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PHYS THER
Vol. 85, No. 12, December 2005, pp. 1340-1348
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Research Reports

Factors Associated With the Level of Movement-Related Everyday Activity and Quality of Life in People With Chronic Heart Failure

Rita J van den Berg-Emons, Johannes B Bussmann, Aggie H Balk and Henk J Stam

RJ van den Berg-Emons, PhD (Health Science), is Research Scientist, Department of Rehabilitation Medicine, Erasmus Medical Center Rotterdam, Dr Molewaterplein 40, 3015 GD Rotterdam, the Netherlands (h.j.g.vandenberg{at}erasmusmc.nl).
JB Bussmann, PhD (Medicine and Health Science), BSC (PT), is Research Scientist, Department of Rehabilitation Medicine, Erasmus Medical Center Rotterdam
AH Balk, PhD (Cardiology), is Cardiologist, Department of Cardiology, Erasmus Medical Center Rotterdam
HJ Stam, PhD (Medicine and Health Science), MD (Medicine and Health Science), is Professor of Rehabilitation Medicine and Head of the Department of Rehabilitation Medicine, Erasmus Medical Center Rotterdam

Address all correspondence to Dr van den Berg-Emons


Submitted December 15, 2004; Accepted April 11, 2005


   Abstract
 
Background and Purpose. Cardiac rehabilitation has been shown to be effective in people with chronic heart failure (CHF), particularly in terms of exercise capacity. However, no effects have been found on the level of movement-related everyday activity. Therefore, rehabilitation programs also should focus on enhancing the level of movement-related everyday activity. The aim of this study was to explore factors associated with the level of movement-related everyday activity and with quality of life in people with CHF. Subjects and Methods. Measurements of movement-related everyday activity (using an accelerometry-based Activity Monitor), quality of life, and associated factors were performed in 36 people with stable CHF (New York Heart Association classes II and III). Results. Knee flexion and extension torque, and particularly extension torque, were significantly associated with movement-related everyday activity (r =.43–.49, P<.05), whereas non-physiological factors such as feelings of being disabled were associated with quality of life (r =.37–.77, P≤.01, P<.05). No relationship was found between movement-related everyday activity and quality of life (r =.20–.22, P>.05). Discussion and Conclusion. The results indicate that knee torque is associated with the level of movement-related everyday activity in people with CHF and that quality of life is mediated by nonphysiological factors.

Key Words: Determinant • Everyday activity • Fitness • Heart failure • Quality of life


   Introduction
Top
 Abstract
 Introduction
Method
 Results
 Discussion
 Conclusion
 References
 
People with chronic heart failure (CHF) may be restricted in the performance of normal everyday activities such as walking, housekeeping, gardening, and shopping. As a result, we believe that they may experience diminished function due to a sequence of negative effects: hypoactivity leading to reduced fitness, leading to further hypoactivity. In a previous study,1 we found that the mean duration that people with CHF performed movement-related activities during a day was considerably lower compared with subjects who were healthy (0.8 versus 2.2 hours per day, respectively; P<.05). This hypoactivity in CHF also has been found in other studies2–6 and may have detrimental effects on fitness,6 social participation, and prognosis.7 Furthermore, considerable reductions in several areas of quality of life have been reported in people with CHF.8,9 It may be hypothesized that this decreased quality of life is partly caused by hypoactivity.10,11

Cardiac rehabilitation in people with CHF has been shown to be effective, particularly in terms of exercise capacity12–15 and quality of life.9,16 However, increased exercise capacity does not necessarily result in a more active lifestyle (eg, more or longer periods of walking or cycling in everyday life). In our randomized clinical trial in people with CHF,6 in which an experimental group participated in a 3-month aerobic training program and a control group received standard medical treatment, we found that aerobic training had favorable effects on exercise capacity. However, no training-related changes were found in the level of movement-related everyday activity, as measured with an Activity Monitor (AM).* Apparently, a discrepancy may exist between the capacity of a person (what a person can do) and actual performance (what a person really does in everyday life). This discrepancy also has been reported previously.2,17

Therefore, we believe that cardiac rehabilitation programs in CHF, besides focusing on improving exercise capacity, also should focus on enhancing the level of movement-related everyday activity. To reach this goal, insight into the factors that are associated with the level of movement-related everyday activity in this group is necessary. The primary aim of our study was to explore factors associated with the level of movement-related everyday activity in people with CHF. Furthermore, we were interested in the factors associated with quality of life in this group, and particularly in whether the level of movement-related everyday activity is associated with quality of life.


