Insulin Resistance, Low Cardiorespiratory Fitness, and
Increased Exercise Blood Pressure
Contribution of Abdominal Obesity
Maxime Huot, Benoit J. Arsenault, Valérie Gaudreault, Paul Poirier, Louis Pérusse, Angelo Tremblay,
Claude Bouchard, Jean-Pierre Després, Caroline Rhéaume
Downloaded from http://hyper.ahajournals.org/ by guest on June 15, 2017
Abstract—Individuals with insulin resistance and low cardiorespiratory fitness are frequently found to have an increased
waist circumference and high exercise blood pressure. We tested the hypothesis that the relationships among insulin
resistance, low cardiorespiratory fitness, and increased exercise blood pressure may be mediated by an elevated waist
circumference. This study included 317 apparently healthy men and women (mean age: 34.8⫾12.8 years; mean body
mass index: 26.1⫾5.2 kg/m2). Exercise blood pressure values were measured using a submaximal ergometer test
evaluating physical working capacity. Plasma insulin and glucose levels were measured during a 3-hour oral glucose
tolerance test. Multivariate regression analyses showed that waist circumference accounted for 32.8% (P⬍0.0001) and
45.1% (P⬍0.0001) of the variance in exercise systolic blood pressure in men and women, respectively. Participants were
classified into tertiles according to either insulin response, measured during the oral glucose tolerance test, or fitness
levels and then further subdivided into 2 subgroups using sex-specific waist circumference thresholds. Individuals with
an increased waist circumference (ⱖ94 cm and ⱖ80 cm for men and women, respectively) had higher exercise systolic
blood pressure compared with individuals with low waist circumference, irrespective of their level of insulin resistance
(10.6 versus 6.8, 12.2 versus 7.7, and 13.2 versus 8.7 mm Hg/metabolic equivalent, respectively, for the low,
intermediate, and high tertiles; P⬍0.05) or fitness levels (13.1 versus 8.2, 12.0 versus 7.9, and 10.6 versus
7.1 mm Hg/metabolic equivalent, respectively, for the low, intermediate, and high tertiles; P⬍0.05). Individuals with a
higher waist circumference have elevated exercise systolic blood pressure, regardless of their insulin sensitivity or level
of cardiorespiratory fitness. (Hypertension. 2011;58:1036-1042.) ● Online Data Supplement
Key Words: insulin resistance 䡲 cardiorespiratory fitness 䡲 abdominal obesity 䡲 exercise blood pressure
I
had higher resting systolic BP (SBP) and diastolic BP (DBP)
than individuals with low levels of visceral adipose tissue.10
Moreover, other investigators observed in women that there is
an association between low CRF and higher exercise SBP
(ExSBP) response during submaximal exercise, even after
adjustment for resting SBP, heart rate, body mass index
(BMI), age, and time to exhaustion.11 However, the specific
contribution of abdominal adiposity to exercise BP (after
control for relevant covariates, including CRF) remains
unclear, but some authors have suggested that this relationship could be related to arterial stiffness, a phenomenon
caused by inflammation.12–14
Although some studies have suggested an association
between insulin resistance (IR) and an increase in BP during
exercise,15 discordant findings have been reported in the
literature. For instance, some have observed a strong relationship between IR and exercise BP,12,16 and others have
t is well-documented that normotensive individuals with an
elevated blood pressure (BP) response to exercise are at a
higher risk of developing future systemic hypertension
(HT).1– 4 It has been reported that individuals characterized by
elevated exercise BP may account for 5%2 to 40%5 of
individuals at risk of developing cardiovascular disease.
Because an abnormal BP response to exercise increases
mortality risk from myocardial infarction and increases the
risk of developing cardiovascular disease,6 – 8 identifying and
understanding the key determinants of exercise-induced BP
response is clinically relevant.
Recently, Carnethon et al9 suggested that low cardiorespiratory fitness (CRF) is associated with incident HT and that
improvement in CRF could prevent 34% of new HT cases. A
previous report from our laboratory showed that, independent
of CRF, individuals with greater visceral adipose tissue
accumulation (measured directly by computed tomography)
Received July 28, 2011; first decision August 22, 2011; revision accepted September 27, 2011.
From the Division of Kinesiology, Department of Social and Preventive Medicine (M.H., L.P., A.T., J.-P.D.) and Department of Family Medicine and
Emergency Medicine (C.R.), Faculty of Medicine, and Faculty of Pharmacy (P.P.), Université Laval, Québec, Québec, Canada; Centre de Recherche de
l’Institut Universitaire de Cardiologie et de Pneumologie de Québec (M.H., B.J.A., V.G., P.P., A.T., J.-P.D., C.R.), Québec, Québec, Canada; Human
Genomics Laboratory (C.B.), Pennington Biomedical Research Center, Baton Rouge, LA.
Correspondence to Caroline Rhéaume, Centre de Recherche de l’Institut Universitaire de Cardiologie et de Pneumologie de Québec, 2725 Chemin
Ste-Foy, Québec, Québec G1V 4G5, Canada. E-mail [email protected]
© 2011 American Heart Association, Inc.
Hypertension is available at http://hyper.ahajournals.org
DOI: 10.1161/HYPERTENSIONAHA.111.180349
1036
Huot et al
reported modest increases in exercise DBP with increases in
IR.13 One study has, however, observed a relationship among
IR, CRF, and obesity (evaluated with BMI and waist:hip
ratio) in men with type 2 diabetes mellitus and found an
independent association between IR and SBP response to
exercise.17
To the best of our knowledge, no study has yet simultaneously examined the relationship among abdominal obesity,
IR, CRF, and BP response to exercise in apparently healthy
adults. The aim of this study was to investigate whether the
relationship between IR and exercise BP, as well as the
relationship between CRF and exercise BP, could be explained by the fact that individuals with IR and/or poor CRF
have greater abdominal fat accumulation.
