Download Effect of obesity and regional adiposity on the QTc interval

International Journal of Obesity (1997) 21, 1104±1110
ß 1997 Stockton Press All rights reserved 0307±0565/97 $12.00
Effect of obesity and regional adiposity on the
QTc interval in women
J-J Park1 and PD Swan2
1
Department of Kinesiology, University of Maryland, MD, USA and 2 Department of Exercise Science and Physical Education,
Arizona State University, Tempe, AZ, USA
OBJECTIVES: To determine whether differences in body fat composition and body fat distribution patterns are
associated with a prolongation of the corrected QT interval for heart rate (QTc) on the electrocardiogram (EKG) during
rest and exercise.
DESIGN: Cross-sectional evaluation of the QTc interval in three groups of premenopausal women during rest and two
_ 2 max).
_ 2 max and VO
exercise conditions (50% VO
SUBJECTS: Thirty-one healthy women with a mean age of 35 y (27±44 y) were classi®ed as either obese (n ˆ 22;
percent body fat [%BF] > 30%) or nonobese (NO; n ˆ 9; %BF 27%) by hydrostatic weighing. Obese subjects matched
for age and %BF were grouped by waist to hip ratio (WHR) into two groups: upper body obesity (UBO; n ˆ 11;
WHR 0.85) and lower body obesity (LBO; n ˆ 11; WHR 0.75).
MEASUREMENTS: RR and QT intervals were measured in a double-blind design with the aid of calipers and
magnifying lens for seven consecutive beats in lead II from a 12-lead EKG at a paper speed of 25 mm/sec. Five
consecutive cardiac cycles excluding the longest and shortest RR and QT intervals were averaged and calculated for
QTc interval using Bazett's formula.
RESULTS: Mean QTc intervals were signi®cantly different (P < 0.001) across the groups for each condition. For all
conditions, UBO had the longest QTc interval as compared to LBO and NO respectively (i.e., Rest: 0.426; 0.413;
0.399 sec1/2; Mid50%: 0.447; 0.426; 0.409 sec1/2; Max: 0.390; 0.374; 0.357 sec1/2).
CONCLUSIONS: The QTc interval is positively associated with UBO even at the same level of body fat in moderately
obese women. It is clear that abdominal obesity may be one of the risk factors for a prolonged QTc interval in
premenopausal women.
Keywords: body fat distribution; electrocardiogram; exercise; waist±hip ratio
Introduction
Obesity has been implicated as a risk factor for sudden
cardiac death as well as cardiovascular morbidity and
mortality for several decades.1±4 In the Framingham
Heart Study, obesity was found to be a strong predictor of sudden cardiac death.1,3 A primary mechanism of sudden cardiac death in obesity has been shown
to be malignant ventricular arrhythmias (MVA),
which may relate to electrocardiogram (EKG)
abnormalities.2,5,6
Prolongation of the QT interval on the EKG,
represents delayed repolarization of the ventricular
myocardium and is considered a precursor of MVA
and sudden cardiac death in obesity.5,7±10 Prolongation
of the QT interval is the most important electrocardiographic abnormality found in obesity.11 Frank et al12
found that 28.3% of their obese outpatients had a mild
prolonged QT interval and 4% of them had a markedly prolonged QT interval. A prolonged QT interval
Correspondence: Pamela D Swan, Ph. D., FACSM, Department of
Exercise Science and Physical Education, Mail Code 870701,
Arizona State University, Tempe, AZ, 85287-0701, USA. E-mail:
[email protected]
Received 16 January 1997; revised 2 July 1997; accepted 21
July 1997
has also been found in obese patients on very low
calorie diets (VLCD) or after surgery for obesity.6,13
From these results, however, it is impossible to
distinguish whether obesity alone or other factors
associated with obesity (for example, VLCD, metabolic abnormalities etc.) increases the risk for prolongation of the QT interval.7,10
Since the duration of the QT interval is altered by
the length of the preceding cardiac cycle, an adjustment for differences in heart rate (QTc) has been
developed.9,14 The length of the QTc interval was
found to be exponentially related to the risk of
developing MVA in patients with QT prolongation.
In healthy obese subjects, El-Gamal et al15 reported
that prolongation of the QTc interval was signi®cantly
associated with relative body mass and fatness,
whereas Peiris et al,16 found no signi®cant association.
