Physiological Reports. 2020;8:e14551. 
 
  |  1 of 13
https://doi.org/10.14814/phy2.14551
wileyonlinelibrary.com/journal/phy2
DOI: 10.14814/phy2.14551  
O R I G I N A L  R E S E A R C H
Indices of leg resistance artery function are independently related 
to cycling V̇O2max
Jayson R. Gifford1,2
 |   Brady E. Hanson1 |   Meagan Proffit1,2 |   Taysom Wallace1 |   
Jason Kofoed1 |   Garrett Griffin1 |   Melina Hanson1
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original 
work is properly cited.
© 2020 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society
1Department of Exercise Sciences, Brigham 
Young University, Provo, UT, USA
2Program of Gerontology, Brigham Young 
University, Provo, UT, USA
Correspondence
Jayson R. Gifford, Department of Exercise 
Sciences, Brigham Young University, 
Provo, UT 84602, USA.
Email: jaysongifford@byu.edu
Funding information
Bobbit Heart Disease Award, Grant/Award 
Number: 1
Abstract
Purpose: While maximum blood flow influences one's maximum rate of oxygen 
consumption (V̇O2max), with so many indices of vascular function, it is still unclear 
if vascular function is related to V̇O2max in healthy, young adults. The purpose of 
this study was to determine if several common vascular tests of conduit artery and 
resistance artery function provide similar information about vascular function and 
the relationship between vascular function and V̇O2max.
Methods: Twenty-two healthy adults completed multiple assessments of leg vas-
cular function, including flow-mediated dilation (FMD), reactive hyperemia (RH), 
passive leg movement (PLM), and rapid onset vasodilation (ROV). V̇O2max was 
assessed with a graded exercise test on a cycle ergometer.
Results: Indices associated with resistance artery function (e.g., peak flow during 
RH, PLM, and ROV) were generally related to each other (r = 0.47–77, p < .05), 
while indices derived from FMD were unrelated to other tests (p < .05). Absolute 
V̇O2max (r = 0.57–0.73, p < .05) and mass-specific V̇O2max (r = 0.41–0.46, p < .05) 
were related to indices of resistance artery function, even when controlling for fac-
tors like body mass and sex. FMD was only related to mass-specific V̇O2max after 
statistically controlling for baseline artery diameter (r = 0.44, p < .05).
Conclusion: Indices of leg resistance artery function (e.g., peak flow during RH, 
PLM, and ROV) relate well to each other and account for ~30% of the variance in 
V̇O2max not accounted for by other factors, like body mass and sex. Vascular inter-
ventions should focus on improving indices of resistance artery function, not conduit 
artery function, when seeking to improve exercise capacity.
K E Y W O R D S
flow-mediated dilation, passive leg movement, rapid onset vasodilation, vascular function, 
V̇O2max
2 of 13 | 
  
GIFFORD et al.
1 | 
INTRODUCTION
One's maximum rate of oxygen consumption (V̇O2max) 
strongly influences exercise performance and is also a 
strong predictor of cardiovascular risk (Poole, Behnke, & 
Musch,  2020). While many systems may limit V̇O2max 
(Wagner, 2008), the cardiovascular system often serves as a 
significant bottleneck, with untrained individuals often ex-
hibiting a much lower cardiac output and muscle blood flow 
than endurance-trained individuals (Gifford et  al.,  2016; 
Levine,  2008). Evidence indicates that cardiac output and 
muscle blood flow during exercise are both strongly in-
fluenced by the ability of the peripheral vasculature to di-
late (Bada, Svendsen, Secher, Saltin, & Mortensen,  2012; 
Hanson, Proffit, & Gifford,  2020; Joyner & Casey, 2015). 
While large conduit arteries, like the brachial or femoral ar-
teries, may dilate during exercise (Tremblay & Pyke, 2018), 
it is the dilation of the network of small resistance arteries, 
whose total cross-sectional area far exceeds that of the large 
conduit arteries (Wiedman,  1963), that primarily regulates 
the increase in blood flow during exercise (Joyner & Casey, 
2015; VanTeeffelen & Segal, 2006).
With fluctuations in the radius of the arterial circulation 
having such a profound impact on blood flow and cardiac 
output, several studies have sought to determine if the ability 
of the vasculature to dilate, often termed vascular function 
(Gifford & Richardson, 2017), is related to exercise capacity 
(Montero, 2015).
In 
such 
studies 
vascular 
function 
has 
usually 
(Montero,  2015) been quantified with a technique that 
measures the vasodilator ability of a conduit artery (Flow-
Mediated Dilation, FMD) in a region not majorly involved 
in most tests of V̇O2max, the arm. Despite vascular function 
being measured in a conduit artery that does not perfuse the 
main exercising muscles, most studies demonstrate a sig-
nificant, positive relationship between brachial FMD and 
V̇O2max during running or cycling exercise (Montero, 2015). 
However, as noted by Montero (Montero, 2015), the com-
parison of conduit artery function of an upper limb to the 
V̇O2max elicited by a lower-body exercise (e.g., cycling or 
running) is problematic since upper-limb vascular function 
is not reflective of lower-limb vascular function (Thijssen, 
Rowley, et al., 2011), and exercise training is known to elicit 
local adaptations in conduit artery structure that may mask 
any adaptation in local vascular function (Green, Spence, 
Rowley, Thijssen, & Naylor, 2012). Moreover, given the neg-
ligible role of conduit arteries in regulating exercise blood 
flow (Joyner & Casey, 2015), the relevance of conduit artery 
function to exercise capacity is unclear.
Multiple noninvasive assessments intended to interrogate 
the function of the resistance arteries (Limberg et al., 2020) 
of the lower limbs have been developed in recent years. 
Indeed, tests such as reactive hyperemia (RH) in response to 
cuff occlusion and removal, the hyperemic response to pas-
sive leg movement (PLM), and the rapid onset of vasodila-
tion and hyperemia in response to a single muscle contraction 
(ROV) have been shown to be NO dependent (Broxterman 
et al., 2017; Casey, Walker, Ranadive, Taylor, & Joyner, 2013; 
Gifford & Richardson, 2017; Limberg et al., 2020) and related 
to peak blood flow during knee extension exercise (Hanson 
et al., 2020). Nevertheless, it is not clear if these distinct indi-
ces of vascular function actually reflect the same underlying 
physiology and are related to each other. It is also unclear how 
relevant these indices of resistance artery function (Limberg 
et al., 2020) are to exercise capacity. If these indices of resis-
tance artery vascular function truly are representative of the 
function of the resistance arteries, which are largely respon-
sible for blood flow control (Joyner & Casey, 2015), one may 
expect them to relate well to exercise capacity.
To date, the relationships between the various tests of vas-
cular function in the lower limb and their relevance to exer-
cise capacity have not been extensively explored. Therefore, 
the purpose of this study was twofold. First, we sought to 
determine how well the various indices of conduit and re-
sistance artery function relate to each other. Second, we 
sought to determine if aerobic exercise capacity, assessed by 
V̇O2max during cycling exercise, is related to various indices 
of conduit artery and resistance artery function.
2 | 
METHODS
2.1 | Subjects
Twenty-two young, healthy subjects (13 males, 9 females, 
18–30  years old) completed the study. All subjects were 
healthy, nonobese, nonsmokers, free from medications 
that would affect their hemodynamic responses to exercise 
(Gifford & Richardson, 2017). Data for females were col-
lected within the first 7 days of the menstrual cycle to mini-
mize variability attributable to hormonal fluctuations. Prior 
to starting the study, the Institutional Review Board (IRB) 
at Brigham Young University (BYU) found the study to be 
safe, ethical, and in agreement with the main principles out-
lined in the Declaration of Helsinki. Prior to participation, all 
subjects provided informed consent. While the study was per-
formed in accordance principles outlined in the Declaration 
of Helsinki, it was not registered on clinicaltrials.gov before 
data collection.
