Resting Metabolic Rate and Substrate Use in
Obesity Hypertension
Iris Kunz, Ulrike Schorr, Susanne Klaus, Arya M. Sharma
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Abstract—There is substantial evidence that obesity is a prime risk factor for the development of hypertension. Although
hyperinsulinemia and an increased activity of the sympathetic nervous system have been implicated in the pathogenesis
of “obesity hypertension,” their effects on energy metabolism have not been studied thus far. In the present study, we
therefore examined resting metabolic rate (RMR) and basal substrate oxidation in subjects with obesity and
obesity-related hypertension. A total of 166 subjects were characterized for RMR and basal substrate use through
indirect calorimetry. Blood pressure was measured at rest and with 24-hour ambulatory monitoring. Blood samples were
collected for the measurement of plasma catecholamines, leptin, and the insulin response to an oral glucose load. In our
study population, 116 subjects were defined as hypertensive and 91 were defined as obese. Hypertensive patients under
␤-adrenergic blockade (n⫽42) had a significantly lower RMR than did patients without ␤-blockade (P⬍0.05) and were
therefore excluded from further analyses. Univariate regression analysis revealed a significant relationship between
RMR and body fat mass, as well as body fat–free mass, in both groups. Compared with obese normotensive control
subjects (n⫽27), obese hypertensives (n⫽43) had a 9% higher RMR (P⬍0.05), higher plasma catecholamine (P⬍0.05)
and leptin (P⬍0.05) levels, and an increased insulin response to oral glucose (P⬍0.01). Together, these findings are
compatible with the idea that chronic neurogenic and metabolic adaptations related to obesity may play a role in the
development of obesity hypertension in susceptible individuals. (Hypertension. 2000;36:26-32.)
Key Words: energy expenditure 䡲 blood pressure 䡲 nervous system, sympathetic 䡲 glucose 䡲 obesity 䡲 leptin
O
subjects with obesity and obesity-related hypertension. All
patients were also characterized for blood pressure, sympathetic nervous system activity, and glucose tolerance.
besity is an increasingly common disorder in both
developed and developing countries.1 There is substantial clinical and epidemiological evidence that obesity represents an independent risk factor for the development of
cardiovascular diseases,2,3 including hypertension.4 Hypertension in obesity is a result of complex interactions among
hormonal, hemodynamic, and nutritional factors, but the
relationship between these factors remains poorly understood.
Nevertheless, both increased activity of the sympathetic
nervous system and hyperinsulinemia, secondary to insulin
resistance, have been implicated in the pathogenesis of
“obesity hypertension.”5
The sympathetic nervous system plays an important role in
the regulation of energy intake and energy expenditure.6
Although several investigators have shown an acute thermogenic effect of catecholamines on energy expenditure,7–9
there is no evidence regarding the chronic adaptation of
energy expenditure to hormonal and endocrine alterations in
obesity-related hypertension.
The aim of our study was therefore to examine resting
metabolic rate (RMR), which accounts for 65% to 75% of
total energy expenditure,10 and basal substrate oxidation in
Methods
Subjects
A total of 166 subjects (51 men and 115 women) with a wide range
of body weights (body mass index [BMI] range 19.4 to 52.2 kg/m2),
with and without hypertension, volunteered for the study. Patients
with known diabetes mellitus, congestive heart failure, abnormal
renal or liver function, and intentional weight reduction during the
past 3 months were excluded from the study. Obesity was defined as
a BMI of ⱖ30 kg/m2,1 and ambulatory blood pressure measurement
(90207; SpaceLabs Medical Inc) was performed for the definition of
hypertension in untreated patients. Patients with a mean 24-hour
ambulatory blood pressure level of ⬎135/85 mm Hg11 or on any
antihypertensive medication were defined as hypertensive. Furthermore, the intake of thyroid hormone and other medications was
recorded. The study protocol was approved by the institutional ethics
committee, and all subjects gave informed consent before participation in the study.
Study Protocol
All subjects were characterized for weight, height, and waist and hip
circumference, and body composition was determined with bioelec-
Received December 10, 1999; first decision January 7, 2000; revision accepted February 18, 2000.
