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Physical Activity Patterns of Patients With Cardiopulmonary Illnesses

      Abstract

      Nguyen HQ, Steele BG, Dougherty CM, Burr RL. Physical activity patterns of patients with cardiopulmonary illnesses.

      Objectives

      The aims of this paper were (1) to describe objectively confirmed physical activity patterns across 3 chronic cardiopulmonary conditions, and (2) to examine the relationship between selected physical activity dimensions with disease severity, self-reported physical and emotional functioning, and exercise performance.

      Design

      Cross-sectional study.

      Setting

      Participants' home environment.

      Participants

      Patients with cardiopulmonary illnesses: chronic obstructive pulmonary disease (COPD) (n=63), heart failure (n=60), and patients with implantable cardioverter defibrillator (n=60).

      Interventions

      Not applicable.

      Main Outcome Measures

      Seven ambulatory physical activity dimensions (total steps, percent time active, percent time ambulating at low, medium, and high intensity, maximum cadence for 30 continuous minutes, and peak performance) were measured with an accelerometer.

      Results

      Subjects with COPD had the lowest amount of ambulatory physical activity compared with subjects with heart failure and cardiac dysrhythmias (all 7 activity dimensions, P<.05); total step counts were: 5319 versus 7464 versus 9570, respectively. Six-minute walk distance was correlated (r=.44–.65, P<.01) with all physical activity dimensions in the COPD sample, the strongest correlations being with total steps and peak performance. In subjects with cardiac impairment, maximal oxygen consumption had only small to moderate correlations with 5 of the physical activity dimensions (r=.22–.40, P<.05). In contrast, correlations between 6-minute walk test distance and physical activity were higher (r=.48–.61, P<.01) albeit in a smaller sample of only patients with heart failure. For all 3 samples, self-reported physical and mental health functioning, age, body mass index, airflow obstruction, and ejection fraction had either relatively small or nonsignificant correlations with physical activity.

      Conclusions

      All 7 dimensions of ambulatory physical activity discriminated between subjects with COPD, heart failure, and cardiac dysrhythmias. Depending on the research or clinical goal, use of 1 dimension, such as total steps, may be sufficient. Although physical activity had high correlations with performance on a 6-minute walk test relative to other variables, accelerometry-based physical activity monitoring provides unique, important information about real-world behavior in patients with cardiopulmonary illness not already captured with existing measures.

      Key Words

      List of Abbreviations:

      ATS (American Thoracic Society), COPD (chronic obstructive pulmonary disease), EF (ejection fraction), FEV1 (forced expiratory volume in 1 second), SAM (StepWatch 3 Activity Monitor), 6MWT (6-minute walk test), V̇o2max (maximal oxygen consumption)
      CARDIOPULMONARY DISEASES are the leading cause of morbidity and mortality worldwide.
      World Health Organization
      Global status report on noncommunicable diseases 2010: description of the global burden of NCDs, their risk factors and determinants.
      Epidemiologic studies based on self-reported physical activity show that higher levels of activity are associated with lower risk of incident chronic obstructive pulmonary disease (COPD) in smokers and in patients with COPD, decreased risk of hospital admissions, exacerbations, and mortality.
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      Regular physical activity reduces hospital admission and mortality in chronic obstructive pulmonary disease: a population based cohort study.
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      Regular physical activity modifies smoking-related lung function decline and reduces risk of chronic obstructive pulmonary disease: a population-based cohort study.
      A recent 4-year prospective study of 170 patients with COPD showed that objectively measured physical activity was the best predictor of all-cause mortality when compared with a broad range of other prognostic factors including airflow obstruction, exercise performance, cardiovascular status, nutritional and muscular status, systemic inflammation, health status, depressive symptoms, and dyspnea. Each increase of 1845 steps per day was associated with a 51% lower risk of death (hazard ratio, .49; 95% confidence interval, .35–.69).
      • Waschki B.
      • Kirsten A.
      • Holz O.
      • et al.
      Physical activity is the strongest predictor of all-cause mortality in patients with chronic obstructive pulmonary disease: a prospective cohort study.
      The physiologic processes underlying the relationship between physical activity and survival are complex and only incompletely understood. However, it has been hypothesized that inactivity leads to cellular and molecular dysregulation, which directly contributes to the development of multiple chronic conditions.
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      Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity).
      US Department of Health and Human Services
      Physical Activity Guidelines Advisory Committee Report.
      Similarly, associations have been found for self-reported physical activity with the primary and secondary prevention of cardiovascular diseases in a number of epidemiologic studies.
      • Thompson P.D.
      • Buchner D.
      • Pina I.L.
      • et al.
      Exercise and physical activity in the prevention and treatment of atherosclerotic cardiovascular disease: a statement from the Council on Clinical Cardiology (Subcommittee on Exercise, Rehabilitation, and Prevention) and the Council on Nutrition, Physical Activity, and Metabolism (Subcommittee on Physical Activity).
      US Department of Health and Human Services
      Physical Activity Guidelines Advisory Committee Report.
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      • et al.
      Walking compared with vigorous exercise for the prevention of cardiovascular events in women.
      • Tanasescu M.
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      • Hu F.B.
      Physical activity in relation to cardiovascular disease and total mortality among men with type 2 diabetes.
      However, far fewer studies have been published on objectively measured physical activity in select cardiac populations, such as heart failure,
      • van den Berg-Emons H.
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      • Balk A.
      • Keijzer-Oster D.
      • Stam H.
      Level of activities associated with mobility during everyday life in patients with chronic congestive heart failure as measured with an “activity monitor”.
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      • Schuster T.
      • et al.
      Accelerometer-based quantification of 6-minute walk test performance in patients with chronic heart failure: applicability in telemedicine.
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      • Hanssen H.
      • Schuster T.
      • Halle M.
      • Koehler F.
      Association of physical activity and prognostic parameters in elderly patients with heart failure.
      severe cardiac dysrhythmias, or coronary artery disease, to provide useful benchmarks of physical activity levels for comparisons across studies. Activity monitoring based on accelerometry can more precisely capture what patients actually do in their daily lives instead of what they report or what they are capable of with laboratory exercise testing.
      • Walker P.P.
      • Burnett A.
      • Flavahan P.W.
      • Calverley P.M.
      Lower limb activity and its determinants in COPD.
      While the pathophysiologic processes in the development of COPD, heart failure, and cardiac rhythm disorders differ, we posit that decreased physical activity is a common pathway to impaired functioning and disability in these and other chronic conditions
      • Tinetti M.E.
      • McAvay G.J.
      • Chang S.S.
      • et al.
      Contribution of multiple chronic conditions to universal health outcomes.
      and that objective assessment of physical activity provides a unique but universal metric for comparison across diseases and studies. Therefore, the aims of this article are (1) to describe objectively confirmed physical activity patterns across 3 chronic cardiopulmonary conditions, and (2) to examine the relationship between selected physical activity dimensions with disease severity, self-reported physical and emotional functioning, and exercise performance.

      Methods

      Participants

      Between 2007 and 2010, a combined convenience sample of 183 outpatients at a Veterans Administration and university medical center were selected for study from the combined databases of 3 similar outpatient studies of activity patterns in cardiopulmonary illness.
      • Dougherty C.M.
      • Glenny R.W.
      • Kudenchuk P.J.
      • Malinick T.E.
      • Flo G.L.
      Testing an exercise intervention to improve aerobic conditioning and autonomic function after an implantable cardioverter defibrillator (ICD).
      • Dougherty C.M.
      • Steele B.G.
      • Hunziker J.
      Testing an intervention to improve functional capability in advanced cardiopulmonary illness.
      All subjects had either a diagnosis of COPD, a history of life-threatening cardiac arrhythmias, or heart failure and had been clinically stable for at least 1 month and under optimal medical management. All subjects were able to read, speak, and write English and were not carrying out more than 2 days of supervised exercise per week. Subjects were excluded if they had less than 1 year to live, active malignancy, hypoxia with exertion (oxygen saturation <86% during exercise testing), significant psychiatric illness or recent drug abuse that would impair participation, and neuromuscular disease that limited daily activity. In addition, subjects were excluded if they evidenced disease exacerbation, uncontrolled cardiac dysrhythmias, unstable angina, recent myocardial infarction, or cardiothoracic surgery within the past 3 months.

      COPD sample (n=63)

      The COPD subjects had to have at least mild COPD (Global Initiative for Obstructive Lung Disease stage I), defined as a postbronchodilator forced expiratory volume in 1 second (FEV1)/forced vital capacity ratio <.70 with FEV1>80% predicted with daily activities limited by dyspnea.

