508
Body Fat and Its Distribution in Relation to
Casual and Ambulatory Blood Pressure
Linda M. Gerber, Peter L. Schnall, and Thomas G. Pickering
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This study was undertaken to evaluate the associations of body fat and its distribution with
casual and ambulatory blood pressure in nonobese men. One hundred and thirty-five
normotensive or mildly hypertensive (but untreated) men employed at three work sites were
studied. Casual blood pressure was measured at the work site at initial screening and on a
second occasion by a nurse. Ambulatory blood pressure was measured noninvasively for 24
hours on a workday and analyzed as work, home, and sleep blood pressure measurements.
Anthropometric measurements included height, weight, and waist and hip circumferences.
Blood pressure was highest while at work; home blood pressure was higher than screening
blood pressure or nurse blood pressure, and sleep blood pressure was lowest. Weight and both
waist and hip circumferences (but not their ratio) were all significantly correlated with
screening, nurse, and sleep blood pressures but not with work or home blood pressures.
Stepwise regression analysis showed that waist circumference was the best overall predictor of
blood pressure. We suggest that in situations where blood pressure is the dependent variable,
correlations with other variables may be closest for "basal" measures of blood pressure and may
be obscured by the effects of daily activities on blood pressure. (Hypertension 1990;15:508-513)
O
besity has been shown to be positively
related to essential hypertension.1-4 Considerable evidence also exists to support an
association between the distribution of body fat and
blood pressure. Measures of centrally located or
upper body fat predominance have been shown to be
positively related to levels of both systolic and diastolic blood pressure.5"11 Few studies, however, have
examined the parameters of weight, body fat distribution, and blood pressure together, especially in a
nonobese population.
Hypertension and blood pressure level in general
have methodological problems in measurement.
Blood pressure is influenced by the instrument and
the individual taking the measure, the subject's physical activity and behavior, and the location and setting
in which the blood pressure is obtained.12-14 Ambulatory blood pressure monitoring offers an alternative
measurement to casual blood pressure. Ambulatory
From the Department of Medicine, Cardiovascular Center, The
New York Hospital-Cornell University Medical College, New
York, New York.
Supported in part by grant HL-30605 from the National Heart,
Lung, and Blood Institute.
Presented in part at the 58th Annual Meeting of the American
Association of Physical Anthropologists in San Diego, California,
April 6-8, 1989.
Address for correspondence: Linda M. Gerber, PhD, Cardiovascular Center, The New York Hospital-Cornell University Medical College, 525 East 68th Street, Starr-4, New York, NY 10021.
Received September 7, 1989; accepted in revised form January
22, 1990.
monitoring has been reported to be more reliable
because of the absence of observer error, the
increased number of readings, and the ability to
measure blood pressure during usual activities of the
subject.1516 There are no published data, however, on
the relation between ambulatory blood pressure and
indexes of overall obesity and fat distribution.
The present study examines the relation of measures of body mass and fat distribution with two
measures of casual blood pressure and three of ambulatory blood pressure in a nonobese male population.
Methods
Subjects were participants in a case-control study
of working men employed at eight New York City
work sites. These subjects are part of a study evaluating the effects of exposure to psychosocial, biological, and anthropometric factors on casual and ambulatory blood pressure.
After comprehensive screening of 3,223 male
employees, all eligible research subjects with screening diastolic blood pressure more than 85 mm Hg and
a random sample (one in eight) of eligible research
subjects with screening diastolic blood pressure 85
mm Hg or less were studied. Of 1,466 eligible subjects, 288 were recruited into the study. One hundred
thirty-five subjects at the last three sites had weight,
height, and waist and hip circumferences measured
and constitute the sample for this study. After the
research protocol and all attendant risks were
Gerber et al
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reviewed, informed consent was obtained from each
participant at the time of recruitment.