Methods
Study Population
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Study participants were apparently healthy men and women who
participated in the Québec Family Study. Included in this analysis
were 317 participants without diabetes mellitus and without HT at
rest for whom we had body composition measurements, position
measurements, and data on waist circumference (WC), resting and
submaximal exercise BP, CRF, glucose homeostasis measurement,
lipid profile, and dietary/physical journals. The study sample included participants from whom we obtained data on body composition, CRF, and glucose homeostasis. The Québec Family Study is a
population-based study of French-Canadian families living in and
around the Québec City area. The Québec Family Study was
approved by the medical ethics committee of Université Laval.
Participants were recruited through the media and gave their written
informed consent to participate in the study. Only men and women,
18 to 65 years of age, who were not receiving medication for
cardiovascular disease, diabetes mellitus, HT, dyslipidemias, or
endocrine disorders were considered for the present analyses. The 79
smokers (24.9%) in our cohort were asked to refrain from smoking
before their evaluation. Additional details about the Québec Family
Study have been reported previously.18
Exercise, Blood Pressure, and Abdominal Obesity
1037
last stage. This allowed for the PWC at a heart rate of 150 bpm to be
interpolated.22 The PWC150, defined as the power output at 150 bpm,
was then calculated from the linear relationship between heart rate
and power output and expressed as kilopound per minute per
kilogram (kpm/kg) to take individual differences in body weight into
account. Expired air was analyzed with a Beckman Measurement
Metabolic Cart to obtain oxygen consumption (V̇O2) corrected for
standard conditions and computed in liters of O2 per minute.23 To
consider the individual differences in workloads attained at the final
stage and body weight, the V̇O2 was converted to metabolic equivalents (METs; 1 MET⫽3.5 mL O2*kg⫺1*min⫺1) using the following formula: (V̇O2 (L/min)*1000)/(weight (kg)*3.5).
Resting Hemodynamic Measurement
Resting BP measurements were taken using standard procedures: in
the morning, in the fasting state, and in a semi-inclined position after
a 45-minute rest (after an assessment of resting metabolic rate) using
a mercury sphygmomanometer (Propper) and an appropriately sizedcuff (Welch Allyn Tycos). Resting BP measurements were taken on
the same day as the exercise test. Participants were asked not to
smoke for 2 hours before the measurement of their BP. The mean of
2 valid BP measurements was retained.
Exercise Hemodynamic Measurement
We used levels of BP attained at the last stage of the submaximal
exercise test. As the workload reached during the final stage of the
PWC150 differed from one individual to another, we used the method
described previously by Zanettini et al24 to quantify the increase in
BP adjusted for each individual’s working capacity. Hence, we
computed the difference between the SBP and DBP from rest to
exercise divided by the intensity reached at the end of the last stage
of the PWC150 (Figure S1, available in the online Data Supplement
at http://hyper.ahajournals.org). The ExSBP and exercise DBP were
expressed as SBP or DBP variation per 1-MET increment (in
millimeters of mercury per MET).
Analysis of Dietary Intake
Height and body weight were measured following standardized
procedures. WC was measured using graduated tape while in a
standing position. WC was measured as the narrowest circumference
of the abdomen, between the iliac crest and the twelfth ribs.19
Dietary intake was assessed through the use of a 3-day dietary
journal, which was completed for 2 weekdays and 1 weekend day.
Subjects were asked to record all of the foods and beverages ingested
(except water) with the use of a balance and measuring cups and
spoons. Subjects received instructions from a nutritionist on the
procedures needed to complete the dietary record and to measure
food portions. After completion, the record was verified by a
nutritionist. Macronutrient and micronutrient intakes were estimated
through the use of a computerized version of the Canadian Nutrient
File. Macronutrient intakes were expressed in absolute values (in
grams) and also as percentages of total energy intake.
Glucose Homeostasis Measurement
Physical Activity Measurement
A 3-hour 75-g oral glucose tolerance test was performed in the
morning after an overnight fast. Blood samples were obtained in
EDTA-containing tubes through a venous catheter placed in an
antecubital vein to determine fasting plasma glucose and insulin
levels. Plasma glucose levels were measured enzymatically, and
plasma insulin levels were measured by radioimmunoassay with
polyethylene glycol separation20 at ⫺15, 0, 15, 30, 45, 60, 90, 120,
150, and 180 minutes. Areas under the curve for insulin during the
oral glucose tolerance test were calculated using the trapezoid
method.21
Daily physical activity level and patterns were evaluated through
the use of a 3-day physical activity diary. Subjects recorded the
energy expenditure level for each 15-minute period over 24 hours
based on activities classified on a 1 to 9 scale, with 1 corresponding with activities of very low energy expenditure, such as
sleeping, and 9 to activities of very high energy expenditure, such
as running. Based on this information, we estimated energy
expenditure with daily physical activities and expressed them as
kilocalories per kilogram of body weight to take into account
individual differences in body weight.
