Download effects of a randomized controlled trial of diet and/or exercise on

EFFECTS OF A RANDOMIZED CONTROLLED TRIAL OF DIET AND/OR
EXERCISE ON OBJECTIVELY MEASURED PHYSICAL ACTIVITY LEVELS IN
OLDER HEART FAILURE PATIENTS
BY
DANIEL SCOTT CLEVENGER
A Thesis Submitted to the Graduate Faculty of
WAKE FOREST UNIVERSITY GRADUATE SCHOOL OF ARTS AND SCIENCES
in Partial Fulfillment of the Requirements
for the Degree of
MASTER OF SCIENCE
Health and Exercise Science
May 2012
Winston-Salem, North Carolina
Approved By:
Peter H. Brubaker, Ph.D., Advisor
Michael J. Berry, Ph.D., Chair
Patricia A. Nixon, Ph.D.
DEDICATION
I would like to dedicate this thesis to my amazing parents. I am blessed beyond measure
to be able to say the two most incredible people I know are my parents. First, to my
mother Nancy: thank you for your unconditional love and support. You have always
been there for me, through life’s successes and trials. You continue to show me every
day how to be Christ-like, by putting the needs and desires of others before your own. I
am incredibly thankful for your example, as well as your guidance. You taught me to
follow my heart even though it might not always be the easiest decision. And to my
father, Jeff: I would not be the man I am today if it was not for your influence. It is my
hope and prayer that someday I will be half of the man that you were. You showed me
what it means to be a Godly man and take care of your family, even among less than
ideal circumstances. Despite your weaknesses, you displayed strength – a strength you
found in Christ. You were the definition of persistence, courage, and determination. I
am fortunate to have developed these characteristics you always portrayed.
ii
ACKNOWLEDGEMENTS
I would like to formally thank:
Dr. Peter Brubaker, for being my thesis advisor, professor, and mentor. I am so thankful
to have been able to work so closely with such a renowned faculty member at Wake
Forest. I am forever grateful for the wealth of knowledge you have shared with me and
for your guidance and direction for my future professional career. I appreciate how you
treated me as a colleague and worked so hard with me to finish this thesis. You made
this process less overwhelming, and without your help it would not have been possible.
Dr. Michael Berry, for being on my thesis committee. I have thoroughly enjoyed having
you as a professor. You taught me that the academic world does not always have to be
professional; it can be fun and entertaining as well. I will never forget your sense of
humor and ability to make stressful environments more easy going.
Dr. Patricia Nixon, for also agreeing to be on my thesis committee. I learned a great deal
from you as a professor and always enjoyed your upbeat attitude. Thank you for further
developing my understanding of the field we study through a larger scope.
Jordan Hauser, for being an amazing supervisor and friend. You were a great example
for how to manage and run a clinic. I am so fortunate to have worked so closely with you
during my second year and I know I will pull from these experiences during my
professional career.
HELPS Participants, who taught me just as much during my time here as the coursework
did. Thank you for the life lessons you taught me and for always being an incredible
resource for advice. I will forever cherish the conversations I had with you all.
My Classmates, for the amazing love and support you gave me over the past 22 months.
I could not have asked for 7 better people to go through this program with. I can honestly
say you know me as well as some of my closest family and friends. You always knew
how to best motivate and encourage me. Each one of you has taught me something I will
forever cherish and I will always consider all of you friends.
Mom, David, Bre, Aaron, and Abbey, for your continuous support. I am so incredibly
blessed to have such amazing people in my life. Despite the difficulty of living so far
away, you were always there to provide encouragement and an escape from the stresses
of my education. At the end of the day, I know you are always there to pick me up when
I need it. I could not ask for better people to call family.
iii
TABLE OF CONTENTS
LISTS OF TABLES AND FIGURES ...................................................................................vii
ABBREVIATIONS ...............................................................................................................viii
ABSTRACT ...........................................................................................................................xii
REVIEW OF LITERATURE ................................................................................................1
Overview of Heart Failure ................................................................................................1
Epidemiology of Heart Failure ....................................................................................1
Risk Factors for Heart Failure ....................................................................................2
Pathophysiology of Heart Failure ...............................................................................4
Acute Responses in Heart Failure ...............................................................................6
Signs/Symptoms, Diagnosis, and Treatment of Heart Failure ....................................7
Recommendation of Physical Activity .............................................................................10
Methods of Quantifying Physical Activity....................................................................13
Comparison of Subjective and Objective Measures of Physical Activity ....................16
Quantifying Physical Activity Levels in Different Populations .......................................19
Healthy Adults ..............................................................................................................19
Elderly ..........................................................................................................................20
Overweight/Obese Individuals .....................................................................................22
Cardiac Patients ..........................................................................................................24
Heart Failure ...............................................................................................................26
Exercise Training Interventions ........................................................................................27
Heart Failure with a Reduced Ejection Fraction (HFrEF) .........................................27
iv
Heart Failure with a Preserved Ejection Fraction (HFpEF) ......................................31
Body Composition and Weight Loss in Heart Failure ......................................................34
SECRET Study .................................................................................................................36
Aims and Hypotheses .......................................................................................................37
METHODS ............................................................................................................................38
Overall SECRET Design ..................................................................................................38
Intervention Groups ..........................................................................................................40
Sub-Study Design .............................................................................................................42
Statistical Analyses ...........................................................................................................44
RESULTS ..............................................................................................................................46
Participant Demographics .................................................................................................46
Treatment Effect on the Primary Outcomes, VO2peak and Body Weight .......................48
Treatment Effect on Physical Activity Measures .............................................................50
Comparison of Exercise and Non-Exercise Days .............................................................54
Physical Activity Measures Versus Primary Outcomes: VO2peak and Body Weight .....58
DISCUSSION ........................................................................................................................59
Participant Demographics .................................................................................................59
Changes in Primary Outcomes: VO2peak and Body Weight............................................61
Changes in Physical Activity Measures ............................................................................64
Comparison of Exercise and Non-Exercise Days .............................................................68
Relationship Between Physical Activity Measures and Primary Outcomes ....................69
Limitations ........................................................................................................................70
Conclusions .......................................................................................................................70
v
APPENDIX A ........................................................................................................................72
APPENDIX B ........................................................................................................................73
APPENDIX C ........................................................................................................................74
APPENDIX D ........................................................................................................................75
REFERENCES ......................................................................................................................79
SCHOLASTIC VITA ............................................................................................................103
vi
LISTS OF TABLES AND FIGURES
TABLES
Table I: Descriptive Characteristics of Study Participants
Table II: Correlations Between Changes in PA Levels and Primary Outcomes
FIGURES
Figure 1: Flow diagram for patient exclusions
Figure 2: Unadjusted Mean Body Weight at Baseline and Follow-Up for the Groups
Figure 3: Unadjusted Mean VO2peak at Baseline and Follow-Up for the Groups
Figure 4: Unadjusted Mean Steps per Day at Baseline and Follow-Up for the Groups
Figure 5: Unadjusted Mean Minutes of LPA at Baseline and Follow-Up for the Groups
Figure 6: Unadjusted Mean Minutes of MVPA and Baseline to Follow-Up for the Groups
Figure 7: Unadjusted Mean Physical Activity Energy Expenditure (PAEE) at Baseline
and Follow-Up for the Groups
Figure 8: Unadjusted Mean Steps/day at 20 Weeks During Non-Exercise Days vs.
Exercise Days
Figure 9: Unadjusted Mean LPA at 20 Weeks During Non-Exercise Days vs. Exercise
Days
Figure 10: Unadjusted Mean MVPA at 20 Weeks During Non-Exercise Days vs.
Exercise Days
Figure 11: Unadjusted Mean Physical Activity Energy Expenditure (PAEE) at 20 Weeks
During Non-Exercise Days vs. Exercise Days
vii
LIST OF ABBREVIATIONS
6MW: Six-Minute Walk Distance
6MWT: Six-Minute Walk Test
ACE – inhibitors: Angiotension-Converting Enzyme - inhibitors
ACSM: American College of Sports Medicine
ALVD: Asyptomatic Left Ventricular Dysfunction
AS: Activity Score
a-vO2 difference: Arterial-Venous Oxygen Difference
BMI: Body Mass Index
BNP: Brain Natriuric Peptide
bpm: Beats per Minute
BRFSS: Behavioral Risk Factor Surveillance System
CAD: Coronary Artery Disease
CDC: Center for Disease Control and Prevention
CHAMPS: Community Health Activities Model Program for Seniors
CLIP: Cooperative Lifestyle Intervention Program
CO: Cardiac Output
COPD: Chronic Obstructive Pulmonary Disease
CPET: Cardiopulmunary Exercise Test
CRC: Colorectal Cancer
CRP: Cardiac Rehabilitation Program
CVD: Cardiovascular Disease
DEE: Daily Energy Expenditure
viii
DEXA: Dual Energy X-ray Absorptiometry
EDV: End-Diastolic Volume
EE: Energy Expenditure
EF%: Ejection Fraction
ESV: End-Systolic Volume
G: Gravitational Constant
HCS: Healthy Control Subject
HF: Heart Failure
HF-ACTION: Heart Failure and A Controlled Trial Investigating Outcomes of exercise
traiNing
HFpEF: Heart Failure with a Preserved Ejection Fraction
HFrEF: Heart Failure with a Reduced Ejection Fraction
HR: Heart Rate
HTN: Hypertension
Hz: Hertz
IADL: Instrumental Activities of Daily Living
IPAQ: International Physical Activity Questionnaire
kcal: kilocalorie
kg: Kilogram
LPA: Light Physical Activity
LV: Left Ventricle
LVEF: Left Ventricular Ejection Fraction
m: Meters
ix
max: Maximum
MET: Metabolic Equivalent
MI: Myocardial Infarction
min: Minimum
MLHF: Minnesota – Living with Heart Failure Quality of Life Questionnaire
mmHg: Millimeters of Mercury
MPA: Moderate Physical Activity
MVPA: Moderate-Vigorous Physical Activity
NHANES: National Health and Nutrition Examination Survey
NHW: Non-Hispanic White
NYHA: New York Heart Association
OR: Odds Ratio
PA: Physical Activity
PAAS: Physical Activity Analysis Software
PADL: Personal Activities of Daily Living
PAEE: Physical Activity Energy Expenditure
PARIS: Prospective Aerobic Reconditioning Intervention Study
PC: Computer
PCA: Principal Components Factors Analysis
QOL: Quality of Life
r: Correlation
RPE: Rating of Perceived Exertion
SD: Standard Deviation
x
SECRET: Study of the Effects of Caloric Restriction and Exercise Training
SEE: Standard Error of the Estimate
Slope: VE/VCO2 Slope
SPSS: Statistical Package for the Social Sciences
SV: Stroke Volume
TEE: Total Energy Expenditure
US: United States
VAT: Ventilatory Anaerobic Threshold
VO2 max: Maximum Oxygen Consumption
VO2 peak: Peak Oxygen Consumption
VPA: Vigorous Physical Activity
vs: Versus
WFUBMC: Wake Forest University Baptist Medical Center
yrs.: Years
xi
ABSTRACT
Daniel Clevenger
EFFECTS OF A RANDOMIZED CONTROLLED TRIAL OF DIET AND/OR
EXERCISE ON OBJECTIVELY MEASURED PHYSICAL ACTIVITY LEVELS IN
OLDER HEART FAILURE PATIENTS
Thesis under the direction of Peter H. Brubaker, Ph.D., Department of Health and
Exercise Science
PURPOSE: To evaluate the changes in primary outcomes (VO2peak and body weight)
and physical activity levels (PA) from baseline to follow-up between four intervention
groups of a weight loss study in older heart failure patients with a preserved ejection
fraction (HFpEF). Additionally, a second purpose was to explore the relationships
between the changes in PA levels and changes in the primary outcomes of the SECRET
trial: VO2peak and body weight.
METHODS: Subjects were assessed at baseline and follow-up of a RCT examining the
effects of an exercise and/or weight loss intervention in older HFpEF patients. Patients
were randomized to one of four intervention groups: Exercise Only (Ex), Diet Only
(Diet), Exercise Plus Diet (E+D), or Attention Control (AC). Inclusion for the RCT
included: a HF Clinical Score of > 3, a normal ejection fraction (> 50%), a BMI of >30
kg/m2, and > 60 years of age. Body weight was measured using a standardized scale.
Peak oxygen consumption (VO2 peak) was obtained from a maximal effort exercise test
on a motorized treadmill. A uniaxial accelerometer (Lifecorder) was worn for 7
continuous days, and evaluated for adequate wear time and days. The average steps/day,
physical activity energy expenditure (PAEE) in kcal/min, minutes of light (LPA) and
moderate-vigorous physical activity (MVPA) were determined for each participant.
xii
RESULTS: The 43 HFpEF subjects included in this study were older (mean age 68 yrs),
mostly female (74%), and overweight/obese (mean BMI of 38.8 kg/m2). The only
variable that was significantly different between the intervention groups was a difference
in age of 6 years between the Ex and E+D groups. The Diet and E+D groups had a
significantly lower body weight at follow-up (94.0 ± 1.27 and 93.5 ± 1.30 kg,
respectively) compared to the AC group (102.9 ± 1.47 kg). The Diet and E+D groups
had a significantly higher VO2peak at follow-up (16.2 ± 0.36 and 16.8 ± 0.37 ml∙kg∙min1
, respectively) compared to the AC group (13.9 ± 0.41 ml∙kg∙min-1). The E+D group
had significantly more steps/day at follow-up (6590.55 ± 445.01 steps/day) compared to
the Diet and AC groups (4086.56 ± 450.54 and 4331.70 ± 502.15 steps/day,
respectively). The E+D had significantly more minutes of MVPA at follow-up (29.42 ±
2.50 min) compared to all three other intervention groups (Ex: 15.50 ± 3.12 min; Diet:
12.19 ± 2.53 min; AC: 11.91 ± 2.82 min). The E+D group had a significantly higher
PAEE at follow-up (261.94 ± 20.96 kcals/day) compared to the Diet and AC groups
(152.05 ± 21.22 and 161.42 ± 23.65 kcals/day, respectively). Changes in minutes of
MVPA was the only PA variable found to be significantly correlated with both changes
in VO2peak (r = 0.329) and changes in body weight (r = 0.387).
CONCLUSION: Results of this 20 week study suggest that exercise and diet is the most
effective short-term combination for weight loss and for increasing VO2peak in this
population. Another unique finding of this study was that diet alone compared to
exercise alone was superior for producing improvements in VO2peak and weight loss.
Results of this trial also suggest that the E+D group demonstrated the largest increase in
PA measures and that changes in PA levels only modestly correlate with changes in
xiii
VO2peak, suggesting other factors, particularly diet changes, also play an important role
in the weight loss in HFpEF patients.
xiv
REVIEW OF LITERATURE
Overview of Heart Failure
Epidemiology of Heart Failure
Chronic heart failure (HF) affects 5.7 million adults in the United States, leading
to nearly one million hospitalizations and 300,000 deaths annually 1. The estimated
annual cost to manage this disease is approximately $40 billion 1,2. Of all categories of
cardiovascular diseases, HF is the only one in which the prevalence, incidence,
hospitalization rate, mortality, and total cost have continued to increase over the past 25
years 3,4. The prevalence of HF in men ages 40-59 is 1.9 percent and progressively
increases to 11.5 percent in men over the age of 80. Women show a similar increase in
prevalence from 0.8 to 11.8 percent from ages 40-59 to over the age of 80, respectively 2.