2.2 | Procedures
Subjects reported to the laboratory on three occasions hav-
ing fasted for 4 hr, rested from exercise and refrained from 
alcohol or caffeine consumption for  ~24  hr (Gifford & 
   | 
3 of 13
GIFFORD et al.
Richardson, 2017). Each visit was separated by a minimum 
of 24 hr. All data collection was completed on the subject's 
right leg, regardless of leg dominance.
On the first visit, body measurements including height (cm), 
body mass (kg), and body mass index (BMI, kg·m−2). After 
resting supine for 20 min, vascular function was assessed by 
the FMD and RH techniques on the superficial femoral artery 
as described below. Subsequently, the maximum rate of oxygen 
consumption during cycling (i.e., V̇O2max) was assessed with a 
graded exercise test (25 watt increments per minute) on a cycle 
ergometer (Excaliber Sport, Lode, Groningen, Netherlands) 
with a Parvo metabolic cart (True One, Parvo-Medics Inc., 
Sandy, Utah, USA) (Gifford et al., 2016)). The greatest power 
sustained for 1 min during the graded exercise test was identified 
as Graded Exercise Test Max (GXTmax). Following 30 min of 
rest from the initial graded exercise test, a constant-load test 
(100% GXTmax) until exhaustion test was performed to verify 
the initial V̇O2max results (Poole & Jones, 2017). The verifi-
cation V̇O2max for all subjects was within ±5% of the initial 
V̇O2max, supporting the attainment of V̇O2max. The higher of 
the two values was recorded as the final V̇O2max.
On the second visit, vascular function was assessed first 
with the passive leg movement (PLM) technique in triplicate. 
Following a ~ 5-min recovery period, vascular function was 
then assessed by the rapid onset vasodilation (ROV) tech-
nique elicited by single kick knee extension exercise as de-
scribed below.
2.3 | Assessments of vascular function
2.3.1 | Flow-mediated dilation (FMD) and 
reactive hyperemia (RH)
During the first visit subjects reported to the laboratory to have 
vascular function assessed via FMD and RH on the superficial 
femoral artery according to current recommendations (Harris, 
Nishiyama, Wray, & Richardson,  2010) and as previously 
described (Hanson et al., 2020). While lying in the supine po-
sition, a 9 cm blood pressure cuff (Hokanson Inc., Bellevue, 
WA, USA) was placed on the thigh proximal to the knee-
cap. Following a 20-min acclimation/resting period, baseline 
measurements (diameter and blood flow) were gathered for 
60 s at the superficial femoral artery ~10 cm proximal to the 
cuff with a GE Logiq E ultrasound (General Electric Medical 
Systems, Milwaukee, WI, USA) operating with a B-mode 
frequency of 9 MHz and a Doppler frequency of 5 MHz. The 
cuff was then inflated for 5 min to 250 mmHg. Blood velocity 
and diameter data were collected for 2 min immediately after 
the release of the cuff pressure. Following the study, artery 
diameter was analyzed frame-by-frame by automated edge 
detection software (Quipu srl., Pisa, Italy) and averaged into 
1-s bins corresponding to 1-s average velocities. A 3-s rolling 
average was applied to smooth diameter and velocity data. 
Blood flow (ml·min−1) was calculated using the equation: 
blood ﬂow=[
(mean blood velocity)×(휋 ×(vessel radius2) ) x 60]
, 
where mean blood velocity is expressed in cm·s−1 and radius 
is expressed in cm. FMD measurements were expressed as a 
percent change in diameter and calculated with the equation:
Shear rate was calculated with the following equation 
Shear rate= 8×mean blood velocity
Diameter
. Subsequently FMD was also 
normalized for total shear area under the curve (i.e., FMD/
shear) as recommended and described by Harris et al (Harris 
et al., 2010). Peak flow during RH following the release of 
the cuff was identified as the greatest 1-s average of flow 
achieved following cuff release (Harris et al., 2010).
2.3.2 | Passive leg movement (PLM)
The hyperemic response induced by PLM, which is NO-
dependent (Broxterman et  al.,  2017; Mortensen, Askew, 
Walker, Nyberg, & Hellsten,  2012; Trinity et  al.,  2012) 
and strongly related to acetylcholine-induced hyperemia 
(Mortensen et al., 2012), was utilized to assess thigh vascular 
function according to recently published guidelines (Gifford 
& Richardson, 2017). Subjects were seated in an upright posi-
tion with knees fully extended (180°) for a 20-min acclimation 
period before any data were collected. Subsequently, resting 
blood flow was measured for 60 s at the common femoral artery 
utilizing a GE Logiq E ultrasound (General Electric Medical 
Systems, Milwaukee, WI, USA) operating with a B-mode 
frequency of 9 MHz, a Doppler frequency of 5 MHz, and an 
insonation angle of 60°. Subsequently, researchers manually 
moved the subject's leg back and forth from the extended posi-
tion of the knee (180°) to the flexed position (90°), at a rate 
of 60 knee extensions per min, while the subjects stayed re-
laxed with no voluntary muscle contraction, while blood flow 
was measured at the common femoral artery throughout. This 
procedure was completed three times with a ~15-min period of 
rest between each trial. Blood flow data were analyzed second-
by-second and a 3-s rolling average was applied to smooth the 
data. The peak blood flow and the area under the curve (PLM 
Total Flow) were identified for each of the three trials and then 
averaged together (Gifford & Richardson, 2017). The data pre-
sented in this manuscript are the average of the three trials.
2.3.3 | Rapid onset vasodilation (ROV)
The hyperemic response to a single muscle contraction (e.g., 
one leg extension) has also been shown to be NO dependent 
FMD (%)= (Peak Diameter−Baseline Diameter)
Baseline Diameter
×100.
4 of 13 | 
  
GIFFORD et al.
(Casey et al., 2013) and is indicative of the responsiveness of 
the vasculature to an exercise stimulus (Credeur et al., 2015; 
Hughes, Ueda, & Casey, 2016). For this study, the hyperemic 
response to a single knee extension of 60 Nm of work was 
used to quantify ROV. Subjects were seated in an upright 
position with legs hanging over the end of a seat with knees 
in a flexed position (knee at 90° flexion at rest). The right 
ankle was then connected to the cable of a knee extension 
machine (a basic pulley system that vertically displaces a se-
lected amount of weight – N.K. Products, Lake Elsinore, CA, 
USA). Subjects then fully extended their leg so that the verti-
cal displacement distance associated with a fully extended 
kick could be measured using a standard tape measure. This 
displacement distance was subsequently used to calculate 
the total work performed during the different kicks. Subjects 
were then familiarized with the kicking motion at various dif-
ferent weights.
Following 20-min recovery, ROV was assessed in du-
plicate in response to a full knee extension totaling 60 Nm 
of work. Repeated trials were separated by at least 2 min of 
recovery. As subjects of different leg lengths displaced the 
weights to different distances, the mass each subject lifted 
was adjusted for the absolute work kick so that the total 
work (i.e., Total Work  =  mass  ×  gravity  ×  displacement 
distance) was 60 Nm when extending the leg through a full 
90° range of motion. For each kick, 1 min of baseline data 
was collected while the leg was rested in a flexed position. 
