The relationship between cardiorespiratory fitness and blood pressure among airline pilots: a mediation analysis of body composition

Abstract

Objective
Blood pressure (BP), cardiorespiratory fitness (CRF), and body composition are independently associated with health outcomes, yet the relationship between these variables has not been explored among airline pilots. The aim of this study was to evaluate the relationship between CRF and BP, and further examine whether the relationship is mediated by body composition.

Methods
A cross-sectional study was conducted among 356 airline pilots in New Zealand. We measured height, body mass, BP, waist circumference, skinfolds, and CRF (via a WattBike cycle ergometer submaximal VO 2max test). Partial correlation coefficients were estimated to examine the relationships between all variables while controlling for age and sex. Haye's PROCESS macro and the Sobel test were utilized for the mediation analysis.

Results
All body composition variables (body mass index, waist circumference and body fat percentage) were positively correlated with all BP variables (systolic pressure, diastolic pressure and mean arterial pressure) ( P < 0.001). CRF was negatively correlated with all body composition and BP variables ( P < 0.001). The Sobel test and indirect effect were significant ( P < 0.001), confirming that all body composition variables partially mediate the relationship between CRF and all blood pressure variables.

Conclusion
Lower CRF is associated with higher blood pressure, and body composition partially mediates the relationship between these health risk factors. These findings highlight the importance of physical fitness and healthy body composition in the management of blood pressure among this occupational group.

Full text

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JH-D-23-00208
The relationship between cardiorespiratory fitness
and blood pressure among airline pilots: a mediation
analysis of body composition
Daniel Wilson
a,b
, Matthew Driller
d
, Ben Johnston
e
, and Nicholas Gill
a,c
Objective: Blood pressure (BP), cardiorespiratory
fitness (CRF), and body composition are independently
associated with health outcomes, yet the relationship
between these variables has not been explored among
airline pilots. The aim of this study was to evaluate
the relationship between CRF and BP, and further
examine whether the relationship is mediated by body
composition.
Methods: A cross-sectional study was conducted
among 356 airline pilots in New Zealand. We measured
height, body mass, BP, waist circumference, skinfolds,
and CRF (via a WattBike cycle ergometer submaximal
VO
2max
test). Partial correlation coefficients were
estimated to examine the relationships between all
variables while controlling for age and sex. Haye’s
PROCESS macro and the Sobel test were utilized for the
mediation analysis.
Results: All body composition variables (body mass index,
waist circumference and body fat percentage) were
positively correlated with all BP variables (systolic
pressure, diastolic pressure and mean arterial pressure)
(P<0.001). CRF was negatively correlated with all body
composition and BP variables (P<0.001). The Sobel test
and indirect effect were significant (P<0.001),
confirming that all body composition variables partially
mediate the relationship between CRF and all blood
pressure variables.
Conclusion: Lower CRF is associated with higher
blood pressure, and body composition partially mediates
the relationship between these health risk factors.
These findings highlight the importance of physical
fitness and healthy body composition in the
management of blood pressure among this occupational
group.
Keywords: blood pressure, body composition,
cardiometabolic health, cardiorespiratory fitness, mediation
analysis
Abbreviations: ANCOVA, analysis of covariance; BP,
Blood pressure; BF%, body fat percentage; BMI, body
mass index; CRF, cardiorespiratory fitness; CVD,
cardiovascular disease; DBP, diastolic blood pressure; MAP,
mean arterial pressure; SBP, systolic blood pressure; WC,
waist circumference
INTRODUCTION
Hypertension, obesity, and low cardiorespiratory
fitness (CRF) are among leading modifiable risk
factors for cardiovascular disease (CVD) and all-
cause mortality [1,2]. Airline pilots face various occupational
demands that may negatively impact cardiovascular disease
risk, including shift work and erratic work schedules,
circadian disruption, psychological stress and fatigue,
and prolonged periods of sitting [3]. Recent studies have
revealed notable prevalence of cardiovascular health risk
factors among airline pilots globally, comparable to general
population estimates, including hypertension, overweight
and obesity, and lifestyle behavioral risks such as insuffi-
cient physical activity [3,4]. However, investigation of the
relationships between such factors among airline pilots has
not been well addressed.
Previous research among the general population has
reported a strong inverse relationship between CRF and
blood pressure (BP), in which higher CRF is associated with
lowered BP [5]. Further studies within the general popula-
tion have suggested body composition variables may influ-
ence the relationship between CRF and BP [6]. BMI, body fat
percentage (BF%), and waist circumference (WC) are the
most widely investigated body composition parameters that
have each independently demonstrated strong relation-
ships with CVD risk [7,8], yet there are discrepancies among
reports as to which of these parameters is optimal for
predicting CVD [9] and hypertension risk [10]. Accordingly,
research is warranted to evaluate the characteristics of these
variables among airline pilots.
Journal of Hypertension 2023, 41:000–000
a
Te Huataki Waiora School of Health, The University of Waikato, Hamilton,
b
Faculty of
Health, Education and Environment, Te Pukenga - New Zealand Institute of Skills and
Technology, Tauranga,
c
New Zealand Rugby, Wellington,
d
Sport and Exercise Science,
School of Allied Health, Human Services and Sport, La Trobe University, Melbourne,
Australia and
e
Aviation and Occupational Health Unit, Air New Zealand, Auckland,
New Zealand
Correspondence to Daniel Wilson, Faculty of Te Huataki Waiora School of Health,
University of Waikato, Adams Centre for High Performance, 52 Miro Street, Mount
Maunganui 3116, New Zealand. E-mail: daniel.wilson@toiohomai.ac.nz
Received 27 March 2023 Revised 18 September 2023 Accepted 27 September
2023
J Hypertens 41:000– 000 Copyright ©2023 Wolters Kluwer Health, Inc. All rights
reserved.
DOI:10.1097/HJH.0000000000003605
Journal of Hypertension www.jhypertension.com 1
Original Article