The incidence of HF increases 2-fold for each decade of age and approximately 750,000
new cases are diagnosed each year 3. The overall risk of developing HF, across a
lifespan, is 20 percent for both men and women 5. These increases in prevalence and
incidence rates over recent decades can be attributed to a longer life-expectancy in
addition to advances in medical care and management of cardiovascular and other
diseases 3,4. By 2040, it is projected there will be 77.2 million new HF cases 6. Even
more alarming, an underestimation of rates most likely occurs because some patients who
have left ventricular dysfunction are asymptomatic and are therefore undiagnosed 3. This
increasing trend is, and will continue to be, a major public health concern.
1
Risk Factors for Heart Failure
Although there are many potential risk factors associated with the development of
HF, the most common causes of HF are hypertension (HTN), coronary artery disease
(CAD), and diabetes 5; however, the strongest risk factor is still a topic of debate in the
literature. The Framingham Heart Study has produced important information in regards
to the development of HF. Framingham participants, who were free of HF at baseline,
were followed to determine the overall lifetime risk for developing HF as well as
potential risk factors for HF. The Framingham Heart Study found 75 percent of HF cases
were preceded by HTN 7. It was also found that at 40 years of age, the overall lifetime
risk for developing HF was 21 and 21.3 percent for men and women, respectively.
However, this risk doubled for participants who had a blood pressure at or above 160/100
mmHg compared to those below 140/90 mmHg 5. The Framingham Offspring Study was
then conducted to determine familial clustering as well as other potential risk factors. In
a study examining both the Framingham Heart Study and Framingham Offspring Study,
HTN preceded HF in 91 percent of the cases and was associated with a two-to-threefold
increase in risk for the development of the HF 8.
Gibson et al. examined the prevalence of HF in two rural communities and found
that CAD was associated with HF in 38.9 and 48.9 percent of the two study groups 9.
Data from the Framingham Heart Study also has shown CAD to be a major risk factor for
HF. Prevalence of CAD was less common in women than men (48% vs. 59.9%,
respectively), for developing HF. However, when further analyses were conducted to see
the impact of HTN, only 9.9 percent of the HF cases had CAD without HTN 10. The
differences noted between these studies can potentially be accounted for by
2
inconsistencies in criteria for diagnosing CAD, HTN, and HF 7. In addition to CAD, the
presence of a previous myocardial infarction (MI), a hard manifestation of CAD, has
been shown to increase the lifetime risk of developing HF in persons over the age of 40.
Therefore a history of HTN or MI significantly increases the risk of developing HF 5.
In order to determine the progression from CAD to HF, Bibbins-Domingo et al. 11
prospectively studied 2,391 diagnosed CAD, postmenopausal women from 1993-2006.
The results from their investigation suggested that diabetes was the strongest predictor for
the development of HF. Women with diabetes and no additional risk factors had a 3.0
percent incidence of HF compared to 0.4 percent for those who were non-diabetic and no
additional risk factors. However, women with diabetes and ≥ 3 risk factors had an 8.2
percent incidence of HF. A difference in risk was also seen for controlled versus
uncontrolled diabetics. Diabetics with fasting blood glucose >300 mg/dL had a threefold
increase in risk compared with those with controlled fasting blood glucose levels after
adjusting for possible covariates 11. Although these investigators found diabetes to
increase the risk for HF, this increased risk has been shown to be higher in women than in
men8.
Research has also shown that obesity (BMI ≥ 30 kg/m2) increases the risk of
developing HF 12. The Physician’s Health Study examined 21,094 men without a history
of CAD. Compared with normal weight participants, overweight participants (BMI ≥ 25
kg/m2) and obese participants had a 49 percent and 180 percent increase in HF risk,
respectively. In fact, for every 1 kg/m2 increase in BMI there was an 11 percent increase
in risk of HF 12. However after adjusting for potentially confounding variables such as
3
HTN, diabetes, and hypercholesterolemia, the relative risk for developing HF decreased
from 3.38 to 2.80 in obese participants compared to normal weight individuals 12.
Whereas many of the aforementioned risk factors can be modified by lifestyle
changes and/or medications, age is a risk factor for HF that cannot be modified.
Increasing age has been shown to be related to the development of HF 7,10,13–15. The
Framingham Heart Study and the Framingham Offspring Study followed 9,405 males and
females to examine the development of cardiovascular disease 10. In this analysis, age
was found to be a major risk factor for the development of HF. The annual incidence rate
increased from 3/1,000 in men ages 50-59 to 27/1,000 in men ages 80-89. A similar
pattern was observed in the women, with the annual incidence rate increasing from
2/1,000 to 22/1,000 in women ages 50-59 to 80-89, respectively. Even after adjustment
for age, the incidence of HF in women was still one-third that of men 10. Therefore
beyond the modifiable risk factors of HTN, CAD, and diabetes, age alone affects the
structure of the left ventricle (LV) and contributes to the pathophysiological changes that
result in HF.
Pathophysiology of Heart Failure
Heart failure can be defined as the inability of the heart to meet the demands of
the tissues due to a reduced cardiac output (CO) 16. Heart failure is often described as a
“syndrome” (see Figure 1) as various pathophysiological responses and symptoms stem
from a reduced CO 2,17.
Initially, the reduced CO to the lungs causes pulmonary mismatching and
manifests in symptoms of fatigue and shortness of breath on exertion. In addition to the
4
lungs, the kidneys are also affected by the reduced perfusion. This leads to the activation
of the renin-angiotensin-aldosterone and sympathetic nervous systems. As a result of the
neurohormonal activation of the renin-angiotensin-aldosterone system, the peripheral
arteries undergo vasoconstriction and consequently increase the afterload on the heart.
Brain natriuretic peptide (BNP) is produced by the ventricular myocardium attempt to
vasodilate the arterioles. Moreover, a decrease in blood flow to the skeletal muscle
occurs as a result of the activation of the sympathetic nervous system and
neurohormones. This activation overrides local metabolites attempting to vasodilate the
arterioles within the active skeletal muscle. The inability to decrease vascular resistance
of the skeletal muscle is one of the predominant causes of the exercise intolerance
experienced by HF patients.
Figure 1. Pathophysiologic Syndrome of Heart Failure
Pathophysiologic “Syndrome” of HF
pulmonary
mismatching
inefficient
ventilation
& DOE
Renal
hypoperfusion
decreased
cardiac
output
exercise
intolerance
neurohormonal
activation
Myocardial
dysfunction
arterial
vasoconstriction
Increased afterload
skeletal muscle
dysfunction
muscle
hypoperfusion
(Brubaker)
5
HF is generally a progressive disease by nature where pathologic remodeling of
the left ventricle compounds the problem by furthering weakening the myocardium. This
leads to diminished contractile functioning of the ventricles which further reduces the
ejection fraction and cardiac output 4,17–19. Because of the numerous physiological
changes discussed above, HF patients experience exercise intolerance in addition to
fatigue and/or dyspnea on exertion 19,20. Consequently, exercise intolerance is shown the
be the most common symptom of the HF population 2,16,18–20
Acute Exercise Responses in Heart Failure
Exercise intolerance is best evaluated by VO2peak which is determined by the
Fick equation. In this equation, VO2peak = cardiac output x arterial-venous oxygen
difference (a-vO2 difference). Through the Fick equation, both central and peripheral
hemodynamics are taken into account to allow one to understand the specific factors that
contribute to the exercise intolerance. In normal subjects, cardiac output (CO) increases
4-6 fold from rest to peak exertion. This increase is due to increases in both heart rate
(HR) and stroke volume (SV). During an acute bout of exercise in normal subjects, SV
increases 20-50% due to an increase in venous return which increases the end-diastolic
volume (EDV). A decrease in end-systolic volume (ESV) is also seen due to an increase
in myocardial contractility. In HF patients, the reduced LV function fails to maintain a
sufficient CO, generally less than 50% of a normal individual. The SV fails to increase to
normal levels because the LV is unable to relax and/or contract in a normal manner. The
reduced CO is primarily attributed to a decrease in SV and frequently an inadequate HR
6
response. A recent study found chronotropic incompetence to occur in 42% of HF
patients 21.
Along with the “central” hemodynamic changes, there are also changes seen in
the periphery. In HF patients, an insufficient widening of the a-vO2 difference occurs
which limits the oxygen delivered to the working skeletal muscles during exertion 20. In
response to the reduced perfusion, the skeletal muscle adapts by decreasing both the
number and size of the “aerobic” Type I muscle fibers. In order to adapt to the reduced
perfusion, there is a decrease in oxidative enzymes and an increase in anaerobic enzymes
within the skeletal muscle. Furthermore, there is a decrease in skeletal muscle
mitochondrial volume as well as density in HF patients. Vasoconstriction also occurs due
to an increase in endothelial dysfunction and vasomotor activity 19. From rest to peak
exertion in normal subjects, a-vO2 difference increases three fold, whereas only a two
fold increase is seen in HF patients 20.
Signs/Symptoms, Diagnosis, and Treatment of Heart Failure
Although HF patients suffer from a variety of symptoms, dyspnea and excessive
fatigue, predominantly with exertion, are the two most common. However, these
symptoms are very prevalent among a variety of other conditions and therefore cannot
serve as diagnostic criteria of HF. This further complicates the diagnostic process of HF.
Patients are first treated for other medical conditions and when they continue to present
with a presence of symptoms over a period of time, these other medical conditions are
slowly ruled out leading to a diagnosis of HF 17,22. Repeatedly measuring the body
7
weight of the patient has been shown to aid in the diagnosis of HF by alerting the
clinician and the patient of possible fluid retention. Typically HF patients are categorized
into subgroups based on both functional capacity and symptoms using the New York
Heart Association (NYHA) and/or the American College of Cardiology Scale (See
Appendices).
Heart failure signs/symptoms manifest when there is significant systolic and/or
diastolic dysfunction of the left ventricle (LV). Aging and increased angiotensin II
production causes the heart to undergo morphological changes which limit its optimal
functioning. The primary assessment used to evaluate the cardiac functioning is the
ejection fraction (EF%). Ejection fraction is calculated by stroke volume (SV)/enddiastolic volume (EDV). In normal individuals, EF% is between 55-65 percent 17.
Patients who present with signs and symptoms of heart failure can be classified into one
of two categories: HF with a reduced EF% (HFrEF) or HF with a preserved EF%
(HFpEF). Those with HFrEF have considerable LV dysfunction, displayed through a
reduced EF% of <35 percent. The heart of a patient with HFrEF is characterized by an
enlarged LV and poor LV contractility. In contrast HFpEF patients have a preserved or
normal EF% of 50 percent or greater 17 and are characterized by having normal LV
systolic function, but a reduced EDV due to diminished LV relaxation and filling. This
leads to in concentric hypertrophy of the LV resulting in a thick and stiffened heart 17–19.
Ejection fraction, LV size, and LV contractility are all used in the evaluation of
the HF patient and categorization of the patient as having either HFrEF or HFpEF. The
echocardiogram is the most useful tool to evaluate HF and to determine systolic or
diastolic dysfunction. The standard 2-D echocardiogram can be used to evaluate EF%,
8
LV wall diameter and thickness, as well as wall motion 2,4. Other assessment tools used
to evaluate LV dysfunction including: nuclear myocardial perfusion imaging, positronemission tomography, cardiac magnetic resonance imaging, and cardiac catheterization 2.
In addition, these tests can determine whether the LV dysfunction is either ischemic or
non-ischemic. Heart failure which is ischemic in nature is usually due to a lack of blood
flow to the myocardium associated with coronary artery disease (CAD). Moreover,
ischemic HF can be due to previous myocardial infarction and/or chronic myocardial
ischemia. Conversely, non-ischemic HF is typically attributed to heart valve dysfunction
or infections of viral origin affecting the myocardium and/or myocytes 19.
Treatment for HF patients depends primarily on the disease progression. The
American College of Cardiology scale (see appendix) can be used to categorize the
patients based on disease progression in stages A-D. Patients in stage A do not have
overt HF and present with risk factors such as HTN, CAD, and diabetes. However, these
patients do not have HF signs or symptoms. The main treatment goal of patients in this
stage is to manage the risk factors in the attempt to prevent overt HF. Trials have shown
reducing blood pressure reduces left ventricular hypertrophy and cardiovascular
mortality, as well as lowering the incidence of heart failure by 30-50% 2,17. Patients with
HTN are often prescribed ACE-inhibitors or angiotensin-receptor blockers in order to
delay or prevent LV remodeling and disease progression 17. In addition, ACE-inhibitors
have also been shown to significantly reduce the incidence of stroke and MI, as well as
mortality 23–25.
Patients with structural heart disease may or may not have signs or symptoms and
are thus categorized as stage B, C, or D. The main objectives for these patients are to
9
slow the progression of the disease, minimize symptoms, manage risk factors, and
improve survival. These objectives can be met through modifying the patient’s lifestyle
through reducing sodium intake, monitoring body weight, and closely adhering to the
prescribed medications. Medications that are commonly prescribed to patients in these
HF stages are ACE-inhibitors, beta blockers, and diuretics. Beta blockers are used to
treat HTN, angina, and arrhythmias as well as counteract the potentially harmful effects
of the sympathetic nervous system in HF. When used in the HF population beta blockers
have been shown to improve morbidity, mortality, LV remodeling, quality of life,
hospital admission rates, as well as sudden death 26,27. Life-threatening ventricular
arrhythmias are common in patients with HF and can be managed with an implantable
cardioverter defibrillator or pacemaker to control both heart rate and rhythm. In those HF
patients who suffer from CAD, myocardial revascularization can also be beneficial. This
can be done either through coronary artery bypass or percutaneous coronary intervention
(i.e. angioplasty/stent). Despite extensive research over the past 30 years consistently
showing the benefits of exercise/physical activity in stable HF patients, most HF
management guidelines fail to include this beneficial therapy 2.
Recommendation of Physical Activity
Physical activity (PA) has a multitude of benefits and has also been shown to
decrease the all-cause mortality rate for all ages. In addition, primary and secondary
prevention of a variety of chronic diseases may be attainable through exercise training 28.
Individuals with coronary artery disease, type 2 diabetes, metabolic syndrome, colon
10
cancer, and breast cancer who are physically active have a reduction in risk of premature
death due to their chronic condition 29–35. Hypertensive individuals benefit from PA as
well, with improvements in blood pressure, muscular strength, feelings of depression and
anxiety through improving mental health, mood, and quality of life. Physical activity
also has a positive effect on weight management by helping to reduce weight and body
fat 36,37.