Subsequently, subjects extended the knee to ~180° and then 
passively allowed the weight to flex the knee back to 90° with 
no engagement of knee flexor or extensor muscles during the 
knee flexion phase (e.g., active contraction during knee ex-
tension and no contraction during flexion). Femoral blood 
flow was assessed, as described for the PLM technique, for 
1 min of baseline prior to contraction, during the kick and for 
1 min following the kick. Data were subsequently analyzed 
second-by-second and a 3-s rolling average was applied to 
smooth the data. The peak blood flow (ROV Peak Flow) was 
subsequently identified as the greatest 1-s average of blood 
flow, while the total flow response (ROV Total Flow) was 
identified as the area under the curve for 60 s. As each ex-
ercise was performed in duplicate, the data reported in this 
manuscript are the average of both trials.
2.4 | Statistical analysis
Test–retest reliability of the variables that were performed 
in repeated measures (PLM-based indices in triplicate and 
ROV-based indices in duplicate) was assessed with intra-
class correlation (ICC) using a two-way mixed model based 
on absolute agreement. As the average of the multiple meas-
urements was used for the analysis in this study, the ICC 
for the average of the repeated measures, not the ICC for an 
individual measure, is reported. Criteria for classifying the 
level of reliability of measurements were based up those set 
forth by Koo & Li (2016), in which an ICC between 0.50 
and 0.75 is evidence of “moderate reliability”, an ICC be-
tween 0.75 and 0.90 is evidence of “good reliability”, and an 
ICC > 0.90 is evidence of “excellent reliability”.
Pearson correlation and a linear regression were utilized 
to determine the relationship between the various assess-
ments of vascular function and other variables. Categorical 
data, like sex, were dummy coded into correlations. Part/
partial correlation was utilized to determine the amount of 
unique variance shared by two variables when removing that 
related to a third variable. Principal components analysis 
was utilized to combine the large amount of information pro-
vided by the multiple indices of vascular function into fewer, 
discrete variables based on the shared variance among the 
different indices of vascular function. Specifically, major 
variables derived from the tests of vascular function (FMD 
% dilation, FMD/shear, RH Peak Flow, RH Total Flow, PLM 
Peak Flow, PLM Total Flow, ROV Peak Flow, and ROV Total 
Flow) were entered into a principal components analysis with 
orthogonal rotation (varimax). Factors with an eigenvalues 
greater than 0.7 were accepted and only variables with load-
ings greater than 0.7 were included in a factor (Field, 2009). 
An independent sample t-test was conducted to identify sex 
differences among the indices of vascular function. Alpha 
was set at p ≤ .05 a priori.
All statistical analyses were completed using SPSS ver-
sion 26 (SPSS Inc.). Data are expressed as the mean ± SE 
unless otherwise stated.
3 | 
RESULTS
3.1 | Test–retest reliability of PLM and 
ROV measurements
The repeated measurements of PLM Peak Flow and PLM 
Total Flow both exhibited “excellent reliability” with ICC 
equal to 0.91. The repeated measurements of ROV Peak 
Flow exhibited “excellent reliability” with ICC equal to 
0.96. The repeated measurements of ROV Total Flow exhib-
ited “moderate reliability” with ICC equal to 0.72. As men-
tioned in the methods section, the average of the repeated 
measurements was utilized for all subsequent analyses in 
this study.
3.2 | Relationship between the various 
assessments of vascular function
As illustrated in Figure 1 and further described in Table 1, 
the relationships between the multiple indices of vascular 
   | 
5 of 13
GIFFORD et al.
function were examined with Pearson correlation. In general, 
indices derived from resistance artery function tests (i.e., RH, 
PLM, and ROV) were related to each other (p < .05), but 
not to indices derived from conduit artery function tests (e.g., 
FMD, p > .05).
Principal components analysis of the variables listed in 
Table 1 was utilized to group indices that share substantial 
variance to condense the multiple indices of vascular func-
tion to fewer factors. In essence, this analysis determines 
the extent to which the various assessments of vascular 
function represent similar or distinct factors. The Kaiser-
Meyer-Olkin measure (KMO = 0.54) supported the sam-
pling adequacy for the factor analysis. Visual analysis of 
a scree plot indicated a breakpoint at two factors, support-
ing the inclusion of two different factors with eigenvalues 
greater than 0.7. Factor #1 was exclusively comprised of 
factors related to FMD (FMD % dilation and FMD/shear) 
with loading factors of 0.72 and 0.89, respectively. Factor 
#2 was comprised of the following variables with the load-
ing factors indicated in parentheses: RH Peak Flow (0.84), 
RH Total Flow (0.75), PLM Peak Flow (0.83), PLM Total 
Flow (0.74), and ROV Peak Flow (0.84). ROV total flow 
was not included in either factor.
3.3 | Relationship between indices of 
vascular function and V̇O2max
As illustrated in Figure 2 and further described in Table 2, 
variables associated with FMD were unrelated to mass-
specific and absolute V̇O2max (p = .12–0.40). Meanwhile, 
variables associated with the second factor revealed in fac-
tor analysis (e.g., RH Peak Flow, PLM Peak Flow, and 
ROV Peak Flow) exhibited moderate-to-strong correla-
tions with absolute and mass-specific V̇O2max (r = 0.56–
73, p < .05).
FIGURE 1 
Relationship between Different Indices of Vascular Function. (a) Relationship between the peak flow achieved during passive 
leg movement (PLM) and the peak flow achieved during the rapid onset vasodilation (ROV) test. (b) Relationship between PLM peak flow 
and the peak flow observed during a reactive hyperemia (RH) test. (c) Relationship between the peak flow achieved during the ROV and RH 
tests. (d) Relationship between flow-mediated dilation (FMD) of the superficial femoral artery and the peak flow achieved during an ROV test. 
(e) Relationship between FMD of the superficial femoral artery and the peak flow achieved during RH. (f) Relationship between FMD of the 
superficial femoral artery and the peak flow achieved during PLM. A solid trendline indicates a significant relationship between the two variables 
(p ≤ .05) while a dotted trendline indicates a nonsignificant relationship between the two variables (p > .05). Light gray circles represent data for 
females and dark gray circles represent data for males
6 of 13 | 
  
GIFFORD et al.
TABLE 1 
Relationship between various indices of vascular function
FMD (% 
Dilation)
FMD (%/ 
Shear)
RH peak flow 
(ml/min)
RH total flow 
(ml)
PLM peak flow 
(ml/min)
PLM total 
flow (ml)
ROV peak flow 
(ml/min)
ROV total flow 
(ml)
Factor 1
FMD (% 
Dilation)
-
r = 0.47
p = .04
r = −0.14
p = .55
r = −0.01
p = .99
r = −0.11
p = .64
r = 0.01
p = .96
r = −0.33
p = .15
r = −0.04
p = .85
FMD (%/ Shear)
r = 0.47
p = .04
-
r = −0.21
p = .37
r = −0.54
p = .01
r = −0.31
p = .18
r = −0.07
p = .78
r = −0.32
p = .17
r = 0.18
p = .45
Factor 2
RH peak flow 
(ml/min)
r = −0.14
p = .55
r = −0.21
p = .37
-
r = 0.82
p < .01
r = 0.47
p = .03
r = 0.31
p = .17
r = 0.77
p < .01
r = 0.36
p = .11
RH total flow 
(ml)
r = −0.01
p = .99
r = −0.54
p = .01
r = 0.82
p < .01
-
r = 0.40
p = .08
r = 0.23
p = .32
r = 0.57
p = .01
r = 0.09
p = .71
PLM peak flow 
(ml/min)
r = −0.11
p = .64
r = −0.31
p = .18
r = 0.47
p = .03
r = 0.40
p = .08
-
r = 0.89
p < .01
r = 0.64
p < .01
r = 0.24
p = .28
PLM total flow 
(ml)
r = 0.01
p = .96
r = −0.07
p = .78
r = 0.31
p = .17
r = 0.23
p = .32
r = 0.89
p = .01
-
r = 0.45
p = .04
r = 0.18
p = .41
ROV peak flow 
(ml/min)
r = −0.33
p = .15
r = −0.32
p = .17
r = 0.77
p < .01
r = 0.57
p = .01
r = 0.64
p < .01
r = 0.45
p = .04
-
r = 0.63
p < .01
ROV total flow 
(ml)
r  = −0.04
p  = .85
r  = 0.18
p  = .45
r  = 0.36
p  = .11
r  = 0.09
p  = .71 .01
r  = 0.24
p  = .28
r  = 0.18
p  = .41
r  = 0.63
p  < .01
Note: The terms “Factor 1” and “Factor 2” at the left of the table refer to the variables that were grouped together via principal components analysis. Significant relationships are in bold font
Abbreviations: FMD, flow-mediated dilation; PLM: passive leg movement; RH: Reactive Hyperemia; ROV: Rapid onset vasodilation.
   | 
7 of 13
GIFFORD et al.
