Download effects of low-intensity exercise conditioning on blood pressure

EFFECTS OF LOW-INTENSITY EXERCISE CONDITIONING ON BLOOD
PRESSURE, HEART RATE, RATE-PRESSURE-PRODUCT AND CARDIAC
AUTONOMIC FUNCTION IN HYPERTENSIVE WOMEN
by
CATHERINE LINDSAY BAINES
A thesis submitted to the School of Nursing
in conformity with the requirements for
the degree of Master of Science
Queen‘s University
Kingston, Ontario, Canada
September 2008
Copyright © Catherine Lindsay Baines, 2008
ii
ABSTRACT
The effects of a twelve-week low-intensity exercise conditioning program on
blood pressure (BP), heart rate (HR), rate-pressure-product (RPP) and cardiac autonomic
function were examined in menopausal and post menopausal women with hypertension.
Eligible participants (n=50) were counterbalanced to either the exercise group or the
control group. Using a pretest-posttest design, participants were tested at the beginning
and the end of the 12-week study period, in which BP, HR, RPP, heart rate variability and
spontaneous baroreflex sensitivity were measured at rest and during standing and low
intensity steady-state exercise. The exercise group participated in a 12-week, lowintensity walking program, 5 days/week, while the comparison group continued with
usual activity. The exercise group adhered to 4 walking sessions per week while the
control group averaged 0.6 walking sessions per week. Repeated measures analysis of
variance (ANOVA) demonstrated a reduction in systolic and diastolic BP and RPP in
hypertensive women. Additionally, the low intensity exercise conditioning program
attenuated the physiological response to stress (standing, exercise). This was evidenced
by decreased systolic and diastolic BP and RPP in the exercise group and increased
diastolic BP in the control group. Postmenopausal women demonstrated decreased log
transformed high frequency power and total power in comparison to menopausal women.
However, postmenopausal women also showed decreased low frequency power in
comparison to menopausal women. It was concluded that a 12-week, low-intensity
exercise conditioning program reduced systolic and diastolic BP and RPP in hypertensive
women while attenuating their physiological responses to stress.
iii
ACKNOWLEDGEMENT
I would like to express my sincere gratitude to Dr Ann Brown for her guidance
and support throughout this project. Ann, I truly appreciate the time you spent helping me
develop my skills as a researcher; your supervision and attention to detail has allowed
me to gain a solid foundation for my career in research to be built upon. This project
could not have been accomplished without the patience and dedication of Dr Sylvia
Hains. Sylvia, thank you for your teaching in statistics; you‘re help was invaluable. The
success of this study is also credited to my committee; Dr Barbara Kisilevsky and Dr
Richard Birtwhistle. Thank you for donating your time, knowledge and experience to this
endeavor.
I am most grateful to the women who participated in this study. Their dedication
and unwavering will to walk through all of natures elements enabled our pursuit of
knowledge. Many women came from far and wide and sacrificed their time and energy in
the spirit of true volunteerism.
On a more personal note, I would like to thank my family for believing in me
throughout my academic career. I would not be enjoying all of my successes without
their perseverance. I am greatly appreciative to my classmates and close friends whose
friendship and support carried me through the last two years. And last but certainly not
least, my boyfriend Craig, thank you for your savvy computer skills in addition to your
continuous love and support.
iv
TABLE OF CONTENTS
Abstract……………………….…………………………………………………………...ii
Acknowledgement……………………………………………………………………..…iii
Table of Contents…………………………………………………………………………iv
List of Tables…………………………………………………………………………....viii
List of Figures………………………………………………………………………….....ix
List of Abbreviations…………………………………………………………………….xii
CHAPTER ONE
Introduction………………………………………………………………………..1
CHAPTER TWO
Literature Review……………………………………………………………………….…3
Cardiovascular Disease……………………………………………………………3
Hypertension……………………………………………………………………....3
Regulation of Heart Rate and Blood Pressure…………………………………….5
Autonomic Regulation of Heart Rate……………………………………………..7
Heart Rate Variability……………………………………………………………..8
Measurement of Heart Rate Variability…………………………………………...9
Arterial Baroreflex……………………………………………………………….12
Measurement of Arterial Baroreflex……………………………………………..13
Physiological Factors Which Effect Cardiac Autonomic Function.......................16
v
Hypertension……………………………………………………………..16
Aging……………………………………………………………………..18
Gender……………………………………………………………………19
Menopause……………………………………………………………….20
Body Posture……………………………………………………………..21
Respiratory Rate…………………………………………….……………22
Antihypertensive Medications…………………………………………...25
Acute Exercise…………………………………………………………...26
Effects of Exercise Conditioning on the Cardiac Autonomic Nervous System....27
Relevant Work by Other Investigators at Queen‘s University………………..…30
Exercise Adherence……………………………………………………………...32
Rationale and Hypothesis……………………………………………………..…34
Rationale………………………………………………………………....34
Hypothesis………………………………………………………………..35
CHAPTER THREE
Method…………………………………………………………………………...36
Participants……………………………………………………………….36
Equipment and Instruments……………………………………………...38
Procedure………………………………………………………………...42
Data Analysis…………………………………………………………….47
Analysis of Heart Rate Variability……………………………….47
Analysis of Baroreflex Sensitivity……………………………….48
Statistical Analysis……………………………………………………….49
vi
CHAPTER FOUR
Results……………………………………………………………………………51
Demographic, Physiological and Lifestyle Measures……………………51
Antihypertensive Medications…………………………………………...53
BpTRU Blood Pressure and Heart Rate Measures over Time…………...54
BpTRU Systolic Blood Pressure…………………………………54
BpTRU Diastolic Blood Pressure………………………………..56
BpTRU Heart Rate……………………………………………….58
BpTRU RPP……………………………………………………...59
Comparison of Body Mass Index and Waist Circumference over Time...62
Heart Rate Variability Measures…………………………………………63
Low Frequency Power…………………………………………...65
High Frequency Power………………………………………..…67
Total Power………………………………………………………69
PNS Indicator…………………………………………………….70
SNS Indicator…………………………………………………….72
Baroreflex Measures…………………………………………………..…76
Baroreflex Slope…………………………………………………78
Systolic Finapres Arterial Blood Pressure……………………….79
R-R Interval……………………………………………………...81
Exercise Compliance…………………………………………………….84
CHAPTER FIVE
Discussion………………………………………………………………………..85
Conclusions………………………………………………………………94
vii
REFERENCES…………………………………………………………………………..96
APPENDIX A
Research Information Consent Form…………………………...131
APPENDIX B
Physical Activity Readiness Questionnaire………...…………..135
APPENDIX C
Measuring Your Pulse and Your Target Heart Rate……………137
APPENDIX D
Borg‘s Rating of Perceived Exertion Scale…………………….138
APPENDIX E
Walking Protocol……………………………………………….139
APPENDIX F
Exercise Log……………………………………………………140
APPENDIX G
Activity Log…………………………………………………….141
APPENDIX H
Study Advertisement……………………………………………142
APPENDIX I
Demographic and Data Form…………………………………...143
APPENDIX J
Editing Heart Rate Variability Data…………………………….144
APPENDIX K
Editing Spontaneous Baroreflex Sensitivity Data………………146
APPENDIX L
Means (±SD) for BpTRU Systolic and Diastolic Blood Pressure,
Heart Rate and Rate-Pressure-Product in Both Control and
Exercise Group at Week 1 and Week 12 .……………………...147
APPENDIX M
Means (±SD) for Log Transformed Heart Rate Variability
Measures for Both Control and Exercise Group at Week 1 and
Week 12 ………………………………………………………..148
APPENDIX N
Means (±SD) for Spontaneous Baroreflex Measures for Both
Control and Exercise Group at Week 1 and Week 12………….150
APPENDIX O
Summary of Study Sample and Reasons for Attrition………….151
APPENDIX P
Other Demographic Data at Baseline Testing………………….152
APPENDIX Q
Chi-squared/ANOVA Summary Tables……………..…………153
viii
LIST OF TABLES
Table 1
Means (±SD) for demographic, physiological and lifestyle measures at
week 1……………………………………………………………………52
Table 2
Antihypertensive medication classification……………………………...53
Table 3
Means (±SD) for log transformed heart rate variability measures at week
1………………………………………………………………………….64
Table 4
Means (±SD) for spontaneous baroreflex sensitivity measures at week 1
……………………………………………………………………………77
ix
LIST OF FIGURES
Figure 1
Study Design……………………………………………………………..42
Figure 2
Mean systolic blood pressure as a function of time for the control and
exercise group……………………………………………………………55
Figure 3
Mean systolic blood pressure in three conditions for the control and
exercise group……………………………………………………………55
Figure 4
Mean diastolic blood pressure as a function of time for the control and
exercise group……………………………………………………………57
Figure 5
Mean diastolic blood pressure in three conditions for the control and
exercise group……………………………………………………………57
Figure 6
Mean heart rate in three conditions for week 1 and week 12…………..58
Figure 7
Mean Rate-Pressure-Product as a function of time for the control and
exercise group……………………………………………………………60
Figure 8
Mean Rate-Pressure-Product in three conditions for the control and
exercise group……………………………………………………………60
Figure 9
Mean body mass index as a function of time for the control and exercise
group…………………………………………………………………… .62
x
Figure 10
Mean of the log transformed low frequency power in three conditions as a
function of time…………….…………………………………………….66
Figure 11
Mean of the log transformed low frequency power as a function of
menopausal state…………………………………………………………66
Figure 12
Mean of the log transformed high frequency power in three conditions for
the control and exercise group…………………………………………...68
Figure 13
Mean of the log transformed high frequency power as a function of
menopausal state for the control and exercise group…………………….68
Figure 14
Mean of the log transformed total power as a function of menopausal
state………………………………………………………………………69
Figure 15
Mean of the log transformed PNS Indicator in three conditions for the
control and exercise group……………………………………………….71
Figure 16
Mean of the log transformed PNS Indicator in three conditions for
menopausal and postmenopausal women…………………………….71
Figure 17
Mean of the log transformed SNS Indicator in three conditions for the
control and exercise group…………………………………………….…72
Figure 18
Mean of the log transformed SNS Indicator in 3 conditions as a function
of menopausal state for a) control group and b) exercise group………....74
xi
Figure 19
Mean baroreflex slope in three conditions for the control and exercise
group……………………………………………………………………..78
Figure 20
Mean systolic Finapres arterial blood pressure in three conditions as a
function of time………………………………………………………….80
Figure 21
Mean systolic Finapres arterial blood pressure in three conditions for the
control and exercise group……………………………………………….80
Figure 22
Mean R-R interval in three conditions for the control and exercise group
…………………………………………………………………………....81
Figure 23
Mean R-R interval in 3 conditions as a function time for a) menopausal
women and b) postmenopausal women……………………………........ 83
xii
Abbreviations
HR
Heart Rate
BP
Blood Pressure
PNS
Parasympathetic Nervous System
SNS
Sympathetic Nervous System
HRV
Heart Rate Variability
SBR
Spontaneous Baroreflex
PSD
Power Spectral Density
VLF
Very Low Frequency
LF
Low Frequency
HF
High Frequency
FFT
Fast Fourier transform
TP
Total Power
1
CHAPTER ONE
Introduction
It is estimated that a Canadian dies from heart disease or stroke every seven
minutes (Heart and Stroke Foundation of Canada [HSFC], 2008). Although the rate of
heart disease and stroke are declining, they remain the leading causes of death and
disability in Canada (HSFC, 2007). The incidence of cardiovascular disease increases
with age and is exaggerated during menopause (Rosano & Panina, 1999). Hypertension
increases the risk of developing cardiovascular disease by three fold (HSFC, 2008). After
45 years of age, one out of every three Canadians has high blood pressure; with a higher
proportion of women affected than men.
Hypertension can cause damage to the heart, blood vessels and autonomic
nervous system. Hypertensive individuals experience increased sympathetic and
decreased parasympathetic cardiac modulation, reduced baroreflex sensitivity and
enhanced vasomotor sympathetic modulation (Julius & Majahalme, 2000; Pagani &
Lucini, 2001; Souza, Ballejo, Salgado, Da Silva & Salgado, 2001). These factors are
detrimental because they decrease an individual‘s ability to maintain blood pressure
within a normal range, react to stressful stimuli and avoid cardiovascular injury (stroke,
heart disease and death). Autonomic balance is further compromised as women transition
though menopause. Menopause causes the protective effect of estrogen to become
attenuated and there is increased sympathetic and decreased parasympathetic modulation
of the heart and decreased R-R interval (Farag, Bardwell, Nelesen, Dimsdale & Mills,
2003; Rosano & Panina, 1999).
2
Exercise conditioning is known to lower blood pressure and improve autonomic
function in hypertensive women (Davy, Willis & Seals, 1997; Whelton, Chin, Xin & He,
2002). Exercise is commonly recommended at high- or moderate-intensity to reduce
blood pressure (Cleroux, Feldman & Petrella, 1999; Parati & Lantelme, 2005). However,
high-intensity exercise can be harmful as it increases sympathetic activity and BP which
could result in cardiovascular injury such as stroke or sudden death. If low-intensity
exercise offers comparable cardiovascular benefits without increasing plasma
catecholamines it would be advantageous. Low-intensity exercise does not put an
individual at risk for injury as there are no drastic fluctuations in sympathetic activity or
BP (Brown, Wolfe, Hains, Pym and Parker, 1994). Walking has been found to be a
suitable low intensity exercise that is recommended for hypertensive individuals (Lesniak
& Dubbert, 2001).
The purpose of this study was to test the effects of a low-intensity exercise
conditioning intervention on heart rate, blood pressure, heart rate variability and
baroreflex sensitivity in hypertensive women. This study will aim to address the
following research questions:
1. What are the effects of a 12 week low intensity exercise conditioning program
on blood pressure, heart rate, rate-pressure-product and cardiac autonomic
function in women with hypertension?
2. How does menopausal state influence blood pressure, heart rate, rate-pressureproduct and cardiac autonomic function in women with hypertension?
3
CHAPTER TWO
Literature Review
Cardiovascular Disease
Cardiovascular disease is a major cause of illness, disability and death in Canada.
The cardiovascular system consists of the heart, the blood and the blood vessels (arteries,
veins, capillaries) throughout the body and within the brain. The function of this system
is to move oxygen and metabolites to and from cells for the purpose of maintaining
internal homeostasis. The Heart and Stroke Foundation of Canada (HSFC) (2007) defines
cardiovascular disease as any injury of the heart, the blood vessels of the heart or the
peripheral blood vessels. Many Canadians have a high prevalence rate of the major risk
factors for cardiovascular disease: smoking, physical inactivity, high blood pressure
(hypertension), dyslipidemias, obesity, and diabetes. There is a disparity in risk factors
that exist among men and women, various age groups and between different geographical
regions of the country. The Heart and Stroke Foundation of Canada (1999) recommends
that available resources be targeted at individuals and communities in order to help
reduce risk factors for heart disease and stroke.
Hypertension
Hypertension is defined as blood pressure (BP) that is chronically high (more than
or equal to 140/90 mm Hg). BP is a measure of the force that blood exerts against the
walls of arteries. The numerator represents the highest pressure as the heart contracts and
pushes blood out (systolic) and the denominator is the lowest pressure when the heart
4
relaxes between beats (diastolic) (HSFC, 2007). The Canadian Hypertension Education
Program (2007) defines hypertension as mild (140-159 / 90-99 mmHg), moderate (160179 / 100-109) and severe (>180 / >110). The risk of being diagnosed with hypertension
increases with age (Wolf-Maiser, Cooper, Banegas, 2003). It is anticipated that 90% of
individuals will suffer from the disease at some point in their life due to lifestyle patterns.
Hypertension can cause serious cardiovascular consequences including stroke, ischemic
heart disease, myocardial infarction, congestive heart failure, peripheral vascular disease,
renal failure, impotence, left ventricular hypertrophy and left ventricular diastolic
dysfunction (Esler & Kaye, 2000; HSFC, 2007; Piccirillo, Germano, Vitarelli, Ragazzo,
di Carlo, De Laurentis et al., 2006). Untreated hypertension ultimately results in death.
Hypertension signifies a huge public health burden and efforts should be directed at
primary prevention (Vasan, Beiser, Seshadri, Larson, Kannel, D'Agostino et al., 2002).
There are three common types of hypertension. Essential hypertension constitutes
90-95% of cases and is considered idiopathic. Secondary hypertension is responsible for
5-10% of cases are instigated by underlying renal (acute glomerulonephritis, chronic
renal disease, polycystic disease, renal artery stenosis, renal vasculitis, renin-producing
tumors), endocrine (adrenocortical hyperfunction, exogenous hormones,
pheochromocytoma, acromegaly, hyperthyroidism, hypothyroidism, pregnancy induced),
cardiovascular (coarctation of the aorta, polyarteritis nodosa, increased intravascular
volume/output, rigidity of the aorta) and neurologic (psychogenic, increased intracranial
pressure, sleep apnea, acute stress) causes. Malignant hypertension is less common and is
accountable for 5% affected individuals. It is characterized by rapidly rising BP which
leads to death within two years if untreated (Cotran, Kumar, Collins, 1999).
5
Regulation of Heart Rate and Blood Pressure
BP is directly determined by two elementary hemodynamic principles: cardiac
output and total peripheral resistance. Cardiac output is the product of heart rate (HR)
multiplied by stroke volume and represents the total amount of blood ejected from the
heart per minute. It is influenced by cardiac contractility and venous return. Total
peripheral resistance is the cumulative resistance of all peripheral vasculature and
dependent on arteriole lumen size. Lumen size is determined by neural and hormonal
influences which cause vasoconstriction and vasodilatation (Cotran, Kumar, Collins,
1999). Hypertension is exemplified by high peripheral vascular resistance and reduced
cardiac output (Sowers & Lester, 2000).
BP control can be understood at a more multifaceted level by investigating the
effect the nervous system has on regulation. There are two components of the nervous
system, the first is the central nervous system which consists of the brain and spinal cord
which integrate incoming afferent information and determine if an efferent response is
necessary. The second is the peripheral nervous system which is comprised of exposed
nerves which branch out from the spinal cord and innervate different regions of the body.
The peripheral nervous system is divided into the somatic nervous system and the
autonomic nervous system. The somatic nervous system controls conscious body
movements through perception of external stimuli and efferent control of skeletal muscle.
The autonomic nervous system is predominantly made up of efferent nerves which
transmit impulses from the central nervous system to peripheral organ systems for the
purpose of maintaining homeostasis without conscious control. The autonomic nervous
6
system is responsible for control of HR, force of cardiac contraction, constriction
/dilatation of blood vessels, contraction and relaxation of smooth muscle in various
organs, visual accommodation, pupillary size and secretions from exocrine and endocrine
glands (Cotran, Kumar, Collins, 1999).
The autonomic nervous system is subdivided into the parasympathetic nervous
system (PNS) and the sympathetic nervous system (SNS). The vagus nerve is the origin
of all parasympathetic nerve fibers and the only cranial nerve that starts in the brainstem
and extends into the abdomen. The vagus nerve is made up of motor neurons that begin
in the medulla oblongata (in cells that lie in the nucleus ambiguous) and travel alongside
the carotid arteries into the thorax where they synapse with the sinoatrial (SA)
/atrioventricular (AV) nodes and atrial muscle. The right vagi innervates SA node firing
while the left innervates AV node conduction (Malik & Camm, 1995). Sympathetic
motor neurons originate in the intermediolateral columns of the spinal cord (C1-C2, T1T5), synapse with paravertebral chains of ganglia and join with PNS fibers to form a
plexus of cardiac nerves which stimulate the heart. Sympathetic postganglionic fibers
innervate the SA/AV node and the atrial and ventricular myocardium (Batulevicius,
Skripka, Pauziene & Pauza, 2008; Malik & Camm, 1995).
The SNS is well known for the sympatho-adrenal response it exhibits to
accelerate HR. The PNS acts to slow HR. The SNS and PNS are antagonists of each other
and have reciprocal actions. HR is determined by the rate of depolarization of the
sinoatrial (SA) node. It represents the net effect of sympathetic and parasympathetic
innervation. In a resting state, the SNS and PNS are both active but the PNS is dominant.
7
If there were no PNS influence, the SNS would prevail and intrinsic HR would exceed
100 beats per minute. The average resting adult HR is 70 beats per minute when it is
mediated by the PNS (Berne & Levy, 2001).
Both divisions of the autonomic nervous system use neurotransmitters for
synaptic communication in order to produce a chronotropic effect. The PNS is mediated
by acetylcholine, which travels from the vagus nerve to muscarinic receptors in the SA
node in order to inhibit cardiac pacemaker activity and slow HR. HR is effected
immediately (<400ms) by vagal stimulation/withdraw (Batulevicius et al., 2008; Malik &
Camm, 1995). This is attributed to the enzyme cholinesterase. The SA and AV nodes are
rich in cholinesterase and acetylcholine is rapidly hydrolyzed by it. The brief latency and
prompt decay of acetylcholine allow the PNS to control HR on a beat-to-beat basis. The
SNS takes longer (3-5s) to elicit a change as it is mediated by norepinephrine.
Norepinephrine binds to beta adrenergic receptors in the SA node to accelerate HR. This
response is too slow to exert beat-by-beat control of HR (Malik & Camm, 1995; Pelosi,
Tavares, Antunes-Rodrigues & Correa, 2008; Silverthorn, 2001).
Autonomic Regulation of Heart Rate
Hypertensive individuals experience impairment of the autonomic nervous
system. Autonomic deregulation is manifested through increased sympathetic and
decreased parasympathetic activity, increased vasomotor sympathetic tone, reduced
spontaneous baroreflex sensitivity (SBR) and reduced heart rate variability (HRV).
Sympathetic over activity is enabled by vagal withdrawal which causes acute and chronic
episodes of BP elevation (Guyenet, 2006; Souza, Ballejo, Salgado, Da Silva & Salgado,
8
2001). After parasympathetic withdrawal, HR is immediately affected followed by an
ensuing change in BP. This sequence of events happens because SNS activity increases
either moderately or completely (Dabrowska, Dabrowski & Skrobowski, 1996; Lewis,
2005; Ohisa, Hashimoto, Yoshida, Imai & Kaku, 2005; Thayer & Lane, 2007). The
distinctive increase in sympathetic drive is widespread across many organs. It is evident
in the heart, the kidneys and in skeletal muscle (Julius & Majahalme, 2000). Reduced
SBR sensitivity also is evident in hypertensive individuals. With increasing BP, the
arterial baroreflex is strained and forced is reset to function outside of normal parameters.
There is consequential diminished vagal influence and a subsequent increase in
sympathetic outflow to the heart and resistance vessels (Labrova, Honzikova, Maderova,
Vysocanova, Novakova, Zavodna, et al., 2005; Myredal, Gao, Friberg, Jensen, Larsson &
Johansson, 2005; Prakash, Madanmohan, Sethuraman & Narayan, 2005). Aging and
thickening of the carotid wall also are associated with an attenuation of the baroreflex
(Parati & Lantelme, 2005).
Heart Rate Variability
HRV is a measure of the beat-to-beat changes in HR and a useful non-invasive
tool to assess short term autonomic control. In healthy individuals, the rhythmic beating
of the heart at rest is not uniform; there is oscillation in the interval between consecutive
heartbeats. This oscillation can be characterized by a variability of 10% of the mean
(Malik & Camm, 1995). Synergistic fluctuations in HR occur on a beat-by-beat basis,
adjusted by efferent parasympathetic and sympathetic output to the sinoatrial node. HRV
is a vital mechanism for achieving flexibility in cardiovascular responses to rapid and
9
unpredictable internal and external stimuli. It can be used as a predictor of mortality after
cardiovascular injury since decreased HRV is linked to the incidence of cardiac
arrhythmias. Loss of HRV occurs in certain pathological conditions before sudden death
(Akselrod, Gordon, Madwed, Snidman, Shannon & Cohen, 1985; Akselrod, Gordon,
Ubel, Shannon, Berger & Cohen, 1981; Goldberger, 1991).
Measurement of Heart Rate Variability
HRV can be enumerated by using an electrocardiogram (ECG) to measure beatto-beat changes in HR from one cardiac cycle to the next. The time interval between two
ventricular contractions, the R-R interval, is the primary measure and can vary on a beatto-beat basis. The R-R interval provides a noninvasive quantitative method for
investigating the dynamic influence of changing physiological parameters on cardiac
regulation. Measurement of HRV has been standardized in order to establish consistent
nomenclature/definitions, standard methods of measurement and to define physiological
correlates and appropriate clinical applications (Task Force of the European Society of
Cardiology and the North American Society of Pacing and Electrophysiology
(TFESCNASPE), 1996).
HRV can be evaluated in two domains; time domain and frequency domain. To
measure HRV in a time domain, the interval between ventricular contractions (QRS
interval) is measured over time (ms) and plotted on a tachogram. The time domain
method calculates the peak-to-peak value of the R-R interval directly from a time sample.
Measurements are reported as a mean, standard deviation or compared at different times
10
of the day. It is commonly used for long-term recordings of HRV (24 hours) and
occasionally for short-term recordings (2-5 minutes).
The frequency domain method or power spectral density (PSD) illustrates how
variance between R-R intervals distributes as a function of frequency. It is used for short
and long term recording and has been chosen for use in this study as it is a more
appropriate means for measurement of HRV (Lewis, 1995). The frequency domain
method converts the R-R interval data from the time domain to the frequency domain by
a Fast Fourier transform (FFT). FFT can plot the relative energy of different frequency
components of HRV. It is based on the Fourier theorem which asserts that any signal can
be expressed as a sum of an infinite set of sine and cosine functions. FFT breaks down
periodic oscillations of R-R interval into fundamental sinusoidal components which are
then transformed into a graphic format to serve as an estimation of HRV spectra. A
periodogram is produced to estimate the power spectrum of a signal and is referred to as
‗‗power spectral density‘‘ (PSD). PSD describes the power content of a signal in a very
narrow frequency range. The segment spectra are then averaged (Freeman, Dewey,
Hadley, Myers & Froelicher, 2006; Lewis, 2005; Pichon, Roulaud, Antoine-Jonville, de
Bisschop & Denjean, 2006; Yamamoto, Hughson & Peterson, 1991).
There are two methods for calculating PSD, nonparametric and parametric. The
nonparametric method is more widely used as it is a simple algorithm (FFT) and fast to
process. Parametric tests can be used on a small sample, offer smoother spectral
components which can be distinguished independently of the selected frequency bands
but are complex calculations that require verification of suitability. The effect of
11
respiration, head tilt, valsalva maneuver or pharmacological intervention can be seen in
both domains and methodologies (TFESCNASPE, 1996).
Mathematical algorithms are then used to generate an interval tachogram which
display three types of frequencies that reflect autonomic modulation on the SA node;
very low frequency (VLF), low frequency (LF) and high frequency (HF)
(TFESCNASPE, 1996). Frequencies are classified by a specific power spectrum and are
expressed in absolute values of power (ms). VLF is characterized by less than 0.04 Hz,
LF signifies 0.04-0.15 Hz and HF corresponds to 0.15-.5 Hz (TFESCNASPE, 1996). HF
symbolizes parasympathetic activity and reflects vagal mediation of HR and respiratory
sinus arrhythmia. HF is associated with more efficient cardiac autonomic control
mechanisms (Akselrod et al., 1981; Manfrini et al., 2008). There is disagreement over the
interpretation of LF; it has been argued to be a distinct indicator of sympathetic activity
(Kamath, Fallen & McKelvie, 1991; Lewis, 2005; Rimoldi, Pagani, Piazza, Pagani, &
Malliani, 1994) and also hypothesized to represent both sympathetic and parasympathetic
contribution (Akselrod et al., 1981; Pichot, Roche, Gaspoz, Enjolras, Antoniadis, Minini,
et al., 2000). The dual influence is believed to be attributable to the arterial baroreflex
which triggers fluctuations in HR through vagally-mediated innervation within the range
0.08-0.12 Hz (Magosso, Biavati & Ursino, 2001). LF can be used within several ratios to
gain further insight into sympatho-vagal balance. LF/HF ratio serves as an index of
sympathetic activity and HF/TP (total power) is used as a measure of PNS activity. TP is
mathematically equal to the sum of the variance of the spectral analysis (Milicevic, 2005;
Pichot et al., 2000; TFNESCASPE, 1996). VLF component is not evaluated in this study
12
as it is a poorly understood physiological measure and not recommended for short term
data recordings (TFNESCASPE, 1996).
Arterial Baroreflex
Healthy individuals experience BP and HR oscillations on a beat-by-beat basis
(Blaber, Yamamoto & Hughson, 1995). The arterial baroreflex adjusts the short term
regulation of BP through the autonomic nervous system. It is a negative feedback system
to maintain arterial BP within a normal range by altering autonomic neural outflow in
order to prevent excessive rise or fall and preserve homeostasis. The arterial
baroreceptors are unencapsulated free nerve endings located in the aortic arch and carotid
sinus which can simultaneously detect either an increase or decrease in arterial BP by
sensing mechanical distension of the blood vessel walls. The autonomic nervous system
responds by sending impulses via the afferent fibers to the nucleus of the tractus solitarius
(NTS) and a complex wiring system ending in the nucleus ambiguus and ventrolateral in
the medulla of the brain stem in order to return arterial BP to the established central
nervous system operating point. An increase in BP alerts the arterial baroreflex to
increase afferent neural impulses to inhibit the SNS and stimulate the PNS. Efferent
autonomic nerve fibres transmit signals to the heart and blood vessels to decrease HR,
cardiac output and systemic vascular resistance. A decrease in BP results in a diminution
of impulses sent to the NTS causing excitation of the SNS and impedance of the PNS.
This leads to an increase in HR and cardiac output (Dampney, 1994; Hainsworth, 1996;
Raven, Fadel & Smith, 2002; Smit, Wieling & Karemaker, 1996).
13
The arterial baroreflex functions around a higher operating point during exercise
and then is reset to its habitual level at the end of activity due to increased central blood
volume (Ogoh, Fisher, Fadel & Raven, 2007). Resetting of the baroreceptors is an
essential property that occurs after a sustained stimulus and is proportional to exercise
intensity; the response may be acute (30 sec - 30 min) or chronic (complete resetting) and
is regulated by the central nervous system. Baroreceptor resetting does not change the
slope of the reflex; it shifts the curve horizontally rightward (Iellamo, Legramante,
Raimondi & Peruzzi, 1997; Joyner, 2006; Raven et al., 2002). Acute resetting occurs in
response to acute exercise. Chronic resetting requires prolonged pressure changes from
months to years; this may be accomplished with participation in a sustained exercise
program (Hainsworth, 1996; Iellamo, Legramante, Massaro, Raimondi & Galante, 2000;
Shi, Schaller, Tierney, Chanthavong, Chen, Raven et al., 2008).
Baroreflex failure arises when afferent baroreceptors become impaired and lose
their buffering ability. There is a resultant widening of pulse pressure and labile HR.
Baroreflex failure can result in hypertensive crisis, volatile hypertension, orthostatic
tachycardia or malignant vagotonia (Ketch, Biaggioni, Robertson & Robertson, 2002).
Measurement of Arterial Baroreflex
Arterial baroreceptors are responsible for rapid reflex BP responses by adjusting
HR and total peripheral resistance through the autonomic nervous system. SBR
sensitivity is the degree to which a change in arterial BP elicits a response in HRV. There
can be a slight time delay (lag) between a change in SBP and a subsequent variation in RR interval. The lag in baroreflex response time varies between zero and two heart beats. It
14
is assumed that SBR sensitivity is predominantly a measure of parasympathetic activity
due to the beat-by-beat control it exerts on HR. SBR sensitivity is used to quantify the
vagal component of the baroreflex (Blaber et al., 1995; Schrezenmaier, Singer, Swift,
Sletten, Tanabe & Low, 2007). SBR sensitivity is influenced by age and gender and is
significantly diminished in individuals who suffer from hypertension (Laitinen,
Hartikainen, Vanninen, Niskanen, Geelen & Lansimies, 1998).