According to the Centers for Disease Control and Prevention (CDC) and the
American College of Sports Medicine (ACSM), both men and women of all ages benefit
from daily PA. Both organizations recommend that adults participate in aerobic exercise
consisting of either 30 minutes of moderate intensity (i.e. brisk walking or cycling at less
than 10 miles per hour) or 15-20 minutes of vigorous intensity (i.e. jogging, running,
swimming laps, or cycling at greater than 10 miles per hour) per day. Following these
recommendations has been shown to reduce the risk of developing cardiovascular disease
(CVD) 38. Consistent with these daily recommendations, the United States Department of
Health and Human Services encourages at least 150 minutes of PA, at a moderate
intensity, per week in order to significantly lower the risk of developing CVD and
maintain overall health. Moreover, research has shown a dose-response relationship
between PA and health benefits; thus increasing PA levels beyond 150 minutes per week
may result in additional benefits. Moderate PA for at least 30 minutes/day results in an
approximate energy expenditure of 150 kcals/day, or 1000 kcals/week, a level thought to
be a minimal threshold for health benefits 39. However if weight loss is the primary goal,
the weekly PA target should increase to at least 180 minutes at a moderate intensity. It
11
has been suggested that some individuals may require at least 300 minutes of moderate
PA per week to effectively lose weight 40.
Despite well-established PA guidelines, most Americans do not meet these
recommendations. According to the 2008 National Health Interview Survey, only 14%
of American adults participated in vigorous leisure-time PA three to four times per week
and even fewer (11.5%) participated at least five times per week. Furthermore, this
survey also found that 36% of adults were sedentary during leisure-time and 59% did no
vigorous PA during their leisure-time 41. Additionally, the National Health and Nutrition
Examination Survey (NHANES) found that only 5% of the adult population met the
recommendation of at least 30 minutes per day of moderate PA 42.
Although there are numerous benefits associated with PA, there is also potential
risk for cardiac complications such as a heart attack and/or sudden cardiac death.
Research has shown these adverse events are associated with a hazard period during or
within one hour of completing heavy physical exertion 43–45. Mittleman et al., found that
54% of those who experienced a myocardial infarction (MI) had participated in heavy
physical exertion within the previous hour prior 44. Research has also shown that
habitually sedentary individuals are most at risk of a MI during the hazard period
associated with heavy physical exertion 43,44. Ultimately the risk of sudden cardiac death
in healthy individuals is low, varying from 0.01-0.20 cases per 10,000 hours 45.
Furthermore when individuals are screened properly and supervised by competent
medical staff, this risk is 0.03 cases per 10,000 hours 45. In spite of a low risk for cardiac
complications among healthy adults, the risk is increased in those with heart disease.
Rogosta et al. found that 88% of the exertion-related deaths had underlying
12
atherosclerotic disease and only 7% of the deaths were in individuals with no known
history or risk factors for atherosclerotic disease 46. The risk of adverse events during
exercise in secondary prevention programs (i.e. cardiac rehabilitation programs) is
slightly higher than that of healthy individuals. Even though MIs are the most common
cardiovascular complication within these programs, Haskell et al. found only 1 MI per
32,593 patient hours of exercise 47. Overall, the risk of cardiovascular complication
during exercise in a cardiac rehabilitation program is 0.08-0.15 cases per 10,000 hours 45.
Even though there is some risk associated with exercise, habitual exercise has been
shown to strongly decrease the risk of sudden cardiac death, especially in those
unaccustomed to vigorous exertion 48.
Methods of Quantifying Physical Activity
The intricate and multidimensional nature of PA makes it difficult to measure and
quantify. By definition, PA is any bodily movement produced by movement of skeletal
muscles 37. Physical activity can be prescribed based upon its intensity, frequency, type,
and duration of the activity. The intensity of PA is commonly categorized according to
the minutes of light (LPA), moderate (MPA), and vigorous (VPA) 49. Energy
expenditure (EE) is another way to determine the PA amount by quantifying the amount
of energy required by the body to perform a certain activity. Evidence suggests that EE
may be a more accurate predictor of health-related outcomes than the type of PA
performed 49. Energy expenditure can also be further classified according to the energy
expended solely during PA (PAEE) 50–56, which is quantified in kilocalories (kcals) 49.
13
There are a variety of subjective and objective approaches available to evaluate
PA levels. Several subjective measures are available to quantify PA patterns over a predetermined period of time. These methods include: PA records, logs, and
recalls/interviews. Physical activity records serve as diaries for the individual in an
attempt to capture all sources and patterns of PA during a certain time frame. Similarly,
PA logs attempt to collect the same information but they are structured more like a
checklist of specific activities commonly performed in a given target population. The
disadvantages of PA records, logs, and recalls are they are very time-consuming to both
the participant and have a significant recall bias. The most commonly used subjective
measure to monitor PA levels is the recall questionnaire 49. The primary advantage to
subjectively measuring PA is that these methods are relatively inexpensive and easy to
administer to a large group. Additionally, these methods are population-specific and do
not require nearly as much time as PA records or logs. Recall questionnaires typically
have 10-20 items which assess frequency, duration, and types of PA during the past day,
week, or month. These questionnaires have several advantages over other techniques,
which is why they are so commonly used. However, questionnaires are also subjected to
significant recall error and bias 49. These subjective measures have been shown to overreport levels of vigorous activity and under-report light activity levels compared with
accelerometry data 53.
Given the potential for recall error and bias of these subjective approaches, a more
objective measure of PA is often preferred. Examples of these objective measures of PA
include doubly labeled water, heart rate monitoring, pedometers, and accelerometers.
The most accurate method for determining energy expenditure is doubly labeled water.
14
However, this method is expensive, only quantifies total EE, and does not provide
information on frequency, intensity, or duration of the PA 49.
The pedometer is a small, inexpensive, device that is commonly used to
objectively measure PA levels. Pedometers provide estimations of total steps, distance
covered, and some devices estimate EE 57–61. To increase accuracy, most units require
the user to enter stride length and body mass into the device. Pedometers can provide
instant feedback to the user and thus can also potentially be used as a motivational tool.
While widely used, pedometers have several important limitations; including the inability
to quantify non-ambulatory activities, the inability to internally to store data, the inability
to determine amount of time the device is worn each day, and possibly the most
significant is their inability to quantify the frequency, intensity, or time of the activity 57.
Furthermore, the speed of ambulation can negatively affect the accuracy of the pedometer
used. Walking speeds < 1.86 miles per hour 61 and running speeds > 9.94 miles per hour
have been shown to elicit significant measurement error 62. Adiposity of the waist causes
a tilt of the device that affects the pedometer’s accuracy. Increased BMI and waist
circumference have also been shown to decrease the accuracy of pedometers by tilting of
the device at the waist which affects the pedometer’s mechanism of measurement 61.
In order to determine the accuracy and reliability of various pedometers,
Schneider et al. 59 compared ten different models over a 400-meter walk. Although eight
models were found to be reasonably accurate, the Kenz-Lifecorder, New Lifestyles-2000,
and the Yamax Digiwalker were shown to be the most accurate with values within ± 3%
of the actual step counts 59. In 2004, Schneider et al. 60 studied 13 motion sensors,
including the Kenz-Lifecorder, and compared the output of each device to the Yamax
15
SW-200 which served as the criterion pedometer. Based on mean values some models
underestimated steps by as much as 25% and others overestimated by as much as 45%.
The Kenz-Lifecorder was one of four models which produced accurate step counts
compared to the criterion model. Consequently these researchers concluded that the
Kenz-Lifecorder was an appropriate PA assessment tool in research settings 60.
In addition to the work done by Schneider et al., other studies have also concluded
the Kenz-Lifecorder to be a valid tool for quantifying PA in a variety of populations 58,63–
67
. Specifically, the Kenz-Lifecorder has been shown to accurately assess energy
expenditure and exercise intensity both during exercise periods and non-structured
activities 63. Kumahara et al. found significant correlations between both total energy
expenditure (TEE) and PAEE (r = 0.928 and 0.564, respectively) when measured by the
Lifecorder and direct calorimetry. In addition, these researchers found a positive
relationship between MET levels and exercise intensity levels measured by the
Lifecorder (r = 0.963). These investigators determined the Lifecorder produced exercise
intensity levels of light, moderate, and vigorous which correspond to < 3.0 METs, 4.0-6.0
METs, and > 7.0 METs, respectively. Furthermore since most PA occurs between 2-8
METs, the Kenz-Lifecorder is accurate in quantifying PA and measuring PAEE in a
various populations 58,636767.
Comparison of Subjective and Objective Measures of Physical Activity
Numerous studies 32,51,53,68–70 have compared different subjective and objective
methodologies for measuring PA levels. The general consensus among these studies is
16
subjective measures of typically overestimate the time spent in PA, particularly for
vigorous PA, compared to objective measures.
Macfarlane et al. 53 examined the convergent validity of six different methods
used to assess daily PA. It was determined that heart rate monitors significantly
overestimated light activity and underestimated moderate activity compared to the
International Physical Activity Questionnaire (IPAQ), PA log, pedometer, uniaxial
accelerometer, and a triaxial accelerometer. The investigators propose that these errors
could be attributed the cut points of the heart rate monitor for what constitutes light
activity 53. Although the HR-VO2 relationship has been shown to be linear over a wide
range of intensities, this is not always the case during low and very high intensity PA 71.
Since many daily activities are low to moderate intensity, heart rate monitoring may not
produce accurate estimations of daily EE 49.
Ainsworth et al. 51 compared three methods used to assess time spent in PA
among 83 adults over a three week period. Each subject participated in a telephone
survey to recall non-occupational walking, moderate intensity activity, and hard/very
hard intensity activities over the previous week. Additionally, each participant wore a
CSA accelerometer and completed a 48-item PA log. This log quantified the amount of
time during which the participant did household activities, occupational activities, their
mode of transportation, participation in sports, and leisure-time PA. Weak correlations
were observed between CSA and PA logs for moderate intensity activity (r = 0.22 and
0.36) and hard/very hard intensity activity (r = 0.31 and 0.36). The relationships between
PA intensity levels obtained during telephone surveys and PA logs were more variable.
Correlations between 0.26 and 0.54 were observed between these methods for moderate
17
intensity PA as well as walking. However, no significant correlation was seen between
the reporting of hard/very hard intensity activities (r < 0.09) suggesting there was no
significant difference between PA logs and telephone surveys in regards to the reporting
of activities at this intensity level. While this study concluded that telephone surveys, PA
logs, and accelerometers all reasonably quantify levels of moderate and hard/very hard
PA, there was very little agreement between these three approaches, suggesting they
cannot be used interchangeably 51.
Using a subset of participants from the Cooperative Lifestyle Intervention
Program (CLIP) study in 2008, Amico and Brubaker 68 quantified PA levels in 184
sedentary, overweight and obese older adults with mobility disability and established
CVD and/or the metabolic syndrome. Participants’ PA levels were subjectively
measured using the Community Health Activities Model Program for Seniors
(CHAMPS) PA questionnaire and objectively measured using the Kenz-Lifecorder
accelerometer. Both measures were analyzed separately in regards to steps, PAEE, LPA,
and MVPA. Results from this study showed there were no significant correlations
between CHAMPS and the accelerometer derived steps, PAEE, LPA, and MVPA (r =
0.002, 0.060, 0.063, and -0.028, respectively). The CHAMPS questionnaire tended to
overestimate MVPA but underestimate light intensity PA compared to the accelerometer
68
.
In order to better understand the relationship between subjective and objective PA
measures in heart failure patients, Brubaker and Shedd 72 evaluated baseline PA patterns
in a subset of participants from the Heart Failure and A Controlled Trial Investigating
Outcomes of exercise traiNing (HF-ACTION) trial. Investigators used the International
18
Physical Activity Questionnaire (IPAQ) and the Kenz-Lifecorder accelerometer to
subjectively and objectively quantify PA levels. There was no significant difference
between the amount of moderate PA (178 ± 27 vs. 441 ± 175) and total PA (1209 ± 83
vs. 1406 ± 385) observed between the accelerometer and the IPAQ, respectively.
However, significant differences were observed in the MET min/wk of light (1018 ± 69
vs. 460 ± 124) and vigorous (12 ± 6 vs. 400 ± 155) activities between the accelerometer
and the IPAQ, respectively. These results indicate the IPAQ tended to underestimate
light PA and overestimate vigorous PA compared to the accelerometer-derived data.
Quantifying Physical Activity Levels in Different Populations
Healthy Adults
The National Health and Nutrition Examination Survey (NHANES) in 2003-2004
collected accelerometer data on 4,867 individuals ranging from children (6-11 years),
adolescents (12-19 years), and adults (20+ years) 42. It was found that objectively
measured PA declined dramatically with age. Tudor-Locke and Myers also observed a
decline in activity with age in their review of 32 studies that examined PA patterns in
American children, adults, and older adults 73. Children accumulated more steps (12,00016,000 steps/day) compared to healthy adults (7,000-13,000 steps/day), and older adults
(6,000-8,500 steps/day). Additionally, individuals suffering from chronic disease
conditions reported even fewer steps/day (3,500-5,500).
In an attempt to provide a more universal agreement on target PA levels, TudorLocke and Bassett proposed a classification system to allow for evaluation of PA levels
in adults: “sedentary = <5,000 steps/day; “low-active” = 5,000-7,499 steps/day;
19
“somewhat active” = 7,500-9,999 steps/day; “active” = 10,000-12,499 steps/day; and
“highly active” = ≥ 12,500 steps/day 74. While it has been recommended that adults
should achieve 10,000 steps/day, this goal might be too high and inappropriate for older
adults as well as individuals with chronic disease conditions 75.
Elderly
Regardless of age, regular PA of moderate to vigorous intensity, has been shown
to be beneficial, yet many older adults are not physically active 76,77. In 2009, it was
reported that roughly 60% of Americans ≥ 65 years of age did not participate in at least
30 minutes of moderate PA five or more days/week, or at least 20 minutes for three or
more days/week 78. While a multitude of research studies have examined PA levels of
older adults 79–84, the general conclusion among researchers is that the total duration of
exercise tends to decrease with age. One study observed 56 older, community dwelling
adults to evaluate their walking, postural transition, and sedentary behavior 81.
Participants wore an accelerometer for seven days allowing investigators to quantify
volume, frequency, intensity and the variability of participants’ PA. It was found that
participants had an average step count/day of 6,343.2 with a range of 864.8 – 15,847
steps/day. Younger age and lower BMI were shown to be significant predictors of PA
levels. Researchers also concluded that walking, sedentary behavior, and postural
transition measure different things, yet when used together they help explain the
complexity of daily function in older community dwelling adults 81. Based on the scale
by Tudor-Locke and Bassett 74, these older adults are considered “somewhat-active”.
20
Bruce et al. 83 studied women between the ages of 70 and 85 years, all of whom
were considered both physically and mentally healthy. Investigators found that 39% of
these women achieved enough PA from their recreational activities, however 26% did no
recreational PA. Of the non-active women, 42.5% attributed their inactivity to a fear of
falling. Of the physically active women, only 27% reported a fear of falling. Results
from this study suggest that a fear of falling is a major contributor to physical inactivity
in older adults 83.