CRF Measurement
Statistical Analysis
The CRF of each participant was assessed using a progressive
submaximal physical working capacity (PWC) test performed on a
modified Monark cycle ergometer (Stockholm, Sweden). Heart rate
was measured through an ECG derivation and was recorded during
3 consecutive 6-minute stages with increasing workloads, each
separated by 1 minute of free pedalling at the minimal workload of
25 W. The protocol was designed to ensure that each subject would
reach a target heart rate between 150 and 170 bpm at the end of the
Data are presented as mean⫾SD in Tables and as mean⫾SEM in
Figures. Baseline characteristics of participants are presented separately for men and women. BP was compared between participants
classified on the basis of WC using the most recent cutoffs
established by the International Diabetes Federation (⬍ or ⱖ94 cm
and ⬍ or ⱖ80 cm for white men and women, respectively)25 and
sex-specific tertiles of insulin area under the curve (AUC) or
sex-specific tertiles of CRF. Differences among groups were evalu-
Anthropometric and Body
Composition Measurements
1038
Hypertension
December 2011
Table 1. Characteristics of the 171 Men and 146 Women of
the Study
Variables
men and women analyzed separately. In this model, we included age,
smoking, salt intake, alcohol intake, energy expenditure by kilograms, BMI, WC, insulin AUC, SBP, DPB, and CRF. Statistical
analyses were performed using SAS version 9.2 (SAS Institute,
Cary, NC).
Men (n⫽171)
Women (n⫽146)
Age, y
36.3⫾13.9
33.1⫾11.1
Waist circumference, cm
89.3⫾12.2
80.7⫾14.5
Body mass index, kg/m2
Results
25.9⫾4.2
26.3⫾6.1
Resting SBP, mm Hg
113⫾10
108⫾9
Resting DBP, mm Hg
70⫾8
67⫾8
6.92⫾1.40
5.90⫾1.38
Total cholesterol, mmol/L
4.8⫾1.0
4.6⫾0.9
HDL cholesterol, mmol/L
1.1⫾0.3
1.3⫾0.3
LDL cholesterol, mmol/L
3.0⫾0.8
2.7⫾0.8
Cholesterol/HDL cholesterol
4.6⫾1.4
3.7⫾1.0
Triglycerides, mmol/L
1.5⫾1.0
1.2⫾0.5
The study sample included 171 apparently healthy men and
146 apparently healthy women. A total of 71 participants
were classified as prehypertensive according to American
guidelines on HT.26 Table 1 presents baseline anthropometric
and metabolic characteristics of study participants, as well as
resting SBP and DBP and exercise BP at 150 bpm. Mean
CRF levels for men and women derived from the PWC150 test
are also shown.
Pearson correlation coefficients for the associations among
WC, insulin AUC, CRF, and BP indices before and after
adjustment for cardiometabolic risk markers are presented in
Table 2. Table 3 presents the partial and total contributions of
the combination of BMI, WC, insulin AUC, age, smoking,
salt intake, alcohol intake, energy expenditure, SBP, DBP,
and PWC150 to the variance of ExSBP for the entire cohort
and for men and women examined separately. Thus, WC
made significant a contribution to the variance of ExSBP in
both sexes.
Because WC is a crude clinical marker of intra-abdominal
obesity, we have repeated all of the above analyses by
replacing WC with a direct measurement of visceral adiposity
measured by computed tomography. Essentially similar results were observed using either WC or visceral adipose
tissue as the abdominal adiposity variable (data not shown).
PWC150/kg, METs
Glucose, mmol/L
Insulin, pmol/L
5.2⫾0.5
5.0⫾0.4
61.2⫾43.1
64.2⫾48.2
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PWC150/kg indicates physical working capacity at 150 bpm; SBP, systolic
blood pressure; DBP, diastolic blood pressure; HDL, high-density lipoprotein;
LDL, low-density lipoprotein; MET, metabolic equivalent. Data are presented as
mean⫾SD.
ated with a 1-way ANOVA. Pearson correlation coefficients, adjusted for age, smoking, physical activity, and diet, or for a
combination of these previous variables and 2 of the 3 cardiometabolic risk markers considered in the present study, were performed to
assess the sex-specific relationships between WC, insulin AUC or
CRF with BP indices. Stepwise multiple regression analyses were
computed to quantify the contribution of cardiometabolic risk
markers to the variance in BP indices for the entire sample and for
Table 2. Correlation Coefficients (R) Among Waist Circumference, Insulin Area Under The Curve Measured During a 75-g Oral
Glucose Tolerance Test, Cardiorespiratory Fitness, and Blood Pressure Indices Before and After Adjustment for Insulin Area Under the
Curve, Cardiorespiratory Fitness, or Waist Circumference
WC
Variable
Adjusted for Age,
Smoking, Physical
Activity, and Diet
Insulin AUC
Adjusted for
Insulin AUC
and CRF
CRF
Adjusted for Age,
Smoking, Physical
Activity, and Diet
Adjusted for WC
and CRF
Adjusted for Age,
Smoking, Physical
Activity, and Diet
Adjusted for WC
and Insulin AUC
⫺0.02
Total (n⫽300)
SBP
0.27†
0.24†
0.12*
0.01
⫺0.06
DBP
0.30†
0.24†
0.19*
0.08
⫺0.04
ExSBP
0.58†
0.48†
0.45†
0.26†
⫺0.20*
⫺0.13*
0.07
0.13*
0.01
0.03
ExDBP
⫺0.09
0.02
⫺0.07
Men (n⫽163)
SBP
0.21*
0.17*
0.13
0.04
⫺0.07
⫺0.00
DBP
0.25*
0.17*
0.23*
0.14
⫺0.07
0.03
0.40†
ExSBP
ExDBP
0.48†
⫺0.03
0.28*
0.02
⫺0.29*
⫺0.18*
⫺0.05
0.02
0.02
⫺0.05
⫺0.05
Women (n⫽137)
SBP
0.28*
0.16
0.12
⫺0.02
⫺0.30*
⫺0.20*
DBP
0.27*
0.18*
0.12
0.00
⫺0.21*
⫺0.10
ExSBP
0.63†
0.50†
0.57†
0.42†
⫺0.31*
0.02
ExDBP
⫺0.17*
0.13
0.22*
0.11
0.07
⫺0.16
WC indicates waist circumference; insulin AUC, insulin area under the curve measured during a 75-g oral glucose tolerance test; CRF, cardiorespiratory fitness;
SBP, systolic blood pressure; DBP, diastolic blood pressure; ExSBP, exercise systolic blood pressure; ExDBP, exercise diastolic blood pressure.