To be included in the study, subjects had to be
between 30 and 60 years of age, employed more than
30 hours per week for at least 3 years in their current
job before the onset of high blood pressure, educated
in the United States and able to read English, have a
body mass index not greater than 30% above ideal,
and have no second job of 15 or more hours per
week. Subjects were excluded if they had a history of
cardiovascular disease or systolic blood pressure
greater than 160 mm Hg or diastolic blood pressure
greater than 105 mm Hg at screening.
Casual screening blood pressures were determined
at the worksite on a workday for all 3,223 men. Blood
pressure was measured by trained nurses and technicians using a standardized protocol based on
American Heart Association criteria. Three blood
pressure measurements were taken in a sitting position, and the average of the last two was used as the
estimate of blood pressure. For all subjects, a standard size blood pressure cuff was used in determining
blood pressure.
Using the American Heart Association protocol as
described above, a second set of blood pressure
measurements was taken by a nurse-practitioner at
the work site, usually within 4 weeks of the screening,
either in a room in a medical clinic or in office space
converted into an examining room.
Subjects then wore a Spacelabs 5200 ambulatory
blood pressure monitor (Hillsboro, Oregon) for 24
hours beginning at the start of a work day. The
monitor was attached at the subject's work site and
calibrated by comparison of five successive systolic
and diastolic readings against simultaneously determined casual readings taken with a mercury column
in which each had to be within 5 mm Hg to be
acceptable. The timer on the monitor was set to take
readings at 15-minute intervals during the day and at
30-minute intervals during the hours of sleep, and
the subject was instructed to proceed through a
normal workday. Each time the monitor took a
reading during waking hours, the subject was asked
to remain as motionless as possible and then to
record his activity, location, position, and mood in a
diary. Averages could then be calculated for work,
home, and sleep blood pressure measurements. Subjects taking medication for hypertension (n=10) were
titrated off treatment under medical supervision and
wore the ambulatory monitor after all medication
was stopped for 3 weeks.
Body mass index was calculated according to the
formula weight (kg)/height (m)2.
Waist and hip circumferences were measured by
one observer using a steel tape. While the subject was
standing, the waist was measured at its minimum
with the abdomen relaxed and the tape held behind
the subject with one edge in the horizontal plane
through the center of the umbilicus. The tape was
then wrapped carefully around the patient's torso
and used as an aid in marking the horizontal plane on
Body Fat Distribution and Blood Pressure
. 509
TABLE 1. Characteristics of Study Population
Characteristic
Age (yr)
Weight (kg)
Height (cm)
Body mass index (kg/m2)
Waist circumference (cm)
Hip circumference (cm)
Waist/hip ratio
n
135
135
135
135
135
135
135
Mean±SD
43.2±8.9
80.5 ±11.4
176.2+6.6
25.9+3.0
89.5+9.0
90.4±8.5
0.99 ±0.03
Range
30-60
53.6-109.1
161.3-191.8
18.8-33.4
68.0-108.0
68.0-111.0
0.85-1.08
the sides and back. The hip circumference was
measured at its maximum, with the tape held at the
top of the patient's hipbone and then wrapped
carefully around the torso.17
A measure of physical exertion was derived from
an item on a self-reported questionnaire. The item,
scored from 1 through 4, from strongly disagree to
strongly agree, was "My job requires lots of physical
effort."
Pairwise correlation coefficients were calculated
for all independent variables with each other and
with the different blood pressure measures. Multiple
linear regression analyses were performed using a
stepwise variable selection procedure. Two-tailed
probability levels for statistical significance tests are
reported.
Because three different worksites were included in
the analysis, site was examined as a potential confounding variable. Regression analyses were performed with and without site as an independent
variable. As site did not alter the results, the findings
are presented without site.
Results
Table 1 describes the characteristics of the study
population. The men were between 30 and 60 years
old with a mean age of approximately 43 years. The
mean body mass index was 26, equivalent to roughly
the 50th percentile for the US population. Mean
waist and hip circumferences were very similar
resulting in a mean waist/hip ratio close to 1.
