MAY 27, 2021

RSAF – 1 Grant Final Report
Grant Code: GR-000080
Grant Title: An Examination in Cardiorespiratory Performance and
Cardiovascular Function in Healthy College Students
Principle Investigator: Dr. Andrew S. Perrotta
Grant Duration: September 1, 2020 – August 31, 2021
Grant Amount: $ 3,000.00

DR. ANDREW S. PERROTTA
LANGARA COLLEGE
Department of Kinesiology

Please introduce yourself – include pertinent background information relating to the topic of your
research project.


Throughout my research, I have had the privilege of working with female athletes that allowed
the data obtained to directly impact athletes within Canada’s National Sporting Organizations.
My research program concentrates on bridging the fields of cardiovascular and exercise
physiology to better understand the body’s response to exercise and stress, as well as how to
enhance human performance. A major focus of my work involves examining the dose-response
to exercise, heart rate variability, as well as alterations in cardiorespiratory performance in
response to environmental stress. The purpose of my work is to conduct applied research that
can relate to practitioners, to support evidence-based decisions to help their patients and
athletes. As a postdoctoral fellow, I expanded upon my work in environmental physiology
examining cardiorespiratory performance and cardiac function in both hot and cold
environments. In particular, my research examining the utility of hot yoga to enhance blood
volume and cardiorespiratory performance has gained international recognition for its
innovation and focus on the female response to a novel form of heat stress.

Please discuss your educational background and your work experience that led you to taking on this
research project. If possible, include a quote that helps define your interest in this project.




I completed my (hon) B.A.Sc in Kinesiology from the University of Guelph that strongly focused
on physiology and nutrition metabolism. My graduate journey began in Calgary where I
completed my M.Kin (applied exercise physiology) at the University of Calgary. I moved to
Vancouver to complete my Ph.D. at UBC in the Faculty of Medicine, that focuses on
cardiovascular and exercise physiology. I completed further training as a postdoctoral fellow at
SFU in the department of Biomedical Physiology and Kinesiology, the focuses on the effect of
the environment on cardiorespiratory function.
Throughout my tenure as PhD student, I was the Head Physiologist for the Canadian Women’s
National Field Hockey team. I was responsible for supervising graduate and undergraduate
students at the University of British Columbia who were keen to learn about human
performance and applied research. This position developed my passion for finding unique and
sustainable avenues that allow kinesiology students to develop as young practitioners and
researchers. I have continued to develop this model of integration as the Head of Sport
Medicine and Sport Science for the Langara College women’s soccer program through
connecting with the Department of Kinesiology. This has allowed me to supervise and train
undergraduate students in conducting exercise assessments and applied research that were
funding by the RSAF-1 Grant. Establishing this form of relationship between departments is an
integral component of my research program, and one that is designed to work in a collegial
environment that maximizes the development of our students, while also supporting the
success of our coaches and student athletes.

Please explain the concept for your project in terms that others not in your field would understand,
like an executive summary.






The purpose of this investigation is to establish a non-invasive technique that elicits suitable
levels of agreement for estimating the volume of oxygen consumption in healthy young adults
during rest and maximal exercise with the use of an automated blood pressure machine and a
heart rate monitor.
A comparison between the estimated volume of oxygen consumption and the direct measure of
oxygen consumption will identify the strength of relationship and level of agreement between
the two methods.
Additionally, the data used for this primary project was analyzed from other perspectives that
supported multiple poster presentations at scientific conferences. All data used was supported
through the achievement of Ethical approval the LREB (Notice of Approval: 20210128-02).

Identify goals and objectives for the project, and how the results may be used, perhaps to solve a
problem, or to inform further research in that field.


The intention of this study is to provide practitioners and clinicians a valid and acceptable
alternative to assessing their patient’s fitness and health status without the use of invasive and
costly equipment.

Briefly explain the steps taken to conduct the project research, and the results found.