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Behavioral interventions that enhance CRF and body
composition variables including BF%, BMI, and WC among
airline pilots have demonstrated favorable changes in BP
[11–13]. However, the specific relationships between CRF,
body composition and BP have not been established
among this occupational group. Progressive insights into
the relationships between health risk factors will inform
interventions and policy to mitigate cardiovascular health
risk factors among airline pilots. Therefore, the aim of this
study was to evaluate the relationship between CRF and BP
and further examine whether the relationship is mediated
by body composition.
METHODS
Design
A retrospective cross-sectional study was performed to
evaluate whether the relationship between CRF and BP
is mediated by body composition. This study examined
objective cardiometabolic health variables: age, sex,
weight, CRF (estimated VO
2max
), BMI, WC, skin folds,
and BP. This study was approved by the Human Research
Ethics Committee of the University of Waikato in New
Zealand (reference number 2019#35).
Participants
The study sample consisted of 356 airline pilots which were
recruited from an international airline in New Zealand, who
participated in voluntary face-to-face health assessments
between 2019 and 2022 (see Table 1). The researchers
invited all pilots working for the company via organization
internal communication channels, to take part in the study.
Based on recent populace estimates [4], our sample size
represents approximately 26% of this occupational popu-
lation. Prior to participating in the study, all participants
gave written consent and were informed that they could
leave the study at any point if they chose to. The criteria for
being included in the study were having a valid commercial
pilot license and working as a permanent employee. Par-
ticipants were excluded if medical clearance was deemed
necessary prior to performing a cardiorespiratory fitness
assessment which was evaluated by the Physical Activity
Readiness Questionnaire for Everyone (PAR-Qþ) [14].
Outcome measures
Participants were instructed to avoid large meals, strenuous
physical activity, and stimulants such as caffeine for 4 h
before their physiological measurements were taken. Pro-
cedures for measuring BP and body composition have been
previously described in detail [4,12]. In brief, body mass was
measured using SECA 813 electronic flat scales and height
with a SECA 206 stadiometer (SECA, Hamburg, Deutsch-
land). Body mass and height values were utilized to deter-
mine BMI (kg/m
2
). WC was measured with a thin-line
metric tape measure (Lufkin; Apex Tool Group, Sparks,
MD, USA) congruent with standardized technique [15].
Skinfold measurements were collected according to stan-
dardized procedures of the International Society for the
Advancement of Kinanthropometry by a certified anthropo-
metrist using Harpenden calipers (British Indicators, Hert-
fordshire, UK). Skin fold measures of biceps, triceps, sub
scapular, and supra iliac in addition to WC were utilized to
estimate BF% based on sex and ethnicity specific prediction
equations reported elsewhere [16].
BP measurements were measured in accordance with
standardized aviation medicine protocol [17]. The measure-
ments were taken twice with an OMRON HEM-757 device
(Omron Corporation, Kyoto, Japan) while the participant
was sitting with their arm supported at the level of the atria.
If the initial two readings were below 140/90, the lowest
measurement was recorded. However, if the readings were
above 140/90, two more readings were taken after a few
minutes’ interval. Mean arterial pressure (MAP) was calcu-
lated using the formula: DBP þ1/3(SBP-DBP).
To assess participants’ aerobic fitness, estimated VO
2max
was determined by having them perform a 3-min aerobic
test (3mAT) on a Wattbike electro-magnetically and air-
braked cycle ergometer, which has been previously vali-
dated among airline pilots [12,18]. Before the test, partic-
ipants were given a thorough explanation of the protocol,
safety procedures, they were provided with a Polar H10
heart rate strap (Polar Electro, Kempele, Finland) and the
TABLE 1. Characteristics of the study sample
Parameters All subjects (n¼356) Female (n¼44) Male (n¼312)
Sex (f/m) 44/312 - -
Age (years) 43.9 10.8 37.1 8.7 44.9 10.7