There are three distinct techniques to assess SBR sensitivity; intravenous
administration of vasoactive medication, direct stimulation of the carotid baroreceptors
with a neck chamber device or by spontaneous baroreflex method. Vasoactive drug
administration provokes the baroreceptor response by sequential intravenous bolus
injections of nitroprusside (depressor) and phenylephrine (pressor) to cause an acute
increase or decrease in arterial BP. This pharmacological method causes an abrupt
aberrant change in the speed and intensity of the BP response that does not precisely
mimic normal physiology (Parlow, Viale, Annat, Hughson & Quintin, 1995; Rudas,
Crossman, Morillo, Halliwill, Tahvanainen, Kuusela et. al, 1999). Use of the noninvasive neck chamber to assess carotid baroreflex by neck suction or neck pressure is
another useful tool to assess SBR sensitivity. The application of neck pressure via a rigid
collar emulates a hypotensive state as it compresses the carotid baroreceptors and causes
a decrease in carotid sinus transmural pressure. The application of neck suction stretches
the carotid baroreceptors creating a simulated hypertensive state as carotid sinus
transmural pressure increases (Fadel, Ogoh, Keller & Raven, 2003). The spontaneous
baroreflex method is used to analyze parasympathetic innervation of the heart after BP
fluctuation. BP and HR are two physiological variables that are interconnected by the
15
actions of the baroreflex. The spontaneous baroreflex method analyzes BP by using a
computer to scan recordings of continuous finger arterial BP and ECG tracings to locate
sequences in which BP spontaneously increases or decreases with parallel changes in
cardiac intervals (Eckberg, 1980; Parlow et. al, 1995).
Each method for testing SBR sensitivity has advantages and disadvantages for
particular patient populations and study resources. The use of vasoactive medications can
be advantageous as they allow investigators to discriminate between resetting of the
baroreflex and changes in sensitivity. However, they are not appropriate in all clinical
situations as they are fast acting potent stimuli that can cause dangerous perturbations in
systolic BP and R-R interval. Another issue arises in the application of the vasoactive
agent. The delivery of chemical vasopressors and vasodilators does not imitate the natural
baroreflex response time accurately. Each injection is given over several seconds and the
effect of the medication is influenced by the rate of administration (Eckberg, 1980;
Parlow et. al, 1995). The application of neck pressure or suction can cause adverse
reactions such as syncope or unsafe elevations in BP (Raine & Cable, 1999). This study
deemed the spontaneous baroreflex method to be the most appropriate technique for
assessing SBR sensitivity as it has several obvious advantages over other methods while
producing replicable values. The spontaneous baroreflex method is non-invasive, reliable
and able to measure SBR sensitivity within a normal physiological range. It allows the
investigator to obtain a true steady-state assessment while the participant is studied in
various conditions such as at rest, standing and during exercise (Parlow et. al, 1995).
16
The spontaneous baroreflex method generates data that can be analyzed by either
the sequence method or by spectral analysis. The investigators of the present study opted
to use the sequence method since it has been found to yield quantitatively similar results
to spectral analysis methods (Hughson, Quintin, Annat, Yamamoto & Gharib, 1993). The
sequence method detects spontaneous sequences of three or more heart beats in which
systolic BP and R-R interval simultaneously change in the same direction. The sequences
are then analyzed by computer software which uses linear regression to calculate the
slope of each series. The mean slope is used to quantify SBR sensitivity; an increase in
the baroreflex slope is associated with greater parasympathetic innervation whereas a
decrease in slope is linked to reduced vagal stimulation (Blaber et al., 1995; Hughson et
al., 1993; La Rovere, Bersano, Gnemmi, Specchia & Schwartz, 2002; Parlow et. al,
1995).
Measuring HRV and SBR sensitivity are safe, reliable approaches to evaluating
cardiac autonomic balance (Amara & Wolfe, 1998). However, these methods are
susceptible to various factors which have influential effects on their measurement. These
factors include hypertension, aging, gender, menopause, body posture, respiratory rate,
antihypertensive medications and acute exercise.
Physiological Factors Which Effect Cardiac Autonomic Function
Hypertension. Impairment of the autonomic nervous system is the hallmark of
essential hypertension and apparent when evaluating HRV and SBR sensitivity in
hypertensive patients. Hypertension is distinguished by an imbalance of sympatho-vagal
function; this is evidenced by increased sympathetic and decreased parasympathetic
17
cardiac modulation with enhanced vasomotor sympathetic innervations (Julius &
Majahalme, 2000; Liao, Cai, Barnes, Tyroler, Rautaharju, Holme et al., 1996; Pagani &
Lucini, 2001; Piccirillo, Germano, Vitarelli, Ragazzo, di Carlo, De Laurentis, et al., 2006;
Souza et al., 2001). Power spectral analysis of ECG recordings reveals that hypertensive
individuals experience low HRV (decreased R-R interval fluctuations) and prolonged QT
intervals. This is attributable to increased LF power (sympathetic innervation) and
reductions in HF power (parasympathetic innervation). Consequently, low to high
frequency ratio, HF power and TP are also reduced (Kaftan & Kaftan, 2000; Kosch,
Hausberg, Barenbrock, Kisters & Rahn, 1999; Passino, Franzoni, Gabutti, Poletti, Galetta
& Emdin, 2004). Decreased vagal function is associated with an increased risk for
morbidity and mortality (Thayer & Lane, 2007). In addition to this, rate-pressure product
[(HR x BP) x 10-2)] is increased in hypertensive patients. Rate-pressure-product (RPP) is
an estimate of myocardial oxygen consumption and gives an indication of the amount of
oxygen demanded by the heart. A normal value is less than 12 ml blood /100g LV/min
(Gobel, Norstrom, Nelson, Jorgensen & Wang, 1978; Pepper & Crawley, 1985; Prakash
et al., 2005).
The ability of the cardiovascular system to maintain BP within a normal range is
further compounded by the effect of hypertension on the arterial baroreflex. The
baroreflex is strained by high BP and forced to reset its sensitivity to a higher operating
point. This is due to diminished vagal modulation and amplified sympathetic innervation
to the heart and resistance vessels. The slope of the baroreflex decreases with increasing
BP (Parati & Lantelme, 2005; Prakash et al., 2005). High BP cultivates carotid wall
thickness which further decreases SBR sensitivity (Labrova et al., 2005). Autonomic
18
dysregulation is evident in the early stages of hypertension and is exaggerated as the
condition worsens (Singh, Larson, Tsuji, Evans, O'Donnell & Levy, 1998). Therefore, the
degree of BP elevation is proportional to the severity of autonomic impairment (Mussalo,
Vanninen, Ikaheimo, Laitinen, Laakso, Lansimies et al., 2001).
Aging. Increasing age hinders the autonomic nervous system in healthy
normotensive and hypertensive individuals. As a function of age, the cardiovascular
system gradually loses its ability to regulate HR on a beat-by-beat basis. Structural and
functional changes in autonomic nerves, ganglia, heart and blood vessels are responsible
for this change. There is ensuing impairment of left ventricular filling, increased afterload
and diminished intotropic and chronotropic responses to catecholamines (Spina, 1999;
Shimazu, Tamura & Shimazu, 2005). Laitinen, Hartikainen, Vanninen, Niskanen,
Geelen & Lansimies (1998) found that plasma noepinephrine concentration increases
with age.
Aging cardiovascular systems demonstrate a marked reduction in parasympathetic
control of HR causing decreased HRV (Jensen-Urstad, Storck, Bouvier, Ericson,
Lindblad & Jensen-Urstad, 1997; Lipsitz, Mietus, Moody & Goldberger, 1990; Ryan,
Goldberger, Pincus, Mietus & Lipsitz, 1994). In elderly individuals (>65yrs), there is an
additional reduction in LF and HF power and HR fluctuation (Lipsitz et al., 1990; Stein,
Ehsani, Domitrovich, Kleiger & Rottman, 1999). This effect is more evident during
activity but can be reduced by regular endurance exercise (Arai, Saul, Albrecht, Hartley,
Lilly, Cohen et al., 1989; Carter, Banister & Blaber, 2003). Goldsmith, Bigger,
Bloomfield & Steinman (1997) argue that vagal modulation is fostered by physical
19
activity. Therefore, the age-related decline in parasympathetic innervation is attributed to
a gradual decrease in fitness level. Aging is also associated with a reduction of maximal
HR and cardiac output during exercise (Fagard, Thijs & Amery, 1993; Piccirillo et al.,
2006; Stratton, Levy, Cerqueira, Schwartz & Abrass, 1994). Advancing age causes
decreased compliance of arterial walls leading to reduced sensitivity of the baroreflex
(Laitinen et al., 1998; Shi, Schaller, Tierney, Chanthavong, Chen, Raven & Smith, 2008).
The effects of aging on arterial SBR sensitivity begin to appear in middle-aged subjects
(Parati & Lantelme, 2005). The above literature highlights the influence of age on cardiac
autonomic function.
Gender. Cardiovascular diseases develop over time and have differential effects
on men and women. The HSFC (2007) recently published a report on Canadians‘ health.
This report highlighted a disparity between the cardiovascular health of men and women.
Approximately 37,000 Canadian women die from cardiovascular diseases each year.
Women have a higher risk of dying after a heart attack or stroke than men. For the first
time in 30 years, women and men have equal mortality rates due to cardiovascular
disease. More research must be directed at investigating women‘s unique cardiovascular
physiology to end this phenomenon.
There is a discrepancy in the literature regarding the effect of gender on the
autonomic nervous system. It is argued that healthy middle-aged women have higher HF
power, lower LF power and lower sympathetic indicator than healthy men (Antelmi, de
Paula, Shinzato, Peres, Mansur & Grupi, 2004; Carter et al., 2003; Huikuri, Pikkujamsa,
Airaksinen, Ikaheimo, Rantala, Kauma et al., 1996). Alternatively, some studies have
20
found that HRV measures are lower (TP and LF power) in women compared to men
(Jensen-Urstad et al., 1997; Ramaekers, Ector, Aubert, Rubens & Van de Werf, 1998). A
higher sympathetic activity has been reported in men compared to women. Franchi,
Lazzeri, Villa, Barletta, Del Bene & Buzzelli (1998) noted that sympathetic control of
cardiac activity is more dominant in men compared to women. Kuo, Lin, Yang, Li, Chen
and Chou (1999) found that women aged 40-59 years of age showed higher
parasympathetic activity in comparison to aged- matched men. Men aged 40-59 years
showed greater sympathetic activity than women. There were no differences in
autonomic function between men and women over the age of 60 years. These findings
indicate that gender does have an effect on cardiac modulation.
There are also opposing claims in the literature about gender differences and SBR
sensitivity. SBR sensitivity has been found to be lower in healthy women compared to
healthy men (Huikuri et al., 1996; Laitinen et al., 1998; Sevre, Lefrandt, Nordby, Os,
Mulder, Gans, Rostrup & Smit, 2001). In contrast, Dougherty et al. (1999) found that
SBR sensitivity was higher in middle-aged women than age-matched men in both supine
and standing postures. Although ambiguous, there is a gender disparity between
autonomic nervous system regulation in men and women.
Menopause. Middle age is a period of transition in autonomic balance for women
as they confront menopause. Menopause, or the permanent end of menstruation and
fertility, is defined as 12 months of amenorrhea. The mean age at menopause is 51 years
in developed countries (Greendale, Lee & Arriola, 1999). Near the onset of menopause,
women experience an increased occurrence of cardiovascular disease (Davy, Willis &
21
Seals, 1997; Eaker, Chesebro, Sacks, Wenger, Whisnant, Winston, 1994). Menopausal
women have a lower incidence of cardiovascular disease than postmenopausal women
and age matched men. This effect may be attributed to estrogen. Estrogen demonstrates
several cardio protective mechanisms which positively affect plasma lipids, carbohydrate
metabolism, hemocoagulation and formation of atherosclerotic plaque. Additionally,
estrogen encourages the release of nitric oxide through endothelial tissues to cause
vasodilation and improve vascular tone. This causes a reduction in peripheral vascular
resistance which maintains BP within a normal range. Estrogen levels decrease
substantially at the onset of menopause (Rosano & Panina, 1999). The use of estrogen
replacement therapy improves cardiac autonomic function, attributing gender differences
in cardiac regulation to hormonal influences (Huikuri et al., 1996).
Menopause is characterized by increased sympathetic and decreased
parasympathetic innervation of the heart (Farag, Bardwell, Nelesen, Dimsdale & Mills,
2003; Rys, Rys, Kogut & Thor, 2006). Furthermore, R-R interval decreases and there is
impairment of the baroreflex (Brockbank, Chatterjee, Bruce & Woledge, 2000). Irigoyen,
Paulini, Flores, Flues, Bertagnolli, Moreira, et al. (2005) suggest that exercise
conditioning can improve SBR sensitivity in postmenopausal women.
Body Posture. Variations in body posture can cause alterations in HRV and
arterial baroreflex (Pagani, Lombardi, Guzzetti, Rimoldi, Furlan, Pizzinelli et al., 1986;
Perini, Orizio, Milesi, Biancardi, Baselli & Veicsteinas, 1993). This has been explored
thoroughly through clinical cardiovascular reflex testing. HR and BP responses are
evaluated after a change in position for the purpose of assessing autonomic nervous
22
system function. Changing physical posture from lying to standing (or standing to steady
state exercise) disrupts sympathovagal balance which prompts a rise in sympathetic
activity leading to an increase in LF power and a decrease in total HRV (Lewis, 2005;
Malliani, Pagani, Lombardi, Furlan, Guzzetti & Cerutti, 1991; Pomeranz, Macaulay,
Caudill, Kutz, Adam, Gordon et al., 1985). This cascade of autonomic reflexes is
attributed to greater parasympathetic control of HR in the supine position compared to
standing position. HR is lower when an individual is lying down due to higher vagal
innervation of the heart (Pagani et al., 1986). When posture changes from supine to
standing, gravity pulls blood downward so that it accumulates in the lower extremities.
As blood pools in the compliant venous vessels, there is less return to the heart causing a
decreased cardiac output and arterial BP. In healthy individuals, a decrease in BP is
detected by arterial baroreceptors in the carotid sinus and aortic arch. The baroreceptors
sense a drop in BP and react by decreasing the frequency of impulses sent to the brain
stem. This causes an increase in sympathetic activity and a decrease in parasympathetic
innervation of the SA node; HR, cardiac output and cardiac contractility increase to
maintain an adequate BP (Kamath et al., 1991; O'Leary & Seamans, 1993). Individuals
with baroreflex failure or an impaired autonomic nervous system do not have the ability
to protect their BP against the excessive rise or fall experienced during a posture change.
In such an event, cerebral blood flow can be compromised and dizziness or syncope can
occur; this is known as orthostatic hypotension (Kappel, Fink & Batzel, 2007; Ketch et
al., 2002).
Respiratory Rate. An individual‘s respiratory rate influences HRV. The nucleus
ambiguous is responsible for increasing parasympathetic nervous input to the heart via
23
the vagus nerve during expiration. Stimulation of the vagus nerve decreases sinoatrial
node firing and slows HR. In contrast, the nucleus accumbens receives inhibitory signals
during inspiration and the vagus nerve remains unstimulated as HR increases (Neff,
Wang, Baxi, Evans & Mendelowitz, 2003). During inspiration, the R-R interval decreases
and HR increases. For the length of expiration, the opposite occurs, the R-R interval
increases and HR decreases. The parasympathetic nervous system is predominant during
expiration and not involved during inspiration (Eckberg, 1980; Kollai & Mizsei, 1990;
Lewis, 2005). This phenomenon is called respiratory sinus arrhythmia and reflects the
changes in R-R interval during inspiration and expiration (Haggenmiller, Baumert, Adt &
Frey, 1996). Respiratory sinus arrhythmia increases the HF component of HRV. This is
due to respiratory-related vagal modulation of HR; the degree of change corresponds to
the amount of cardiac vagal tone (Hayano, Mukai, Sakakibara, Okada, Takata &
Fujinami, 1994). There is a relationship between respiratory sinus arrhythmia amplitude
and breathing frequency. For breathing frequencies over .01 Hz, HF power decreases at a
rate of about 20dB/decade (Hirsch & Bishop, 1981).
There are several interconnected physiological mechanisms that contribute to
respiratory sinus arrhythmia; the first is tidal volume. Tidal volume is the amount of air
moved in and out of the lungs during a single respiration. Greater tidal volumes cause
increased HRV (Brown, Beightol, Koh, & Eckbarg, 1993). This can be attributed to the
Hering-Breuer reflex, stretch receptors located in the smooth muscle of the airways
provide vagal feedback to slow respiration when there is over inflation or when tidal
volumes exceeds 1000 mL (Taha, Simon, Dempsey, Skatrud & Iber, 1995; West, 2005).
Large tidal volumes create negative intrathoracic pressure. Inspiration is accomplished by
24
the contraction or decent of the diaphragm. This creates negative intrathoracic pressure in
the chest cavity which causes increased blood flow and volume into the thoracic vena
cava. There is a consequent increase in HR and stroke volume due to increased venous
return to the right atrium (Hayano et al., 1994).
It may be assumed that conscious mental measurement of the rate and depth of
breathing during HRV data collection is imperative due to the existence of the respiratory
sinus arrhythmia. However, this study did not incorporate measured breathing techniques
as there is no consistent recommendation in the literature regarding standardized
breathing protocols to control for the effects of breathing on HRV. The literature
insinuates a disagreement over the use of breathing protocols versus voluntary control of
breathing. Some researchers support the use of controlled breathing as a means to
enhance vagal modulation. Cooke and colleagues (1998) evaluated several breathing
protocols and found that a structured pattern without strict control of inspired volume is
the most efficient method to reduce the impact of respiratory sinus arrhythmia on HRV
interpretation. Brown et al. (1993) argue that since respiration increases LF power spectra
and decreases HRV, breathing protocols must be used in order for valid interpretation.
Patwardhan, Evans, Bruce & Knapp (2001) disagree; they argue that regulated breathing
is associated with a small but significant increase in mean HR and a decrease in
respiratory synchronous variation in HR. They also found that HF power was similar
during spontaneous versus metronomic breathing suggesting that there is no advantage to
a calculated breathing regime. Further, Haggenmiller et al. (1996) advocate for voluntary
control of breathing as controlled ventilation may cause participants to experience
psychological stress as they attempt to counter their natural breathing pattern. This
25
conscious effort has an effect on HRV. Sufficient evidence implies that structured
breathing protocols can interfere with HRV interpretation.
Antihypertensive Medications. Antihypertensive therapy is initiated for the
treatment of hypertension. Antihypertensive medications act by reducing systolic and
diastolic BP to prevent the damaging effects of chronic elevation (Black, Elliott, Neaton,
Grandits, Grambsch, Grimm, et al., 2001). There is a large variety of drugs available in
the current market for reducing BP. The five most common medications can be grouped
into five classes: diuretics, beta blockers, angiotension converting enzyme-inhibitors
(ACE inhibitors), angiotension II receptor antagonists and calcium channel blockers
(Chobanian, Bakris, Black, Cushman, Green, et al., 2003). Diuretics influence the
kidneys to excrete excess salt and water from blood and tissues. Beta blockers block the
action of catecholamines on β-adrenergic receptors. ACE inhibitors prevent angiotension
converting enzyme from changing angiotension l into angiotension ll; a powerful
vasoconstrictor. Angiotension II receptor antagonists work in the same pathway to
antagonize the activation of angiotension receptors. Calcium channel blockers impede the
entry of calcium into muscle cells in artery walls, inhibiting vasoconstriction (Abrams,
2004). Two-thirds of individuals suffering from hypertension will require two or more
antihypertensive medications selected from different drug classes (Chobanian et al.,
2003). The current literature suggests that lifestyle modification, such as exercise, plus
antihypertensive therapy is the most effective multidimensional treatment to combat
hypertension (Lochner, Rugge, Judkins & Saseen, 2006).
26
Beta blockers and calcium channel blockers have distinctive characteristics that
allow them to manipulate the cardiac autonomic nervous system. Beta blockers reduce
HR at rest and during exercise by diminishing LF power (sympathetic innervation) and
LF/HF ratio. HR is further compounded by enhanced parasympathetic modulation which
lengthens R-R interval by increased HF power (Pagani, 1986; Panfilov, Morris,
Donnelly, Scemama & Reid, 1995). Takase, Abe, Nagata, Matsui, Hattori, Ohsuzu et al.
(2005) supported these findings; they found that treatment with a beta blocker decreased
BP and increased in HRV. Calcium channel blockers can interfere with the baroreceptorvagal reflex by increasing SBR sensitivity causing increased HR in some cases (Eguchi,
Tomizawa, Ishikawa, Hoshide, Fukuda, Numao, Shimada, & Kario, 2007; Taylor &
Kowalski, 1984).
Acute Exercise. Exercise is defined as, ―any muscular activity that generates force
and disrupts homeostasis‖ (ACSM, 2000). Acute exercise is defined by the performance
of a short session of any aerobic exercise and has an impact on the autonomic nervous
system (Maeda, Tanabe, Otsuki, Sugawara, Ajisaka & Matsuda, 2008). The current
literature describes HRV indices in healthy individuals. In a resting state, the PNS is the
primary influence on HR. At the onset of exercise, there is vagal withdrawal and a
temporary increase in sympathetic tone. This causes HR to increase by 30-50 beats per
minute. Continued activity is associated with progressive parasympathetic withdrawal
and attenuation of sympathetic over-activity (Brenner, Thomas & Shephard, 1998; Chiu,
Wang, Huang, Tso & Kao, 2003; Freeman et al., 2006; Nakamura, Yamamoto &
Muraoka, 1993; Yamamoto, Hughson & Peterson, 1991). HR and myocardial oxygen
demand increase linearly in proportion to metabolic demand during exercise. Active
27
tissues respond to the metabolic demands of exercise by local vasodilation. Increased
cardiac output, decreased peripheral vascular resistance, redistribution of blood flow to
active muscles, venoconstriction, and increased oxygen extraction occur at the onset of
acute exercise (Silverthorn, 2001).
The carotid baroreflex is reset to a higher operating point during acute exercise
with no attenuation in maximal sensitivity. This is substantiated by the resulting
hypotension experienced by hypertensive individuals in the post exercise period
(Minami, Mori, Nagasaka, Ito, Kurosawa, Kanazawa et al., 2006; Potts, Shi & Raven,
1993; Silva, Brum, Negrao, Krieger, 1997).
Effects of Exercise Conditioning on the Cardiac Autonomic Nervous System
Aerobic exercise is defined as ―any activity that uses large muscle groups, can be
maintained continuously and is rhythmic in nature‖ (ACSM, 2000). Regular aerobic
exercise has different effects on the autonomic nervous system relative to acute aerobic
exercise. Exercise conditioning is characterized as routine performance of aerobic
exercise over time. Physiological responses to training include cardiac and peripheral
adaptations. Pagani et al. (1988) studied a sample of 11 men and women with mild
hypertension during an intensive 6 month physical training program. Training increased
the resting R-R interval, decreased systemic arterial BP by 10.2 mmHg and diastolic BP
by 7.1 mmHg. Resting LF power decreased and HF power increased. This signifies an
increase in parasympathetic activity. Yamamoto et al. (1991) and Nakamura, Yamamoto
& Muraoka (1993) found that during acute low intensity exercise, parasympathetic
effects on HR are more dominant than sympathetic effects. Regular exercise conditioning
28
reduces resting and exercise HR, lowers low density lipoprotein, increases high density
lipoprotein and assists with weight control (Cade, Mars, Wagemaker, Zauner, Packer,
Privette et al., 1984; Malliani et al., 1991; Pagani et al., 1988).
Exercise training has been found to increase the gain of the baroreflex. It appears
that moderate intensity training for at least 3 months is sufficient to achieve change.
Goldsmith et al., (1992) reported that parasympathetic activity is greater in aerobically
trained vs. untrained normotensive men. Participation in moderate-intensity exercise has
consistently lowered BP and HR in multiple populations of individuals (Campbell,
Burgess, Choi, Taylor, Wilson, Cleroux et al., 1999; Fagard, 1995; Lackland, 2005).
Prolonged and intense exercise training does not necessarily lead to greater enhancement
of the autonomic nervous system and may not provide any added protective benefits
(Iwasaki, Zhang, Zuckerman & Levine, 2003).
Exercise conditioning is known to lower BP in hypertensive individuals (Davy et
al., 1997; Dubbert, Martin, Cushman, Meydrech & Carroll, 1994; Ishikawa, Ohta, Zhang,
Hashimoto & Tanaka, 1999; Maddens, Imam & Ashkar, 2005; Miller et al., 2002;
Moreau et al., 2001; Whelton, Chin, Xin & He, 2002). Davy et al. (1997) noted a
reduction in systolic and diastolic BP in post-menopausal, hypertensive women after 12
weeks of moderate-intensity aerobic exercise training. Similarly, Hagberg, Park & Brown
(2000) observed that exercise training decreased BP in approximately 75% of individuals
with hypertension. Systolic and diastolic BP reductions averaged approximately 11
mmHg and 8mmHg, respectively.
29
Hypertensive individuals who participate in regular exercise experience decreased
total peripheral resistance and increased overall vascularization of skeletal muscle after 3
months of moderate exercise training (Iwasaki et al., 2003; Izdebska, Cybulska,
Izdebskir, Makowiecka-Ciesla & Trzebski, 2004; Martin & Dubbert, 1987; O'Sullivan &
Bell, 2000). There are opposing claims in the literature about the health benefits of
varying intensities of exercise. Exercise is commonly recommended at high or moderateintensity to reduce high BP and restore baroreflex function (Cleroux et al., 1999; Parati &
Lantelme, 2005). The problem with this prescription is that moderate and high intensity
exercise increases sympathetic activity and BP. These two effects are undesirable to
hypertensive individuals as they are associated with a risk for acute cardiovascular injury
(Nakamura, Yamamoto & Muraoka, 1993; Yamamoto, Hughson & Peterson, 1991).
In contrast, few studies have described the advantages of low intensity exercise.
Low intensity exercise lowers BP and does not increase plasma catecholamines
(Nakamura et al., 1993; Yamamoto et al., 1991). In a six year randomized control trial of
140 middle aged men, Tuomainen, Peuhkurinen, Kettunen and Rauramaa (2005) found
that low to moderate intensity exercise has beneficial effects on the cardiac autonomic
nervous system. Brown, Wolfe, Hains, Pym and Parker (1994) evaluated the effects of a
12 week low intensity vs. a moderate intensity home walking program with post
operative coronary artery bypass graft patients and noted comparable cardiovascular
improvements. Sugawara, Inoue, Hayashi, Yokoi and Kono (2004) reported that low
intensity exercise training improves central arterial compliance in postmenopausal
women. These studies support the use of low intensity exercise in cardiovascular
rehabilitation programs.
30
Walking has been found to be an excellent low intensity exercise that is
recommended for hypertensive individuals over other exercise regimes such as weight
training (Lesniak & Dubbert, 2001; Wallace, 2003). Walking 10,000 steps per day,
without regard to pace, is effective in lowering BP, increasing exercise capacity, and
reducing sympathetic nerve activity in hypertensive patients (Iwane, Arita, Tomimoto,
Satani, Matsumoto, Miyashita et al., 2000). A low intensity, 20 week, walking program
was implemented in multiple community settings for elderly adults by Kolbe-Alexander,
Lambert and Charlton (2006). They found that those who were involved in the exercise
intervention had a significant decrease in systolic BP. Sakuragi and Sugiyama (2006)
studied 21 healthy female subjects who underwent a four week walking program. At the
end of the program, their autonomic nervous system had shifted toward parasympathetic
predominance. It is recommended that postmenopausal women incorporate 30 minutes of
daily walking in to their routine as it is a feasible approach to increase activity level
(Asikainen, Kukkonen-Harjula & Miilunpalo, 2004). Williams (2008) assessed the
relationships of walking distance and frequency to the prevalence of antihypertensive
drug therapy in hypertensive individuals. He found that medication use could be
substantially reduced by walking. Further, the effects of long term aerobic exercise on BP
are comparable to the benefits of antihypertensive drug use (Ketelhut, Franz & Scholze,
2004; Whelton et al., 2002).
Relevant work by other investigators at Queen’s University
Previous research from this laboratory has laid a foundation for further
investigation in the area of low intensity physical conditioning and the effect of age and
31
gender on cardiac autonomic function. Dougherty (1999) investigated the autonomic
modulation of HR in healthy middle-aged men and women and was able to describe
characteristics of HRV and SBR sensitivity. She tested participants in supine and
standing positions but did not implement an exercise intervention. Dougherty (1999)
found that gender affects HRV and SBR sensitivity as males age in a relatively stable
fashion whereas females are affected by their menstrual cycle which causes autonomic
imbalance during the fifth decade. Females showed higher HRV than men. Women in
their fifth decade showed greater sympathetic activity compared to women in their fourth
decade. Males showed a declining trend in sympathetic activity as they passed through
their 4th and 5th decades. There was no difference in sympathovagal balance between men
and women after 50 years of age.
Myslivecek, Brown and Wolfe (2002) studied the effect of low-intensity exercise
on HRV and spontaneous baroreflex function in 32 normotensive middle-aged women.
They were specifically interested in investigating the differences between menopausal
and postmenopausal women. Participants were placed into one of two hormonal groups:
menopausal (n= 16) and postmenopausal (n=16) and then randomly assigned to either a
12-week, low-intensity exercise training group or to a non-exercise control group. The
exercise group was required to walk 3 days /week. Myslivecek et al. (2002) found that
menopausal and postmenopausal women in the exercise group experienced higher vagal
modulation, lower sympathetic innervation and longer R-R intervals than the sedentary
control group.
32
Hua (2006) examined the effects of low-intensity exercise conditioning on BP,
HR and cardiac autonomic function in men and women with mild hypertension. Forty
participants were separated according to their gender and then randomized into either a
12 week low-intensity exercise program or delegated to a control group. Participants in
the exercise group were required to walk 3 days/week. Hua (press) found that the 12
week walking program reduced diastolic BP and increased R-R interval during exercise
testing in hypertensive men and women. A reduction in men‘s resting HR was also noted.
These results suggest that an exercise conditioning effect had been achieved.
It has not been determined if a low intensity exercise program, performed five
days/week, would reduce HR, systolic/diastolic BP and improve autonomic balance in
women with hypertension. This investigation will not be a replication of previous studies
but will utilize earlier findings to guide the hypothesis and study design. Further research
directed towards women‘s unique cardiovascular physiology has been identified by
Dougherty (1999). The present study aimed to achieve cardiovascular and autonomic
adaption through low-intensity exercise by applying a Myslivecek et al. (2002) finding‘s
to a population of hypertensive women. Addtionally, Hua et al. (in press) recommended
that the quantity of low-intesity exercise be increased from 3 days/ week in order to
achieve autonomic adaption. These recommendations were incorporated into the current
research design; participants were required to walk 5 days/week.
Exercise Adherence
Compliance poses the largest obstacle to successful participation in an exercise
regime. Compliance and adherence are two words that are often used interchangeably in
33
the literature but are defined slightly differently. This paper will use both terms but favors
the use of adherence because it requires patient agreement to the recommendations; this
seems appropriate due to the voluntary nature of the study. Compliance will be used
because of its wide spread acceptance in the literature. Adherence is defined as, ―the
extent to which a persons‘ behavior – taking medications and/or executing lifestyle
changes, corresponds with agreed recommendations from a health care provider‖ (Sabaté,
2003). Efficacy of exercise is determined by an individual‘s adherence rate to it. Two
thirds of patients are non-adherence with exercise programs. The problem is further
complicated as it is difficult to assess compliance rates when noncompliance is not
readily admitted and there are extremes of compliance to a regimen (Sluijs, Kok & van
der Zee, 1993). Adherence is quantitatively defined as the percentage of sessions
completed relative to the number of session prescribed (Cox, Burke, Morton, Gillam,
Beilin, & Puddey, 2001). An individual‘s level of self-efficacy is the strongest predictor
of adherence to regular exercise (Egan, 2006; McAuley et al, 2003; Sears & Stanton,
2001). Lee, Avis & Arthur (2007) found that self efficacy was directly associated with
success in a community based walking program. The Cleveland Clinic, the United States
national leader in cardiovascular rehabilitation links personal factors (perceived
seriousness of their health problem, feeling of control over their health situation and their
level of self-efficacy) to exercise adherence (Egan, 2006).
