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European Journal of Heart Failure 2004 6(5):577-584; doi:10.1016/j.ejheart.2003.11.022
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© 2004 European Society of Cardiology

A questionnaire-based assessment of daily physical activity in heart failure

Martin Gareta,*, Jean Claude Barthélémya, Francis Degachea, Frédéric Costesa, Antoine Da-Costab, Karl Isaazb, Jean René Lacourc and Frédéric Rochea

a Laboratoire de Physiologie, Groupe PPEH, GIPE2S, Hôpital Nord-niv.6, Université Jean Monnet CHU Nord, 42055 Saint-Etienne Cedex 2, France
b Service de Cardiologie, CHU Nord 42055 Saint-Etienne Cedex 2, France
c Laboratoire de Physiologie, Faculté de Médecine Lyon-Sud 69921 Oullins, France

* Corresponding author. Tel.: +33-4-77-82-83-00; Fax: +33-4-77-82-84-47. E-mail address: martingaret{at}hotmail.com


   Abstract
Top
 Abstract
1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 
Type and dose of daily energy expenditure (DEE) play a major role in modulations of health status and an increased knowledge of these dimensions of physical activity in congestive heart failure (CHF) patients would be valuable for clinical and epidemiological aims. We propose a new self-administered DEE questionnaire adapted to CHF patients and tested its validity. One hundred and five stable CHF participants, NYHA class I–IV, LVEF=33.2±6.1% performed an incremental symptom-limited VO2 (peak) test and filled in the questionnaire for DEE calculation. Reproducibility (n=24), sensitivity (n=21) of the questionnaire and inter-observer variability (n=105) were tested. Intensity levels were identified from DEE and their relationships to VO2(peak), ventilatory and anthropometric characteristics were assessed by simple and multiple regression models. Reproducibility and sensitivity were high (r=0.98 and 0.88, respectively, P<0.0001) and inter-observer error reached 1.37%. DEE was highly correlated to physical activity energy expenditure (r=0.96, P<0.0001). Relationships between DEE, VO2(peak), VE/VO2 and anthropometric characteristics were significant. An activity level above 3 MET was the best intensity criteria related to VO2(peak) (r=0.62, P<0.0001) and DEE (r=0.80, P<0.0001). The questionnaire seems reproducible, sensible and valid for DEE estimation. VO2(peak) appears related to DEE and especially to activities above 3 MET in CHF.

Key Words: Physical activity • Congestive heart failure • Questionnaire • Health status

Received September 4, 2003; Revised October 30, 2003; Accepted November 19, 2003


   1. Introduction
Top
 Abstract
 1. Introduction
2. Methods
 3. Results
 4. Discussion
 References
 
Through an active lifestyle, physical activity has been shown to play a major role on health status in several populations [12,19,32] and is not only beneficial for the primary prevention of cardiovascular disease and all-cause mortality [13,22,29] but can also be a major component of secondary prevention with undeniable beneficial effects after, for example, myocardial infarction, cardiac surgery, or stable congestive heart failure (CHF) [1,3,11,15]. Lifestyle physical activity is a complex and multidimensional behavior and its measurement remains difficult. Several methods and measurement instruments have been developed to assess physical activity or daily energy expenditure (DEE) in various healthy populations but none have been specifically adapted for large studies in people with CHF. Objective quantitative and qualitative information of daily physical activity in this population would be very valuable in clinical supervision as well as in observational epidemiological studies of physical activity and health-related issues (evaluation and interpretation of dose-response characteristics between physical activity and specific health-related parameters).

Estimating energy expenditure is a possible way for assessing the type and quantity of physical activity in free-living conditions, where no gold-standard field measure of physical activity exists [17]. The important cost of the doubly labeled water technique, the most accurate in field research, makes it not adapted to large population surveys or routine use. Besides, no information concerning the pattern of activities or the detail of one's living habitudes is available without activity diaries. Heart-rate monitoring is another method but does not seem to provide precise estimates of daily energy expenditure (DEE) among free-living individuals and has not been adapted to individuals with chronic heart failure under medication. Motion detection and other indirect techniques have not been validated in populations with deficiencies. Physical activity questionnaires have represented the instrument of choice for physical activity surveys [21] or to assess DEE but should reflect both the type and quantity of habitual physical activity in the target population and the result be expressed in standardized units of energy expenditure in order to allow a dose–response analysis between physical activity and health related issues. To our knowledge, no such questionnaire exists or has been adapted to CHF patients.