      Heart failure sample (n=60)

      In addition to the general inclusion and exclusion criteria described earlier, heart failure subjects had to have an ejection fraction (EF) of ≤.35
      • Moss A.J.
      • Zareba W.
      • Hall W.J.
      • et al.
      Prophylactic implantation of a defibrillator in patients with myocardial infarction and reduced ejection fraction.
      • Bardy G.H.
      • Lee K.L.
      • Mark D.B.
      • et al.
      Amiodarone or an implantable cardioverter-defibrillator for congestive heart failure.
      and daily activities limited by dyspnea or fatigue.

      Cardiac dysrhythmia sample (n=60)

      In addition to the general inclusion and exclusion criteria, the cardiac dysrhythmia sample had a history of life-threatening dysrhythmia that required the placement of an implantable cardioverter defibrillator for secondary prevention of sudden cardiac arrest. These subjects were also on beta blockers.

      Measurements

      Demographics

      Data included self-reported age, sex, education, and marital status.

      Health status

      Health status included self-report of chronic conditions (Charlson comorbidity index), EF obtained from medical records, and spirometry, which was performed according to American Thoracic Society (ATS) standards using a Koko spirometer.a Postbronchodilator values were used.

      Exercise performance

      Performance was assessed using the 6-minute walk test (6MWT)
      ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories
      ATS statement: guidelines for the Six-Minute Walk Test.
      and a modified Balke treadmill symptom-limited test protocol.
      • Balke B.
      • Ware R.
      An experimental study of physical fitness of air force personnel.
      Participants performed two 6MWTs according to ATS guidelines, and the longer of the 2 tests was used for analysis. Maximal oxygen consumption (V̇o2max) was measured during the cardiopulmonary exercise test session in an exercise laboratory and determined as the average value observed over the last 10 seconds of exercise (Viasys VMax series 229b).

      Ambulatory physical activity

      This was measured using a pager-sized, lightweight, StepWatch 3 Activity Monitor (SAM)c fastened above the right ankle. The SAM is a dual-axis accelerometer linked to a microprocessor sensor that directly and continuously records gait cycles (strides) based on acceleration, position, and timing information. Stride counts are doubled to represent steps. The SAM has been validated for use in healthy and chronically ill older adults in laboratory and community settings and has an accuracy of 98% to 99%.
      • Cavanaugh J.T.
      • Coleman K.L.
      • Gaines J.M.
      • Laing L.
      • Morey M.C.
      Using step activity monitoring to characterize ambulatory activity in community-dwelling older adults.
      • Gardner A.W.
      • Montgomery P.S.
      • Scott K.J.
      • Afaq A.
      • Blevins S.M.
      Patterns of ambulatory activity in subjects with and without intermittent claudication.
      Participants were asked to wear the SAM during waking hours for 7 days at baseline. The SAM was programmed to record in 1-minute epochs; a valid day was defined as having 10 or more hours (600min) of monitor wear.
      The StepWatch software was used to produce the following physical activity dimensions: (1) total daily steps taken, percent time active, percent time spent ambulating at low intensity (1–30 steps/min), medium intensity (31–80 steps/min), and high intensity (≥80 steps/min), (2) maximum cadence for 30 continuous minutes, which provides a proxy of walking intensity during a typical recommended bout of endurance exercise, and (3) peak performance, which represents short walking bursts and is obtained by ranking all minutes of the day according to cadence, and then averaging the highest 30 values. These variables were calculated for each day, and then the daily values were averaged over the total monitoring period.

      Health-related quality of life

      Health-related quality of life was measured with the Medical Outcomes Study 36-Item Short-Form Health Survey.
      • Ware Jr, J.E.
      • Sherbourne C.D.
      The MOS 36-item short-form health survey (SF-36) I. Conceptual framework and item selection.
      The Medical Outcomes Study 36-Item Short-Form Health Survey produces 2 composite scales of physical and mental functioning with higher scores indicating better health-related quality of life.

      Data Analysis

      Analysis of variance or Fisher exact tests were used to compare demographic, disease severity, functioning, and physical activity patterns across groups. Pearson correlation coefficients were computed for the bivariate correlations. All analyses were conducted using SPSS 15.0.d The P value <.05 was considered statistically significant.