*Pⱕ0.05.
†P⬍0.0001.
Exercise, Blood Pressure, and Abdominal Obesity
R2, %
Dependent
Variables
Independent Variables
Partial
Total
P
WC
40.1
40.1
⬍0.0001
⫹Insulin AUC
⫹4.3
44.4
⬍0.0001
⫹Age
⫹4.0
48.4
⬍0.0001
⫹DBP
⫹1.2
49.7
0.0075
⫹BMI
⫹0.7
Total (n⫽300)
ExSBP
50.4
0.0432
⫹SBP
⫹PWC150/kg
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⫹Smoking
⫹Salt intake
⫹Alcohol intake
⫹Energy expenditure
Men (n⫽163)
ExSBP
WC
32.8
32.8
⬍0.0001
⫹Age
⫹6.0
38.8
0.0001
⫹DBP
⫹4.0
42.8
0.001
⫹PWC150/kg
⫹1.9
44.7
0.0216
⫹BMI
16
14
Low WC
High WC
12
1
1,2,3,5
1,3
1,2,4
10
2
8
6
4
2
0
B
1039
(1) (2)
Low
(3) (4)
Intermediate
(5) (6)
High
Insulin AUC Tertiles
1.6
1.4
Low WC
High WC
1,2
1.2
1.0
0.8
0.6
0.4
0.2
0
(1) (2)
Low
(3) (4)
Intermediate
(5) (6)
High
Insulin AUC Tertiles
Figure 1. Mean variation values of systolic blood pressure (SBP;
A) and diastolic blood pressure (DBP; B) induced by exercise
corrected for intensity (⌬SBP and ⌬DBP per 1-metabolic equivalent [MET] increment) classified on the basis of sex-specific
tertiles of insulin area under the curve (AUC; lowest: ⬍40 785;
intermediate: ⱖ40 785 and ⬍70 230; or highest: ⱖ70 230
pmol/L for men and lowest: ⬍46 931; intermediate: ⱖ46 931
and ⬍69 701; or highest: ⱖ69 701 pmol/L for women) and waist
circumference (WC; ⬍ or ⱖ94 cm and ⬍ or ⱖ80 cm for men
and women, respectively). 1, 2, 3, 4, and 5 are significantly different from corresponding subgroup. P⬍0.05.
⫹Insulin AUC
⫹SBP
⫹Smoking
⫹Salt intake
⫹Alcohol intake
⫹Energy expenditure
Women (n⫽137)
ExSBP
A
Δ SBP per 1-MET increment
(mm Hg / MET)
Table 3. Multivariate Regression Analyses Showing the
Contribution of Age, Smoking, Salt Intake, Alcohol Intake,
Energy Expenditure, Body Mass Index, Waist Circumference,
Insulin Area Under the Curve, Systolic Blood Pressure, Diastolic
Blood Pressure, and Cardiorespiratory Fitness to the Variance
in Exercise Systolic Blood Pressure
Δ DBP per 1-MET increment
(mm Hg / MET)
Huot et al
WC
45.1
45.1
⬍0.0001
⫹Insulin AUC
⫹9.1
54.2
⬍0.0001
⫹Age
⫹3.9
58.1
0.0006
⫹BMI
⫹SBP
⫹DBP
⫹PWC150/kg
⫹Smoking
⫹Salt intake
⫹Alcohol intake
⫹Energy expenditure
Variables included in the multivariate model were age, smoking, salt intake,
alcohol intake, energy expenditure per kilogram, BMI, WC, insulin AUC, SBP, DBP,
PWC150/kg, and ExSBP. WC indicates waist circumference; insulin AUC, insulin area
under the curve measured during a 75-g oral glucose tolerance test; CRF,
cardiorespiratory fitness; SBP, systolic blood pressure; DBP, diastolic blood
pressure; ExSBP, exercise systolic blood pressure; BMI, body mass index;
PWC150/kg, physical working capacity at 150 bpm; salt intake, average No. of salted
foods recorded in each participant’s dietary journal; alcohol intake, average grams
per day of alcohol recorded in each participant’s dietary journal; energy expenditure, expressed as kilocalories per kilogram of body weight (kcal/kg).
To determine whether IR is associated with higher exercise
BP, we classified men and women on the basis of sex-specific
tertiles of insulin AUC and sex-specific WC (⬍ or ⱖ94 cm
and ⬍ or ⱖ80 cm for men and women, respectively). Figure
1A shows that individuals with elevated WC had higher
values of ⌬SBP per 1-MET increment compared with individuals with low WC, independent of insulin levels. There
was no relationship between groups of insulin AUC and WC
for ⌬DBP per 1-MET increment (Figure 1B).
Finally, to determine whether poor CRF is associated with
higher exercise BP, men and women were classified on the
basis of sex-specific tertiles of CRF and sex-specific WC (⬍
or ⱖ94 cm and ⬍ or ⱖ80 cm for men and women,
respectively). Figure 2A shows that individuals with elevated
WC had higher values of ⌬SBP per 1-MET increment
compared with individuals with low WC, independent of
CRF. However, individuals with high CRF had lower ⌬SBP
per 1-MET increment compared with those with low CRF for
similar WC. There was no difference between groups of CRF
and WC for ⌬DBP per 1-MET increment (Figure 2B).
