Blood pressure risk factors in healthy postmenopausal
women: physical activity and hormone replacement
EDITH T. STEVENSON,1 KEVIN P. DAVY,1 PAMELA P. JONES,1 CHRISTOPHER A. DESOUZA,1
AND DOUGLAS R. SEALS1,2 (With the Technical Assistance of Mary Jo Reiling)
1Department of Kinesiology and 2Divisions of Cardiology and Geriatric Medicine,
Department of Medicine, University of Colorado, Boulder, Colorado 80309
body fat distribution; exercise; aging; hormone replacement
therapy
women is associated with reduced arterial blood pressure (BP)-related CVD risk factors. These BP behaviors
include the following: elevated levels of casual BP at
rest (8, 34) and 24-h ambulatory BP (22, 24), elevated
BP load (i.e., percentage of 24-h BP recordings exceeding 140/90 mmHg) (39), reduced or absent nocturnal
decline in BP (37), elevated BP variability (22), and an
augmented systolic BP (SBP) response to acute aerobic
exercise (5, 18).
Data on middle-aged and older US women indicate
either lower or similar levels of casual BP at rest in
physically active compared with more sedentary subjects (1, 26). However, there is very little information on
the relationship between physical activity levels and
other BP-related CVD risk factors. Accordingly, the
primary purpose of the present study was to test the
hypothesis that highly physically active postmenopausal women demonstrate more favorable BP-related
risk factors for CVD than do healthy nonobese but
less-active controls.
Our subject population also allowed us to examine
possible differences in BP-related CVD risk factors in
users vs. nonusers of hormone replacement therapy
(HRT), another factor that has been associated with a
reduced risk of CVD (3, 15). As with high physical
activity levels, however, it is not known whether HRT
use confers its beneficial effects, in part, through an
association with reduced BP-related CVD risk. Therefore, the secondary purpose of the present study was to
obtain preliminary information on this question.
To address these purposes, a cross-sectional model
was used that we have employed successfully in the
past to gain insight into such issues (30, 35). Specifically, BP-related CVD risk factors in middle-aged and
older highly physically active women were compared
with those in age-matched healthy nonobese sedentary
controls.
METHODS
(CVDs) are the leading cause
of death in middle-aged and older American women (3,
10, 15). The prevalence of CVD increases with age in
women, rising sharply after menopause (3, 10). Regular
physical activity is associated with a reduced risk of
CVD in postmenopausal women (25). Our recent work
(36) and that of others (12, 13, 28) suggest that this
protective effect may be due at least in part to more
favorable levels of various metabolic risk factors, such
as plasma lipids, fasting plasma glucose and insulin
levels, and glucose tolerance. It is also possible, however, that the decrease in CVD risk in physically active
CARDIOVASCULAR DISEASES
652
Subjects
Fifty-two healthy nonobese Caucasian women served as
subjects in this study, including 18 highly physically active
distance runners [mean 55 6 1 (SE) yr; range 49–69 yr] and
34 sedentary-to-minimally active controls (59 6 1 yr; range
50–70 yr). The physically active women had been training for
16 6 1 yr (range 6–26 yr) and typically ran 31 6 2 miles/wk
(range 16–46 miles/wk), in addition to one to four weekly
sessions of other types of training. The controls followed no
program of regular physical exercise.
The physically active women were selected from participants in local and regional road-running races. The controls
were recruited by advertisements in local newspapers. Those
0161-7567/97 $5.00 Copyright r 1997 the American Physiological Society
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Stevenson, Edith T., Kevin P. Davy, Pamela P. Jones,
Christopher A. Desouza, and Douglas R. Seals. Blood
pressure risk factors in healthy postmenopausal women:
physical activity and hormone replacement. J. Appl. Physiol.
82(2): 652–660, 1997.—The prevalence of cardiovascular
disease (CVD) increases with advancing age in women,
particularly after menopause. CVD risk is lower in physically
active women relative to their sedentary peers, but the
responsible mechanisms are not well understood. The aims of
this study were to test the hypotheses that 1) physically
active postmenopausal women demonstrate more favorable
blood pressure (BP)-related risk factors for CVD than do
sedentary healthy women and 2) women on hormone replacement therapy (HRT) also have more favorable levels of these
CVD risk factors. BP-related CVD risk factors were measured
in physically active women (n 5 18; age 55 6 1 yr; n 5 8 on
HRT) and in healthy less-active controls (n 5 34; age 59 6 1
yr; n 5 17 on HRT). Maximal oxygen consumption was higher
in the active group, whereas waist-to-hip ratio and waist
circumference were lower (all P , 0.005). The active women
demonstrated marginally lower (5–8 mmHg; P # 0.10) levels
of casual, 24-h, and daytime systolic BP (SBP). They also
tended to have lower (P 5 0.11) daytime SBP loads (percentage of BP recordings .140/90 mmHg) and lower daytime and
nighttime BP variabilities (P 5 0.04) and a reduced (P ,
0.007) SBP response to submaximal exercise. Women on HRT
tended to have lower (3–4 mmHg; P 5 0.07) levels of 24-h and
nighttime diastolic BP (DBP) relative to the nonusers and
smaller (P , 0.04) daytime and 24-h DBP loads. Stepwise
multiple regression indicated that waist circumference was
the primary predictor of most of the SBP-related CVD risk
factors while HRT use was the best predictor for DBP loads.
