adjustments were made for selected variables whose P
values were 0.10 and under in univariate analyses with
Walking Behavior and Walking Speed in the Elderly 843
MWS based on age, height, weight, hip and knee pain,
and/or a number of chronic diseases for model 1 and by
all these potential confounding factors for model 2. Data
on walking for recreation and for transport were simultaneously analyzed in multiple linear regression analyses.
Significance was set at a level of P < .05. Analyses were
conducted using SPSS 14.0J for Windows (SPSS Japan
Inc., Tokyo, Japan, 2006)
This study was approved by the research ethics committee of the Physical Education and Medicine Research
Center UNNAN. All the subjects took part in the study
after signing informed consent forms.
Results
Subject characteristics are shown in Table 1. The mean
values of MWS were 2.2 ± 0.4 m/s in men and 2.0 ± 0.4
m/s in women. The mean walking times for recreation
and for transport were 66 ± 101 min/w and 26 ± 51
min/w, respectively, in men, and 47 ± 87 min/w and 35
± 70 min/w, respectively, in women. The median values
of walking times for recreation and for transport were 0
min/w for both men and women. About 40% of the subjects engaged in walking for both recreation and transport,
while 37.9% of the subjects engaged in neither. Although
a direct comparison cannot be made, the prevalence of
recreational walkers in our study was similar to national
data of annual participation rates of walking for recreation
in Japanese elderly (47.2% for 60–69 year-olds; 35.6%
for 70+ year-olds).21 Women were more likely to be
younger, have smaller height and weight, have hip and
knee pain, and have lower MWS, compared with men.
MWS was significantly correlated with age and
walking time for transport in men and with age, height,
hip and knee pain, number of chronic diseases, and
walking time for recreation in women (Table 2). The
correlation between walking times for recreation and
for transport was not significant (men: Spearman’s ρ =
–0.048, P = .59; women: Spearman’s ρ = 0.038, P = .56,
not shown in tables).
Table 3 shows the results of multiple linear regression analyses. Both in men and women, walking time
for recreation was positively and significantly associated
with MWS after controlling for potential confounding
factors. However, walking time for transport was not significantly associated with MWS. Each model explained
22% of the variance of MWS in men and 25% in women.
Results did not change much and the model R2 values
decreased somewhat when walking times were analyzed
as categorical variables divided into nearly 3 equal parts
Table 1 Subject Characteristics (Shimane, Japan, 2007)
Men (n = 132)
Women (n = 240)
Mean ± SD
or Number (%)
71.7 ± 5.8
17 (12.9)
Mean ± SD
or Number (%)
69.8 ± 5.7
48 (20.0)
65–69
30 (22.7)
73 (30.4)
70–74
41 (31.1)
69 (28.8)
75–79
33 (25.0)
35 (14.6)
Age (years)
60–64
80+
11 (8.3)
15 (6.3)
161.1 ± 5.8
58.3 ± 8.6
22.4 ± 2.8
63 (47.7)
148.9 ± 5.2
50.1 ± 7.0
22.6 ± 2.9
154 (64.2)
0
56 (42.4)
118 (49.4)
1
56 (42.4)
102 (42.7)
2+
20 (15.2)
19 (7.9)
Walking time for recreation (min/w)
Walking time for transport (min/w)
Maximum walking speed (m/s)
66 ± 101
26 ± 51
2.2 ± 0.4
47 ± 87
35 ± 70
2.0 ± 0.4
Height (cm)
Weight (kg)
Body mass index (kg/m2)
Hip and knee pain
Number of chronic diseasesb
Pa
<0.01
<0.01
<0.01
0.60
<0.01
0.08
0.06
0.12
<0.01
Note. Sample sizes vary due to missing values.
a Compares prevalences by gender using t test for age, height, weight, body mass index, and maximum walking speed and Mann-Whitney test for others.
b Number of the following diseases: cerebrovascular disorder, diabetes, heart disease, liver disease, lung disease, hypertension.