This investigation involved healthy young adults, male and female, that allows for the
examination of cardiovascular function without the influence of disease and health
complications. All participants where Langara Kinesiology students registered in KINS 2235
Exercise Physiology during the 2019 and 2020 school year.
This investigation examined the level of agreement between actual VO2 and estimated VO2
during rest VO2EST-REST and maximal exercise VO2EST-MAX. Nine (n=9) healthy college
students (4 males & 5 females) with an age of (mean ± SD) 21.3 ±1.2 yr, a weight of 63.4 ± 17.2
kg and a height of 162.4 ± 10.2 cm performed a graded maximal exercise test on a cycle
ergometer, after being fitted with a mouth piece for the collection of expired gas concentrations
and analysis using a calibrated metabolic cart. Initial fly-wheel resistance was set at 2W x
bodyweight (kg) and involved 25 W increments every three minutes until volitional fatigue.
Resting and maximum Q were calculated immediately before and upon completion of the
exercise test while seated on the cycle ergometer. An automated BP monitor using an arm cuff
positioned around the brachial artery and a HR monitor chest strap were utilized to calculate Q
using the formula: [(SBP – DBP) / (SBP + DBP) x HR] x 0.29. VO2 was estimated using the
formula: [(VO2EST) = [(Q) / (Q / body weight (lbs)) x1000]. A Pearson correlation coefficient (r)
and a Bland Altman analysis examined the association and level of agreement between
estimated and actual VO2. This study was approved by the Research Ethics Review Board at
Langara College.

Who else was involved in this project? How did their involvement help? Ie: other faculty, students,
community partners


Two kinesiology students were involved in this project. Each student was responsible for
creating components of the poster and providing a verbal 3-min presentation for each poster at
each conference.

What were/are you hoping to get from conducting this research?




Cardiovascular function, specifically cardiac output, has demonstrated to be the determining
factor in oxygen utilization, whereby concomitantly regulating maximum aerobic power
(VO2MAX). The utility for determining cardiac output using a non-invasive technique such as
blood pressure and heart rate, coupled with its strong association to oxygen utilization, may
allow for the estimation of VO2 during rest and exercise without the use of invasive and costly
equipment.
The purpose of this investigation was to examine the level of agreement for determining VO2 at
rest and during maximal exercise using a non-invasive technique for estimating cardiac output
using heart rate and blood pressure when compared to an automated metabolic cart

Can you share any personal stories that made this research experience memorable/valuable?


It was an amazing experience watching my trainees present at conferences of the highest calibre
in the field of exercise physiology. These experiences will no doubt support their applications
when transferring to UBC and for graduate scholarships.

Do you have any tips/suggestions/ideas for applying this research in your field? Or for others in their
fields? Or for conducting future research of this kind?


Our abstracts have been published in the Journal of Applied Physiology, Nutrition and
Metabolism as well as the Journal of Medicine & Science in Sports & Exercise. As such,
researchers and practitioners will have access to our findings and guidelines for conducting
replications studies or using our techniques.

Any final comments? What are the “next steps” for this project? And for you?


This grant was able to support two kinesiology students in attending and presenting 5 poster at
national and international scientific conferences. Each poster was accepted for publication as a
conference abstract in prestigious scientific journals that have an impact factor >3.5. Please find
attached all five posters for your review. I wish to sincerely thank you for supporting my work
with the RSAF-1 Grant. This grant was used to develop our student’s ability in conducting
applied research. I will continue to apply for ARC grant moving forward for the same purpose.

The association between fatigue index and anthropometric and physiological performance
measures from an anaerobic performance assessment in healthy college students
Arif D. Khan, Camila J. Correa and Andrew S. Perrotta
Department of Kinesiology, Langara College, Vancouver, BC, Canada

ABSTRACT

RESULTS

CONCLUSION

Background. Anaerobic performance, when examined using a 60-sec Wingate test, allows for the
assessment of anaerobic capacity and the calculation of a fatigue index (FI), a derivative of the depletion in
anaerobic metabolism. Objective. This study examined the association between the FI calculated from a 60sec Wingate test and both anthropometric and physiological performance measures in healthy young adults.
Methods. Ten (n=10) college students (7 males & 3 females) with an age of (mean ± SD) 21.9 ±2.3 yr, a
body weight of 78.4 ±13.0 kg, a height of 174.2 ±8.4 cm, a BMI of 25.7 ±2.7 kg/m2 , and a body surface
area (BSA) of 1.89 ±0. 17 m2 performed a 60-sec Wingate test with an initial fly-wheel resistance set at 0.075
x body weight (kg). A graded maximal exercise test was performed on a separate occasion using a cycle
ergometer and involved an initial resistance of 2W x body weight (kg) and progressed using 25 W increments
every three minutes until volitional fatigue. The collection of expired gas concentrations for analysis using a
calibrated metabolic cart was used to record VO2MAX and maximum aerobic power (MAP). FI was calculated
using the formula: FI = [(Peak 5-sec PWR – Lowest 5-sec PWR/Peak 5-sec PWR) x 100]. A Pearson
correlation coefficient (r) was utilized to examine the strength of association between the FI and both
anthropometric and physiological measures. This study was approved by the Research Ethics Review Board
at Langara College. Results. The strength of association between the FI and anthropometric characteristics
were as follows; BMI (r = 0.18, p = 0.621), height (r = 0.68, p = 0.031), weight (r = 0.47, p = 0.166) and BSA (r
= 0.73, p = 0.017). The association between the FI and physiological measures were; VO2MAX (r = 0.17, p =
0.647), 5- sec peak PWR (r = 0 .54, p = 0.105), relative power (r = 0.45, p = 0.187) and MAP (r = 0.10, p =
0.785). Conclusion. The FI from a 60-sec Wingate test was positively associated to anthropometric
characteristics, namely height and BSA, a possible result of altered biomechanics and physiological strain.