It has become increasingly evident that obesity is a
heterogeneous disorder. Body fat location, speci®cally
abdominal or visceral obesity, is a higher predictor of
cardiovascular and metabolic disease risk, than the
amount of body fat alone.17±19 In addition, abdominal
fat deposition has been suggested as an independent
risk factor for prolongation of the QTc interval.16
Peiris et al16 found that increasing intra-abdominal
deposition of fat was closely associated with prolon-
QTc interval and regional adiposity in women
J-J Park and PD Swan
gation of the QTc interval independent of obesity and
other cardiovascular risk factors. The data obtained
from these studies suggest that the risk for prolongation of the QTc interval in obesity, may be in¯uenced
by body fat distribution pattern (that is, abdominal vs
gluteal/femoral).
No previous studies have examined the relationship
between prolongation of the QTc interval and obesity
subtypes. In addition, most studies of prolonged QTc
syndromes have observed QTc intervals only during
rest. Nonetheless, exercise is commonly recommended for obese individuals. The effect of progressive exercise on the QTc interval is unknown.
Therefore, the purpose of this study was to determine
differences in the QTc intervals between three groups
of women with distinctly different body fat composition and body fat distribution patterns during rest and
exercise. It was hypothesized that the obese women
would have a prolongation of the QTc interval, as
compared to nonobese women, and that upper body
obese (UBO) women would show a larger prolongation of the QTc interval than lower body obese (LBO)
women during both rest and exercise.
Methods
metabolic risk in women with a WHR of > 0.85 and
average risk in women with a WHR of 0.75. By using
these `cutoff' values, it was possible to distinguish
distinctly different body fat distribution subgroups.
Anthropometry
Subjects were measured to the nearest 0.25 inch in
height and 0.25 lb in weight. These measures were
converted to metric units for BMI determination.
WHR was established by standardized procedures.23
Measurement sites were ascertained with the subject
assuming a standing position and then these points
were marked on the subject's skin for a subsequent
supine measurement. Standardized waist circumferences were determined at the narrowest point between
the ribs and hips from a posterior view. If it was
dif®cult to determine this point, the level of the
umbilicus was measured.23 Standardized hip circumferences were determined at the widest protrusion of
the buttocks from a side view of the subject. All
circumferences were measured with the subject
supine and wearing only undergarments. Measurements were performed twice to the nearest 0.1 cm
using a Gulick II tape measure which is nonstretchable and tension controlled. WHR was calculated as
waist circumference in centimeters divided by hip
circumference in centimeters.
Subjects
Obese and non obese (NO) premenopausal women,
aged 25±46 y, were recruited from the Metropolitan
Phoenix Area, surrounding Arizona State University,
Tempe, AZ. All women were sedentary (2 h per week
of planned exercise or physical activity) with no
evidence of current (within the last 6 months) participation in diet reduction programs.
All subjects were asked to complete a personal
health and medical history questionnaire, which
served as a screening tool and provided basic descriptive data.20 Subjects were screened by questionnaire
for any metabolic abnormalities or for any medication
use which has a cardiac effect. They were deemed
apparently healthy, as de®ned by the American College of Sports Medicine (ACSM) guidelines.21 After
being screened, each subject was informed of the
procedures and risks of the study, and signed an
informed consent, according to procedures established
by the University Human Subjects19 Research Review
Board.
Each screened subject was classi®ed as either obese
(percent body fat [%BF] > 30%) or nonobese
(%BF 27%) based on hydrostatic weighing. According to waist to hip circumference ratio (WHR), obese
subjects matched for age, body mass index (BMI) and
%BF were divided into an upper body obesity group
(UBO; WHR 0.85; n11) and a lower body obesity
group (LBO; WHO 0.75; n ˆ 11). Nonobese subjects were a control group (NO; n ˆ 9). WHR criteria
were based on Bray's22 nomogram that indicates high
Body composition
The simpli®ed oxygen dilution technique of Wilmore
et al24 was used to measure residual lung volume
using a Beckman O2 analyzer (Model OM-11, Fullerton, CA) and a Beckman CO2 analyzer (Model LB2) with ¯ow control (Model R-1). Prior to testing,
O2and CO2 analyzers were calibrated to register the
correct percentage of calibrated gas (certi®ed to the
nearest 0.01%) and ¯ow control was adjusted to
500 ml/min. Measurements of underwater weight consisted of 5±10 trials for each subject. Within each trial,
3±5 readings from the computer were obtained. Mean
underwater weight was calculated from the highest
values with the least variability from each trial. This
underwater weight was used to determine body density following the equation of Buskirk.25 Percent body
fat (% BF) was estimated using the formula of
Lohman et al26 developed for women.
