Gait Variability and Quality of Life in Postmenopausal Women
Ronaldo Gabriel
1
, Helena Moreira
2
, Patrícia Soares
3
, Catarina Abrantes
2
,
Florbela Aragão
4
and Aurélio Faria
5
1
Department of Sport Sciences, Exercise and Health, Center for the Research and Technology of Agro-Environmental and
Biological Sciences (CITAB), University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
2
Department of Sport Sciences, Exercise and Health, Research Center in Sports Sciences, Health and Human Development
(CIDESD), University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
3
Department of Sport Sciences, Exercise and Health,University of Trás-os-Montes and Alto Douro, Vila Real, Portugal
4
Research Center in Sports Sciences, Health and Human Development (CIDESD), University of Trás-os-Montes and Alto
Douro, Vila Real, Portugal
5
Department of Sport Science, Research Center in Sports Sciences, Health and Human Development (CIDESD),
University of Beira Interior, Covilhã, Portugal
1 OBJECTIVES
The study of gait variability offers a complementary
way of quantifying locomotion and its changes with
aging (Hausdorff, 2005) and may contribute to
improving the quality of life of women after
menopause. The aim of this study was to describe
gait variability at usual walking speed in
postmenopausal women and to evaluate the
influence of this variability in the quality of life.
2 METHODS
2.1 Subjects
The sample include 31 postmenopausal women
physically active. Before inclusion in the study the
reproductive and medical history of each woman
was collected and the following inclusion criteria
been observed: (a) absence of premature menopause
(Shuster et al., 2010); (b) nonexistence of acute pain
or foot deformities; (c) no surgery of the lower limbs
as the application of prosthesis of the hip, knee or
foot; (d) absence of visual and auditory disorders
that may compromise the testing and; (e) no
peripheral neuropathy related to diabetes. The
marked discrepancy in the length of legs and the
presence of cognitive impairment were considered
exclusion criteria of the study. The survey was
conducted in accordance with the Declaration of
Helsinki (WMA, 2013) and approved by University
of Trás-os-Montes and Alto Douro. An informative
written consent was obtained from each participant.
2.2 Procedures
Quality of life was measured using the Menopause-
Specific Quality of Life (MENQOL) questionnaire
(Hilditch et al., 1996). This questionnaire is a 29-
item validated instrument that assesses the effects of
the items, divided into 4 domains, physical (16
items/11-26), vasomotor (3 items/1-3), psychosocial
(7 items/4-10) and sexual (3 items/27-29) on quality
of life in postmenopausal women. The reliability of
this questionnaire was evaluated in Portuguese
postmenopausal women by Serrão (2004). Mini
Mental State was used to assess the cognitive state
of participants (Folstein et al., 1975).
Height (H) was determined by a stadiometer (SECA
220, Seca Corporation, Hamburg, Germany) and
trochanteric height (right and left limb) was
evaluated with the segmometer (Rosscraft, Blaine,
USA), being complied with the procedures described
in the literature (Heyward & Wagner, 2004). The
body mass index (BMI) was calculated using the
formula: BMI (kg/m
2
) = W/H
2
.
Gait data were collected using a portable wireless
system of inertial sensors (BTS G-WALK; BTS
Bioengineering Corp., Brooklyn NY, USA), with
sample rate of 100 Hz, that when positioned around
the patient’s waist (on L5 vertebrae) allows for a
valid, reliable and accurate functional gait analysis
(Bugane et al., 2012). The subjects were asked to
stand up and remain in the up-right posture for a few
seconds, and then to walk barefoot along a 9-m
horizontal pathway, at a self-selected speed. This
entailed 9–10 steps, according to the subject’s
natural cadence; the central three, for the right and
left full gait cycles, were analysed. Six trials were
collected for each participant. From the collected
Gabriel R., Moreira H., Soares P., Abrantes C., Aragão F. and Faria A..
Gait Variability and Quality of Life in Postmenopausal Women.
Copyright
c
 2014 SCITEPRESS (Science and Technology Publications, Lda.)

signals, spatial-temporal gait parameters are then
obtained.
2.3 Intra-Individual Variability
The Coefficients of Variation (COV), was used to
quantify the intra-individual variability of the
spatial-temporal gait parameters obtained. Both right
and left gait parameters were used because they
were not statistically different. The COV, [Standard
Deviation (SD) / mean] 100%, was determined over
the six successive trials to express the percentage
variation in a subjects’ gait between successive
trials.
3 RESULTS
The Table 1 express the descriptive analysis of the
data.
Table 1: Descriptive analysis of age, time since
menopause, quality of life and anthropometric parameters.
(n=31).
Variables
Mean

