Neurological Sciences

, Volume 33, Issue 4, pp 779–784

Energy cost of spontaneous walking in Parkinson’s disease patients

Authors

    • Department of Sport, Nutrition and Health SciencesUniversity of Milan
  • Arsenio Veicsteinas
    • Department of Sport, Nutrition and Health SciencesUniversity of Milan
    • Centre of Sports Medicine Don C. Gnocchi Foundation
  • Susanna Rampichini
    • Department of Sport, Nutrition and Health SciencesUniversity of Milan
  • Emiliano Cè
    • Department of Sport, Nutrition and Health SciencesUniversity of Milan
    • Centre of Sports Medicine Don C. Gnocchi Foundation
  • Raffaello Nemni
    • Centre of Neurology Don C. Gnocchi Foundation
  • Giulio Riboldazzi
    • Parkinson’s Disease and Movement Disorders’ CentreOspedale di Circolo
  • Giampiero Merati
    • Department of Sport, Nutrition and Health SciencesUniversity of Milan
    • Centre of Sports Medicine Don C. Gnocchi Foundation
Original Article

DOI: 10.1007/s10072-011-0827-6

Cite this article as:
Maggioni, M.A., Veicsteinas, A., Rampichini, S. et al. Neurol Sci (2012) 33: 779. doi:10.1007/s10072-011-0827-6

Abstract

In healthy subjects, comfortable walking minimizes the energy cost (Ec) of locomotion. In Parkinson’s disease (PD) patients walking is slower than in healthy subjects: this may increase Ec. Our aims were to analyze gait and Ec in PD patients during walking, particularly at self-selected speed, and the possible pathological, mechanical, and cardiorespiratory limitations. Fourteen mild-to-moderate PD and 14 control subjects were enrolled. Subjects underwent 5-min walking tests at two speeds: self-selected and as-fast-as-possible speeds. Cardiopulmonary and gait parameters (heart rate, ventilation, gas exchanges, step count) were recorded. Velocity was reduced in PD compared to control subjects at both speeds (P < 0.05), and PD patients had shorter strides (P < 0.05) at both speeds and reduced cadence (P = 0.01) at fastest speed. No significant difference was found in Ec at self-selected (0.12 ± 0.04 versus 0.11 ± 0.02 mLO2 kg−1 m−1 in PD and control subjects, respectively) and maximal (0.14 ± 0.03 versus 0.15 ± 0.02  mLO2 kg−1 m−1 in PD and control subjects, respectively) speed. However, the Ec increment from self-selected to fastest velocity was significantly lower (P = 0.02) in PD patients. PD patients failed to walk at a self-selected speed, which minimizes the Ec. This could be mainly due to the inability to develop a wider stride. Cardiorespiratory adaptation was not affected, except for the possible reduced cardiac adaptation observed in some (28%) cases. Presumably, rehabilitation procedures that improve flexibility and step length may help maintain walking ability.

Keywords

Parkinson’s diseaseGaitSpontaneous walkingOxygen consumptionEfficiencyClinical scores

Introduction

Parkinson’s disease (PD) is a syndrome characterized by a number of symptoms leading to functional impairment during daily activities and reducing the individual’s quality of life [1, 2]. Gait disturbances occur early in these patients and seem to result from shortened step length [3, 4], reduced lower limb muscle strength and deficits of inter-limb coordination [5]. In addition, PD patients are frequently affected by altered cardiovascular response to exercise, mainly due to the physical deconditioning [6, 7]. Compared to age-matched controls, a lower maximal oxygen uptake (VO2max) and a higher submaximal heart rate (HR) for the same workload were therefore observed in PD patients [6].

With the exception of few observations on the stride frequency and length during walking in PD patients [1], we are not aware of studies on cardiorespiratory adaptation and energy cost (Ec) of spontaneous walking in these patients. Previous studies on energy costs in clinical populations have been focused on maximal tests, which provide valuable information but do not reflect the needs of the patient on a day-to-day basis. The only recent study which assessed walking economy in PD patients at slow velocities [8, 9] used fixed incremental speeds on a treadmill walk (which has shown to be different from overground walking), and did not evaluate the self-selected speed.