3.4 | Other factors that relate to the 
indices of vascular function
As described in Table 3, factors related to a subject's anat-
omy, sex, and body mass were related to the outcomes of the 
vascular function tests. Notably, FMD exhibited a negative 
correlation with the artery diameter at baseline (r = −0.64, 
p = .002), such that individuals with larger arteries tended 
to exhibit lower FMD (Table 3). Meanwhile, body mass was 
positively related with RH Peak Flow (r = 0.47, p = .01), 
PLM Peak Flow (r = 0.62, p < .01), and ROV Peak Flow 
(r = 0.53, p = .01).
3.4.1 | Sex differences in indices of 
vascular function
PLM Peak Flow (Female: 1,140  ±  98  ml  min−1, Male: 
1626  ±  114  ml  min−1; p  =  .006) and PLM Total Flow 
(Female: 333 ± 57 ml, Male: 566 ± 56 ml; p = .01) were 
both significantly greater in males than females. ROV peak 
flow also tended to be greater in males than females (Female: 
1762 ± 149 ml min−1, Male: 2,196 ± 186 ml min−1; p = .10), 
while FMD (% Dilation) tended to be lower in males than fe-
males (Female: 6.98 ± 0.78%, Male: 4.73 ± 0.85%; p = .09). 
The sex difference in PLM Peak Flow and Total Flow disap-
peared when controlling for body mass (p = .98), which was 
significantly different between the females and males in the 
study (57.00 ± 1.69 kg vs. 82.35 ± 1.69 kg, respectively, 
p < .01).
3.5 | Relationship between vascular 
function and V̇O2max when controlling for 
other variables
Recognizing that several other factors may potentially influ-
ence the responses observed in the different vascular func-
tion tests (see Table  3), the relationship between V̇O2max 
and the various indices of vascular function was examined 
when controlling for potentially confounding variables. 
When controlling for the variation in FMD accounted for by 
baseline diameter, FMD was found to be significantly related 
to the mass-specific V̇O2max (r = 0.44, p = .04; Table 4). 
Moreover, when simultaneously accounting for the variance 
related to body mass, sex, and BMI with partial correlation, 
RH Peak Flow, PLM Peak, and ROV Peak Flow were still 
significantly related to absolute V̇O2max (r  =  0.49–0.59, 
p < .05) and mass-specific V̇O2max (r = 0.46–0.55, p ≤ .05).
Finally, stepwise linear regression was performed to 
explore the possibility of predicting V̇O2max with vascu-
lar function data and other subject characteristics. Of the 
five variables entered into the regression (body mass, sex, 
height, BMI, and PLM Peak Flow), only body mass, PLM 
FIGURE 2 
The Relationship between 
Vascular Function and The Maximum Rate 
of Oxygen Consumption (V̇O2max) during 
Cycling. The relationship between absolute 
V̇O2max and (a) flow-mediated dilation 
(FMD) of the superficial femoral artery (b) 
peak flow during Reactive hyperemia (RH), 
(c) peak flow during passive leg movement 
(PLM) and (d) peak flow during a rapid 
onset vasodilation (ROV) test. V̇O2max. 
A solid trendline indicates a significant 
relationship between the two variables 
(p ≤ .05), while a dotted trendline indicates 
a nonsignificant relationship between the 
two variables (p > .05). Light gray circles 
represent data for females and dark gray 
circles represent data for males
8 of 13 | 
  
GIFFORD et al.
Peak Flow, and BMI were retained by the stepwise regres-
sion, yielding the following equation (R2 = 0.83, p < .01): 
Absolute V̇O2max = 970.82 + 55.83 (Body Mass) + 0.68 
(PLM Peak Flow) – 121.75 (BMI).
4 | 
DISCUSSION
The purpose of this study was to determine how well the vari-
ous indices of vascular function relate to each other and if 
aerobic capacity, assessed by V̇O2max, is related to these in-
dices of vascular function. The results of this inquiry yielded 
two major findings. First, in agreement with current thought 
(Limberg et al., 2020; Thijssen, Black, et al., 2011), the as-
sessments of conduit artery function (FMD and its deriva-
tives) and resistance artery function (derivatives of RH, PLM, 
and ROV) appear to reflect two different aspects of vascular 
function, with the indices derived from the RH, PLM, and 
ROV being strongly correlated with each other, but not with 
FMD and its derivatives. The second major finding of this 
study is that leg vascular function, especially resistance ar-
tery function, is strongly related to V̇O2max, accounting for 
approximately 30% of the variance in V̇O2max not accounted 
for by known influencers, like body mass, sex, and BMI.
4.1 | Are the various indices of vascular 
function interchangable with one another?
Multiple methods exist for quantifying a person's vascular 
function, yet it is unclear if these various methods are related 
to each other. Therefore, in the current study vascular func-
tion was measured in multiple ways (FMD, RH, PLM, and 
ROV) on a group of young, healthy adults. As illustrated in 
Figure 1 and further described in Table 1, lower limb vas-
cular function assessed by the resistance artery tests RH, 
PLM, and ROV exhibits strong relationships with each other 
(r  =  0.54–0.83, p  <  .05), supporting the notion that they 
reflect some of the same physiological processes (Limberg 
et  al.,  2020). This comes in agreement with data from 
Rossman, Groot, Garten, Witman, & Richardson (2016) and 
Walker et al. (2016) who observed significant correlations 
between PLM-induced hyperemia and RH in various popu-
lations. However, as was the case for Rossman et al. (2016), 
vascular function assessed by FMD of the superficial femo-
ral artery was not related to the other measurements of vas-
cular function (e.g., PLM-induced hyperemia) examined in 
the current study (Figure 1, Table 1).
The lack of relationship between FMD and the other vari-
ables should not be interpreted as evidence of superiority 
or inferiority of one test over another, but as an indication 
that these validated tests of vascular function capture differ-
ent aspects of cardiovascular physiology. Indeed, principal 
components analysis, which consolidated the various indices 
of vascular function into two different factors, supports the 
idea that the results of the various tests capture two general 
aspects of vascular physiology. As illustrated in Table  1, 
Factor 1 is comprised exclusively of FMD and factors de-
rived from the FMD test, which have been suggested to rep-
resent conduit artery function (Thijssen, Black, et al., 2011). 
Meanwhile, Factor 2 was comprised of the main indices de-
rived from RH, PLM, and ROV, all of which have recently 
been referred to as tests of resistance artery or resistance 
vessel function (Limberg et al., 2020). Thus, the current data 
indicate that the tests of resistance artery function used in 
the current study are relatively interchangeable, but that tests 
reflecting conduit artery function should not be considered 
as surrogates for tests of resistance artery function, or vice 
versa.