Exercise testing
Pre-exercise testing. The protocol and sequence of
the tests were explained to all subjects. Each subject
was prepared for standard 12-lead electrocardiogram
(EKG) and rested in a darkened quiet room for 10 min.
Resting heart rate, blood pressure and 12-lead EKG
were taken in the supine, sitting and standing positions.
1105
QTc interval and regional adiposity in women
J-J Park and PD Swan
1106
Exercise testing. Each subject was instructed to
walk on the treadmill to determine a comfortable
walking speed for a 3 min warm-up. According to
individual walking speed, a walking protocol, with a
range of walking speeds of 2.5±3.7 mph, was selected.
Once the speed was selected, treadmill grade was
increased by 2% every 2 min. Arterial blood pressure
was measured by mercury sphygmomanometry every
2 min. Subjects were verbally encouraged to walk,
until they reached their volitional exhaustion. Metabolic measures were made using indirect calorimetry.
An AeroSport TEEM 100, portable indirect calorimeter (AeroSport, Ann Arbor, MI), was calibrated for
volume, using a 3 liter calibrated syringe, prior to use.
Gas analyzers were calibrated using certi®ed calibraÇ O2 max was
tion gases prior to exercise testing. V
Ç
attained when VO2 did not increase (> 150 ml/min)
despite increasing exercise work rate or if the respiratory exchange ratio (R) was greater than 1.12 and
heart rate was within 10 beats of age predicted
maximum.21
Electrocardiography
A standard 12-lead EKG was measured to monitor the
changes of the adjusted QT intervals for heart rate
(QTc interval) both at rest and during exercise using a
Quinton 4000 stress test monitor (Quinton Instrument
Co., Seattle, WA). For a standard 12-lead EKG
recording, electrode sites were prepared for a modi®ed
10-electrode placement.21 Skin on the chest was
abraded with ®ne-grain emery paper to remove epidermis and oil, and cleaned with an alcohol gauze
pad.21
A resting 12-lead EKG was recorded in a supine
position at a paper speed of 25 mm/sec. The RR and
QT intervals were measured from seven cardiac
cycles from a recording of lead II of the resting
EKG. During exercise, the EKG was continuously
monitored and recorded every min. Measurements of
exercise EKG parameters were made during maximal
exercise (Max) and at the time period that represented
50% of the maximal aerobic capacity (Mid50%).
All EKGs were coded and evaluated blindly, such
that the subject group was not known to the investigator. The same well trained non-physician researcher
read all the EKGs. The QT interval was measured
following the method described by Browne et al27
from the earliest onset of the QRS complex to the
terminal portion of the T wave, where it met the
baseline. The RR interval from the preceding cardiac
cycle was measured from the peaks of the R waves to
correct the QT interval for heart rate (QTc). The QT
and the preceding RR intervals were measured with
the aid of calipers and magnifying lens for seven
consecutive beats in lead II.11 To calculate QTc
interval, the mean value of ®ve consecutive beats,
excluding the longest and the shortest RR and QT
intervals, were used following the equation from
Bazett:28
QT
QTc ˆ p
RR
Statistical analysis
A 3 6 3 study design with one between-subject variable (treatment group) and one within-subject variable
(condition) was used. A two-way factorial ANOVA
with repeated measurement was used to analyze
differences between means. Signi®cant F ratios were
then followed with Newman-Keuls test. The Statistical Package for the Social Sciences (SPSS)29 was used
for all statistical analysis.
Results
The physical characteristics of subjects are shown in
Table 1. The mean age and height were similar in all
three groups; UBO, LBO and NO. Body weight, BMI
and %BF were matched between the two obese
groups, but were signi®cantly higher (P < 0.05) than
the NO group. WHR was signi®cantly higher ( < 0.05)
in UBO than LBO or NO groups. Maximal aerobic
Ç O2max) was signi®power relative to body weight (V
cantly higher (P < 0.05) in NO than the obese groups.
Mean RR intervals were not signi®cantly different
across groups for any condition; Rest, Mid50% and
Max. In all groups, the duration of the RR intervals
were signi®cantly shortened (data not shown) across
conditions paralleling the heart rate increase with
progressive exercise.