1040
Δ SBP per 1-MET increment
(mm Hg / MET)
A
Hypertension
16
14
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Δ DBP per 1-MET increment
(mm Hg / MET)
Low WC
High WC
1
1,3
1,2,3,5
12
10
2
8
1,2,4
6
4
2
0
B
December 2011
(1) (2)
Low
(3) (4)
Intermediate
(5) (6)
High
CRF Tertiles
1.8
1.6
Low WC
High WC
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0
(1) (2)
Low
(3) (4)
Intermediate
(5) (6)
High
CRF Tertiles
Figure 2. Mean variation values of systolic blood pressure (SBP;
A) and diastolic blood pressure (DBP; B) induced by exercise
corrected for intensity (⌬SBP and ⌬DBP per 1-metabolic equivalent [MET] increment) classified on the basis of sex-specific
tertiles of CRF (lowest: ⬍9.63; intermediate: ⱖ9.63 and ⬍12.07;
highest: ⱖ12.07 kpm/kg for men and lowest: ⬍6.93; intermediate: ⱖ6.93 and ⬍8.65; highest: ⱖ8.65 kpm/kg for women) and
waist circumference (WC; ⬍ or ⱖ94 cm and ⬍ or ⱖ80 cm for
men and women, respectively). 1, 2, 3, 4, and 5 are significantly
different from corresponding subgroup. P⬍0.05.
Discussion
The most important finding of our study is that, irrespective
of IR and/or CRF levels, apparently healthy men and women
with elevated WC had a more pronounced increase in
exercise BP than subjects with a lower WC. Although we did
notice that IR and CRF levels were associated with BP
indices (especially ExSBP) measured during a submaximal
test, our results suggest that such an association could be
explained to a large extent by the fact that individuals with IR
and/or low CRF levels were also characterized by abdominal
obesity. This finding suggests that an increased WC may capture
a fair amount of metabolically active visceral fat, which may
represent a key “mediating factor” linking low CRF and/or IR to
higher ExSBP. The rationale for identifying another potential
mediating factor in the relationship between low CRF and
incident HT using an intermediate risk marker for HT is that the
evaluation of exercise BP combined with abdominal obesity
could enable the clinician to identify, at an earlier stage,
individuals at increased risk of cardiovascular events.
Previous studies have also examined the relationship between IR and exercise BP. In a sample of treated nondiabetic
hypertensive individuals, Park et al27 showed that individuals
with an elevated homeostasis model assessment index were
also likely to have an exaggerated BP response to exercise, a
finding that suggests the contribution of IR to the regulation
of exercise BP.27 This association was also found to be
independent of resting BP.27 Other authors who previously
studied IR and exercise BP in normotensive insulin resistant
HT-prone subjects,28 active asymptomatic men,29 and uncomplicated type 2 diabetic men,29 observed an increase in
exercise DBP with increases in IR. The hypothesis put
forward to explain these variations is that there is a close
relationship between DBP and peripheral vascular resistance28 or there is an impaired vascular reactivity combined to
higher serum cholesterol concentrations.29 However, our
study only showed a difference in the ExSBP of abdominally
obese individuals who were in the highest insulin tertiles.
Thus, our study provides evidence that the previously reported association between IR and exercise BP could be
explained by the concomitant presence of abdominal obesity.
In addition, Brett et al29 have also suggested that IR was
influenced by CRF and that it could partly explain the
association between exercise DBP and IR. In a large population of 1411 normotensive and hypertensive women, Kokkinos et al11 showed that the most important determinants of
BP response to exercise were resting SBP and effort duration.11 After 6 minutes of exercise, SBP was significantly
more elevated in women with low CRF, even after adjustment
for age, BMI, and resting BP,11 compared with women with
high CRF. Results obtained by Brett et al29 are similar to our
results in that low CRF seemed to be associated with higher
ExSBP compared with individuals with high levels of CRF.
Kumagai et al17 studied the relationship of SBP during
exercise with IR, obesity, and CRF in men with type 2
diabetes mellitus. Their results showed that changes in SBP
during exercise were significantly and negatively associated
with glucose tolerance and IR. These findings suggested an
independent association between IR and SBP response to
exercise.17 However, they did not find any relationship
between ExSBP and markers of adiposity, such as waist:hip
ratio, BMI, body fat percentage, and either visceral fat area or
subcutaneous fat area.17 However, this study included only 63
men, all of whom had type 2 diabetes mellitus. It is also
possible that the more pronounced impairments in the plasma
glucose-insulin homeostasis, such as those observed in patients with type 2 diabetes mellitus, may contribute to
deteriorations in hemodynamic parameters, irrespective of
adiposity indices.
Several pathophysiological mechanisms linking IR, CRF,
abdominal obesity, and exercise BP may contribute to an
increased BP response to exercise. Previous studies have
shown that arterial stiffness is associated with an exaggerated
BP response to exercise, obesity, IR,30 and poor CRF.12,31
One factor typically observed in individuals with IR and/or
abdominal fat accumulation is a decrease in NO bioavailability, which could be the result of increased blood glucose and
free fatty acid concentrations and an increased superoxide
production by adipocytes.32 This impairment could also be
related to inflammation with visceral fat producing several
proinflammatory cytokines14 or the result of an inappropriately
elevated cyclic GMP stimulated by NO, therefore impairing
Huot et al
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vasodilation.13 It is also plausible that renin-angiotensin-aldosterone system could be involved, because visceral fat secretes
renin-angiotensin-aldosterone system mediators, such as angiotensinogen,14 which is associated with vascular inflammation.