Ambulatory, screening, and nurse blood pressure
measurements of the study population are presented
in Table 2. Of note is the finding that mean ambulatory work blood pressures were the highest, followed
by home, and then by sleep blood pressures. This is
the case for both systolic and diastolic blood pressures. Mean screening and nurse blood pressure
measurements were substantially lower than either
work or home ambulatory blood pressures. In addition, the nurse systolic blood pressure measurement
was even lower than the screening blood pressure,
although for diastolic blood pressure the two were
very similar.
The correlation coefficients between the anthropometric variables, age, and physical exertion and
ambulatory, screening, and nurse systolic and diastolic blood pressure measurements are shown in
Table 3. Age was consistently and significantly
510
Hypertension
Vol 15, No 5, May 1990
TABLE 2. Ambulatory, Screening, and Nurse Blood Pressure of
Study Population
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Mean+SD
n
Measurements
Ambulatory blood pressure (mm Hg)
Systolic
130.1±10.9
Work
135
Home
135
125.4+11.0
110.5±11.6
125
Sleep
Diastolic
85.1±9.0
135
Work
80.6±9.4
135
Home
68.4±9.4
125
Sleep
(mm Hg)
Screening blood pressure
135
122.6±12.8
Systolic
78.0±8.4
Diastolic
135 "
Nurse blood pressure (mm Hg)
135
116.8+13.3
Systolic
78.5 ±9.1
135
Diastolic
Range
107.4-166.0
103.3-172.1
81.0-148.1
69.4-109.5
61.8-114.9
52.4-96.2
96.0-157.0
49.0-98.0
91.0-164.0
61.0-104.0
related to all measures of blood pressure except sleep
systolic pressure. The anthropometric variables, on
the other hand, did not show as straightforward a
pattern.
Among measures of ambulatory systolic blood
pressure, sleep blood pressure had the strongest
correlation with anthropometric parameters. Weight,
height, and waist and hip circumferences all had
significant correlations with sleep systolic blood pressure and weaker associations with work and home
blood pressure measurements. For the most part,
these anthropometric variables, except for height,
were even more strongly related to nurse and screening blood pressure measurements when compared
with sleep blood pressure; nurse blood pressure had
the strongest relation. Physical exertion was not
significantly related to any systolic blood pressure
measure.
With diastolic ambulatory blood pressure, age again
had the most consistent correlation across all measures. However, physical exertion had a stronger and
negative correlation with work and home blood pres-
sure measurements. Sleep blood pressure was also
significantly and negatively associated with physical
exertion, whereas no relation existed between physical
exertion and screening and nurse blood pressure.
Among ambulatory diastolic pressures, all relations
with anthropometric variables were strongest for sleep
blood pressures. Of these, only waist and hip circumferences reached significance. As with systolic blood
pressure, the correlations between diastolic blood
pressure and anthropometric variables were more
often significant and greater for the nurse and the
screening blood pressures than the ambulatory measures. Again, the nurse blood pressure had even
stronger relations than the screening blood pressure.
As expected, among the anthropometric variables,
there were many significant associations (Table 4).
Weight and height and waist, hip, and body mass
index were all significantly correlated. Height was
also significantly related to waist and hip circumferences. Waist, in addition, had very high correlation
coefficients with weight (r=0.87), hip (r=0.94), and
body mass index (r=0.83).
A multivariate procedure was used to quantify the
relative contribution of each variable to blood pressure level when examined in the presence of the
others. The six anthropometric variables, age, and
physical exertion were analyzed with a stepwise multiple regression model.
The results for ambulatory systolic and diastolic
blood pressure are included in Table 5. For both
work and home blood pressures, only age was found
to be significantly predictive. The percent of variance
accounted for by age was approximately 8 and 6% for
work and home, respectively. Waist circumference
was found to be predictive of sleep blood pressure,
explaining 7% of the variance.