Short haul (n) 179 29 150
Long haul (n) 177 15 162
Height (cm) 177.9 8.0 167.4 6.5 179.3 7.1
Body mass (kg) 90.214.3 77.8 10.8 92.0 13.9
BMI (kgm
2
) 28.53.9 27.9 4.2 28.6 3.8
Waist circumference (cm) 96.3 11.3 86.5 11.5 97.7 10.6
Body fat (%) 24.1 5.7 31.26.6 23.1 4.8

CRF (mlkg
1
min
1
) 36.2 7.0 33.8 8.8 36.6 6.6

SBP (mmHg) 131.6 9.6 128.8 9.6 132.0 9.5
DBP (mmHg) 84.2 6.5 82.18.6 84.5 6.1

MAP (mmHg) 100.07.0 97.6 8.5 100.3 6.8
Note: Mean SD reported for all participants.
BMI, body mass index; CRF, cardiorespiratory fitness; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure; SD, standard deviation.

Indicates statistical significance P<0.05.

indicates P<0.001.
Wilson et al.
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seat and handle were fitted correctly. The full procedure has
been described in detail elsewhere [18]. Participants com-
pleted a 10-min warm-up, which included self-paced cy-
cling at 70–90 rpm, along with two 6-s sprints as suggested
by the manufacturer. During the 3mAT, participants were
encouraged verbally and allowed to adjust resistance and
pedal cadence as necessary to maintain the highest power
output possible for the full 3 min.
Statistical analysis
All analyses were performed in SPSS (Version 29; IBM Corp.,
Armonk, NY). The Shapiro–Wilk test and its histograms, Q–
Qplots, and box plots were analyzed for data distribution
normality. The Levene’s test was used to test homogeneity of
variance. Continuous descriptive data were compared via
independent t-tests and the Chi square test was utilized for
categorical variables. Partial correlation coefficients were
estimated for examination of relationships between CRF,
BP variables [systolic blood pressure (SBP), diastolic blood
pressure (DBP), mean arterial pressure (MAP)], and body
composition variables (BMI, WC, BF%), controlling for age,
sex and use of antihypertensive medication.
ANCOVA models were utilized to quantify BP descrip-
tive data across different CRF and body composition cate-
gories. BMI were categorized as underweight, normal
weight, overweight, and obese by values <18.5, 18.5–
24.9, 25–29.9, and >30 (kg/m
2
), respectively. CRF, WC,
and BF% were categorized as first, second, third, and fourth
quartiles. ANCOVA model one controlled for age and sex,
whereas further models also adjusted for CRF, BMI, BF%, or
WC, depending on the fixed factor. Bonferroni correction
pairwise post hoc hypotheses were utilized to account for
multiple comparisons and examine significant relationships
between categories.
For the mediation analysis, the PROCESS macro for SPSS
[19] was utilized to examine the total, direct, and indirect
effects (IE). The total effect represents the overall effect of
one variable on another, encompassing all paths. The direct
effect denotes the impact of CRF on BP without considering
the influence of body composition, whereas the indirect
effect reveals the change in this relationship that is mediated
by body composition. The bootstrapping method advised
by Preacher and Hayes [20] to test the mediation hypotheses
was used at 10 000 bootstrap samples to calculate point
estimates and confidence intervals for the IE. Further, the
Sobel test [21] was conducted to determine if the relation-
ship between variables was significant, which included
estimating the IE, dividing by the standard error, and
performing a Ztest to determine if the IE is equal to zero.
RESULTS
Characteristics of the study population are depicted in
Table 1. The population was entirely Caucasian ethnicity,
which is comparable with a previously published cross-
sectional study among this population [4]. Age, CRF, and
DBP were higher in males (P<0.05), whereas BF% was
higher in females (P<0.001). The partial correlation coef-
ficients relationship between body composition, CRF and
BP variables are presented in Table 2. All variables investi-