Significant associations were observed between
the FI and both BSA (m2) (r = 0.73, p = 0.017)
and height (cm) (r = 0.68, p = 0.031). Remaining
anthropometric
measures
displayed
an
insignificant association with the FI; BMI (kg/m2)
(r = 0.18, p = 0.621), weight (kg) (r = 0.47, p =
0.166). The association between physiological
performance measures and FI were as follows;
VO2MAX (L●min-1) (r = 0.17, p = 0.647), 5-sec
peak PWR (W) (r = 0 .54, p = 0.105), relative
power (W/kg) (r = 0.45, p = 0.187) and MAP (r =
0.10, p = 0.785).

Anthropometric measures, specifically BSA and
height, were positively associated with the FI
from a 60-sec Wingate test. Previous evidence
has shown a significant correlation between
height and anaerobic power within sub-elite
athletes5, supporting the current study’s results
as the calculation for FI relies on Peak 5-sec
PWR
to
calculate
anaerobic
capacity.
Furthermore, previous inquiries that have
categorized subjects by BSA, while testing for
anaerobic and aerobic performance, have
observed positive correlations between BSA and
maximal anaerobic power6. These findings
encourage
support
staff
to
monitor
anthropometric adaptations from participating in
sport or exercise to help maximize human
performance.

INTRODUCTION
Anthropometric characteristics are often a critical
focus point for integrative support staff when
monitoring adaptation to exercise and its utility to
reinforce exercise programs to maximize human
performance. The significant association of
somatotype on both anaerobic capacity1,2 and
aerobic power (VO2MAX)3,4 supports the need for
further examination between the association of
anthropometric characteristics and anaerobic
performance measures. This study examined the
association between the fatigue index (FI)
calculated from a 60- sec Wingate test and both
anthropometric and physiological performance
measures in healthy young adults.

METHODOLOGY
7 males & 3 females with an age of (mean ±
SD) 21.9 ±2.3 yr, a body weight of 78.4 ±13.0
kg, a height of 174.2 ±8.4 cm, a BMI of 25.7
±2.7 kg/m2 , and a body surface area (BSA) of
1.89 ±0. 17 m2 performed a 60-sec Wingate test
with a fly-wheel resistance set at 0.075 x body
weight (kg). A graded maximal exercise test
performed on a cycle ergometer was used to
record VO2MAX and maximum aerobic power
(MAP). FI was calculated using the formula: FI =
[(Peak 5-sec PWR – Lowest 5-sec PWR/Peak 5sec PWR) x 100]. A Pearson correlation
coefficient (r) was utilized to examine the strength
of association between the FI and both
anthropometric and physiological measures.

KINESIOLOGY
Corresponding Author: aperrotta@langara.ca

REFERENCES
1) Ryan-Stewart, H., Faulkner, J., & Jobson, S. (2018). The influence
of somatotype on anaerobic performance. Plos One, 13(5).
2) Sukanta, S. (2014). Somatotype, Body Composition and Explosive
Power of Athlete and Non-Athlete. LASE Journal of Sport Science,
5(1), 26-34.
3) Goran, M., Fields, D., Hunter, G., Herd, S., & Weinsier, R. (2000).
Total body fat does not influence maximal aerobic capacity.
International Journal of Obesity, 24(7), 841-848.
4) Maciejczyk, M., Więcek, M., Szymura, J., Szyguła, Z., Wiecha, S., &
Cempla, J. (2014). The Influence of Increased Body Fat or Lean Body
Mass on Aerobic Performance. Plos One, 9(4).
5) ASLAN, Cem & Koc, Hurmuz & Aslan, Murat & Özer, Uğur. (2011).
The effect of height on the anaerobic power of sub-elite athletes.
World Applied Sciences Journal. 12. 208.
6) Washington, R. L., Gundy, J. C., Cohen, C., Sondheimer, H. M., &
Wolfe, R. R. (1988). Normal aerobic and anaerobic exercise data for
North American school-age children. The Journal of Pediatrics, 112(2),
223-233.
This study was funded by the Langara College RSAF-1 Grant.