TABLE 2 
Relationship between different indices of vascular 
function and maximum rate of oxygen consumption (V̇O2max) 
achieved during cycling
Mass-Specific V̇O2max
(ml/kg/min)
Absolute V̇O2max
(ml/min)
FMD (% 
Dilation)
r = 0.20
p = .40
r = −0.24
p = .31
FMD (%/shear)
r = −0.27
p = .24
r = −0.35
p = .12
RH Peak Flow 
(ml/min)
r = 0.26
p = .25
r = 0.49
p = .02
RH Total Flow 
(ml)
r = 0.41
p = .06
r = 0.44
p = .04
PLM Peak Flow 
(ml/min)
r = 0.48
p = .03
r = 0.72
p < .01
PLM Total 
Flow (ml)
r = 0.42
p = .05
r = 0.65
p < .01
ROV Peak Flow 
(ml/min)
r = 0.36
p = .11
r = 0.58
p < .01
ROV Total 
Flow (ml)
r = 0.10
p = .65
r = 0.03
p = .91
Body Mass (kg)
r = 0.16
p = .49
r = 0.84
p < .01
Body Mass 
Index (kg/m2)
r = −0.16
p = .49
r = 0.64
p < .01
Sex 
(Female = −1, 
Male = +1)
r = 0.01
p = .98
r = 0.79
p < .01
Note: Note that sex has been dummy coded with females being coded as −1 
and males being entered as + 1. In this dummy coding scenario, a negative 
correlation indicates greater values are associated with the female sex, while a 
positive correlation indicates greater values are associated with the male sex. 
Significant relationships are in bold font
Abbreviations: FMD, flow-mediated dilation; PLM, passive leg movement; RH, 
reactive hyperemia; ROV, rapid onset vasodilation.
   | 
9 of 13
GIFFORD et al.
4.2 | Are conduit and/or resistance artery 
function related to V̇O2max?
The overarching aim of this study was to answer the ques-
tion, “Is vascular function related to V̇O2max?” However, 
the data in Table  1 make it clear that one must clarify 
which aspect of vascular function is of interest when 
answering this question, since indices of conduit artery 
function and resistance artery function are not well cor-
related. As illustrated in Figure  2, resistance artery, but 
not conduit artery, function was strongly related to ab-
solute V̇O2max, meaning that an individual with a large 
hyperemic response to the vascular tests would be likely 
to achieve a greater maximal rate of oxygen consumption 
and power output (e.g., GXTmax) during a graded exer-
cise test. Meanwhile, mass-specific V̇O2max was only re-
lated to resistance artery function assessed by PLM Peak 
Flow (r = 0.46, p = .03) and RH Total Flow (r = 0.41, 
p  =  .05), but not conduit artery function assessed by 
FMD (r = 0.20, p = .40). The strong relationship between 
Baseline Artery 
Diameter (mm)
Body Mass
(kg)
BMI
(kg/m2)
Sex 
(Female = −1, 
Male = +1)
FMD (% 
Dilation)
r = −0.64
p < .01
r = −0.47
p = .03
r = −0.48
p = .03
r = −0.38
p = .09
FMD (%/shear)
r = −0.49
p = .03
r = −0.27
p = .26
r = −0.33
p = .17
r = −0.15
p = .54
RH Peak Flow 
(ml/min)
r = 0.65
p < .01
r = −0.47
p = .03
r = 0.48
p = .03
r = 0.30
p = .19
RH Total Flow 
(ml)
r = 0.48
p = .03
r = 0.28
p = .22
r = 0.31
p = .17
r = 0.17
p = .46
PLM Peak 
Flow (ml/min)
r = 0.85
p < .01
r = 0.62
p < .01
r = 0.59
p < .01
r = 0.56
p < .01
PLM Total 
Flow (ml)
r = 0.74
p < .01
r = 0.58
p < .01
r = 0.54
p < .01
r = 0.54
p = .01
ROV Peak 
Flow (ml/min)
r = 0.75
p < .01
r = 0.53
p = .01
r = 0.61
p < .01
r = 0.35
p = .11
ROV Total 
Flow (ml)
r = 0.18
p = .43
r = 0.01
p = .99
r = 0.15
p = .50
r = 0.03
p = .98
Note: Note that sex has been dummy coded with females being coded as −1 and males being entered as +1. 
Significant relationships are in bold font.
Abbreviations: BMI, body mass index; FMD, flow-mediated dilation; PLM, passive leg movement; ROV, 
rapid onset vasodilation.
TABLE 3 
Relationship between 
indices of vascular function and other 
subject characteristics
Mass-Specific V̇O2max
(ml/kg/min)
Absolute V̇O2max
(ml/min)
FMD (% Dilation)
Controlling for baseline diameter
r = 0.45
p = .04
r = 0.35
p = .14
Peak Reactive Hyperemia (ml/
min)
Controlling for body mass, sex, 
and BMI
r = 0.46
p = .05
r = 0.49
p = .04
PLM Peak Flow (ml/min)
Controlling for body mass, sex, 
and BMI
r = 0.53
p = .02
r = 0.58
p = .01
ROV Peak Flow (ml/min)
Controlling for body mass, sex, 
and BMI
r = 0.55
p = .01
r = 0.59
p < .01
Note: Note that sex has been dummy coded with females being coded as −1 and males being entered as +1. 
Significant relationships are in bold font.
Abbreviations: BMI, body mass index; FMD, flow-mediated dilation; PLM, passive leg movement; ROV, 
rapid onset vasodilation.
TABLE 4 
Partial correlations 
between indices of vascular function and 
the maximum rate of oxygen consumption 
(V̇O2max) during cycling exercise when 
controlling for potentially confounding 
variables
10 of 13 | 
  
GIFFORD et al.
resistance artery function and V̇O2max in these healthy 
young adults is consistent with previous studies that have 
reported relationships between V̇O2max and the hypere-
mic responses to RH (Robbins et al., 2011) and ROV (19) 
in various populations.
It makes sense that V̇O2max would be more related 
to resistance artery function than conduit artery func-
tion since V̇O2max is strongly influenced by maximum 
blood flow (Gifford et al., 2016; Levine, 2008) which is 
primarily controlled by the dilation and constriction of 
the myriad of resistance arteries (Dodd & Johnson, 1991; 
Joyner & Case y, 2015). Along these lines, our group re-
cently reported that factors associated with resistance ar-
tery function (e.g., PLM Peak Flow and ROV Peak Flow) 
were very predictive of peak blood flow achieved during 
knee extension exercise, while FMD was not (Hanson 
et al., 2020). A large PLM, RH, or ROV response seems 
to be indicative of a limb with a network of resistance 
arteries that can accommodate high rates of blood flow, 
thereby facilitating a greater V̇O2max. Thus, interven-
tions targeting resistance artery function may potentially 
have more impact on exercise tolerance in healthy adults 
than interventions seeking to improve conduit artery 
function. Future studies could potentially further exam-
ine the relationship between conduit artery function and 
V̇O2max by measuring conduit artery diameter during 
a V̇O2max test. Unfortunately, such precise diameter 
measurements are not currently possible during cycling 
exercise.