The purposes of this study were therefore: (1) to determine the cardiorespiratory response and the Ec of level-surface walking at two different speeds: the most comfortable self-selected speed and the maximal speed that could be achieved and tolerated for few minutes; (2) to evaluate whether the disease severity, quantified by current clinical scoring, may affect the Ec of locomotion and other metabolic and mechanical variables.

Methods

Subjects

Fourteen mild-to-moderate PD patients and 14 healthy age-matched control subjects were enrolled (Table 1).
Table 1

Sample demographic characteristics (m ± SD), clinical scoring and disease duration

 

PD (m ± SD)

C (m ± SD)

P value

Sex (M/F)

9/5

6/8

0.25§

Age (years)

67.9 ± 8.1

66.6 ± 5.3

0.62

Weight (kg)

74.2 ± 13.3

70.5 ± 9.9

0.43

Height (cm)

166.5 ± 8.2

165.3 ± 6.9

0.68

BMI (kg/m2)

26.5 ± 2.8

25.7 ± 2.4

0.43

Hoen and Yahr stage (1–5)

2.0 ± 0.6

UPDRS III (0–108)

12.7 ± 6.3

UPDRS I–III (0–176)

20.4 ± 15.4

Disease duration (years)

6.2 ± 4.1

§χ2 test, Student’s t test for independent samples

PD was diagnosed during outpatient visits according to clinical criteria [10]. An experienced neurologist determined the disease severity using the global (I–V) and motor (III) scores of the Unified Parkinson Disease Rating Scale (UPDRS), collected during the medication ON condition, [11] and the Hoehn and Yahr staging [12]. Disease duration (time from PD diagnosis), the Hoehn and Yahr scores, and the global (I–IV) and motor (III) UPDRS scores are also shown in Table 1. PD patients were on optimized pharmacological therapy: 10 subjects were being treated with at least two different anti-Parkinsonian drugs (levodopa, dopamine agonists, MAO-B or COMT inhibitors) and the other 4 patients were on levodopa treatment only.

Exclusion criteria were the following: other neurological disorders such as neuromuscular diseases; metabolic disorders as diabetes, dysthyroidism, etc.; cardiorespiratory disorders requiring medical treatment; motor impairment such as intermittent claudication or muscular and joint disorders of the lower limbs. No subject required the use of a walking aid, and no patient was suffering from freezing of gait or festination at the time of the experiments. All study participants were classified as “sedentary,” as all of them were categorized in the “lowest activity level” of the International Physical Activity Questionnaire (IPAQ). In particular, none of the patients reported any regular walking activity of at least 30 min/day.

All participants gave a written informed consent before data collection and the study was approved by the local ethics committee.

Experimental procedures

The walking tests were carried out on the ground of a wide gymnasium hall. A square path with a perimeter of 40 m was prepared using adhesive markers on the floor.

The experiments were carried out in the morning, at least 2 h after drug consumption.

A period of about 5-min rest (prior to initial baseline measures) was taken to determine resting HR. Then, the subjects were required to walk unassisted on the floor at the self-selected speed for 5 min. Finally, after 10 min of recovery, they were required to walk at the fastest speed they could maintain for 5 min. Therefore, both velocities were chosen by the subject, based on each individual capacity and feeling. The order of testing was not randomized, to avoid fatigue accumulation. Patients were asked to maintain a regular and constant speed while walking.

The HR was recorded on a beat-to-beat basis by a heart rate monitor (model S810i, Polar, Finland) throughout the whole procedure. Expiratory gases were continuously measured on a breath-by-breath basis by a mobile metabolic portable low-weight system (mod. K4b2, Cosmed, Italy). The gas analyzer and the pneumotachometer were calibrated before each experimental session.

The mean step length was calculated from the distance covered during each walk, using covered distance/number of steps (step number was evaluated by a pedometer, model PET316 FM, Oregon Scientific Inc., USA). The averaged stride cycle length was calculated as double the mean step length.

Data analysis

The VO2 (mL min−1) during each phase was calculated by averaging the breath-by-breath values of the last 2 min of each 5-min walking phase. The estimated maximal VO2 was calculated by extrapolating the HR/VO2 relationship to the age-predicted theoretical maximal HR [13]. The net energy cost of walking (Ec, mLO2 kg−1 m−1), i.e., the energy required to cover 1 m per unit of transported mass [14], was calculated as:
$$ E_{\text{c}} = \left( {V{\text{O}}_{2}\;{\text{walk}} - V{\text{O}}_{2}\;{\text{standing}}} \right)/{\text{walking}}\,{\text{velocity}} $$
(1)

The oxygen pulse (VO2/HR, mLO2 beat−1), i.e., the amount of oxygen consumed per heartbeat, was also calculated as an index of global cardiovascular efficiency for the aerobic metabolism [15].