Compliance to an exercise regime is quantified by a simple numeric rating
system; high compliance is defined as participation in 67% of prescribed exercise
sessions; moderate compliance is associated with 33-66% involvement; low compliance
is less than 33% (Hawkins & Hackett, 1982). This study defined adherence to the
34
exercise regime as a minimum of three out of five walks per week at the prescribed
distance. Participants were required to complete the entire 12 week protocol. This is
consistent with other studies done with similar populations. A minimum of three exercise
sessions per week is necessary to produce a conditioning effect (Cleroux, Feldman &
Petrella, 1999; Cox et al., 2001; Hua, 2006; Hua et al., in press; Myslivecek et al., 2002).
Rationale and Hypothesis
Rationale. Hypertension is a well known precursor to stroke and heart disease and
has been identified as one of the leading risk factors for death in developed countries
(WHO, 2002). Hypertensive individuals experience impairment of the autonomic nervous
system. Autonomic deregulation is manifested through increased sympathetic and
decreased parasympathetic activity, increased vasomotor sympathetic tone, reduced SBR
sensitivity and reduced HRV. The risk of developing hypertension increases with age.
More women suffer from hypertension than men (Corrao, Becker, Ockene & Hamilton,
1990). Physical inactivity is a major risk factor which contributes to the development of
hypertension. Exercise conditioning is known to lower BP in hypertensive women and
reverse some effects of autonomic dysregulation (Davy, Willis & Seals, 1997; Whelton,
Chin, Xin & He, 2002). Exercise is commonly recommended at high- or moderateintensity to reduce high BP and restore baroreflex function (Cleroux, Feldman & Petrella,
1999; Parati & Lantelme, 2005). However, moderate-intensity exercise can be harmful as
it increases sympathetic activity and BP which could result in cardiovascular injury. Low
intensity exercise may offer comparable cardiovascular benefits without increasing
plasma catecholamines (Brown et al., 1994; Nakamura et al., 1993; Yamamoto et al.,
35
1991). Walking has been found to be a suitable low intensity exercise that is
recommended for hypertensive individuals (Lesniak & Dubbert, 2001).
Currently, there are is no available literature which describes the effect of a low
intensity exercise conditioning program on BP, HR and cardiac autonomic function in
middle-aged women diagnosed with hypertension. The purpose of this study is to
determine the effects of a 12 week low intensity exercise conditioning program on BP,
RPP, HR and cardiac autonomic function in women with hypertension. Additionally, the
influence of menopausal state will be evaluated to determine its influence on the outcome
variables.
Hypothesis. Compared with hypertensive women in a non exercising comparison
group, those in a 12 week low intensity home walking program will demonstrate the
following:
1) Cardiovascular adaptation (decreased systolic BP, diastolic BP, HR and RPP
at rest, standing and at a given sub maximal exercise)
2) Autonomic adaptation (increased parasympathetic modulation of HR and
decreased sympathetic indicator at rest, standing and at a given submaximal
exercise).
Additionally, menopausal state (menopausal, postmenopausal) will influence
HRV and SBR sensitivity such that postmenopausal women will demonstrate increased
sympathetic and decreased parasympathetic innervation of the heart and decreased
spontaneous baroreflex sensitivity compared to menopausal women.
36
CHAPTER THREE
Method
Participants
Fifty sedentary, non-smoking women, diagnosed with hypertension by a
physician (BP ≥ 140/90 mmHg) (Canadian Hypertension Education Program (CHEP),
2007), aged 45-65 years, were invited to participate in this study. Consistent with the
American College of Sports Medicine (ACSM) (2006) guidelines, sedentary was defined
as performance of fewer than two sessions per week of regular aerobic exercise. Nonsmoking status was defined as self reported abstinence from cigarette smoking for a
period of three months prior to the study. Participants were required to read and write the
English language and give informed consent in order to volunteer for this study
(Appendix A). Physician approval had to be obtained for women who answered ―yes‖ to
at least one of seven questions on the Physical Activity Readiness Questionnaire (PARQ) (Canadian Society for Exercise Physiology, 2002) (Appendix B). Individuals were
excluded from the study for the following reasons: 1) currently participating in more than
two aerobic physical activity sessions per week; 2) co-morbid conditions that limited
ability to participate in exercise or exercise testing; 3) taking hormone replacement
therapy; 4) diagnosed with stroke, heart failure, ischemic heart disease, myocardial
infarction, renal disease or vascular disease; 5) tobacco/ marijuana smoking; 6) family
physician disapproval. Four eligible women withdrew from the study due to illness (n= 1)
37
and loss to follow up (n= 3). See Appendix O for a summary of the study sample and
reasons for attrition.
Antihypertensive medications are prescribed by family physicians in this region
as standard practice for the treatment of hypertension. Consequently, BP medications
were accounted for in the data analysis. Participants were eliminated from the study if
they underwent a change of medication type or dose during the study.
Recruitment was carried out in Kingston, Ontario from September 2007 to March
2008. Potential participants were solicited through community newspapers, internet
advertisements and through flyers distributed at local hospitals, family physician‘s
offices, post secondary institutions and public notice boards. A convenience sample was
utilized; 150 interested women responded to advertisements and were screened for
preliminary eligibility by telephone or e-mail. Women who failed to meet the inclusion
criteria were excluded from the study. Eligible women were then invited to the Exercise
Research Laboratory in the Hotel Dieu Hospital (Kingston, Ontario) in order to confirm
eligibility, provide written informed consent and perform the initial HR and BP testing.
Participants were counterbalanced within the exercise and control group according to
classification of BP medications (beta blocker or no beta blocker). Blinding was not
possible as participants in the exercise group had to actively engage in a walking program
and the control group maintained their sedentary lifestyle. To decrease contamination, the
control group was specifically asked to maintain their current lifestyle (exercise/nutrition)
for the duration of the experiment.
38
The sample size was calculated using systolic BP as the primary outcome measure
and based on previous findings in women. Hua, Brown, Hains, Godwin, and Parlow (in
press) used a sample of 20 women divided into two groups (control/exercise) in order to
demonstrate a reduction in BP due to low intensity exercise performed over 12 weeks.
Using the systolic BP values obtained from women in the exercise group (Week 1136mmHg, Week 12- 129 mmHg, SD 12, alpha .05, desired power .80) the sample size
for this study was calculated to be 37.
Ethics approval was obtained from the Queen‘s University Research Ethics Board
and the Affiliated Teaching Hospitals Health Sciences Human Research Ethics Board
(Kingston, ON). Permission was granted for all previously developed tools used within
this study.
Equipment and Instruments
The PAR-Q (CSEP, 2002) was used to screen interested women for eligibility
before they came to the Exercise Physiology Laboratory at Hotel Dieu Hospital for initial
testing. The PAR-Q consists of seven ―yes‖ or ―no‖ questions which are designed to
identify adults for whom physical activity may be inappropriate. If a participant answered
―yes‖ to one or more questions, their Family physician was notified and written approval
was obtained. If a participant answered ―no‖ to all questions, she proceeded through the
study design and did not require permission from her family physician. This procedure
was established in consultation with the medical supervisor of this research project.
Permission to use the PAR-Q was granted by the Canadian Society for Exercise
Physiology.
39
The Human Activity Profile (HAP) (Daughton, Fix, Kass, Bell & Patil, 1982) is
an instrument that was used to measure regular physical activity. The HAP consists of 94
common daily activities ranked in order from least to most amount of energy expenditure.
These activities cover a wide range and represent self care tasks (taking a bath),
personal/household work (carrying out the garbage), entertainment /social activities
(golfing 18 holes without riding a cart) and independent activities. Participants indicated
if they are currently able, unable or have never been able to perform the activity. The
Maximum Activity Score (MAS) and the Adjusted Activity Score (AAS) are calculated
from participant responses. Higher MAS and AAS scores signify activities which require
more energy to perform. Low scores indicate difficulty with activity levels. The HAP
takes about ten minutes to complete and is a valid and reliable measure of physical
activity (Bilek, Venema, Camp, Lyden & Meza, 2005; Davidson & de Morton, 2007).
Participant‘s weight and height were measured with a Seca 700 scale (Seca
Corporation, Hanover, MD); measurements were used to calculate body mass index
(kg/m2). Waist circumference was measured with a soft plastic measuring tape while the
participant stood upright. The measuring tape was placed around the participant‘s waist,
parallel to the floor, between the bottom of the rib cage and the top of the hipbones.
The BpTRU (Model BPM-300, VSM Medtech Ltd. Coqitlam, BC) is an
automated non invasive BP monitor that was used to measure systolic and diastolic BP
and HR via an inflatable arm cuff, at rest, standing and at peak exercise. The BpTRU has
been shown to be an accurate non-invasive BP monitoring device for individuals aged 383 years (Mattu, Heran & Wright, 2004)
40
The Finapres® 2300 (Ohmeda, Englewood, CO) is a digital automated BP
monitor which was used during testing to measure and record spontaneous changes in
beat-by-beat finger arterial BP. This is a photoplethysmographic measure. The reliability
of the Finapres® 2300 in detecting changes in systolic BP has been demonstrated by
several studies (Iellamo, Legramante, Raimondi, Castrucci, Massaro & Peruzzi, 1996;
Imholz, van Montfrans, Settels, van der Hoeven, Karmaker & Weiling, 1988; Imholz,
Wieling, van Montfrans, Wesseling, 1998). A computer software program developed by
Blaber, Yamamoto & Hughson (1995) was used for spontaneous baroreflex analysis.
The Spacelab 521T Cardiac Monitor with QRS detector (Squibb Vitatek Inc.,
Hillsboro, USA) was used to collect HRV data (R-R interval). Standard surface
electrocardiographic (ECG) electrodes were used with the monitor. The cardiac monitor
was interfaced with a personal computer by means of an eight-channel analog/digital
convertor (DAS-16, Metrabyte Corp., Multitest Electronics, Scarborough, ON). The
DAS-16 provides an R-R interval accuracy of 1 ms at a sampling rate of 1000Hz (Parlow,
Viale, Annat, Hughson & Quintin, 1995). The digital R-R interval output was stored on a
password protected personal laptop computer (Dell Inspiron 9400). Hughson and
Yamamoto (1993) computer software program was used for spectral analysis of HRV.
Each participant performed steady-state exercise on the Ergometrics er800s cycle
ergometer (Ergoline GmbH, Lindenstrabe, Germany). This is an electronic,
computerized, stationary ergometer that is self regulated.
Borg‘s Rating of Perceived Exertion (Borg, 1982) was used by participants during
steady-state exercise testing and by the exercise group during the 12 week walking
41
program. It is a 6-20 point descriptive scale where 6 represents, "no exertion at all" and
20 represents "maximal exertion." Participants in the exercise group were told to aim for
a perceived exertion level of 11-13 (light - somewhat hard) as 12-14 (somewhat hard –
hard) is associated with a moderate intensity level of intensity. The scale is based on
physical sensations experienced during activity; increased HR, increased respiration,
increased sweating and muscle fatigue. Although this is a subjective measure, exertion
rating is indicative of HR during physical activity (Borg, 1998). Borg‘s Rating of
Perceived Exertion scale has been shown to be a valid measure of exercise intensity
(Robertson & Noble, 1997).
A log was provided to participants in both groups. The exercise log for the
exercise group contained instructions on how to measure radial/carotid pulse (Appendix
C), Borg‘s Rating of Perceived Exertion (Appendix D), a 12 week low-intensity walking
protocol (Brown, Laschinger, Hains & Parry, 1992; Brown, Wolfe, Hains, Pym & Parker,
1994) (Appendix E), and a log to measure compliance to the exercise regime: distance,
duration of exercise, HR, perceived exertion, reasons for not exercising and additional
physical activity (Appendix F). The control group received an activity log which
contained a 12 week log to record daily physical activity (Appendix G).
42
Eligible Sample
N=50
Inclusion Criteria;
Female
Age >44 yrs
Diagnosed with Hypertension (BP >140/90)
Sedentary (<2 exercise sessions/week)
Approval of physician or pass PAR-Q
Time
N = 12
weeks
Assignment to Groups
Control
N=23
Exercise
N=27
Week 1- Baseline
Telephone call every
three weeks
Week 12 – Follow-up
Figure 1. Study design
Procedure
Prior to testing, participants were screened through telephone interviews based on the
inclusion and exclusion criteria. During the initial telephone screening, participants
verbally completed the PAR-Q questionnaire (CSEP, 2002). Responses were documented
and evaluated for entrance into the study. Physician‘s written approval was granted for
women who answered ―yes‖ to one or more of the PAR-Q questions. After telephone
screening, potential participants were invited to the Exercise Physiology Laboratory at
Hotel Dieu Hospital and asked to refrain from consuming alcohol or caffeine 12 hours
before testing (Daniels, Mole, Shaffrath & Stebbins, 1998; Richardson, Rozkovec,
Thomas, Ryder, Meckes & Kerr, 2004). Participants were also asked to avoid eating a
large meal two hours in advance and refrain from strenuous physical activity for 24 hours
prior to testing.
During the initial visit, the researcher explained the study in detail and answered
participants‘ questions. Eligible participants provided written informed consent,
43
following which demographic data was collected to determine if there were any
confounding influences on the outcome measures. Demographic data included age,
education level, marital status, occupation, cardiovascular medical history/medications
and menopausal state. Participants completed the HAP (Daughton et al., 1982) before
height, weight and waist circumference were measured with the shoes removed. Body
mass index (BMI) was calculated by dividing body weight by height squared (kg/m2).
The physiological data that were collected included arterial BP in the brachial
artery and autonomic data (HRV [R-R interval data] and beat-by-beat finger arterial BP)
in three conditions (supine, standing, exercise). Arterial BP, using a BpTRU automatic
BP monitor on the left arm, was taken in two postures (supine, standing) and at the end
(peak) of low intensity exercise. The lower edge of the BpTRU BP cuff was placed
approximately 2.5 cm above the site of the brachial artery (determined by palpation of the
left arm). Autonomic data were measured and recorded continuously for 10 min, after 35 min equilibration, in each condition, for a minimum of 512 cardiac cycles. R-R interval
data were obtained using an ECG recording, with 3 latex-free, standard surface ECG
electrodes in a Lead II configuration (right arm, left arm and left leg). Beat-by-beat
arterial BP data were measured using the Finapres 2300 automated BP monitor. A finger
cuff was placed on the middle phalanx of the third digit on the left hand and connected to
a transducer that is positioned on top of the left hand. The left hand was elevated to the
level of the phlebostatic axis of the heart by placing it on an adjustable side table.
In the supine position, arterial BP (BpTRU) was measured in a quiet, lightattenuated room after a 3 min equilibration period. Autonomic data (HRV, beat-by-beat
44
arterial BP) were then recorded continuously for 10 min. Participants were advised to
relax and refrain from speaking or moving during data recording (Brown, Wolfe, Haines,
Ropchan & Parlow, 2003). Electrocardiogram electrodes were placed in a Lead II
configuration in order to obtain R-R interval data. A finger cuff was placed on the
participant‘s middle finger in order to obtain arterial BP.
Participants then stood upright for a 3-5 min equilibration period (Kamath, Fallen &
McKelvie, 1991). After the equilibration period, arterial BP (BpTRU) was taken in the
left arm. Subsequently, R-R interval and beat-by-beat arterial BP data were collected for
10 min in the free standing position. The 512 cardiac cycles recorded was used for
analyses of HRV and SBR sensitivity (Brown et al., 2003; Hughson, Northey, Xing,
Dietrich, & Cochrane, 1991). HRV and arterial BP were measured with the same
electrocardiogram electrode configuration and finger cuff placement as the supine
position. Subjects were reminded to remain as still as possible and not to talk during data
collection. The participants were advised to notify the researcher immediately if they
experienced signs of orthostatic hypotension: dizziness, light-headedness, shortness of
breath, weakness or palpitations. If they experienced any of these symptoms, the testing
was discontinued.
Participants then performed low-intensity, steady-state exercise at a constant work
rate on a cycle ergometer (Brown et al., 2003; Hua et al., in press; Myslivecek et al.,
2002). Each participant sat upright on the cycle ergometer with the seat, handle bars and
foot straps adjusted to suit them comfortably. The finger cuff was maintained at the level
of the heart by elevating the hand/transducer parallel to the participant‘s body with an
45
adjustable stainless steel side table. After a 3-5 min equilibration period, autonomic data
were collected for 512 cardiac cycles during steady-state exercise and was used for
analyses of HRV and SBR sensitivity. At peak exercise, arterial BP (BpTRU) was taken
in the left arm.
Steady state is reached when HR remains constant at the desired work intensity. A
four minute warm-up at 20 watts was followed by a ramp increase in work rate within 30
seconds to a work rate equivalent to 40% of the maximal HR reserve (HRR). The
Karvonen method was used to determine participants target HR (40% of maximum HRR)
(Miller, Wayne, Wallace & Eggert, 1993; Myslivecek, Brown & Wolfe, 2002; Stejskal,
Rechbergova, Salinger, Slachta & Elfmark, 2001). A participant‘s maximum HR, resting
HR (recorded by BpTru) and the percentage of desired exercise intensity (40% HRR) are
used in the formula below to determine target HR:
Target HR= (40%) (HR max - HR rest) + HR rest
Steady state exercise intensity was determined by measuring HR. HR rises
exponentially during the first minutes of exercise as it eventually reaches a plateau. After
this initial period, it remains relatively stable for the duration of the effort (McArdle,
Katch & Katch, 2007). A participant‘s HR was monitored and steady state was
recognized as a HR which was no longer increasing at the target work rate.
After the initial testing, women were counterbalanced between one of two groups,
exercise (n=27) or control (n=23). The exercise group was given verbal and written
instructions for a 12 week, low-intensity progressive walking program, an exercise log (to
record exercise sessions, HR, level of perceived exertion and reasons for not exercising),
46
Borg‘s rating of perceived exertion scale (Borg, 1982; Borg, 1998) and instructions to
measure HR. Participants were taught how to monitor HR by radial palpation, use the
walking protocol, record their walking sessions and use Borg‘s Rating of Perceived
Exertion. Their understanding was verified by having them demonstrate each task prior to
leaving the laboratory. Compliance rates were to be recorded in the log, a participant was
considered compliant if they completed a minimum of three exercise sessions per week
(Cleroux, Feldman & Petrella, 1999; Lesniak & Dubbert, 2001; Wallace, 2003). The
women in the exercise group were asked to refrain from making any dietary changes
during the study. They were advised not to walk within two hours of consuming a large
meal, alcohol or caffeine and encouraged to stretch and drink adequate fluids before and
after each walking session. In the event of an adverse reaction to exercise (shortness of
breath, dizziness, chest pain or any musculoskeletal injury), participants were told to
contact their family physician. See Figure 1 for study design.
Participants were told to notify the primary investigator in the event of illness or
injury. They were instructed to continue to record daily activity regardless of inactivity
and to resume the walking program from the point where they initially left off. These
periods were analyzed at the end of the 12 week walking program. Participants who were
sick for >3 weeks were encouraged to see their family physician and were excluded from
the study.
The exercise conditioning protocol was a 12-week progressive, low-intensity (40%
maximum RR), walking program, which was validated by Brown et al. (1992; 1994),
Hua et al. (in press) and Myslivecek et al. (2002). Participants in the exercise group were
47
instructed to walk five times per week at a prescribed distance. The walking program
started at .08 km/day for the first two weeks and then gradually increased in increments
of 400 meters (1.2 km/day, 1.6km/day, 2 km/day) every week to a maximum distance of
4.8 km/day. See Appendix E for exercise conditioning protocol.
The control group was given verbal instructions to record daily physical activity in
the activity log provided. They were also asked to maintain their current level of activity
and refrain from making dietary changes during the 12 week study. Exercise and control
groups were given telephone calls or sent e-mails from the primary investigator every
three weeks to answer questions and monitor progress.
The testing procedures were repeated at the end of the 12-week study period. The
initial testing lasted approximately 2 hours to complete while the follow-up after 12
weeks took 1 hr. Exercise/activity logs were collected at the follow-up visit to measure
compliance.
Data Analysis
Analysis of Heart Rate Variability. HRV is a measure of beat-to-beat variations in
HR and was analyzed by power spectral analysis using the frequency domain method
(TFESCNASPE, 1996). R-R interval data from electrocardiogram recordings were
converted into a tachogram. The tachogram was then subjected to Fast Fourier
Transformation and converted into a frequency spectrum, separated into LF and HF
power. The variables for analysis of HRV are HF, LF and TP, the ratio of HF to TP
(parasympathetic indicator) and the ratio of LF to HF power (sympathetic indicator). The
editing process was guided by the methods used by Hua, Brown, Hains, Godwin &
48
Parlow (in press) and Hughson, Quintin, Annat, Yammamoto & Gharib (1993). See
Appendix J for a description of the editing process.
Analysis of Baroreflex Sensitivity. The arterial baroreceptor reflex is a
homeostatic mechanism which adjusts the short term, beat-by-beat, regulation of arterial
BP. Measuring the sensitivity of the arterial baroreflex serves as an index of cardiac
autonomic control (Kardos, Watterich, de Menezes, Csanády, Casadei & Rudas, 2008).
SBR sensitivity was evaluated using the sequence method. The sequence method detects
spontaneous sequences of three or more heart beats in which systolic BP and R-R interval
simultaneously change in the same direction. SBR sensitivity is quantified by an R-R
interval response to a 1 mmHg change in systolic BP (Brown, et al., 2003). The
sequences are then analyzed by computer software which uses linear regression to
calculate the slope of each series. The mean slope is used to quantify SBR sensitivity; an
increase in the baroreflex slope is associated with greater parasympathetic innervation
whereas a decrease in slope is linked to reduced vagal stimulation (Hughson et al., 1993;
Blaber et al., 1995; La Rovere, Bersano, Gnemmi, Specchia & Schwartz, 2002; Parlow
et. al, 1995). The variables for analysis of SBR sensitivity include mean baroreceptor
slope, systolic BP and R-R interval. R-R interval data from the electrocardiogram and
arterial BP from the Finapres were collected and edited (Hua et al., 2006; Blaber,
Yammamoto & Hughson, 1995). The methods used for editing can be found in Appendix
K.
49
Statistical Analysis
Descriptive statistics were used to determine the means, frequencies and standard
deviations for the demographic, physiological and lifestyle data collected. Demographic
variables that were analyzed included: age, education level (years), marital status,
menopausal state (pre vs. post), antihypertensive medications, height, weight, body mass
index and waist circumference. Physiological data included: HR, systolic BP, diastolic
BP, HRV and SBR sensitivity in three conditions (supine, standing, steady state
exercise). A numeric activity profile was used to determine lifestyle data. All variables
were evaluated at the beginning and the end of the exercise program. Student t-statistics
were used to determine if the two groups differed from each other in these variables at
week 1 and 12. Repeated measures analysis of variance (ANOVA), with time (two levels:
week 1, week 2) and condition (rest, standing, exercise) as the within-subjects factors,
group (two levels: exercise, control) and menopausal state (two levels: menopausal,
postmenopausal) as the between-subjects factors, was done to determine if there were any
significant differences between means at week 12.
Several repeated measures ANOVA‘s were performed using two-between factors
(Group- exercise, control; Menopausal state- pre, post) and two-within factors (Timeweek 1, week 12; Condition- resting, standing, exercise) to evaluate HR, BP and cardiac
autonomic function. The following were analyzed using this method: BP, HR, RPP, HRV
(R-R interval, HF power, LF power, TP, parasympathetic indicator, sympathetic
indicator) and SBR sensitivity (slope, systolic BP, R-R interval). All data analysis was
conducted with SPSS version 16.0. Compliance rates were determined by calculating
50
average number of walking sessions completed per week. Mean number of walking
sessions were calculated and compared between groups. Differences for all analysis will
be significant if p<.05.
51
CHAPTER FOUR
Results
Descriptive statistics were used to determine the means, frequencies and standard
deviations for the demographic, physiological and lifestyle data. Independent t-tests were
used to determine if there were any significant differences between the two groups. Fifty
hypertensive women enrolled in this study. Forty-six participants completed the 12-week
study. The means (±SD) at week1 for participants‘ age, education level, body mass index
(BMI), waist circumference, maximum activity score, adjusted activity score, BpTRU
resting systolic and diastolic blood pressure, BpTRU resting heart rate and resting ratepressure-product are shown in Table 1. There were 18 menopausal and 32
postmenopausal women in the study sample. The control group consisted of 39%
menopausal and 61% postmenopausal women. The exercise group included 33%
menopausal and 67% postmenopausal women. At week 1, there was no significant
difference between the two groups. At week 12, BMI was lower in the Exercise group
compared to the control group (see page 62). See Appendix O for study sample and
reasons for attrition, Appendix P for other demographic data (marital status, employment
status) and Appendix Q for demographic, physiological and lifestyle Chisquared/ANOVA summary tables.
52
Table 1. Means (±SD) at week 1 for demographic, physiological and lifestyle measures in
both control and exercise group separately.
Measure
Control Group
Exercise Group
(n = 23)
(n = 27)
Age (years)
51.9 (5.8)
55.0 (7.2)
Education (years)
13.3 (2.5)
13.1 (2.4)
Body Mass Index (kg/m2)
34.9 (6.8)
32.6 (5.7)
Waist Circumference (inches)
41.9 (5.3)
40.8 (5.4)
Mean Activity Score
79.9 (5.9)
78.3 (6.8)
Adjusted Activity Score
68 (10.2)
63.7 (17.7)
Resting Systolic BP (mmHg)
130 (17)
137 (21)
Resting Diastolic BP (beats/min)
81 (10)
86 (13)
Resting HR (beats/min)
67(7)
67(10)
Resting Rate-Pressure-Product
9 (1)
9 (2)
((HR x systolic BP) x10-2)
Note. BP taken using BpTRU automated BP monitor.
BP = blood pressure; HR = heart rate; min = minute
53
Antihypertensive Medications
The majority of participants were taking at least one antihypertensive medication
during the 12 week study. Twenty of twenty-three women in the control group were on
antihypertensive medications; similarly 23 out of 27 in the exercise group were using
antihypertensive drugs. The exercise and control groups were counterbalanced by
medication type (beta blocker or no beta blocker). At week 1, there was no difference
between the two groups. See Table 2 for antihypertensive medication classification.
Table 2. Antihypertensive medication classification for both control and exercise group
separately.
Antihypertensive Medication
Control Group
Exercise Group
Classifications
(n = 23)
(n = 27)
Diuretics
1
1
Ace-Inhibitors
2
4
Angiotensin II Receptor Antagonist
3
2
Calcium Channel Blockers
1
0
Beta Blockers
5
3
Combination of ≥ 2 BP Medications
8
13
No BP Medications
3
4
Total:
23
27
Note. BP = blood pressure
54
BpTRU Blood Pressure and Heart Rate Measures over Time
BpTRU systolic BP, diastolic BP, heart rate (HR) and rate-pressure-product
(RPP) means (±SD) are shown at week 1 in Table 1. To test for the effects of exercise
conditioning, repeated measures ANOVA with two-between (Group– control, exercise;
Menopausal state- pre, post) and two-within (Time- week 1, week 12; Condition – rest,
standing, exercise) were performed to analyze changes in BpTRU BP, HR and RPP
between groups over the 12 week study period. See Appendix Q for ANOVA summary
tables for BpTRU BP, HR and RPP measures.
BpTRU Systolic BP. In the ANOVA performed on systolic BP data, there was a
significant main effect of Time, F(1,42) = 8.07, p<.01 and Condition, F(2, 84) = 51.79,
p<.001. The main effect of Time was qualified by a significant Time X Group
interaction, F(1,42) = 4.30, p<.05. See Figure 2 for the linear Time X Group interaction;
the exercise group experienced a significant reduction in systolic BP. See Figure 3 for the
linear main effect of Condition; when compared to rest, there was an increase in systolic
BP during standing and exercise. No other effects were found.
55
Figure 2. Mean systolic blood pressure as a function of time for the control and exercise
group separately.
Figure 3. Mean systolic blood pressure in three conditions for the control and exercise
group over time.
56
BpTRU Diastolic BP. In the ANOVA performed on diastolic BP data, there was a
significant Time X Group interaction, F(1, 42) = 7.97, p<.01 and a main effect of
Condition, F(2, 84) = 30.07, p<.001. See Figure 4 for the linear Time X Group
interaction; the Control group experienced a significant increase in diastolic BP over time
while the Exercise group experienced a significant decrease in diastolic BP over time.
See Figure 5 for the quadratic main effect of Condition; compared to rest, there was an
increase in diastolic BP during standing and exercise. No other effects were found.
57
Figure 4. Mean diastolic blood pressure as a function of time for the control and exercise
group separately.
Figure 5. Mean diastolic blood pressure in three conditions for the control and exercise
group separately.
58
BpTRU HR. In the ANOVA performed on HR data, there was a main effect of
Condition, F(2, 84) = 164.21, p<.001. The effect of condition which was qualified by a
Time X Condition interaction, F(2, 84) = 3.33, p<.05. See Figure 6 for the linear Time X
Condition interaction; compared to rest, there was an increase in HR during standing and
exercise. HR increased over time during standing compared with rest. No other effects
were found.
Figure 6. Mean heart rate in three conditions for week 1 and week 12.
59
BpTRU RPP. In the ANOVA performed on RPP data, there was a significant
Time X Group interaction, F(1, 42) = 5.71, p<.05 and a main effect of Condition, F(2,
84) = 152.27, p<.001. See Figure 7 for the linear Time X Group interaction; the exercise
group experienced a significant decrease in RPP over time. See Figure 8 for the linear
main effect of Condition; compared to rest, there was a significant increase in RPP during
standing and exercise. No other effects were found.
60
Figure 7. Mean Rate-Pressure-Product as a function of time for the control and exercise
group separately.
Figure 8. Mean Rate-Pressure-Product in three conditions for the control and exercise
group separately.
61
There was no correlation between BMI and BpTRU measures (systolic BP,
diastolic BP, HR and RPP). BMI (week 1, week 12) was examined by bivariate
correlation with the outcome measures. Further, age and menopausal state did not affect
any of the BpTRU measures (systolic BP, diastolic BP, HR and RPP). Age was examined
as a covariate and menopausal state was examined as a between-subjects factor.
62
Comparison of Body Mass Index and Waist Circumference over Time
Repeated measures ANOVA with one-between (Group– control, exercise) and
one-within (Time- week 1, week 12) were performed to examine BMI and waist
circumference. BMI measures demonstrated a significant Time X Group, F(1,44) = 9.34,
p<.01, interaction. See Figure 9 for linear Time X Group interaction. No significant
effects were found for waist circumference. At week 1, the control group had a mean
waist circumference of 41.9 (SD± 5.3) inches and the exercise group had a mean waist
circumference of 40.8 (SD±5.4) inches. At week 12, the control group had a mean waist
circumference of 42.5 (SD± 5.5) inches and the exercise group had a mean waist
circumference of 40.0 (SD±5.1) inches. No other effects were found.
Figure 9. Mean body mass index as a function of time for the control and exercise group
63
Heart Rate Variability Measures
Eleven out of 294 raw data files collected were missing when heart rate variability
(HRV) analysis was performed (4% of total). Five files corresponded to participants in
the control group and seven belonged to participants in the exercise group. Due to
skewness, outliers and unequal variation that existed in the raw HRV data, log
transformations were performed on low frequency (LF) power, high frequency (HF)
power, total power (TP), parasympathetic nervous system (PNS) indicator and
sympathetic nervous system (SNS) indicator to minimize the effect of extreme values.
Log transformed data was used for all HRV statistical analyses. Independent t-tests
determined that there were no significant differences between the two groups at week 1.
See Table 3 for HRV means (±SD) at week 1.
Repeated measures ANOVA with two-between factors (Group- exercise, control;
Menopausal state- pre, post) and two-within factors (Time- week 1, week 12; Conditionresting, standing, exercise) were performed on each HRV measure (LF, HF, TP, PNS
indicator and SNS indicator). See Appendix Q for ANOVA summary tables for all HRV
measures.
64
Table 3. Means (±SD) for log transformed heart rate variability measures for both
control and exercise group at week 1.