A comparison in VO2MAX when using different sampling intervals of
metabolic data in healthy college students
Arif D. Khan, Camila J. Correa and Andrew S. Perrotta
Department of Kinesiology, Langara College, Vancouver, BC, Canada

ABSTRACT

RESULTS

CONCLUSION

Background. Maximal aerobic power (VO2MAX) is a classic and valid assessment for examining
cardiorespiratory performance and overall health. The utility of metabolic carts for assessing VO2MAX in postsecondary programs allow students the opportunity to conduct assessments and familiarize themselves with
data collection and its analysis. The influence of sampling intervals for determining VO2MAX is an important
aspect one should consider when learning to implement standardized testing procedures. This investigation
compared the difference in VO2MAX when using 10-sec and 30-sec sampling intervals in healthy college
students. Methods. Twenty (n=20) healthy college students (13 males & 7 females) with an age of (mean ±
SD) 21.7 ±2.9 yr, a weight of 70.6 ±16.4 kg, and a height of 167.7 ±9.5 cm performed a graded maximal
exercise test on a computer controlled cycle ergometer, after being fitted with a mouth piece consisting of a
one-way breathing valve for the collection of expired gas concentrations and analysis using a calibrated
metabolic cart. Initial fly-wheel resistance was set at 2W x kg bodyweight and involved 25 W increments every
three minutes until volitional fatigue. Participants were verbally encouraged throughout each test. Absolute
(L●min-1) and relative (mL●kg-1●min-1) VO2MAX was examined using 10-sec and 30-sec sampling intervals. A
one-way ANOVA and standardized mean differences to reveal the effect size (ES), with accompanied 95% CI,
were utilized to examine the variance between each sampling interval. Significance was declared as (p<0.05).
This study was approved by the Research Ethics Review board at Langara College. Results. Differences
(mean ± SD) between 10-sec ‘vs’ 30-sec sampling in relative VO2 [(40.5 ± 8.0 ‘vs’ 38.5 ± 7.6 mL●kg-1 ●min-1
), ES = 0.25 ± 0.65, p = 0.43] and absolute VO2 [(2.9 ± 0.89 ‘vs’ 2.7 ± 0.85 L●min-1 ), ES = 0.16 ± 0.65, p =
0.61] were observed. Conclusion. This study revealed larger VO2MAX values using 10-sec sampling that were
not significant when compared to 30-sec sampling intervals. However, students should consider the reliability
of each sampling interval for identifying VO2MAX when implementing repeated testing.

The differences (mean ± SD) between 10-sec
‘vs’ 30-sec sampling in relative VO2MAX [(40.5 ±
8.0 ‘vs’ 38.5 ± 7.6 mL●kg-1 ●min-1 ), ES = 0.25
± 0.65, p = 0.43] and absolute VO2MAX [(2.9 ±
0.89 ‘vs’ 2.7 ± 0.85 L●min-1 ), ES = 0.16 ±
0.65, p = 0.61] were observed.

This investigation revealed no significant
differences between sampling intervals of 10-sec
‘vs’ 30-sec when examining both relative and
absolute VO2MAX in healthy college students.
Previous literature has demonstrated the
significant influence of test duration on VO2MAX
values, with shorter duration tests eliciting larger
VO2 consumption3. It is recommended future
investigations focus on the influence of sampling
intervals when using multiple test durations
when examining VO2MAX.

INTRODUCTION

METHODOLOGY

REFERENCES

When performing a VO2MAX test the sampling
interval at which expired gas is analyzed has
demonstrated to significantly influence both peak
VO2 and the presence of a plateau in oxygen
consumption1. Short sampling intervals have
shown to elicit larger VO2MAX values1, an
outcome that has demonstrated to be
independent of the testing protocol utilized2.
However, there remains a paucity of research
examining the effect of different sampling
intervals when analyzing VO2MAX in healthy
college students whose activity levels are widely
varied.

Twenty (n=20) healthy college students (13
males & 7 females) with an age of (mean ± SD)
21.7 ±2.9 yr, a weight of 70.6 ±16.4 kg, and a
height of 167.7 ±9.5 cm performed a graded
maximal exercise test on a computer-controlled
cycle ergometer. Initial resistance was set at 2W
x kg bodyweight and incrementally added 25 W
every three minutes until volitional fatigue.
Absolute and relative VO2MAX was examined
using 10-sec and 30-sec sampling intervals. A
one-way ANOVA and standardized mean
differences to reveal effect size (ES), with
accompanied 95% CI, were used to examine
variance between each sampling interval.
Significance was declared as (p<0.05).