      Results

      Sample Characteristics

      The COPD sample was the oldest with a mean age of 67. A majority of the total sample were obese white males with at least some college education (table 1). Although the heart failure sample had the highest chronic disease burden, their self-reported physical functioning score was better than the COPD sample. The younger sample with cardiac dysrhythmias had the worst mental health functioning score despite a lower chronic disease burden and the highest physical functioning score of the 3 groups. The 6MWT was not significantly different between the COPD sample and heart failure sample. As expected, V̇o2max was significantly different between patients with heart failure and cardiac dysrhythmias.
      Table 1Subject Characteristics
      CharacteristicsCOPDHeart FailureCardiac DysrhythmiasTotalANOVA
      Overall group comparison; pairwise comparisons with Bonferroni corrections: P<.05,
      (n=63)(n=60)(n=60)(N=183)(P)
      Age67.0±9.360.5±10.855.4±11.661.1±11.6<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      Sex (male)58 (91)57 (95)44 (72)159 (86)<.001
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      Ethnicity (white)53 (83)48 (80)58 (95)159 (86).040
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      Education (at least some college)31 (48)41 (73)44 (72)119 (64).006
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      Body mass index29.7±7.030.5±7.029.0±6.029.7±6.7.460
      Charlson comorbidity index1.6±1.22.3±1.31.0±0.91.6±1.2<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      EF55±827±749±1141±15<.001
      COPD versus heart failure,
      heart failure versus cardiac dysrhythmias.
      Spirometry
       FEV1 (% predicted)36±1572±2085±1564±27<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
       FVC (% predicted)57±1673±1785±1472±20<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
       FEV1/FVC0.46±0.160.73±0.110.73±0.080.64±0.17<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      Health-related quality of life
       SF-36 physical component score30.7±7.742.7±11.851.2±9.041.4±12.8<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
       SF-36 mental component score45.3±13.043.4±8.640.7±6.343.1±9.9.035
      Exercise performance
       6MWT (m)340.2±113.1385.2±104.4 (n=24)NA353.6±112.0.094
       V̇o2max (mL·min-1·kg-1)NA20.3±5.3 (n=36)24.4±6.122.8±6.1.001
      NOTE. Values shown are mean ± SD or count (%).
      Abbreviations: ANOVA, analysis of variance; FVC, forced vital capacity; NA, not applicable; SF-36, Medical Outcomes Study 36-Item Short-Form Health Survey.
      low asterisk Overall group comparison; pairwise comparisons with Bonferroni corrections: P<.05,
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      § heart failure versus cardiac dysrhythmias.

      Physical Activity Patterns

      StepWatch recordings were available for a median of 5 days (range, 3–18d), a sufficient duration for cross-sectional descriptions of physical activity patterns.
      • Trost S.G.
      • McIver K.L.
      • Pate R.R.
      Conducting accelerometer-based activity assessments in field-based research.
      • Nguyen H.Q.
      • Burr R.L.
      • Gill D.P.
      • Coleman K.
      Validation of the Stepwatch device for measurement of free-living ambulatory activity in patients with COPD.
      The COPD sample engaged in the lowest amount of ambulatory physical activity compared with the 2 cardiac samples—total daily steps were 5319 (COPD) versus 7464 (heart failure) versus 9570 (cardiac dysrhythmias) (P<.001) (table 2). The total daily step count for subjects with cardiac dysrhythmias was comparable with that of healthy adults.
      • Tudor-Locke C.
      • Bassett Jr, D.R.
      How many steps/day are enough? Preliminary pedometer indices for public health.
      • Tudor-Locke C.E.
      • Myers A.M.
      Methodological considerations for researchers and practitioners using pedometers to measure physical (ambulatory) activity.
      The COPD subjects also spent the lowest percentage of time being active but this was only significantly different from subjects with cardiac dysrhythmias (32% vs 38%, P<.05). The 2 cardiac samples spent a similar percentage of time in medium intensity walking activity (25% and 27%) and were both significantly higher than the COPD sample (22%). Subjects with COPD spent most of their active time in low intensity activity (76%) in contrast with subjects with cardiac dysrhythmias, who spent 66% of their time in low intensity activity. Peak performance was significantly different across groups with the cardiac dysrhythmias sample having the highest step rate. MaxSteps30, which captures the highest step rate in 30 minutes and is a proxy for walking intensity during a typical recommended bout of endurance exercise, showed that subjects with COPD performed only 51% of their walking capacity (peak performance) compared with 61% to 66% in the cardiac samples.
      Table 2Ambulatory Physical Activity Across Cardiopulmonary Diseases
      Physical Activity DimensionsCOPD (n=63)Heart Failure (n=60)Cardiac Dysrhythmias (n=60)Total (N=183)FANOVA
      Overall group comparison; pairwise comparisons with Bonferroni corrections: P<.05,
      (P)
      Total steps5319±27127464±37249570±36227416±378324.4<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      % time active32±1435±1238±1135±134.1.015
      COPD versus cardiac dysrhythmias, and
      % time high intensity (>80 steps/min)2±25±57±54±519.4<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      % time medium intensity (31–80 steps/min)22±825±827±625±89.5<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      % time low intensity (≤30 steps/min)76±970±1066±871±1022.4<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      Peak performance (steps/min)57±1671±2085±1871±2138.4<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      MaxSteps30 (steps/min)28±1243±2357±2443±2326.9<.001
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      heart failure versus cardiac dysrhythmias.
      NOTE. Values shown are mean ± SD.
      Abbreviation: ANOVA, analysis of variance.
      low asterisk Overall group comparison; pairwise comparisons with Bonferroni corrections: P<.05,
      COPD versus heart failure,
      COPD versus cardiac dysrhythmias, and
      § heart failure versus cardiac dysrhythmias.