From the German Institute of Human Nutrition (I.K., S.K.), Division of Biochemistry and Physiology of Nutrition, Potsdam-Rehbrücke, Germany; and
Department of Internal Medicine (I.K., U.S., A.M.S.), Division of Endocrinology and Nephrology, Universitätsklinikum Benjamin Franklin, Berlin,
Germany.
Correspondence to Prof Arya M. Sharma, Abteilung für Nephrologie u. Hypertensiologie, Franz-Volhard-Klinik-Charité, Humboldt Universität zu
Berlin, 13122 Berlin-Buch, Germany. E-mail [email protected]
© 2000 American Heart Association, Inc.
Hypertension is available at http://www.hypertensionaha.org
26
Kunz et al
Energy Metabolism in Obesity Hypertension
27
measurements at 60 and 120 minutes. Impaired glucose tolerance
was defined according to the World Health Organization criteria.13
A minimum of 7 days after the oral glucose tolerance test, all
subjects underwent a measurement of energy expenditure. For
this measurement, subjects were admitted to a metabolic ward on
the evening before the test and were given a light evening snack.
After a 12-hour overnight fast, RMR was measured in the sitting
awake subject in a temperature-controlled room over two 25minute periods with an open-circuit indirect calorimetry system
(standardized for temperature, pressure, and moisture) fitted with
a face mask (Sensor Medics 2900 Z; NewMedics Medizinelektronik GmbH). During the measurement of energy expenditure,
complete urine samples were collected for the assessment of
nitrogen excretion. For each measurement, the first 5 minutes
were discarded to allow subjects to adapt to the measurement
procedure, and data from the remaining 20 minutes were averaged
and used to calculate energy expenditure and substrate oxidation
based on oxygen consumption, carbon dioxide production, and
urinary nitrogen excretion.14,15
Analytical Measurements
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Plasma electrolytes and glucose were measured according to standard laboratory techniques. Radioimmunoassays were used for the
measurement of plasma insulin (Biermann) and leptin (DRG). The
area under the curve (AUC) was calculated for glucose and insulin
response during oral glucose tolerance test according to the trapezoidal rule. Plasma epinephrine and norepinephrine levels were
measured with HPLC with electrochemical detection as described
previously.16
Figure 1. RMR in nonobese and obese hypertensive subjects
without and with ␤-adrenergic blockade (mean⫾SEM).
trical impedance analysis (Akeru-RJL; BIA 101/S).12 After a 30minute resting period after the insertion of a venous cannula, blood
pressure was measured in the recumbent fasting subject over 1 hour
at 1-minute intervals with an automatic oscillometric device (Dinamap 1846SX; Criticon), and subsequently, blood samples were
collected for the measurements of glucose, insulin, epinephrine, and
norepinephrine. For the assessment of oral glucose tolerance, each
subject received an oral glucose load (75 g of glucose in 250 mL of
water), and blood samples were collected for insulin and glucose
Statistical Analysis
Statistical analysis was performed with the SPSS-PC⫹ software
package (SPSS Inc). Data are reported as mean⫾SD. Differences
and correlations were considered significant at P⬍0.05.