   Method
Top
 Abstract
 Introduction
 Method
Results
 Discussion
 Conclusion
 References
 
Subjects

The study was part of a training study in people with CHF. In this training study, effects of aerobic exercise on variables such as the level of movement-related everyday activity, fitness, and quality of life were evaluated by comparing post-treatment measurements with baseline measurements. The results of this training study are described elsewhere.6 The results of the present study only concern the baseline measurements of the training study.

People were recruited during 1 year from the cardiology outpatient clinic of Erasmus Medical Center Rotterdam. Inclusion criteria were: heart failure (New York Heart Association [NYHA] classes II and III)18 because of primarily systolic dysfunction and in stable condition for at least 1 month prior to inclusion; left ventricular ejection fraction (LVEF) <40% (echocardiography); age 40 to 75 years; and etiology of ischemic heart disease, idiopathic dilated cardiomyopathy, hypertension, or nonobstructive valvular disease. Exclusion criteria were: exercise-induced ischemia or arrhythmias, uncontrolled hypertension, and exercise limitation due to chronic obstructive pulmonary disease. Written informed consent was obtained from all participants.

Forty-five people were found to be eligible for the study, of which 36 people (80%) agreed to participate. Reasons for nonparticipation were distance between home and training center (n=3), being busy with other activities (eg, sports group, housekeeping, looking after children) (n=3), and feeling unable to perform sports activities (n=3). There were no differences in relevant characteristics between the people who participated and the people who decided not to participate. Clinical characteristics of the participants are presented in Table 1.


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  		Table 1. Clinical Characteristics of the Participants (N=36)

 
Level of Movement-Related Everyday Activity

For the assessment of the level of movement-related everyday activity, an AM (15 x 9 x 3.5 cm, weight= 500 g) was used (Figure). The AM is based on long-term ambulatory monitoring of signals from body-fixed accelerometers and consists of 4 accelerometers, a portable data recorder, and a computer with analysis programs.19 From the accelerometer signals, the duration, rate, and moment of occurrence of activities associated with mobility and transitions between postures can be detected with a 1-second resolution. The activities associated with mobility consisted of the stationary activities lying, sitting, and standing and of the movement-related activities walking (including walking up and down stairs) and running, cycling, wheelchair driving, and general (noncyclic) movement. Furthermore, information on the variability of the acceleration signal (motility) can be obtained, which is related to the intensity of body-segment movements.20–22 Apart from monitoring accelerations, other signals such as heart rate or electrocardiographic activity can be measured simultaneously. Validity studies of subjects who were healthy and several patient groups, including people with CHF, in which simultaneously made video registrations (reference method) were compared with the outcome of the AM, have shown that measurements recorded by the AM are valid and reliable to quantify activities associated with mobility.23–26 Furthermore, the AM can detect differences in level of movement-related everyday activity during everyday life between groups,1,27,28 which supports its validity and applicability in clinical research.


Figure 1
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  		Figure. Subject wearing the Activity Monitor.

 
Measurements with the AM were performed during 2 randomly selected consecutive weekdays (48-hour measurement) in the home situation and, if applicable, in the work situation. To avoid measurement bias, the principles of the AM were explained to the subjects only after the measurements. All subjects agreed with this procedure. Subjects were instructed to continue their ordinary daily life; however, they were not allowed to swim or take a bath or shower.