      Bivariate Correlations

      In the COPD sample, 6-minute walk distance had moderate to high correlations (r=.44–.65, P<.01) with all 7 physical activity dimensions, the strongest correlations being with total steps and peak performance (table 3 and fig 1). Airway obstruction (FEV1% predicted) had small to moderate correlations with all (r=.30 to –.45, P<.01) but 1 dimension of physical activity: percent time active. Self-reported physical functioning was correlated only with peak performance (r=.27, P<.05). Age, body mass index, and mental health functioning were not significantly correlated with any of the physical activity dimensions, whereas higher chronic disease burden was associated with less time spent in high intensity walking activity (r=−.26, P<.05).
      Table 3Correlations Between Physical Activity Dimensions With Demographics, Health Status, and Exercise Performance in Patients With COPD (n=63)
      Variables1234567891011121314
      1. Total steps1.00
      2. % time active0.85
      P<.01;
      1.00
      3. % time high intensity0.53
      P<.01;
      0.25
      P<.05.
      1.00
      4. % time medium intensity0.63
      P<.01;
      0.32
      P<.05.
      0.30
      P<.05.
      1.00
      5. % time low intensity−0.68
      P<.01;
      −0.33
      P<.01;
      −0.63
      P<.01;
      −0.98
      P<.01;
      1.00
      6. Peak performance0.87
      P<.01;
      0.62
      P<.01;
      0.80
      P<.01;
      0.70
      P<.01;
      −0.80
      P<.01;
      1.00
      7. MaxSteps300.79
      P<.01;
      0.60
      P<.01;
      0.75
      P<.01;
      0.54
      P<.01;
      −0.65
      P<.01;
      0.90
      P<.01;
      1.00
      8. 6-minute walk distance0.64
      P<.01;
      0.51
      P<.01;
      0.47
      P<.01;
      0.53
      P<.01;
      −0.57
      P<.01;
      0.65
      P<.01;
      0.44
      P<.01;
      1.00
      9. Age−0.22−0.19−0.09−0.110.12−0.13−0.07−0.221.00
      10. Body mass index0.02−0.080.090.22−0.210.080.13−0.21−0.091.00
      11. FEV1 (% predicted)0.30
      P<.05.
      0.150.44
      P<.01;
      0.40
      P<.01;
      −0.45
      P<.01;
      0.43
      P<.01;
      0.39
      P<.01;
      0.170.100.41
      P<.01;
      1.00
      12. Comorbidity−0.17−0.09−0.26
      P<.05.
      −0.150.19−0.17−0.12−0.220.230.23−0.101.00
      13. SF-36 physical component score0.180.150.280.18−0.220.27
      P<.05.
      0.220.41
      P<.01;
      0.03−0.060.010.041.00
      14. SF-36 mental component score−0.06−0.150.19−0.060.000.040.07−0.020.22−0.010.060.090.171.00
      Abbreviation: SF-36, Medical Outcomes Study 36-Item Short-Form Health Survey.
      low asterisk P<.01;
      P<.05.
      Figure thumbnail gr1
      Fig 1Scatterplots of the 6-minute walk distance, total steps, and peak performance in subjects with COPD (n=63).