The group mean adjusted QT intervals for heart rate
(QTc intervals) were signi®cantly different (P < 0.05)
Table 1 The physical characteristics of subjects
Variable
Age (y)
BMI (kgm72)
% BF
WHR
_ 2max (mlkg71min71)
VO
UBO (n ˆ11)
LBO (n ˆ11)
NO (n ˆ 9)
34.64 6.01
30.46 5.45
38.15 5.62
0.87 0.04*
27.19 5.48
35.73 5.29
30.52 5.51
39.86 5.57
0.75 0.03
26.37 4.15
33.67 4.47
20.56 1.38*
24.59 4.87*
0.73 0.03
33.73 4.78*
Values are mean s.d. *Signi®cantly different from other groups, P < 0.001.
UBO ˆ upper body obesity; LBO ˆ lower body obesity; NO ˆ nonobese; BMI ˆ body mass
index; % BF ˆ percentage body fat; WHR ˆ waist-hip ratio.
QTc interval and regional adiposity in women
J-J Park and PD Swan
Table 2 The QTc intervals (sec1/2) across groups within condition
Condition
UBO (n ˆ11)
LBO (n ˆ11)
NO (n ˆ 9)
Rest
Mid50%
Max
0.426 0.009*
0.447 0.014*
0.390 0.014*
0.413 0.115*
0.426 0.123*
0.374 0.018*
0.399 0.020*
0.409 0.023*
0.357 0.019*
Values are mean s.d. *Signi®cantly different from other
groups, P < 0.05 (UBO > LBO > NO).
UBO ˆ upper body obesity; LBO ˆ lower body obesity;
_ 2max.
_ 2max; Max ˆ VO
NO ˆ nonobese; Mid50% ˆ 50% VO
for each condition (Table 2). Within each condition,
UBO had the longest QTc interval, NO had the
shortest and LBO had intermediate values. Figure 1
shows the changes in QTc intervals during rest and
exercise conditions. As seen from Figure 1, in the
obese groups, mean QTc intervals were signi®cantly
(P < 0.05) longer during Mid50%, but shorter during
Max. However, in the NO group, the change in the
QTc interval between Rest and Mid50% did not
achieve signi®cance.
A Pearson's correlation matrix29 to examine the
relationship between QTc interval and anthropometric
conditions is summarized in Table 3. There was a
signi®cant correlation (P < 0.001) between WHR and
QTc interval at all conditions. Body weight, BMI and
%BF were also signi®cantly correlated with QTc
interval at all conditions. A partial correlation
between WHR and QTc after adjusting for %BF
also indicated a signi®cant relationship between
WHR and QTc for all conditions (Table 4).
Table 3 Pearson's Correlation of QTc interval and selected
body composition parameters
Variable
Rest QTc
Mid50%
QTc
Max QTc
Weight (kg)
BMI (kgm72)
% BF
WHR
0.4757*
0.4717*
0.4975*
0.5248**
0.4168*
0.4367*
0.3789*
0.6111**
0.5890**
0.6335**
0.5551**
0.6101**
Values are correlation coef®cients. *Signi®cant correlation,
P < 0.05; ** Signi®cant correlation, P < 0.001.
_ 2max; BMI ˆ body mass
_ 2max; Max ˆ VO
Mid50% ˆ 50% VO
index; % BF ˆ percentage body fat; WHR ˆ waist-hip ratio.
Table 4 Partial Correlation of QTc interval and WHR after
adjusting for % BF
Variable
Rest QTc
Mid50% QTc
Max QTc
WHR
0.4154
P ˆ 0.02
0.5441
P ˆ 0.002
0.5158
P ˆ 0.004
Values are correlation coef®cients.
WHR ˆ waist-hip
ratio;
%
BF ˆ percentage
_ 2max.
_ 2max; Max ˆ VO
Mid50% ˆ 50% VO
body
fat;
Discussion
As anticipated, both obese groups (UBO and LBO)
had signi®cantly longer QTc intervals than NO at rest.
However, the duration of the QTc intervals of all
subjects were normal considering that the generally
accepted upper limit of normal for QTc interval is
0.44 sec1=2 .11,29 There were signi®cant relationships
between the QTc interval, body weight, %BF and
Figure 1 Changes of the QTc interval across condition. *Signi®cantly different, P < 0.05, Rest vs Mid50% and Max. **Signi®cantly
different, P < 0.05, Mid50% vs Max. ***Signi®cantly different, P < 0.05, Max vs Rest and Mid50%. UBO ˆ Upper body obesity.