Four ADXL202 uniaxial piezo-resistive accelerometers{dagger} (1.5 x 1.5 x 1 cm) were used. One accelerometer was attached to each thigh (while standing, accelerometer is sensitive in an anteroposterior direction), and 2 accelerometers were attached to the skin over the sternum (while standing, one accelerometer is sensitive in an anteroposterior direction and one accelerometer is sensitive in a longitudinal direction). The accelerometers were connected to the AM, which was worn in a padded bag around the waist. Accelerometer signals were stored digitally on a PCMCIA flash card with a sampling frequency of 32 Hz. After the measurement, data were downloaded onto a computer for analysis by the kinematic analysis part of the Vitagraph Software.*,29 A detailed description of the activity detection procedure has been described previously.1,19,26

Data of the AM measurement were calculated per day (24-hour period) and averaged over the 2 measurement days. The level of movement-related everyday activity was expressed by the duration of movement-related activity (composite measure: walking [including walking up and down stairs] and running, cycling, and general movement) as percentage of a 24-hour period. Results for other output parameters of the AM, such as number of transitions and number of walking periods, are described elsewhere.6

Quality of Life

Quality of life was assessed with the Dutch version30 of the Minnesota Living With Heart Failure Questionnaire, as originally developed by Rector et al.31 The instrument is a patient self-assessment measure that focuses on patients' perceptions of the effects of CHF on their lives. The instrument consists of 21 questions and comprises a physical dimension (7 questions; eg, difficulty with walking or climbing stairs, difficulty with working around the house) and an emotional dimension (6 questions; eg, difficulty with relating to or doing things with people, feeling burdersome to other people). The remainder of the 21 questions represent other dimensions of quality of life. Response possibilities range from 0 ("no impairment") to 5 ("very much impaired"). The maximum total score is 105 units (sum score of 21 questions), the maximum score on the physical dimension is 35 units (sum score of 7 of the 21 questions), and the maximum score on the emotional dimension is 30 units (sum score of 6 of the 21 questions). The questionnaire was completed by the subjects in the presence of a researcher.

The Minnesota Living With Heart Failure Questionnaire has been found to yield reliable and valid data for use in the United States.32,33 The Dutch version has been found to yield reliable and valid measurements of quality of life in Dutch people with CHF.30 Test-retest reliability, as assessed with the Pearson correlation coefficient (r), was .86 for the total score, .87 for the physical dimension, and .85 for the emotional dimension. Dimensions of the questionnaire correlated significantly with dimensions of other health-related quality-of-life instruments, with NYHA class, and with oxygen consumption at peak exercise and at anaerobic threshold, which supports the construct validity of data obtained with the questionnaire.

Physiological Factors

Left ventricular ejection fraction.
Left ventricular ejection fraction (LVEF) was assessed by echocardiography.34

Fitness.
Aerobic capacity was tested by a symptom-limited bicycle{ddagger} ergometer test at a constant pedaling speed of 60 rpm with workload increments of 10 W·min–1. This kind of exercise testing has been found to yield valid measurements for assessment of aerobic capacity.35 Heart rate, blood pressure, and a 12-lead electrocardiogram were monitored during the test. Gas volume and gas concentrations were measured continuously using a breath-by-breath system and a face mask with a digital volume sensor (Oxycon Champion§). Gas analyses were made by a paramagnetic oxygen and infrared carbon dioxide analyzer. Aerobic capacity was defined as the mean oxygen uptake (VO2) during the last 30 seconds of exercise (VO2peak, expressed per kilogram of bodyweight). The peak power (Wpeak, measured in watts per kilogram of bodyweight), which reflects the rate at which work is performed, also was registered. In addition, the VO2 at which the respiratory exchange ratio equals unity (VO2rer=1, an approximate marker of when anaerobic muscular metabolism is starting) was determined, and the carbon dioxide ventilatory equivalent (VE/VCO2, representing ventilatory efficiency) at peak exercise was calculated. Finally, the half-recovery time of VO2peak (in seconds), or the time to reach half of the change to the final VO2, was assessed.

Besides the symptom-limited exercise test, the submaximal 6-minute walk test was performed.36 Patients were instructed to walk, not run, as far as they could along a 25-m marked tape during a 6-minute period in a quiet room.