gated were significantly correlated (P<0.001). BMI, WC,
and BF% were positively correlated with all BP variables
(P<0.001). CRF was negatively correlated with all body
composition and BP variables (P<0.001).
The mean difference in BP variables across body com-
position and CRF categories are displayed in Table 3 and
the Supplementary File. Across all statistical models, lower
values for BMI, WC, and BF% were associated with signifi-
cantly lower SBP, DBP, and MAP (P<0.001). Among CRF
category models factoring age, sex, and each body compo-
sition variable (BMI, WC, or BF%), higher CRF was associ-
ated with lower SBP, DBP, and MAP (P<0.001).
As shown in Figure 1, the results revealed a significant IE
of all body composition variables as a mediator between
CRF and BP variables, as the confidence intervals did not
contain zero [19]. A significant direct effect of CRF on BP
variables in the presence of the mediator was observed
(P<0.001). Furthermore, the total effect, representing the
overall relationship between the predictor and outcome
variables, including both the direct and IE was significant
for all analyses (P<0.001). Finally, the Sobel test was
significant for each body composition variable in the rela-
tionship between CRF and BP. Overall, body composition
variables partially mediated the relationship between CRF
and BP variables.
DISCUSSION
To our knowledge, this is the first study to evaluate the
relationship between CRF and BP in airline pilots. We
believe it is also the first study to further examine whether
TABLE 2. Pearson correlation coefficients between body composition variables with cardiorespiratory fitness and blood pressure
variables, controlling for age and sex
WC BF% CRF SBP DBP MAP
BMI 0.84

0.85

-0.51

0.49

0.49

0.52

WC 0.85

-0.48

0.43

0.40

0.44

BF% -0.56

0.48

0.48

0.51

CRF -0.57

-0.59

-0.62

SBP 0.75

0.91

DBP 0.95

MAP
BF%, body fat percentage; BMI, body mass index; CRF, cardiorespiratory fitness; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure; WC, waist
circumference.

Indicates statistical significance P<0.001.
Relationship between blood pressure, cardiorespiratory fitness, and body composition
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this relationship is mediated by body composition. Our
findings demonstrate a negative relationship between CRF
and BP, with higher CRF levels associated with lower BP
levels. Body composition variables, including BMI, WC,
and BF%, were also significantly related to BP. When
controlling for these variables in partial correlation analysis,
the relationship between CRF and BP remained significant,
suggesting that body composition does not fully mediate
the relationship between CRF and BP in this population.
These findings provide further insight into the cardio-
vascular health risk factors present among airline pilots. As
BP is incorporated in CVD risk evaluation models utilized in
aviation medicine [17], our findings add new insights rele-
vant to the field, uncovering CRF and body composition as
relevant metrics for modifying BP. It is the responsibility of
aviation medical regulators to apply safety management
principles to the aviation medical assessment process and
to implement appropriate health promotion for license
holding pilots to mitigate future health risks to flight oper-
ation safety [17]. Recent reports of notable health risk factor
prevalence for insufficient physical activity, excess body
mass, and elevated blood pressure among airline pilots
globally [3] highlight the need for enhanced health risk
factor mitigation strategies among this occupational group.
TABLE 3. Mean differences in blood pressure variables by fat mass and cardiorespiratory fitness categories
Model 1 Model 2
BMI categories
Underweight Normal Overweight Obese Underweight Normal Overweight Obese
SBP 116.1 6.1
4
123.3 1.2
3,4
130.9 0.6
2,4
136.2 0.8