Contrary 
to 
our 
findings, 
previous 
research 
(Montero, 2015) has indicated that FMD is typically re-
lated to V̇O2max, most commonly the mass-specific 
V̇O2max. The reason for the disagreement between find-
ings may be due to measurement location. In contrast to 
most previous studies, which measured FMD in the arm, 
the current study compared vascular function, including 
FMD, assessed in the lower limb to cardiorespiratory fit-
ness assessed during a predominantly lower-limb exercise 
like cycling or running. Indeed, the aforementioned me-
ta-analysis (Montero,  2015) concluded “further studies 
are needed to elucidate the association of cardiorespi-
ratory fitness with lower limb endothelial function.” As 
mentioned earlier, exercise-induced adaptations to arterial 
structure and diameter appear to be of a greater magnitude 
in exercise-trained muscles than in nontrained muscles 
(Rowley et al., 2012). It is possible that exercise-induced 
adaptations in the diameter of the superficial femoral ar-
tery masked the relationship between FMD in the lower 
limb and V̇O2max. Thus, further investigation into the 
relationship between vascular function and V̇O2max, 
when controlling for potentially confounding variables, is 
warranted.
4.3 | What other factors influence the 
indices of vascular function?
It is important to recognize that although these indices of vas-
cular function are related to NO bioavailability and endothe-
lial function (Casey & Joyner, 2011; Green, 2005; Mortensen 
et al., 2012), multiple other factors, besides endothelial func-
tion, can influence the results of these vascular function 
tests. As listed in Table 3, the measures of vascular func-
tion utilized in the current study are sensitive to several fac-
tors that should be considered when interpreting the results 
of a test. For example, in agreement with previous research 
(Anderson et al., 1995; Celermajer et al., 1992), FMD was 
negatively related to baseline artery diameter, such that indi-
viduals with a large diameter artery at baseline tend to exhibit 
a lower FMD. In the initial paper to link brachial artery FMD 
to coronary endothelial dysfunction (Anderson et al., 1995), 
the authors indicated that baseline brachial artery diameter 
was the strongest predictor of a decreased FMD, not the coro-
nary endothelial dysfunction for which the paper is famous. 
With ~41% of the variation in FMD in the current sample 
being related to baseline diameter (i.e., R2 = 0.41, p < .01), 
it is possible that the arterial enlargement associated with ha-
bitual exercise (Green et al., 2012) may have masked any 
potential relationship between FMD and V̇O2max in the cur-
rent study.
As depicted in Table 3 tests of resistance artery func-
tion are strongly related with body mass and BMI, such 
that larger individuals with larger thighs tend to exhibit a 
greater RH Peak Flow, PLM Peak Flow, and ROV Peak 
Flow. It is not possible to conclude why this relationship 
exists from the current data, but it seems likely that larger 
limbs have a larger vascular network, which can accommo-
date greater flows. Whatever the mechanism, the influence 
of body mass on the measures of resistance artery function 
is not trivial and should be considered when interpreting 
these tests, especially when relating vascular function to 
V̇O2max, which is also strongly influenced by body mass 
(Proctor & Joyner, 1997).
Sex is also related to resistance artery function (Table 3), 
with males exhibiting a greater peak flow response to PLM. 
A similar tendency was also observed with ROV Peak Flow 
(p = .10). However, this sex difference in resistance artery 
function appears to be driven by differences in body mass 
between females and males (males were 25.35  ±  2.73  kg 
heavier than the females in this study, p < .01), since the sex 
differences in PLM Peak Flow disappeared when statistically 
removing variance in PLM Peak Flow accounted for by body 
mass (p = .98).
In addition to the factors mentioned above, previous re-
search has revealed other factors that must be considered when 
performing and interpreting tests of vascular function. For 
   | 
11 of 13
GIFFORD et al.
example, the placement of the cuff proximal or distal to the site 
of measurement may impact the results of an FMD test (Doshi 
et al., 2001), the frequency of movement and the range of mo-
tion of PLM (Gifford et al., 2019), and the amount of work 
performed during ROV (Tschakovsky et al., 2004) have been 
shown to strongly impact the results. Therefore, these factors 
should be considered when exploring the relationship between 
vascular function and other variables, like V̇O2max.
4.4 | Is vascular function related to V̇O2max 
when controlling for potentially confounding 
variables?
As described above, several factors, independent of the 
health of the vascular system, may impact the results of a 
vascular function test. Thus, it is possible that the underlying 
influences of variables, like artery diameter and body size, 
either mask potential relationships between vascular func-
tion and V̇O2max or potentially account for them. Partial 
correlations between the indices of vascular function and 
V̇O2max were performed to statistically remove variance ac-
counted for potentially confounding variables. As described 
in Table 4, when statistically controlling for the variance in 
FMD related to baseline artery diameter, superficial femoral 
artery FMD does exhibit the weak relationship with mass-
specific V̇O2max (r = 0.45, p = .05) that has been indicated 
by studies measuring FMD in the arm (Montero, 2015). No 
such relationships were observed with absolute V̇O2max 
(p > .05). Thus, conduit artery function does appear to be 
weakly related to mass-specific V̇O2max, but the relationship 
is obscured by variation in artery diameter.
While indices of resistance artery function are related 
to V̇O2max (Table 2), this relationship could potentially be 
completely dependent upon body mass, sex, and BMI, which 
are also strongly related to vascular function (Table 3) and 
V̇O2max (Table 2). Thus, the partial correlation between the 
indices of resistance artery function and V̇O2max was ex-
plored when simultaneously controlling for body mass, sex, 
and BMI. As described in Table 4, the relationship between 
resistance artery function and absolute V̇O2max persists, 
while the relationship between resistance artery function 
and mass-specific V̇O2max is apparently strengthened when 
removing any variance in vascular function and V̇O2max 
related to body mass, sex, and BMI. Similarly, previous re-
search indicated that PLM Peak Flow was related to peak 
exercise blood flow in a mass-independent manner (Hanson 
et al., 2020). Thus, the relationship between resistance artery 
function and V̇O2max occurs independently and is not merely 
a product of sex, mass, or BMI.
As described by Wagner (Wagner, 2008), V̇O2max can be 
simultaneously influenced by the function of many systems, 
including the lungs, heart, arteries, skeletal muscle mass, and 
mitochondria. With so many factors influencing V̇O2max in 
healthy young adults that resistance artery function accounts 
for ~30% of the variance in V̇O2max not accounted for by 
body mass, sex, and BMI is quite notable. Factors that were 
not measured in the current study, like maximal cardiac out-
put, mitochondrial density, and muscle oxygen diffusion are 
likely to account for some of the remaining variance (Gifford 
et al., 2016; Wagner, 2008). Since V̇O2max is limited by dif-
ferent factors in different populations (Gifford et al., 2016; 
Wagner,  2008), the amount of variance in V̇O2max ac-
counted for by resistance artery function likely differ in other 
populations.
4.5 | Clinical relevance
Since V̇O2max strongly influences exercise performance and is 
also a strong predictor of cardiovascular risk (Poole et al., 2020), 
there is great interest in identifying what limits or reduces an 
individual's V̇O2max (Wagner, 2008) so that appropriate steps 
may be taken to improve it. With resistance artery function 
being related to both maximum exercise blood flow (Hanson 
et al., 2020) and V̇O2max (Table 2), noninvasive assessments, 
like passive-leg movement (PLM)-induced hyperemia, may 
conceivably be used to easily determine the likelihood that im-
pairments in muscle resistance artery function and leg blood 
flow impair a person's V̇O2max. Since the PLM technique oc-
curs while the subject is in a completely rested state, this could 
be particularly useful in scenarios in which direct assessment of 
exercise blood flow may not be possible or practical.