Finally, a ventilatory efficiency index was calculated as the ventilatory equivalents for oxygen (VE/VO2).

Statistical analysis

Unless otherwise stated, data are reported as mean ± standard deviation (SD). During standing, the differences in metabolic parameters between PD patients and control subjects were tested by a Student’s t test for unpaired samples. During walking, we tested in each group the responses of metabolic and mechanic pattern of walking at the different velocities, by applying a repeated measure analysis of variance (2 × 2 repeated-measures ANOVA), with two levels: group and speed. A post-hoc analysis (LSD Fisher test) was then performed.

The possible relationship between clinical scores and metabolic/mechanic parameters was analyzed by simple regression analysis.

All the statistical analyses were performed with the statistical software Statistica (v7.1, Stat Soft, USA). The significance level was set at P < 0.05.

Results

During standing at rest, none of the metabolic parameters significantly differed between PD and control group: HR was 76 ± 15 versus 76 ± 8 beats m−1, VE was 11.0 ± 2.2 versus 11.1 ± 1.4 L min−1, VO2 was 3.6 ± 0.7 versus 3.9 ± 0.6 mL kg−1 min−1 and VE/VO2 was 40.3 ± 7.5 versus 35.0 ± 7.2 in PD versus control subjects, respectively. Similarly, the estimated VO2max did not differ between groups (30.6 ± 8.9 mL kg−1 min−1 in PD patients versus 35.8 ± 10.6 mL kg−1 min−1 in control subjects).

During the walking test at self-selected speed, the PD group covered significantly less distance than the control group: 201.3 ± 42.6 m versus 246.2 ± 50.9 m, respectively. Thus, spontaneous walking speed was significantly reduced in PD versus control subjects: 50.3 ± 0.6 versus 61.5 ± 12.7 m min−1, respectively (−18%, P = 0.02). Similarly, during the walking test at the fastest speed, PD patients covered significantly less distance than did control individuals: 263.8 ± 50.8 versus 341.2 ± 53.6 m, respectively, which again corresponded to reduced velocity in PD patients in comparison to control subjects: 65.9 ± 12.7 versus 85.3 ± 13.4 m min−1 (−24%, P = 0.0006).

Table 2 shows the mean values of the functional, cardiorespiratory, and metabolic variables measured in the two groups during self-selected and maximal speed. No significant difference was found between PD and control groups, with the exception of stride length at both speeds and VO2 and cadence at the fastest speed only.
Table 2

Functional and cardiorespiratory parameters measured at self-selected and as-fast-as-possible speeds

Parameter

PD subjects (n = 14)

Control subjects (n = 14)

P value (post hoc analysis)

Self-selected speed

   

 HR (beats m−1)

87 ± 13

87 ± 9

ns

 VE (L min−1)

21.2 ± 4.1

21.1 ± 5.2

ns

 VO2 (mL kg−1 min−1)

9.8 ± 2.5

10.7 ± 2.2

ns

 Oxygen pulse (mLO2 beat−1)

8.7 ± 3.6

8.7 ± 1.9

ns

 VE/VO2

28.1 ± 3.6

26.1 ± 3.8

ns

 Net Ec (mLO2 kg−1 m−1)

0.12 ± 0.04

0.11 ± 0.02

ns

 Stride length (m)

0.98 ± 0.20

1.15 ± 0.11

0.04

 Cadence (steps min−1)

103.4 ± 14.6

109.8 ± 13.3

ns

As-fast-as-possible speed

   

 HR (beats m−1)

97 ± 14

107 ± 14

ns

 VE (L min−1)

28.6 ± 6.9

33.9 ± 7.3

ns

 VO2 (mL kg−1 min−1)

12.8 ± 3.3

16.9 ± 3.1*

0.007

 Oxygen pulse (mLO2 beat−1)

9.9 ± 3.6

11.2 ± 2.4

ns

 VE/VO2

29.1 ± 2.9

27.4 ± 4.6

ns

 Net Ec (mLO2 kg−1 m−1)