      Maximum V̇o2 had only small to moderate correlations with 5 of the 7 physical activity dimensions (r=.22−.40, P<.05) in the combined cardiac sample (table 4); the strongest correlations were with total steps and peak performance (fig 2). In contrast, correlations between distance covered on a 6MWT with 5 physical activity dimensions were higher (r=.48–.61, P<.01), albeit in a smaller sample of only patients with heart failure (fig 3). Higher comorbidity was associated with less physical activity (r=–.27 to –.44, P<.01) but the EF was only correlated with time spent in high intensity walking activity (r=.19) and peak performance (r=.26). Self-reported physical functioning had small to moderate correlations with 6 of the 7 physical activity dimensions (r=.22–.37, P<.05). Age, FEV1% predicted, body mass index, and mental health functioning were not significantly correlated with any of the physical activity dimensions, with the exception of percent time active and body mass index.
      Table 4Correlations Between Physical Activity Dimensions With Demographics, Health Status, and Exercise Performance in Patients With Heart Failure and Cardiac Dysrhythmias (n=96)
      12345678910111213141516
      1. Total steps1.00
      2. % time active0.78
      P<.01;
      1.00
      3. % time high intensity0.45
      P<.01;
      0.011.00
      4. % time medium intensity0.50
      P<.01;
      0.35
      P<.01;
      −0.031.00
      5. % time low intensity−0.68
      P<.01;
      −0.27
      P<.01;
      −0.64
      P<.01;
      −0.75
      P<.01;
      1.00
      6. Peak performance0.74
      P<.01;
      0.39
      P<.01;
      0.82
      P<.01;
      0.22
      P<.05.
      −0.71
      P<.01;
      1.00
      7. MaxSteps300.69
      P<.01;
      0.33
      P<.01;
      0.83
      P<.01;
      0.15−0.66
      P<.01;
      0.91
      P<.01;
      1.00
      8. V̇o2max0.40
      P<.01;
      0.34
      P<.01;
      0.22
      P<.05.
      0.06−0.190.39
      P<.01;
      0.31
      P<.01;
      1.00
      9. 6-minute walk distance (n=24)0.52
      P<.01;
      0.59
      P<.01;
      0.48
      P<.05.
      0.25−0.380.58
      P<.01;
      0.61
      P<.01;
      NA1.00
      10. Age−0.09−0.140.03−0.020.00−0.080.05−0.41
      P<.01;
      −0.261.00
      11. Body mass index−0.18−0.25
      P<.05.
      −0.070.020.03−0.19−0.16−0.45
      P<.01;
      −0.060.151.00
      12. FEV1 (% predicted)0.190.170.030.15−0.130.130.100.34
      P<.01;
      0.410.03−0.091.00
      13. EF0.120.010.19
      P<.05.
      −0.01−0.120.26
      P<.01;
      0.160.33
      P<.01;
      0.10−0.16−0.070.22
      P<.05.
      1.00
      14. Comorbidity−0.35
      P<.01;
      −0.29
      P<.01;
      −0.27
      P<.01;
      −0.140.29
      P<.01;
      −0.44
      P<.01;
      −0.36
      P<.01;
      −0.51
      P<.01;
      −0.360.30
      P<.01;
      0.24
      P<.05.
      −0.12−0.42
      P<.01;
      1.00
      15. SF-36 physical component score0.35
      P<.01;
      0.210.23
      P<.05.
      0.22
      P<.05.
      −0.32
      P<.01;
      0.37
      P<.01;
      0.27
      P<.01;
      0.29
      P<.01;
      0.39−0.020.060.140.11−0.181.00
      16. SF-36 mental component score0.030.07−0.010.000.01−0.02−0.05−0.010.150.160.080.12−0.150.190.191.00
      Abbreviations: NA, not applicable; SF-36, Medical Outcomes Study 36-Item Short-Form Health Survey.
      low asterisk P<.01;
      P<.05.
      Figure thumbnail gr2
      Fig 2Scatterplots of Vo2max, total steps, and peak performance in subjects with heart failure and cardiac dysrhythmias (n=96).
      Figure thumbnail gr3
      Fig 3Scatterplots of 6-minute walk distance, total steps, and peak performance in subjects with heart failure (n=24).