It is not known if peak VO2, usually considered as the best measure of physical fitness [1,16,23,29] and an excellent integrated measure of function in these and other patients, is related to a particular type or quantity of activity as assessed by components of DEE, which is the case in populations with cardiopulmonary or musculoskeletal chronic diseases [26] and in the elderly [9,31,32].

A simplified DEE estimation with a precise, inexpensive, sensible and easy to use measurement of daily physical activity would be of great interest in CHF patients, notably to assume prescription and follow-up if measures of physical fitness as peak VO2 were related to DEE. We thus designed a detailed self-administered questionnaire of DEE providing a complete picture of the patient's habitual activities. The purpose of this study was to assess the reproducibility, sensitivity and concurrent validity of this questionnaire with indicators of physical fitness as peak VO2 in a population of stable patients with CHF.


   2. Methods
Top
 Abstract
 1. Introduction
 2. Methods
3. Results
 4. Discussion
 References
 
2.1. Subjects
A group of 105 caucasian participants (mean age±S.D.: 55.8±12.4 years, range 31–80 years old) including 18 women, with stable CHF, were recruited from the University Hospital of Saint-Etienne, France. Mean left ventricular ejection fraction (LVEF) was 33.2±6.1% as determined by Doppler echocardiography. Sixty-one patients suffered dilated cardiomyopathy (DCM) and 36 patients ischemic cardiomyopathy (ICM). At the time of exercise testing, patients were hemodynamically stable, free of visible oedema and were taking two or more of the following medications: diuretics (n=68, 71%), vasodilators (angiotensin-converting enzyme inhibitor or nitrates; n=72, 75%), beta-blockade (n=30, 31%), digoxin (n=23, 24%) and antiarrhythmics (n=16, 17%). One patient had type-2 diabetes mellitus and was taking oral hypoglycaemic drugs. Participants were defined by the New York Heart Association functional scale as class I (n=17, 16%), class II (n=63, 60%), class III (n=14, 13%) and class IV (n=3, 3%). All subjects were free of cigarette use although three had a history of heavy smoking. None had significant pulmonary disease and all were stopped by dyspnoea or leg fatigue on incremental exercise testing. No patient was wasted, cachectic, or with morbid obesity (BMI: 25.8±4.0 kg m–2). The investigation conforms with the principles outlined in the declaration of Helsinki. Written informed consent was given by all participants and the study was approved by the local institutional ethics committee.

2.2. Questionnaire
Our questionnaire is inspired from the Questionnaire d'Activité Physique de Saint-Etienne of Berthouze et al. which has been validated in healthy individuals and used in previous studies [4–8]. However, the QAPSE was not adapted in individuals with specific deficiencies as CHF patients. We have constructed a questionnaire composed of 82 questions and subquestions dealing with seven main dimensions of everyday life with added specific consideration for autonomy and/or perceived exertion. The seven main dimensions considered were sleeping and resting periods, basic everyday activities (eating, washing, toilet), housework activities, leisure time physical activities, physical activity at work or way of being occupied, moving about and miscellaneous activities. Autonomy and/or perceived exertion addressed specific information about the amount of help provided by a third person for an activity and if interruption was needed systematically, sometimes or never while doing a specific activity. The main areas of the questionnaire are summarized in Table 1.


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  		Table 1 Dimensions covered by the questionnaire

 
Activities were reported retrospectively over a duration of 1 week, including the weekend, in accordance with the minimal investigation period defined by Passmore and Durnin [23]. This questionnaire can be, preferably, self-administered in approximately 15 min or completed by an interviewer during a personal interview of approximately 20 min. All participants but three (for language misunderstanding) completed the questionnaire themselves. The patients fill out the questionnaire by completing the time spent in each activity, quantifying the number of times the activity is done in a week or a day and informing if help or interruption was needed systematically, sometimes, or never in an activity (autonomy).