For ambulatory diastolic blood pressure, physical
exertion and waist circumference and physical exertion and age were significant contributors to the
fraction of the explained variance for work and home
blood pressures, respectively. Sleep diastolic blood
pressure was dependent in a first step on age, in a
second step on physical exertion, and in a third step
TABLE 3. Correlation Coefficients Between Anthropometric Variables, Age, and Physical Exertion, and Ambulatory, Screening, and Nurse
Blood Pressure
Variable
Weight
Height
Body mass index
Waist circumference
Hip circumference
Waist/hip ratio
Age
Physical exertion
*p<0.05.
Systolic blood pressure
Ambulatory
Screening
Work
Home
Sleep
0.12
0.24*
0.17
0.24"
0.17
0.13
0.17
0.24'
0.03
0.17
0.13
0.14
0.12
0.16
0.26'
0.29t
0.14
0.08
0.22'
0.30t
0.02
0.10
0.14
0.18
0.24*
0.19
0.41f
0.28t
-0.02
-0.14
-0.11
-0.01
Nurse
0.32t
0.13
0.28t
0.37t
0.36t
0.12
0.38t
0.01
Diastolic blood pressure
Ambulatory
Work
Sleep
Screening
Home
0.14
0.11
0.20
0.23*
0.03
0.02
0.06
0.02
0.15
0.11
0.19
0.27t
0.25*
0.16
0.12
0.32t
0.14
0.01
0.21*
0.32t
0.10
0.10
0.13
0.09
0.21*
0.23*
0.21*
0.29f
-0.24*
-0.01
-0.42+
-0.36t
Nurse
0.3 It
0.06
0.33t
0.40t
0.36t
0.18
0.30t
0.03
Gerber et al
TABLE 4.
Body Fat Distribution and Blood Pressure
511
Intrasubject Correlations of Anthropometric Measurements and Age
Correlation coefficients
Variable
Weight
Weight
Height
BMI
Waist
Hip
1.00
0.56*
1.00
0.84*
0.87*
0.03
1.00
0.35*
0.83*
1.00
0.86*
0.38*
0.78*
0.94*
Height
BMI
Waist
Hip
Waist/hip ratio
Age
1.00
Waist/hip
ratio
0.20t
0.00
0.27*
0.36*
0.02
1.00
Age
0.14
0.14
0.08
0.30'
0.28*
0.12
1.00
BMI, body mass index.
*p<0.01.
tp<0.05.
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on waist circumference. The addition of waist circumference to work blood pressure contributed
nearly 5% to the explained variance. Waist circumference contributed to explaining an additional 4%
to sleep blood pressure variance.
Table 6 shows the results of regression analysis of
screening and nurse blood pressure. Systolic blood
pressure was dependent in a first step on age and in
a second step on hip circumference. Both weight and
waist circumference were significant after adjusting
for age and could have been substituted for hip
circumference. Age and hip circumference together
explained nearly 22% of the variation of screening
systolic blood pressure. Age and waist circumference
contributed significantly to predicting nurse systolic
blood pressure.
With diastolic blood pressure, waist circumference
was the only variable to significantly predict screenTABLE 5. Stepwise Multiple Regression Analysis of Ambulatory
Systolic and Diastolic Blood Pressure
Dependent variable
Multiple R
r2
TABLE 6. Stepwise Multiple Regression Analysis of Screening and
Nurse Systolic and Diastolic Blood Pressure
Wnrt
wurK
Sleep
Step 1: waist
Diastolic blood pressure
Work
Step 1: physical exertion
Step 2: waist
Home
Step 1: physical exertion
Step 2: age
Sleep
Step 1: age
Step 2: physical exertion
Step 3: waist
Discussion
These results suggest that, in nonobese hypertensive and normotensive men, the relation of measures
of body fat and distribution to level of blood pressure
varies depending on the measure of blood pressure
examined. The anthropometric variables were all
highly intercorrelated as well as highly correlated
with age and were also significantly correlated with
measures of ambulatory, screening, and nurse blood
pressures. The strongest relations among ambulatory
systolic and diastolic measures were found between
sleep blood pressure and waist and hip circumferences. Screening and nurse systolic and diastolic
blood pressure measurements had even higher correlation coefficients with waist and hip circumferences than sleep blood pressures. In addition, weight
t
Systolic blood pressure
Step 1: age
Home
Step 1: age
ing blood pressure. Waist circumference and age
both contributed significantly to predicting nurse
diastolic blood pressures.