121.6 5.4 127.1 1.2
3,4
131.4 0.6
2,4
133.9 0.7

DBP 76.6 4.0
4
78.3 0.8
3,4
83.4 0.4
2,4
87.8 0.5

80.2 3.5 80.8 0.8
3,4
83.7 0.4
2,4
86.3 0.5

MAP 89.74.3
4
93.3 0.9
3,4
99.3 0.4
2,4
103.9 0.5

94.0 3.7 96.2 0.8
3,4
99.6 0.4
2,4
102.2 0.5

CRF categories
1st Quartile 2nd Quartile 3rd Quartile 4th Quartile 1st Quartile 2nd Quartile 3rd Quartile 4th Quartile
SBP 137.7 0.9
2–4
133.6 0.9
1,3– 4
130.3 0.9
1–2,4
124.5 0.9

135.6 0.9
3–4
133.5 0.8
4
130.6 0.8
1,4
126.5 0.9

DBP 88.6 0.6
2–4
85.1 0.6
1,4
83.4 0.6
1,4
79.4 0.6

87.2 0.6
2–4
85.1 0.6
1,4
83.6 0.6
1,4
80.7 0.6

MAP 105.0 0.6
2–4
101.3 0.6
1,4
99.0 0.6
1,4
94.4 0.6

103.4 0.6
3–4
101.2 0.6
4
99.2 0.6
1,4
96.0 0.6

Note: The data are presented by marginal estimated mean s.e. The measurement unit for all blood pressure values is mmHg. Model 1 ¼controlling for age and sex. Model
2¼controlling for age, sex, and CRF (for body mass categories) or BMI (for CRF categories).
BMI, body mass index; CRF, cardiorespiratory fitness; DBP, diastolic blood pressure; MAP, mean arterial pressure; SBP, systolic blood pressure.

Indicates ANCOVA statistically significance group difference at level P<0.05.

Indicates P<0.001. Superscript number identifies significant relationship within categories from the post hoc analysis, 1 represents the leftmost category, 2 denotes the second
category from the left and so forth.
FIGURE 1 Body composition mediated models of the relationship between cardiorespiratory fitness and blood pressure variables, controlling for age and sex. BF%, body
fat percentage; BMI, body mass index; CRF, cardiorespiratory fitness; DBP, diastolic blood pressure; IE, indirect effect; MAP, mean arterial pressure; SBP, systolic blood
pressure; WC, waist circumference.