Baseline Characteristics and Blood Pressure in Nonobese and Obese Normotensive and Hypertensive Subjects
Nonobese
Parameter
F/M, %
Obese
Normotensive
(n⫽23)
Hypertensive
(n⫽31)
Normotensive
(n⫽27)
Hypertensive
(n⫽43)
57/43
68/32
78/22
58/42
Age, y
45.6⫾13.4
53.5⫾12.6
49.9⫾10.9
54.4⫾8.0
BMI, kg/m2
25.7⫾3.3
26.3⫾2.8
35.0⫾4.6
36.4⫾5.0
Body fat–free mass, %
74.8⫾7.9
70.0⫾7.4
63.7⫾7.0
64.5⫾7.1
Body fat mass, %
25.2⫾7.9
30.0⫾7.4
36.3⫾7.0
35.1⫾6.9
WHR, F
0.88⫾0.04
0.89⫾0.04
0.92⫾0.05
0.90⫾0.05
WHR, M
0.94⫾0.05
0.97⫾0.02
0.98⫾0.03
1.00⫾0.02
Resting measurements
Blood pressure, mm Hg
Heart rate, bpm
111/66⫾13/10
62⫾8
133†/74†⫾22/12
62⫾9
115/66⫾10/8
65⫾6
134†/75†⫾19/12
67⫾9
24-h ambulatory measurements
Daytime blood pressure, mm Hg
Daytime heart rate, bpm
Nighttime blood pressure, mm Hg
Nighttime heart rate, bpm
Fasting insulin, mU/L
Fasting glucose, mmol/L
127/81⫾11/8
81⫾7
116/70⫾12/10
129*/75⫾15/12
66⫾8
69⫾10
128/80⫾7/5
81⫾6
117/70⫾9/6
70⫾7
145†/91†⫾14/9
84⫾10
129*/77*⫾12/10
74⫾12
12.7 (4.2–26.5)
17.0 (4.4–42.4)*
17.1 (2.6–40.0)
21.3 (3.1–66.5)
5.4 (4.6–7.5)
5.4 (4.1–10.0)
5.5 (4.5–18.4)
5.8 (3.8–11.5)
Treated hypertensives, %
Thyroid hormones, %
146*/90*⫾17/12
79⫾8
68
4
WHR indicates waist-to-hip ratio.
*Pⱕ0.05, †Pⱕ0.0001 vs nonobese/obese normotensive subjects.
13
77
19
9
28
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July 2000
Figure 2. Relationship between RMR and FFM
(a) and FM (b) in normotensive and hypertensive male and female subjects.
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the Table. There were no significant differences in gender
distribution, BMI, and body composition between hypertensive and normotensive subjects. Hypertensive subjects
were slightly older and, as expected, revealed a significantly higher 24-hour ambulatory blood pressure. Because
resting blood pressure was measured under standardized
conditions over 60 minutes at complete rest, blood pressure levels in the hypertensive group, although significantly higher than in normotensive subjects, were within
the normotensive range.
Multiple stepwise regression analysis revealed significant effects of body fat–free mass (FFM), body fat mass
(FM), gender, and age on RMR. Together, these variables
accounted for 75% of the variation in RMR (Pⱕ0.0001;
公SE⫽586 kJ) (see equation at bottom of page). Univariate regression analysis revealed a significant relationship
between RMR and FM as well as FFM in both groups
(Figure 2).
There was no overall difference in RMR between
normotensive and hypertensive subjects (6651⫾1046 versus 6903⫾1302 kJ/24 h). However, in subjects with BMI
of ⬎30 kg/m2 RMR was significantly higher in hypertensive subjects (Figure 3). Furthermore, plasma epinephrine
and norepinephrine levels and the insulin response to an
oral glucose load were higher in the obese hypertensive
than in the obese normotensive subjects (Figure 3). In
nonobese subjects, fasting insulin levels were significantly
Differences between groups were tested for significance with
2-tailed Student‘s t test for independent samples or the nonparametric Mann-Whitney U test as appropriate. The ␹2 statistic was
used to detect differences in the distribution between men and
women, obese and nonobese subjects, and subjects with impaired
and normal glucose tolerance. Univariate and stepwise multiple
linear regression analyses were performed with RMR and basal
fat oxidation as dependent variables to explore their dependence
on gender, age, body weight, body composition, waist-to-hip
ratio, hypertension, impaired glucose tolerance, epinephrine,
norepinephrine, leptin, drugs, and thyroid hormones. Associations
between blood pressure, heart rate, and fat oxidation were
explored with Pearson correlation coefficients, after we established that the data were normally distributed.
Results
According to these criteria, 116 subjects were hypertensive
and 91 were obese. Of the hypertensive patients, 73% were
on antihypertensive medication, but multiple regression
analysis revealed no influence of diuretics, calcium channel blockers, and ACE inhibitors on RMR. However, in
obese patients under ␤-adrenergic blockade (n⫽42), RMR
was 12% lower than in patients without ␤-blockade
(6717⫾775 versus 7478⫾1292 kJ/24 h; Pⱕ0.05, Figure
1). Patients with ␤-blockade were therefore excluded from
further analyses. Although 12% of the subjects were on
thyroid hormone supplements, multiple regression analyses did not show an effect of this medication on RMR.