0.14 ± 0.03

0.15 ± 0.02

ns

 Stride length (m)

1.22 ± 0.17

1.36 ± 0.18*

0.05

 Cadence (steps min−1)

108.8 ± 16.5

126.5 ± 10.4*

0.01

HR heart rate, VE minute ventilation, VO2 oxygen consumption, Net Ec net energy cost, VO2max maximal VO2, ns not significant

P < 0.05 between groups

Although HR, oxygen pulse and pulmonary ventilation values were similar between groups at both speeds (Table 2), the 2 × 2 ANOVA (Table 3) demonstrated a significant interaction (P < 0.01 for all comparisons) on these variables of the two main factors, “group” and “speed”. Moreover, PD patients’ oxygen pulse values were more dispersed than those of control subjects were; the oxygen pulse values of four PD patients fell outside the 95% confidence limits of the cumulative distribution of oxygen pulse values in control and PD individuals both at self-selected (n = 28, mean 8.6, IC 95% 7.5–9.7 mLO2 beat−1) and as-fast-as-possible (n = 28, mean 10.5, IC 95% 9.3–11.7 mLO2 beat−1) speeds.
Table 3

Interaction between “group” and “speed” on the metabolic and mechanic parameters of walking (2 × 2 ANOVA)

Parameter

Main effects

Interaction

 

Group

Speed

Group ×  speed

HR

0.300

<0.001

0.004

VE

0.240

<0.001

0.003

VO2

0.017

<0.001

0.001

Oxygen pulse

0.567

<0.001

0.008

VE/VO2

0.200

0.002

ns

Net Ec

0.922

<0.001

0.012

Stride length

0.035

<0.001

ns

Cadence

0.019

<0.001

0.009

Significant (P < 0.05) values are reported in bold. Main effects of the analysis were “Group” (PD or control) and “Speed” (self-selected and as-fast-as possible)

Abbreviations as in Table 2

Oxygen ventilatory equivalent (VE/VO2) values were similar between PD patients and control subjects both at self-selected and fastest speed (Table 2), with no interaction between pathology and speed (Table 3).

As regards the energy cost of walking, although on average no significant differences were found between the PD and the control groups in the net Ec at both velocities (Table 2), the Ec at the self-selected (but not at the fastest) speed tended to be higher in PD than in control subjects, and the factorial ANOVA showed a significant interaction between the main factors on this variable. In addition, the Ec increment from self-selected to fastest velocity was significantly lower (P = 0.02) in PD patients.

The individual values of the net Ec of locomotion are plotted against walking speed in Fig. 1 for all the investigated subjects. The linear trend of PD subjects shows a negative slope, whereas the linear trend slope of control subjects is positive. The second order polynomial interpolation of the pooled data (PD patients and control subject at both velocities) shows a U-shaped curve typical of such relationship, with a minimum Ec near at 60 m min−1.
https://static-content.springer.com/image/art%3A10.1007%2Fs10072-011-0827-6/MediaObjects/10072_2011_827_Fig1_HTML.gif
Fig. 1

Net energy cost of walking (Ec, mLO2 kg−1 m−1) plotted as function of walking speed (m min−1). Open circles are control subjects and closed circles are PD subjects. Ec energy cost of locomotion, v velocity

No significant relationship was found between functional (velocity, stride length, cadence) or metabolic (VE, VO2, HR, Ec) parameters and the Hoehn and Yahr and UPDRS global or motor score, both at self-selected and as-fast-as-possible speeds.

Discussion

The main findings of this study are that in mild-to-moderate, optimally treated PD patients, self-selected and maximal sustainable speeds are lower as compared to healthy control subjects. Moreover, PD patients failed to walk at a self-selected speed, which minimizes the energy cost of locomotion. Such limitations may be due to mechanic and/or energy reasons.

Until now, there is only a comparison between walking in PD and control subjects at steady-state fixed speeds [8], showing that walking economy was significantly worse and VO2 was 6–10% higher in PD patients than in controls at all speeds. In our study, oxygen consumption was not different between PD and control subjects when walking at comfortable speed, but it was significantly higher in control subjects at the fastest speed achievable (Table 2). We did not assess VO2max or peak VO2 with an incremental exercise test. However, some reports have shown that submaximal oxygen uptake measures were more predictive of the functional mobility performance than peak VO2 in both healthy and impaired older subjects [17]. Nevertheless, we can express VO2 at comfortable speed as a percentage of maximally sustainable VO2 observed at the as-fast-as-possible velocity. Indeed, in PD patients, VO2 at self-selected speed was 77% of VO2 at fastest speed, whereas in control subjects VO2 at self-selected speed accounted for only 64% of VO2 at fastest speed (P < 0.05). The higher value found in PD individuals suggests that these patients can develop fatigue after a shorter time of walking.