Time
Week 1
Group
Control
Exercise
(n=23)
(n=27)
Resting
1.94 (.37)
1.99 (.48)
Standing
2.07 (.37)
2.05 (.41)
Exercise
1.50 (.64)
1.43 (.73)
Resting
1.78 (.43)
1.81 (.52)
Standing
1.45 (.33)
1.42 (.53)
Exercise
1.33 (.69)
1.27 (.70)
Resting
2.57 (.32)
2.55 (.46)
Standing
2.56 (.30)
2.51 (.40)
Exercise
2.28 (.58)
2.41 (.66)
Low Frequency Power (ms2/Hz)
High Frequency Power (ms2/Hz)
Total Power (ms2/Hz)
PNS Indicator (HF/TP)
Resting
-.79 (.26)
-.74 (.24)
Standing
-1.11(.24)
-1.09 (.35)
Exercise
-.95 (.36)
-1.13 (.30)
Resting
.16 (.37)
.18 (.33)
Standing
.62 (.30)
.63 (.36)
Exercise
.17 (.23)
.16 (.20)
SNS Indicator (LF/HF)
Note. SNS = sympathetic nervous system; PNS = parasympathetic nervous system; ms =
milliseconds; m2/Hz = milliseconds squared per hertz; HF/TP = high frequency/ total
power; LF/HF = low frequency/ high frequency
65
Low Frequency Power. In the ANOVA performed on LF data, there was a
significant main effect of Condition, F(2, 72) = 16.57, p<.001, which was qualified by a
Time X Condition, F(2, 72) = 5.28, p<.01 interaction. There was also a significant main
effect of Menopause, F(1, 36) = 6.43, p<.05, between subjects. See Figure 10 for the
quadratic Time X Condition interaction; compared to rest, there was a significant
increase in LF power during standing and a decrease during exercise. LF power increased
over time during standing compared to rest. See Figure 11 for the linear main effect of
Menopause; LF power was lower in postmenopausal than menopausal women. No other
effects were found.
66
Figure 10. Mean of the log transformed low frequency power in three conditions as a
function of time.
Figure 11. Mean of the log transformed low frequency power as a function of
menopausal state.
67
High Frequency Power. In the ANOVA performed on HF data, there was a
significant main effect of Condition, F(2, 72) = 11.34, p<.001 and a Menopause X Group
interaction, F(1, 36) = 5.20, p<.05 between subjects. See Figure 12 for the quadratic main
effect of Condition; compared to rest, there was a significant decrease of HF power
during standing and exercise. See Figure 13 for the linear Menopause X Group
interaction; HF power was lower in the postmenopausal exercise group than the
postmenopausal control group. No other effects were found.
68
Figure 12. Mean of the log transformed high frequency power in three conditions for the
control and exercise group separately.
Figure 13. Mean of the log transformed high frequency power as a function of
menopausal state for the control and exercise group separately.
69
Total Power. In the ANOVA performed on TP data, there was a main effect of
Menopause, F(1, 36) = 4.28, p<.05, between subjects. See Figure 14 for the linear main
effect of Menopause; TP was lower in postmenopausal than Menopausal women. No
other effects were found.
Figure 14. Mean of the log transformed total power as a function of menopausal state.
70
PNS Indicator. In the ANOVA performed on PNS Indicator data, there was a
significant main effect of Condition, F(2, 72) = 33.34, p<.001, which was qualified by
Condition X Group interaction, F(2, 72) = 5.55, p<.01, and a Condition X Menopause
interaction, F(2, 72) = 3.94, p<.05, within subjects. See Figure 15 for the quadratic
Condition X Group interaction; the Exercise group experienced a decreased PNS
indicator compared to the Control group during steady-state exercise. See Figure 16 for
the quadratic Condition X Menopause interaction; postmenopausal women had lower
PNS indicator during rest and standing compared to menopausal women. No other effects
were found.
71
Figure 15. Mean of the log transformed PNS Indicator in three conditions for the control
and exercise group separately.
Figure 16. Mean of the log transformed PNS Indicator in three conditions for menopausal
and postmenopausal women separately.
72
SNS Indicator. In the ANOVA performed on SNS Indicator data, there was a
significant main effect of Condition, F(2, 72) = 50.29, p<.001 and a Condition X
Menopause X Group interaction, F(2, 72) = 5.24, p<.01, within subjects. See Figure 17
for the quadratic main effect of Condition; compared to rest, SNS indicator increased
during standing. See Figure 18 for the quadratic Condition X Menopause X Group
interaction. Postmenopausal women in control group had decreased SNS indicator during
rest and steady-state exercise compared to menopausal women in the control group.
Menopausal women in the exercise group demonstrated decreased SNS indicator during
rest compared to postmenopausal women in the exercise group.
Figure 17. Mean of the log transformed SNS Indicator in three conditions for the control
and exercise group separately.
73
To sort out the Condition X Menopause X Group interaction, a simple effects
analysis was conducted by separating the groups (Group- Exercise, Control; Menopausal
State- pre, post) and then repeating the analysis. For menopausal women in the Control
group, F(1, 7) = 8.44, p<.05, and postmenopausal women in the Control, F(1, 11) =
29.85, p<.001 and Exercise group, , F(1, 13) = 11.67, p<.01, there was a significant
increase in SNS indicator during standing. For menopausal women in the Exercise group,
there was a significant increase in SNS indicator during standing, F(1, 5) = 17.02, p<.01
and exercise, F(1, 5) = 19.22, p<.01. No other effects were found
74
a) Control Group
b) Exercise Group
Figure 18. Mean of the log transformed SNS Indicator in 3 conditions as a function of
menopausal state for a) control group and b) exercise group.
75
There was no correlation between BMI and HRV measures (LF, HF, TP, PNS
indicator, SNS indicator). BMI (week 1, week 12) was examined by bivariate correlation
with the outcome measures. Further, Age did not affect any of the BpTRU measures
(systolic BP, diastolic BP, HR and RPP). Age was examined as a covariate.
76
Baroreflex Measures
Eleven out of 294 raw data files collected were missing when HRV and
spontaneous baroreflex sensitivity analysis was performed (4% of total). Five files
corresponded to participants in the control group and seven belonged to participants in
the exercise group. Independent t-tests determined that there were no significant
differences between the Exercise and Control group at week 1. The means (±SD) for
spontaneous baroreflex sensitivity measures at week 1 are shown in Table 4.
Repeated measures ANOVA with two-between (Group- Exercise, Control;
Menopausal state- menopausal and postmenopausal) and two-within (Time- week 1,
week 12; Condition- resting, standing, exercise) were performed to examine the effects of
exercise conditioning on spontaneous baroreflex measures (slope, systolic BP, R-R
interval) between groups, over time.
77
Table 4. Means (±SD) for spontaneous baroreflex measures for in both control and
exercise group at week 1.
Time
Week 1
Group
Control
Exercise
(n=23)
(n=27)
Resting
6.38 (3.88)
6.55 (3.37)
Standing
3.16 (1.59)
3.12 (2.01)
Exercise
5.57 (5.13)
6.38 (4.70)
Resting
108 (36)
122 (28)
Standing
147 (27)
140 (25)
Exercise
157 (39)
169 (42)
Resting
882 (91)
897 (119)
Standing
776 (95)
764 (101)
Exercise
518 (99)
530 (74)
Baroreflex Slope
(ms/mmHg)
Systolic Finapres arterial
BP (mmHg)
R-R Interval (ms)
Note. BP = blood pressure; ms = milliseconds; mmHg = millimeters of mercury
78
Baroreflex Slope. In the ANOVA performed on baroreflex slope data, there was a
significant main effect of Condition, F(2, 72) = 12.16, p<.001. See Figure 19 for the
quadratic main effect of Condition; compared to rest, there was a decrease in baroreflex
slope during standing. No other effects were found.
Figure 19. Mean baroreflex slope in three conditions for the control and exercise group
separately.
79
Systolic Finapres Arterial BP. In the ANOVA performed on systolic BP data,
there was a significant main effect of Condition, F(2, 72) = 36.61, p<.001, which can be
qualified by a Time X Condition interaction, F(2, 72) = 4.87, p<.05 and a Condition X
Group interaction, F(2, 72) = 5.63, p<.01. See Figure 20 for the linear Time X Condition
interaction; compared to rest, there was a significant increase in systolic BP during
standing and steady-state exercise. Systolic BP decreased over time during standing and
steady-state exercise compared to rest. See Figure 21 for the quadratic Condition X
Group interaction; the Exercise group experienced a significant increase in systolic BP
during steady-state exercise compared to rest. No other effects were found.
80
Figure 20. Mean systolic Finapres arterial blood pressure in three conditions as a function
of time.
Figure 21. Mean systolic Finapres arterial blood pressure in three conditions for the
control and exercise group separately.
81
R-R Interval. In the ANOVA performed on R-R interval data, there was a
significant main effect of Condition, F(2, 72) = 372.49, p<. 001, and a there was a Time
X Condition X Menopause interaction, F(2, 72) = 3.31, p<.05. See Figure 22 for the
linear main effect of Condition; compared to rest, there was a decrease in R-R interval
during standing and steady-state exercise. See Figure 23 for the linear Time X Condition
X Menopause interaction; over time, R-R interval decreased significantly in
postmenopausal women during exercise compared with rest.
Figure 22. Mean R-R Interval in three conditions for the control and exercise group
separately.
82
To sort out the Time X Condition X Menopause interaction, a simple effects
analysis was conducted by separating the groups by menopausal state (menopausal,
postmenopausal) and then repeating the analysis. For menopausal women, there was a
significant decrease in R-R interval during standing, F(1, 12) = 93.03, p<.001, and
exercise, F(1, 12) = 269.95, p<.001, vs. rest. For postmenopausal women, there was a
significant decrease in R-R interval during standing, F(1, 24) = 194.69, p<.001, and
during exercise, F(1, 24) = 338.57, p<.001, vs. rest. Over time, there was a significant
Time X Condition interaction found during exercise in the postmenopausal group, F(1,
24) = 15.18, p<.001. R-R interval decreased during exercise compared with rest. No other
effects were found.
83
a) Menopausal Women
b) Postmenopausal Women
Figure 23. Mean R-R interval in 3 conditions as a function time for a) menopausal
women and b) postmenopausal women separately.
84
There was no correlation between BMI or age and spontaneous baroreflex
sensitivity (slope, systolic Finapres BP, R-R interval). BMI (week 1, week 12) was
examined by bivariate correlation. Age was examined as a covariate with the outcome
measures. R-R interval decreased over time during exercise compared with rest. No
effects were found.
Exercise Compliance
Volunteers for this study were required to be sedentary at week 1 (<2 exercise
sessions per week). Participants who were assigned to the exercise group were given a 12
week low-intensity walking program and asked to perform 5 sessions of structured low
intensity walking per week. Those who were assigned to the control group were asked to
maintain their current activity level for the 12 week study. Compliance to these
requirements was monitored with self report log books which were distributed at the
beginning of the study and collected at the end. There was a significant difference
between activity levels in the two groups; the exercise group participated in an average of
4.06 (±SD 1.55) walking sessions per week while the control group averaged 0.63 (±SD
1.06) walking sessions per week.
85
CHAPTER FIVE
Discussion
The purpose of this study was to test the effects of a low-intensity exercise
conditioning intervention on HR, BP, RPP, HRV and SBR sensitivity in hypertensive
women. Our results confirm that the low-intensity walking program lowers systolic and
diastolic BP and RPP in hypertensive women. Additionally, the low intensity exercise
conditioning program attenuated the physiological response to stress. This was evidenced
by decreased systolic and diastolic BP and RPP in the exercise group and increased
diastolic BP in the control group. These findings suggest that a conditioning effect was
achieved and can be attributed to the exercise intervention as there was an 81%
compliance rate among participants. This is the first study to report and statistically
account for the effects of a low-intensity exercise conditioning program on menopausal
and postmenopausal hypertensive women.
The results of this study support the hypothesis that a low-intensity exercise
conditioning program reduces systolic and diastolic BP and RPP in hypertensive women.
As expected, mean systolic and diastolic BP and RPP decreased after 12 weeks of lowintensity exercise. Women in the exercise group experienced a mean systolic BP
reduction of 10 mmHg, mean diastolic BP reduction of 5 mmHg and mean RPP reduction
of .96 . In contrast, women in the control group had a mean diastolic BP increase of 5
mmHg. This degree of BP and RPP reduction is statistically significant and clinically
relevant as it has been shown to decrease the incidence of coronary heart disease and
stroke (Cook, Cohen, Hebert, Taylor & Hennekens, 1995).
86
This degree of systolic BP reduction is consistent with previous findings for
hypertensive populations. Hua, Brown, Hains, Godwin & Parlow (in press) implemented
a similar exercise intervention with analogous methods of testing and analysis in the
same laboratory as the present study. After 40 men and women completed the 12 week
low intensity exercise program, they noted an 11 mmHg reduction in systolic BP. Davy et
al. (1997) studied eight sedentary postmenopausal women with either high normal BP or
hypertension as they participated in a 12 week moderate-intensity exercise program and
found a systolic BP reduction of 8 mmHg. Likewise, Moreau, et al. (2001) followed 24
postmenopausal hypertensive women through a 12 week moderate-intensity walking
program and revealed a 6 mmHg decrease in systolic BP with no change in diastolic BP.
By 24 weeks, systolic BP had decreased by an additional 5 mmHg. Hagberg, Park &
Brown (2000) reported analogous findings with low-to-moderate-intensity exercise,
describing a systolic BP reduction of 11 mmHg. Similarly, Ishikawa et al. (1999) asserted
comparable reductions in systolic (10 mmHg) BP in women aged 50-69 years after eight
weeks of low-intensity exercise. Slight variation exists among the above findings as
differences in the intensity and duration of exercise vary along with sample size. There
was no difference in systolic BP reduction between menopausal and postmenopausal
women. This is in contrast to a study done by Staessen, Bulpitt, Fagard, Lijnen & Amery
(1989) where a random sample (n=430) of normotensive and hypertensive women
revealed that postmenopausal women had higher systolic BP compared to menopausal
women. The present study may have not found comparable findings due to
antihypertensive medication use and homogenous hypertensive sample.
87
This degree of diastolic BP reduction is consistent with previous findings for
hypertensive populations. Hua et al. (in press) also found that a similar 12 week walking
program reduced diastolic BP by 5mmHg. Davy et al. (1997) found a similar reduction in
diastolic (5 mmHg) BP. Likewise, Hagberg et al. (2000) reported a diastolic BP reduction
of 8 mmHg and Ishikawa et al. (1999) asserted a diastolic reduction of 6 mmHg. This
magnitude of diastolic BP reduction has clinical implications for hypertensive women.
Cook et al. (1995) found that a 2 mmHg diastolic BP reduction produced a 6% decrease
in the incidence of coronary heart disease and a 15% decrease in the incidence of stroke.
Stamler, Stamler, Gosch, Civinelli, Fishman, McKeever et al. (1989) performed a five
year prospective study with men and women with high normal BP and found that the
incidence of hypertension could be decreased by 20-30% with a 1-3 mmHg reduction of
diastolic BP. These findings suggest that low-intensity exercise training is an essential
component of primary prevention of cardiovascular disease. The results clearly illustrate
the importance of physical activity in the treatment of hypertension.
A number of studies using moderate-to-high intensity exercise claim smaller
reductions in systolic BP than low-intensity regimes (Hagberg et al., 2000). Kelley
(1999) performed a meta-analysis of 10 randomized trials (n= 732 hypertensive women)
in which moderate intensity exercise lasting between 10-52 weeks reduced resting
systolic BP by 2% (~3 mmHg). Fagard (1995) performed a meta-analysis of 36 studies
evaluating moderate-to-high intensity exercise and reported a reduction of 5.3 mmHg for
systolic BP. This is consistent with the findings of Whelton et al. (2002). They reviewed
54 randomized controlled trials to evaluate the effect of moderate-to-high aerobic
exercise on BP and found an average decrease of 4 mmHg systolic BP. Cox, Burke,
88
Morton, Gillam, Beilin and Puddey (2001) found remarkably similar results in a
normotensive population. 126 normotensive women participated in an 18 month
moderate intensity exercise intervention and experienced a 2.81 mmHg reduction in
systolic BP.
In the present study, the exercise group showed a significant reduction in RPP.
RPP is an estimate of myocardial work load and gives an accurate indication of
myocardial oxygen consumption (Laaksonen, Kalliokoski, Luotolahti, Kemppainen,
Teras, Kyrolainen, et al., 2007). These findings suggest that low-intensity exercise
training decreases RPP and is consistent with previous findings (Nagpal, Walia, Lata,
Sood & Ahuja, 2007; Prakash et al., 2005). Jarrell, Hains, Kisilevsky & Brown (2005)
examined hemodynamic responses to exercise in men and women after early recovery
from myocardial infarction and documented decreased RPP in both genders. Kokkinos,
Andreas, Coutoulakis, Colleran, Narayan and Dotson (2002) found that unfit,
hypertensive women had a higher RPP than aerobically fit hypertensive women. The
literature does not specify a normative decrease in RPP for hypertensive women after an
exercise intervention. RPP is negatively affected by gender (female), increasing age and
BMI (Hui, Jackson & Wier, 2000).
Previous exercise conditioning studies done with men and women have reported
reductions in resting HR and increased R-R interval which indicate improved
parasympathetic modulation of the heart (Amano, Kanda, Ue & Moritani, 2001; Antelmi,
et al., 2004). The present study did not find a significant change in HR or R-R interval
between the Exercise and Control group. This could be attributed to gender differences
89
which were not detected in earlier studies. This study focused on women exclusively and
the results reflect previous research. Hua et al. (in press) implemented the same lowintensity walking program with a sample of hypertensive men and women. They reported
a decrease in resting HR in men but not women and an increased R-R interval in both
sexes. Davy et al. (1997) studied eight women with either high BP or hypertension and
found a comparable BP reduction and no change in resting HR or R-R interval. Similarly,
Ramaekers et al. (1998) studied a sample of 276 normotensive men and women and
found that R-R interval was lower in women compared to men. This is further supported
by Gregoire, Tuck, Yamamoto and Hughson (1996) and Ueno & Moritani, (2003), who
affirm that men experience a significantly greater mean R-R interval than women after an
exercise conditioning program. However, these studies are in contrast to those that report
greater parasympathetic activity in normotensive women compared to men (Carter et al.,
2003; Kuo et al., 1999).
There were no significant differences in HF power, TP, parasympathetic
indicator, sympathetic indicator, baroreflex slope or R-R interval between the exercise
and control group. Consistent with the literature, both groups experienced progressive
withdrawal of parasympathetic innervation in response to standing and submaximal
steady-state exercise (Macor, Fagard & Amery, 1996). However, the results of this study
indicate that participation in the low-intensity exercise conditioning program attenuated
physiological responses to stress in hypertensive women. This was demonstrated by a
significant decrease in systolic and diastolic BP and RPP in the exercise group and a
significant increase in diastolic BP in the control group during standing and at a given
low submaximal steady-state exercise test at week 12. These findings are consistent with
90
previous research which supports the use of exercise conditioning to suppress
sympathetic modulation induced by stress (Morimoto, Tan, Nishiyasu, Sone &
Murakami, 2000; Pagani, Somers, Furlan, Dell'Orto, Conway, Baselli et al., 1988).
It remains unclear as to what mechanism is responsible for the significant systolic
and diastolic BP reduction found in this study. Since HRV and SBR measures did not
change significantly, which would have been a clear indication of autonomic adaptation,
interpretation of the BP reduction can only be considered speculation. Sowers & Lester
(2000) suggest that hypertension and aging instigate structural and functional changes in
the peripheral vasculature causing increased peripheral vascular resistance and enhanced
vascular reactivity. These changes decrease beta-adrenergic responses to catecholamines
while leaving alpha-adrenergic responses intact, creating vasoconstriction of peripheral
vessels. Structural alteration of resistance arteries occur first, followed by endothelial
dysfunction and in some cases cardiac hypertrophy (Park & Schiffrin, 2001). Sivertsson
(1987) proposes that in addition to changes in vessel caliber, hypertension causes
thickening of the arterial walls. Furthermore, menopause appears to impair endothelial
vasodilation in normotensive and hypertensive women which potentiates increased
systolic BP (Staessen, Celis & Fagard, 1998; Taddei, Virdis, Ghiadoni, Mattei, Sudano,
Bernini, et al., 1996). Therefore, increased total peripheral resistance may contribute to
the etiology of hypertension.
Increased peripheral vascular resistance appears to decline with participation in
exercise. Support for this theory comes from Iwasaki et al. (2003). They calculated total
peripheral resistance through similutaneous measurement of HR and BP
91
(electrosphygmomanometry) at baseline and then at three, six, nine and twelve months of
moderate-intensity exercise. After three months, they credited a 10 mmHg decrease in
systolic BP to a 136 dynes x s x cm-5 reduction in total peripheral resistance. Exercise
conditioning also has been linked to increased vascularization of skeletal muscle,
peripheral vasodilation and increased tissue perfusion (Halliwill, Taylor, Hartwig &
Eckberg, 1996; Lesniak & Dubbert, 2001; Martin, Montgomery, Snell, Corbett, Sokolov,
Buckey, et al., 1987). These findings are noteworthy as they may be the mechanisms
which contributed to the systolic and diastolic BP reduction found in this study.
Eighteen menopausal and thirty-two postmenopausal women were involved in
this study. Counter-balanced allocation to either exercise or control group resulted in
equal distribution of menopausal women. There was a difference between menopausal
women and postmenopausal women in regard to HRV measures. Consistent with the
literature, postmenopausal women demonstrated decreased HF power and TP in
comparison to menopausal women. This is consistent with studies done with
normotensive menopausal and postmenopausal women. Our findings were remarkably
similar to those found by Farag, Bardwell, Nelesen, Dimsdale and Mills (2003). They
studied 18 menopausal women and 34 postmenopausal women without subjecting them
to an exercise program and found that postmenopausal women have increased
sympathetic, decreased parasympathetic activity and decreased R-R interval. However,
their findings were no longer significant when age was used as a covariate. Age did not
affect the findings of the present study. Brockbank, Chatterjee, Bruce and Woledge
(2000) and Rys, Kogut and Thor (2006) also documented decreased parasympathetic
innervation of HR and significant reductions in R-R interval in postmenopausal women.
92
The present study found that postmenopausal women showed lower LF power in
comparison to menopausal women. LF power has been hypothesized to be jointly
mediated by both the sympathetic and parasympathetic nervous system (Akselrod,
Gordon, Madwed, Snidman, Shannon & Cohen, 1985). It is possible to speculate that the
low-intensity exercise conditioning program caused a non significant decrease in
sympathetic activity in postmenopausal women as seen by lower LF power. These
findings may suggest that postmenopausal hypertensive women experience greater
benefits than menopausal women with a low-intensity exercise regime.
There were no significant differences in HRV or SBR sensitivity measures
between the exercise and control group. These findings do not support the hypothesis that
the low-intensity exercise conditioning program improves autonomic adaptation
(increased parasympathetic modulation of HR and decreased sympathetic indicator at
rest, standing and during submaximal steady-state exercise) in hypertensive women.
Previous low and moderate-intensity exercise conditioning studies done with
normotensive and hypertensive populations have also resulted in non-significant changes
in HRV and BRS sensitivity (Davy et al., 1997; Hua et al., in press; Loimaala, Huikuri,
Oja, Pasanen and Vuori, 2000; Reiling & Seals, 1988). Conversely, other studies have
demonstrated differences in HRV and SBR sensitivity after a low-moderate-intensity
exercise program (Amano et al., 2001; Malliani, Pagani, Lombardi, Furlan, Guzzetti &
Cerutti, 1991). Myslivecek et al. (2002) studied the effect of moderate-intensity exercise
on HRV and SBR function between pre and post menopausal normotensive women. They
found that pre and post menopausal women in the exercise group experienced higher
vagal modulation, lower sympathetic innervation and longer R-R intervals than the
93
sedentary control group. O'Sullivan and Bell (2000) demonstrated that chronic moderateintensity exercise training reduced sympathetic activity and increased the slope of the
arterial baroreflex. Iwasaki, Zhang, Zuckerman and Levine (2003) found that three
months of physical training increased HRV and SBR sensitivity in sedentary participants.
The quantity of exercise conditioning may have contributed to the non-significant
differences in HRV and SBR sensitivity between groups. The present study used previous
findings from Hua et al. (in press) in order to design a 12-week low-intensity exercise
conditioning program which could affect HRV and SBR sensitivity. Hua et al. (in press)
used the same low-intensity walking program as the present study but required that
participants perform 4 sessions of walking per week. After finding no significant
differences in HRV between the exercise and control group, they concluded that
hypertensive individuals may require a higher quantity of exercise to achieve a significant
difference between groups. However, they did find a significant increase in R-R interval
during submaximal steady-state exercise in men and women. The present study required
participants to complete five walking sessions per week in an attempt to document a
change in HRV and SBR sensitivity. This higher quantity of low-intensity exercise
conditioning did not produce the significant difference in HRV or SBR sensitivity
between the exercise and control group. Previous studies which have demonstrated an
improvement in cardiac autonomic function have implemented a moderate-intensity
exercise conditioning program (Davy et al., 1997; Myslivecek et al., 2002; Tuomainen et
al., 2005).
94
Participants in this study demonstrated an 81% compliance rate. Hawkins and
Hackett (1982) define a high compliance rate as participation in 67% of prescribed
exercise sessions. Women in the exercise group were asked to perform 5 sessions of
structured low-intensity walking per week. Participants recorded their exercise sessions
in a log book. The exercise group participated in an average of 4.06 (±SD 1.55) walking
sessions per week while the control group averaged 0.63 (±SD 1.06) walking sessions per
week. The significant reduction in systolic BP and RPP combined with a high compliance
rate suggests that the low-intensity walking program is an effective means for reducing
systolic BP and RPP.
Conclusions
This is the first study to report and statistically account for the influence of a lowintensity exercise conditioning program on cardiac and autonomic function in
menopausal and postmenopausal hypertensive women. The results of this study indicate
that a low-intensity exercise conditioning program lasting three months is sufficient to
reduce systolic and diastolic BP and RPP, but not adequate to influence cardiac
autonomic function in hypertensive women. Additionally, the low-intensity exercise
conditioning program attenuated the physiological response to stress. This was evidenced
by decreased systolic and diastolic BP and RPP in the exercise group and increased
diastolic BP in the control group. It was evident that menopausal and postmenopausal
women differ from each other in regard to cardiac autonomic function. Postmenopausal
women demonstrated greater sympathetic activity in comparison to menopausal women.
Postmenopausal women had decreased HF power and TP. However, postmenopausal
95
women demonstrated a significant reduction in LF power compared to menopausal
women. This may indicate that the low-intensity exercise program fosters autonomic
adaption in postmenopausal women. The implication of such a finding may suggest that
menopausal state should direct exercise prescription. There is a need for further research
in this area. This study was accomplished by high compliance rates among participants.
The findings of this study show that walking is an effective activity for menopausal and
postmenopausal hypertensive women to lower systolic and diastolic BP, RPP and
attenuate physiological responses to stress.
96
References
Abrams, A.C. (2004). Antihypertensive Drugs. Clinical Drug Therapy: Rationales for
Nursing Practice (pp. 797-831). Philadelphia: Lippincott Williams & Wilkins.
Akselrod, S., Gordon, D., Madwed, J.B., Snidman, N.C., Shannon, D.C., & Cohen,
R.J. (1985). Hemodynamic regulation: investigation by spectral analysis.
American Journal of Physiology. 249(4 Pt 2), H867-75.
Akselrod, S., Gordon, D., Ubel, F. A., Shannon, D. C., Berger, A. C., & Cohen. R. J.
(1981). Power spectrum analysis of heart rate fluctuation: a quantitative probe
of beat-to-beat cardiovascular control. Science. 213, 220-2.
Amano, M., Kanda, T., Ue, H., & Moritani, T. (2001). Exercise training and
autonomic nervous system activity in obese individuals. Medicine & Science
in Sports & Exercise, 33(8), 1287-91.
Amara, C.E., & Wolfe, L.A. (1998). Reliability of noninvasive methods to measure
cardiac autonomic function. Canadian Journal of Applied Physiology.
23(4), 396-408.
American College of Sports Medicine (ACSM). (2000). Guidelines for Graded
Exercise Testing and Prescription. 6th Ed. Philadelphia: Lippincott, Williams
and Wilkins.
Antelmi, I., de Paula, R.S., Shinzato, A.R., Peres, C.A., Mansur, A.J., & Grupi. C.J.
(2004). Influence of age, gender, body mass index, and functional capacity on
97
heart rate variability in a cohort of subjects without heart disease. American
Journal of Cardiology, 93(3), 381-5.
Arai, Y., Saul, J.P., Albrecht, P., Hartley, L.H., Lilly, L.S., Cohen, R.J., & Colucci,
W.S. (1989). Modulation of cardiac autonomic activity during and
immediately after exercise. American Journal of Physiology. 256(1 Pt 2),
H132-41.
Asikainen, T.M., Kukkonen-Harjula, K., & Miilunpalo, S. (2004). Exercise for health
for early postmenopausal women: a systematic review of randomized
controlled trials. Sports Medicine. 34(11), 753-78.
Batulevicius, D., Skripka, V., Pauziene, N., & Pauza, D.H. (2008). Topography of the
porcine epicardiac nerve plexus as revealed by histochemistry for
acetylcholinesterase. Autonomic Neuroscience-Basic & Clinical. 138(1-2), 64-75.
Berne, R. M., & Levy, M. N. (2001). Cardiovascular Physiology (8th ed.).St Louis,
MO: Mosby, Inc.
Bilek, L. D., Venema, D. M., Camp, K. L., Lyden, E. R. & Meza, J. L. (2005).
Evaluation of the human activity profile for use with persons with arthritis.
Arthritic care and research. 53(5): 756-763.
Blaber, A.P., Yamamoto, Y. & Hughson, R.L. (1995). Methodology of spontaneous
baroreflex relationship assessed by surrogate data analysis. American Journal
of Physiology. 268(4 Pt 2), H1682-7.
98
Black, H.R., Elliott, W.J., Neaton, J.D., Grandits, G, Grambsch, P., Grimm, R. et al.
(2001). Baseline characteristics and early blood pressure control in the
CONVINCE trial. Hypertension. 37:12–18.
Borg, G. A. (1982). Psychophysical bases of perceived exertion. Medicine & Science
in Sports & Exercise. 14(5), 377-8.
Borg, G. (1998). Perceived exertion and pain scales. Human Kinetics Publishers,
Champaign, Illinois.
Brenner, I.K., Thomas, S., & Shephard, R.J. (1998). Autonomic regulation of the
circulation during exercise and heat exposure. Inferences from heart rate
variability. Sports Medicine. 26(2):85-99.
Brockbank, C.L., Chatterjee, F., Bruce, S.A., & Woledge, R.C. (2000). Heart rate and
its variability change after the menopause. Experimental Physiology, 85(3),
327-30.
Brown, C. A., Laschinger, S., Hains, S., & Parry, M. (1992). Discharge functional
capacity and self-efficacy after coronary artery bypass graft surgery.
Canadian Journal of Cardiovascular Nursing. 3(203), 18-24.
Brown, C.A., Wolfe, L.A., Hains, S., Pym, J., & Parker, J.O. (1994). Early low
intensity home exercise after coronary artery bypass graft surgery. Journal of
Cardiopulmonary Rehabilitation, 14(4), 238-45.
Brown, C. A., Wolfe, L. A., Haines, S., Ropchan, G., & Parlow, J. (2003).
Spontaneous baroreflex sensitivity after coronary artery bypass graft surgery
99
as a function of gender and age. Canadian Journal of Physiology
Pharmacology, 81(9), 894-902.
Brown, T.E., Beightol, L.A., Koh, J., & Eckberg, D.L. (1993). Important influence of
respiration on human R-R interval power spectra is largely ignored. Journal of
Applied Physiology, 75(5), 2310-7.
Buckworth, J., Dishman, R. K., & Cureton, K. J. (1994). Autonomic responses of
women with parental hypertension. Effects of physical activity and fitness.
Hypertension, 24(5), 576-84.
Cade, R., Mars, D., Wagemaker, H., Zauner, C., Packer, D., Privette, M., Cade, M.,
Peterson, J., & Hood-Lewis, D. (1984). Effect of aerobic exercise training on
patients with systemic arterial hypertension. American Journal of Medicine,
77(5):785-90.
Campbell, N.R., Burgess, E., Choi, B.C., Taylor, G., Wilson, E., Cleroux, J., Fodor,
J.G., Leiter, L.A., & Spence, D. (1999). Lifestyle modifications to prevent and
control hypertension. CMAJ Canadian Medical Association Journal, 160(9
Suppl), S1-6.