Given the strong relationship between resistance artery 
function and V̇O2max, vascular function data collected at rest 
could potentially be used to predict V̇O2max. For example, 
stepwise linear regression revealed that absolute V̇O2max 
(expressed in ml·min−1) could be predicted (R2  =  0.83, 
p < .01, n = 22) when considering the peak flow response to 
PLM (expressed in ml·min−1), body mass (expressed in kg), 
and BMI (expressed in kg·m−2):
Clearly, these data are very preliminary, and a much 
larger, more heterogeneous sample is needed before a pre-
diction equation may be validated and standardized, but the 
prospect of accurately predicting V̇O2max without breaking 
a sweat is enticing.
4.6 | Conclusions
This study supports the notion that noninvasive indices of 
vascular function generally reflect two different aspects of 
Absolute ̇VO2max =970.82+55.83 (Body Mass)
+0.68 (PLM Peak Flow)−121.75 (BMI) .
12 of 13 | 
  
GIFFORD et al.
vascular function: conduit artery function (e.g., FMD) and 
resistance artery function (e.g., RH Peak Flow, PLM Peak 
Flow, and ROV Peak Flow). Importantly, the results of the 
tests within each aspect of vascular function (i.e., conduit or 
resistance artery function) relate well to one another, such 
that inferences about one test may be made based on the 
results of another. While only a weak relationship between 
conduit artery function (e.g. FMD) and V̇O2max is observed 
when accounting for baseline artery diameter, resistance 
artery function, assessed by multiple different tests, is con-
sistently and independently related to V̇O2max. While FMD 
has been related to various aspects of cardiovascular health 
(Broxterman et  al.,  2019), it is the function of the resist-
ance arteries, not the conduit arteries, that is tightly related 
to exercise capacity and physical function. Thus, vascu-
lar interventions, like exercise training (Montero, Walther, 
Diaz-Cañestro, Pyke, & Padilla, 2015), seeking to improve 
exercise capacity should target resistance artery function, as 
represented by factors like peak flow during PLM, RH, or 
ROV.
ACKNOWLEDGMENTS
The authors acknowledge and thank the participants for their 
gracious participation, and the peer reviewers for their ef-
forts in refining this manuscript. This study was funded by 
the Bobbitt Heart Disease Research Award and the BYU 
Graduate Student Mentorship Award. The authors have no 
conflicts of interest to report.
AUTHOR CONTRIBUTIONS
JG: Designed and performed the study, analyzed the data, 
and wrote the manuscript. BH: Designed and performed the 
study and wrote the manuscript. MP: Performed the study, 
analyzed the data, and approved the final manuscript. TW: 
Performed the study, analyzed the data, and approved the 
final manuscript. GG: Performed the study, analyzed the 
data, and approved the final manuscript. JK: Performed the 
study, analyzed the data, and approved the final manuscript. 
MH: Performed the study, analyzed the data, and approved 
the final manuscript.
ORCID
Jayson R. Gifford 
 https://orcid.org/0000-0002-6034-306X 
REFERENCES
Anderson, T. J., Uehata, A., Gerhard, M. D., Meredith, I. T., Knab, S., 
Delagrange, D., … Selwyn, A. P. (1995). Close relation of endo-
thelial function in the human coronary and peripheral circulations. 
Journal of the American College of Cardiology, 26, 1235–1241. 
https://doi.org/10.1016/0735-1097(95)00327 -4
Bada, A. A., Svendsen, J. H., Secher, N. H., Saltin, B., & Mortensen, S. 
P. (2012). Peripheral vasodilatation determines cardiac output in ex-
ercising humans: Insight from atrial pacing. Journal of Physiology, 
590, 2051–2060.
Broxterman, R. M., Trinity, J. D., Gifford, J. R., Kwon, O. S., Kithas, 
A. C., Hydren, J. R., … Richardson, R. S. (2017). Single passive 
leg movement assessment of vascular function: The contribution of 
nitric oxide. Journal of Applied Physiology, 123, 1468–1476.
Broxterman, R. M., Witman, M. A., Trinity, J. D., Groot, H. J., Rossman, 
M. J., Park, S.- H.- S.-Y., … Richardson, R. S. (2019). Strong rela-
tionship between vascular function in the coronary and brachial ar-
teries. Hypertension, 74, 208–215. https://doi.org/10.1161/HYPER 
TENSI ONAHA.119.12881
Casey, D. P., & Joyner, M. J. (2011). Local control of skeletal muscle 
blood flow during exercise: Influence of available oxygen. Journal 
of Applied Physiology, 111, 1527–1538.
Casey, D. P., Walker, B. G., Ranadive, S. M., Taylor, J. L., & Joyner, M. 
J. (2013). Contribution of nitric oxide in the contraction-induced rapid 
vasodilation in young and older adults. Journal of Applied Physiology, 
115, 446–455. https://doi.org/10.1152/jappl physi ol.00446.2013
Celermajer, D. S., Sorensen, K. E., Gooch, V. M., Spiegelhalter, D. 
J., Miller, O. I., Sullivan, I. D., … Deanfield, J. E. (1992). Non-
invasive detection of endothelial dysfunction in children and adults 
at risk of atherosclerosis. Lancet, 340, 1111–1115. https://doi.
org/10.1016/0140-6736(92)93147 -F
Credeur, D. P., Holwerda, S. W., Restaino, R. M., King, P. M., Crutcher, 
K. L., Laughlin, M. H., … Fadel, P. J. (2015). Characterizing rap-
id-onset vasodilation to single muscle contractions in the human 
leg. Journal of Applied Physiology, 118(4), 455–464. https://doi.
org/10.1152/jappl physi ol.00785.2014
Dodd, L. R., & Johnson, P. C. (1991). Diameter changes in arterio-
lar networks of contracting skeletal muscle. American Journal of 
Physiology-Heart and Circulatory Physiology, 260(3), H662–H670. 
https://doi.org/10.1152/ajphe art.1991.260.3.H662
Doshi, S. N., Naka, K. K., Payne, N., Jones, C. J., Ashton, M., Lewis, 
M. J., & Goodfellow, J. (2001). Flow-mediated dilatation following 
wrist and upper arm occlusion in humans: The contribution of nitric 
oxide. Clinical Science (Lond), 101, 629–635.
Field, A. (2009). Discovering statistics using SPSS, 3rd ed. Los Angeles: 
SAGE Pulbications LTD.
Gifford, J. R., Bloomfield, T., Davis, T., Addington, A., McMullin, 
E., Wallace, T., … Hanson, B. (2019). The effect of the speed and 
range of motion of movement on the hyperemic response to pas-
sive leg movement. Physiological Reports, 7, e14064. https://doi.
org/10.14814/ phy2.14064
Gifford, J. R., Garten, R. S., Nelson, A. D., Trinity, J. D., Layec, G., 
Witman, M. A. H. H., … Richardson, R. S. (2016). Symmorphosis 
and skeletal muscle V̇O2 max: In vivo and in vitro measures reveal 
differing constraints in the exercise-trained and untrained human. 
Journal of Physiology, 594, 1741–1751.
Gifford, J. R., & Richardson, R. S. (2017). CORP: Ultrasound assess-
ment of vascular function with the passive leg movement technique. 
Journal of Applied Physiology, 123, 1708–1720.
Green, D. (2005). Point: Counterpoint Point : Flow-mediated dilation 
does reflect nitric oxide-mediated endothelial function. Journal of 
Applied Physiology, 99, 1233–1238.
Green, D. J., Spence, A., Rowley, N., Thijssen, D. H. J., & Naylor, L. 
H. (2012). Vascular adaptation in athletes: Is there an “athlete’s ar-
tery”? Experimental Physiology, 295–304. https://doi.org/10.1113/
expph ysiol.2011.058826
Hanson, B. E., Proffit, M., & Gifford, J. R. (2020). Vascular function 
is related to blood flow during high-intensity, but not low-intensity, 
knee extension exercise. Journal of Applied Physiology, 128(3), 
698–708. https://doi.org/10.1152/jappl physi ol.00671.2019
   | 
13 of 13
GIFFORD et al.