Another study 80 looked the mean PA level (PAL) in older versus younger adults
(mean ages: 61 versus 27 years). In order to calculate the mean PAL, the average daily
metabolic rate (ADMR) was divided by the basal metabolic rate (BMR). A tri-axial
accelerometer was used to measure PA. Activity counts of ≤ 200/min were categorized
as light PA (<3 METs). Moderate intensity PA was defined by activity counts of 200500/min and was associated with MET levels of 3-6, such as walking. Lastly, high
intensity PA was defined as at least 500 counts/min and include activities such as
domestic activities performed around the house, exercise, and/or sport activities all of
which resulted in > 6 METs. Results showed that PAL values were significantly
correlated with activity counts produced from the tri-axial accelerometer (r = 0.78) and
VO2max (r = 0.59). Results also demonstrated that elderly subjects spent significantly
more time performing light intensity activities compared to moderate or high intensity
activities. The opposite pattern was observed for younger individuals.
21
Overweight/Obese Individuals
Several studies have examined the PA levels of overweight/obese individuals 85–
88
. As expected, these populations are almost always less physically active than their
normal weight counterparts. One published review of 58 studies over the past 40 years
evaluated to PA levels in overweight/obese persons and found an inverse relationship
between PA level and percent body fat (r = -0.5 to -0.16) 87. Additionally, results from
this review showed that those classified as overweight showed lower levels of PA
compared to those classified as having a normal weight 87. Another study 88 administered
pedometers to participants and evaluated the steps/day of 1,136 adults. On average these
adults took 5,117 steps/day, yet the number of steps/day significantly decreased as BMI
levels increased (Normal = 5,864, Overweight = 5,200, Obese = 4,330 steps/day,
respectively) 88.
Tudor-Locke et al. 86 evaluated PA and physical inactivity based on BMI from the
2005-2006 National Health and Nutrition Examination Survey (NHANES) accelerometry
data. Individuals were separated according to BMI categories in order to determine if
each group met the public health recommendation of accumulating 30 minutes (or the
equivalent in 10 minute intervals) of PA per day of moderate or vigorous intensity on 5 or
more days per week. The BMI categories were grouped into normal (< 25 kg/m2),
overweight (25-30 kg/m2), and obese (≥ 30 kg/m2). Results showed that only 3.2% of
American adults met the Surgeon General’s recommendation for PA. The data also
revealed that fewer adults achieved the recommended PA levels as BMI increased. In
addition to decreasing PA levels, increased sedentary levels were also observed. Within
a 24-hour period the time spent in sedentary, light, moderate, and vigorous activities
22
differed significantly for obese males (486.8 min/day, 142.4 min/day, 22.4 min/day, 3.7
min/day, respectively) compared to the overweight males (484.2 min/day, 155.4 min/day,
30.7 min/day, 5.3 min/day, respectively) and normal weight males (466.9 min/day, 160.2
min/day, 34.6 min/day, 6.0 min/day, respectively). Conversely, females only displayed
significant differences in PA distribution during a 24-hour period in the moderate and
vigorous categories for obese (13 min/day, 2.5 min/day), compared to the overweight
(17.5 min/day, 5.3 min/day) and normal (19.9 min/day, 8.7 min/day) women. This study
validates that both BMI and gender differences have an impact on PA levels among
American adults 86.
Adams et al. 85 analyzed data from the Centers for Disease Control and Prevention
Behavioral Risk Factor Surveillance (BRFSS) to examine PA levels in adults living in
South Carolina. The goal of these investigators was to determine if these individuals met
the PA recommendations of the Centers for Disease Control and Prevention (CDC) and
the American College of Sports Medicine (ACSM), which are defined as ≥ 30 minutes of
moderate intensity PA on ≥ 5 days per week or ≥ 20 minutes of vigorous intensity PA on
≥ 3 days per week 38,85. Individuals were categorized according to BMI: lean (< 25
kg/m2), overweight (25-29.9 kg/m2), and obese (≥ 30 kg/m2). Physical activity levels
were also dichotomized into inactive (no PA participation), insufficiently active
(physically active, but did not meet the CDC-ACSM PA recommendations), and
sufficiently active (met the CDC-ACSM PA recommendations). Investigators found that
even though 29.5% of lean, 27.8% of overweight, and 19.3% of obese males were
sufficiently active, 23.6% of lean, 23.4% of overweight, and 31.9% of obese males were
inactive. Furthermore, 46.9% of lean, 48.8% of overweight, and 48.9% of obese males
23
were insufficiently active. Females showed similar results, with 22.4% of lean, 32.3% of
overweight, and 41.7% of obese women being inactive and 48.1% of lean, 44.5% of
overweight, and 41.9% of obese women being insufficiently active. However, 29.4% of
lean, 23.3% of overweight, and 16.4% of obese women were sufficiently active 85.
Results from this study conclude that both obese and overweight males and females
participated in significantly less leisure-time PA and had significantly more physical
inactivity than their normal weight counterparts. In general, this study showed an inverse
relationship between PA levels and BMI in men and women 85.
Cardiac Patients
Multiple studies 89–91 have evaluated the PA levels of cardiac rehabilitation
program (CRP) participants. Ayabe et al. 91 used Kenz-Lifecorder EX accelerometers to
examine PAEE, light PA (LPA), moderate PA (MPA), and vigorous (VPA) on both CRP
and non-CRP days. Researchers found that PAEE was significantly less on non-CRP
days than on CRP days (177 ± 113 vs. 299 ± 161 kcals/day). Additionally, CRP
participants had significantly less LPA, MPA, and VPA on non-CRP days compared to
CRP days (49.3 ± 19.3 vs. 59.7 ± 19.8; 10.5 ± 14.6 vs. 26.4 ± 20.4; 0.4 ± 1.7 vs. 1.4 ± 3.0
minutes/day, respectively). Based on these results, it appears that CRP participants were
close to accumulating the PA recommendation of 30 minutes of MVPA/day on days they
participated in the exercise program. However on non-CRP days, PA levels were far less
than recommended. Consequently, it was concluded that patients who only participate in
three days of CRP without additional activity on non-CRP days are not achieving enough
activity to maintain cardiovascular health (> 1,500 kcals/week) 91.
24
Jones et al. 90 evaluated 25 males, ranging in age from 39 to 69 years of age, with
a history CAD who were participating in a phase III CRP. Using an Actigraph
accelerometer, PA levels were measured in steps and EE over the course of 7 days.
Researchers then made comparisons between CRP and non-CRP days as well as
additional PA outside of the CRP. Consistent with the findings of Ayabe et al. 91, PA
levels were significantly higher on CRP days compared to non-CRP days (10,087 ± 631
vs. 5,287 ± 520 steps/day). Results also showed those who participated in home exercise
in addition to CR were significantly more active than individuals who only participated in
CR (7,993 ± 604 vs. 5,277 ± 623 steps/day). Researchers concluded that even though
attending CRP sessions helps patients accumulate adequate PA on CRP days, only 8% of
patients reached the recommended minimum level of weekly PA. However, patients who
did some form of home-exercise on non-CRP days in addition to CRP sessions were able
to increase their total volume of PA closer to recommended levels 90.
Another study 89 examined the PA levels of 31 phase IV CRP patients that
participated in an “Active for Life” class. This study found no significant changes in PA
levels from phase III to phase IV CRP, regardless of attendance in the “Active for Life”
classes after phase III. Based on patients PA diaries, it was estimated that leisure-time
PA energy expenditure averaged 1,376 kcals/week (range: 128 – 3,380 kcals/week). This
amount is less than what is associated with increased fitness (1,400 kcals/week),
inhibiting disease CAD progression (1,600 kcals/week), or CAD regression (≥ 2,200
kcals/week) 89. Since these were self-reported PA levels, these values are likely to be
overestimated. Thus, several studies provide objective evidence that most CRP
participants do not get enough PA to reduce progression of CAD or lose weight.
25
Heart Failure
Despite the multitude of benefits, exercise and PA had been contraindicated in HF
patients until recently. This contributes to the lack of PA often observed in HF patients as
exercise/PA may still not be recommended by their health care provider. Additionally,
HF patients may not participate in exercise as they are often limited by symptoms of
exercise intolerance and/or there is no reimbursement for HF patients to exercise within a
CRP. A handful of studies have attempted to quantify, both subjectively and objectively,
the level of PA in HF patients 92–95.
Garet et al. 95 administered a PA questionnaire to 105 patients with HF to evaluate
the validity, reliability, and sensitivity of the PA questionnaire in this population. This
PA questionnaire not only quantified PA levels, but also quantified daily energy
expenditure (DEE). Physical activity levels were categorized into 3 different groups:
PAlow (< 3 METs), PAhigh (3-5 METs), PAintensive (> 5 METs). Daily energy expenditure
was shown to decline with both age and NYHA functional class. The test-retest
correlation coefficient for activities between 3-5 METs was 0.82. Investigators
determined that this questionnaire produced a reproducible estimate of DEE and suggest
that HF patients spend the majority of their time in PAlow (< 3 METs). It is hypothesized
that these HF patients spent less time in PAhigh or PAintensive (> 3 METs) in order to avoid
worsening of their symptoms 95.
Walsh and colleagues 92 investigated predictors of long-term prognosis in 84 HF
patients (based on performance on a treadmill exercise test and daily levels). To measure
exercise capacity, researchers used both the modified Bruce treadmill protocol and a self26
paced corridor walk. Daily PA was measured using a Digiwalker pedometer. This study
concluded that the duration of exercise tests results were not significant predictors of
long-term prognosis. However, the pedometer scores (> 25,000 steps per week) were
shown to be significant predictors of prognosis in both univariate and multivariate
analysis. Therefore, a reduced daily amount of PA in HF patients appears to be an
important prognostic measure 92.
Oka et al. 93 examined the relationship between exercise capacity, measured from
a treadmill exercise test, and objectively measured PA levels of 45 HF patients. Vitalog
activity monitors were used to quantify PA levels over a two day period. In addition,
participants also recorded the amount of time spent in each activity, the rating of
perceived exertion (RPE) of each activity, and any symptoms they experienced. Daily
PA resulted in shortness of breath (SOB) (22%), fatigue (16%), and muscle/joint soreness
(13%) in these HF patients. However, 46% of these participants reported they did not
experience any HF symptoms during daily PA. Investigators suggest that daily PA levels
of HF patients are reduced in order to avoid further exacerbating symptoms. Furthermore
the amount of daily PA performed by these HF patients was fairly low. Only 6.6% of
subjects reported exercising regularly at a moderate intensity. Thus, it appears that HF
patients often restrict levels of PA in order to avoid unpleasant symptoms 93.
Exercise Training Interventions
Heart Failure with a Reduced Ejection Fraction (HFrEF)
Many HF patients suffer from exercise intolerance, and thus do not participate in
exercise related activities due to exacerbation of HF symptoms or a fear of being active.
27
Over the past 20 years, there have been multiple studies evaluating the effect of an
exercise training (ET) intervention on exercise capacity, health-related quality of life
(HRQOL), as well as morbidity and mortality in HFrEF patients 96–104. The results of
these studies have consistently demonstrated a significant increase in peak exercise
workload, exercise time to exhaustion, and 6-minute walk test (6MWT) distance 96,97,99–
102,104
. The majority of these studies also demonstrated a significantly increased (≥ 10%)
VO2peak from baseline 96,99–102,104. Conversely, two studies showed an increase in
VO2peak of greater than 10% 96,100,105. The multi-center randomized control trial, Heart
Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION)
of 2,300 patients showed a non-significant 4% increase in VO2peak from baseline to 12
months. However, investigators concluded that regular ET is safe for these patients and
reduces all-cause mortality and hospitalization 98. With the exception of an early study
by Sullivan et al. 97, no other exercise intervention trials of HFrEF patients reported any
significant adverse events 96–104.
In 1999, Belardinelli et al. 103 randomly assigned 99 clinically stable HFrEF
patients (Age: 59 ± 14 years, EF% in Training: 28.4 ± 6%, EF% in Control: 27.9 ± 5%)
to either an ET group or a control group. The ET group underwent 12 months of
exercise, 3 times per week at 60% of their measured VO2peak. During the 12-months,
participants performed the exercise as follows: warm-up (stretching) 15-20 minutes and
40 minutes on a cycle ergometer. Investigators performed exercise testing at baseline, 2
months and 14 months 103. Resting heart rate significantly decreased in the training
group (88 ± 12, 80 ± 10, 78 ± 10 bpm, respectively, P < 0.005 between groups) compared
to the control group (93 ± 10, 91 ± 11, 89 ± 9 bpm, respectively). A significant increase
28
in VO2peak was observed in the ET group (15.7 ± 2, 18.6 ± 1, 19.9 ± 1 ml∙kg∙min-1,
respectively) compared to the control group (15.2 ± 2, 15.6 ± 2, 16 ± 2 ml∙kg∙min-1,
respectively) 103. The training group also showed a reduced mortality rate compared to
the control group (9 vs. 20, respectively; Relative Risk (RR): 0.37 (0.17-0.84)) and a
significant reduction in hospital re-admissions (ET: 5 vs. Control: 14; RR: 0.29 (0.110.88)). The findings of this randomized controlled trial show that ET can be beneficial
for clinically stable HFrEF population as VO2peak, mortality, and hospital re-admissions
all improved 103.
Hambrecht et al. 101 utilized a prospective randomized trial to evaluate the
benefits of ET for 73 men with HFrEF. At baseline, thirty-six participants were
randomized to the ET group, and 37 participants were randomized into the control group.
The first part of the ET regimen took place inside the hospital for the 2 weeks. During
this time, the subjects worked out 4-6 times per day for 10 minute increments on a cycle
ergometer. Patients exercised at 70% of their VO2peak that was attained during the
CPET at baseline. After the first 2 weeks, the ET participants underwent another CPET
to revise the exercise intensity for a home-based program (70% VO2peak) that involved
exercise on a cycle ergometer for 20 minutes per day for a 6 month period. The ET
subjects also had to attend one group exercise session per week that included a one hour
session of walking, ball games, or calisthenics. At the 6 month follow-up, those
randomized to the ET group showed a significant improvement in VO2peak compared to
the control group (18.2 ± 3.9 vs. 23.0 ± 4.7 ml-kg-min-1 , 17.8 ± 4.5 vs. 18.1 ± 4.1 ml-kgmin-1, respectively). It was also found that there was a significant increase in cardiac
output at peak exercise in the ET group, while there was a significant decrease in cardiac
29
output in the control group (14.4 ± 6.2 vs. 17.1 ± 6.1 L/min, 14.2 ± 4.9 vs. 13.9 ± 5.1
L/min, respectively). These researchers found that there were significant changes in both
exercise capacity as well as hemodynamic changes in regards to those with HFrEF 101.