These patients were therefore included in the analyses.
Characteristics of the remaining subjects are presented in
RMR(kJ/24h)⫽4348⫹45.0⫻FFM⫹39.0⫻FM⫺882.1⫻gender (for female)⫺15.8⫻age
(⫾492)
(⫾6.7)
(Pⱕ0.0001) (Pⱕ0.0001)
(⫾5.8)
(Pⱕ0.0001)
(⫾180.6)
(⫾4.3)
(Pⱕ0.0001)
(Pⱕ0.0001)
Kunz et al
Energy Metabolism in Obesity Hypertension
29
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Figure 3. RMR, basal fat oxidation,
plasma catecholamines, AUC glucose,
and AUC insulin after glucose load and
plasma leptin in nonobese (n⫽23) and
obese (n⫽27) normotensive (open columns) and nonobese (n⫽31) and obese
(n⫽43) hypertensive (filled columns)
subjects (mean⫾SEM).
30
Hypertension
July 2000
Figure 4. Relationship between resting heart rate and basal fat
oxidation in obese normotensive and hypertensive subjects.
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higher in the hypertensive than in the normotensive group
(P⬍0.05), and AUC glucose (P⬍0.01) and AUC insulin
(P⫽0.07) also appeared higher in the hypertensive than in
the normotensive groups. Leptin levels appeared higher in
hypertensive compared with normotensive subjects in both
the obese and nonobese groups, but this difference
achieved statistical significance only in obese men (Figure
3). The RMR was not different between the nonobese
hypertensive and normotensive groups.
Neither relative nor absolute basal substrate oxidation
was significantly different between obese normotensives
and hypertensives (Figure 3). Stepwise multiple regression
analysis revealed FM, gender, and AUC glucose as independent determinants of basal fat oxidation (kJ/h), accounting for 40% of the variation (Pⱕ0.001; 公SE⫽28.2
kJ/h), whereas age, FM, catecholamines, leptin, blood
pressure, and hypertension had no significant effect. Although there was no relationship between blood pressure
and basal fat oxidation, resting heart rate was significantly
associated with basal fat oxidation in both obese normotensive (r⫽0.41, Pⱕ0.001) and obese hypertensive
(r⫽0.35, Pⱕ0.001) subjects (Figure 4).
Discussion
The main finding of the present study was that obese
hypertensive subjects have a small but significant increase
in RMR compared with age- and BMI-matched obese
normotensive control subjects. Furthermore, obese hypertensive patients have higher plasma catecholamine and
leptin levels and an increased insulin response to an oral
glucose load compared with obese normotensive subjects.
Although the association between obesity and hypertension is well recognized, the relationship between energy
metabolism and hypertension has not been widely studied.
In fact, we are aware of only 2 studies that specifically
investigated RMR in small groups of normotensive and
hypertensive subjects: 1 in obese Chinese normotensive
(n⫽10) and hypertensive (n⫽9) women17 and 1 in white
normotensive (n⫽7) and hypertensive (n⫽8) men.18 Both
studies found no difference in energy expenditure, but this
may have been due to the rather small number of probands
in these studies. Indirect findings on the relationship
between energy expenditure and hypertension are limited
to early reports that demonstrate a greater increase in
oxygen consumption during mental challenge, which was
associated with an increased response in heart rate in
patients with mild hypertension.19,20 These studies, however, provide no useful information regarding basal metabolic rates in these individuals.