Angiotensin also mediates negative cardiovascular effects
through the signaling pathways of reactive oxygen species,
which amplifies oxidative stress provoked by other agents33 and
has been linked to increases in exercise BP.34
According to previous work35–38 showing the stronger
predictive value of WC for incident HT, our results indicate
that WC seems to be more closely associated with BP indices
than any other obesity indices, such as BMI (Table 3). Such
a conclusion is also consistent with findings from our
previous longitudinal study, which indicated that maintaining
low levels of visceral adiposity and high levels of CRF were
both important targets for the maintenance of a healthy
cardiometabolic risk profile (including BP) in apparently
healthy individuals.39
It is important to note that our study population was limited
to middle-aged white participants with a relatively low
prevalence of HT. This may limit the generalization of our
findings to other populations with various ethnicities and with
broader age ranges or diseases.40 In addition, considering that
there was no replication sample available, the unique size and
characteristics of our cohort may have had an impact on
which variables were retained in our model. Also, the
possibility of a measurement bias in the assessment of resting
BP (only office BP) should be taken into consideration,
because ambulatory BP monitoring has been shown to provide more accurate assessment of BP.
In conclusion, these results suggest that abdominally obese
individuals are characterized by an elevated SBP response to
exercise, irrespective of IR and CRF levels. The evaluation of
exercise BP combined with abdominal obesity could enable
the clinician to identify, at an earlier state, individuals at
increased risk of cardiovascular events.
Perspectives
Based on our findings, we believe that longitudinal and/or
intervention studies with specific measurements of IR, CRF,
exercise BP, and abdominal obesity are required to properly
investigate risk factors of HT and the extent to which the
relationship between these parameters is explained by abdominal obesity. Of course, we recognize that the BP response to exercise is not routinely performed in clinical
practice for abdominally obese patients, but we hope that our
study will raise interest in future studies looking further at
this potentially useful marker. Moreover, because of the lack
of studies investigating the impact of physical activity and/or
CRF levels and other lifestyle interventions, further interventional studies are needed to investigate whether increasing
CRF levels and decreasing abdominal obesity will lead to
improvements in BP at exercise and, consequently, will
decrease cardiovascular disease risk. Identifying cardiometabolic risk factors of HT and the extent to which these risk
factors contribute to BP are key to the development of
successful BP managing strategies.
Exercise, Blood Pressure, and Abdominal Obesity
1041
Acknowledgments
We express our gratitude to the Québec Family Study subjects for
their excellent collaboration and the staff of Centre Hospitalier de
l’Université Laval. We especially thank Guy Fournier and Lucie
Allard of the Centre de Recherche de l’Institut Universitaire de
Cardiologie et de Pneumologie de Québec; Dr Germain Thériault of
Université Laval; and Claude Leblanc of the Physical Activity
Sciences Laboratory for their help with data collection and for their
contribution to the study.
Sources of Funding
B.J.A. is supported by a postdoctoral fellowship from the Fonds de
la Recherche en Santé du Québec and the Fondation de l’Institut
Universitaire de Cardiologie et de Pneumologie de Québec. C.B. is
partly funded by the John W. Barton, Sr, Chair in Genetics and
Nutrition. A.T. is partly funded by the Canada Research Chair in
Environment and Energy Balance. J.-P.D. is the scientific director of
the International Chair on Cardiometabolic Risk, which is based at
Université Laval. P.P. is a clinical scholar from the Fonds de la
Recherche en Santé du Québec. The Québec Family Study was
supported by multiple grants from the Medical Research Council of
Canada (now the Canadian Institutes of Health Research), the
Canadian Diabetes Association, and other agencies in Québec and
elsewhere in Canada.
Disclosures
None.
References
1. Manolio TA, Burke GL, Savage PJ, Sidney S, Gardin JM, Oberman A.
Exercise blood pressure response and 5-year risk of elevated blood
pressure in a cohort of young adults: the CARDIA Study. Am J
Hypertens. 1994;7:234 –241.
2. Singh JP, Larson MG, Manolio TA, O’Donnell CJ, Lauer M, Evans JC,
Levy D. Blood pressure response during treadmill testing as a risk factor
for new-onset hypertension: the Framingham Heart Study. Circulation.
1999;99:1831–1836.
3. Miyai N, Arita M, Morioka I, Miyashita K, Nishio I, Takeda S. Exercise
BP response in subjects with high-normal BP: exaggerated blood pressure
response to exercise and risk of future hypertension in subjects with
high-normal blood pressure. J Am Coll Cardiol. 2000;36:1626 –1631.
4. Matthews CE, Pate RR, Jackson KL, Ward DS, Macera CA, Kohl HW,
Blair SN. Exaggerated blood pressure response to dynamic exercise and
risk of future hypertension. J Clin Epidemiol. 1998;51:29 –35.
5. Laukkanen JA, Kurl S, Rauramaa R, Lakka TA, Venalainen JM, Salonen
JT. Systolic blood pressure response to exercise testing is related to the
risk of acute myocardial infarction in middle-aged men. Eur J Cardiovasc
Prev Rehabil. 2006;13:421– 428.
6. Mundal R, Kjeldsen SE, Sandvik L, Erikssen G, Thaulow E, Erikssen J.
Exercise blood pressure predicts mortality from myocardial infarction.
Hypertension. 1996;27:324 –329.
7. Filipovsky J, Simon J, Chrastek J, Rosolova H, Haman P, Petrikova V.
Changes of blood pressure and lipid pattern during a physical training
course in hypertensive subjects. Cardiology. 1991;78:31–38.
8. Kurl S, Laukkanen JA, Rauramaa R, Lakka TA, Sivenius J, Salonen JT.
Systolic blood pressure response to exercise stress test and risk of stroke.
Stroke. 2001;32:2036 –2041.