Muscle torque (recorded in newton-meters) of the extensor and flexor muscles of the knees was determined with a Biodex isokinetic dynamometer.|| To correct for differences in body composition, results for knee extension torque and knee flexion torque were expressed per kilogram of body weight. Torque determinations were made while the subjects were seated with thigh and pelvis stabilized. After a warm-up, the subjects performed 10 maximal contractions at 180°/s with each leg. Peak torque was defined as the maximum torque generated by a subject throughout one series of repetitions. Gravity correction was obtained by measuring the torque exerted on the dynamometer lever arm with the knee in a relaxed state in nearly full extension. For practical reasons, we had to limit the number of measurements of muscle torque to measurements of knee extension and knee flexion torque. We chose these muscle groups because they are important during walking. An earlier study by our group showed that walking is the most prominent movement-related activity in people with CHF: 88% of the time during a day spent on movement-related activities was walking, 3% was cycling, and 9% was general noncyclic movement.1

Nonphysiological Factors

Fear of movement was determined by one question designed for this study ("How much do you shrink from performing physically intensive tasks?"), which was scored by visual analog rating scales with scores ranging from 0 cm ("no fear") to 10 cm ("very great fear"). Visual analog rating scales have been found to yield reliable and valid data.37,38

Dissatisfaction with movement-related everyday activity was determined by one question designed for this study ("How satisfied are you with your activity pattern?"), which was scored by visual analog rating scales, with scores ranging from 0 cm ("complete satisfaction") to 10 cm ("complete dissatisfaction").

Feelings of being disabled were determined by the I subscale of the Medical Psychological Questionnaire for Heart Patients.39 This questionnaire has been found to yield reliable and valid scores.39 Scores range from 12 units ("no feelings of being disabled") to 36 units ("strong feelings of being disabled").

Depression and anxiety were determined by the Dutch version of the Hospital Anxiety and Depression Scale (7 questions on depression and 7 questions on anxiety), which has been found to yield reliable and valid scores.40 Scores range from 0 units ("no anxiety; no depression") to 21 units ("anxiety; depression"). All of these parameters were self-assessed by the subjects in the presence of a researcher.

Data Analysis

Statistical analysis was performed using SPSS 10.1 for Windows.# Results are presented as means with standard deviations and ranges unless otherwise indicated. A P value of <.05 was considered statistically significant. Because several factors (particularly fitness parameters) were correlated with age and sex but not with the level of movement-related everyday activity or quality of life, a partial correlation analysis was performed, adjusting for age and sex, to explore univariate relationships between: (1) the level of movement-related everyday activity and all physiological and nonphysiological factors, including quality of life, and (2) quality of life and all physiological and nonphysiological factors, including the level of movement-related everyday activity. All factors (both physiological and nonphysiological) that showed a significant univariate relationship (P<.05) with the level of movement-related everyday activity were entered stepwise in the multiple linear regression analysis to construct a regression model for the level of movement-related everyday activity. All factors (both physiological and nonphysiological) that showed a significant univariate relationship (P<.05) with quality of life were entered stepwise in the multiple linear regression analysis to construct a regression model for quality of life. However, in case of multicollinearity (r>.8 between 2 independent factors),41 only one of the parameters was included in the regression model. The regression analyses were adjusted for age and sex (enter method). Probability of F to enter the analysis was set at P≤.05, and the probability to remove was set at P≥.10.


   Results
Top
 Abstract
 Introduction
 Method
 Results
Discussion
 Conclusion
 References
 
Level of Movement-Related Everyday Activity and Quality of Life

The mean level of movement-related everyday activity was 8.3% (SD=3.0%, range=4.0%–18.8%), which equals 118 minutes of walking, cycling, or general movement per 24-hour period. Results for quality of life were 25.9 units (SD=17.2, range=0–59) for the total score, 6.6 units (SD=6.2, range=0–19) for the emotional dimension, and 11.9 units (SD=7.5, range=0–27) for the physical dimension.

Factors

Mean results (and standard deviations and ranges) for the factors and partial correlation coefficients between these factors and the level of movement-related everyday activity and quality of life are presented in Tables 2 and 3, respectively. The only factors that were significantly related to the level of movement-related everyday activity were the physiological factors knee extension peak torque and knee flexion peak torque (Tab. 3). There were no significant correlations between the level of movement-related everyday activity and quality of life (r =.20, r =.22, and r =.21 for the total score, the emotional dimension, and the physical dimension, respectively; P>.05) or between the level of movement-related everyday activity and any of the nonphysiological factors (Tab. 3). Because there was no multicollinearity between knee extension peak torque and knee flexion peak torque (r =.78, P<.05), both factors were entered stepwise in the multiple regression analysis (adjusted for age and sex). The obtained regression model (Tab. 4) for the level of movement-related everyday activity explained 17% of the total variance.