Canadian Hypertension Education Program (2007). The 2007 Canadian Hypertension
Education Program recommendations: the scientific summary - an annual
update.Canadian Journal of Cardiology, 23(7), 521-7.
Canadian Society for Exercise Physiology [CSEP] (2002). Physical Activity
Readiness Questionnaire. Retrieved April 22nd 2007 from
100
http://www.csep.ca/communities/c574/files/hidden/pdfs/par-q.pdf
Carter, J.B., Banister, E.W., & Blaber, A. P. (2003). Effect of endurance exercise on
autonomic control of heart rate. Sports Medicine, 33, 33-46.
Chiu, H.W., Wang, T.H., Huang, L.C., Tso, H.W., & Kao, T. (2003). The influence
of mean heart rate on measures of heart rate variability as markers of
autonomic function: a model study. Medical Engineering & Physics, 25(6),
475-81.
Chobanian, A.V., Bakris, G.L., Black, H.R., Cushman, W.C., Green, L.A. et al.
(2003). Joint National Committee on Prevention, Detection, Evaluation, and
Treatment of High Blood Pressure. National Heart, Lung, and Blood Institute.
National High Blood Pressure Education Program Coordinating Committee.
Seventh report of the Joint National Committee on Prevention, Detection,
Evaluation, and Treatment of High Blood Pressure. Hypertension, 42(6),
1206-52.
Cleroux, J., Feldman, R.D., & Petrella, R.J. (1999). Lifestyle modifications to prevent
and control hypertension. Recommendations on physical exercise training.
Canadian Medical Association Journal, 160(9 Suppl), S21-8.
Cleroux, J., Kouame, N., Nadeau, A., Coulombe, D., & Lacourciere, Y. (1992).
After effects of exercise on regional and systemic hemodynamics in
hypertension. Hypertension, 19(2), 183-91.
Cook, N.R., Cohen, J., Hebert, P.R., Taylor, J.O., & Hennekens, C.H. (1995).
101
Implications of small reductions in diastolic blood pressure for primary
prevention. Archives of Internal Medicine, 155(7), 701-9.
Cooke, W. H., Cox, J. F., Diedrich, A. M., Taylor, J. A., Beightol, L.A., Ames, J. E.
et al. (1998). Controlled breathing protocols probe human autonomic
cardiovascular rhythms. American Journal of Physiology, 274(2 Pt2 ), H709H718.
Corrao, J.M., Becker, R.C., Ockene, I. S., & Hamilton, G. A. (1990). Coronary heart
disease risk factors in women. Cardiology, 77, 8-12.
Cotran, R. S., Kumar, V., & Collins, T. (1999). Blood vessels. Robbins pathologic
basis of disease (pp. 511-514). Pennsylvania: W.B. Saunders Company.
Cox, K. L., Burke, V., Morton, A. R., Gillam, H. F., Beilin, L. J., & Puddey, I. B.
(2001). Long-term effects of exercise on blood pressure and lipids in healthy
women aged 40±65 years: The Sedentary Women Exercise Adherence Trial
(SWEAT). Journal of Hypertension, 19, 1733-1743.
Dabrowska, B., Dabrowski, A., & Skrobowski, A. (1996). Parasympathetic
withdrawal precedes spontaneous blood pressure elevations in women with
primary hypertension. Cardiology, 87(2), 119-24.
Dampney, R. A. L. (1994). Functional organization of central pathways regulating the
cardiovascular system. Physiological Reviews, 74, 323-364.
Daniels, J. W., Molé, P. A., Shaffrath, J. D., & Stebbins, C. L. (1998). Effects of
caffeine on blood pressure, heart rate, and forearm blood flow during dynamic
102
leg exercise Journal of Applied Physiology, 85, 154-159.
Daughton, D., Fix, A., Kass, I., Bell, W., & Patil, K. (1982). Maximum oxygen
consumption and the ADAPT Quality-of-Life Scale. Arch Phys Med
Rehabilitation, 63, 620-22.
Davidson, M., & de Morton, N. (2007). A systematic review of the Human Activity
Profile. Clinical Rehabilitation, 21(2), 151-62.
Davy, K.P., Miniclier, N.L., Taylor, J.A., Stevenson, E.T., & Seals, D.R. (1996).
Elevated heart rate variability in physically active postmenopausal women: a
cardioprotective effect? American Journal of Physiology, 271(2 Pt 2), H45560.
Davy, K.P., Willis, W.L., & Seals, D.R. (1997). Influence of exercise training on
heart rate variability in post-menopausal women with elevated arterial blood
pressure. Clinical Physiology, 17(1), 31-40.
Doll, S., Paccaud, F., Bovet, P., Burnier, M., & Wietlisbach, V. (2002). Body mass
index, abdominal adiposity and blood pressure: consistency of their association
across developing and developed countries. International
Journal of Obesity & Related Metabolic Disorders: Journal of the International
Association for the Study of Obesity, 26(1), 48-57.
Dougherty, J. (1999). The Autonomic Modulation of Heart Rate in Healthy MiddleAged Adults. Unpublished master‘s thesis, Queen‘s University, Kingston,
Ontario, Canada.
103
Dubbert, P.M., Martin, J.E., Cushman, W.C., Meydrech, E.F., & Carroll, R.G. (1994).
Endurance exercise in mild hypertension: effects on blood pressure and associated
metabolic and quality of life variables. Journal of Human Hypertension, 8(4),
265-72.
Eaker, E., Chesebro, J.H., Sacks, F.M., Wenger, N.K., Whisnant, J.P., & Winston, M.
(1994). Special report: cardiovascular disease in women. Heart Disease &
Stroke. 3(2), 114-9.
Eckberg, D.L. (1980). Parasympathetic cardiovascular control in human disease: a
critical review of methods and results. American Journal of Physiology.
239(5), H581-93.
Egan, P. (2006). Exercise, too little of a good thing. Cleveland Clinic. Retrieved
November 12, 2006, from http://www.clevelandclinic.org.
Eguchi, K., Tomizawa, H., Ishikawa, J., Hoshide, S., Fukuda, T., Numao, T.,
Shimada, K., & Kario, K. (2007). Effects of new calcium channel blocker,
azelnidipine, and amlodipine on baroreflex sensitivity and ambulatory blood
pressure. Journal of Cardiovascular Pharmacology, 49(6), 394-400.
Esler, M., & Kaye, D. (2000). Sympathetic nervous system activation in essential
hypertension, cardiac failure and psychosomatic heart disease. Journal of
Cardiovascular Pharmacology, 35(7 Suppl 4), S1-7.
Fadel, P.J., Ogoh, S., Keller, D.M., & Raven, P.B. (2003). Recent insights into carotid
baroreflex function in humans using the variable pressure neck chamber.
104
Experimental Physiology, 88(6), 671-80.
Fagard, R.H. (1995). Prescription and results of physical activity. Journal of
Cardiovascular Pharmacology, 25 Suppl 1, S20-7.
Fagard, R., Thijs, L., & Amery, A. (1993). Age and hemodynamic response to
posture in non-elderly hypertensive patients. American Journal of Geriatric
Cardiology, 2, 23-40.
Fagard, R.H. (1995). The role of exercise in blood pressure control: supportive
evidence. Journal of Hypertension, 13(11), 1223-7.
Farag, N.H., Bardwell, W.A., Nelesen, R.A., Dimsdale, J.E., & Mills, P.J. (2003).
Autonomic responses to psychological stress: the influence of menopausal
status. Annals of Behavioral Medicine, 26(2), 134-8.
Fei, L., Anderson, M.H., Statters, D.J., Malik, M., & Camm, A.J. (1995). Effects of
passive tilt and submaximal exercise on spectral heart rate variability in
ventricular fibrillation patients without significant structural heart disease.
American Heart Journal, 129(2), 285-90.
Franchi, F., Lazzeri, C., La Villa, G., Barletta, G., Del Bene, R., & Buzzelli, G.
(1998). Cardiac autonomic modulation and incidence of late potentials in
essential hypertension: role of age, sex, ventricular mass and remodeling.
Journal of Human Hypertension, 12(1), 13-20.
Freeman, J.V., Dewey, F.E., Hadley, D.M., Myers, J., & Froelicher, V.F. (2006).
Autonomic nervous system interaction with the cardiovascular system during
105
exercise. Progress in Cardiovascular Diseases, 48(5), 342-62.
Gobel, F.L., Norstrom, L.A., Nelson, R.R., Jorgensen, C.R., & Wang, Y. (1978). The
rate-pressure product as an index of myocardial oxygen consumption during
exercise in patients with angina pectoris. Circulation, 57(3), 549-56.
Goldberger, A.L. (1991). Is the normal heartbeat chaotic or homeostatic?. News in
Physiological Sciences, 6, 87-91.
Goldsmith, R.L., Bigger, J.T., Bloomfield, D.M., & Steinman, R.C. (1997). Physical
fitness as a determinant of vagal modulation. Medicine & Science in Sports &
Exercise, 29(6), 812-7.
Greendale, G.A., Lee, N.P., & Arriola, E.R. (1999). The menopause. Lancet.
353(9152), 571-80.
Gregoire, J., Tuck, S., Yamamoto, Y., & Hughson. R.L. (1996). Heart rate variability
at rest and exercise: influence of age, gender, and physical training. Canadian
Journal of Applied Physiology, 21(6), 455-70.
Guyenet, P.G. (2006). The sympathetic control of blood pressure. Nature Reviews
Neuroscience, 7(5), 335-46.
Hagberg, J.M., Park, J.J., & Brown, M.D. (2000). The role of exercise training in the
treatment of hypertension: an update. Sports Medicine, 30(3), 193-206.
Haggenmiller, C., Baumert, J.H., Adt, M., & Frey, A.W. (1996). Modulation of
respiratory sinus arrhythmia by breathing pattern. Clinical Science, 91, 40-2.
Hainsworth, R. (1996). The physiological approach to cardiovascular reflexes.
106
Clinical Science, 91, 43-9.
Halliwill, J.R., Taylor, J.A., Hartwig, T.D., & Eckberg, D.L. (1996). Augmented
baroreflex heart rate gain after moderate-intensity, dynamic exercise.
American Journal of Physiology, 270(2 Pt 2), R420-6.
Hayano, J., Mukai, S., Sakakibara, M., Okada, A., Takata, K., & Fujinami, T. (1994).
Effects of respiratory interval on vagal modulation of heart rate. American
Journal of Physiology. 267(1 Pt 2), H33-40.
Healthy Ontario (2005). Hypertension. Retrieved March 19th 2007 from
http://www.healthyontario.com.
Heart and Stroke Foundation of Canada (1999). The Changing Face of Heart
Disease and Stroke in Canada. Retrieved October 20th 2006 from
www.phac-aspc.gc.ca/ccdpc-cpcmc/cvdmcv/publications/pdf/card2ke.pdf
Heart and Stroke Foundation of Canada [HSFC] (2007). Heart Disease. Retrieved
March 20th 2007 from http://ww2.heartandstroke.ca/
Heart and Stroke Foundation of Canada [HSFC] .(2007). 2007 Report on Canadians‘
Health. Retrieved March 23rd 2007 from http://ww2.heartandstroke.ca/
Heart and Stroke Foundation of Canada [HSFC]. (2008). Small increase in activity
benefits obese, overweight women. Retrieved March 17th 2008 from
http://www.heartandstroke.com.
Heart and Stroke Foundation of Canada. [HSFC]. (2008). Statistics.
107
Retrieved May 6, 2008 from
www.heartandstroke.com/site/c.ikIQLcMWJtE/b.3483991/k.34A8/Statistics
Hillsdon, M., Foster, C. & Thorogood, M. (2006). Interventions for promoting
physical activity. Cochrane Database of Systematic Reviews, (1),CD003180.
Hirsch, J.A., & Bishop, B. (1981). Respiratory sinus arrhythmia in humans: how
breathing pattern modulates heart rate. American Journal of Physiology 241
(Heart and Circulatory Physiology, 10, H620-H629.
Hua, L. P. T., Brown, C. A., Hains, S., Godwin, & Parlow, J. (in press) Effects of low
intensity exercise conditioning on blood pressure, heart rate and cardiac
autonomic function in men and women with mild hypertension. Unpublished
master‘s thesis, Queen‘s University, Kingston, Ontario, Canada.
Hughson, R. L., Northey, D. R., Xing, H. C., Dietrich, B. H., & Cochrane, J. E.
(1991). Alignment of ventilation and gas fraction for breath-by-breath
respiratory gas exchange calculations in exercise. Computers and Biomedical
Research, 24, 118-128.
Hughson, R. L., Quintin, L., Annat, G., Yamamoto, Y., & Gharib, C. (1993).
Spontaneous baroreflex by sequence and power spectral methods in humans.
Clinical Physiology, 13, 663-676.
Hui, S.C., Jackson, A.S., & Wier, L.T. (2000). Development of normative values for
resting and exercise rate pressure product. Medicine & Science in Sports &
Exercise, 32(8), 1520-7.
108
Huikuri, H.V., Pikkujamsa, S.M., Airaksinen, K.E., Ikaheimo, M.J., Rantala, A.O.,
Kauma, H., Lilja, M., & Kesaniemi, Y.A. (1996). Sex-related differences in
autonomic modulation of heart rate in middle-aged subjects. Circulation,
94(2), 122-5.
Iellamo, F., Legramante. J.M., Raimondi, G., & Peruzzi, G. (1997). Baroreflex
control of sinus node during dynamic exercise in humans: effects of central
command and muscle reflexes. American Journal of Physiology, 272(3 Pt 2),
H1157-64.
Iellamo, F., Legramante, J.M., Massaro, M., Raimondi, G., & Galante A. (2000).
Effects of a residential exercise training on baroreflex sensitivity and heart
rate variability in patients with coronary artery disease: A randomized,
controlled study. Circulation, 102(21), 2588-92.
Imholz, B.P., van Montfrans, G.A., Settels, J.J., van der Hoeven, G.M.,
Karemaker, J.M., & Wieling, W. (1988). Continuous non-invasive blood pressure
monitoring: reliability of Finapres device during the Valsalva manoeuvre.
Cardiovascular Research, 22(6), 390-7.
Imholz, B. P. M., Wieling, W., van Montfrans, G. A., & Wesseling, K. H. (1998).
Fifteen years experience with finger arterial pressure monitoring: assessment
of the technology. Cardiovascular Research, 38, 605–616.
Irigoyen, M.C., Paulini, J., Flores, L.J., Flues, K., Bertagnolli, M., Moreira, E.D.,
Consolim-Colombo, F., Bello-Klein, A., & De Angelis, K. (2005). Exercise
109
training improves baroreflex sensitivity associated with oxidative stress
reduction in ovariectomized rats. Hypertension, 46(4), 998-1003.
Ishikawa, K., Ohta, T., Zhang, J., Hashimoto, S. & Tanaka H. (1999). Influence of
age and gender on exercise training-induced blood pressure reduction in
systemic hypertension. American Journal of Cardiology, 84(2), 192-6.
Iwane, M., Arita, M., Tomimoto, S., Satani, O., Matsumoto, M., Miyashita, K., &
Nishio. (2000). Walking 10,000 steps/day or more reduces blood pressure and
sympathetic nerve activity in mild essential hypertension. Hypertension
Research - Clinical & Experimental. 23(6), 573-80.
Iwasaki, K., Zhang, R., Zuckerman, J.H., & Levine, B.D. (2003). Dose-response
relationship of the cardiovascular adaptation to endurance training in healthy
adults: how much training for what benefit? Journal of Applied Physiology,
95(4), 1575-83.
Izdebska, E., Cybulska, I., Izdebskir, J., Makowiecka-Ciesla, M., & Trzebski, A.
(2004). Effects of moderate physical training on blood pressure variability and
hemodynamic pattern in mildly hypertensive subjects. Journal of Physiology
& Pharmacology, 55(4), 713-24.
Jarrell, L.A., Hains, S.J., Kisilevsky, B.S., & Brown, C.A. (2005). Gender differences
in functional capacity following myocardial infarction: an exploratory study.
Canadian Journal of Cardiovascular Nursing, 15(1), 28-33.
Jensen-Urstad, K., Storck, N., Bouvier, F., Ericson, M., Lindblad, L.E., & Jensen-
110
Urstad, M. (1997). Heart rate variability in healthy subjects is related to age
and gender. Acta Physiologica Scandinavica, 160(3), 235-41.
Joyner, M.J. (2006). Baroreceptor function during exercise: resetting the record.
Experimental Physiology, 91(1), 27-36.
Julius, S., & Majahalme, S. (2000). The changing face of sympathetic overactivity in
hypertension. Annuals of Medicine, 32(5), 365-70.
Jurca, R., Church, T.S., Morss, G.M., Jordan, A.N., & Earnest, C.P. (2004). Eight
weeks of moderate-intensity exercise training increases heart rate variability
in sedentary postmenopausal women. American Heart Journal, 147(5), e21.
Kaftan, A. H., & Kaftan, O. (2000). Qt intervals and heart rate variability in
hypertensive patients. Japanese Heart Journal, 41, 173-182.
Kamath, M.V., Fallen, E.L., & McKelvie, R. (1991). Effects of steady state exercise
on the power spectrum of heart rate variability. Medicine & Science in Sports
& Exercise, 23(4), 428-34.
Kappel, F., Fink, M., & Batzel, J.J. (2007). Aspects of control of the cardiovascularrespiratory system during orthostatic stress induced by lower body negative
pressure. Mathematical Biosciences. 206(2), 273-308.
Kardos, A., Watterich, G., de Menezes, R., Csanády, M., Casadei, B., & Rudas, L.
(2008). Determinants of spontaneous baroreflex sensitivity in a healthy
working population. Hypertension, 37, 911-916.
Kelemen, M.H., Effron, M.B., Valenti, S.A., & Stewart, K.J. (1990). Exercise
111
training combined with antihypertensive drug therapy. Effects on lipids, blood
pressure, and left ventricular mass. JAMA, 263(20), 2766-71.
Kelley, G. A. (1999). Aerobic exercise and resting blood pressure among women; A
Meta-analysis. Preventive Medicine, 28, 264–275.
Ketch, T., Biaggioni, I., Robertson, R., & Robertson, D. (2002). Four faces of
baroreflex failure: hypertensive crisis, volatile hypertension, orthostatic
tachycardia, and malignant vagotonia. Circulation, 105(21), 2518-23.
Ketelhut, R.G., Franz, I.W., & Scholze, J. (2004). Regular exercise as an effective
approach in antihypertensive therapy. Medicine & Science in Sports &
Exercise, 36(1), 4-8.
Kokkinos, P.F., Andreas, P.E., Coutoulakis, E., Colleran, J.A., Narayan, P., Dotson,
C.O., Choucair, W., Farmer, C., & Fernhall, B. (2002). Determinants of
exercise blood pressure response in normotensive and hypertensive women:
role of cardiorespiratory fitness. Journal of Cardiopulmonary Rehabilitation,
22(3), 178-83.
Kokkinos, P., Chrysohoou, C., Panagiotakos, D., Narayan, P., Greenberg, M., & Singh,
S. (2006). Beta-blockade mitigates exercise blood pressure in
hypertensive male patients. Journal of the American College of Cardiology,
47(4), 794-8.
Kolbe-Alexander, T. L., Lambert, E. V., & Charlton, K. E. (2006). Effectiveness of a
community based low intensity exercise program for older adults. Journal of
112
Nutrition. 10(1), 21-9.
Kollai, M., & Mizsei, G. (1990). Respiratory sinus arrhythmia is a limited measure of
cardiac parasympathetic control in man. Journal of Physiology, 424, 329-42.
Kosch, M., Hausberg, M., Barenbrock, M., Kisters, K., & Rahn. K.H. (1999). Studies
on cardiac sympathovagal balance and large artery distensibility in patients
with untreated essential hypertension. Journal of Human Hypertension, 13(5),
315-9.
Kuo, T.B., Lin, T., Yang, C.C., Li, C.L., Chen, C.F., & Chou, P. (1999). Effect of
aging on gender differences in neural control of heart rate. American Journal
of Physiology, 277(6 Pt 2), H2233-9.
Laaksonen, M.S., Kalliokoski, K.K., Luotolahti, M., Kemppainen, J., Teras, M.,
Kyrolainen, H., Nuutila, P., & Knuuti, J. (2007). Myocardial perfusion during
exercise in endurance-trained and untrained humans. American Journal of
Physiology - Regulatory Integrative & Comparative Physiology, 293(2),
R837-43.
Labrova, R., Honzikova, N., Maderova, E., Vysocanova, P., Novakova, Z., Zavodna,
E. et al. (2005). Age-dependent relationship between the carotid intimamedia thickness, Baroreflex sensitivity, and the inter-beat interval in
normotensive and hypertensive subjects. Physiology Research, 54(6), 593600.
Lackland, D.T. (2005). Racial disparities in hypertension. Journal of Clinical
113
Hypertension, 7(9), 500-2.
La Rovere, M.T., Bersano, C., Gnemmi, M., Specchia, G., & Schwartz, P.J. (2002).
Exercise-induced increase in baroreflex sensitivity predicts improved
prognosis after myocardial infarction. Circulation, 106(8), 945-9.
Laitinen, T., Hartikainen, J., Vanninen, E., Niskanen, L., Geelen, G., & Lansimies, E.
(1998). Age and gender dependency of baroreflex sensitivity in healthy
subjects. Journal of Applied Physiology, 84(2), 576-83.
Lee, L.L., Avis, M., & Arthur A. (2007). The role of self-efficacy in older peoples
decisions to initiate and maintain regular walking as exercise -- Findings from
a qualitative study. Preventive Medicine, 45(1), 62-5.
Leicht, A.S., Allen, G.D., & Hoey, A.J. (2003). Influence of intensive cycling training
on heart rate variability during rest and exercise. Canadian Journal of
Applied Physiology, 28(6), 898-909.
Lellamo, F., Legramante, J. M., Raimondi, G., Filippo, C., Massaro, M., & Peruzzi,
G. (1996). Evaluation of reproducibility of spontaneous baroreflex sensitivity
at rest and during laboratory tests. Journal of Hypertension, 4, 1099-1104.
Lesniak, K. T. & Dubbert, P. M. (2001). Exercise and hypertension. Current Opinion
in Cardiology, 16(6), 356-359.
Lewis, M.J. (2005). Heart rate variability analysis: a tool to assess cardiac autonomic
function. CIN: Computers, Informatics, Nursing, 23(6), 335-41.
Liao, D., Cai, J., Barnes, R.W., Tyroler, H.A., Rautaharju, P., Holme, I., & Heiss,
114
G. (1996). Association of cardiac autonomic function and the development of
hypertension: the ARIC study. American Journal of Hypertension,
9(12 Pt 1), 1147-56.
Lipsitz, L.A., Mietus, J., Moody, G.B., & Goldberger, A.L. (1990). Spectral
characteristics of heart rate variability before and during postural tilt.
Relations to aging and risk of syncope. Circulation, 81(6), 1803-10.
Lochner, J., Rugge, B., Judkins, D., & Saseen, J. (2006). Clinical inquiries: How
effective are lifestyle changes for controlling hypertension?. Journal of
Family Practice, 55(1), 73-4.
Loimaala, A., Huikuri, H., Oja, P., Pasanen, M., & Vuori, I. (2000). Controlled 5month aerobic training improves heart rate but not heart rate variability or
baroreflex sensitivity. Journal of Applied Physiology, 89(5), 1825-1829.
McAuley, E. et al. (2003). Predicting long term maintenance of physical activity in
older adults. Preventative Medicine, 37 (2), 110-8.
Maddens, M., Imam, K., & Ashkar, A. (2005). Hypertension in the elderly. Primary
Care; Clinics in Office Practice, 32(3), 723-53.
Maeda, S., Tanabe, T., Otsuki, T., Sugawara, J., Ajisaka, R., & Matsuda, M. (2008).
Acute exercise increases systemic arterial compliance after 6-month exercise
training in older women. Hypertension Research - Clinical & Experimental,
31(2), 377-81.
Macor, F., Fagard, R., & Amery, A. (1996). Power spectral analysis of RR interval
115
and blood pressure short-term variability at rest and during dynamic exercise:
comparison between cyclists and controls. International Journal of Sports
Medicine, 17, 175-181.
Magosso, E., Biavati, V., & Ursino, M. (2001). Analysis of cardiovascular instability
by a mathematical model of baroreflex control. Engineering in Medicine and
Biology Society, 1, 596- 599.
Malik, M., & Camm, A. J. (1995). The control and physiological importance of heart
rate. Heart rate variability (pp.3-20). New York : Futura Publishing Company.
Malliani, A., Pagani, M., Lombardi, F., Furlan, R., Guzzetti, S., & Cerutti S. (1991).
Spectral analysis to assess increased sympathetic tone in arterial hypertension.
Hypertension, 17(4 Suppl), III36-42.
Manfrini, O., Pizzi, C., Viecca, M., & Bugiardini, R. (2008). Abnormalities of cardiac
autonomic nervous activity correlate with expansive coronary artery remodeling.
Atherosclerosis, 197(1), 183-9.
Martin, J.E., & Dubbert, P.M. (1987). The role of exercise in preventing and
moderating blood pressure elevation. Bibliotheca Cardiologica, 41, 120-42.
Martin, W.H, Montgomery, J., Snell, P.G., Corbett, J.R., Sokolov, J.J., Buckey, J.C.,
Maloney, D.A., & Blomqvist, C.G. (1987). Cardiovascular adaptations to
intense swim training in sedentary middle-aged men and women. Circulation,
75(2), 323-30.
Mattu, G. S., Heran, B. S., & Wright, J. M. (2004). Overall accuracy of the BpTRU-
116
an automated electronic blood pressure device. Blood Pressure Monitoring, 9,
47–52.
McArdle, W. D., Katch, F. I., & Katch, V. K. (2007). Exercise Physiology, Maryland:
Lippincott Williams & Wilkins.
Milicevic G. (2005). Low to high frequency ratio of heart rate variability spectra fails
to describe sympatho-vagal balance in cardiac patients. Collegium
Antropologicum, 29(1), 295-300.
Miller, E.R. 3rd., Erlinger, T.P., Young, D.R., Jehn, M., Charleston, J., Rhodes, D.,
Wasan, S.K., & Appel, L.J. (2002). Results of the Diet, Exercise, and Weight
Loss Intervention Trial (DEW-IT), Hypertension. 40(5), 612-8.
Miller, W. C., Wayne, C., Wallace, J. P., & Eggert, K. E. (1993). Predicting max HR
and the HR relationship for exercise prescription in obesity. Medicine &
Science in Sports & Exercise, 25(9), 1077-1081.
Minami, N., Mori, N., Nagasaka, M., Ito, O., Kurosawa, H., Kanazawa, M., Kaku, K.,
Lee, E., & Kohzuki, M. (2006). Mechanism behind augmentation in
baroreflex sensitivity after acute exercise in spontaneously hypertensive rats.
Hypertension Research - Clinical & Experimental, 29(2), 117-22.
Moreau, K.L., Degarmo, R., Langley, J., McMahon, C., Howley, E.T., Bassett, D.R.
Jr., & Thompson, D.L. (2001). Increasing daily walking lowers blood pressure in
postmenopausal women. Medicine & Science in Sports & Exercise, 33(11), 182531.
117
Morimoto, K., Tan, N., Nishiyasu, T., Sone, R., & Murakami, N. (2000).
Spontaneous wheel running attenuates cardiovascular responses to stress in
rats. Pflugers Archiv - European Journal of Physiology, 440(2), 216-22.
Mussalo, H., Vanninen, E., Ikaheimo, R., Laitinen, T., Laakso, M., Lansimies, E., &
Hartikainen J. (2001). Heart rate variability and its determinants in patients
with severe or mild essential hypertension. Clinical Physiology, 21(5), 594604.
Myredal, A., Gao, S., Friberg, P., Jensen, G., Larsson, L., & Johansson M. (2005).
Increased myocardial repolarization lability and reduced cardiac baroreflex
sensitivity in individuals with high-normal blood pressure. Journal of
Hypertension, 23(9), 1751-6.
Myslivecek, P. R., Brown, C. A., & Wolfe, L. A. (2002). Effects of Physical
Conditioning on Cardiac Autonomic Function in Healthy Middle-Aged
Women. Canadian Journal of Applied Physiology, 27(1), 1-18.
Nagpal, S., Walia, L., Lata, H., Sood, N., & Ahuja, G.K. (2007). Effect of exercise on
rate pressure product in premenopausal and postmenopausal women with
coronary artery disease. Indian Journal of Physiology & Pharmacology,
51(3), 279-83.
Nakamura, Y., Yamamoto, Y., & Muraoka, I. (1993). Autonomic control of heart rate
during physical exercise and fractal dimension of heart rate variability.
Journal of Applied Physiology, 74(2), 875-81.
118
Neff, R. A., Wang, J., Baxi, S., Evans, C., & Mendelowitz, D. (2003). Respiratory
sinus arrhythmia: endogenous activation of nicotinic receptors mediates
respiratory modulation of brainstem cardioinhibitory parasympathetic
neurons. Circulation, 93, 565-572.
Ogoh, S., Fisher, J.P., Fadel, P.J., & Raven, P.B. (2007). Increases in central blood
volume modulate carotid baroreflex resetting during dynamic exercise in
humans. Journal of Physiology, 581(Pt 1), 405-18.
Ohisa, N., Hashimoto, J., Yoshida, K., Imai, Y., & Kaku M. (2005). The
relationships between autonomic function and heart rate in essential
hypertension. Rinsho Byori Japanese Journal of Clinical Pathology, 53(3),
195-200.
O'Leary, D.S., & Seamans, D.P. (1993). Effect of exercise on autonomic mechanisms
of baroreflex control of heart rate. Journal of Applied Physiology, 75(5),
2251-7.
O'Sullivan, S.E. & Bell, C. (2000). The effects of exercise and training on human
cardiovascular reflex control. Journal of the Autonomic Nervous System, 81(1-3),
16-24.
Pagani, M., Lombardi, F., Guzzetti, S., Rimoldi, O., Furlan, R., Pizzinelli, P.,
Sandrone, G., Malfatto, G., Dell'Orto, S., & Piccaluga, E. (1986). Power
spectral analysis of heart rate and arterial pressure variabilities as a marker of
sympatho-vagal interaction in man and conscious dog. Circulation Research,
119
59(2), 178-93.
Pagani, M., & Lucini, D. (2001). Autonomic dysregulation in essential hypertension:
insight from heart rate and arterial pressure variability. Autonomic
Neuroscience-Basic & Clinical, 90(1-2), 76-8.
Pagani, M., Somers, V., Furlan, R., Dell'Orto, S., Conway, J., Baselli, G., Cerutti, S.,
Sleight, P., & Malliani, A. (1988). Changes in autonomic regulation induced
by physical training in mild hypertension. Hypertension, 12(6), 600-10.
Panfilov, V., Morris, A.D., Donnelly, R., Scemama, M., & Reid, J.L. (1995). The
effects of rilmenidine and atenolol on mental stress, dynamic exercise and
autonomic function in mild to moderate hypertension. British Journal of
Clinical Pharmacology, 40(6), 563-9.
Parati, G., & Lantelme, P. (2005). Mechanical and neural components of the cardiac
baroreflex: new insights into complex physiology. Journal of Hypertension,
23(4), 717-20.
Park, J.B., & Schiffrin, E.L . (2001). Small artery remodeling is the most prevalent
(earliest?) form of target organ damage in mild essential hypertension. Journal
of Hypertension, 19(5), 921-30.
Parlow, J., Viale, J. P., Annat, G., Hughson, R., & Quintin, L. (1995). Spontaneous
cardiac baroreflex in humans. Comparison with drug-induced responses.
Hypertension, 25, 1058-1068.
120
Passino, C., Franzoni, F., Gabutti, A., Poletti, R., Galetta, F., & Emdin, M. (2004).
Abnormal ventricular repolarization in hypertensive patients: role of
sympatho-vagal imbalance and left ventricular hypertrophy. International
Journal of Cardiology, 97(1), 57-62.
Pelosi, G.G., Tavares, R. F., Antunes-Rodrigues, J., & Correa, F. M. (2008).
Cardiovascular responses to noradrenaline microinjection in the ventrolateral
periaqueductal gray of unanesthetized rats. Journal of Neuroscience Research,
86(3), 712-9.