9. Carnethon MR, Evans NS, Church TS, Lewis CE, Schreiner PJ, Jacobs
DR Jr, Sternfeld B, Sidney S. Joint associations of physical activity and
aerobic fitness on the development of incident hypertension: coronary
artery risk development in young adults. Hypertension. 56:49 –55.
10. Rheaume C, Arsenault BJ, Belanger S, Perusse L, Tremblay A, Bouchard
C, Poirier P, Despres JP. Low cardiorespiratory fitness levels and elevated
blood pressure: what is the contribution of visceral adiposity?
Hypertension. 2009;54:91–97.
11. Kokkinos PF, Andreas PE, Coutoulakis E, Colleran JA, Narayan P,
Dotson CO, Choucair W, Farmer C, Fernhall B. Determinants of exercise
blood pressure response in normotensive and hypertensive women: role
of cardiorespiratory fitness. J Cardiopulm Rehabil. 2002;22:178 –183.
12. Tsiachris D, Tsioufis C, Dimitriadis K, Kokkinos P, Faselis C, Tousoulis
D, Michaelides A, Papademetriou V, Stefanadis C. Relationship of ambu-
1042
13.
14.
15.
16.
17.
18.
Downloaded from http://hyper.ahajournals.org/ by guest on June 15, 2017
19.
20.
21.
22.
23.
24.
25.
Hypertension
December 2011
latory arterial stiffness index with blood pressure response to exercise in
the early stages of hypertension. Blood Press Monit. 15:132–138.
Chang HJ, Chung JH, Choi BJ, Choi TY, Choi SY, Yoon MH, Hwang
GS, Shin JH, Tahk SJ, Choi BI. Endothelial dysfunction and alteration of
nitric oxide/cyclic GMP pathway in patients with exercise-induced hypertension. Yonsei Med J. 2003;44:1014 –1020.
Hutley L, Prins JB. Fat as an endocrine organ: relationship to the metabolic syndrome. Am J Med Sci. 2005;330:280 –289.
Sironi AM, Gastaldelli A, Mari A, Ciociaro D, Positano V, Buzzigoli E,
Ghione S, Turchi S, Lombardi M, Ferrannini E. Visceral fat in hypertension: influence on insulin resistance and ␤-cell function. Hypertension.
2004;44:127–133.
Tzemos N, Lim PO, MacDonald TM. Exercise blood pressure and endothelial dysfunction in hypertension. Int J Clin Pract. 2009;63:202–206.
Kumagai S, Kai Y, Hanada H, Uezono K, Sasaki H. Relationships of the
systolic blood pressure response during exercise with insulin resistance,
obesity, and endurance fitness in men with type 2 diabetes mellitus.
Metabolism. 2002;51:1247–1252.
Bouchard C. Genetic epidemiology, association, and sib-pair linkage:
Results from the Québec Family Study. In: Bray GA, Ryan DH, eds.
Molecular and Genetic Aspects of Obesity. Pennington Center Nutrition
Series. Baton Rouge, LA: Louisiana State University Press; 1996;5:
470 – 481.
Lohman TG, Roche AF, Martorell R. Chapter 4: circumferences. In:
Book HK, ed. Anthropometric Standardization Reference Manual.
Champaign, IL: Human Kinetics Books; 1988:39 – 80.
Richterich R, Dauwalder H. Determination of plasma glucose by
hexokinase-glucose-6-phosphate dehydrogenase method [in German].
Schweiz Med Wochenschr. 1971;101:615– 618.
Arsenault BJ, Lachance D, Lemieux I, Alméras N, Tremblay A, Bouchard
C, Pérusse L, Després JP. Visceral adipose tissue accumulation, cardiorespiratory fitness, and features of the metabolic syndrome. Arch Intern
Med. 2007;167:1518 –1525.
Bouchard C, Lortie G, Simoneau JA, Leblanc C, Theriault G, Tremblay
A. Submaximal power output in adopted and biological siblings. Ann
Hum Biol. 1984;11:303–309.
Lortie G, Bouchard C, Leblanc C, Tremblay A, Simoneau JA, Theriault
G, Savoie JP. Familial similarity in aerobic power. Hum Biol. 1982;54:
801– 812.
Zanettini JO, Pisani Zanettini J, Zanettini MT, Fuchs FD. Correction of
the hypertensive response in the treadmill testing by the work performance improves the prediction of hypertension by ambulatory blood
pressure monitoring and incidence of cardiac abnormalities by echocardiography: results of an eight year follow-up study. Int J Cardiol. 141:
243–249.
Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA,
Fruchart JC, James WP, Loria CM, Smith SC Jr. Harmonizing the
metabolic syndrome: a joint interim statement of the International
Diabetes Federation Task Force on Epidemiology and Prevention;
National Heart, Lung, and Blood Institute; American Heart Association;
World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:
1640 –1645.
26. Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL
Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ. The
seventh report of the Joint National Committee on Prevention, Detection,
Evaluation, and Treatment of High Blood Pressure: the JNC 7 report.
Hypertension. 2003;42:1206 –1252.
27. Park S, Shim J, Kim JB, Ko YG, Choi D, Ha JW, Rim SJ, Jang Y, Chung
N. Insulin resistance is associated with hypertensive response to exercise
in non-diabetic hypertensive patients. Diabetes Res Clin Pract. 2006;73:
65– 69.
28. Andersen UB, Olsen MH, Dige-Petersen H, Ibsen H. Exercise blood
pressure is related to insulin resistance in subjects with two hypertensive
parents. Blood Press. 2003;12:314 –318.
29. Brett SE, Ritter JM, Chowienczyk PJ. Diastolic blood pressure changes
during exercise positively correlate with serum cholesterol and insulin
resistance. Circulation. 2000;101:611– 615.