A meta-analysis on 35 randomized control trials was performed by van Tol and
colleagues in order to evaluate the effect of ET in those with HFrEF using summary
effect sizes (SESs) 96. A total of 1,486 subjects with HFrEF were evaluated. There were
701 subjects who participated in ET while 651 subjects were in the control group (Age:
60.6 ± 7.5 years, BMI: 26.9 ± 1.3, EF: 27.7 ± 4.2%). The average aerobic training period
for the ET groups was 13.0 ± 7.8 weeks with an average duration of 50.0 ± 22.0 minutes
per session. The frequency of the exercise sessions per week were 3.7 ± 1.7 times per
week. The intensities at which the subjects worked varied between 50-80% VO2peak,
60-80% maximum heart rate, or 60-80% heart rate reserve. Some studies used resistance
training or interval training, while others used a combination of aerobic training with
resistance training. Cardiac output at peak exercise, VO2peak, anaerobic threshold, and 6
minute walk distance significantly increased from baseline (+2.51 L/min, 21.3% increase
from baseline, SES: 0.58 (0.19-0.97), P = 0.004; +2.06 mL/kg/min, 13% increase form
baseline, SES: 0.60 (0.42-0.79) P = 0.000; +1.91 mL/kg/min, 17.4% increase from
baseline, SES: 0.84 (0.48-1.20), P = 0.000; +46.2 m, 11.6% increase from baseline, SES:
0.52 (0.36-0.69), P = 0.000, respectively). The meta-analysis shows that there are
significant benefits of ET in those with stable HFrEF 96.
Brubaker et al. 102 evaluated the effects of aerobic ET on 59 older HFrEF patients
(Age: ≥ 60 years). Patients were randomized to 16 weeks (48 sessions) of either a control
group or an aerobic ET group. Each ET session lasted for one hour at a lower intensity
30
(40-50% of their heart rate reserve (HRR)) during the first two weeks then at a slightly
higher intensity (60-70% HRR) for the remaining 14 weeks. Although the ET subjects
attended an average of 45 ET sessions and significantly increased their combined walking
and cycling distance (4.11 ± 1.09 vs. 4.81 ±0.99 miles per session), there was no
significant overall change in VO2peak, peak ventilation, or VE/VCO2 slope. However,
23 of the ET subjects demonstrated an increase in VO2peak, six (26%) increased by ≥
10%, which represents a clinically significant change, and nine (39%) increased their
VO2peak by 0-9.9%. The major finding of this study alone is that not all HFrEF patients
respond favorably to ET 102. More research is needed in HFrEF patients to determine the
differences between “responders” vs. “non-responders”.
Heart Failure with a Preserved Ejection Fraction (HFpEF)
Despite the fact that HFpEF has similar incidence and prevalence rates, only five
studies 102,106–109 to date have evaluated the effects of ET on HF patients with a preserved
ejection fraction (HFpEF). Gary et al. 107 was the first to examine exercise training in the
HFpEF population. The primary purpose of this study was to evaluate the effects of
exercise training on exercise self-efficacy. Thirty-two older women with HFpEF were
included in the study (NYHA III, Age Range: 50-85). After undergoing baseline testing,
patients were randomized to either a home-based walking intervention or an education
control group for 12 weeks. Those in the home-based walking group walked 3
days/week outside their homes. Patients initially exercised at 40% heart rate reserve
monitored by a heart rate monitor and gradually increased to 60% heart rate reserve,
while maintaining a duration of 20-30 minutes. Patients in the home-based exercise
31
significantly improved their 6 minute walk distance compared to the control group (∆203
vs. ∆93 feet, respectively). Participants in the exercise group significantly increased their
exercise self-efficacy which was correlated with increased 6 minute walk distance. This
study indicates that low to moderate walking can increase exercise self-efficacy in older
HFpEF women thus giving them the confidence to exercise 107.
Smart et al. 106 was the first to compare the ET response between those with
HFrEF (N = 24, Age: 62 ± 8 years, EF: < 35%) and HFpEF (N = 9, Age: 65 ± 5 years,
EF: > 45%). After baseline testing, both groups of clinically stable HF patients
participated in 16 weeks of ET on a cycle ergometer at 60-70% VO2peak for 3 one hour
sessions per week. Both HFpEF and HFrEF groups were similar at baseline in regards to
VO2peak (12.5 ± 4.1 vs. 11.9 ± 2.5 ml-kg-min-1, respectively), ventilatory threshold (7.7
± 2.5 vs. 7.9 ± 1.9, respectively), and VE/VCO2 slope (32.8 ± 8.3 vs. 33.8 ± 5.7,
respectively). Both the HFpEF and HFrEF groups demonstrated significant changes from
pre- to post-ET for VO2peak (HFpEF: 12.5 ± 4.1 vs. 16.2 ± 5.6 ml-kg-min-1; HFrEF: 11.9
± 2.5 vs. 14.8 ± 4.1 ml-kg-min-1) and ventilatory threshold (HFpEF: 7.7 ± 2.5 vs. 9.5 ±
2.6; HFrEF: 7.8 ± 1.9 vs. 10.3 ± 2.3). The percent change in VO2peak for HFpEF and
HFrEF (30% and 24%, respectively) are larger than typically reported 105.
Kitzman et al. 110 utilized a randomized, controlled, single-blind trial to evaluate
the response to ET in those with HFpEF. Fifty-three clinically stable HFpEF patients
(Age: 70 ± 6 years (60-82), EF: ≥ 50%), were randomized to either a control group or ET
intervention. After ET, the ET subjects had a greater exercise time, peak workload, and
VO2peak (ET: 13.8 ± 2.5 vs. 16.1 ± 2.6 ml-kg-min-1, Control: 12.8 ± 2.6 vs. 12.5 ± 3.4
32
ml-kg-min-1, P = 0.0001). This study was the first randomized, controlled, single-blind
study to evaluate the effects of exercise training in HFpEF patients 110.
Edelmann et al. 108 conducted the first multicenter, prospective RCT on exercise
training in HFpEF patients. Sixty-four patients with HFpEF (Age: 65 ± 7 years, 56%
female) were randomized to either endurance/resistance training in addition to usual care
or to usual care alone for 12 weeks. Patients in the ET group cycled at an a HR that
corresponded to 50-70% of their VO2peak. After 4 weeks, resistance training was
incorporated twice per week. Fifteen repetitions were performed at an intensity of 6065% of their 1-RM. At follow-up, VO2peak increased in the ET group (16.1 ± 4.9 to 18.7
± 5.4 ml∙kg∙min-1) and remained unchanged in the usual care group (16.7 ± 4.7 to 16.0 ±
6.0 ml∙kg∙min-1). This study shows that a short-term supervised exercise program
consisting of both endurance and resistance training is safe, feasible, and effective for
patients with HFpEF.
Alves et al. 109 studied the effects of exercise training on exercise tolerance in
heart failure patients with mild and moderate-severe HFrEF, as well as HFpEF. Ninetyeight patients with moderate-severe (N = 34), mild (N = 33), and preserved (N = 31) were
randomized to exercise training plus usual care or usual care alone. The exercise training
group underwent 5-7 intervals of 3-5 minutes in duration at 70-75% of HRmax with 1
minute of active recovery at 45-55% of HRmax. All 3 training groups significantly
improved their exercise tolerance compared to the usual care group (moderate-severe:
62% vs. 22%; mild: 48% vs. 11%; preserved: 45% vs. 0%). The results of this study
indicate that interval exercise training can improve exercise tolerance of heart failure
patients independent of the degree of baseline LV dysfunction.
33
Body Composition and Weight Loss in Heart Failure
Large population-based studies, such as the Health, Aging and Body Composition
(HABC) 111 and the Cardiovascular Health Study (CHS) 112, indicate that 89% of HFpEF
patients are overweight (BMI>25) and 61% are obese (BMI>30). Additionally, patients
with HFpEF have many significant abnormalities in body composition including,
increased total and regional fat mass, decreased type I/type II muscle fibers, increased
intramuscular fat 113, decreased capillary density 114, and increased levels of circulating
inflammatory markers 115, including IL-6 and C-reactive protein. These abnormalities
contribute to the exercise intolerance commonly seen in HFpEF patients. Consequently,
more studies are needed to evaluate the impact of body composition on the
pathophysiology of exercise intolerance in HFpEF patients.
Adipose tissue near and/or within the skeletal muscle significantly affects skeletal
muscle function. Adipose tissue located in this area increases inflammatory cytokines,
and can worsen exercise intolerance 111,115,116. Adipose tissue can be deposited between
skeletal muscle bundles during aging and is more pronounced in patients with physical
disability 114114,117–119. Kouba et al. found that HFpEF patients to have an increase in
intermuscular fat (IMF), that is inversely related to VO2peak 113. Moreover, IMF can be
modifiable through exercise training and weight loss thus making it a potential target for
improving exercise intolerance in overweight HFpEF patients 120,121.
Obesity and fat mass are directly associated with many abnormalities that can
potentially lead to the development of HFpEF including, abnormal left ventricular
diastolic function 122–124, left ventricular hypertrophy 125, atherosclerosis 126–128, increased
markers of inflammation 115,116,127,129, increased blood lipids 127, increased blood pressure
34
130
, and decreased glycemic control 127. Obese individuals who lose weight not only
improve survival 131 but also improve physical function 120,121. Exercise training and
caloric restriction have complementary effects on body composition and physical
function 132–138. Alone, exercise training maintains and improves skeletal muscle
function but often results in minimal weight loss 139. On the other hand, caloric
restriction generally results in significant weight loss but in addition to a loss of fat mass
there can also be a significant loss of muscle mass 140. Thus, it appears that combining
caloric restriction is the optimal method to decrease fat mass yet maintain muscle mass
and improve physical function 135. Furthermore, the combination of the two interventions
also increases thigh muscle mitochondrial size and content 138. To date, there has not
been a trial utilizing caloric restriction in the HFpEF population, alone or in combination
with exercise.
Although the prevalence of older HFpEF patients with obesity is increasing,
physicians are often hesitant to recommend weight loss in this population 141. Much of
this concern is due to the reports of observational studies that indicate a significant
relationship between body fat and survival in HF patients 141,142. A recent review of this
obesity “paradox” suggests there may be a “U-shaped” curve of BMI vs. mortality in
elderly heart failure patients 143. Thus the highest mortality is seen in patients with the
lowest and highest BMI. Moreover, physicians are often concerned that HFrEF patients
who have involuntary weight loss associated with loss of skeletal muscle, depletion of
energy stores, and cytokine activation are in a terminal phase of the disease process 144.
However, HFpEF patients generally differ significantly from HFrEF patients with
regard to body composition. These HFpEF patients are more likely to be overweight
35
and/or obese than HFrEF patients and are more predominantly female 145–147. Very obese
hospitalized heart failure patients are more likely to have HFpEF 142. In contrast to
HFrEF patients, involuntary weight and/or muscle weight loss and catabolism are rarely
seen in HFpEF patients. Furthermore, Kitzman et al. has demonstrated that muscle mass
may actually be well preserved in HFpEF patients, but that the muscle tissue is
dysfunctional, possibly due to adipose infiltration. Despite the uncertainty about the
relationship between body weight and survival in HF, the relationship between obesity
and weight gain are strongly associated with increased morbidity and reduced physical
function in most clinical populations 148.
SECRET Study
To date, no study has look at the effects of weight loss in HF patients. This led to
the design of the Study of the Effects of Caloric Restriction and Exercise Training
(SECRET), which was funded by the National Institute of Health (NIH), in which
participants for this particular study were utilized. The SECRET study was designed to
determine if exercise intolerance and quality of life (QOL) could be improved through
exercise training and caloric restriction in elderly patients with heart failure with a
preserved ejection fraction (HFpEF) 149. Once eligible, the SECRET participants were
randomized into one of four groups: diet only (Diet), exercise only (Ex), exercise and diet
combined (E+D), or an attention control group (AC). This thesis has two aims: (1) to
evaluate the change in objectively measured physical activity levels from baseline to
follow-up in the intervention groups; and (2) to explore the relationship between change
36
in physical activity levels and the primary outcomes of this study (VO2peak and body
weight).
Aims and Hypotheses
Heart failure with a preserved ejection fraction is a significant public health
concern, yet little is known about the PA levels this population and the effects of weight
loss. Thus, this SECRET sub-study has two primary aims. The first aim of this study is
to objectively measure PA levels and evaluate the changes in PA variables (steps/day,
PAEE, LPA, and MVPA) between the intervention groups. We hypothesize the patients
participating in the exercise intervention groups (exercise only and exercise plus diet)
will demonstrate significant increases in objectively measured PA levels compared to
non-exercise intervention groups (diet only and attention control). If an increase in PA
levels are observed, a second aim will be to explore the relationships between the change
in PA levels and change in the primary outcomes of the SECRET trial: VO2peak and
body weight. We hypothesize that there will be a significant correlation between
increases in PA levels and increases in VO2peak, but no significant correlation will be
seen in the relationship between PA levels and weight loss.
37
METHODS
Overall SECRET Design
The recruitment goal for SECRET was to obtain 100 participants within the area
of Wake Forest University Baptist Medical Center. Participant inclusion required a heart
failure diagnosis based upon a clinical score > 3 and a normal ejection fraction (> 50%),
determined by echocardiography. In addition to the above criteria, the participant must
have been at least 60 years of age, had a body mass index of > 30 kg/m2, been managed
for heart failure using the appropriate medical therapy, and be able to perform exercise at
a moderate intensity 149. See Appendix D for detailed inclusion and exclusion criteria for
SECRET.
The testing procedures for the entire SECRET study took place over four different
testing visits. During the first visit, each participant signed an informed consent and
completed medical history forms. This visit also included a medical screening,
anthropometric measurements (height and weight), a basic 2-D echocardiogram, and a
dietary evaluation. Additional assessments during the next three visits included: resting
metabolic rate, phlebotomy for biomarkers, lipoproteins, and brain natriuretic peptide
(BNP), cardiac magnetic resonance imaging (MRI), dual energy x-ray absorptiometry
(DEXA), echocardiography including doppler, maximal isokinetic knee extensor strength
(KinCom), leg muscle power, a skeletal muscle biopsy, and administration of the
Minnesota Living with Heart Failure Questionnaire (MLHF). Furthermore, the 6 minute
walk test (6MWT) and cardiopulmonary exercise test (CPET) with breath-by-breath
expired gas measurements were measured in order to evaluate functional capacity.
38
In elderly patients with HF, the CPET provides reproducible measures of
VO2peak as well as ventilatory anaerobic threshold (VAT) 150. The CPET was conducted
on a motorized treadmill, using the modified Naughton protocol to determine VO2 peak,
VE/VCO2 Slope, and ventilatory anaerobic threshold (VAT) measures. Expired gas
analysis was conducted using a commercially available system (CPX-2000;
MedGraphics; Minneapolis, MN). The system was calibrated according to specification
before testing so that expired gases could be analyzed. The SECRET participants were
encouraged to give a maximal effort during the CPET. Maximal effort during CPET was
determined by an RER > 1.05, RPE > 15, and > 90% age predicted maximal HR. The
participant’s blood pressure, heart rate, and ECG were continuously monitored by a
Master’s level exercise physiologist and a board-certified cardiologist. Peak VO2 was
determined by calculating the average VO2 over the last 15 seconds of the test.
Ventilatory anaerobic threshold was determined with the V-slope method by an
experienced exercise physiologist who was blinded to the participant’s group assignment
149
.
The NYHA functional classification scale was used to determine the extent of
symptom exacerbation during physical exertion or rest (See Appendix A). New York
Heart Association functional classification was determined by the attending cardiologist.