1) Astorino, T. A. (2009). Alterations in VO2max and the
VO2 plateau with manipulation of sampling interval.
Clinical physiology and functional imaging, 29(1), 6067.

KINESIOLOGY
Corresponding Author: aperrotta@langara.ca

2) Scheadler, C. M., Garver, M. J., & Hanson, N. J.
(2017). The Gas Sampling Interval Effect on V˙O2peak
Is Independent of Exercise Protocol. Medicine &
Science in Sports & Exercise, 49(9), 1911-1916.
3) Yoon, B. K., Kravitz, L., & Robergs, R. (2007). V
O2max, protocol duration, and the V O2 plateau.
Medicine & Science in Sports & Exercise, 39(7), 11861192.
This study was funded by the Langara College RSAF-1
Grant.

A comparison in power output between maximal aerobic power
(MAP) and 60-second Wingate end power
Camila J. Correa, Arif D. Khan and Andrew S. Perrotta
Department of Kinesiology, Langara College, Vancouver, BC, Canada

ABSTRACT

RESULTS

CONCLUSION

Background. Power output (W) at VO2MAX can be defined as maximal aerobic power (MAP) and represents
the transition where work completed above this point is primarily derived through anaerobic metabolism.
Exhaustion in anaerobic metabolism from a constant load test, such as a 60-sec Wingate, may produce
similar end power outputs as MAP. This investigation examined the similarity between MAP derived from a
graded maximal exercise test and the power output upon completion of a 60-sec Wingate test. Methods. Ten
(n=10) healthy college students (7 males & 3 females) with an age of (mean ± SD) 21.9 ±2.3 yr, a weight of
78.4 ±13.0 kg and a height of 174.2 ±8.4 cm performed a graded maximal exercise test on a cycle
ergometer after being fitted with a mouth piece for the collection of expired gas concentrations and analysis
using a calibrated metabolic cart. Initial fly-wheel resistance was set at 2W x body weight (kg) and involved
25 W increments every three minutes until volitional fatigue. A 60-sec Wingate test was completed one
month after and involved a resistance of 0.075 x body weight (kg). A one-way ANOVA and standardized
mean differences to reveal the effect size (ES), along with a Pearson correlation coefficient (r) were utilized
to examine the variance and magnitude of association between final power outputs. This study was approved
by the Research Ethics Review Board at Langara College. Results. Difference in power output (mean±SD)
at MAP (219.1 ± 42.5 W) and 60-sec Wingate end power (217.1 ± 67.8 W) was not significant (p = 0.87,
ES = -0.04). A significant association between 60-sec Wingate end power and MAP was observed (r = 0.78,
p = 0.008). Conclusion. These findings suggest a 60-sec Wingate test may sufficiently diminish anaerobic
capacity to elicit similar end power outputs compared to MAP in healthy college students.

As presented in figure 1, the correlation between
MAP and
60-sec Wingate end power
demonstrated a very large association (r = 0.78, p
= 0.008). Figure 2 illustrates an insignificant
difference in power output (mean±SD) between
MAP (219.1 ± 42.5 W) and 60-sec Wingate end
power (217.1 ± 67.8 W).

The results presented in this investigation
displayed a very large association between MAP
obtained from a graded maximal exercise test
and the power output upon completion of a 60sec Wingate test. This suggests that a 60second Wingate test may provide enough time
to adequately diminish anaerobic capacity to
elicit similar end power outputs compared to
MAP in healthy college students. These findings
may be useful for practitioners as they can utilize
shorter test protocols to evaluate MAP, thus
saving time and the need for expensive
laboratory equipment.

INTRODUCTION

METHODOLOGY

Given that brief high-intensity exercise relies
predominantly on anaerobic metabolism1,
practitioners typically utilize maximal tests of
short duration to evaluate anaerobic power and
capacity. However, Serresse et al.1 demonstrated
that VO2MAX can be achieved after approximately
60-sec in a 90-sec maximal ergometer test. As
such, a constant load test, such as a 60-second
Wingate, may sufficiently deplete both the ATPPC and glycolytic system to produce similar end
power outputs as maximal aerobic power (MAP).
The purpose of this investigation was to examine
the similarity between MAP derived from a
graded maximal exercise test and the power
output upon completion of a 60-sec Wingate test.