Table 2 Correlations Between Maximum Walking Speed and the Measured Items
(Shimane, Japan, 2007)
Men (n = 132)
ρa
r or
–0.45
0.08
0.05
0.00
0.082
–0.17
0.17
–0.18
Age (years)
Height (cm)
Weight (kg)
Body mass index (kg/m2)
Hip and knee pain
Number of chronic diseasesb
Walking time for recreation (min/w)
Walking time for transport (min/w)
Women (n = 240)
r or ρa
–0.40
0.29
0.06
–0.10
–0.25
–0.13
0.19
–0.12
P
<0.001
0.37
0.61
0.97
0.36
0.058
0.059
0.040
P
<0.001
<0.001
0.37
0.13
<0.001
0.044
<0.01
0.061
Note. Sample sizes vary due to missing values.
a Pearson’s correlation coefficients (r) for age, height, weight, and body mass index and Spearman’s ρ for other variables with nonnormal distributions.
b Number of the following diseases: cerebrovascular disorder, diabetes, heart disease, liver disease, lung disease, hypertension.
Table 3 Multiple Linear Regression Analyses for the Assessment of Associations
Between Walking Behavior and Maximum Walking Speed (Shimane, Japan, 2007)
Model 1a
Model 2a
βb
P
βb
P
Walking time for recreation (min/w)
0.16
0.046
0.18
0.024
Walking time for transport (min/w)
–0.12
0.14
–0.094
0.24
–0.43
<0.001
–0.46
<0.001
Height (cm)
0.035
0.71
Weight (kg)
–0.14
0.18
0.10
0.21
–0.0037
0.97
Men (n = 132)
Walking behavior
Covariates
Age (years)
Hip and knee pain
Number of chronic
Adjusted
R2
diseasesc
of the model
–0.033
0.68
0.22
0.22
Women (n = 240)
Walking behavior
Walking time for recreation (min/w)
0.17
<0.01
0.17
<0.01
Walking time for transport (min/w)
–0.040
0.49
–0.040
0.50
Age (years)
–0.25
<0.001
–0.25
<0.001
Height (cm)
0.20
<0.01
0.19
<0.01
0.0088
0.89
Covariates
Weight (kg)
Hip and knee pain
Number of chronic
Adjusted
R2
diseasesc
of the model
–0.22
<0.001
–0.22
<0.001
–0.060
0.30
–0.062
0.30
0.25
0.25
Note. Sample sizes vary due to missing values.
a Model 1 is adjusted for covariates those P values were 0.10 and under in univariate correlation analyses with maximum walking speed (ie, age and
chronic diseases for men and age, height, pain, and chronic diseases for women) and model 2 is adjusted for all covariates.
b β is the standardized partial regression coefficient for maximum walking speed.
c Number of the following diseases: cerebrovascular disorder, diabetes, heart disease, liver disease, lung disease, hypertension.
844
Walking Behavior and Walking Speed in the Elderly 845
(ie, 0 min/w; >0 to <90 min/w; 90+ min/w), and body
mass index was not significantly associated with MWS
when it was analyzed in the models instead of height and
weight (data not shown).
Discussion
Both in men and women, walking times for recreation
had a significant relationship with MWS, while no
significant relationship was observed between walking
times for transport and MWS. Significant negative simple
correlations of walking times for transport in men and a
number of chronic diseases in women with MWS became
insignificant in multiple linear regression analyses.
As we hypothesized, one possible interpretation
of the observed stronger relationship of walking for
recreation with MWS is the greater intensity involved
with recreational walking in contrast to walking for
transport. We believe that if the elderly walk intentionally to improve and maintain health, the intensity of such
walking is greater than of those walks involving routine
activities of daily living (eg, walking around home, to
work, or for shopping).10,22 Our pilot study examining the
intensity of walking for recreation and for transport by
use of a walking diary and accelerometer in 16 Japanese
elderly individuals showed a trend of greater intensity
while walking for recreation than that of walking for
transport (unpublished data). However, we believe it
likely that in cases of elderly people engage in walking for
relaxation,23 the intensity of such walks are low, although
this form of waling is deemed to be recreational. Hills et
al conducted an experimental study on Australian adults
and reported “walking for pleasure” (included in walking
for recreation) was sufficient to improve cardiovascular
fitness in obese, but not normal-weight, individuals.24
There may be intra- and interpersonal variations in the
intensities of walking behavior. Further investigation is
needed to determine the intensities of walking for particular purposes.