_ 2max
_ 2max. Max ˆ VO
LBO ˆ Lower body obesity. NO ˆ Nonobese. Mid50% ˆ 50% VO
1107
QTc interval and regional adiposity in women
J-J Park and PD Swan
1108
BMI. These ®ndings con®rm previous studies of the
QTc interval in obesity.12,16 Frank et al12 found a low
but statistically signi®cant relationship (r ˆ 0.22,
P < 0.001) between percent overweight and QTc
interval in obese patients without cardioactive medications. In addition, El-Gamal et al15 recently found
signi®cant correlations between QTc intervals and
both BMI (r ˆ 0.31, P ˆ 0.0002) and %BF (r ˆ 0.25,
P ˆ 0.003) in healthy obese people. In contrast to
these studies, Peiris et al16 reported no association
between obesity and QTc interval in healthy premenopausal women. However, the subjects in Peiris's
study were all signi®cantly obese and very similar in
%BF (Mean s.d. ˆ 42.0 0.9%). Perhaps the homogeneity in body fat between subjects may have
masked any correlations with QTc in this population.
Results from the current study, clearly indicate that
excess fatness, in healthy premenopausal women, is
associated with a longer QTc interval at rest, compared to lean women.
Body fat distribution patterning also had a signi®cant effect on the length of the QTc intervals at rest.
The QTc interval was signi®cantly greater in UBO
than LBO even though age, body weight, BMI and
%BF were matched between groups. Signi®cant correlations (r ˆ 0.52; P < 0.001) were observed between
the QTc interval and the WHR. In addition, the partial
correlation between WHR and QTc after adjusting for
%BF was also signi®cant at all conditions. These
®ndings support those of Peiris et al16 who found a
signi®cant linear association (r ˆ 0.54, P < 0.05)
between the QTc interval and intra-abdominal deposition of fat as measured by computerized tomography
(CT) in healthy premenopausal obese women. These
data indicate that increasing abdominal adiposity is
accompanied by prolonged QTc interval in obese
people even after adjusting for fatness. Thus, although
obesity is associated with a prolonged QTc interval,
UBO may be a higher risk for potential EKG abnormalities.
During exercise, the associations between the QTc
interval and body fat distribution patterns were maintained. For each condition, the obese groups (UBO
and LBO) had longer QTc intervals than NO and the
UBO had longer values than LBO. The results indicated no interaction between exercise condition and
group on the QTc interval. However, there were
signi®cant effects of exercise condition on the QTc
interval. For all groups, the RR and QT intervals
progressively shortened during exercise in response
to the increase in heart rate that accompanies
increased physical work. According to the ACSM21
description of normal electrocardiographic response to
exercise, these intervals should normally shorten with
an increase in exercise intensity. However, the intervals did not shorten proportionally. At Mid50%, the
proportional decrease in RR interval was greater than
that for the QT interval. Thus, the QTc interval which
is calculated from the ratio of QT to RR, actually
increased slightly compared to resting values.
The reason for this surprising increase in the QTc
interval may be due to an uncoupling between heart
rate and the oxygen requirements at this intensity.
Work intensity at Mid50% was based on 50% of
Ç O2max) and not 50% of
maximal aerobic power (V
maximal heart rate. Thus, the heart rate response at
this work rate represented approximately 75% of the
maximal heart rate. Any uncoupling or unproportional
shortening of the heart rate in comparison to the
repolarization wave (i.e., QT interval) would alter
the QTc interval. At Mid exercise, the greater proportional change in heart rate as compared to the QT
interval shortening, resulted in a slight increase in
QTc interval. This ®nding suggests that the QTc
interval is responsive to the absolute heart rate at
any submaximal intensity of work.
The precise mechanisms of the prolonged QTc
interval in obesity are unknown. However, obesity
and UBO have been documented to be independent
risk factors for coronary heart disease (CHD), which
may induce prolongation of the QTc interval.7 Possible mechanisms of the prolonged QTc interval in
obesity include cardiac autonomic nervous system
dysfunction, electrolyte abnormalities, left ventricular hypertrophy (LVH), hyperinsulinemia and
CHD.5,7,12,30±33
Obesity and UBO have been associated with autonomic nervous system dysfunction34,35 which may
result in prolongation of the QTc interval.5,7,27,30,31
An imbalance in cardiac sympathetic enervation has
been shown to prolong the QTc interval in men and
women.30 Gao et al,34 found that women with UBO
had signi®cantly higher cardiac sympathetic and parasympathetic activity than those with LBO. They
compared autonomic function by power spectral analysis in women with subcutaneous vs visceral abdominal body fat as assessed by CT. Signi®cantly higher
autonomic nerve frequencies were reported for the
women with predominantly visceral body fat. Browne
et al,27 who investigated prolonged QTc intervals in
patients with ventricular arrhythmia during sleep,
demonstrated that increased parasympathetic activity
may result in prolongation of the QTc interval. Kahn
et al,31 reported that cardiac autonomic neuropathy
may result in sympathetic imbalance and QTc interval
prolongation. Furthermore, El-Gamal et al15 suggested that an elevated cardiac output in obesity,
due to an increased stroke volume and overall greater
body mass, may contribute to alter autonomic nervous
system balance. It is possible that some unknown
dysfunction in autonomic nervous system balance
could have in¯uenced the ®ndings of increased QTc
interval in this study.