39
Intervention Groups
Attention Control (AC): The attention control group received a counseling session
regarding general health education at baseline. Throughout the 20 week study timeframe,
the subjects in this group were contacted every 2 weeks by SECRET staff members via
telephone to discuss the participant’s general health status without specific reference to
exercise, diet, or weight loss.
Exercise Only (Ex): The exercise group participated in a center-based exercise
program 3 times per week at the Geriatrics Research Center under medical supervision.
Upon the participant’s arrival, body weight; pre-exercise heart rate (HR) and blood
pressure was obtained. Participants then participated in an aerobic warm-up (lap
walking), aerobic exercise (lap walking or treadmill), and a cool-down. Throughout the
exercise session, the staff periodically monitored the participant’s HR and O2 saturations
using a pulse oximeter to ensure the participant’s safety during exercise. Rating of
perceived exertion (RPE) was also monitored to gauge the intensity of exercise (35). The
exercise information (HR and RPE) was recorded on a monthly log form.
Each participant in the Ex group received his or her own exercise prescription
based on the CPET performed at baseline before randomization. The standard exercise
prescription for each participant started at a low intensity (40-50% of VO2 reserve) and
corresponding HR range. As the participant became more tolerant to exercise, the
exercise specialist increased the intensity of the aerobic exercise at a gradual rate.
Exercise intensity was increased until the participant could maintain 60% of his/her VO2
reserve for at least 20 minutes 149. It should also be noted that the exercise prescription
40
and/or modality was altered for those with physical limitations or injuries during the
study. The NuStep (a seated, reclined elliptical) was utilized if participants were unable
to walk sufficiently.
Diet Only (Diet): The Diet group of SECRET included a dietary consultation at
baseline with a registered dietician (RD) at the Geriatric Research Center at Wake Forest
University Baptist Medical Center. Each participant received a breakfast menu from
which they choose a breakfast to prepare for themselves every morning. Two
hypocaloric meals were provided for lunch, supper, and snacks for the rest of the day.
The participant chose between 24 dietary items on a menu and were prepared by the
GCRC metabolic kitchen. This 24 item menu was designed to promote a balanced diet
with <30% of calories from fat and 1.2 grams of protein/kg of ideal body weight/day.
The hypocaloric meals were picked up three times per week by the participant at the
GCRC metabolic kitchen. A dietary log was kept by each participant to monitor their
intake of foods and beverages. The diet was adjusted, as needed, to achieve a 2,500
kcals/week deficit in order to produce an approximate 1 pound per week weight loss. No
patient received a diet <1,000 kcals per day. For safety measures, total weight loss for
each subject was capped at 15% initial body weight at baseline or at a BMI of <27 for
that individual. Participants in the exercise interventions (both with and without weight
loss) participated in a weekly weigh-in. If the participants experienced an excessive
weight loss, then their caloric needs and diet plan were recalculated so that the participant
would achieve the appropriate weight. Weekly individual counseling sessions with a RD
were utilized to enhance compliance to the diet.
41
Exercise and Diet (E+D): If the participant was randomized to the E+D group,
then the participant received both the exercise and diet interventions described above.
During the final week of the 20-week intervention, participants in all four groups
wore the accelerometer to measure follow-up PA levels. The accelerometry data was
processed following the procedures described for baseline measures. Participants then
underwent follow-up testing at the end of the 20-week intervention. This testing included
the same measures that were obtained at baseline and were completed over the same
number of visits. A 12-month follow-up was also conducted with a SECRET staff
member over the phone to determine the participant’s current clinical status, weight, and
physical function. In addition, the SECRET personnel performing outcomes assessments
were blinded from group randomization when feasible 149.
Sub-Study Design
All SECRET participants were given a programmed Kenz Lifecorder Ex
accelerometer, prior to randomization, on their second clinical visit and were instructed to
wear it for at least 7 days. Each accelerometer was programmed with the participant’s
age, weight, height, gender, and time of day before being given to the participant to wear.
Instructions on how to wear the accelerometer were verbally given to the participant. The
device was sealed so the participant was unable to obtain any feedback about their
activity level. The subject was told to consistently wear the device on either the left or
right hip with the safety cord attached to clothing. They were instructed to begin wearing
the device as soon as they woke up, and to continue to wear the accelerometer during all
42
waking hours except for when showering, swimming, or sleeping. Ideally the device
should be worn between 7-10 days to obtain stable baseline measures of the participant’s
physical activity levels. A slight variability in the number of days the device was worn
occurred because the accelerometer could be returned in person during one of the other
visits or through the mail in a protective envelope. Once the device was returned, the
device was connected to a PC and the information collected by the device was
downloaded.
The Kenz Lifecorder is a device that is 6 x 4.6 x 2.6cm and lightweight (40
grams) and analyzes vertical accelerations ranging from 0.06 to 1.94 G, where 1 G is
equal to the acceleration of earth’s gravity, at a frequency of 32 Hz. The movement
intensity is determined by the frequency and magnitude of the accelerations and recorded
every 4 seconds. The movement intensity is measured on a scale of 1 to 9, with 1 being
the lowest intensity of movement and 9 being the highest movement intensity. These
intensity levels have been previously shown to correlate highly with metabolic
equivalents (METs) and divided into categories of 1 to 3, 4 to 6, and 7 to 9 METs, for
light, moderate, and vigorous levels of PA, respectively 91,153. It should be noted that light
physical activity may be underestimated with this device as the intensity level of 1
correlates to approximately 2 METs 91,153. Given the population explored in this thesis,
light PA (LPA) was defined as 1-2 METs and moderate-vigorous PA (MVPA) was
defined as 3-9 METs. Also, it is important to note that these cut-points are not relative to
each individual patient.
Physical activity analysis software (PAAS) allows for data to be downloaded
from the accelerometer to the PC. Data is then viewed on a Microsoft Excel CSV
43
spreadsheet as well as in a customized report. The spreadsheet contains the following
information; dates of wear, the participant’s height, weight, gender, and age, total daily
energy expenditure (DEE) expended in kilocalories. Physical activity energy expenditure
(PAEE) expressed in kilocalories (kcal), daily step count, and minutes spent in light,
moderate, and vigorous activity levels are quantified for each day. The customized report
reflected the same information, but also includes graphs describing the frequency of
device usage and number of minutes at each movement intensity level.
From the customized report, each subject’s physical activity data was evaluated to
determine if he or she would be included or excluded further data analysis. The total time
for each day was determined and had to meet or exceed 10 hours for inclusion. When the
participant fulfilled the first criteria of wear time (≥ 10 hrs.) for a particular day, the
percent of wear time for each day was also calculated. If the participant did not wear the
device for at least 80 percent of the total wear time, then that day was excluded from
further analysis. To be included in this SECRET sub-study, the participant had to have at
least three days that met the accelerometry inclusion criteria. These inclusion and
exclusion criteria for the physical activity measures were based on previous research
154,155
. Thus, for each participant in this sub-study we were able to obtain the following
measures: steps/day, minutes of light (LPA) and moderate/vigorous physical activity
(MVPA), and physical activity energy expenditure (PAEE).
Statistical Analyses
All of the data were entered into SPSS Statistics 19.0 for Windows and analyzed
for normality. Descriptive statistics, including mean, standard deviations, and ranges,
44
were run on all data sets. A Two-Way Repeated Measures ANCOVA was used to
examine the changes in PA measures, physical fitness, and body composition from
baseline to 20 weeks. During this analysis, adjustments were made for both age and
baseline values. Pearson Product Moment Correlations were performed to examine the
relationships between the primary outcomes (VO2peak and body weight) and PA
measures. Paired sample t-tests were also conducted to compare PA measures between
Exercise and Non-Exercise days. A P-value of < 0.05 was considered statistically
significant for all analyses.
45
RESULTS
The primary aim of this thesis was to objectively quantify the changes in physical
activity (PA) levels in those with heart failure and a preserved ejection fraction (HFpEF)
during a 20 week intervention. The PA levels were evaluated using a Kenz-Lifecorder
Ex accelerometer at baseline and follow-up of a single-blinded, randomized controlled
trial. The PA measures obtained from the accelerometer were steps/day, minutes of light
(LPA) and moderate-vigorous (MVPA) PA, as well as PA energy expenditure (PAEE).
The second objective of this thesis was to explore the relationships between the change in
PA measures and the primary outcomes of the study, VO2peak and body weight. Eighty
participants from the SECRET study at Wake Forest University Baptist Medical Center
were recruited for this study. Eighty HFpEF patients were included in the SECRET
study, of which 54 had sufficient accelerometer data at baseline, of which 43 subjects met
the inclusion criteria for this particular sub-study and were included in this analysis. See
the diagram in Figure 1 for a detailed explanation of participant exclusions after baseline.
Participant Demographics
Descriptive statistics of the SECRET participants included in this investigation
are listed in Table I. This sample included a greater number of females (N = 32)
compared to males (N = 11). There were a higher percentage of whites (N = 27, 62.8%)
compared to blacks (N = 15, 34.9%) and Hispanics (N = 1, 2.3%). This sample was
comprised only of NYHA Class II and III patients (N = 29 and N = 13, respectively).
Ninety-eight percent of these patients had a history of hypertension and 44.2% were
diagnosed with type 2 diabetes. Among the patients in the study, 37% were on beta
46
blockers, 49% were on ACE inhibitors, and 67% were on diuretics. Additionally, there
were no differences in medications between the groups and the medications did not
change during the course of the study. The participants included in this study were well
managed for their HF and hypertension. The only significant difference between the
intervention groups was age (the Ex group was significantly older than the E+D group).
Figure 1: Flow diagram for patient exclusions
47
Table I: Descriptive Characteristics of Study Participants
ALL
(N = 43)
Exercise
(N = 9 )
Diet
(N = 13)
Mean ± SD
Exercise
Plus Diet
(N = 12 )
Mean ± SD
Variables
Mean ± SD
Mean ± SD
Age (Years)
Min – Max
68.1 ± 5.7
Mean ± SD
Min – Max
72.6 ± 4.9*
Min – Max
68.4 ± 5.6
Min – Max
66.0 ± 5.1*
Min – Max
66.0 ± 5.4
BMI (kg/m )
60 – 81
38.8 ± 5.7
67 – 81
38.5 ± 7.5
60 – 78
36.1 ± 3.3
60 – 79
40.2 ± 4.8
61 – 78
41.1 ± 7.0
Ejection
30.1 – 55.6
61.6 ± 6.3
30.8 – 55.6
59.8 ± 7.0
30.1 – 42.1
61.7 ± 7.2
32.7 – 48.3
61.7 ± 5.9
32.0 – 51.2
63.2 ± 5.3
Fraction (%)
Body Fat
49.0 – 73.9
45.0 ± 7.4
49.0 – 68.9
45.2 ± 3.7
50.0 – 72.6
44.0 ± 6.6
55.1 – 72.0
45.0 ± 7.4
56.8 – 73.9
44.1 ± 7.5
(%)
6MW (m)
32.8 – 56.3
416.7 ± 59.9
39.5 – 50.0
400.6 ± 69.4
29.6 – 56.1
435.4 ± 60.3
32.8 – 56.3
416.7 ± 59.9
29.5 – 51.1
412.6 ± 83.0
313 - 513
304 – 487
343 – 550
313 – 513
253 – 505
2
Control
(N = 9)
*Significant Difference between Exercise and Diet Plus Exercise (P < 0.05)
BMI = Body Mass Index; 6MW = Six Minute Walk
Treatment Effect on the Primary Outcomes, VO2peak and Body Weight
Patients were randomized into one of four interventions: Exercise Only (Ex), Diet
Only (Diet), Exercise Plus Diet (E+D), and Attention Control (AC). Both body weight
and VO2peak were normally distributed. Analysis of covariance indicated there was a
significant group main effect for body weight (p < 0.001). Post hoc analysis determined
that at follow-up, participants in the Diet and E+D groups had a significantly lower
adjusted mean body weight (94.0 ± 1.27 and 93.5 ± 1.30 kg, respectively) than the AC
48
group (102.9 ± 1.47 kg) (Figure 2). The adjusted body weight at follow-up for the Ex
group (99.0 ± 1.60 kg) was not significantly different from any of the other groups.
Additionally, there was no statistical difference in adjusted body weight at follow-up
between the Diet and E+D groups. The absolute mean (and %) change in body weight
from baseline to follow-up for the AC, Diet, Ex, and E+D was 0 (0%), -8.4 (-9%), -4.3 (4%), and -10.3 (-9%) kg, respectively.
Figure 2: Unadjusted Mean Body Weight at Baseline and Follow-Up for the Groups
* Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Attention Control group (P < 0.01)
Average unadjusted values for VO2peak for the four groups at baseline and
follow-up are presented in Figure 3. Analysis of covariance indicated there was a
significant group main effect for VO2peak (p < 0.001). Post hoc analysis indicated that at
follow-up, participants in the Diet and E+D groups had a significantly higher adjusted
VO2peak (16.2 ± 0.36 and 16.8 ± 0.37 ml∙kg∙min-1, respectively) than the AC group (13.9
± 0.41 ml∙kg∙min-1) (Figure 2). However after adjusting for body weight by examining
VO2peak in ml∙min-1, there was no significant difference between the Diet and AC
49
groups. Furthermore, no significant differences in adjusted VO2peak values were
observed between the Ex (15.5 ± 0.45 ml∙kg∙min-1) group and the other three groups
(Diet, E+D, and AC) at follow-up. The absolute unadjusted mean (and %) change in
VO2peak from baseline to follow-up for the AC, Diet, Ex, and E+D was -0.8 (-5%), 1.3
(9%), 0.9 (7%), and 2.3 (13%) ml∙kg∙min-1, respectively.
Figure 3: Unadjusted Mean VO2peak at Baseline and Follow-Up for the Groups
* Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Attention Control group (P < 0.01)
Treatment Effect on Physical Activity Measures
Analysis of covariance, controlling for age and baseline values, was used to
analyze differences in PA measures (steps/day, minutes of LPA and MVPA, and PAEE)
between the groups. A significant group interaction was found for steps per day (p <
50
0.01). Post hoc analysis indicated that participants in the E+D group obtained
significantly more adjusted steps per day (6590.55 ± 445.01 steps/day) at follow-up than
the Diet (4086.56 ± 450.54 steps/day) and AC (4331.70 ± 502.15 steps/day) groups
(Figure 4). The adjusted mean for the Ex group (4754.70 ± 554.37 steps/day) was not
significantly different than the other groups. The absolute mean (and %) change in
steps/day from baseline to follow-up for the AC, Diet, Ex, and E+D was 532 (16%), 543
(13%), 1349 (46%), and 2649 (67%) steps/day, respectively.
Figure 5 displays the changes in unadjusted mean LPA values for the four groups.