Pepper, M.G., & Crawley, B.E. (1985). Calculation and display of the rate/pressure
product during anaesthesia using binary rate multipliers. Medical & Biological
Engineering & Computing, 23(2), 187-9.
Perini, R., Orizio, C., Milesi, S., Biancardi, L., Baselli, G., & Veicsteinas. (1993).
Body position affects the power spectrum of heart rate variability during
dynamic exercise. European Journal of Applied Physiology & Occupational
Physiology, 66(3), 207-13.
Petretta, M., Bonaduce, D., de Filippo, E., Mureddu, G.F., Scalfi, L., Marciano, F.,
Bianchi, V., Salemme, L., de Simone, G., & Contaldo, F. (1995). Assessment
of cardiac autonomic control by heart period variability in patients with earlyonset familial obesity. European Journal of Clinical Investigation, 25(11),
826-32.
Piccirillo, G., Germano, G., Vitarelli, A., Ragazzo, M., di Carlo, S., De Laurentis, T.,
121
Torrini, A., Matera, S., Magnanti, M., Marchitto, N., Bonanni, L., & Magri.
D. (2006). Autonomic cardiovascular control and diastolic dysfunction in
hypertensive subjects. International Journal of Cardiology, 110(2), 160-6.
Pichot, V., Roche, F., Gaspoz. J.M., Enjolras, F., Antoniadis, A., Minini, P. et al.
(2000). Relation between heart rate variability and training load in middledistance runners. Medicine & Science in Sports & Exercise, 32(10), 1729-36.
Pichon, A., Roulaud M., Antoine-Jonville, S., de Bisschop, C., & Denjean, A. (2006).
Spectral analysis of heart rate variability: interchangeability between
autoregressive analysis and fast Fourier transform. Journal of
Electrocardiology, 39(1), 31-37.
Pomeranz, B., Macaulay, R.J., Caudill, M.A., Kutz, I., Adam, D., Gordon, D.,
Kilborn, K.M., Barger, A.C., Shannon, D.C., Cohen, R.J. et al. (1985).
Assessment of autonomic function in humans by heart rate spectral analysis.
American Journal of Physiology, 248(1 Pt 2), H151-3.
Potts, J.T., Shi, X.R., & Raven, P.B. (1993). Carotid baroreflex responsiveness during
dynamic exercise in humans. American Journal of Physiology, 265(6 Pt 2),
H1928-38.
Prakash, E.S., Madanmohan, Sethuraman K.R., & Narayan, S.K. (2005).
Cardiovascular autonomic regulation in subjects with normal blood pressure,
high-normal blood pressure and recent-onset hypertension. Clinical &
Experimental Pharmacology & Physiology, 32(5-6), 488-94.
122
Public Health Agency of Canada (1998). Economic Burden of Illness in Canada.
Retrieved October 20th 2006 from http://www.phac-aspc.gc.ca/publicat/ebicfemc98/index.html
Radcliffe, A. (2000). Physical activity and hypertension. Sportex Health, 14, 11-14.
Raine, N.M., & Cable, N.T. (1999). A simplified paired neck chamber for the
demonstration of baroreflex blood pressure regulation. American Journal of
Physiology, 277(6 Pt 2), S60-6.
Ramaekers, D., Ector, H., Aubert, A.E., Rubens, A., & Van de Werf, F. (1998). Heart
rate variability and heart rate in healthy volunteers. Is the female autonomic
nervous system cardioprotective? European Heart Journal, 19(9), 1334-41.
Raven, P.B., Fadel, P.J., & Smith, S..A. (2002). The influence of central command on
baroreflex resetting during exercise. Exercise and Sport Sciences Reviews,
30, 39-44.
Reiling, M. J., & Seals, D. R. (1988). Respiratory sinus arrhythmia and carotid
baroreflex control of heart rate in endurance athletes and untrained controls.
Clinical Physiology, 8(5), 511-519.
Richardson, T., Rozkovec, A., Thomas, P., Ryder, J., Meckes, C., & Kerr, D. (2004).
Influence of caffeine on heart rate variability in patients with long standing
type 1 diabetes. Diabetes Care, 27, 1127-1131.
123
Rimoldi, O., Pagani, M. R., Piazza, S., Pagani, M., & Malliani, A. (1994). Restraining
effects of captopril on sympathetic excitatory responses in dogs: a spectral
analysis approach. American Journal of Physiology, 267, H1608-18.
Robertson, R. J., & Noble, B. J. (1997). Perception of physical exertion: methods,
mediators, and applications. Exercise and sport sciences reviews, 25, 407-52.
Rosano, G.M., & Panina, G. (1999). Oestrogens and the heart. Therapie, 54(3),
381-5.
Rudas, L., Crossman, A.A., Morillo, C.A., Halliwill, J.R., Tahvanainen, K.U.,
Kuusela, T.A., & Eckberg, D.L. (1999). Human sympathetic and vagal
baroreflex responses to sequential nitroprusside and phenylephrine. American
Journal of Physiology, 276(5 Pt 2), H1691-8.
Ryan, S.M., Goldberger, A.L., Pincus, S.M., Mietus, J., & Lipsitz, L.A. (1994).
Gender- and age-related differences in heart rate dynamics: are women more
complex than men?. Journal of the American College of Cardiology, 24(7),
1700-7.
Rys, A., Rys, A., Kogut, P., & Thor, P.J. (2006). Menopausal changes in circadian
heart rate variability. Folia Medica Cracoviensia, 47(1-4), 69-78.
Sabaté, E. (2003). Adherence to Long term Therapies: Evidence for Action. World
Health Organization, 1- 212.
Sakuragi, S., & Sugiyama, Y. (2006). Effects of Daily Walking in Subjective
Symptoms, Mood and Autonomic Nervous Function. Journal of Physiological
124
Anthropology, 25, 281-289.
Sandrone, G., Mortara, A., Torzillo, D., La Rovere, M.T., Malliani, A., & Lombardi,
F. (1994). Effects of beta blockers (atenolol or metoprolol) on heart rate
variability after acute myocardial infarction. American Journal of Cardiology,
74(4), 340-5.
Sayers, B M. (1973). Analysis of heart rate variability. Ergonomics, 16(1), 17-32.
Schrezenmaier, C., Singer, W., Swift, N.M., Sletten, D., Tanabe, J., & Low, P.A.
(2007). Adrenergic and vagal baroreflex sensitivity in autonomic failure. Archives
of Neurology, 64(3), 381-6.
Sears, S. R., & Stanton, A. L. (2001). Expectancy-value constructs and expectancy
violation as predictors of exercise adherence in previously sedentary women.
Health Psychology, 20(5), 326-33.
Sevre, K., Lefrandt, J.D., Nordby, G., Os, I., Mulder, M., Gans, R.O., Rostrup, M., &
Smit, A.J. (2001). Autonomic function in hypertensive and normotensive
subjects: the importance of gender. Hypertension, 37(6), 1351-6.
Shi, X., Schaller, F.A., Tierney, N., Chanthavong, P., Chen, S., Raven, P.B., & Smith,
M.L. (2008). Physically active lifestyle enhances vagal-cardiac function but
not central autonomic neural interaction in elderly humans. Experimental
Biology & Medicine, 233(2), 209-18.
Shimazu, T., Tamura, N., & Shimazu, K. (2005). Aging of the autonomic nervous
system. Nippon Rinsho - Japanese Journal of Clinical Medicine, 63(6), 973-7.
125
Silva, G.J., Brum, P.C., Negrao, C.E., & Krieger, E.M. (1997). Acute and chronic
effects of exercise on baroreflexes in spontaneously hypertensive rats.
Hypertension, 30(3 Pt 2):714-9.
Silverthorn, D. U. (2001). Efferent peripheral nervous system: The autonomic
and somatic motor divisions. Human Physiology (pp.326-339). New Jersey:
Prentice-Hall.
Singh, J. P., Larson, M. G., Tsuji, H., Evans, J. C., O'Donnell, C. J., & Levy, D.
(1998).Reduced heart rate variability and new-onset hypertension: Insights
into pathogenesis of hypertension: The Framingham Heart Study.
Hypertension, 32, 293-297.
Sivertsson, R. (1987). Structural adaptation of the cardiovascular system in
hypertension. Hemodynamic consequences of vascular wall hypertrophy.
Nephron, 47 Suppl 1, 71-5.
Sluijs, E.M., Kok, G.J., & van der Zee, J. (1993). Correlates of exercise compliance
in physical therapy. Physical Therapy, 73(11), 771-86.
Smit, A.A., Wieling, W., & Karemaker, J.M. (1996). Clinical approach to
cardiovascular reflex testing. Clinical Science, 91 Suppl, 108-12.
Souza, H. C., Ballejo, G., Salgado, M.C., Da Silva, S. V., & Salgado, H. C. (2001)
Cardiac sympathetic overactivity and decreased baroreflex sensitivity in LName hypertensive rats. American Journal of Physiology-Heart and
Circulatory Physiology, 280, H844-H850.
126
Sowers, J.R., & Lester, M. (2000). Hypertension, hormones, and aging. Journal of
Laboratory & Clinical Medicine, 135(5), 379-86.
Spina, R. J. (1999). Cardiovascular adaptations to endurance exercise training in older
men and women. Exercise and Sport Sciences Reviews, 27, 317-332.
Staessen, J., Bulpitt, C.J., Fagard, R., Lijnen, P., & Amery, A. (1989). The influence
of menopause on blood pressure. Journal of Human Hypertension, 3(6), 42733.
Staessen, J.A., Celis, H., & Fagard, R. (1998). The epidemiology of the association
between hypertension and menopause. Journal of Human Hypertension, 12(9),
587-92.
Stamler, R., Stamler, J., Gosch, F.C., Civinelli, J., Fishman, J., McKeever, P.,
McDonald, A., & Dyer, A.R. (1989). Primary prevention of hypertension by
nutritional-hygienic means. Final report of a randomized, controlled trial.
JAMA, 262(13), 1801-7.
Stein, P.K., Ehsani, A.A., Domitrovich, P.P., Kleiger, R.E., & Rottman, J.N. (1999).
Effect of exercise training on heart rate variability in healthy older adults.
American Heart Journal, 138(3 Pt 1), 567-76.
Stejskal, P., Rechbergova, J., Salinger, J., Slachta, R., Elfmark, M., Kalina, M., et al.
(2001). Power spectral of heart rate variability in exercising humans: The
effect of exercise intensity. Sports Medicine Training and Rehabilitation,
10(1), 39-57.
127
Stewart, K.J., Effron, M.B., Valenti, S.A., & Kelemen, M.H. (1990). Effects of
diltiazem or propranolol during exercise training of hypertensive men.
Medicine & Science in Sports & Exercise, 22(2), 171-7.
Stratton, J. R., Levy, W.C., Cerqueira, M.D., Schwartz, R.S., & Abrass, I. B. (1994).
Cardiovascular responses to exercise. Effects of aging and exercise training in
healthy men. Circulation. 89(4), 1648-1655.
Sugawara, J., Inoue, H., Hayashi, K., Yokoi, T., & Kono, I. (2004). Effect of lowintensity aerobic exercise training on arterial compliance in postmenopausal
women. Hypertension Research - Clinical & Experimental, 27(12), 897-901.
Swansburg, M. L., Brown, C. A., Hains, S. M., Smith, G.N., & Kisilevsky, B. S.
(2005). Maternal cardiac function and fetal heart rate in preeclamptic
compared to normotensive pregnancies. Canadian Journal of Cardiovascular
Nursing, 15(3), 42-52.
Taddei, S., Virdis, A., Ghiadoni, L., Mattei, P., Sudano, I., Bernini, G., Pinto, S., &
Salvetti, A. (1996). Menopause is associated with endothelial dysfunction in
women. Hypertension, 28(4), 576-82.
Taha, B.H., Simon, P.M., Dempsey, J.A., Skatrud, J.B., & Iber, C. (1995).
Respiratory sinus arrhythmia in humans: an obligatory role for vagal feedback
from the lungs. Journal of Applied Physiology, 78(2), 638-45.
Takase, B., Abe, Y., Nagata, M., Matsui, T., Hattori, H., Ohsuzu, F., Ishihara, M., &
Kurita, A. (2005). Effect of betaxolol hydrochloride on heart rate variability
128
indices during exercise stress testing in patients with hypertension.
Biomedicine & Pharmacotherapy, 59 (Suppl 1), S158-62.
Task Force of the European Society of Cardiology and the North American Society of
Pacing and Electrophysiology. (1996). Heart rate variability: Standards of
measurement, physiological interpretation, and clinical use. European Heart
Journal, 17, 354-381.
Taylor, D.G., & Kowalski, T.E. (1984). Comparison of calcium channel inhibitors on
vagal heart rate responses elicited by arterial baroreceptor reflexes in
anesthetized dogs. Journal of Pharmacology & Experimental Therapeutics,
228(2), 491-9.
Thayer, J. F., & Lane, R. D. (2007) The role of vagal function in the risk for
cardiovascular disease and mortality. Biological Psychology, 74(2), 224-42.
Tuomainen, P., Peuhkurinen, K., Kettunen, R., & Rauramaa, R. (2005). Regular
physical exercise, heart rate variability and turbulence in a 6 year randomized
controlled trial in middle aged men: The DNASCO study. Life Sciences,
77(21), 2723-2734.
Ueno, L.M., & Moritani, T. (2003). Effects of long-term exercise training on cardiac
autonomic nervous activities and baroreflex sensitivity. European Journal of
Applied Physiology, 89(2), 109-14.
Vasan, R.S., Beiser, A., Seshadri, S., Larson, M.G., Kannel, W.B., D'Agostino, R.B.,
& Levy, D. (2002). Residual lifetime risk for developing hypertension in
129
middle-aged women and men: The Framingham Heart Study. JAMA, 287(8),
1003-10.
Wallace, J. P. (2003). Exercise in hypertension. A clinical review. Sports Medicine,
33(8), 585-98.
West, John F. (2005). Respiratory physiology: the essentials (pp. 127-8). Hagerstwon,
MD: Lippincott Williams & Wilkins.
Whelton, S.P., Chin, A., Xin, X., & He, J. (2002). Effect of aerobic exercise on blood
pressure: a meta-analysis of randomized, controlled trials. Annals of Internal
Medicine, 136(7), 493-503.
Williams, P.T. (2008). Reduced diabetic, hypertensive, and cholesterol medication
use with walking. Medicine & Science in Sports & Exercise, 40(3), 433-43.
Wolf-Maiser, K., Cooper, R. S., Banegas, J. R., et al (2003). Hypertension Prevalence
and Blood Pressure Levels in 6 European Countries, Canada and the United
States. JAMA, 289, 2363-9.
World Health Organization (2002). The World Health Report. Geneva, Switzerland:
World Health Organization.
World Health Organization (2006). Physical Inactivity Prevalence – leisure timeCanada by age group. Retrieved October 21st, 2006 from
http://www.who.infobase.int
Yamamoto, Y., Hughson R. L., & Peterson, J.C. (1991). Autonomic control of heart
rate during exercise studied by heart rate variability spectral analysis. Journal
130
of Applied Physiology, 71(3), 1136-42.
131
Appendix A
Queen’s University
RESEARCH INFORMATION CONSENT FORM
Title of Project: Effects of low intensity exercise conditioning on blood pressure, heart
rate, rate-pressure-product and cardiac autonomic modulation in hypertensive women
Background Information:
You are being invited to participate in a research study directed by Dr. Ann
Brown, RN, Ph.D, to evaluate the effects of a 12 week walking program on high blood
pressure. Catherine Baines, BScN, RN MSc (c), will read through this consent form with
you and describe procedures in detail and answer any questions you may have.
Details of the Study:
Aim of the study:
The aim of this study is to determine the extent to which low intensity exercise
conditioning will decrease your blood pressure. You will be considered eligible to
participate in the study if you are a woman with hypertension (as diagnosed by your
family physician), are a non smoker, do not perform regular physical exercise more than
twice per week, are between 45-65 years of age, not taking hormone replacement therapy
and not diagnosed with stroke or heart disease. You may be assigned to either an exercise
group or a non-exercise group.
Description of visits and tests to be performed as part of the study:
The study involves your participation for two sessions in a research laboratory at
Hotel Dieu Hospital, at the beginning and at the end of the 12 week study period. Your
blood pressure will be measured while you are resting on a cot for 10 minutes, while you
stand for 10 minutes and while you are performing light exercise on an exercise bike for
5 minutes. The first session will take an hour and a half and the second session will last
45 mins.
If you are assigned to the 12 week walking program, we will provide you with an
explanation, written instructions and materials for the low intensity walking program.
If you are assigned to the control group, you will be asked to avoid changing your
current level of activity for the duration of the study. At the end of 12 weeks, you will be
provided with an explanation, written instructions and materials to carry out the walking
program.
132
All participants will be asked to refrain from making dietary changes or changes
in exercise that differ from the study‘s guidelines for 12 weeks.
The principal investigator will be calling you every three weeks to monitor
progress and answer questions.
Risks/Side Effects:
Risks:
There are unlikely to be any physical risks associated with the walking program
or the low intensity exercise testing protocol. Nevertheless, all volunteers will have to
complete the Physical Activity Readiness Questionnaire (PAR-Q) as a condition of
eligibility for participation in the study. Physician approval must be obtained for
participants if they answered ―yes‖ to one of seven questions on the PAR-Q. Participants
will have blood pressure and heart rate monitored continuously during the testing and
will be taught to take their own pulse during exercise. It is possible that this level of
exercise will not reduce your blood pressure. Similarly, patients in the non-exercise group
will not be using this form of lifestyle change to reduce blood pressure for the study
duration. However, at the end of the 12 weeks of their participation, they will be provided
with the same information given to the exercise group.
Emergency contact persons: If any untoward symptoms occur during exercise, please
contact your family physician or local emergency department to obtain the appropriate
treatment advice. Please contact the study investigators (either Catherine Baines (613544-3400 ext. 2473) or Dr Ann Brown, School of Nursing, 613-533-4480, ext 74763) to
inform them of your symptoms.
Benefits:
For participants in the exercise group, there may be a reduction in your blood
pressure by the end of 12 weeks. For those in the non exercise group, there may be no
direct benefits. Indirect benefits for each group include contributing to the knowledge
base that could benefit themselves or other people with high blood pressure in the future.
Confidentiality:
All information obtained during the course of this study is strictly confidential and
your anonymity will be protected at all times. All of the information collected will be
identified using a coding system. All data will be stored in locked files and will be
available only to Catherine Baines and Dr Ann Brown. There is a possibility that your
medical record, including identifying information, may be inspected by regulatory
agencies in the course of carrying out regular government functions. You will not be
identified in any publications or reports.
133
Alternative Therapies:
At this time, your Family Physician has recommended lifestyle change and/or
medication as methods of reducing your blood pressure. Exercise is one of the lifestyle
changes that are normally recommended. Other lifestyle changes may include changes in
your diet or a decrease in your stress level.
Voluntary nature of study/Freedom to withdraw or participate:
Your participation in this study is voluntary. You may withdraw from this study at
any time, for any reason. Your withdrawal will not affect your present/future medical
care with your Family Physician or at Hotel Dieu Hospital.
Withdrawal of subject by principle investigator:
The study investigators may decide to withdraw you from this study if your
Family Physician wishes to change your medical treatment or if you experience
symptoms during exercise or during testing.
Liability:
In the event that you are injured as a result of the study procedures, medical care
will be provided to you until resolution of the medical problem. By signing this consent
form, you do not waive your legal rights nor release the investigator(s) and sponsors from
their legal and professional responsibilities.
134
SUBJECT STATEMENT AND SIGNATURE SECTION:
I have read and understand the consent form for this study. I have had purposes,
procedures and technical language of this study explained to me. I have been given
sufficient time to consider the above information and seek advice if I chose to do so. I
have had the opportunity to ask questions which have been answered to my satisfaction. I
am voluntarily signing this form. I will receive a copy of this consent form for my
information. The results of my tests may be made available to my family physician. My
family physician may also be contacted if there are any significant health related issues
that occur during the study. If at any time I have further questions, problems or adverse
events, I can contact
Principal Investigator:
Catherine Baines, BScN, RN, MSc (c) at 613-544-3400 ext 2473 or Dr Ann Brown PhD,
Queen‘s School of Nursing at 613-533-6000 ext 74763
Or
Department Head:
Dr. C. Baker, Director, Queen‘s School of Nursing at 613-533-2668
or
If I have questions regarding my rights as a research subject I can contact
Dr. Albert Clark, Chair, Research Ethics Board at 613-533-6081
By signing this consent form, I am indicating that I agree to participate in this study.
------------------------------
-----------------------------------
Signature of Participant
Date
Statement of Investigator:
I have carefully explained to the subject the nature of the above research study. I certify
that, to the best of my knowledge, the subject understands clearly the nature of the study
and demands, benefits, and risks involved to participants in this study.
-------------------------------------------
-------------------------------------------
Signature of Principal Investigator
Date
135
Appendix B
Physical Activity Readiness Questionnaire
Regular physical activity is fun and healthy, and increasingly more people are starting
to become more active every day. Being more active is very safe for most people.
However, some people should check with their doctor before they start becoming much
more physically active. If you are planning to become much more physically active than
you are now, start by answering the seven questions in the box below. If you are between
the ages of 15 and 69, the PAR-Q will tell you if you should check with your doctor
before you start. If you are over 69 years of age, and you are not used to being very
active, check with your doctor. Common sense is your best guide when you answer these
questions. Please read the questions carefully and answer each one honestly: check YES
or NO.
1. Has your doctor ever said that you have a heart condition and that you
should only do physical activity recommended by a doctor?
2. Do you feel pain in your chest when you do physical activity?
3. In the past month, have you had chest pain when you were not doing physical
activity?
4. Do you lose your balance because of dizziness or do you ever lose
consciousness?
5. Do you have a bone or joint problem (for example, back, knee or hip) that
could be made worse by a change in your physical activity?
6. Is your doctor currently prescribing drugs (for example, water pills) for your
blood pressure or heart condition?
7.
Do you know of any other reason why you should not do physical activity?
If answered YES to any of the above questions, tell your fitness or health
professional. Ask whether you should change your physical activity plan. Talk with your
doctor by phone or in person BEFORE you start becoming much more physically active
or BEFORE you have a fitness appraisal. Tell your doctor about the PAR-Q and which
questions you answered YES. You may be able to do any activity you want — as long as
you start slowly and build up gradually. Or, you may need to restrict your activities to
those which are safe for you. Talk with your doctor about the kinds of activities you wish
to participate in and follow his/her advice.
136
If you answered NO honestly to all PAR-Q questions, you can be reasonably sure that
you can: start becoming much more physically active; begin slowly and build up
gradually. This is the safest and easiest way to go.
Take part in a fitness appraisal, this is an excellent way to determine your basic
fitness so that you can plan the best way for you to live actively. It is also highly
recommended that you have your blood pressure evaluated. If your reading is over
144/94, talk with your doctor before you start becoming much more physically active.
DELAY BECOMING MUCH MORE ACTIVE; if you are not feeling well because of a
temporary illness such as a cold or a fever, wait until you feel better; or if you are or may
be pregnant, talk to your doctor before you start becoming more active.
PLEASE NOTE: If your health changes so that you then answer YES to any of the above
questions, tell you fitness or health professional. Ask whether you should change your
physical activity plan.
Informed Use of the PAR-Q: The Canadian Society for Exercise Physiology, Health
Canada, and their agents assume no liability for persons who undertake physical activity,
and if in doubt after completing this questionnaire, consult your doctor prior to physical
activity.
―I have read, understood and completed this questionnaire. Any questions I had were
answered to my full satisfaction."
NAME: _________________________________________________________________
SIGNATURE:____________________________________________________________
DATE:__________________________________________________________________
SIGNATURE OF PARENT WITNESS or GUARDIAN (for participants under the age of
majority):________________________________________________________________
WITNESS ______________________________________________________________
l questions
Note: This physical activity clearance is valid for a maximum of 12 months from the date
it is completed and becomes invalid if your condition changes so that you would answer
YES to any of the seven questions.
© Canadian Society for Exercise Physiology
Supported by:
HealthCanadaSantéCanada
Source: Physical Activity Readiness Questionnaire (PAR-Q) © 2002. Reprinted with
permission from the Canadian Society for Exercise Physiology.
http://www.csep.ca/forms.asp
137
Appendix C
Measuring Your Pulse and Your Target Heart Rate
What is your pulse?
Your pulse is your heart rate, or the number of times your heart beats in one minute.
Pulse rates vary from person to person. Your pulse is lower when you are at rest and
increases when you exercise (because more oxygen-rich blood is needed by the body
when you exercise).
Knowing how to take your pulse can help you evaluate your exercise program.
How to take your pulse
1. Place the tips of your index, second, and third fingers on the palm side of your other
wrist, below the base of the thumb. Or, place the tips of your index and second fingers on
your lower neck, on either side of your windpipe. (See the illustrations below.)
2. Press lightly with your fingers until you feel the blood pulsing beneath your fingers.
You might need to move your fingers around slightly up or down until you feel the
pulsing.
3. Use a watch with a second hand, or look at a clock with a second hand.
4. Count the beats you feel for 10 seconds. Multiply this number by six to get your heart
rate (pulse) per minute.
Check your pulse: _______________ x 6 = ________________
(beats in 10 seconds)
(your pulse)
138
Appendix D
Borg Rating of Perceived Exertion (RPE) Scale
While doing physical activity, we want you to rate your perception of exertion. This
feeling should reflect how heavy and strenuous the exercise feels to you, combining all
sensations and feelings of physical stress, effort, and fatigue. Do not concern yourself
with any one factor such as leg pain or shortness of breath, but try to focus on your total
feeling of exertion.
Look at the rating scale below while you are engaging in an activity; it ranges from 6 to
20, where 6 means "no exertion at all" and 20 means "maximal exertion." Choose the
number from below that best describes your level of exertion. This will give you a good
idea of the intensity level of your activity, and you can use this information to speed up or
slow down your movements to reach your desired range. Try to appraise your feeling of
exertion as honestly as possible, without thinking about what the actual physical load is.
Your own feeling of effort and exertion is important, not how it compares to other
people. Look at the scales and the expressions and then give a number.
6 No exertion at all
7
Extremely light (7.5)
8
9 Very light
10
11 Light
12
13 Somewhat hard
14
15 Hard (heavy)
16
17 Very hard
18
19 Extremely hard
20 Maximal exertion
139
Appendix E
Walking Protocol
Week
Distance (km/day)
Distance (mile/day)
1
.8 km /day
.50 mile/day
2
.8 km /day
.50 mile/day
3
1.2 km /day
.74 mile/day
4
1.6 km /day
1.0 mile/day
5
2.0 km /day
1.2 mile/day
6
2.4 km /day
1.5 mile/day
7
2.8 km /day
1.7 mile/day
8
3.2 km /day
2.0 mile/day
9
3.6 km /day
2.2 mile/day
10
4.0 km /day
2.5 mile/day
11
4.4 km /day
2.7 mile/day
12
4.8 km /day
3.0 mile/day
* Adopted from Brown et al. (1992; 1994), Myslivecek et al. (2002) and Hua et al.
(2006)
140
Appendix F
Exercise Log
ID_________________
Age________________
Start Date___________
End Date ___________
Wk
Day Distance
(km/mile)
Duration
(min)
Heart Rate
Borg‘s
(beats/min)
Perceived
Exertion #
1
Before
Exercise:
After
Exercise:
2
Pre:
Post:
3
Pre:
Post:
4
Pre:
Post:
5
Pre:
Post:
6
Pre:
Post:
7
Pre:
Post:
Reason (s)
for stopping
Other
physical
activity
141
Appendix G
Activity Log
ID_________ Age______
Start Date_________________________ End Date ___________________________
Week
Day
Physical Activities
1
2
3
4
5
6
7
Week
Day
1
2
3
4
5
6
7
Physical Activities
142
Appendix H
Study Advertisement
143
Appendix I
Demographic and Data Form
ID :
Group:
Age:
yrs
Address:
Education:
Phone #:
Marital Status:
Occupation:
Menopausal State:
Blood Pressure Medications:
Time 1 Height:
Weight:
Waist Circumference:
Time 2 Height:
Weight:
Waist Circumference:
Time #1
Time #2
Date:
Date:
Supine
Supine
BP
BP
HR
HR
Standing
Standing
BP
BP
HR
HR
Exercise
Exercise
HR MAX
40% HR
BP Peak
BP Peak
HR Peak
HR Peak
144
Appendix J
Editing Heart Rate Variability Data
HRV data files were collected using a Spacelab 521T Cardiac Monitor with QRS
detector (Squibb Vitatek Inc., Hillsboro, USA) which was interfaced with a personal
computer by means of an eight-channel analog/digital convertor (DAS-16, Metrabyte
Corp., Multitest Electronics, Scarborough, ON). After raw binary data files were accrued,
they were converted into RR files by exporting them to an ASCII text format and
assigning them an extension (‗.RR‖) based on the original binary file name. These RR
files, which contained HR, systolic BP, diastolic BP and R-R interval data, were imported
into a general spectral analysis computer software program (Hughson and Yamamoto,
1993). This program used RR files to generate an R-R interval time series graph. The
graph was manually edited as described below and then saved to a separate file
containing the edited data (―.GSA‖). Editing of the time series graph was accomplished
by examining each data point of a series. Obvious outliers or artifacts which deviated by
more than 30% from the previous data point were deleted. This was accomplished by use
of a toggle which was maneuvered from the beginning to the end of the data set; touching
each data point separately. Editing outliers or artifacts was a step-wise process; the toggle
was moved directly over the start and end points of the outlying data with the right and
left arrow keys; the ENTER key was pressed to highlight each point; the DELETE key
was then pressed to eliminate the line connecting the start and end points of the outlier
data. After removing outliers, the time series graph was subjected to Fast Fourier
Transform analysis converting the edited data into a power frequency spectrum. The
145
summary of the power frequency spectrum was saved for separately for analysis. The
original raw HRV data files were maintained during this process.
146
Appendix K
Editing Baroreflex Sensitivity Data
BRS data files were collected using R-R interval data from the Spacelab 521T
Cardiac Monitor with QRS detector (Squibb Vitatek Inc., Hillsboro, USA) and the
Finapres® 2300 (Ohmeda, Englewood, CO) which were interfaced with a personal
computer by means of an eight-channel analog/digital convertor (DAS-16, Metrabyte
Corp., Multitest Electronics, Scarborough, ON). After raw binary data files were accrued,
they were converted into RR files by exporting them to an ASCII text format and
assigning them an extension (‗.RR‖) based on the original binary file name. RR files were
imported into the Spontaneous Baroreflex Analysis program developed by Andrew
Blaber of Cambridge, Ontario, Canada and the summary data generated by this program
as described below was saved to a separate file with the extension ―.SBR‖. This program
detects spontaneous sequences of three or more heart beats in which systolic BP and R-R
interval simultaneously change in the same direction. It then uses linear regression to
calculate the slope of each sequence. Editing for outliers or artifacts was accomplished
automatically by using the ―fl‖ command-line parameter when executing the program for
each RR file.