In regards to ventilation and to ventilatory equivalent, no significant differences were observed between PD and control subjects at all speeds (Table 2). Therefore, it is unlikely that respiratory function could limit walking efforts in PD patients. These results are in agreement with those of Haas et al. [18].

Finally, there were no significant differences between the two groups in terms of HR while walking at self-selected and fastest speeds (Table 2), although there was a significant interaction in the ANOVA analysis between group and speed, which suggests that PD patients could not increase adequately their HR from comfortable to fastest speed. Indeed, submaximal HR at self-selected speed was 90% of the HR value at fastest speed in PD patients, whereas it was only 81% of the HR at fastest speed in control subjects (P < 0.05 between groups). Therefore, the response of HR to walking seems to be limited in PD patients. A possible explanation for the reduced cardiac adaptation to self-selected walking in PD individuals is the cardiovascular deconditioning that develops over time in PD patients. Another possible reason for the reduced HR adaptation to comfortable walking could be the cardiac autonomic dysfunction in PD patients, which typically develops during PD evolution [8]. These aspects deserve further studies. Moreover, the fact that the patients’ oxygen pulse values were more dispersed than those of the control subjects suggests that a subgroup of PD individuals (28%) had higher oxygen pulse values compared to the other PD patients and to the control subjects. Therefore, in some PD patients a limitation in cardiac aerobic efficiency may be responsible for the reduced cardiopulmonary adaptation to spontaneous walking.

Our results on the Ec of walking in PD patients, measured both at the self-selected and as-fast-as-possible speeds, cannot be easily compared with other published data, as most of the previous studies were obtained using maximal exercise tests or standard 6-min walking tests [1, 6, 7, 16].

Surprisingly, no statistically significant difference was found in the Ec between the two groups at either velocity, although the Ec at the self-selected (but not at the as-fast-as-possible speed) speed tended to be higher in PD than in control subjects. This may be due to the significant difference in walking speed between PD versus control subjects, as the Ec is known to increase with increasing walking velocity, up to a given limit [19]. However, the interaction between the 2 × 2 ANOVA main factors, velocity and group, on net Ec was again significant (Table 3), suggesting that this effect is due not only to the different speeds but also to PD per se. The negative slope observed in linear trend for PD subjects (Fig. 1) suggests that in these subjects Ec is reduced by increasing speed, whereas the positive linear trend found in control subjects suggests that in these subjects Ec increases with walking speed. Indeed, the second order polynomial interpolation of the pooled data (PD patients and control subject at both velocities) shows a typical U-shaped curve, in which PD patients are observed mainly in the descending arm, whereas the control subjects are found mainly in the ascending one. This may be relevant especially for the self-selected speed, which seems to be chosen by PD patients at a velocity, which is not corresponding to a minimal Ec. This could cause at last more fatigue development in these individuals.

Finally, the clinical scores did not seem to be predictive of the impairment of locomotion that typically develops in mild-to-moderate PD patients.

Study limitations

Ten minutes rest was allowed between the two measurements on self-selected and maximal speed. This could have been short in some subjects and should have been a factor in the faster walking test. However, none of the subjects at study reported subjective fatigue after the stage at self-selected speed.

In addition, in this study we assessed neither the step variability nor the contribution of the upper extremities to walking economy, which may be possible factors in reducing the walking economy in PD patients.

All the subjects enrolled were sedentary. However, this was determined only from the initial subjects’ enrolment interview.

Finally, we did not consider the possible effects on walking economy of pharmacological agents (as β-blockers, other neurologically active drugs, etc.) other than anti-parkinsonian drugs.

Acknowledgments

This study was supported by the Italian Health Ministry (Project PS/03/12, Treatment of the Parkinsonian subject: integration between diagnostic and therapeutic aspects for the optimization of the total rehabilitative procedure).

Copyright information

© Springer-Verlag 2011