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  		Table 2. Results on the Factors in Subjects With Chronic Heart Failure (N=36)

 

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  		Table 3. Partial Correlation Coefficients, Adjusted for Age and Sex, for Relationships Between Factors and Level of Movement-Related Everyday Activity and Quality of Life

 

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  		Table 4. Multiple Regression Models for Prediction of the Level of Movement-Related Everyday Activity and Quality of Life

 
Only nonphysiological factors (Tab. 3) were significantly related to quality of life (r =.37–.77, P≤.01, P<.05). Because there was no multicollinearity (correlation coefficients between the independent factors ranged from .42 to .80), all factors that showed a significant univariate correlation to quality of life were entered stepwise in the multiple regression analysis (adjusted for age and sex). The obtained regression models (Tab. 4) for quality of life (total score, emotional dimension, and physical dimension) explained 53%, 53%, and 55%, respectively, of the total variance.


   Discussion
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
Conclusion
 References
 
General

The primary aim of our study was to identify factors associated with the level of movement-related everyday activity in people with CHF in order to develop cardiac rehabilitation programs aimed at a more active lifestyle. For this purpose, a novel and extensively validated activity monitor was used.

Our study, however, may have some limitations. First, the present study was part of an investigation of training effects, so subjects were asked to participate in a training study. This may have resulted in a study sample that was more active or more fit than the general population of people with CHF. However, only 3 of the 9 nonparticipants gave as a reason for their nonparticipation that they felt unable to perform sports activities; the other nonparticipants were too busy with other activities (eg, sports group) or the distance between home and training center was too large. Therefore, we do not believe that the recruitment procedure resulted in a more active or more fit study sample. Second, we realize that, because of the relatively small sample size, some of the studied relationships may have failed to show statistical significance (eg, relationships between level of movement-related everyday activity and VO2peak, Wpeak, and VE/VCO2peak and between 6-minute walk test distance and quality of life; all P≤.10, Tab. 3). However, there may be no relationship between these parameters in the population of people with CHF. Finally, we by no means imply that our list of factors is complete.

Duration of the day that movement-related activities were performed was considerably larger in the present study (X=8.3%, SD=3.0%) than in our pilot study on the level of movement-related everyday activity in people with CHF (X=3.9%, SD=1.5%)1 (P<.01). This discrepancy between the studies may be explained by the small number of subjects in the pilot study (n=5) and by a possible selection bias in both studies. However, in comparison with normative values for the duration of dynamic activities as measured with the AM (X=11.5%, SD=3.8%),1,27,28,42 the mean level of movement-related everyday activity in the present study was low (72% of normative values). When defining hypo-activity as the norm minus 1 standard deviation, more than half of the subjects (n=20, 56%) was classified as hypoactive.

Most of our results for quality of life are in agreement with the results of the study of Wijbenga et al,30 who applied the Dutch version of the Minnesota Living With Heart Failure Questionnaire in a large group (n=184) of people in NYHA classes II and III. However, people in NYHA class III in our study scored lower on the physical dimension of the quality-of-life questionnaire, indicating better quality of life, than in the study of Wijbenga et al.30

Factors Associated With the Level of Movement-Related Everyday Activity

In their study on predictors of movement-related everyday activity, which was assessed with a questionnaire, Oka et al43 found that belief in self-efficacy (confidence in being able to successfully perform a specific activity or behavior) was a stronger predictor of the level of movement-related everyday activity in CHF than parameters of fitness. The factors included in our study differed somewhat from those in the study of Oka et al,43 but we found no indication that nonphysiological factors are associated with the level of movement-related everyday activity in CHF. Contrary to our expectations, only knee muscle torque (Tab. 3), and particularly knee extension torque (Tab. 4), turned out to be significantly associated with the level of movement-related everyday activity in our study sample.