An observer had thereafter to code the questionnaire using a specific written computer spreadsheet. Decoding last approximately 15 min per questionnaire. Daily energy expenditure (DEE) was calculated from the questionnaire using the usual equation DEE (kJ 24 h–1)={sum}(IAxDA) where IA is intensity of activity in J min–1 kg–1 and DA the duration of activity reported in min day–1.

The IA was determined according to activity tables listing standard values for EE for more than 350 physical activities [2] and from several scientific publications providing IA for any specific population [10,18,36]. Resting energy expenditure (REE) was calculated as the mean of REE from previous studies in age and symptom-matched populations [20,27,28,33,34]. The sum of all described activities was established and DEE was then adjusted for 24 h as far as the missing or excess in time reported did not overreach 20%, or 288 min, in which case the questionnaire was considered invalid. Adjustment was made by multiplying the excess or missing time by an IA corresponding to a very sedentary activity like sitting, reading a book. Corrections were also made for the subject's age and sex as presented elsewhere [4–8], as well as for autonomy (Table 2).


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  		Table 2 Corrections for autonomy reported in specific activities

 
Intensity levels and types of activity were identified in reference to DEE as presented below in order to explore the influence of the amount of specific activity levels on physical fitness:
– PAEE: physical activity energy expenditure during the awakened period.
– PAlow: Physical activity below 3 MET (metabolic equivalent), including housework, chores, moving about...below 3 MET.
– PAhigh: Physical activity above 3 MET, including sports, gardening, housework, leisure...above 3 MET.
– PAintensive: Intensive activities (greater than 5 MET).
– The intensity of 3 MET, corresponding to the IA of walking, was chosen to separate active from non-active patients.

2.3. Validation of the questionnaire
The questionnaire-derived measures were compared to data available from the literature obtained with the doubly labeled water technique in age and pathology-matched individuals in free-living conditions [20,31,33,34]. Reported values range from 7817±1453 kJ 24 h–1 in 12 cachectic CHF patients [33] to 11816 range 5960–22622 kJ 24 h–1 in 12 compensated CHF patients [31].

Peak VO2, maximal VE/VO2 and maximal VE/VCO2 were established from a maximal cycloergometer symptom-limited exercise test performed by all participants on an electronically calibrated cycle ergometer under control of a cardiologist and specialized technicians. After a 2 min warm-up at 10 W, braking forces increased by 10 W every minute at a cycling frequency of 60 rev./min. Standard 12-lead electrocardiograms were obtained at rest, each minute during exercise and in the recovery phase. Blood pressure was monitored using a standard sphygmomanometer, at rest and every two minutes during exercise and recovery. Levels of mixed expired oxygen (O2), mixed expired carbon dioxide (CO2), and expired volume were analyzed at rest and every 15 s during the protocol using the Medical Graphic Corporation Metabolic cart gas analyzer (Saint Paul, Minnesota, USA). Instruments were calibrated before each test. Peak VO2 was defined as the average VO2 occurring during the last 30 s of maximal exercise. A minimum of 3 min was allowed before starting each test to ensure that stable resting measurements were obtained. Each subject was encouraged to exercise until exhaustion and none of them stopped exercise due to angina or claudication. The criteria for reaching the peak O2 consumption were a respiratory exchange ratio above one and/or dyspnoea and/or physical exhaustion.

Anthropometric characteristics were also used as measures of health status and physical fitness and include height, weight and body mass index (BMI) in all participants. Body composition assessment were performed using bioelectrical impedance analysis (BIA) in a subgroup of 21 participants. Resistance and reactance were measured by BIA generator (Bio-Z2, Spengler, Paris, France) and used to mathematically derive fat-free mass (FFM) and fat mass (FM), by using the formula V={rho}xht2/R, where the conductive volume (V) is assumed to represent FFM, {rho} is the specific resistivity of the conductor, height (ht) is the length of the conductor, and where the body resistance (R) is measured with four surface electrodes placed on the right wrist and ankle [24].