Previous studies demonstrate that a large proportion of
variability in RMR is related to differences in body
composition.21 Despite the potential effect of increased
sympathetic activity on RMR, it is apparent that as in
normotensive individuals, RMR in hypertensive subjects
was predominantly determined by FFM, FM, gender, and
age. This is in line with previous findings that demonstrate
FFM alone accounts for 60% to 85% of variation in
RMR.21–23 Interestingly, the small but statistically significant effect of FM on RMR observed in the present study is
in line with the observation by Nelson et al,24 who have
previously shown that although the contribution of FM to
the variation of RMR is negligible in lean individuals, it
becomes more important with increased FM in obese
subjects. Nevertheless, despite this effect of FM, higher
RMR in obese subjects is mainly attributable to the higher
FFM present in obese individuals.25
Consistent with previous findings,26,27 hypertension was
associated with an increased insulin response to oral
glucose in obese individuals. Similarly, as in some,28,29 but
not all,30,31 studies, the obese hypertensive subjects tended
to have higher plasma norepinephrine levels than the
normotensive subjects. Previous investigators have suggested that insulin resistance in hypertensive patients may
be due in part to increased sympathetic activity,32,33 but
insulin has also been shown to increase sympathetic nerve
activity.34 More recent studies suggest that leptin may also
stimulate sympathetic outflow from the hypothalamus,
thereby contributing to increased heart rate and perhaps a
rise in blood pressure.35–37 This idea is in line with our
observation that plasma leptin levels were higher in obese
hypertensive men (P⬍0.05) and women (P⫽0.06) than in
the obese normotensive control subjects. Clearly, the role
of leptin in the development of obesity hypertension
deserves further exploration.
In the present study, basal fat oxidation and basal
substrate oxidation did not differ between obese hypertensive and normotensive individuals. This finding is in line
with the previous report by Natali et al,18 who found no
differences in the exchange of lipid substrates (free fatty
acids, glycerol, and ␤-hydroxybutyrate) in the forearm of
hypertensive and normotensive individuals. This comes as
a surprise, because higher insulin levels, secondary to
insulin resistance in hypertensives, may be expected to
inhibit fat oxidation.38 On the other hand, higher sympathetic activity in hypertensive subjects could counteract the
inhibitory effect of hyperinsulinemia, because catecholamines are known to stimulate fat oxidation.39 The idea
that increased sympathetic activity in hypertensive individuals is related to fat oxidation is also supported by the
Kunz et al
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presence of a positive correlation between resting heart
rate and basal fat oxidation in the present study.
The importance of increased sympathetic activity in the
maintenance of higher energy expenditure and thus counteracting an increase in body weight is also illustrated by
our observation of a significantly lower RMR in patients
on ␤-blockers. This is consistent with previous reports that
␤-adrenergic blockade affects energy expenditure by lowering RMR,40,41 as well as glucose-42 and diet-9 induced
thermogenesis. The clinical relevance of this effect is
apparent from several clinical trials, including the recent
United Kingdom Prospective Diabetes Study,43 in which
treatment with atenolol resulted in twice the weight gain
compared with that observed in patients on captopril.
Although this is the largest study to date on the
relationship between energy metabolism and hypertension,
some important study limitations must be considered.
Physical activity, an important determinant of lean body
mass and energy expenditure, was not assessed in our
study; it must, however, be noted that the impact of
physical training on RMR is still controversial.44 Furthermore, although not statistically significant, hypertensive
subjects were slightly older than normotensive subjects in
both groups. Thus, because RMR is known to decrease
with age,45 the difference in RMR between obese hypertensive and normotensive subjects may have been underestimated in the present study. On the other hand, hypertensive subjects were also slightly heavier in both groups.
It therefore cannot be ruled out that some of the difference
in RMR between the obese hypertensive and normotensive
individuals is attributable to this small difference in body
weight.
In summary, the present study demonstrates a significant, albeit marginal, increase in RMR in obese hypertensive patients. This finding is associated with higher plasma
catecholamine levels, a hyperinsulinemic response to an
oral glucose load, and higher leptin levels in these individuals. Together, these findings are compatible with the
idea that chronic neurogenic and metabolic adaptations
related to obesity may play a role in the development of
obesity hypertension in susceptible individuals.
Acknowledgments
The study was supported by the Bundesministerium für Bildung,
Wissenschaft, Forschung und Technologie (BMBF, 685.20). We
thank Brigitte Geue, Monika Hantschke-Brüggemann, Bärbel
Girresch, Lisa Wolf, and Klaus Schlotter for their excellent
technical help.
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Resting Metabolic Rate and Substrate Use in Obesity Hypertension
Iris Kunz, Ulrike Schorr, Susanne Klaus and Arya M. Sharma
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Hypertension. 2000;36:26-32
doi: 10.1161/01.HYP.36.1.26
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