      Discussion

      The primary finding from this study, which used a highly accurate ankle mounted accelerometer, showed that all dimensions of ambulatory physical activity discriminated between subjects with COPD, heart failure, and cardiac dysrhythmias. Specifically, subjects with COPD engaged in the lowest volume of ambulatory physical activity followed by subjects with heart failure and cardiac dysrhythmias. To the best of our knowledge, we are not aware of any other published reports that have compared physical activity patterns across 3 cardiopulmonary conditions. In both subjects with COPD and cardiac impairment, all 7 physical activity dimensions had the highest correlations with distance covered on a 6MWT; smaller, less consistent associations were found between physical activity and self-reported physical functioning and airway obstruction in the COPD sample and self-reported functioning, EF, and V̇o2max in patients with cardiac impairment. In addition, age, body mass index, and mental health functioning were not related to any of the physical activity dimensions for all subjects. These collective findings suggest that physical activity as measured by an accelerometer provides unique, important information about real-world behavior in patients with COPD, heart failure, and cardiac dysrhythmias not already captured with existing instruments.
      Tudor-Locke et al
      • Tudor-Locke C.
      • Johnson W.D.
      • Katzmarzyk P.T.
      Accelerometer-determined steps per day in US adults.
      established pedometer-determined physical activity cut points for healthy adults as: <2500 steps/day (basal physical activity), 2500 to <5000 steps/day (limited physical activity), 5000 to <7500 (low activity), 7500 to <10,000 (somewhat active), 10,000 to <12,500 (active), and >12,500 (highly active). Recently, a review of 28 studies that included older adults aged 50 to 94 showed mean pedometer-determined physical activity ranged from 2015 steps/day to 8938 steps/day.
      • Tudor-Locke C.
      • Hart T.L.
      • Washington T.L.
      Expected values for pedometer-determined physical activity in older populations.
      Based on these classifications, our COPD sample is considered to be in the low activity category but well within the range of expected step counts for older adults. Earlier studies of patients with COPD that used different activity devices showed similar total step counts and distribution of activity intensity with our study.
      • Walker P.P.
      • Burnett A.
      • Flavahan P.W.
      • Calverley P.M.
      Lower limb activity and its determinants in COPD.
      • Nguyen H.Q.
      • Burr R.L.
      • Gill D.P.
      • Coleman K.
      Validation of the Stepwatch device for measurement of free-living ambulatory activity in patients with COPD.
      • Pitta F.
      • Troosters T.
      • Spruit M.A.
      • Probst V.S.
      • Decramer M.
      • Gosselink R.
      Characteristics of physical activities in daily life in chronic obstructive pulmonary disease.
      • Watz H.
      • Waschki B.
      • Boehme C.
      • Claussen M.
      • Meyer T.
      • Magnussen H.
      Extrapulmonary effects of chronic obstructive pulmonary disease on physical activity: a cross-sectional study.
      • Watz H.
      • Waschki B.
      • Meyer T.
      • Magnussen H.
      Physical activity in patients with COPD.
      Because this is the first study (to the best of our knowledge) to report physical activity patterns in patients with cardiac dysrhythmias, we did not have any benchmark to compare our findings. We were surprised to find relatively high total step count in subjects with cardiac dysrhythmias. Tudor-Locke's classification
      • Tudor-Locke C.
      • Johnson W.D.
      • Katzmarzyk P.T.
      Accelerometer-determined steps per day in US adults.
      would place them in the somewhat active to active category, and they would have the highest step count in comparison with 10 other chronic conditions.
      • Tudor-Locke C.
      • Washington T.L.
      • Hart T.L.
      Expected values for steps/day in special populations.
      Their younger age, limited physical impairment, and few comorbid conditions partly explain their ability to engage in a higher volume of physical activity, that is, more steps, active time, and time spent in high and moderate intensity walking activity. The total step count for subjects with heart failure is similar to one other published study that had a higher percentage of women in the sample, in comparison with our study.
      • Jehn M.
      • Schmidt-Trucksass A.
      • Hanssen H.
      • Schuster T.
      • Halle M.
      • Koehler F.
      Association of physical activity and prognostic parameters in elderly patients with heart failure.
      It is interesting to note that MaxSteps30, which is a proxy for continuous ambulatory exercise intensity over a 30-minute interval, was as low as 51% (COPD sample) to 67% (cardiac dysrhythmias sample) of the peak performance step rate. These data suggest that patients with cardiopulmonary illnesses likely engage in only low to moderate intensity walking exercises when they are unsupervised. Two recent studies of patients with COPD that measured either total energy expenditure using an arm-mounted device or oxygen uptake during 5 self-paced activities of daily living using a portable metabolic cart found that patients use a high proportion of their peak aerobic capacity (55%–85% of peak oxygen consumption) to perform daily activities.
      • Hill K.
      • Dolmage T.E.
      • Woon L.
      • Coutts D.
      • Goldstein R.
      • Brooks D.
      Defining the relationship between average daily energy expenditure and field-based walking tests and aerobic reserve in COPD.
      • Vaes A.W.
      • Wouters E.F.
      • Franssen F.M.
      • et al.
      Task-related oxygen uptake during domestic activities of daily life in patients with COPD and healthy elderly subjects.
      If indeed patients with COPD are already exerting themselves at close to peak capacity with routine domestic activities of daily living, it is only understandable that they may not have sufficient reserve and/or desire to perform their independent walking exercises at a higher intensity. Further research is needed to understand this relationship between metabolic load experienced during domestic activities of daily living and exercise intensity.
      Although the highest correlations between the 7 physical activity dimensions were with distance walked on a 6MWT, these correlations were not as high as a previous study of COPD patients, which used an older model accelerometer that measured activity in vector magnitude units (r=.74).
      • Steele B.
      • Holt L.
      • Belza B.
      • Ferris S.
      • Lakshminaryan S.
      • Buchner D.M.
      Quantitating physical activity in COPD using a triaxial accelerometer.
      The finding of only small correlations between V̇o2max with 5 of the 7 activity dimensions in this study is in contrast to findings by Jehn et al,
      • Jehn M.
      • Schmidt-Trucksass A.
      • Hanssen H.
      • Schuster T.
      • Halle M.
      • Koehler F.
      Association of physical activity and prognostic parameters in elderly patients with heart failure.
      • Jehn M.
      • Schmidt-Trucksass A.
      • Schuster T.
      • et al.
      Daily walking performance as an independent predictor of advanced heart failure: prediction of exercise capacity in chronic heart failure.
      where a different activity monitor and cycle ergometer protocol were used. The correlation between total time walked and V̇o2max was .72 in that study. Differences in the magnitude of associations between various measures of laboratory exercise performance and physical activity across studies could also partly be because of the stability of the estimates and the degree of variability in the correlates. Nevertheless, the consistent small to moderate correlations between the 7 physical activity dimensions with self-reported physical functioning and disease severity across the 3 samples suggest that the measurement of actual physical activity behavior provides additional valuable information on functional impairments associated with cardiopulmonary illnesses and may also contribute to better prediction of survival in these clinical populations.
      • Waschki B.
      • Kirsten A.
      • Holz O.
      • et al.
      Physical activity is the strongest predictor of all-cause mortality in patients with chronic obstructive pulmonary disease: a prospective cohort study.