The reproducibility of the questionnaire was assessed by a test–retest design. It was completed twice with an interval of at least 6 weeks [5] by 24 stable CHF patients. Initially, patients were addressed to the hospital for exercise testing in the follow-up control of their heart failure condition (including echography and clinical observation). On this occasion, they were asked to fill in the physical activity questionnaire and instructed to be as precise and objective as possible with regard to their usual mean daily physical activities. If no intervention was to take place (cardiac rehabilitation, surgery...), a second questionnaire was sent by regular mail at least six weeks (minimal period between two assessments in order not to be influenced by the first questionnaire) [22] after the first administration for test-retest purposes. Reproducibility was tested for total DEE and each of its single major components.

The sensitivity of the questionnaire was assessed in 21 patients by changes in DEE or its components in reference to changes in peak VO2, VE/VO2, VE/VCO2 and anthropometric characteristics following an intervention (cardiac rehabilitation program of two months or any intervention like pacemaker implantation or routine clinical follow-up resulting in a control visit at the hospital with symptom-limited maximal exercise testing).

Inter-observer variability was assessed with two experienced technicians decoding the 105 questionnaires.

2.4. Statistical analysis
Differences in anthropometric characteristics, peak VO2, VE/VO2, VE/VCO2 and activity scores between men and women and ICM/DCM groups were assessed by an analysis of variance and an unpaired Student t-test.

Reproducibility was assessed by repeated measures ANOVA. Sensitivity was assessed by simple regression analysis between differences in DEE, anthropometric variables and peak VO2. Inter-observer variability was assessed by a paired Student t-test with an estimation of the average error between the energy expenditures obtained from the questionnaire.

The relationships between validation variables, characteristics of the subjects and the questionnaire's activity scores were estimated using simple and multiple regression analysis and Pearson product moment correlation coefficients. Non-linear regression was used to assess the standard error of estimates for DEE and PAEE-peak VO2 relationships. Analysis of covariance (ANCOVA) was used to calculate the interaction between DEE and its components estimated from the questionnaire, ICM/DCM, NYHA class, sex, LVEF and age with peak VO2 as the dependant variable. Statistical significance was set at P<0.05 for all analyses.


   3. Results
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
4. Discussion
 References
 
3.1. Subjects
One hundred and five patients met all inclusion criteria. Because no significant differences in any variable between ICM and DCM subgroups was found, besides for height in women (P=0.02), data were pooled for these groups. No significant differences were found for age, LVEF, BMI, NYHA, and peak VO2 between women and men (Table 3).


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  		Table 3 Characteristics of the population

 
3.2. Reproducibility
Repeated measures ANOVA revealed no significant differences between two administrations of the 24 questionnaires explored in any area of activities’ energy expenditure investigated.

3.3. Sensitivity of the questionnaire
No changes in NYHA class, age, or LVEF were noticed between two assessments in the population sample retained. Change in peak VO2 (ml min–1) was statistically related to DEE (kJ 24 h–1) and PAEE (kJ 24 h–1) variations (r=0.88, P<0.0001 and r=0.84, P=0.0006, respectively) in 21 patients. Post rehabilitation VE/VCO2 reduction was significantly related to increases in DEE (r=0.723, P=0.0298). No significant relationships were noted between modifications in VE/VO2 and DEE.

3.4. Inter-observer validity
The paired Student t-test did not reach statistical significance for any of the area of activities’ energy expenditure when analyzed by two independent observers. Inter-observer variability error was 1.37% for DEE. Fig. 1 illustrates DEE and DEE dimensions obtained by the two observers in 105 questionnaires.


Figure 1
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  		Fig. 1 DEE and DEE dimensions obtained through questionnaire processing by two independent observers (N=105).

 
3.5. DEE and activity components
The average error in the number of minutes the subject reported for a day was 51±18 min. All patients but 19 were out of work, stopped or retired.

Neither sex, LVEF, ICM/DCM nor BMI were significant factors of variations in DEE when corrected for weight. DEE from the questionnaire was in accordance with the literature in age and pathology matched populations and averaged 11 127.52±3051.83 kJ 24 h–1. DEE was strongly correlated to PAEE (r=0.96, P<0.0001) and both decreased with age (r=0.71 and 0.54, respectively, P<0.0001 both). DEE and PAEE were significantly different between NYHA class I and classes II, III, and IV but not between classes II, III and IV. DEE was significantly higher in the group of subjects, all men, with an occupation (13 604±2905 kJ 24 h–1 vs. 10 702±2549 kJ 24 h–1, P<0.0001) since PAEE was significantly higher (6361±1903 kJ 24 h–1 vs. 4099±1432 kJ 24 h–1). Individuals with an occupation, all men, were significantly younger (47±7 years vs. 58±12 years, P<0.0001) and all in NYHA classes I and II.