30. Webb DR, Khunti K, Silverman R, Gray LJ, Srinivasan B, Lacy PS,
Williams B, Davies MJ. Impact of metabolic indices on central artery
stiffness: independent association of insulin resistance and glucose with
aortic pulse wave velocity. Diabetologia. 53:1190 –1198.
31. Tsioufis C, Dimitriadis K, Thomopoulos C, Tsiachris D, Selima M,
Stefanadi E, Tousoulis D, Kallikazaros I, Stefanadis C. Exercise blood
pressure response, albuminuria, and arterial stiffness in hypertension.
Am J Med. 2008;121:894 –902.
32. Seifalian AM, Filippatos TD, Joshi J, Mikhailidis DP. Obesity and arterial
compliance alterations. Curr Vasc Pharmacol. 8:155–168.
33. Nashar K, Nguyen JP, Jesri A, Morrow JD, Egan BM. Angiotensin
receptor blockade improves arterial distensibility and reduces exerciseinduced pressor responses in obese hypertensive patients with the metabolic syndrome. Am J Hypertens. 2004;17:477– 482.
34. Shim CY, Ha JW, Park S, Choi EY, Choi D, Rim SJ, Chung N. Exaggerated blood pressure response to exercise is associated with augmented
rise of angiotensin II during exercise. J Am Coll Cardiol. 2008;52:
287–292.
35. Chuang SY, Chou P, Hsu PF, Cheng HM, Tsai ST, Lin IF, Chen CH.
Presence and progression of abdominal obesity are predictors of future
high blood pressure and hypertension. Am J Hypertens. 2006;19:
788 –795.
36. Poirier P, Lemieux I, Mauriège P, Dewailly E, Blanchet C, Bergeron J,
Despres JP. Impact of waist circumference on the relationship between
blood pressure and insulin: the Quebec Health Survey. Hypertension.
2005;45:363–367.
37. Yanai H, Tomono Y, Ito K, Furutani N, Yoshida H, Tada N. The
underlying mechanisms for development of hypertension in the metabolic
syndrome. Nutr J. 2008;7:10.
38. Kanai H, Matsuzawa Y, Kotani K, Keno Y, Kobatake T, Nagai Y,
Fujioka S, Tokunaga K, Tarui S. Close correlation of intra-abdominal fat
accumulation to hypertension in obese women. Hypertension. 1990;16:
484 – 490.
39. Rheaume C, Arsenault BJ, Dumas MP, Perusse L, Tremblay A, Bouchard
C, Poirier P, Despres JP. Contributions of cardiorespiratory fitness and
visceral adiposity to six-year changes in cardiometabolic risk markers in
apparently healthy men and women. J Clin Endocrinol Metab. 2011;96:
1462–1468.
40. Poirier P. Obesity, adiposity indices, and blood pressure; ethnicity does
matter. Am J Hypertens. 2008;21:244.
Insulin Resistance, Low Cardiorespiratory Fitness, and Increased Exercise Blood
Pressure: Contribution of Abdominal Obesity
Maxime Huot, Benoit J. Arsenault, Valérie Gaudreault, Paul Poirier, Louis Pérusse, Angelo
Tremblay, Claude Bouchard, Jean-Pierre Després and Caroline Rhéaume
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Hypertension. 2011;58:1036-1042; originally published online October 24, 2011;
doi: 10.1161/HYPERTENSIONAHA.111.180349
Hypertension is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231
Copyright © 2011 American Heart Association, Inc. All rights reserved.
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Online Supplement
INSULIN RESISTANCE, LOW CARDIORESPIRATORY FITNESS AND INCREASED
EXERCISE BLOOD PRESSURE: CONTRIBUTION OF ABDOMINAL OBESITY
Short title: Exercise, blood pressure and abdominal obesity
Maxime Huot, BSc1,2, Benoit J. Arsenault, PhD2, Valérie Gaudreault, MD², Paul Poirier, MD,
PhD, FRCPC, FACC, FAHA2,3, Louis Pérusse, PhD1, Angelo Tremblay, PhD1,2, Claude
Bouchard, PhD4, Jean-Pierre Després, PhD, FAHA1,2, Caroline Rhéaume, MD, PhD, CFPC2,5
1) Division of Kinesiology, Department of Social and Preventive Medicine, Faculty of
Medicine, Université Laval, Québec, Canada
2) Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de
Québec, Québec, Canada
3) Faculty of Pharmacy, Université Laval, Québec, Canada
4) Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge,
LA, United States.
5) Department of Family Medicine and Emergency Medicine, Faculty of Medicine,
Université Laval, Québec, Canada
Address for correspondence:
Caroline Rhéaume, MD, PhD, CFPC
Centre de recherche de l’Institut universitaire de cardiologie et de pneumologie de
Québec
2725 Chemin Ste-Foy
Québec, Québec
G1V 4G5, Canada
TEL: (418) 656-8711 x 3717
Examples of the correction of peak exercise blood pressure by intensity in MET
Figure S1. Example A shows the blood pressure response of 2 individuals who reached the same
intensity (7 METs, an average response for our cohort) at the last stage of the PWC150. However,
the high responder with a peak SBP of 210 mm Hg had an increase of 12,86 mm Hg/MET
compared to the low responder who only increased his SBP by 5 mm Hg/MET, reaching 155 mm
Hg. Example B shows the blood pressure response of 2 individuals who reached the same SBP
(210 mm Hg) but at different intensities for the last stage of the PWC150. Even though both had
an elevated SBP increase at exercise, the high SBP responder, who only reached 7 METs(,) had
an increase of 12,86 mm Hg/MET compared to the low SBP responder, who reached 12 METs
with a 7,5 mm Hg/MET increase.