Indicates within group statistical significance P<0.05, and

indicates P<0.001. a,b, c’ and crepresent unstandardized regression
coefficient. a¼independent variable to mediator path, b¼mediator to dependent variable path, c’¼direct effect, c¼total effect.
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The evident role of CRF and body composition in influenc-
ing BP underscores the importance of evaluating these
outcomes in aviation medical practice and warrants imple-
mentation of evidence-based approaches to promote phys-
ical fitness and healthy body mass among airline pilots to
mitigate cardiometabolic health risk.
Although comparable literature pertaining to airline
pilots is scant, some of our findings regarding the relation-
ships between CRF, body composition and BP are consis-
tent with past research in other populations. These include
a large cohort study (n¼1 547 478) among adult males
revealed CRF and BMI were each strongly and indepen-
dently associated with BP, and those with a combination of
high BMI and low CRF were associated with the highest risk
of hypertension [22]. A recent study among middle aged
adults (n¼24 349) utilizing whole-body dual-energy X-ray
revealed both central adiposity and lean mass were inde-
pendently associated with blood pressure [6]. Moreover,
another study reported body composition variables BMI,
WC and BF% also mediated the relationship between CRF
and BP in cohort of young adults [23]. A meta-analysis of
experimental randomized control trials revealed improve-
ments in moderate-intensity leisure-time physical activity
was associated with significant reduction in both SBP and
DBP [24]. Further, a meta-analysis of weight-reduction
randomized control trials reported a 4-kilogram weight
reduction was associated with 6 mmHg reduction in SBP
[25]. Collectively, these studies demonstrate congruent
trends with our present findings.
Previous research has proposed measures of adiposity
such as BF% may be a better predictor of CVD risk factor
profile than standard body mass indices such as BMI [26].
Indeed, BMI fails to account for the proportion of skeletal
muscle mass that contributes to an individual’s body mass.
As low skeletal muscle mass [27] and high adiposity [28]
have been associated with adverse outcomes to cardiovas-
cular health, such as vascular dysfunction, metabolic
impairments, dyslipidemia, hypertension, and inflamma-
tion, the relevance of investigating BF% may be postulated.
Interestingly, in our study, BMI demonstrated a marginally
stronger correlation with MAP, compared with estimated BF
%(r¼0.52 and 0.51, respectively). Therefore, this prelimi-
nary evidence suggests BMI has similar utility as BF% in
predicting BP among airline pilots, of which measurement
is typically more resource intensive. However, future re-
search utilizing measures of higher validity such as DEXA
to precisely quantify body composition are needed to
enhance the accuracy and generalizability of conclusions.
Our findings which revealed higher BP among higher
body composition categories is consistent with past re-
search [29]. This trend continued in our analysis when
CRF was integrated into the ANCOVA as a covariate (model
2). Therefore, it appears that CRF does not fully mitigate the
adverse effects of excess body mass on BP. Indeed, past
research has reported higher visceral adipose tissue is
associated with elevated blood pressure, independent of
CRF [29]. However, our analysis also revealed lower BP in
higher CRF categories regardless of body composition
variables being included as covariates. Collectively, these
findings demonstrate the notable independent effects of
CRF and body composition on BP, yet further research is
needed to better understand the specific mechanisms and
modifiable factors that contribute to the relationship be-
tween CRF, body composition, and BP among airline pilots.
There are various limitations that need to be considered
in the interpretation of our findings. First, as participants
were those who chose to engage in voluntary health
evaluations, these individuals may have higher motivation
to improve their health than those from the population that
did not choose to participate. More robust recruitment
methodology such as population random sampling may
yield a superior representation of the population and
enhance generalizability of findings. Second, airline pilots
routinely have their blood pressure taken during aviation
medical examinations, of which outcomes influence their
flight certification. Consequently, some individuals experi-
ence white coat syndrome [30] when blood pressure is
measured in a physician’s venue. Future research utilizing
at home ambulatory blood pressure measurement may
enhance accuracy [30] of population blood pressure quan-
tification. Third, due to resource availability and feasibility
reasons, a submaximal CRF test was used to quantify
estimated VO
2max
and skinfold measures were imple-
mented for BF% estimation. Future research utilizing gold
standard measures such as a graded maximal CRF test and
dual-energy X-ray for body composition would add value
to the scientific body. Fourth, various dietary behaviors are
associated with body composition and cardiometabolic
disease risk status. Thus, future research should quantify
dietary behaviors including energy balance, sodium and
omega-3 fatty acid intake, and the Western dietary pattern
to evaluate their independent role in the relationship be-
tween physical fitness, body composition and blood pres-
sure. Finally, our sample comprised a largely homogenous
sample of New Zealand Caucasian airline pilots. Therefore,
a more diverse demographic representation is needed to
enhance the generalizability of findings.
In conclusion, our study found that higher cardiorespi-
ratory fitness was associated with lower blood pressure,