0.281
0.249
0.257
0.079
0.062
0.066
0.001
0.004
0.004
0.379
0.433
0.143
0.188
0.000
0.009
0.420
0.454
0.176
0.206
0.000
0.030
0.288
0.353
0.404
0.083
0.125
0.163
0.001
0.018
0.021
Independent variables included were age, weight, height, body
mass index, waist and hip circumferences, waist/hip ratio, and
physical exertion.
Multiple R
r2
(
0.420
0.463
0.176
0.215
0.000
0.013
0.384
0.470
0.147
0.220
0.000
0.001
Step 1: waist
0.335
0.113
0.000
Nurse
Step 1: waist
Step 2: age
0.405
0.441
0.167
0.194
0.000
0.029
Dependent variable
Systolic blood pressure
Screening
Step 1: age
Step 2: hip*
Nurse
Step 1: age
Step 2: waist
Diastolic blood pressure
Screening
Independent variables included were age; weight, height, body
mass index, waist and hip icircumferences, waist/hip ratio, and
Dhvsical exertion.
'Weight («=0.02) and waist (r=0.03) were significant after
adjusting for age but did not enter into the equation after hip was
added.
512
Hypertension
Vol 15, No 5, May 1990
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was significantly related to both systolic and diastolic
screening and nurse blood pressure measurements.
Stepwise regression analyses showed that the
anthropometric variables best predicted, of all the
blood pressure measurements, ambulatory sleep,
screening, and nurse blood pressures. For sleep
blood pressures, waist circumference for systolic and
diastolic blood pressures contributed significantly to
the fraction of explained variance. The anthropometric parameters found to be predictive of screening
systolic blood pressure level included waist circumference, hip circumference, and weight, whereas only
waist circumference predicted screening diastolic
blood pressure. Waist circumference contributed significantly to predicting both nurse systolic and diastolic blood pressures.
One caveat that should be kept in mind is that many
of the anthropometric measures were highly correlated with each other (e.g., waist and hip circumferences, r=0.94), which created a problem of multicollinearity in the database. As a consequence, in many
of the stepwise regression analyses, hip circumference
was virtually indistinguishable from waist circumference in its relation to blood pressure, and weight and
body mass index lagged only slightly behind.
Two important conclusions emerge from our findings. First, although there was a strong relation
between waist circumference and many measures of
blood pressure, a relatively weak relation between
the waist/hip ratio and blood pressure measures was
observed. The former finding was not unexpected;
the second, however, was.
Results from the Framingham study report a correlation coefficient of 0.27 between waist circumference and systolic blood pressure among men, the
strongest relation among all the indexes of obesity
examined.18 Berglund et al19 also found a significant
relation between waist circumference and mean arterial pressure among men. In this study also, blood
pressure was found to be more highly correlated to
waist circumference than to body weight.19 The present study confirms these observations and extends
their validity as waist circumference was found to be
strongly related to ambulatory as well as screening
and nurse blood pressures.
The weak relation between the waist/hip ratio and
blood pressure measures observed in this study was
not expected. Larsson et al20 reported that as the
waist/hip ratio increased, so did levels of both systolic
and diastolic blood pressure. Although hip circumference was not directly measured in the 1960-1962
Health Examination Survey, Gillum11 derived an
index of fat distribution computed as waist circumference divided by the estimated hip circumference.
Systolic and diastolic blood pressures were both
found to be significantly correlated with this fat
distribution index.
The waist and hip circumferences reported for
Swedish men were 86.0 and 93.7 cm, respectively.