Ten healthy college students (7 males & 3
females) with an age of (mean ± SD) 21.9 ±2.3
yr, a weight of 78.4 ±13.0 kg and a height of
174.2 ±8.4 cm performed a graded maximal
exercise test on a cycle ergometer. Initial
flywheel resistance was set at 2W x bodyweight
(kg) and involved 25 W increments every three
minutes until volitional fatigue. A month later,
participants performed a 60-sec Wingate test
that involved a resistance of 0.075 x body weight
(kg). A one-way ANOVA and standardized mean
differences to reveal the effect size (ES), along
with a Pearson correlation coefficient (r) were
utilized to examine the variance and magnitude
of association between final power outputs

KINESIOLOGY
Corresponding Author: aperrotta@langara.ca

REFERENCES
1. Serresse, O., Lortie, G., Bouchard C., & Boulay M.R.
(1988). Estimation of the contribution of the various
energy systems during maximal work of short duration. Int
Journal of Sports Medicine, 9(6), 456-460
2. Yamamoto, M., & Kanehisa, H. (1995). Dynamics of
anaerobic and aerobic energy supplies during sustained
high intensity exercise on cycle ergometer. European
Journal of Applied Physiology, 71, 320-325.

This study was funded by the Langara College RSAF-1
Grant.

Estimated Cardiac Output for Determining Resting and Maximal VO2
in Healthy Individuals: A non-invasive Technique
Camila J. Correa, Arif D. Khan and Andrew S. Perrotta
Department of Kinesiology, Langara College, Vancouver, BC, Canada

ABSTRACT

RESULTS

CONCLUSION

Background. Non-invasive techniques for estimating cardiac output (Q) using heart rate (HR) and systolic
(SBP) and diastolic (DBP) blood pressure allow for advanced examination in cardiovascular function. Oxygen
(O2) utilization during rest and maximal exercise are largely dependent upon Q and the concomitant delivery of
O2 to the body. Consequently, the relationship between Q and VO2 supports the concept for estimating VO2
using a non-invasive assessment. Methods. This investigation examined the level of agreement between actual
VO2 and estimated VO2 during rest VO2EST-REST and maximal exercise VO2EST-MAX. Nine (n=9) healthy college
students (4 males & 5 females) with an age of (mean ± SD) 21.3 ±1.2 yr, a weight of 63.4 ± 17.2 kg and a
height of 162.4 ± 10.2 cm performed a graded maximal exercise test on a cycle ergometer, after being fitted
with a mouth piece for the collection of expired gas concentrations and analysis using a calibrated metabolic
cart. Initial fly-wheel resistance was set at 2W x bodyweight (kg) and involved 25 W increments every three
minutes until volitional fatigue. Resting and maximum Q were calculated immediately before and upon
completion of the exercise test while seated on the cycle ergometer. An automated BP monitor using an arm cuff
positioned around the brachial artery and a HR monitor chest strap were utilized to calculate Q using the
formula: [(SBP – DBP) / (SBP + DBP) x HR] x 0.29. VO2 was estimated using the formula: [(VO2EST) = [(Q) / (Q
/ body weight (lbs)) x1000]. A Pearson correlation coefficient (r) and a Bland Altman analysis examined the
association and level of agreement between estimated and actual VO2. This study was approved by the
Research Ethics Review Board at Langara College. Results. VO2EST-REST values fell within the levels of
agreement (-512 : 397 mL) but displayed an insignificant association with actual VO2 (r = 0.32, p = 0.41). Eight
VO2EST-MAX values resided within the levels of agreement (- 799 : 732 mL) and displayed a significant
association with actual VO2 (r = 0.88, p = 0.005). Conclusion. These results suggest improved accuracy in
estimating VO2 during maximal exercise that may be the result of greater association between cardiovascular
function and oxygen utilization.

VO2EST-REST values fell within the levels of
agreement (-512 : 397 mL) but displayed a
moderate association with actual VO2 (r = 0.32,
p = 0.41). Eight of nine VO2EST-MAX values
resided within the levels of agreement (- 799 :
732 mL) and displayed a significant association
with actual VO2 ( r = 0.88, p = 0.005)

This investigation displayed a stronger level of
agreement between the direct measurement and
our predicted calculation of VO2 during maximal
exercise when compared to rest. VO2MAX has
demonstrated to be largely dependent on
cardiovascular function3 whereby alterations in
Q can influence O2 transportation and
subsequent skeletal muscle O2 utilization1. The
concomitant relationship between cardiovascular
function and oxygen utilization may be
responsible for the superior accuracy in
estimating VO2 during exercise1. These findings
demonstrate the utility of a non-invasive
technique for estimating VO2MAX using blood
pressure and heart rate in healthy college age
students.