147
Appendix L
Means (±SD) for BpTRU Systolic and Diastolic Blood Pressure, Heart Rate and RatePressure-Product in Both Control and Exercise Group at Week 1 and Week 12
Time
Week 1
Week 12
Group
Control
Exercise
Control
Exercise
Systolic Blood Pressurea, b, c
(n=23)
(n=27)
(n=23)
(n=27)
Resting
130 (17)
137 (21)
128 (16)
131.3 (22)
Standing
140 (25)
146 (21)
140 (25)
133.0 (20)
Exercise
154 (20)
160 (25)
153 (24)
148.8 (28)
Resting
81 (10)
86 (13)
81 (10)
81 (13)
Standing
91 (17)
99 (14)
99 (19)
92 (13)
Exercise
90 (16)
98 (18)
97 (10)
93 (20)
Resting
67.0 (7.3)
67.1 (10.4)
70.2 (8.6)
66.6 (8.9)
Standing
76.7 (10.3)
78.5 (11.0)
80.2 (10.2)
79.1 (12.4)
Exercise
92.2 (10.3)
89.2 (13.4)
91.3 (12.8)
87.3 (14.5)
Resting
8.7 (1.3)
9.2 (2.0)
8.9 (1.4)
8.7 (1.7)
Standing
10.8 (2.5)
11.4 (2.0)
11.2 (2.4)
10.5 (2.0)
Exercise
14.2 (2.2)
14.24 (3.0)
13.91 (2.68)
13.0 (3.6)
(mmHg)
Diastolic Blood Pressureb, c
(mmHg)
Heart Rate (beats/min)c
Rate-Pressure- Productb, c
((HR x systolic BP) x10-2)
Note. BP and HR taken using BpTRU automated BP monitor. BP = blood pressure; HR =
heart rate; min = minute; ms = milliseconds
a
c
significant Time effect , p.<.05 bsignificant Time X Group interaction, p<.05
significant Condition effect, p<.001
148
Appendix M
Means (±SD) for Log Transformed Heart Rate Variability Measures for Both Control and
Exercise Group at Week 1 and Week 12
Time
Week 1
Group
Week 12
Control
Exercise
Control
(n=23)
(n=27)
(n=23)
Exercise
(n=27)
Low Frequency Powera, b, d
(ms2/Hz)
Resting
1.94 (.37)
1.99 (.48)
1.82 (.43)
1.90 (.53)
Standing
2.07 (.37)
2.05 (.41)
2.10 (.32)
2.0 (.43)
Exercise
1.50 (.64)
1.43 (.73)
1.86 (.67)
1.42 (.62)
Resting
1.78 (.43)
1.81 (.52)
1.71 (.51)
1.75 (.70)
Standing
1.45 (.33)
1.42 (.53)
1.50 (.34)
1.45 (.55)
Exercise
1.33 (.69)
1.27 (.70)
1.57 (.78)
1.20 (.68)
Resting
2.57 (.32)
2.55 (.46)
2.48 (.38)
2.54 (.46)
Standing
2.56 (.30)
2.51 (.40)
2.58 (.29)
2.60 (.41)
Exercise
2.28 (.58)
2.41 (.66)
2.61 (.62)
2.34 (.48)
Resting
-.79 (.26)
-.74 (.24)
-.77 (.25)
Standing
-1.11(.24)
-1.09 (.35)
-1.08 (.24) -1.15 (.26)
Exercise
-.95 (.36)
-1.13 (.30)
-1.03 (.28) -1.13 (.50)
High Frequency Powera, e
(ms2/Hz)
Total Powerd
(ms2/Hz)
PNS Indicatora, c, f
(HF/TP)
-.79 (.34)
149
SNS Indicatora, g
(LF/HF)
Resting
.16 (.37)
.18 (.33)
.11 (.32)
.15 (.31)
Standing
.62 (.30)
.63 (.36)
.60 (.25)
.55 (.29)
Exercise
.17 (.23)
.16 (.20)
.29 (.28)
.22 (.29)
Note. SNS = sympathetic nervous system; PNS = parasympathetic nervous system; ms =
milliseconds; m2/Hz = milliseconds squared per hertz; HF/TP = high frequency/ total
power; LF/HF = low frequency/ high frequency
a
significant Condition effect , p.<.001
b
c
significant Condition X Time interaction, p<.05
significant Condition X Group interaction, p<.01
d
significant Menopause effect, p<.05
e
significant Menopause X Group interaction, p<.05
f
significant Condition X Menopause interaction, p<.05
g
significant Condition X Menopause X Group interaction, p<.01
150
Appendix N
Means (±SD) for Spontaneous Baroreflex Measures for Both Control and Exercise Group
at Week 1 and Week 12
Time
Week 1
Group
Week 12
Control
Exercise
Control
(n=23)
(n=27)
(n=23)
Exercise
(n=27)
Baroreflex Slopea
(ms/mmHg)
Resting
6.38 (3.88)
6.55 (3.37)
5.80 (3.43)
6.19 (5.39)
Standing
3.16 (1.59)
3.12 (2.01)
3.41 (1.61)
3.23 (2.15)
Exercise
5.57 (5.13)
6.38 (4.70)
8.27 (6.56)
4.22 (4.60)
Resting
108 (36)
122 (28)
126 (26)
143 (23)
Standing
147 (27)
140 (25)
143 (31)
135(30)
Exercise
157 (39)
169 (42)
150 (38)
165 (40)
Resting
882 (91)
897 (119)
852 (97)
894 (147)
Standing
776 (95)
764 (101)
759 (110)
783(114)
Exercise
518 (99)
530 (74)
530 (92)
590 (103)
Systolic Finapres arterial
BP (mmHg)a, b
R-R Interval (ms)a, c
Note. BP = blood pressure; ms = milliseconds; mmHg = millimeters of mercury
a
significant effect of Condition , p.<.001
b
c
significant Condition X Group interaction, p<.05
significant Time X Condition X Menopause, p<.05
151
Appendix O
Summary of Study Sample and Reasons for Attrition
Participants
Control
Exercise
Total # completed the
study
Menopausal
9
9 **
18
Post menopausal
14
18 **
32
Total (n=)
23
27
50
# Loss to follow-up
0
4
Total # completed the
study
23
27
50
Note. ** = two lost to follow up
4 participants lost to follow up due to illness (n=1) or unable to contact after initial
testing (n=3)
152
Appendix P
Other demographic data at baseline testing
Measure
Control Group
Exercise Group
(n = 23)
(n = 27)
Marital Status
Married/Common Law
18 (78.3%)
22 (81.5%)
Single
5 (21.7 %)
5 (18.5%)
Total:
23 (100%)
27 (100%)
Working
17 (73.9%)
18 (66.7%)
Not working
2 (8.7%)
3 (11.1%)
Retired
4 (17.4%)
6 (22.2%)
Total:
23 (100%)
27 (100%)
Employment Status
153
Appendix Q
Chi-squared Summary Tables
Demographic, Physiological and Lifestyle Measures
Participant‘s Age at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
20.612
27.213
df
17
17
Asymp. Sig.
.244
.055
2.735
1
.098
50
Participant‘s Education Level at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
.028
.028
df
2
2
Asymp. Sig.
.986
.986
.014
1
.907
50
Participant‘s Maximum Activity Level at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
21.964
29.951
df
21
21
Asymp. Sig.
.402
.093
.757
1
.384
50
Participant‘s Menopausal State at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
.181
.181
df
1
1
Asymp. Sig.
.670
.671
.178
1
.673
50
154
Participant‘s Body Mass Index at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
50.000
68.994
df
49
49
Asymp. Sig.
.433
.031
1.670
1
.196
50
Participant‘s Resting Systolic Blood Pressure at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
27.053
36.631
df
29
29
Asymp. Sig.
.569
.156
1.847
1
.174
50
Participant‘s Resting Diastolic Blood Pressure at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
33.561
45.767
df
26
26
Asymp. Sig.
.146
.010
1.689
1
.194
50
Participant‘s Resting HR at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
33.561
45.767
df
25
25
Asymp. Sig.
.118
.007
.001
1
.977
50
Participant‘s Resting Rate-Pressure-Product at Baseline Testing
Chi-Square Tests
Pearson Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value
47.987
66.222
df
47
47
Asymp. Sig.
.433
.034
1.177
1
.278
50
155
Appendix Q
ANOVA Summary Tables
BpTRU Systolic Blood Pressure (SBP)
Descriptive Statistics
Group
SBPrest1
DBPstand1
SBPexer1
SBPrest12
Std. Deviation
Control
129.8261
16.94282
Exercise
138.3478
21.26373
Total
134.0870
19.49225
Control
90.6087
16.71890
Exercise
97.3478
13.02309
Total
93.9783
15.20452
Control
154.3043
20.24494
Exercise
161.6957
26.36188
Total
158.0000
23.53909
Control
127.4783
15.68980
Exercise
131.3043
22.36156
Total
129.3913
19.19778
139.9565
25.25052
Exercise
132.9565
20.34359
Total
136.4565
22.94700
Control
152.5652
23.45756
Exercise
148.4783
28.15843
Total
150.5217
25.70840
SBPstand12 Control
SBPexer12
Mean
Tests of Within-Subjects Effects
Source
Time (T)
T X Group (Gr)
T X Menopause (M)
T X Gr X M
Error (T)
Condition (C)
CXG
CXM
C X Gr X M
Error (C)
TYPE III SS
2260.666
1205.310
.921
51.653
11773.560
20275.207
557.204
663.499
60.755
16443.893
Df
1
1
1
1
42
2
2
2
2
84
MS
2260.666
1205.310
.921
51.653
280.323
10137.603
278.602
331.749
30.377
195.761
F
8.065
4.300
.003
.184
Sig.
.007*
.044*
.955
.670
51.786
1.423
1.695
.155
.000*
.247
.190
.857
156
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
52.366
138.296
6.542
613.164
9666.041
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
4964910.356
Gr
207.022
M
57.039
Gr X M
80.976
Error
94424.166
2
2
2
2
84
df
1
1
1
1
42
26.183
69.148
3.271
306.582
115.072
MS
4964910.356
207.022
57.039
80.976
2248.194
.228
.601
.028
2.664
F
2208.399
.092
.025
.036
.797
.551
.972
.076
Sig.
.000
.763
.874
.850
BpTRU Systolic Blood Pressure (SBP) for the Exercise Group
Tests of Within-Subjects Contrasts
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
940177.394
Error
16861.106
TYPE III SS
1333.452
2646.382
793.065
18883.130
6402.435
9746.870
287.500
438.348
2254.000
8045.652
df
1
22
MS
940177.394
766.414
df
1
22
1
1
22
22
1
1
22
22
MS
1333.452
120.290
793.065
18883.130
291.020
443.040
287.500
438.348
102.455
365.711
F
1226.723
F
11.085
Sig.
.003*
2.725
42.622
.113
.000*
2.806
1.199
.108
.285
Sig.
.000
BpTRU Systolic Blood Pressure (SBP) for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Type III SS
22.727
1295.995
5946.283
28252.174
8836.217
5502.826
56.543
4.261
Df
1
22
1
1
22
22
1
1
MS
22.727
58.909
5946.283
28252.174
401.646
250.128
56.543
4.261
F
.386
Sig.
.541
14.805
112.951
.001*
.000*
.325
.022
.574
.884
157
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
910676.060
Error
14657.106
3827.957
4306.739
df
1
22
MS
910676.060
666.232
22
22
F
1366.905
173.998
195.761
Sig.
.000
158
Appendix Q
ANOVA Summary Tables
BpTRU Diastolic Blood Pressure (DBP)
Descriptive Statistics
DBPrest1
Group
Mean
Control
81.2609
10.42382
Exercise
85.3913
12.64817
Total
83.3261
11.64866
90.6087
16.71890
Exercise
97.3478
13.02309
Total
93.9783
15.20452
Control
89.6522
16.16846
Exercise
97.5217
20.04511
Total
93.5870
18.44099
Control
80.5652
10.23286
Exercise
81.2174
13.31765
Total
80.8913
11.74777
98.7826
18.86304
Exercise
92.4348
13.03082
Total
95.6087
16.34826
97.2609
10.02369
Exercise
93.4348
20.32649
Total
95.3478
15.96415
DBPstand1 Control
DBPexer1
DBPrest12
DBPstand12 Control
DBPexer12 Control
Std. Deviation
Tests of Within-Subjects Effects
T
T X Gr
TXM
T X Gr X M
Error (T)
C
C X Gr
TYPE III SS
14.393
950.659
3.078
437.963
5007.614
8702.208
81.589
df
1
1
1
1
42
2
2
MS
14.393
950.659
3.078
437.963
119.229
4351.104
40.795
F
.121
7.973
.026
3.673
Sig.
.730
.007*
.873
.062
30.074
.282
.000*
.755
159
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error(T X C)
102.505
10.909
12153.131
286.604
326.418
17.559
644.855
9199.590
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
2064045.528
Gr
156.669
M
2337.743
Gr X M
153.559
Error
29305.952
2
2
84
2
2
2
2
84
df
1
1
1
1
42
51.252
5.454
144.680
143.302
163.209
8.780
322.427
109.519
MS
2064045.528
156.669
2337.743
153.559
697.761
.354
.038
.703
.963
1.308
1.490
.080
2.944
.276
.231
.923
.058
F
2958.099
.225
3.350
.220
Sig.
.000
.638
.074
.641
BpTRU Diastolic Blood Pressure (DBP) for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept
382808.988
1
Error
6155.957
22
Type III SS
221.761
838.739
6175.848
6817.391
4719.652
8632.609
6.283
.087
2247.217
6657.913
MS
382808.988
279.816
Df
1
22
1
1
22
22
1
1
22
22
MS
221.761
38.125
6175.848
6817.391
214.530
392.391
6.283
.087
102.146
302.632
F
1368.073
Sig.
.000
F
5.817
Sig.
.025*
28.788
17.374
.000*
.000*
.062
.000
.806
.987
160
BpTRU Diastolic Blood Pressure (DBP) for the Control Group
Source
T
Error (T)
C
Error (C)
TXC
Error (T X C)
Condition
Type III SS
290.843
979.435
8738.174
7237.587
7020.826
3968.913
904.696
793.065
5748.304
2839.435
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
370024.466
Error
4469.589
df
1
22
MS
370024.466
203.163
Df
1
22
1
1
22
22
1
1
22
22
MS
290.843
44.520
8738.174
7237.587
319.128
180.405
904.696
793.065
261.287
129.065
F
1821.317
Sig.
.000
F
6.533
Sig.
.018*
27.381
40.119
.000*
.000*
3.462
6.145
.076
.021*
161
Appendix Q
ANOVA Summary Tables
BpTRU Heart Rate (HR)
Descriptive Statistics
HRrest1
HRstand1
HRexer1
HRrest12
Group
Mean
Control
67.0000
7.28635
Exercise
67.4348
10.36527
Total
67.2174
8.86169
Control
76.6522
10.34236
Exercise
78.1739
11.61759
Total
77.4130
10.90275
Control
92.2174
10.32630
Exercise
89.3478
13.71664
Total
90.7826
12.09208
Control
70.2174
8.75399
Exercise
66.5652
8.89242
Total
68.3913
8.91809
80.2174
10.23344
Exercise
79.0870
12.40203
Total
79.6522
11.25703
Control
91.3913
12.78756
Exercise
87.2609
14.50460
Total
89.3261
13.68057
HRstand12 Control
HRexer12
Std. Deviation
Tests of Within-Subjects Effects
TYPE III SS
T
T X Gr
TXM
T X Gr X M
Error (T)
C
C X Gr
CXM
16.635
125.336
9.230
2.122
3944.116
20406.064
107.831
64.847
df
1
1
1
1
42
2
2
2
MS
16.635
125.336
9.230
2.122
93.908
10203.032
53.916
32.423
F
Sig.
.177
1.335
.098
.023
.676
.255
.755
.881
164.212
.868
.522
.000*
.424
.595
162
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Group X M
Error (T X C)
69.028
5219.192
186.890
5.924
19.577
32.132
2360.627
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
1534599.445
Gr
322.643
M
4.975
Gr X M
300.335
Error
20643.646
2
84
2
2
2
2
84
df
1
1
1
1
42
MS
1534599.445
322.643
4.975
300.335
491.515
34.514
62.133
93.445
2.962
9.789
16.066
28.103
F
3122.180
.656
.010
.611
.555
.576
3.325
.105
.348
.572
.041*
.900
.707
.567
Sig.
.000
.422
.920
.439
163
Appendix Q
ANOVA Summary Tables
BpTRU Rate-Pressure-Product (RPP)
Descriptive Statistics
RPPrest1
RPPstand1
RPPexer1
RPPrest12
Group
Mean
Control
8.6807
1.30891
Exercise
9.3183
1.96001
Total
8.9995
1.67917
Control
10.7719
2.48239
Exercise
11.2790
1.99892
Total
11.0255
2.24317
Control
14.1952
2.17364
Exercise
14.4223
3.08878
Total
14.3088
2.64335
Control
8.9350
1.44423
Exercise
8.7029
1.69586
Total
8.8190
1.56190
11.1988
2.37558
Exercise
10.4525
1.96167
Total
10.8256
2.18693
Control
13.9108
2.68465
Exercise
12.9988
3.59233
Total
13.4548
3.16941
RPPstand12 Control
RPPexer12
Std. Deviation
Tests of Within-Subjects Effects
Source
Type III SS
T
11.471
T X Gr
17.911
8T X M
.341
T X Gr X M
.098
Error (T)
131.665
C
1003.863
C X Gr
2.301
CXM
12.245
C X Gr X M
3.810
Df
1
1
1
1
42
2
2
2
2
MS
11.471
17.911
.341
.098
3.135
501.932
1.151
6.123
1.905
F
3.659
5.713
.109
.031
Sig.
.063
.021*
.743
.860
152.266
.349
1.857
.578
.000*
.706
.162
.563
164
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error(T X C)
276.899
7.007
.633
.962
1.721
175.023
84
2
2
2
2
84
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
31167.215
Gr
2.398
M
.004
Gr X M
8.050
Error
808.153
df
1
1
1
1
42
3.296
3.503
.317
.481
.860
2.084
MS
31167.215
2.398
.004
8.050
19.242
1.681
.152
.231
.413
F
1619.772
.125
.000
.418
.192
.859
.794
.663
Sig.
.000
.726
.989
.521
BpTRU Rate-Pressure-Product (RPP) for the Control Group
Tests of Within Subjects Contrasts
Source
T
TXM
Error (T)
C
CXM
Error (C)
TXC
TXCXM
Error (T X C)
Condition
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Type III SS
.126
.143
16.617
224.002
1160.568
6.440
9.115
75.959
109.518
.374
4.767
.035
3.388
34.471
91.373
df
1
1
21
1
1
1
1
21
21
1
1
1
1
21
21
MS
.126
.143
.791
224.002
1160.568
6.440
9.115
3.617
5.215
.374
4.767
.035
3.388
1.641
4.351
Tests of Between-Subjects Effects
Source
Intercept
M
Error
Type III SS
5616.444
1.366
111.216
df
1
1
21
MS
5616.444
1.366
5.296
F
1060.504
.258
Sig.
.000
.617
F
.160
.180
Sig.
.693
.675
61.929
222.538
1.780
1.748
.000*
.000*
.196
.200
.228
1.096
.021
.779
.638
.307
.886
.388
165
BpTRU Rate-Pressure-Product (RPP) for the Exercise Group
Tests of Within Subjects Contrasts
Source
T
TXM
Error (T)
C
CXM
Error (C)
T XC
TXCXM
Error (T X C)
Condition
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Type III SS
9.137
.012
27.271
146.357
855.351
1.758
.051
71.864
200.970
.889
6.600
.527
.015
19.294
132.606
Df
1
1
21
1
1
1
1
21
21
1
1
1
1
21
21
MS
9.137
.012
1.299
146.357
855.351
1.758
.051
3.422
9.570
.889
6.600
.527
.015
.919
6.315
F
7.036
.009
Sig.
.015*
.926
42.768
89.378
.514
.005
.000*
.000*
.481
.942
.968
1.045
.574
.002
.336
.318
.457
.962
Tests of Between-Subjects Effects
Intercept
Menopause
Error
4820.261
1.321
158.168
1
1
21
4820.261
1.321
7.532
639.988
.175
.000
.680
166
Appendix Q
ANOVA Summary Tables
Log Transformed Low Frequency (LgLF) Power
LgLFrest1
Group
Control
Exercise
Total
LgLFstand1
Control
Exercise
Total
LgLFexer1
Control
Exercise
Total
LgLFrest12
Control
Exercise
Total
Menopause
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Mean
2.1299
1.8395
1.9557
2.1422
1.8802
1.9588
2.1352
1.8614
1.9572
2.0673
2.0895
2.0806
2.3976
1.8556
2.0182
2.2089
1.9636
2.0494
1.4810
1.5581
1.5273
1.6041
1.2258
1.3393
1.5338
1.3792
1.4333
2.0002
1.7144
1.8287
2.1440
1.7494
1.8678
2.0618
1.7333
1.8483
Std. Deviation
.29837
.38760
.37560
.47023
.42025
.44068
.36472
.39796
.40416
.35092
.43023
.39071
.16238
.41920
.43830
.32439
.43239
.41105
.66384
.66970
.65078
.60655
.55912
.58511
.61870
.62326
.61820
.37532
.48489
.45678
.46000
.55618
.54933
.40335
.51441
.49905
167
LgLFstand12
Control
Exercise
Total
LgLFexer12
Control
Exercise
Total
Tests of Within-Subjects Effects
Source
T
T X Gr
TXM
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Type III SS
.063
.167
.036
.004
5.282
9.030
1.084
.080
.633
19.624
1.276
.336
.144
.036
8.698
Tests of Within-Subjects Contrasts
Source
Condition
T
T X Gr
TXM
2.0406
2.0893
2.0698
2.2392
1.8328
1.9547
2.1257
1.9512
2.0123
1.9595
1.9007
1.9242
1.7986
1.2127
1.3884
1.8905
1.5302
1.6563
Df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Type III SS
.021
.056
.012
.32463
.34221
.32745
.25174
.39683
.40117
.30252
.38785
.36612
.57142
.75113
.66919
.58781
.61759
.65405
.56173
.75428
.70723
MS
.063
.167
.036
.004
.147
4.515
.542
.040
.317
.273
.638
.168
.072
.018
.121
Df
1
1
1
MS
.021
.056
.012
F
.429
1.137
.244
.025
Sig.
.517
.293
.624
.874
16.565
1.989
.146
1.162
.000*
.144
.864
.319
5.281
1.391
.597
.151
.007*
.255
.553
.860
F
.429
1.137
.244
Sig.
.517
.293
.624
168
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
754.398
Group
.232
M
3.487
Gr X M
1.619
Error
19.530
.001
1.761
1.147
9.156
.042
1.864
.141
.092
.987
.911
6.768
27.424
.035
2.152
.088
.656
.094
.052
.068
.005
2.759
11.741
df
1
1
1
1
36
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
.001
.049
1.147
9.156
.042
1.864
.141
.092
.987
.911
.188
.762
.035
2.152
.088
.656
.094
.052
.068
.005
.077
.326
MS
754.398
.232
3.487
1.619
.542
F
1390.617
.427
6.428
2.984
.025
.874
6.102
12.020
.223
2.447
.752
.121
5.250
1.196
.018*
.001*
.640
.127
.392
.730
.028*
.281
.451
6.599
1.147
2.013
1.229
.159
.887
.015
.506
.014*
.291
.165
.275
.692
.353
.904
Sig.
.000
.518
.016*
.093
Log Transformed Low Frequency (LgLF) Power for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CX M
S vs. R
E vs. R
Type III SS
.078
.003
1.229
.872
1.477
1.005
.848
Df
1
1
18
1
1
1
1
MS
.078
.003
.068
.872
1.477
1.005
.848
F
1.137
.043
Sig.
.300
.838
5.466
3.064
6.297
1.759
.031*
.097
.022*
.201
169
Error (C)
TXC
TXCXM
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
139.477
M
.063
Error
3.670
2.872
8.680
.125
2.778
.001
.047
1.183
7.370
df
1
1
18
18
18
1
1
1
1
18
18
MS
139.477
.063
.204
.160
.482
.125
2.778
.001
.047
.066
.409
F
684.087
.310
1.898
6.785
.017
.116
.185
.018*
.896
.738
Sig.
.000
.585
Log Transformed Low Frequency (LgLF) Power for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.004
.010
.532
.352
9.039
.179
.199
3.897
18.744
.006
.202
.151
.012
1.577
4.370
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept
113.779
1
M
1.540
1
Error
2.840
18
MS
113.779
1.540
.158
Df
1
1
18
1
1
1
1
18
18
1
1
1
1
18
18
MS
.004
.010
.030
.352
9.039
.179
.199
.216
1.041
.006
.202
.151
.012
.088
.243
F
721.158
9.763
Sig.
.000
.006*
F
.131
.331
Sig.
.721
.572
1.625
8.680
.826
.191
.219
.009*
.375
.667
.066
.833
1.724
.049
.801
.374
.206
.828
170
Appendix Q
ANOVA Summary Tables
Log Transformed High Frequency (lgHF) Power
Descriptive Statistics
LgHFrest1
Group
Control
Exercise
Total
LgHFstand1
Control
Exercise
Total
LgHFexer1
Control
Exercise
Total
LgHFrest12
Control
Exercise
Total
Menopause
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Mean
1.7943
1.7080
1.7425
2.1253
1.6259
1.7757
1.9362
1.6638
1.7591
1.4240
1.4217
1.4226
1.7691
1.2625
1.4145
1.5719
1.3360
1.4185
1.2162
1.4262
1.3422
1.2840
1.1431
1.1854
1.2453
1.2738
1.2638
1.7167
1.6672
1.6870
2.2514
1.4496
1.6901
1.9459
Std.
Deviation
.26337
.44411
.37634
.48270
.46962
.51704
.39478
.45078
.44668
.17704
.41743
.33530
.64428
.49712
.57883
.45599
.46013
.46692
.70666
.72066
.70414
.62607
.53345
.54977
.64874
.63025
.62857
.51889
.53492
.51524
.43762
.63633
.68526
.54227
171
LgHFstand12
Control
Exercise
Total
LgHFexer12
Control
Exercise
Total
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Tests of Within-Subjects Effects
Source
T
T X Gr
TXM
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
Tests of Within-Subjects Contrasts
Source
Condition
T
T X Gr
TX M
Type III SS
.119
.128
.193
.147
6.985
7.208
1.346
.627
.022
22.880
.567
.175
.192
.100
10.404
Type III SS
.040
.043
.064
1.5500
1.6885
1.4503
1.4634
1.4581
1.6953
1.2390
1.3759
1.5553
1.3426
1.4170
1.5784
1.6904
1.6456
1.5628
1.0017
1.1700
1.5717
1.3196
1.4078
Df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Df
1
1
1
.59050
.59842
.22383
.38556
.32337
.50213
.47379
.51571
.37387
.44175
.42690
.84635
.77102
.78182
.74505
.64406
.70674
.77413
.77450
.77402
MS
.119
.128
.193
.147
.194
3.604
.673
.314
.011
.318
.283
.088
.096
.050
.145
MS
.040
.043
.064
F
.616
.661
.992
.755
Sig.
.438
.422
.326
.391
11.341
2.117
.987
.035
.000*
.128
.378
.966
1.960
.607
.665
.346
.148
.548
.518
.709
F
.616
.661
.992
Sig.
.438
.422
.326
172
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Type III
Source
SS
Intercept
510.164
Gr
.008
M
2.863
Gr X M
3.735
Error
25.849
.049
2.328
7.648
13.219
.145
2.472
.263
1.252
.041
.022
7.053
31.960
.022
.974
.061
.348
.123
.071
.157
.000
2.993
15.005
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
Df
MS
510.164
.008
2.863
3.735
.718
1
1
1
1
36
.049
.065
7.648
13.219
.145
2.472
.263
1.252
.041
.022
.196
.888
.022
.974
.061
.348
.123
.071
.157
.000
.083
.417
.755
.391
39.035
14.890
.739
2.784
1.345
1.410
.210
.025
.000*
.000*
.396
.104
.254
.243
.649
.875
.262
2.336
.734
.834
1.480
.171
1.886
.001
.612
.135
.397
.367
.232
.681
.178
.978
F
710.500
.011
3.987
5.202
Sig.
.000
.916
.053
.029
Log Transformed High Frequency (LgHF) Power for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Type III SS
.088
.001
1.569
3.047
2.281
.052
.503
Df
1
1
18
1
1
1
1
MS
.088
.001
.087
3.047
2.281
.052
.503
F
1.015
.006
Sig.
.327
.937
15.515
3.238
.262
.714
.0*
.089
.615
.409
173
Error (C)
TXC
TXCXM
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
91.826
M
.010
Error
3.861
3.535
12.682
.083
1.331
.001
.044
1.697
10.665
df
1
1
18
18
18
1
1
1
1
18
18
MS
91.826
.010
.215
.196
.705
.083
1.331
.001
.044
.094
.593
F
428.060
.048
.884
2.247
.012
.074
.359
.151
.915
.789
F
.001
2.500
Sig.
.981
.131
23.738
11.871
1.231
.704
.000*
.003*
.282
.412
.064
.307
3.631
.121
.802
.587
.073
.733
Sig.
.000
.829
Log Transformed High Frequency (LgHF) Power for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept
79.081
1
M
2.053
1
Error
4.755
18
Type III SS
2.385E-5
.105
.759
4.639
12.714
.241
.754
3.518
19.278
.005
.074
.261
.029
1.296
4.339
MS
79.081
2.053
.264
Df
1
1
18
1
1
1
1
18
18
1
1
1
1
18
18
MS
2.385E-5
.105
.042
4.639
12.714
.241
.754
.195
1.071
.005
.074
.261
.029
.072
.241
F
299.353
7.770
Sig.
.000
.012*
174
Appendix Q
ANOVA Summary Tables
Log Transformed Total Power (LgTP)
Descriptive Statistics
LgTPrest1
Group
Control
Exercise
Total
LgTPstand1
Control
Exercise
Total
LgTPexer1
Control
Exercise
Total
LgTPrest12
Control
Exercise
Total
Menopause
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Mean
2.6316
2.4995
2.5523
2.6563
2.4526
2.5137
2.6421
2.4742
2.5330
2.5300
2.5721
2.5553
2.7983
2.3553
2.4882
2.6450
2.4553
2.5217
2.3545
2.2130
2.2696
2.4560
2.3265
2.3654
2.3980
2.2741
2.3175
2.5975
2.3994
2.4786
2.7332
2.3850
2.4894
2.6557
Std.
Deviation
.26199
.35534
.32062
.40692
.43379
.42602
.31750
.39240
.37267
.26304
.36219
.31919
.17946
.42363
.41793
.26197
.40397
.36862
.63470
.58569
.59336
.54657
.60174
.57452
.57839
.58528
.57851
.38602
.40855
.40181
.46465
.43263
.46010
.41004
175
LgTPstand12
Control
Exercise
Total
LgTPexer12
Control
Exercise
Total
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
2.3916
2.4840
2.5528
2.5480
2.5500
2.6718
2.4847
2.5408
2.6038
2.5139
2.5454
2.6362
2.6370
2.6367
2.7357
2.1726
2.3415
2.6789
2.3869
2.4891
.41331
.42640
.18950
.35237
.29176
.35617
.40889
.39436
.26807
.37764
.34243
.61368
.69544
.64711
.69912
.27951
.50218
.62721
.55604
.59094
MS
.187
.070
.032
.046
.169
.311
.024
.027
.060
.191
.302
.165
.081
.217
.112
F
.107
.412
.190
.273
Sig.
.300
.525
.666
.605
1.631
.125
.141
.314
.203
.882
.869
.731
2.704
1.475
.723
1.945
.074
.236
.489
.150
Tests of Within-Subjects Effects
Source
Type III SS
T
.187
T X Gr
.070
TX M
.032
T X Gr X M
.046
Error (T)
6.092
C
.622
C X Gr
.048
CX M
.054
C X Gr X M
.120
Error (C)
13.728
TXC
.605
T X C X Gr
.330
TXCXM
.162
T X C X Gr X M
.435
Error(T X C)
8.051
df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Tests of Within-Subjects Contrasts
Source
Condition
T
T X Gr
TX M
Type III SS
.062
.023
.011
Df
1
1
1
MS
.062
.023
.011
F
1.107
.412
.190
Sig.
.300
.525
.666
176
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
453.986
Gr
.000
M
.663
Gr X M
.258
Error
5.574
.015
2.031
.028
.759
6.968E-5
.069
.094
.003
.223
.122
4.090
21.769
.018
1.024
.022
.586
.197
.007
.163
.277
2.284
10.381
df
1
1
1
1
36
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
MS
453.986
.000
.663
.258
.155
.015
.056
.028
.759
6.968E-5
.069
.094
.003
.223
.122
.114
.605
.018
1.024
.022
.586
.197
.007
.163
.277
.063
.288
.273
.605
.246
1.256
.001
.115
.825
.004
1.959
.202
.623
.270
.980
.737
.370
.947
.170
.656
.282
3.553
.343
2.032
3.111
.025
2.568
.961
.598
.068
.562
.163
.086
.874
.118
.334
F
2932.180
.003
4.283
1.669
Sig.
.000
.960
.046*
.205
MS
.087
.000
.072
.014
.198
.324
.086
.111
.371
F
1.197
.003
Sig.