Analysis of covariance determined there was no significant group main effect (p = 0.644)
for minutes of LPA. However there was a significant group interaction for minutes of
MVPA (p < 0.001). Post hoc analysis determined that participants in E+D group had
significantly more adjusted minutes of MVPA at follow-up (29.42 ± 2.50 min) when
compared to the other three groups (Ex: 15.50 ± 3.12 min; Diet: 12.19 ± 2.53 min; AC:
11.91 ± 2.82 min) (Figure 6). No other significant differences were observed at followup between the intervention groups. The absolute mean (and %) change in minutes of
MVPA from baseline to follow-up for the AC, Diet, Ex, and E+D was 2.1 (25%), 2.6
(23%), 5.9 (90%), and 20.2 (202%) minutes of MVPA, respectively.
51
Figure 4: Unadjusted Mean Steps per Day at Baseline and Follow-Up for the Groups
* Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Attention Control group (P < 0.01)
‡ Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Diet group (P < 0.01)
Figure 5: Unadjusted Mean Minutes of LPA at Baseline and Follow-Up for the Groups
No significant differences were observed for minutes of LPA per day between groups.
52
Figure 6: Unadjusted Mean Minutes of MVPA and Baseline to Follow-Up for the Groups
* Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Attention Control group (P < 0.01)
† Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Diet Only group (P < 0.01)
‡ Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Exercise Only group (P < 0.01)
Analysis of covariance demonstrated a significant group interaction (P < 0.01) for
PAEE and therefore post hoc analysis was conducted. The E+D group had significantly
higher adjusted mean PAEE at follow-up (261.94 ± 20.96 kcals) compared to the Diet
(152.05 ± 21.22 kcals) and AC (161.42 ± 23.65 kcals) groups (Figure 7). The adjusted
PAEE for the Ex group (183.00 ± 26.12 kcals) was not statistically different from any of
the other groups at follow-up. The absolute mean (and %) change in PAEE from baseline
53
to follow-up for the AC, Diet, Ex, and E+D was 19.2 (14%), 8.5 (6%), 55.5 (48%), and
109.6 (68%) kcals, respectively.
Figure 7: Unadjusted Mean Physical Activity Energy Expenditure (PAEE) at Baseline
and Follow-Up for the Groups
* Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Attention Control group (P < 0.05)
‡ Indicates a statistically significant difference at follow-up based on adjusted means
(from ANCOVA) compared to Diet Only group (P < 0.05)
Comparison of Exercise and Non-Exercise Days
In order to further investigate the changes observed in the PA variables, additional
analyses were conducted to compare days that patients attended a cardiac rehab program
exercise session (exercise day) compared to days they did not attend an exercise session
54
(non-exercise day) during the final week of the intervention. Since not all of the groups
received exercise treatment, this analysis was only conducted on those in the Ex and E+D
groups.
Paired sample t-tests indicated there was a significant difference in steps per day
between non-exercise days and exercise days at follow-up in both the Ex (3433.57 ±
540.63 to 6808.86 ± 1094.35, respectively) and E+D (4627.44 ± 557.61 to 9037.89 ±
1168.36, respectively) groups (Figure 8). Only the E+D had significantly greater minutes
of LPA on exercise days than non-exercise days (48.66 ± 5.32 vs. 40.71 ± 5.02,
respectively) as well as minutes of MVPA (52.96 ± 7.12 vs. 15.85 ± 2.15, respectively)
(Figures 9 and 10). Furthermore, the Ex and E+D groups had significantly higher PAEE
on exercise days than non-exercise days (262.00 ± 52.85 vs. 119.71 ± 20.47 and 378.84 ±
56.88 vs. 172.64 ± 26.75, respectively) (Figure 11). However, no significant differences
were observed between the Ex and E+D groups for steps/day, minutes of LPA or MVPA,
or PAEE on either exercise or non-exercise days.
55
Figure 8: Unadjusted Mean Steps/day at 20 Weeks During Non-Exercise Days vs.
Exercise Days
No significant differences were observed between groups for non-exercise and exercise
days.
Figure 9: Unadjusted Mean LPA at 20 Weeks During Non-Exercise Days vs. Exercise
Days
No significant differences were observed between groups for non-exercise and exercise
days.
56
Figure 10: Unadjusted Mean MVPA at 20 Weeks During Non-Exercise Days vs.
Exercise Days
No significant differences were observed between groups for non-exercise and exercise
days.
Figure 11: Unadjusted Mean Physical Activity Energy Expenditure (PAEE) at 20 Weeks
During Non-Exercise Days vs. Exercise Days
No significant differences were observed between groups for non-exercise and exercise
days.
57
Physical Activity Measures Versus Primary Outcomes: Body Weight and VO2peak
The relationship between the change in accelerometer-derived PA measures
(steps/day, PAEE, minutes of LPA and MVPA) from baseline to follow-up and change in
primary outcomes (VO2peak and body weight) were determined using the Pearson
Product Moment Correlations. The calculated r-values are shown in Table II. The
increase in minutes spent in MVPA from baseline to follow-up was significantly
correlated, albeit weakly, with both primary outcome measures, VO2peak and body
weight. No other PA variables were significantly correlated with the primary outcome
measures. There was a significant correlation between change in body weight and
VO2peak (r = 0.684).
Table II: Correlations Between Changes in PA Levels and Primary Outcomes
Variables
Steps/day
PAEE
LPA
MVPA
VO2 peak
.053
.039
-.260
.329*
Body Weight
.212
.236
-.133
.387*
*Significant correlation with a P-value < 0.05
58
DISCUSSION
Numerous studies have evaluated, either subjectively and/or objectively with
accelerometers, the physical activity (PA) levels of healthy subjects 73,78,80–84,86,156, those
with cardiovascular disease 89,91,157–159, as well as patients with heart failure and a reduced
ejection fraction (HFrEF) 96–98,100–104. However, no studies to date have evaluated the PA
levels of subjects with heart failure and a preserved ejection fraction (HFpEF).
Additionally no studies to date have studied the effects of a randomized controlled trial of
an exercise intervention, with and without weight loss, in either type of heart failure
patient. Therefore, the primary aim of this thesis was to objectively measure PA levels in
those with HFpEF and evaluate the changes in PA variables between patients in the four
intervention groups: exercise only (Ex), diet only (Diet), exercise plus diet (E+D), and
attention control (AC). The secondary objective of this thesis was to explore the
relationship between the changes in PA levels and changes the primary outcomes of the
study, VO2peak and body weight.
Participant Demographics
As shown in Figure 1, 80 HFpEF patients were recruited for the SECRET study at
the Wake Forest University Baptist Medical Center. However due to either lack of
adequate data and/or lack of accelerometer wear, at either baseline or follow-up, 37
patients were excluded from this sub-study. Most of these exclusions were because
subjects did not meet the criteria for sufficient wear-time of ≥ 10 hours of data for ≥ 3
days. Ultimately, 43 HFpEF patients were included in this study. Patients had an EF%
of approximately 61%, which is consistent with the definition used to diagnose HFpEF in
59
which patients present with symptoms but have a normal EF% (≥ 50%). The participants
in this sample were elderly (mean: 68 ± 5.7 years), mostly female (74%), and
predominantly white (62.8%). Additionally, participants in this study were
overweight/obese with a mean weight of 103 ± 17.5 kg, a BMI of 38.8 ± 5.7 kg/m2, and a
% body fat of 44.5 ± 6.4%. There was a significant difference in age (6 years) between
the Ex and E+D groups, but no other significant demographic differences were observed
between the groups.
This SECRET trial consisted of a greater proportion of females than males, which
is to be expected in the HFpEF population and widely reported in the literature 110. The
exact reason for the increased prevalence of HFpEF in women is unclear, but it has been
speculated that the “protective” role of estrogen is absent in elderly women after
menopause 160,161. Additionally, women have been shown to demonstrate a greater
amount of LV hypertrophy and less LV dilation in response to the pressure overload
associated with high blood pressure than men 162.
To date, four randomized controlled trials of exercise training in the HFpEF
population have been reported 107–110. Overall, the participants in the present study were
similar to the participants of the previous studies in regards to age, gender, EF%, and
NYHA class. The main differences between the four previous RCTs and this study is the
higher body weight and body fat of the participants of the present investigation.
However, SECRET was designed with the goal of weight loss through diet and/or
exercise and therefore the inclusion criteria included obese HFpEF patients with a BMI >
30 kg/m2 compared to the lower BMI criteria (>25) for the previous RCTs.
60
Changes in Primary Outcomes: Body Weight and VO2peak
Both the Diet and E+D groups had significantly lower body weight at follow-up
(94.0 ± 1.27 and 93.5 ± 1.30 kg, respectively) compared to the AC group (102.9 ± 1.47
kg). As discussed earlier, no studies to date have examined the effects of exercise, with
or without a dietary component, in either HFpEF or HFrEF patients. However, the
changes in body weight observed in the present study are consistent with other weight
loss programs reported in the literature. Ross et al. 135 reported a 10% weight reduction
in 16 weeks in obese individuals undergoing diet, both with and without an exercise
training program. Ades et al. 163 examined body composition changes in overweight
cardiac rehabilitation participants undergoing a 16 week high-caloric expenditure
exercise training program and dietary changes. Despite a combination of high-caloric
expenditure exercise and dietary changes, there was a slightly smaller reduction in body
weight (-8.2 kg) in the study by Ades et al. than in the E+D group in the present study (10.3 kg). This could be attributed to the higher body weight (104 vs. 95 kg) of the
participants in this particular study compared to the cardiac rehabilitation participants of
Ades et al., respectively. Individuals with a higher body mass expend a greater number
of calories at the same level of exercise as individuals with a lower body mass.
Although the Ex group did lost weight from baseline to follow-up (-4.3 kg, 4%),
the body weight at follow-up was not found to be statistically different than the other
three groups. This was not totally unexpected, since several studies 164–166 have shown
that 3 day/week of exercise training within a traditional cardiac rehabilitation (CR)
programs does not to produce significant weight loss. One study found a weight
reduction of 5% after 12 weeks of CR 165, while another 166 observed a weight loss of -4.5
61
kg after 12 weeks. It is generally well accepted that ≥180 minutes/week of exercise are
necessary for significant weight loss without significant dietary changes 167. The Ex
group in the present investigation participated in an exercise program consisting of 30-40
minutes of aerobic exercise 3 times/week. Consequently, patients in the Ex only group
only accumulated ~90-120 minutes per week of moderate intensity PA, an amount
apparently insufficient for weight loss.
Patients in the Diet and E+D groups had a significantly higher VO2peak at followup (16.2 ± 0.36 and 16.8 ± 0.37 ml·kg·min-1, respectively) compared to the AC group
(13.9 ± 0.41 ml·kg·min-1). The Ex group was not found to be statistically different at
follow-up than the other groups (15.5 ± 0.45 ml·kg·min-1). The Diet and E+D groups
increased their VO2peak by 9 and 13%, respectively; whereas the Ex group only
increased their VO2peak by 7%. Multiple studies have examined the effects of exercise
training in the HFrEF population and generally report improvements of 18-25% in
VO2peak 97,99–101,103,104. However, Brubaker et al. 102 reported a similar non-significant
increase in VO2peak in older HFrEF patients participating in a 16 week exercise only
intervention results after exercise training in HFrEF patients. Further analysis of this data
indicated that after 16 weeks of aerobic training, 26% of patients had a clinically
significant increase of ≥10% and another 39% had an improvement of 0-9.9%.
Comparable results were found in the Ex group of the present study in which 22% had a
clinically significant increase in VO2peak (≥ 10%) and the remaining 78% increased their
VO2peak by 0-9.9%. It appears that exercise training alone produces variable responses
in the change in VO2peak, despite similar training programs in older HFrEF and HpEF
62
patients. Further studies are warranted to determine why some older HF patients respond
more favorably to exercise training than others.
Five studies to date have examined the effects of exercise training in the HFpEF
population 106–110; however, only two studies 108,110 were similar to the present
investigation in regards to design (RCT) as well as the frequency, duration and intensity
of the exercise program. Both Kitzman et al. 110 and Edelmann et al. 108 reported similar
increases in VO2peak of 16%, despite differences in training duration (16 and 12 weeks,
respectively). The main difference between the present investigation and the previous
reports mostly relate to the patient populations. Although the patients studied by
Kitzman et al. 110 were similar in age (70 vs. 68 years, respectively) to the patients in the
present investigation, they had significantly lower body weight (79 vs. 104 kg,
respectively). The HFpEF patients studied by Edelmann et al. 108 were slightly younger
than those in the present study (65 vs. 68 years, respectively) and also had a lower BMI
(31 vs. 38 kg/m2, respectively). The combination of older age and higher body weight of
the participants may explain the lower VO2peak changes observed in the present study.
In contrast to the Ex group, patients in the Diet and E+D significantly improved
their VO2peak after 20 weeks. The significant increase in VO2peak in the Diet group was
unexpected since these patients were not assigned to an exercise group. However, the
Diet group lost a significant amount of body weight, whereas the Ex group did not lose
any weight. Since VO2peak is expressed in ml∙kg∙min-1, losing weight, even without
exercise, will increase an individual’s VO2peak. In fact, after adjusting for body weight
by expressing VO2peak in ml∙min-1, there was no significant difference between the Diet
and AC groups at follow-up. Furthermore, in this investigation there was a significant
63
correlation (r = 0.68) between change in body weight and change in VO2peak. This
indicates that the weight loss observed in this trial explains 46% of the variance in the
change in VO2peak. Other factors such as medication, disease severity, and genetics may
contribute to the remainder of change in functional capacity. Furthermore the possibility
that the Diet group may have begun exercising on their own cannot be ignored as patients
will often “drop-in” to interventions they did not receive.
The E+D group demonstrated the greatest increase (13%) in VO2peak as well
decrease in body weight (9%). This further demonstrates the important relationship
between changes in body weight and VO2peak in this population. Annesi 168 found
controlled eating self-efficacy has a mediating role between exercise and weight loss,
which explains why the Diet and E+D groups lost a significant amount of weight but the
Ex group did not. Annesi also observed a significant relationship between controlled
eating self-efficacy and exercise self-efficacy. It is possible that as individuals
experienced weight loss, they felt better physically and gained confidence about exercise,
allowing more PA both during and outside the exercise program. Moreover, as weight
loss was the goal of this group, it is likely that patients in the E+D group were more
motivated to increase their PA levels in order to reach their weight loss goals.
Changes in Physical Activity Measures
A uniaxial accelerometer was used in this investigation to objectively measure
physical activity (PA) and quantify steps/day, minutes of light (LPA), moderate-vigorous
(MVPA), and PA energy expenditure (PAEE). At baseline, this sample of HFpEF
patients averaged 3,679 steps/day with a range of 1,354-6,514 steps/day. Based on the
64
classification system of Tudor-Locke and Bassett, these HFpEF patients used in this
investigation would be classified as “sedentary” (< 5,000 steps/day) 156. Although this is
the first study to examine PA levels in the HFpEF population, Shedd 72 objectively
quantified PA levels of HFrEF patients participating in the HF-ACTION trial. The
HFrEF patients averaged more steps/day (4,858 ± 1,895 steps/day) than the HFpEF
participants in the present study. The 32% higher step counts found by Shedd could be
related to the younger (58 vs. 68 years), lower BMI levels (30 vs. 38 kg/m2), and a higher
functional capacity (VO2peak = 15.8 vs. 14.7 ml∙kg∙min-1) of the HF ACTION patients
compared to participants in the present study.