Multiple regression analysis showed that the contribution to DEE of its components was different in women and men. In women, DEE depended mainly on PAhigh (r=0.79, P<0.0001) but not PAlow nor PAintensive (NS). In men, the major contributors to DEE was PAhigh (r=0.74, P<0.0001) and PAlow (r=0.35, P=0.0025) but not PAintensive (NS). In the group of individuals with an occupation, no specific factor was outstanding although PAhigh, even decreased, remained the principal, but non-significant contributor.

3.6. Peak VO2
Results of peak VO2 are presented in Table 3 and were independent of ICM/DCM condition and sex, poorly related to LVEF (r=0.24, P=0.018) and decreased with age (r=0.49, P<0.0001). Average maximal heart rate was 142±23 bpm corresponding to 86±14% of the predicted maximal heart rate. Average maximal respiratory exchange ratio was 1.19±0.1, suggesting a maximal effort in all. Significant differences were noticed in peak VO2 between all NYHA classes (P<0.0001 to P=0.017) but between classes III and IV (P=0.28; class I: 22.6±4.4 ml min–1 kg–1, class II: 14.4±4.0 ml min–1 kg–1, class III: 13.1±2.1 ml min–1 kg–1, class IV: 11.5±2.5 ml min–1 kg–1). ANCOVA analysis of the interaction between NYHA classes and age with peak VO2 as the dependant variable did not indicate further difference between classes III and IV. Peak VO2 estimated from the questionnaire was not different from peak VO2 obtained from exercise testing (t-value=–0.043; P=NS).

3.7. Relationships between EE and validation variables
Table 4 presents the relationships between DEE and the validation variables. DEE and PAEE were strongly correlated to peak VO2 in the whole sample (r=0.72, SEE=3.32 and 0.72, SEE=10.32, respectively, P<0.0001) as presented in Fig. 2. ANCOVA indicated that there were no differences in these relationships in either sex (F=O.152, P=0.70; F=0.18, P=0.89, respectively) but depended significantly on NYHA classes (P<0.0001 all) except between classes III and IV (NS). VE/VO2 and VE/VCO2 were both inversely related to DEE (r=0.301, P=0.0059 and r=O.313, P=0.0039, respectively) and PAEE (r=0.291, P=0.0069 and r=O.321, P=0.003, respectively). Multiple regression analysis showed that among the components of PAEE, PAhigh was the most significantly correlated to peak VO2 (r=0.62, P<0,0001) for the whole group. This relationship was very significant in men both with and without an occupation. In women, multiple regression analysis showed that peak VO2 was not principally explained by any specific component of PAEE.


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  		Table 4 Relationships between DEE and validation variables. For abbreviations, see text

 


Figure 2
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  		Fig. 2 Relationships between DEE or PAEE and peak VO2 for the whole population sample (N=105).

 
Multiple regression analysis showed for the whole population sample that peak VO2 was significantly related to DEE (P<0.0001) and NYHA class (P<0.0001) but not with LVEF nor age. In women though, none of these factors explained principally peak VO2 (all NS). No significant differences were found between ICM and DCM condition.

As a peak VO2 of 15 ml min–1 kg–1 is often considered as a threshold for considering heart transplantation in heart failure, it is important to notice that the relative error of prediction by DEE estimated by the questionnaire is higher for the lowest values. Mean error below 15 ml min–1 kg–1 was 21.0±22.9% and –6.4±13.8% above.


   4. Discussion
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
References
 
The main finding of this study was that the present questionnaire appears to be a reproducible, sensible, objective and valid tool for the estimation of peak VO2 and daily energy expenditure, offering the opportunity to get a detailed picture of habitual physical activities in CHF patients. More specifically, among the components of DEE, only PAhigh was significantly correlated to peak VO2 (r=0.62).