      Study Limitations

      There are several limitations to this descriptive study. A limitation of the SAM, similar to most other activity monitors on the market, includes the inability to measure activities of the upper extremity and other activities such as bicycling. While lower limb activity cannot be substituted for estimates of total energy expenditure, it is clearly a major determinant of energy expenditure (r=.92) and in most circumstances, is an acceptable surrogate.
      • Walker P.P.
      • Burnett A.
      • Flavahan P.W.
      • Calverley P.M.
      Lower limb activity and its determinants in COPD.
      Because the combined dataset emanated from 3 clinical intervention studies that had specific inclusion and exclusion criteria, the findings may not be generalizable to the broader population of patients with cardiopulmonary illnesses who are more severely affected by their condition and were unable to participate in the clinical trials or were insufficiently active to benefit from an exercise intervention. The COPD and heart failure samples were comprised mostly of men; thus, the findings may not extend to women. In addition, the heart failure sample was relatively small. Also, seasonal variations may also affect physical activity patterns.
      • Sewell L.
      • Singh S.J.
      • Williams J.E.
      • Morgan M.D.
      Seasonal variations affect physical activity and pulmonary rehabilitation outcomes.
      Baseline measurements across the 3 randomized controlled trials were performed throughout the year, though this may not fully account for the variability in the activity patterns.

      Conclusions

      Findings from this study provide a useful benchmark of physical activity patterns in individuals with cardiopulmonary illness for comparison with future studies. All 7 dimensions of ambulatory physical activity discriminated between subjects with COPD, heart failure, and cardiac dysrhythmias. Depending on the research or clinical goal, the use of 1 dimension, such as total steps, may be sufficient. Although physical activity had high correlations with performance on a 6MWT relative to other variables, accelerometry-based physical activity monitoring provides unique, important information about real-world behavior in patients with cardiopulmonary disease, not already captured with existing measures.
      • a
        Pulmonary Data Services, 1301 Courtesy Rd, Louisville, CO 80027.
      • b
        CareFusion Corporation, 3750 Torrey View Ct, San Diego, CA 92130.
      • c
        StepWatch Orthocare Innovations, 840 Research Pkwy, Ste 200, Oklahoma City, OK 73104.
      • d
        SPSS Inc, 233 S Wacker Dr, 11th Fl, Chicago, IL 60606.

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