Harris, R. A., Nishiyama, S. K., Wray, D. W., & Richardson, R. 
S. (2010). Ultrasound assessment of flow-mediated dilation. 
Hypertension, 55, 1075–1085. https://doi.org/10.1161/HYPER 
TENSI ONAHA.110.150821
Hughes, W. E., Ueda, K., & Casey, D. P. (2016). Chronic endurance ex-
ercise training offsets the age-related attenuation in contraction-in-
duced rapid vasodilation. Journal of Applied Physiology, 120, 
1335–1342. https://doi.org/10.1152/jappl physi ol.00057.2016
Joyner, M. J., & Casey, D. P. (2015). Regulation of increased blood flow 
(hyperemia) to muscles during exercise: A hierarchy of competing 
physiological needs. Physiological Reviews, 95, 549–601.
Koo, T. K., & Li, M. Y. (2016). A guideline of selecting and reporting 
intraclass correlation coefficients for reliability research. Journal 
of Chiropractic Medicine, 15, 155–163. https://doi.org/10.1016/j.
jcm.2016.02.012
Levine, B. D. (2008). VO2max: What do we know, and what do we 
still need to know? Journal of Physiology, 586, 25–34. https://doi.
org/10.1113/jphys iol.2007.147629
Limberg, J. K., Casey, D. P., Trinity, J. D., Nicholson, W. T., Wray, D. W., 
Tschakovsky, M. E., … Padilla, J. (2020). Assessment of resistance 
vessel function in human skeletal muscle: Guidelines for experimen-
tal design, Doppler ultrasound, and pharmacology. American Journal 
of Physiology. Heart and Circulatory Physiology, 318, H301–H325.
Montero, D. (2015). The association of cardiorespiratory fitness with 
endothelial or smooth muscle vasodilator function. European 
Journal of Preventive Cardiology, 22, 1200–1211. https://doi.
org/10.1177/20474 87314 553780
Montero, D., Walther, G., Diaz-Cañestro, C., Pyke, K. E., & Padilla, 
J. (2015). Microvascular dilator function in athletes: A systematic 
review and meta-analysis. Medicine & Science in Sports & Exercise, 
47, 1485–1494.
Mortensen, S. P., Askew, C. D., Walker, M., Nyberg, M., & Hellsten, Y. 
(2012). The hyperaemic response to passive leg movement is depen-
dent on nitric oxide: A new tool to evaluate endothelial nitric oxide 
function. Journal of Physiology, 590, 4391–4400.
Poole, D. C., Behnke, B. J., & Musch, T. I. (2020). The role of vascu-
lar function on exercise capacity in health and disease. Journal of 
Physiology, https://doi.org/10.1113/JP278931.
Poole, D. C., & Jones, A. M. (2017). Measurement of the maximum 
oxygen uptake V̇O2max : V̇O2peak is no longer acceptable. Journal of 
Applied Physiology, 122, 997–1002.
Proctor, D. N., & Joyner, M. J. (1997). Skeletal muscle mass and the 
reduction of V̇O2(max) in trained older subjects. Journal of Applied 
Physiology, 82, 1411–1415.
Robbins, J. L., Jones, W. S., Duscha, B. D., Allen, J. D., Kraus, W. 
E., Regensteiner, J. G., … Annex, B. H. (2011). Relationship be-
tween leg muscle capillary density and peak hyperemic blood flow 
with endurance capacity in peripheral artery disease. Journal of 
Applied Physiology, 111, 81–86. https://doi.org/10.1152/jappl physi 
ol.00141.2011
Rossman, M. J., Groot, H. J., Garten, R. S., Witman, M. A. H., & 
Richardson, R. S. (2016). Vascular function assessed by passive leg 
movement and flow-mediated dilation: Initial evidence of construct 
validity. American Journal of Physiology-Heart and Circulatory 
Physiology, 311, ajpheart.00421.2016.
Rowley, N. J., Dawson, E. A., Hopman, M. T. E., George, K. P., Whyte, 
G. P., Thijssen, D. H. J., & Green, D. J. (2012). Conduit diame-
ter and wall remodeling in elite athletes and spinal cord injury. 
Medicine and Science in Sports and Exercise, 44, 844–849. https://
doi.org/10.1249/MSS.0b013 e3182 3f6887
Thijssen, D. H. J., Black, M. A., Pyke, K. E., Padilla, J., Atkinson, G., 
Harris, R. A., … Green, D. J. (2011). Assessment of flow-mediated 
dilation in humans: A methodological and physiological guideline. 
American Journal of Physiology-Heart and Circulatory Physiology, 
300, H2–12.
Thijssen, D. H. J., Rowley, N., Padilla, J., Simmons, G. H., Laughlin, 
M. H., Whyte, G., … Green, D. J. (2011). Relationship between 
upper and lower limb conduit artery vasodilator function in hu-
mans. Journal of Applied Physiology, 111, 244–250. https://doi.
org/10.1152/jappl physi ol.00290.2011
Tremblay, J. C., & Pyke, K. E. (2018). Flow-mediated dilation stim-
ulated by sustained increases in shear stress: A useful tool for as-
sessing endothelial function in humans? American Journal of 
Physiology-Heart and Circulatory Physiology, 314, H508–H520.
Trinity, J. D., Groot, H. J., Layec, G., Rossman, M. J., Ives, S. J., Runnels, S., 
… Richardson, R. S. (2012). Nitric oxide and passive limb movement: 
A new approach to assess vascular function. Journal of Physiology, , 
590(6), 1413–1425. https://doi.org/10.1113/jphys iol.2011.224741
Tschakovsky, M. E., Rogers, A. M., Pyke, K. E., Saunders, N. R., Glenn, 
N., Lee, S. J., … Dwyer, E. M. (2004). Immediate exercise hyper-
emia in humans is contraction intensity dependent: Evidence for 
rapid vasodilation. Journal of Applied Physiology, 96, 639–644.
VanTeeffelen, J. W. G. E., & Segal, S. S. (2006). Rapid dilation of arte-
rioles with single contraction of hamster skeletal muscle. American 
Journal of Physiology-Heart and Circulatory Physiology, 290, 119–
127. https://doi.org/10.1152/ajphe art.00197.2005
Wagner, P. D. (2008). Systemic oxygen transport and utili-
zation. Journal of Breath Research, 2, 1–12. https://doi.
org/10.1088/1752-7155/2/2/024001
Walker, M. A., Hoier, B., Walker, P. J., Schulze, K., Bangsbo, J., 
Hellsten, Y., & Askew, C. D. (2016). Vasoactive enzymes and blood 
flow responses to passive and active exercise in peripheral arterial 
disease. Atherosclerosis, 246, 98–105. https://doi.org/10.1016/j.
ather oscle rosis.2015.12.029
Wiedman, M. P. (1963). Dimensions of blood vessels from distributing 
artery to collecting vein. Circulation Research, 12, 375–378. https://
doi.org/10.1161/01.RES.12.4.375
How to cite this article: Gifford JR, Hanson BE, 
Proffit M, et al. Indices of leg resistance artery 
function are independently related to cycling V̇O2max. 
Physiol Rep. 2020;8:e14551. https://doi.org/10.14814/ 
phy2.14551

Indices of leg resistance artery function are independently related to cycling V̇O<sub>2</sub> max.
Gifford, Jayson R,Hanson, Brady E,Proffit, Meagan,Wallace, Taysom,Kofoed, Jason,Griffin, Garrett,Hanson, Melina