Another possible cause of the lack of a significant
relationship between walking time for transport and
MWS is the lower standard deviation and the fewer
instances of transport-walking than walking for recreation
for this particular study population. In rural areas such
as Unnan City, where the automobile is a dominant and
necessary form of transportation, the interpersonal difference in walking times for transport is considered to
be small. Thus, it is possible we were unable to detect
any association between walking for transport and MWS
because of insufficient statistical power.
The mean age of our subjects was less than 75 years.
Shinkai et al suggested that MWS was most sensitive in
predicting future functional dependence for those aged
between 65 to 74 years, while usual walking speed was
most sensitive for people aged ≥75 years.12 Our observed
stronger relationship of walking time for recreation with
MWS, compared with walking time for transport, is also
believed to be based on the fact that MWS is a relatively
vigorous mobility index compared with other indices of
physical fitness (eg, usual walking speed) in the elderly.
These results did not contradict the health benefits of
active transport (ie, walking or bicycling for transport),
especially in younger adults.25
Previous study has shown that time spent in moderate to vigorous intensity physical activity significantly
decreased with aging, even though the number of counted
steps did not differ significantly.26 Recent recommendations for physical activity in older adults have stated the
importance of increased levels of aerobic activity over and
above the routine activities of daily living which include
light to moderate-intensity activity of less than 10 min
duration.1 Our present study also supports walking for
recreation as an effective moderate physical activity for
maintaining functional ability in the elderly. Both the
promotion of walking for recreation and improvement of
public transportation service to promote active transport
is needed, especially in rural areas.27
The determinants of walking behavior have been
reported to vary with the purposes of walking,28,29 so it
may be necessary to consider walking for recreation and
for transport as separate behaviors, especially in the case
of planning health promotion strategies and promoting
these behaviors. Differences between the specific association of walking time for recreation and for transport with
health benefits require further study.
In addition, the presence of hip or knee pain was
associated to low MWS in women. Musculoskeletal conditions have been suggested as determinants of physical
activity18 and functional ability19 in the elderly. Assistance
in the care and treatment of musculoskeletal conditions
may be of importance in promoting physical activity and
maintaining functional ability in the elderly.
Limitations
This study had several limitations. First, the exclusion of
other domains of physical activity,2,30 visual and mental
health status,31 and/or socioeconomic status,32 may cause
low model R2 values (0.22 and 0.25) in multiple linear
regression analyses. Assessment of how long the participants had been walking for recreation and for transport
would also provide important insight into their effects
on functional abilities. Second, our findings may not be
attributable generally to populations of elderly people in
other geographic locations, given that our subjects were
restricted only to Japanese elderly in a rural town. Finally,
we were unable to confirm any causality from this crosssectional study. There is the possibility of reverse causation in the observed associations (eg, participants with
higher MWS might be more capable of participating in
recreational activities). Future prospective and intervention studies focusing on differences in health outcomes of
walking for particular purposes would provide valuable
knowledge to health professionals.
In spite of these limitations, the results of this study
are notable in that they serve to advance our knowledge
of differences between walking for recreation and for
transport in association with maintained functional ability, which has not previously received much scrutiny.
846 Kamada et al
Conclusions
Elderly people with longer walking times for recreation
had faster MWS. However, walking time for transport
was not significantly associated with MWS. Walking for
recreation in addition to that for routine activities of daily
living may contribute to the maintaining of functional
ability in the elderly. Considering the several limitations
of this study, further research is needed to confirm the
differences in the health benefits associated with walking
for recreation and those for transport.
Acknowledgments
We greatly appreciate the cooperation of the participants and
staff members of the Shimane study. We also appreciate the
generous assistance provided by Mr. Roger Matthews, Mr.
Nicholas Zimmermann, and Ms. Atsuko Sato. This study was
supported by Health and Labor Sciences Research Grants from
the Japanese Ministry of Health, Labor and Welfare.
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