Another possible mechanism contributing to prolongation of the QTc interval in obesity and UBO may
be electrolyte abnormalities. High levels of cytosolic
free calcium and low levels of free magnesium have
been found in even healthy obese individuals.36 Phinney et al,32 found that chronic oral magnesium supplementation signi®cantly shortened the QTc intervals
QTc interval and regional adiposity in women
J-J Park and PD Swan
in obese patients with dietary-induced (VLCD) prolonged QTc interval. In the current study, electrolyte
balance was not measured. However, the dietary
habits of the women were not signi®cantly different
between the groups. It is possible, however, that the
UBO group had electrolyte abnormalities that were
not accounted for in this study.
Electrolyte abnormalities are also known to cause
increased heart muscle contractility, increased vasoconstriction and may predispose one to LVH.33 In
nonhypertensive obese individuals, LVH of the
eccentric type, which is an increase in myocardial
mass combined with chamber dilation, is considered a
primary risk factor for ventricular arrhythmias.2,12 In
their investigation of sudden death in obesity, Messerli et al2 suggested that the hypertrophied myocardium in obesity may induce ventricular arrhythmias.
Indeed, it is recommended that the QTc interval must
be monitored if LVH is found.12 In the current study,
no women had electrocardiographic evidence of LVH.
However, since echocardiographic measures of LVH
were not made, it is possible that the UBO group had
some evidence of LVH.
Results from this study suggest that UBO may be
a higher risk factor for prolonged QTc interval
than obesity alone. In addition, it is well known
that UBO is associated with the group of risk factors
called the metabolic syndrome.37 The increased
portal free fatty acid (FFA), hyperinsulinemia and
insulin resistance in UBO are closely aligned with
CHD.38±40 Abraham et al 41 reported that increased
plasma FFA levels in patients with acute myocardial
infarction, had signi®cant effects on ventricular
arrhythmias. Peiris et al16 also suggested that
hyperinsulinemia and insulin resistance of abdominal
obesity may induce cardiovascular disease and may
play a role in prolonged QTc interval. Recently,
Dekker et al 42 found that the QTc interval was
signi®cantly longer in elderly men with glucose intolerance and newly diagnosed diabetes, compared to
men with normal carbohydrate metabolism. The
authors suggest that the observed association might
be evidence that insulin-induced sympathetic activity,
may precipitate myocardial repolarization abnormalities and/or that disturbed glucose metabolism may
alter ion exchange at the myocardium, which may also
manifest in QTc prolongation. Thus, any factor associated with the development of CHD such as diabetes
or hyperinsulinemia would obviously effect cardiac
function. The increased QTc intervals noted in this
study may be evidence of an initial development of
some undiagnosed factor associated with the metabolic syndrome. Further research into the association
of UBO with diabetes, hyperinsulinemia and CHD is
warranted.
Exercise induced a shortening of the QTc interval
in all the healthy women evaluated in this study.
However, group differences in the duration of the
QTc interval persisted throughout exercise condition.
Despite the common practice of recommending exer-
cise for overweight individuals, research about EKG
abnormalities, during exercise in obesity, is rare.
Sudden death in an obese patient with a prolonged
QTc interval during exercise has been reported.31
Thus, it seems important to carefully monitor the
QTc interval especially in UBO individuals during
exercise. It remains to be shown, however, what value
of the QTc interval during exercise would be deemed
critical. In addition, it is unknown why the QTc
interval is prolonged in UBO individuals and what
effects exercise training would have on this EKG
index.
In conclusion, this study demonstrated that prolongation of the QTc interval is associated with increased
body fatness and increased abdominal fat distribution
even at the same level of body fatness. It is clear that
abdominal obesity may be one of the risk factors for
prolongation of the QTc interval in otherwise healthy
premenopausal women.
Acknowledgements
The authors wish to thank Ms Mary Boynton, MS for
her help and collaboration in all aspects of this
project. Also we would like to acknowledge the
Arizona State University Women's Studies program
for partial funding of this project.
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