and that body composition variables such as body mass
index, waist circumference, and body fat percentage also
had an impact on the relationship between CRF and BP.
These findings highlight the importance of addressing
health risk factors among airline pilots through targeted
interventions and policies to mitigate the risk of cardiovas-
cular disease and other health problems.
ACKNOWLEDGEMENTS
The authors wish to thank the pilots for providing their time
to participate in this study.
Author contributions: Conceptualization, D.W. and N.G.;
methodology, D.W. and N.G.; software, D.W. and N.G.;
validation, D.W. and N.G.; formal analysis, D.W. and N.G.;
investigation, D.W., M.D. and N.G.; resources, D.W.; data
curation, D.W. and N.G.; writing—original draft prepara-
tion, D.W.; writing—review and editing, D.W., M.D., B.J.
and N.G.; visualization, D.W.; supervision, M.D., B.J. and N.
G.; project administration, D.W. and M.D.; funding acqui-
sition, N/A. All authors have read and agreed to the pub-
lished version of the manuscript.
Funding: This research received no external funding.
Relationship between blood pressure, cardiorespiratory fitness, and body composition
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Conflicts of interest
The authors declare they have no competing interests.
REFERENCES
1. Miranda JJ, Barrientos-Guti
errez T, Corvalan C, Hyder AA, Lazo-Porras
M, Oni T, et al. Understanding the rise of cardiometabolic diseases in
low- and middle-income countries. Nat Med 2019; 25:1667– 1679.
2. Stenholm S, Head J, Aalto V, Kivim€
aki M, Kawachi I, Zins M, et al. Body
mass index as a predictor of healthy and disease-free life expectancy
betweenages 50 and 75: a multicohort study.Int J Obes 2017; 41:769– 775.
3. Wilson D, Driller M, Johnston B, Gill N. The prevalence of cardiome-
tabolic health risk factors among airline pilots: a systematic review. Int
J Environ Res Public Health 2022; 19:4848.
4. Wilson D, Driller M, Johnston B, Gill N. The prevalence and distribu-
tion of health risk factors in airline pilots: a cross-sectional compari-
son with the general population. Aust N Z J Public Health 2022;
46:572–580.
5. Sui X, Sarzynski MA, Lee D-c. Kokkinos PF. Impact of changes in
cardiorespiratory fitness on hypertension, dyslipidemia and survival:
an overview of the epidemiological evidence. Prog Cardiovasc Dis
2017; 60:56– 66.
6. Zhao S, Tang J, Zhao Y, Xu C, Xu Y, Yu S, et al. The impact of body
composition and fat distribution on blood pressure in young and
middle-aged adults. Front Nutr 2022; 9:979042.
7. Sheibani H, Esmaeili H, Tayefi M, Saberi-Karimian M, Darroudi S,
Mouhebati M, et al. A comparison of body mass index and percentage
body fat as predictors of cardiovascular risk factors. Diabetes Metab
Syndr: Clin Res Rev 2019; 13:570– 575.
8. Nevill AM, Duncan MJ, Myers T. BMI is dead; long live waist-circum-
ference indices: But which index should we choose to predict cardio-
metabolic risk? Nutr Metab Cardiovasc Dis 2022; 32:1642– 1650.
9. Andreacchi AT, Griffith LE, Guindon GE, Mayhew A, Bassim C, Pigeyre
M, et al. Body mass index, waist circumference, waist-to-hip ratio, and
body fat in relation to healthcare use in the Canadian Longitudinal
Study on Aging. Int J Obes 2021; 45:666– 676.
10. Silva DAS, Petroski EL, Peres MA. Is high body fat estimated by body
mass index and waist circumference a predictor of hypertension in
adults? A population-based study. Nutr J 2012; 11:112.
11. Wilson D, Driller M, Ben J, Gill N. The effectiveness of a 17-week
lifestyle intervention on health behaviors among airline pilots during
COVID-19. J Sport Health Sci 2021; 10:333– 340.
12. Wilson D, Driller M, Winwood P, Clissold T, Johnston B, Gill N. The
effectiveness of a combined healthy eating, physical activity, and sleep
hygiene lifestyle intervention on health and fitness of overweight
airline pilots: a controlled trial. Nutrients 2022; 14:1988.
13. Wilson D, Driller M, Winwood P, JohnstonB, Gill N. The effects of a brief
lifestyle intervention on the health of overweight airline pilots during
COVID-19: a 12-month follow-up study. Nutrients 2021; 13:4288.
14. Warburton DER, Jamnik V, Bredin SSD, Shephard RJ, Gledhill N. The
2020 physical activity readiness questionnaire for everyone (PAR-Qþ)
and electronic physical activity readiness medical examination
(ePARmed-Xþ): 2020 PAR-Qþ.Health Fit J Can 2019; 12:58– 61.
15. World Health Organization. Waist circumference and waist-hip ratio:
report of a WHO expert consultation. Geneva, Switzerland: World
Health Organization; 2008.
16. Davidson LE, Wang J, Thornton JC, Kaleem Z, Silva-Palacios F, Pierson
RN, et al. Predicting fat percentage by skinfolds in racial groups: Durnin
and Womersley revisited. Med Sci Sports Exerc 2011; 43:542–549.
17. International Civil AviationAuthority. Manual of civil aviationmedicine,
3rd ed. Quebec, Canada: International Civil Aviation Authority; 2012
.
18. Hanson NJ, Scheadler CM, Katsavelis D, Miller MG. Validity of the
Wattbike 3-Minute Aerobic Test: measurement and estimation of
V
˙o2max. J Strength Cond Res 2022; 36:400–404.
19. Hayes AF. Introduction to mediation, moderation, and conditional
process analysis: a regression-based approach. New York, NY, USA:
Guilford Press; 2013.
20. Preacher KJ, Hayes AF. Asymptotic and resampling strategies for
assessing and comparing indirect effects in multiple mediator models.
Behav Res Methods 2008; 40:879– 891.
21. Sobel ME. Asymptotic confidence intervals for indirect effects in
structural equation models. Sociol Methodol 1982; 13:290– 312.
22. Crump C, Sundquist J, Winkleby MA, Sundquist K. Interactive effects of
physical fitness and body mass index on the risk of hypertension. JAMA
Intern Med 2016; 176:210– 216.
23. D
ıez-Fern
andez A, S
anchez-L
opez M, Nieto JA, Gonz
alez-Garc