SD
Range
Age (years)
61.204.96
52.61 – 72.56
Time of Menopause (years)
12.616.45
12.61 – 28.00
Anthropometry
Weight (kg)
65.888.41
44.87 – 83.38
Height (m)
1.560.04
1.45 – 1.63
Body Mass Index (kg/m
2
)
27.023.37
19.01 – 33.83
Quality of Life
Total of Scale (points)
8
0.8727.94
33.00 – 150.00
The spatio-temporal gait parameters are shown in
Table 2.
Table 2: Descriptive analysis of the spatio-temporal gait
parameters.
Spatio-Temporal Gait Parameters
Mean

SD
Range
Speed (m/s)
1.580.27
1.02 – 2.03
Cadence (steps/min)
113.657.80
98.61 –133.89
Stride Length (m)
1.530.21
1.10 – 1.92
Stride Length/Height (%)
97.6012.96
67.92 –121.19
Stride Duration (sec)
1.060.07
0.90 – 1.20
Stance Phase Duration (%)
63.262.55
58.37 – 69.34
Swing Phase Duration (%)
36.742.55
30.66 – 41.63
Double Support Duration (%)
13.362.45
8.30 – 18.60
Single Support Duration (%)
36.762.32
32.12 – 41.72
Single Support Slope (º)
7.321.25
4.96 – 10.41
Variability of Speed (%)
24.076.51
7.11 – 35.54
Variability of Cadence (%)
3.451.18
1.44 – 6-01
Variability of Stride Length (%)
21.065.97
8.31 – 31.82
Variability of Stride Length/Height (%)
21.065.97
8.29 – 31.81
Variability of Stride Duration (%)
3.601.14
1.47 – 6.44
Variability of Stance Phase Duration (%)
2.851.41
1.01 – 7.09
Variability of Swing Phase Duration (%)
5.123.07
1.65 – 14.62
Variability of Double Support Duration (%)
12.125.39
4.14 – 24.73
Variability of Single Support Duration (%)
5.383.18
1.49 – 14.15
Variability of Single Support Slope (%)
14.446.36
5.28 – 29.30
The correlations of spatial-temporal parameters of
walking with the quality of life is shown in Table 3.
Table 3: Correlation of spatio-temporal gait parameters
with the total scale for assessing quality of life.
Spatio-Temporal Gait Parameters Correlation
Speed (m/s) -0.40*
Cadence (steps/min) -0.65**
Stride Length (m) -0.24
Stride Length/Height (%) -0.24
Gait Cycle Duration (sec) 0.68**
Stance Phase Duration (%) 0.33
Swing Phase Duration (%) -0.33
Double Support Duration (%) 0.31
Single Support Duration (%) -0.31
Single Support Slope (º) -0.28
Variability of Speed (%) -0.08
Variability of Cadence (%) 0.47**
Variability of Stride Length (%) -0.13
Variability of Stride Length/Height (%) -0.13
Variability of Stride Duration (%) 0.40*
Variability of Stance Phase Duration (%) 0.44*
Variability of Swing Phase Duration (%) 0.47**
Variability of Double Support Duration (%) 0.21
Variability of Single Support Duration (%) 0.40*
Variability of Single Support Slope (%) 0.25
*p≤ 0.05, **p≤ 0.01
4 DISCUSSION
There is a “younger” behaviour of the sample of this
study. The positive association between quality of
life and variability of spatio-temporal gait
parameters which have small variability should be
investigated in future studies examining stability of
performance in activities of daily living to avoid the
falls. Therefore, is necessary a theoretical
framework to understand those results.
ACKNOWLEDGEMENTS
This work is supported by national funds by FCT -
Portuguese Foundation for Science and Technology,
under the project PEst-OE/AGR/UI4033/2014.
REFERENCES
Bugane F, Benedetti M, Casadio G, Attala S, Biagi F,
Manca M, et al., 2012. Estimation of spatial-temporal
gait parameters in level walking based on a single
accelerometer: validation on normal subjects by
standard gait analysis. Computer Methods and
Programs in Biomedicine;108(1):129-137.
Folstein, M., Folstein, S., Mchugh, P., 1975. Mini-Mental
State: practical method for grading cognitive state of
patients for clinician. Journal of Psychiatric Research;
12(3), 189-198.
Hausdorff J., 2005. Gait variability: methods, modeling
and meaning. Journal of Neuroengineering and
Rehabilitation; 2:19.
Heyward V., Wagner D., 2004. Applied body composition
assessment. Humn Kinetics. Champaign.
Hilditch J., Lewis J., Peter A., et al., 1996. A menopause-
specific quality of life questionnaire: development and
psychometric properties. Maturitas;24(3):161-175.

Serrão C., 2004. Climatério feminino: representações ,
qualidade de vida e sintomatologia. Braga:
Dissertação de Mestrado em Psicologia da Saúde,
Braga. Universidade do Minho.
Shuster L, Rhodes D, Gostout B, Grossardt B, Rocca W.,
2010. Premature menopause or early menopause:
long-term health consequences. Maturitas; 65(2):161-
166.
WMA, 2013. WMA Declaration of Helsinki: ethical
principles for medical research involving human
subjects. World Medical Association. Fortaleza.