However, it should be realized that only a small part of the variance in level of movement-related everyday activity is explained by fitness (Tab. 4); thus, a large discrepancy exists between the fitness of a person (what a person can do) and the actual performance (what a person really does in everyday life). Therefore, the level of movement-related everyday activity in patients with CHF cannot be predicted well from parameters of fitness, which is in agreement with the findings of previous studies.2,7,43,44

Factors Associated With Quality of Life

In the studies by Davies et al2 and Houghton et al,45 significant correlations (r =.49, P=.006 [movement monitor on ankle]2 and r =.47, P=.04 [pedometer on hip]45) were found between the level of movement-related everyday activity and quality of life in people with CHF. In contrast to these studies and in contrast to what we expected, no relationship was found in the present study between the level of movement-related everyday activity and quality of life. However, dissatisfaction with movement-related everyday activity was found to be associated with quality of life. We also expected an inverse relationship between dissatisfaction with movement-related everyday activity and the level of movement-related everyday activity, but we found no relationship between these parameters. This finding may be explained by personal preferences concerning an active or inactive lifestyle. Furthermore, it should be realized that most of the subjects were diagnosed with CHF several years ago (Tab. 1) and may have resigned themselves to their inactive lifestyle.

Besides this dissatisfaction with everyday activity, the other factors that turned out to be associated with quality of life were all nonphysiological factors (particularly feelings of being disabled, dissatisfaction with everyday activity, and depression; Tab. 4). No significant relationships were found between the physiological parameters and quality of life. This finding seems to be in contrast to the findings of previous studies8,9,46 in which relationships were found between exercise capacity and quality of life in CHF. Training-related improvements in exercise capacity in people with CHF, however, do not have to be related to improvements in quality of life.6,9,47


   Conclusion
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
 Conclusion
References
 
This study is an initial step in identifying factors associated with movement-related everyday activity in people with CHF, and additional research is needed to fully understand why some patients are more active than others. The results of the study indicate that only knee flexion and knee extension torque are significantly associated with the level of movement-related everyday activity in people with CHF, whereas quality of life is mediated by nonphysiological factors. No relationship was found between the level of movement-related everyday activity and quality of life. We believe that the findings of our study may help in the development of a cardiac rehabilitation program aimed at enhancing the level of movement-related everyday activity for people with CHF.


   Footnotes
 
All authors provided concept/idea/research design. Dr van den Berg-Emons provided writing. Dr van den Berg-Emons and Dr Balk provided data collection, and Dr van den Berg-Emons and Dr Bussman provided data analysis. Dr van den Berg-Emons, Dr Balk, and Dr Stam provided project management. Dr van den Berg-Emons and Dr Stam provided fund procurement. Dr Balk provided subjects. Dr Stam provided institutional liaisons. Dr Bussman, Dr Balk, and Dr Stam provided facilities/equipment and consultation (including review of manuscript before submission). The authors thank Yvonne Grubben and Han van Nieuwenhuizen (Department of Rehabilitation, Erasmus Medical Center Rotterdam) and fellows and paramedics of the Ergometry Lab (Thoraxcenter, Erasmus Medical Center Rotterdam) for performing the measurements.

The study was approved by the Medical Ethics Committee of Erasmus Medical Center Rotterdam.

The study was funded by the Netherlands Heart Foundation (grant 1998B111) and the Rotterdam Foundation for Cardiac Rehabilitation.

* Supplied by Temec Instruments BV, Spekhofstraat 2, 6460 HA Kerkrade, the Netherlands. Back

{dagger} Analog Devices, Breda, the Netherlands, adapted by Temec Instruments BV, Kerkrade, the Netherlands. Back

{ddagger} Lode Medical Technology, Zernikepark 16, 9747 AN Groningen, the Netherlands. Back

§ Mijnhardt Oxycon Systems, Bunnik, the Netherlands. Back

|| Biodex Medical Systems, 20 Ramsay Rd, Shirley, NY 11967-4704. Back

# SPSS Benelux BV, PO Box 115, 2200 AC Gorinchem, the Netherlands. Back


   References
Top
 Abstract
 Introduction
 Method
 Results
 Discussion
 Conclusion
 References
 

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