.288
.956
.122
.533
2.913
.232
.731
.475
.105
.636
Log Transformed Total Power (LgTP) for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CX M
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
Type III SS
.087
.000
1.305
.014
.198
.324
.086
2.003
6.686
Df
1
1
18
1
1
1
1
18
18
177
TXC
TXCXM
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
242.754
M
.050
Error
3.001
.042
1.693
.001
.104
.920
7.314
df
1
1
18
1
1
1
1
18
18
MS
242.754
.050
.167
.042
1.693
.001
.104
.051
.406
F
1456.224
.301
.829
4.167
.017
.256
.375
.056
.897
.619
Sig.
.000
.590
Log Transformed Total Power (LgTP) for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TX M
Error (T)
C
S vs. R
E vs. R
CX M
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept
213.202
1
M
.820
1
Error
2.573
18
Type III SS
.004
.024
.726
.014
.604
.013
.042
2.086
15.083
8.665E-5
.029
.337
.176
1.364
3.067
MS
213.202
.820
.143
Df
1
1
18
1
1
1
1
18
18
1
1
1
1
18
18
F
1491.379
5.737
MS
.004
.024
.040
.014
.604
.013
.042
.116
.838
8.665E-5
.029
.337
.176
.076
.170
Sig.
.000
.028*
F
.110
.601
Sig.
.744
.448
.125
.721
.111
.050
.728
.407
.743
.826
.001
.167
4.447
1.030
.973
.687
.049
.324
178
Appendix Q
ANOVA Summary Tables
Log Transformed PNS Indicator (LgPNSI)
Descriptive Statistics
LgPNSIrest1
Group
Control
Exercise
Total
LgPNSIstand1 Control
Exercise
Total
LgPNSIexer1
Control
Exercise
Total
LgPNSIrest12
Control
Exercise
Menopause
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Mean
-.8372
-.7915
-.8098
-.5310
-.8267
-.7380
-.7060
-.8104
-.7739
-1.1060
-1.1505
-1.1327
-1.0292
-1.0927
-1.0737
-1.0731
-1.1194
-1.1032
-1.1383
-.7868
-.9274
-1.1719
-1.1834
-1.1800
-1.1527
-1.0003
-1.0537
-.8809
-.7322
-.7917
-.4818
-.9354
-.7993
Std.
Deviation
.28688
.19770
.23125
.12971
.26407
.26734
.27482
.23191
.24939
.23235
.24446
.23450
.49941
.31307
.36549
.35574
.27951
.30457
.40474
.25284
.35858
.25254
.31063
.28781
.33621
.34491
.34548
.26468
.22161
.24459
.06025
.29217
.32380
179
Total
LgPNSIstand12 Control
Exercise
Total
LgPNSIexer12 Control
Exercise
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Menopausal
Post Menopausal
Total
Tests of Within-Subjects Effects
Source
T
T X Gr
TXM
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
-.7098
-.8416
-.7955
-1.1026
-1.0847
-1.0918
-.9765
-1.2456
-1.1649
-1.0485
-1.1713
-1.1284
-1.0579
-.9466
-.9911
-1.1729
-1.1708
-1.1715
-1.1072
-1.0673
-1.0813
Type III SS
.008
.009
.067
.028
2.523
5.423
.903
.640
.245
5.856
.001
.039
.017
.201
3.842
df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Tests of Within-Subjects Contrasts
Source
Condition Type III SS Df
T
.003
1
T X Gr
.003
1
.28481
.27689
.28327
.20423
.22167
.20951
.19445
.24025
.25584
.20296
.24152
.23375
.31581
.17795
.24126
.54697
.52567
.51749
.41505
.41306
.40885
MS
.008
.009
.067
.028
.070
2.712
.452
.320
.123
.081
.000
.019
.008
.100
.053
MS
.003
.003
F
.108
.126
.962
.403
Sig.
.744
.725
.333
.530
33.341
5.553
3.937
1.507
.000*
.006*
.024*
.228
.007
.365
.155
1.879
.993
.696
.857
.160
F
.108
.126
Sig.
.744
.725
180
TXM
T X Gr X M
Error (T)
C
C X Gr
CXM
C X Gr X M
Error (C)
TXC
T X C X Gr
TXCXM
T X C X Gr X M
Error (T X C)
Tests of Between-Subjects Effects
Source
Intercept
Gr
M
Gr X M
Error
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
.022
.009
.841
8.601
7.641
.151
1.712
.043
1.139
.455
.249
4.605
7.311
.000
.001
.010
.031
.009
.033
5.742E-5
.297
1.927
4.501
Type III SS
68.334
.005
.026
.369
2.274
1
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
Df
1
1
1
1
36
.022
.009
.023
8.601
7.641
.151
1.712
.043
1.139
.455
.249
.128
.203
.000
.001
.010
.031
.009
.033
5.742E-5
.297
.054
.125
MS
68.334
.005
.026
.369
.063
.962
.403
.333
.530
67.230
37.627
1.182
8.433
.335
5.607
3.560
1.227
.000*
.000*
.284
.006*
.566
.023*
.067
.275
.003
.005
.185
.248
.163
.264
.001
2.373
.953
.943
.669
.622
.689
.610
.974
.132
F
1081.990
.081
.418
5.842
Sig.
.000
.777
.522
.021*
Log Transformed PNS Indicator (LgPNSI) for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CX M
S vs. R
E vs. R
Type III SS
8.014E-6
.001
.347
3.467
1.135
.117
.173
Df
1
1
18
1
1
1
1
MS
8.014E-6
.001
.019
3.467
1.135
.117
.173
F
.000
.078
Sig.
.984
.783
40.938
8.436
1.384
1.284
.000*
.009*
.255
.272
181
Error (C)
TXC
TXCXM
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
35.976
M
.106
Error
.694
1.524
2.422
.007
.022
.004
.283
1.184
1.362
df
1
1
18
18
18
1
1
1
1
18
18
MS
35.976
.106
.039
.085
.135
.007
.022
.004
.283
.066
.076
F
933.492
2.751
.104
.287
.060
3.735
.750
.599
.809
.069
Sig.
.000
.115
Log Transformed PNS Indicator (LgPNSI) for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
32.589
M
.278
Error
1.580
Type III SS
.005
.029
.494
5.171
7.776
.365
1.150
3.081
4.888
.003
.011
.005
.062
.743
3.138
df
1
1
18
MS
32.589
.278
.088
Df
1
1
18
1
1
1
1
18
18
1
1
1
1
18
18
MS
.005
.029
.027
5.171
7.776
.365
1.150
.171
.272
.003
.011
.005
.062
.041
.174
F
371.289
3.166
F
.186
1.041
Sig.
.671
.321
30.212
28.631
2.130
4.234
.000*
.000*
.162
.054
.084
.061
.116
.354
.775
.808
.737
.559
Sig.
.000
.092
182
Log Transformed PNS Indicator (LgPNSI) for Menopausal Women in the Control
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
16.661
Error
.593
Type III SS
.001
.154
.962
.914
.279
1.199
.009
.062
.362
.393
df
1
7
df
1
7
1
1
7
7
1
1
7
7
MS
.001
.022
.962
.914
.040
.171
.009
.062
.052
.056
MS
16.661
.085
F
.033
Sig.
.862
24.171
5.335
.002*
.054
.171
1.097
.691
.330
F
196.786
Sig.
.000
Log Transformed PNS Indicator (LgPNSI) for Postmenopausal Women in the Control
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.001
.193
3.037
.264
1.246
1.223
.000
.288
.823
.970
Tests of Between-Subjects Effects
Source
Type III SS
Df
Intercept 20.110
1
Error
.101
11
MS
20.110
.009
df
1
11
1
1
11
11
1
1
11
11
MS
.001
.018
3.037
.264
.113
.111
.000
.288
.075
.088
F
2189.675
F
.046
Sig.
.834
26.816
2.373
.000*
.152
.003
3.269
.955
.098
Sig.
.000
183
Log Transformed PNS Indicator (LgPNSI) for Menopausal Women in the Exercise
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.003
.052
2.958
5.323
1.070
1.632
3.790E-5
.008
.150
.478
Tests of Between-Subjects Effects
Source
Type III SS
Df
Intercept 9.589
1
Error
.427
5
MS
9.589
.085
df
1
5
1
1
5
5
1
1
5
5
MS
.003
.010
2.958
5.323
.214
.326
3.790E-5
.008
.030
.096
F
112.347
F
.325
Sig.
.593
13.828
16.305
.014*
.010*
.001
.079
.973
.790
Sig.
.000
Log Transformed PNS Indicator (LgPNSI) for Postmenopausal Women in the Exercise
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
Error (T)
C
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.048
.442
2.325
2.454
2.012
3.256
.014
.103
.593
2.660
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept 32.405
1
Error
1.153
13
MS
32.405
.089
df
1
13
1
1
13
13
1
1
13
13
MS
.048
.034
2.325
2.454
.155
.250
.014
.103
.046
.205
F
365.308
F
1.419
Sig.
.255
15.024
9.800
.002*
.008*
.300
.503
.593
.491
Sig.
.000
184
Appendix Q
ANOVA Summary Tables
Log Transformed SNS Indicator (LgSNSI)
Descriptive Statistics
LgSNSIrest1
Menopause
Menopausal
Post Menopausal
Total
LgSNSIstand1 Menopausal
Post Menopausal
Total
LgSNSIexer1
Menopausal
Post Menopausal
Total
LgSNSIrest12
Menopausal
Post Menopausal
Total
Group
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Mean
.3356
.0169
.1990
.1315
.2543
.1976
.2131
.1831
.1981
.6433
.6285
.6370
.6678
.5931
.6276
.6580
.6037
.6309
.2648
.3201
.2885
.1319
.0827
.1054
.1851
.1539
.1695
.2835
-.1074
.1160
.0473
.2998
.1833
.1418
.1777
Std.
Deviation
.37815
.25567
.35905
.23069
.37242
.31533
.30661
.35292
.32667
.32345
.49982
.39048
.27174
.33201
.30208
.28539
.37608
.33067
.23735
.23336
.22822
.21034
.16168
.18354
.22546
.21136
.21628
.30738
.15884
.31761
.27497
.26307
.29282
.30444
.30108
185
LgSNSIstand12 Menopausal
Post Menopausal
Total
LgSNSIexer12 Menopausal
Post Menopausal
Total
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Tests of Within-Subjects Effects
Source
Type III SS
T
.009
TXM
.062
T X Gr
.003
TXMX G
.104
Error (T)
1.565
C
8.501
CXM
.381
C X Gr
.025
C X M X Gr
.886
Error (C)
6.086
TXC
.142
TXCXM
.003
T X C X Gr
.027
T X C X M X Gr
.019
Error(T X C)
2.787
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Error (T)
.1597
.5903
.5439
.5705
.6259
.5937
.6086
.6117
.5788
.5952
.3812
.2358
.3188
.2103
.2109
.2107
.2787
.2184
.2485
df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Type III SS
.003
.021
.001
.035
.522
.29941
.23310
.30367
.25553
.27043
.30249
.28289
.25035
.29567
.27093
.37321
.26652
.32848
.21376
.31377
.26702
.29179
.29358
.29052
MS
.009
.062
.003
.104
.043
4.250
.190
.012
.443
.085
.071
.002
.013
.009
.039
Df
1
1
1
1
36
MS
.003
.021
.001
.035
.014
F
.207
1.434
.058
2.383
Sig.
.652
.239
.810
.131
50.285
2.253
.147
5.244
.000*
.112
.863
.007*
1.840
.045
.346
.240
.166
.956
.709
.787
F
.207
1.434
.058
2.383
Sig.
.652
.239
.810
.131
186
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error(T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
7.936
M
.010
Gr
.051
M X Gr
.145
Error
2.488
14.719
.372
.019
.665
.031
.043
1.432
1.219
8.528
3.478
.001
.231
.002
.002
.002
.049
.018
.003
2.141
3.255
df
1
1
1
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
14.719
.372
.019
.665
.031
.043
1.432
1.219
.237
.097
.001
.231
.002
.002
.002
.049
.018
.003
.059
.090
MS
7.936
.010
.051
.145
.069
62.133
3.849
.080
6.879
.130
.443
6.044
12.619
.000
.058
.779
.013
.720
.510
.019*
.001*
.025
2.551
.032
.017
.041
.538
.308
.029
.876
.119
.858
.897
.840
.468
.582
.866
F
114.816
.148
.740
2.102
Sig.
.000
.702
.395
.156
Log Transformed SNS Indicator (LgSNSI) for Menopausal Women in the Control
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
C X Gr
S vs. R
Type III SS
5.732E-5
.000
.000
.000
.067
1.511
.003
.000
.000
.000
Df
1
0
0
0
7
1
1
0
0
0
MS
5.732E-5
F
.006
Sig.
.940
.010
1.511
.003
8.441 .023*
.019 .893
187
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error(T X C)
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
2.775
M
.000
Gr
.000
M X Gr
.000
Error
.706
.000
.000
.000
1.253
1.047
2.843E-6
.113
.000
.000
.000
.000
.000
.000
.457
1.036
df
1
0
0
0
7
0
0
0
7
7
1
1
0
0
0
0
0
0
7
7
MS
2.775
.179
.150
2.843E-6
.113
.000
.766
.995
.410
.065
.148
F
27.528
Sig.
.001
.101
Log Transformed SNS Indicator (LgSNSI) for Postmenopausal Women in the Control
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
C X Gr
S vs. R
E vs. R
C X M X Gr
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
Type III SS
.002
.000
.000
.000
.248
7.459
.160
.000
.000
.000
.000
.000
.000
2.748
.564
Df
1
0
0
0
11
1
1
0
0
0
0
0
0
11
11
MS
.002
F
.067
.023
7.459
.160
29.854 .000*
3.128 .105
.250
.051
Sig.
.800
188
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
2.196
M
.000
Gr
.000
M X Gr
.000
Error
.319
.011
.159
.000
.000
.000
.000
.000
.000
.337
.673
df
1
0
0
0
11
1
1
0
0
0
0
0
0
11
11
MS
2.196
.011
.159
.351 .565
2.597 .135
.031
.061
F
75.680
Sig.
.000
.029
Log Transformed SNS Indicator (LgSNSI) for Menopausal Women in the Exercise
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
C X Gr
S vs. R
E vs. R
C X M X Gr
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
T X C X Gr
S vs. R
Type III SS
.029
.000
.000
.000
.048
4.785
1.253
.000
.000
.000
.000
.000
.000
1.406
.326
.005
.005
.000
.000
.000
Df
1
0
0
0
5
1
1
0
0
0
0
0
0
5
5
1
1
0
0
0
MS
.029
F
Sig.
2.979 .145
.010
4.785
1.253
17.018 .009*
19.224 .007*
.281
.065
.005
.005
.059
.060
.818
.817
189
T X C X M X Gr
Error (T X C)
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
.894
M
.000
Gr
.000
M X Gr
.000
Error
.439
.000
.000
.000
.403
.403
df
1
0
0
0
5
0
0
0
5
5
MS
.894
.081
.081
F
10.185
Sig.
.024
.088
Log Transformed SNS Indicator (LgSNSI) for Postmenopausal Women in the Exercise
Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
C X Gr
S vs. R
E vs. R
C X M X Gr
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
T X C X Gr
S vs. R
E vs. R
T X C X M X Gr
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.024
.000
.000
.000
.159
2.802
.475
.000
.000
.000
.000
.000
.000
3.121
1.542
.014
.048
.000
.000
.000
.000
.000
.000
.944
1.143
Df
1
0
0
0
13
1
1
0
0
0
0
0
0
13
13
1
1
0
0
0
0
0
0
13
13
MS
.024
F
Sig.
1.936 .187
.012
2.802
.475
11.672 .005*
4.004 .067
.240
.119
.014
.048
.195
.544
.073
.088
.666
.474
190
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
3.220
M
.000
Gr
.000
M X Gr
.000
Error
1.025
df
1
0
0
0
13
MS
3.220
.079
F
40.847
Sig.
.000
191
Appendix Q
ANOVA Summary Tables
Baroreflex Slope (BSLOPE)
Descriptive Statistics
BSLOPErest1
Menopause
Menopausal
Post Menopausal
Total
BSLOPEstand1
Menopausal
Post Menopausal
Total
BSLOPEexer1
Menopausal
Post Menopausal
Total
BSLOPErest12
Menopausal
Post Menopausal
Total
Group
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Mean
6.6193
8.8679
7.5830
5.5978
5.1201
5.3406
6.0064
6.2444
6.1254
2.8873
4.5621
3.6050
3.1848
2.4832
2.8070
3.0658
3.1068
3.0863
5.4825
5.8156
5.6253
5.9920
5.9837
5.9875
5.7882
5.9333
5.8607
5.7710
7.4161
6.4760
5.6259
4.4648
5.0007
5.6840
Std.
Deviation
3.19693
4.33135
3.74865
3.19380
2.40681
2.74943
3.15190
3.46487
3.27157
.62491
2.94747
2.07157
2.05674
1.53367
1.79210
1.61718
2.20248
1.90730
4.91715
5.56402
4.99554
5.52858
3.80426
4.57977
5.16420
4.24916
4.66842
2.90354
2.85097
2.89472
3.59153
3.26227
3.39972
3.25257
192
BSLOPEstand12 Menopausal
Post Menopausal
Total
BSLOPEexer12
Menopausal
Post Menopausal
Total
Tests of Within-Subjects Effects
Source
T
TXM
T X Gr
T X M X Gr
Error (T)
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error(T X C)
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Type III SS
1.103
1.043
43.321
.086
433.125
421.914
20.726
78.732
14.068
1248.913
30.259
14.625
50.009
.013
698.890
5.3502
5.5171
3.0217
4.5493
3.6764
3.4022
2.3884
2.8563
3.2500
3.0367
3.1433
9.6170
5.5545
7.8759
8.5711
3.9327
6.0735
8.9895
4.4193
6.7044
Df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
3.36838
3.27262
.58814
2.79998
1.95371
2.09959
1.25605
1.73944
1.64808
2.04322
1.83542
7.73857
5.03729
6.80867
5.75465
4.86587
5.69593
6.44296
4.84342
6.08341
MS
1.103
1.043
43.321
.086
12.031
210.957
10.363
39.366
7.034
17.346
15.129
7.312
25.004
.007
9.707
F
.092
.087
3.601
.007
Sig.
.764
.770
.066
.933
12.162
.597
2.269
.406
.000*
.553
.111
.668
1.559
.753
2.576
.001
.217
.474
.083
.999
193
Tests of Within-Subjects Contrasts
Source
Condition
T
TX M
T X Gr
T X M X Gr
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
C X Gr
S vs. R
E vs. R
C X M X Gr
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
T X C X Gr
S vs. R
E vs. R
T X C X M X Gr
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
.368
.348
14.440
.029
144.375
592.686
2.408
20.746
38.665
.660
126.580
.423
23.856
363.887
1929.392
11.265
60.155
3.131
28.203
.767
67.072
.008
.027
122.256
1092.437
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
2004.346
M
22.404
Gr
2.673
M X Gr
16.080
Error
217.421
df
1
1
1
1
36
df
1
1
1
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
MS
2004.346
22.404
2.673
16.080
6.039
MS
.368
.348
14.440
.029
4.010
592.686
2.408
20.746
38.665
.660
126.580
.423
23.856
10.108
53.594
11.265
60.155
3.131
28.203
.767
67.072
.008
.027
3.396
30.345
F
331.874
3.710
.443
2.663
F
.092
.087
3.601
.007
Sig.
.764
.770
.066
.933
58.636
.045
2.052
.721
.065
2.362
.042
.445
.000*
.833
.161
.401
.800
.133
.839
.509
3.317
1.982
.922
.929
.226
2.210
.002
.001
.077
.168
.343
.341
.637
.146
.961
.976
Sig.
.000
.062
.510
.111
194
Appendix Q
ANOVA Summary Tables
Systolic Finapres Arterial Blood Pressure (ABP)
Descriptive Statistics
ABPrest1
Menopause
Menopausal
Post Menopausal
Total
ABPstand1
Menopausal
Post Menopausal
Total
ABPexer1
Menopausal
Post Menopausal
Total
ABPrest12
Menopausal
Post Menopausal
Total
Group
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Mean
107.4879
124.1400
114.6245
101.2255
121.3368
112.0547
103.7304
122.1778
112.9541
155.6149
132.5202
145.7171
138.3213
143.8478
141.2971
145.2388
140.4495
142.8441
166.9878
161.9130
164.8129
145.8618
171.3493
159.5858
154.3121
168.5184
161.4153
141.2592
140.2733
140.8367
116.2907
143.9591
131.1890
126.2781
Std.
Deviation
39.39609
16.81488
31.89982
33.94152
34.67261
35.16488
35.33665
29.97822
33.66620
27.05537
34.56587
31.53341
21.38058
22.52484
21.74540
24.69593
26.26656
25.28097
46.00835
61.95207
51.21295
30.49683
31.39523
33.01013
37.82945
41.28072
39.73835
28.26807
9.79785
21.62070
19.67023
26.69295
27.17745
25.99813
195
ABPstand12
Menopausal
Post Menopausal
Total
ABPexer12
Menopausal
Post Menopausal
Total
Tests of Within-Subjects Effects
Source
T
TXM
T X Gr
T X M X Gr
Error (T)
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error (T X C)
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Type III SS
554.871
35.337
.216
39.083
40176.897
40809.424
152.835
6277.436
143.488
40130.055
9395.469
168.632
197.427
1512.637
69495.979
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
T X Gr
T X M X Gr
Type III SS
184.957
11.779
.072
13.028
142.8533
134.5657
148.0385
130.2258
140.4045
134.3718
135.3135
134.8788
139.8384
133.7872
136.8128
150.4952
162.5120
155.6453
144.7000
161.7190
153.8641
147.0181
161.9569
154.4875
df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
22.71067
25.51483
26.64428
19.21771
24.65747
30.64824
36.36133
33.18198
29.19844
31.74174
30.25864
38.52393
41.69193
38.80408
36.60486
41.31436
39.39545
36.48283
40.31659
38.69796
MS
554.871
35.337
.216
39.083
1116.025
20404.712
76.418
3138.718
71.744
557.362
4697.734
84.316
98.713
756.319
965.222
Df
1
1
1
1
MS
184.957
11.779
.072
13.028
F
.497
.032
.000
.035
Sig.
.485
.860
.989
.853
36.609
.137
5.631
.129
.000*
.872
.005*
.879
4.867
.087
.102
.784
.010*
.916
.903
.461
F
.497
.032
.000
.035
Sig.
.485
.860
.989
.853
196
Error (T)
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
13392.299
16747.032
81385.458
279.718
163.180
10731.266
219.437
260.883
13.339
32487.225
57019.004
13538.879
14626.519
103.307
335.931
130.111
391.816
1376.858
2885.221
53642.561
96532.189
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
372.008
16747.032
81385.458
279.718
163.180
10731.266
219.437
260.883
13.339
902.423
1583.861
13538.879
14626.519
103.307
335.931
130.111
391.816
1376.858
2885.221
1490.071
2681.450
18.558
51.384
.310
.103
11.892
.139
.289
.008
.000*
.000*
.581
.750
.001*
.712
.594
.927
9.086
5.455
.069
.125
.087
.146
.924
1.076
.005*
.025*
.794
.725
.769
.705
.343
.307
Tests of Between-Subjects Effects
Source
Intercept
M
Gr
M X Gr
Error
Type III SS
1421504.805
496.611
765.984
1647.312
26828.965
Df
1
1
1
1
36
MS
1421504.805
496.611
765.984
1647.312
745.249
F
1907.423
.666
1.028
2.210
Sig.
.000
.420
.317
.146
Systolic Finapres Arterial Blood Pressure (ABP) for the Control Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
Type III SS
103.032
.017
6449.251
29083.929
48244.757
.176
44.577
23853.558
32214.193
Df
1
1
18
1
1
1
1
18
18
MS
103.032
.017
358.292
29083.929
48244.757
.176
44.577
1325.198
1789.677
F
.288
.000
Sig.
.598
.995
21.947
26.957
.000
.025
.000*
.000*
.991
.876
197
TXC
TXCXM
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
726576.074
M
2117.610
Error
10707.806
8744.715
10610.461
1197.031
2780.435
27167.225
47807.967
df
1
1
18
1
1
1
1
18
18
MS
726576.074
2117.610
594.878
8744.715
10610.461
1197.031
2780.435
1509.290
2655.998
F
1221.386
3.560
5.794
3.995
.793
1.047
.027*
.061
.385
.320
F
.216
.060
Sig.
.648
.809
.651
24.883
1.056
.092
.430
.000*
.318
.765
3.510
1.772
.231
.217
.077
.200
.636
.647
Sig.
.000
.075
Systolic Finapres Arterial Blood Pressure (ABP) for the Exercise Group
Tests of Within-Subjects Contrasts
Source
Condition
T
TXM
Error (T)
C
S vs. R
E vs. R
CXM
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
TXCXM
S vs. R
E vs. R
Error (T X C)
S vs. R
E vs. R
Type III SS
83.311
23.241
6943.048
312.466
34290.427
506.660
126.482
8633.667
24804.811
5163.053
4795.535
340.253
586.949
26475.336
48724.222
Df
1
1
18
1
1
1
1
18
18
1
1
1
1
18
18
Tests of Between-Subjects Effects
Source
Type III SS
df
Intercept
697624.799
1
M
157.019
1
Error
16121.159
18
MS
697624.799
157.019
895.620
F
778.930
.175
MS
83.311
23.241
385.725
312.466
34290.427
506.660
126.482
479.648
1378.045
5163.053
4795.535
340.253
586.949
1470.852
2706.901
Sig.
.000
.680
198
Appendix Q
ANOVA Summary Tables
R-R Interval (RRI)
Descriptive Statistics
RRIrest1
Menopause
Menopausal
Post Menopausal
Total
RRIstand1
Menopausal
Post Menopausal
Total
RRIexer1
Menopausal
Post Menopausal
Total
RRIrest12
Menopausal
Post Menopausal
Group
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Mean
830.7290
884.0470
853.5796
901.6607
869.2388
884.2027
873.2880
873.6812
873.4846
729.9809
757.1833
741.6391
785.7792
754.9782
769.1940
763.4598
755.6398
759.5498
499.7738
544.2400
518.8307
517.3518
544.8580
532.1628
510.3206
544.6726
527.4966
833.0479
906.8267
864.6674
862.4817
846.2444
Std.
Deviation
50.13143
73.05291
64.46379
101.63311
116.50396
108.97076
90.42722
103.63293
95.99973
70.34136
102.26987
82.95876
96.86768
109.11620
102.78704
89.67683
104.40270
96.14450
54.73911
70.99132
63.82221
115.45238
73.04380
93.99376
94.33410
70.54696
84.03917
75.79177
125.24953
102.77337
106.19357
127.90775
199
Total
RRIstand12
Menopausal
Post Menopausal
Total
RRIexer12
Menopausal
Post Menopausal
Total
Tests of Within-Subjects Effects
Source
T
TXM
T X Gr
T X M X Gr
Error (T)
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error(T X C)
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Control
Exercise
Total
Type III SS
1875.673
3747.443
4423.919
137.513
289530.260
3985739.034
2398.208
8591.132
12295.560
385212.381
11394.505
12508.205
537.944
222.804
136054.769
Tests of Within-Subjects Contrasts
Source
Condition
T
Type III SS
625.224
853.7385
850.7081
864.4191
857.5636
730.4174
792.0498
756.8313
762.4317
748.8001
755.0916
749.6260
761.7750
755.7005
507.7736
561.3735
530.7450
550.1352
589.1197
571.1269
533.1906
580.7959
556.9932
Df
1
1
1
1
36
2
2
2
2
72
2
2
2
2
72
Df
1
116.35059
94.14911
127.01787
110.57358
67.85807
121.05543
95.48610
108.21297
98.47355
101.20725
93.46069
104.42571
98.00955
82.85149
121.71967
100.75831
103.80690
102.66821
103.03100
96.02599
106.21271
102.80715
MS
1875.673
3747.443
4423.919
137.513
8042.507
1992869.517
1199.104
4295.566
6147.780
5350.172
5697.253
6254.102
268.972
111.402
1889.650
MS
625.224
F
.233
.466
.550
.017
Sig.
.632
.499
.463
.897
372.487
.224
.803
1.149
.000*
.800
.452
.323
3.015
3.310
.142
.059
.055
.042*
.868
.943
F
.233
Sig.
.632
200
TXM
T X Gr
T X M X Gr
Error (T)
C
CXM
C X Gr
C X M X Gr
Error (C)
TXC
TXCXM
T X C X Gr
T X C X M X Gr
Error (T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
1249.148
1474.640
45.838
96510.087
852910.762
7686076.083
338.423
4491.828
1297.399
8306.490
2021.914
23282.575
116625.927
511278.863
2056.679
21718.488
564.151
21696.763
250.459
287.920
188.825
49.097
46635.259
173413.383
1
1
1
36
1
1
1
1
1
1
1
1
36
36
1
1
1
1
1
1
1
1
36
36
1249.148
1474.640
45.838
2680.836
852910.762
7686076.083
338.423
4491.828
1297.399
8306.490
2021.914
23282.575
3239.609
14202.191
2056.679
21718.488
564.151
21696.763
250.459
287.920
188.825
49.097
1295.424
4817.038
.466
.550
.017
.499
.463
.897
263.276
541.189
.104
.316
.400
.585
.624
1.639
.000*
.000*
.748
.577
.531
.449
.435
.209
1.588
4.509
.435
4.504
.193
.060
.146
.010
.216
.041*
.514
.041
.663
.808
.705
.920
Tests of Between-Subjects Effects
Source
Intercept
M
Gr
M X Gr
Error
Type III SS
3.729E7
3014.388
10278.728
14436.500
441362.989
Df
1
1
1
1
36
MS
3.729E7
3014.388
10278.728
14436.500
12260.083
F
3041.602
.246
.838
1.178
Sig.
.000
.623
.366
.285
R-R Interval (RRI) for the Menopausal Group
Tests of Within-Subjects Contrasts
Source
Condition
T
T X Gr
Error (T)
C
S vs. R
E vs. R
Type III SS
1393.566
780.786
46461.226
339500.608
3085019.187
Df
1
1
12
1
1
MS
1393.566
780.786
3871.769
339500.608
3085019.187
F
.360
.202
Sig.
.560
.661
93.025 .000*
269.951 .000*
201
C X Gr
Error (C)
TXC
T X C X Gr
Error(T X C)
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
1.401E7
Group
18779.931
Error
66843.044
2509.665
1444.765
43794.726
137136.703
178.510
.002
334.524
219.951
13226.358
74439.665
df
1
1
12
1
1
12
12
1
1
1
1
12
12
MS
1.401E7
18779.931
5570.254
F
2515.831
3.371
2509.665
1444.765
3649.561
11428.059
178.510
.002
334.524
219.951
1102.197
6203.305
.688
.126
.423
.728
.162
.000
.304
.035
.694
1.000
.592
.854
Sig.
.000
.091
R-R Interval (RRI) for the Postmenopausal Group
Tests of Within-Subjects Contrasts
Source
Condition
T
T X Gr
Error (T)
C
S vs. R
E vs. R
C X Gr
S vs. R
E vs. R
Error (C)
S vs. R
E vs. R
TXC
S vs. R
E vs. R
T X C X Gr
S vs. R
E vs. R
Error(T X C)
S vs. R
E vs. R
Tests of Between-Subjects Effects
Source
Type III SS
Intercept
2.738E7
Group
254.016
Error
374519.945
df
1
1
24
Type III SS
77.085
721.515
50048.860
590819.792
5278090.635
57.718
42838.324
72831.201
374142.160
3443.621
62618.147
3.134
71.558
33408.901
98973.718
MS
2.738E7
254.016
15604.998
Df
1
1
24
1
1
1
1
24
24
1
1
1
1
24
24
F
1754.424
.016
MS
77.085
721.515
2085.369
590819.792
5278090.635
57.718
42838.324
3034.633
15589.257
3443.621
62618.147
3.134
71.558
1392.038
4123.905
Sig.
.000
.900
F
.037
.346
Sig.
.849
.562
194.692
338.572
.019
2.748
.000*
.000*
.891
.110
2.474
15.184
.002
.017
.129
.001*
.963
.896