Ayabe et al. 169 examined the relationship between step counts and PAEE in
cardiac patients involved in a CR program. The investigators found patients should
accumulate at least 6,500 steps/day in order to achieve the 1,500 kcal of PAEE, the
generally recommended for the secondary prevention of CVD. After the 20 weeks of the
present intervention, all four groups increased their steps/day, but the E+D group was
significantly greater than the other groups at the 20 week follow-up. At follow-up, the
E+D group averaged 6,629 steps/day which changed their initial activity classification
from “sedentary” to “low-active” and close to the target level established by Ayabe et al.
169
. All other groups remained in the “sedentary” category. It is interesting to note that
the AC and Diet groups increased their steps from baseline to follow-up by (~500
steps/day, ~15%). These findings suggest that patients participating in a lifestyle
intervention study, regardless of group assignment, do often “drop-in” and increase their
PA levels. The Ex group also increased their steps/day, to a greater extent (+ 1349
steps/day, 46%) than the AC and Diet groups; however, at follow-up the steps/day
65
achieved by the Ex group was not significantly different than the other groups. Thus, it
appears that participating in the exercise intervention 3 times per week did have a greater
impact (2-3 fold) on steps/day than the non-exercise Diet and AC groups.
The number of minutes/day of light (LPA) and moderate-vigorous (MVPA) PA
were also quantified in order to assess the levels of PA in these HFpEF patients. At
baseline, the patients in this particular study accumulated approximately 32 minutes/day
of LPA. There are no specific recommendations for the recommended amount of LPA,
but it is generally believed that “more is better”. There were no significant differences
between the groups in minutes of LPA at follow-up. This would be expected as patients
undergoing exercise training (Ex and E+D) would likely exercise at an intensity that
would be expected to be within the moderate-vigorous range.
At baseline, the patients in this study accumulated approximately 9.5 minutes/day
of MVPA. Although there are no specific recommendations for the amount of LPA, the
CDC recommends that individuals accumulate at least 30 minutes/day of MVPA most
days of the week to improve health. All four groups increased minutes of MVPA from
baseline to follow-up, but the E+D group was significantly higher than the other groups
at 20 weeks. Patients in the E+D group increased their MVPA by over 200% to 30.1
minutes/day, more than double observed in the Ex group (12.4 minutes/day) at follow-up.
Consequently, patients in the E+D group meet the CDC recommendation of ≥ 30
minutes/day of MVPA whereas the Ex group did not. Minutes of MVPA has been shown
to have the greatest relationship to a variety of health outcomes 38.
Physical activity energy expenditure (PAEE) was also used in this investigation to
quantify PA levels in HFpEF patients. The amount of PAEE generally recommended by
66
the CDC-ACSM and Surgeon General is ≥ 150 kcals/day or 1,000 kcals/week. However,
weight loss and coronary artery disease regression are more likely to occur at ≥ 2,000
kcals/week (≥300 kcals/day) 170. At baseline, the HFpEF patients in this investigation
averaged 142 kcals/day. While this appears to be close to the recommended levels, there
was a wide range of PAEE observed among the participants in this investigation (38 –
226 kcals/day). The high levels of body weight of these HFpEF patients would make it
easier to expend more calories and thus may explain the relatively high baseline levels of
PAEE. Despite increases in PAEE from baseline to follow-up in all four groups, only the
E+D group was significantly higher than the other groups at follow-up. At follow-up,
patients in the E+D group expended an average of 1,834 kcals/week which approaches
the recommended PAEE level associated with CAD regression and/or weight loss (>
2,000 kcals/week) 91. When this caloric expenditure of 1,834 kcals/week is extrapolated
over the course of the 20 week intervention it would be expected that patients would lose
~10.5 kg. In fact, on average, the E+D group lost on average,10.3 kg. In contrast, the Ex
group did not significantly increase their PAEE from baseline to follow-up.
Using similar methods, Childress 171 objectively quantified the PA levels of
overweight older adults randomized to a physical activity (PA) group, physical activity
and weight loss (PA + WL) group, or control. Physical activity levels were measured
using a Kenz-Lifecorder accelerometer, the same device used in this present
investigation. In contrast to the present investigation of HFpEF, Childress observed
significant increases in PAEE levels in both the PA and PA + WL at 6 months, but there
were no differences between the two PA groups. While the HFpEF patients used in the
present investigation were older and heavier, the primary difference was the exercise
67
intervention. Whereas the present investigation involved center-based exercise training
only, the intervention employed by Childress was a community-based intervention that
focused on increasing lifestyle PA at a community center and at home. This approach
appears to result in greater amounts of PAEE compared to a “traditional” exercise
program.
Comparison of Exercise and Non-Exercise Days
The E+D group increased their steps/day by approximately twice as much as the
Ex group, which was somewhat surprising since both groups were prescribed the same
exercise intervention of 3 times per week for 40-60 minutes. One potential explanation
for these differences could be that participants in the E+D group might have been more
physically active on non-exercise days than the Ex group. Figure 8 indicates that the
E+D group did accumulate more steps (1,193) on non-exercise days than the Ex group
(4,627 vs. 3,434 steps/day, respectively). Moreover, the E+D group took 2,230 more
steps than the Ex group on exercise program days. This suggests that the E+D patients
did more PA during the exercise sessions or additional PA outside of the structured
program. In either case, this additional PA in the E+D patients likely contributed to the
greater weight loss and improvement in VO2peak observed in the E+D group.
The E+D group also demonstrated non-significantly higher levels of LPA,
MVPA, and PAEE on non-exercise and exercise days compared to the Ex group. This is
unexpected as both groups participated in the same exercise intervention. Figure 10
shows minimal difference in MVPA between the Ex and E+D groups on non-exercise
days (9.1 vs. 15.9 minutes, respectively). Although not statistically different, the E+D
68
group had 23.3 more minutes of MVPA on exercise days than the Ex group. Furthermore,
the E+D group expended nearly 100 more kcal than the Ex group on the three exercise
days. Higher levels of MVPA and PAEE in the E+D group, compared to the Ex group,
may be explained by the impact of weight loss on physical activity. The decreased body
weight in the E+D group may have increased exercise tolerance allowing them to
exercise for a longer duration during exercise sessions. These benefits could have
potentially extended to non-exercise days as well, thus resulting in more minutes of LPA
on non-exercise days in the E+D group than the Ex group (40.7 vs. 29.9 minutes,
respectively). It was also interesting to observe that the Ex group appeared to decrease
their PAEE on non-exercise days compared to the AC group. This compensation of
decreased PA levels the day after a structured bout of exercise has been observed in
previous studies in the elderly population 172,173. Patients either are fatigued from the
previous bout of PA or believe that the structured bouts of activity (2-3 times/week) are
sufficient.
Relationship Between Physical Activity Measures and Primary Outcomes
The change in minutes of MVPA per day was the only PA measure found to be
correlated with both primary outcomes (VO2peak and body weight). Since the major
difference in treatments between the Diet and E+D groups is the moderate intensity PA
obtained in the center-based exercise program, this finding does not come as a surprise.
Childress et al. 171 reported a similar correlation between minutes of MVPA and change
in body weight in overweight older adults during a weight loss intervention. In contrast
to the present study, Childress et al. 171 also found significant correlations between
69
changes in body weight and changes in steps/day (r = .42) and PAEE (r = .37). The
higher BMI and disease severity of the HFpEF patients in the present study may have
prevented them from reaching the same PA levels as the older overweight adults studied
by Childress et al. The lower range of PA and primary outcome measures observed in
the present study may have reduced the correlations between these measures.
Limitations
There were several limitations to the present study. This study did have a high
exclusion rate. It could be argued that the participants who were excluded were less
compliant and more physically inactive which could have biased the results. Secondly,
while dietary data has been collected for this study, it has not yet been analyzed and thus
could not be included in this thesis. Consequently, the impact of diet changes on the
primary outcomes and PA measures could not be determined. Another limitation is that
PA levels were assessed at both baseline and follow-up by wearing an accelerometer for
~10 days. It is possible that participants in any of the groups could have temporarily
modified their PA levels and thus altered the accelerometry results. Finally, as the case
with any RCT, the impact of “drop-outs” and “drop-ins” cannot be controlled and may
have affected the results of the study.
Conclusions
This is the first study to evaluate a randomized controlled trial of an exercise and
diet intervention in HFpEF patients. Results of this 20 week study suggest that exercise
and diet is the most effective short-term combination for weight loss and for increasing
70
VO2peak in this population. Another unique finding of this study was that diet alone
compared to exercise alone was superior for producing improvements in VO2peak and
weight loss. This is also the first study to evaluate PA levels before and during an RCT
of diet and exercise in HFpEF patients. Results of this trial suggest that the E+D group
demonstrated the largest increase in PA measures and that changes in PA levels only
modestly correlate with changes in VO2peak, suggesting other factors, particularly diet
changes, also play an important role in the weight loss in HFpEF patients.
71
APPENDIX A
New York Heart Association Functional Classification
Class I: Patient that has heart disease and symptoms are exacerbated at physical activity
levels that would inhibit normal individuals
Class II: Symptoms are exacerbated at levels of ordinary exertion
Class III: Symptoms are exacerbated at exertion levels that are less than ordinary
Class IV: Symptoms are exacerbated at rest
72
APPENDIX B
American Heart Association and American College of Cardiology Heart Failure
Classification System
Stage A: Patients who have no structural disease or disorder of the heart, but are at high
risk of developing heart failure
Stage B: Patients who have structural disease or disorder of the heart, but have not yet
developed symptoms of heart failure
Stage C: Patient who has underlying heart disease, which is associated with past or
present heart failure symptoms
Stage D: Patient in end-stage heart failure which requires a specialized treatment regimen
such as mechanical circulatory support, cardiac transplantation, continuous
inotropic infusions, or hospice care
73
APPENDIX C
SECRET Study Hypotheses
Primary Hypothesis: The Exercise plus Diet group will have a greater increase in
VO2peak and lose more body weight than the other intervention groups.
Secondary Hypothesis: Patients participating in the exercise interventions (Exercise Only
and Exercise plus Diet) will demonstrate significant increases in objectively
measured physical activity levels compared to the non-exercise groups (Diet Only
and Attention Control).
Tertiary Hypothesis: A significant correlation will be observed between increased
physical activity levels and increased VO2peak but there will not be a significant
relationship observed between changes in physical activity levels and weight loss.
74
APPENDIX D
SECRET Inclusion and Exclusion Criteria
Inclusion Criteria:
HF Clinical Score (>3)
Clinical Variables
Score
Dyspnea/difficulty breathing
Trouble with breathing (SOB)
1
Hurrying on the level or up slight hill
1
At ordinary pace on the level?
2
Do you stop for breath when walking at own pace? 2
Do you stop for breath after 100 yds on the level? 2
Physical Examination
Heart Rate (bpm)
91 to 110
1
111+
2
Rales/Crackles
Either lower lung field
1
Either lower and either upper lung field
2
Jugulovenous Distention
Alone
1
Plus Edema
2
Plus Hepatomegaly
2
75
Chest X-Ray Film
Cephalizaiton of pulmonary vessels
1
Interstitial edema
2
Alveolar Fluid plus Pleural Fluid
3
Interstitial Edema plus Pleural Fluid
3
Normal EF (>50%)
>60 years of age
BMI >30 kg/m2
Exclusion Criteria:
Medical
Valvular heart disease as the primary etiology of CHF
Significant change in cardiac medication <4 weeks
Uncontrolled hypertension as defined according to current JNC guidelines
Uncontrolled diabetes
Evidence of significant COPD; assessment may be made by pulmonary
function test
Recent or debilitating stroke
Cancer or other non-cardiovascular conditions with life expectancy less
than 2 years
Anemia (<11 grams Hgb) determined by CBC
Significant renal insufficiency (creatinine >2.5mg/dl) determined by CMP
Pregnancy-women of child bearing potential are excluded from
76
participation
Psychiatric disease- uncontrolled major psychoses, depressions, dementia, or
personality disorder
Other
Plans to leave area within 1 year
Refuses informed consent
Screening Echocardiogram
Left ventricular ejection fraction < 50%
Significant valvular heart disease
Familiarization/Screening Exercise Test
Evidence of significant ischemia
ECG: 1mm flat ST depression (confirm with echocardiogram wall motion)
Echo: Wall motion abnormality or decrease in global contractility
Stopped exercising due to chest or leg pain or any reason other than
exhaustion/fatigue/dyspnea
Exercise SBP > 240 mmHg, DBP > 110 mmHg
Unstable hemodynamics or rhythm
Unwilling or unable to complete adequate exercise test
Magnetic resonance imaging
Indwelling metal-containing prosthesis (orthopedic, valvular, other)
Pacemaker or defibrillator
History of welding occupation (ocular metal debris)
Uncontrollable claustrophobia
77
Any other contra-indication to MRI
Thigh muscle biopsy
History of bleeding disorder
Current anticoagulation
Contraindication to stopping aspirin for 1 week
Allergy to topical anesthetic
78
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SCHOLASTIC VITA
DANIEL CLEVENGER
PERSONAL INFORMATION
Birthplace:
Birth date:
Muncie, Indiana
June 13, 1986
UNDERGRADUATE STUDY
2005-2010
Ball State University
Muncie, Indiana
B.S. Pre-Medicine and Exercise Science
Minor: Chemistry
GRADUATE STUDY
2010-2012
Wake Forest University
Winston-Salem, North Carolina
M.S. Health and Exercise Science
Advisor: Peter H. Brubaker, Ph.D.
Thesis: “Effects of a Randomized Controlled Trial of Diet and/or
Exercise on Objectively Measured Physical Activity Levels in
Older Heart Failure Patients”
PROFESSIONAL EXPERIENCE
2010-2011
Laboratory Coordinator
Healthy Exercise and Lifestyle Programs (HELPS)
Wake Forest University
Winston-Salem, North Carolina
2010-2012
Action Health’s PLAN Exercise Supervisor
Wake Forest University Baptist Medical Center
Winston-Salem, North Carolina
2009-2011
Research Assistant
Department of Health and Exercise Science
Wake Forest University
Winston-Salem, North Carolina
103
2009-2011
Graduate Teaching Assistant
Department of Health and Exercise Science
Wake Forest University
Winston-Salem, North Carolina
2010-2011
Exercise Supervisor
Healthy Exercise and Lifestyle Programs (HELPS)
Wake Forest University
Winston-Salem, North Carolina
2005
Adult Physical Fitness Program Intern
Clinical Exercise Physiology Program
Ball State University
Muncie, Indiana
PRESENTATIONS
2012
Effects of a Randomized Controlled Trial of Diet and/or
Exercise on Objectively Measured Physical Activity Levels in
Older Heart Failure Patients
ACSM National Conference
San Francisco, California
2010
Pitching Biomechanics and Injuries of the Elbow in Youth
Baseball Players
Wake Forest University
Winston-Salem, North Carolina
MEMBERSHIPS
2009-2013
American College of Sports Medicine
CERTIFICATIONS
2012-2015
ACSM Certified Clinical Exercise Specialist
2010-2012
Adult CPR/AED
104