INTRODUCTION

METHODOLOGY

Cardiovascular function, specifically cardiac output
(Q), has demonstrated to be the determining factor
in oxygen utilization, whereby concomitantly
regulating maximum aerobic power (VO2MAX)1.
The utility for determining Q using a non-invasive
technique such as blood pressure and heart rate2,
coupled with its strong association to oxygen
utilization, may allow for the estimation of VO2
during rest and exercise without the use of
invasive and costly equipment. The purpose of this
investigation was to examine the level of
agreement for determining VO2 at rest and during
maximal exercise using a non-invasive technique
for estimating Q using heart rate (HR) and blood
pressure when compared to a metabolic cart.

Nine healthy college students (4 males & 5 females)
with an age of (mean ± SD) 21.3 ±1.2 yr, a weight
of 63.4 ± 17.2 kg and a height of 162.4 ± 10.2 cm
performed a graded maximal exercise test on a
cycle ergometer. Initial flywheel resistance was set
at 2W x bodyweight (kg) and involved 25 W
increments every three minutes until volitional
fatigue. Expired gas concentrations were analyzed
using a calibrated metabolic cart. Prior to and upon
completion of the exercise test, Q was calculated
while seated on the cycle ergometer using an
automated BP monitor and a HR monitor chest
strap. Q was calculated using the formula: [(SBP –
DBP) / (SBP + DBP) x HR] x 0.29. VO2 was
estimated using the formula: [(VO2EST) = [(Q) / ([Q /
body weight (lbs)) x1000].

KINESIOLOGY
Corresponding Author: aperrotta@langara.ca

REFERENCES
1. Gledhill, N., Warburton, D., & Jamnik, V. (1999).
Haemoglobin, blood volume, cardiac function, and aerobic
power. Canadian Society for Exercise Physiology, 24(1),
54-65.
2. Koenig, J., Hill, L. K., Williams, D. P., & Thayer J. K.
(2015). Estimating cardiac output from blood pressure and
heart rate: the Liljestrand & Zander formula. Biomedical
Sciences Instrumentations, 87-92
3. Bassett, D. R., Howley E. T. (1999). Limiting factors for
maximum oxygen uptake and determinants of endurance
performance. Medicine & Science in Sports & Exercise,
70-84
This study was funded by the Langara College RSAF-1Grant.

Association between Anthropometry and Indices of Cardiovascular
Function at Maximal Exercise in Healthy College Students
Camila J. Correa and Andrew S. Perrotta
Department of Kinesiology, Applied Research Centre, Langara College, Vancouver, BC, Canada

ABSTRACT

RESULTS

The delivery of oxygen to the working muscle has shown to be a limiting factor to maximal aerobic
exercise (VO2 Peak). Both cardiac and vascular function play a pivotal role in the transportation of
oxygen, however, the association between anthropometric characteristics and indices of cardiac and
vascular function have yet to be explored at VO2 peak. PURPOSE: To examine the association
between indices of cardiovascular function and anthropometric characteristics at VO2 peak in healthy
college students. METHODS: Ten healthy college students (4 males & 5 females) with an age of
(mean ± SD) 21.4 ± 1.2 yr, a weight of 64.3 ± 16.8 kg and a height of 163.0 ± 10.5 cm performed a
graded maximal exercise test on a cycle ergometer. Each participant was fitted with a mouthpiece for
the collection of expired gas concentrations and was analyzed using a calibrated metabolic cart.
Initial flywheel resistance was set at 2W x bodyweight (kg) and involved 25 W increments every three
minutes until volitional fatigue. An automated blood pressure monitor using an arm cuff positioned
around the left brachial artery and a heart rate monitor chest strap were utilized to record data
immediately upon completion of the test while seated on the cycle ergometer to analyze indices of
cardiac and vascular function. Data was analyzed using a Pearson correlation coefficient to examine
the association (r) between anthropometric characteristics and indices of cardiovascular function.
This study was approved by and followed the recommendation of the Research Ethics Review board
at Langara College. RESULTS: A significant and inverse association between heart rate and both
body weight (r = -0.69, p < 0.05) and body surface area (r = -0.65, p < 0.05) were observed. A
positive and significant association were observed between; 1) stroke volume and both height (r =
0.82, p < 0.05) and body surface area (r = 0.72, p < 0.05), 2) height and cardiac output (r = 0.77, p <
0.05) and 3) body mass index and both mean arterial pressure (r = 0.64) and systolic blood pressure
(r = 0.64, p < 0.05). CONCLUSION: Indices of both cardiac and vascular function are associated with
anthropometric characteristics at VO2 peak in healthy college students.