The questionnaire showed a very good reproducibility in all activity areas. All existing questionnaires evaluating the patient's functional status, prognosis, symptoms, exercise capacity or therapeutic interventions were not systematically tested for reproducibility or usually showed poor results like for the NYHA. The high coherence between observers further demonstrated the good internal structure of the questionnaire, allowing little subjective interpretation. This was all the more confirmed by the good sensitivity of the questionnaire, having wider implications in the follow-up control of patients (effects of exercise training, pacemaker therapy...).

The good correlation between DEE and peak VO2 and other indices of physical fitness is of particular importance since the knowledge of the appropriate dose and type of physical activity for health benefits in CHF patients is an unresolved issue. Peak VO2 provides valuable information about clinical outcome, pathophysiological assessment and general health status in CHF but its sole use is not sufficient in order to represent ‘real life’ condition. Strong relationships between peak VO2 and daily energy expenditure have been reported in populations with cardiopulmonary or musculoskeletal chronic diseases [26] and in the elderly. In healthy populations, the daily amount of physical activity along with the phenotype appeared to be the major determinants of peak VO2. In CHF, the phenotype may explain in part the discrepancies in the relationship between DEE and peak VO2 with the pathology being an added determinant factor.

DEE estimated from the questionnaire using the factorial method, that has proved to be valid in specific populations [6,14,18,30,35,36], was in agreement with previous studies measuring DEE with the doubly labeled water technique in similar but slightly older free-living CHF patients [31,33,34]. Corrections in the energy cost values had to be made for age and sex and the error in time reporting had to be minimized, usually with acceptance margins or error thresholds. The specific design of the questionnaire with a very precise exploration of daily physical activities added to the special consideration, even though subjective, made for autonomy in CHF patients, and a time reporting error less than five percent probably explain the accuracy of the DEE estimation. Furthermore, the obtained values were coherent with the literature and discriminate correlation coefficients could be obtained between the types of activities. However, the accuracy of this questionnaire may be reinforced with a validation study with doubly labeled water or a determination of specific energy costs of activities, relative to the severity of the condition in CHF patients. Further studies should address these issues in such specific populations.

Total DEE was correlated to PAEE and the pattern of activities contributing to DEE variations was different between women and men while PAhigh was in all cases the major factor of variation along with age, even when still on occupation. The decrease of DEE with age is in accordance with previous studies in healthy subjects and can be explained both with the decrease in daily physical activity confirmed here and the decrease in muscle mass and muscle cell activity as recently proved by Piers et al. [25]. We did not find significant differences in DEE between women and men, which is rather unusual in healthy populations. This may be explained by the reduced number of female patients, the expression of DEE relative to body weight and by the differences in pattern of activities. The negative relationship between DEE, PAEE and the ventilatory cost of O2 consumption and CO2 elimination suggests an impact of the severity of the disease on exercise capacity and DEE. Also, a tendency towards a decrease in DEE was noticed in relation to the NYHA classes suggesting that even at a low DEE, the severity of the state may contribute to a higher sedentarity. This assumption is all the more reinforced by the observation that the subjects who addressed the questions dealing with autonomy were the oldest and those with the lowest DEE. However, both the hypothesis of a higher metabolic rate in relation to the condition, as sometimes reported for the resting energy expenditure [20,27,28], and a possible insufficient sensitivity of the questionnaire might explain these results.

Total DEE and more specifically PAhigh appears thus to be highly correlated to peak VO2 in CHF patients, supporting the assumption of the importance of a physical active lifestyle in cardiovascular fitness and more broadly health status, even in CHF patients. It seems that this questionnaire meets the requirements for a valid and reliable physical activity questionnaire to discriminate various levels of energy expenditure. It could be used in epidemiology and in clinical settings in complement to exercise testing to prescribe and monitor an adapted personalized physical rehabilitation program and/or drug treatment as well as to assess objectively its benefit, in terms of DEE and peak VO2, in follow-up control routine. Combined to the clinical characteristics and the feelings of the patient as well as an eventual exercise testing, an optimized treatment strategy can be adapted. After all, a physically active lifestyle may just be public health's best buy [29].


   References
Top
 Abstract
 1. Introduction
 2. Methods
 3. Results
 4. Discussion
 References
 

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