ıa A,
Miota-Ibarra J, Ortiz-Galeano I, et al. Relationship between cardiore-
spiratory fitness and blood pressure in young adults: a mediation
analysis of body composition. Hypertension Res 2017; 40:511– 515.
24. Shariful Islam M, Fardousi A, Sizear MI, Rabbani MG, Islam R, Saif-Ur-
Rahman KM. Effect of leisure-time physical activity on blood pressure
in people with hypertension: a systematic review and meta-analysis.
Sci Rep 2023; 13:10639.
25. Horvath K, Jeitler K, Siering U, Stich AK, Skipka G, Gratzer TW, et al.
Long-term effects of weight-reducing interventions in hypertensive
patients: systematic review and meta-analysis. Arch Intern Med 2008;
168:571– 580.
26. Christou DD, Gentile CL, DeSouza CA, Seals DR, Gates PE. Fatness is a
better predictor of cardiovascular disease risk factor profile than
aerobic fitness in healthy men. Circulation 2005; 111:1904– 1914.
27. Abramowitz MK, Hall CB, Amodu A, Sharma D, Androga L, Hawkins M.
Muscle mass, BMI, and mortality among adults in the United States: a
population-based cohort study. PLoS One 2018; 13:e0194697.
28. Xu H, Cupples LA, Stokes A, Liu C-T. Association of obesity with
mortality over 24 years of weight history: findings from the Framing-
ham Heart Study. JAMA Netw 2018; 1:e184587– e1184587.
29. Rh
eaume C, Arsenault BJ, B
elanger S, P
erusse L, Tremblay A, Bouchard
C, et al. Low cardiorespiratory fitness levels and elevated blood
pressure. Hypertension 2009; 54:91– 97.
30. Ogedegbe G, Pickering TG, Clemow L, Chaplin W, Spruill TM, Alba-
nese GM, et al. The misdiagnosis of hypertension: the role of patient
anxiety. Arch Intern Med 2008; 168:2459–2465.
Wilson et al.
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