Correlation Matrix: Association between Anthropometry and Cardiac Function at VO2 Peak
1
2
3
4
1 Height (cm)
2 Weight (kg)
0.80
2
3 Body Surface Area (m )
0.92
0.97
4 BMI (kg/m2)
0.48
0.90
0.79
5 Heart Rate (bpm)
-0.52
-0.69*
-0.65*
-0.61
6 Cardiac Ouput (L·min-1)
0.77*
0.47
0.62
0.18
0.82*
0.72*
7 Stroke Volume (mL)
0.59
0.31
Pearson correlation coefficients. * p < 0.05 (n = 10)
Correlation Matrix: Association between Anthropometry and Vascular Function at VO2 Peak
1
2
3
4
1 Height (cm)
2 Weight (kg)
0.80
3 Body Surface Area (m2)
0.92
0.97
4 BMI (kg/m2)
0.48
0.90
0.79
5 Systolic Blood Pressure (mmHg)
0.33
0.60
0.50
0.64*
6 Diastolic Blood Pressure (mmHg)
-0.45
-0.11
-0.23
0.11
7 Mean Arterial Blood Pressure (mmHg)
0.23
0.57
0.45
0.64*
8 Total Peripheral Resistance (mmHg.sec/mL) -0.62
-0.21
-0.41
0.08
Pearson correlation coefficients. * p < 0.05 (n = 10)

5

6

7

-0.19
-0.41

0.97

-

5

6

7

8

0.07
0.98
0.30

0.25
0.60

0.40

-

INTRODUCTION

METHODOLOGY

CONCLUSION

REFERENCES

When evaluating cardiovascular function, practitioners
often focus on blood pressure and cardiac output to
determine the performance of the cardiovascular
system (Chantler et al., 2005). Adjustments in
cardiovascular function are required during exercise to
assure the metabolic demands of the body are
achieved. Such adjustments provide practitioners a
comprehensive measure of the malleability of the
cardiovascular system and its relationship to
anthropometry (Vella et al., 2012, Chantler et al., 2005).
Establishing which anthropometric measurements are
associated with cardiovascular function, is important
when exploring differences found between subjects in
data sets (Chantler et al., 2005). The purpose of this
investigation was to examine the association between
indices of cardiovascular function and anthropometric
characteristics at VO2 peak in healthy college students.

Ten healthy college students (4 males & 5 females)
with an age of (mean ± SD) 21.4 ±1.2 yr, a weight
of 64.3 ±16.8 kg and a height of 163.0 ±10.5 cm
performed a graded maximal exercise test on a
cycle ergometer. The initial flywheel resistance was
set at 2W x bodyweight (kg) and involved 25 W
increments every three minutes until volitional
fatigue. An automated blood pressure monitor using
an arm cuff positioned around the left brachial artery
and a heart rate monitor chest strap were utilized to
record data immediately upon completion of the test
while seated on the cycle ergometer to analyze
indices of cardiac and vascular function. Data was
analyzed using a Pearson correlation coefficient to
examine the association (r) between anthropometric
characteristics and indices of cardiovascular
function.

The results presented in this investigation displayed
significant associations between anthropometric
characteristics and indices of both cardiac and
vascular function at VO2 peak. This evidence is
suggestive that body size (height, weight, body
surface area, and body mass index), may influence
cardiovascular function at maximal aerobic exercise.
The current investigation expands on our previous
work
displaying
the
association
between
anthropometry and maximal anerobic performance
(Khan et at., 2021). These findings may be useful for
practitioners when reviewing heterogenous data sets
or for developing future studies examining
cardiovascular function in diverse populations, as
anthropometry may account for confounding
outcomes.

Chantler, P. D., Clements, R. E., Sharp, L., George, K.
P., Tan, L. B., Goldspink, D. F. (2005). The influence of
body size on measurements of overall cardiac function.
American Journal of Physiology – Heart and Circulatory
Physiology, 289(5), 2059-2065.

KINESIOLOGY
Corresponding Author: aperrotta@langara.ca

Khan, A. D., Correa, C. J. & Perrotta, A. S. (2021). The
association between fatigue index and anthropometric
and physiological performance measures from an
anaerobic performance assessment in healthy college
students. Applied Physiology, Nutrition & Metabolism
(45), Canadian Society for Exercise Physiology Annual
General Meeting - CSEP 2020.
Vella, C. A., Paul, D. R., Bader, J. (2012). Cardiac
response to exercise in normal-weight and obese,
Hispanic men and women: implications for exercise
prescription. Acta Physiologica, 205(1), 113-123.
This study was funded by the Langara College RSAF-1
Grant.