The mean waist/hip ratio was 0.93 cm with a range
from 0.75 to 1.10 cm.20 Although hip circumference
data among Framingham residents were not obtained, the mean waist circumference among men
was reported to be 91.5 cm.18 In the present study,
the mean waist circumference of 89.5 cm falls
between the results of the Swedish and Framingham
studies. The mean hip circumference is much closer
to the mean waist circumference in the current study
compared with that in Sweden, and as a result, the
mean waist/hip ratio is much closer to 1.0. In addition, the range and standard deviation of the ratio in
the current study is smaller, possibly contributing to
reducing the correlations with blood pressure compared with other studies.
Nevertheless, the mean waist and hip circumferences in the present study had ranges in values
similar to the Swedish study. The associations of
waist and hip circumferences to blood pressure measures were also strong and comparable to those in the
Swedish study. It may be that the waist/hip ratio is
just not as important in relation to blood pressure in
this sample.
Second, within our database, nurse, screening, and
sleep blood pressures were all better correlated with
body fat and distribution measures than were ambulatory work and home blood pressures. This result
was somewhat surprising as, for several reasons,
ambulatory blood pressure measurement had been
considered superior to casual blood pressure measurement in reliability15 and in its association with
several measures of target organ damage.21-27 However, it is possible that the more variable blood
pressure occurring during daily activities while at
work and at home obscured the relation between
anthropometric variables and blood pressure in the
present study. The situations that gave the best
correlations (ambulatory sleep, nurse, and screening
blood pressures) were all circumstances in which
daily activities were either eliminated or highly controlled. On the assumption that physical activity at
work and at home might confound the weightambulatory blood pressure relation, a measure of
physical exertion was entered into our regression
model. Although physical exertion was highly correlated with ambulatory diastolic blood pressures, it
was not correlated with the anthropometric measures, and when entered into the regression analyses,
did not substantially alter the findings. Given the
subjective nature of this measure of activity, it is
possible that other more objective measures may
remain as potential confounders.
Our findings of the higher correlations of anthropometric measures with nurse, screening, and ambulatory sleep blood pressures may be interpreted as
the consequence of the fact that body mass and
distribution directly influence basal blood pressure,
whereas work and home ambulatory blood pressures
are additionally influenced by both activity and psychosocial factors.
It is noteworthy that generally similar correlations
were obtained with these three measures of basal
pressure, which were taken on three separate occa-
Gerberetal
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sions. Although these findings may at first appear to
be in conflict with the studies showing that daytime
or 24-hour ambulatory blood pressure measures correlate better with target organ damage, there are two
important differences in the present study. First, in
the case of target organ damage, it is assumed to be
the prevailing level of blood pressure that is the
independent variable, whereas in the case of the
anthropometric measurements, blood pressure is
assumed to be the dependent variable, so that the
daytime fluctuations of pressure may be merely adding "noise" to the measure of blood pressure. Second, our measures of casual pressure are different
from the conventional measures of clinic pressure
made by a physician in his office. The closest correlations with anthropometric measurements were
obtained with the nurse blood pressure measurements, which were made in relaxed circumstances at
the work sites and which were lower than both the
daytime ambulatory blood pressure and the screening blood pressure measurements. Numerous studies
have shown that physician-measured clinic blood
pressures are consistently higher than daytime ambulatory blood pressures.15 The reason for this difference may be the "white coat" effect provoked by a
physician, which varies in extent from one patient to
another, hence explaining the generally poor correlation between clinic pressure and blood pressurerelated variables. At the very least, our findings
suggest a need for researchers to include varying
methods of measuring both body mass and distribution as well as different measures of blood pressure
depending on the independent variable of interest.
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KEY WORDS: • blood pressure • ambulatory blood pressure •
body fat • body fat distribution • body weight • anthropometry
Body fat and its distribution in relation to casual and ambulatory blood pressure.
L M Gerber, P L Schnall and T G Pickering
Hypertension. 1990;15:508-513
doi: 10.1161/01.HYP.15.5.508
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