These findings indicate that, in general, physically active
postmenopausal women demonstrate more favorable SBPrelated CVD risk factors relative to their less-active healthy
peers, which may be mediated, in part, by their lower levels of
abdominal adiposity. In addition, HRT use tends to be associated with lower levels of DBP-related CVD risk factors.
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
Measurements
Maximal oxygen consumption (V̇O2 max) was measured by
using on-line computer-assisted open-circuit spirometry during incremental treadmill exercise, as described previously
(35), and was used as a measure of aerobic fitness. Physical
activity level, defined as the estimated daily energy expenditure, was assessed by using the Stanford Physical Activity
Questionnaire (29). Body composition and regional body fat
distribution were estimated from various skinfold and circumference measurements because of their potential influence on
BP behavior (38). All anthropometric measures were made by
a single investigator while the subject was in a standing
position. Skinfolds were measured at five body sites by using
a Lange caliper. The sum of these skinfolds was used to
estimate percent total body fat (7). The waist was measured
at the narrowest part of the torso while the hip was measured
at the widest extension of the buttocks. The waist circumference and waist-to-hip ratio were used as an index of an
abdominal or upper body fat distribution, respectively. To
assess any dietary influences on BP-related CVD risk factors,
3-day dietary records were analyzed to provide an estimate of
total caloric intake and composition (Food Processor Plus,
ESHA Research, Salem, OR).
Casual BP at rest was measured by conventional sphygmomanometry by using guidelines established by the American
Heart Association (23) while subjects were in the supine,
sitting, and standing positions as described previously (31).
Changes in SBP and diastolic BP (DBP) from the supine to
standing position were used as a measure of autonomic
nervous system and cardiovascular functions as well as BP
tolerance to orthostatic stress.
BP recordings over a 24-h period of normal daily activity
were made by using a noninvasive ambulatory monitor
(model 90207, Spacelabs, Redlands, WA) as described in
detail previously (31). The ambulatory system was calibrated
against a mercury sphygmomanometer, and the cuff was
programmed to inflate automatically every 15 min from 6 A.M.
to 11 P.M. and every 20 min between 11 P.M. and 6 A.M.
Measuremens obtained from the ambulatory recordings
included mean levels of 24-h, daytime, and nighttime SBP
and DBP, where the nighttime period was individually defined as the period from when the subject went to bed at night
until she arose the following morning and daytime was
defined as the 24-h complement of night. Day-to-night differences in SBP and DBP were calculated to indicate the
presence or absence of a nocturnal decline in BP. In addition,
SBP load (percentage of SBP recordings exceeding 140 mmHg)
and DBP load (the percentage of DBP recordings exceeding 90
mmHg) were determined from the ambulatory recordings.
SBP and DBP variabilities were assessed as the SDs of the
individual BP recordings over the 24-h period, during the day,
and during the night (2, 27).
In accordance with established CVD risk factors associated
with the BP response to acute exercise (5, 18, 40), SBP was
measured during submaximal and maximal exercise, and the
increases from preexercise to submaximal and maximal
exercise were calculated. To determine the SBP response to
submaximal exercise, BP was recorded during the 2nd min of
each 2-min stage of an incremental treadmill-walking protocol as described previously (35). The SBP at the common
workload of 6.4 metabolic equivalents (METs) (corresponding
to a V̇O2 max of ,22 ml · kg21 · min21 ) was determined in each
subject. This workload was selected because it represented
the highest submaximal level attained by all subjects in the
study. Maximal SBP was measured during the final minute of
the exercise protocol when the subject had attained maximal
heart rate. Both the absolute levels of SBP at submaximal
and maximal exercise and the magnitudes of the increases
from standing rest were used to characterize the submaximal
and maximal SBP responses. In addition, the percentage of
subjects in each group whose SBP increased by .7 mmHg/
MET from rest to submaximal exercise (,45 mmHg from rest
to 6.4 METs) was calculated as an indication of an exaggerated SBP response (19).
All measurements were made over a 2- to 3-wk period
during three separate sessions at least 72 h apart. Session 1
included the diagnostic treadmill ECG test, together with
instructions for completing the 3-day dietary records. During
session 2, the physical activity questionnaire was administered, anthropometric measures were made, and a treadmill
V̇O2 max test was performed. In the final session, casual BP was
measured and the subject was fitted with a 24-h ambulatory
BP monitor.
BP has been reported to be reduced for up to 13 h after an
acute bout of physical exercise (11). Therefore, to eliminate
such effects while preserving as much as possible the normal
biological state of the runners, all of the above BP measurements were obtained ,20 h after their last bout of exercise. In
addition, the 24-h ambulatory BP recording for the active
women was made on a nonexercise day.
Data Analysis
Differences in the dependent variables between the physically active women and the controls were assessed by multiple analysis of variance with subsequent post hoc analysis if
the significance level was P , 0.05. Repeated-measures
analysis of variance was used to determine differences when
sequential measures were made. Univariate correlational
analysis was used to assess relationships between physical
activity levels, V̇O2 max, body composition, diet, HRT use, and
the other dependent variables of the study. Forward stepwise
multiple regressions were used to assess the relative contribu-
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respondents who met the criteria of the study were invited to
undergo a diagnostic treadmill electrocardiogram (ECG) test.
If the test proved negative, they were accepted into the study.
Approximately 40% of the active women contacted agreed to
participate in the study, whereas only 10–20% of the respondents to the newspaper advertisements were eligible to serve
as controls. Most of those responding were either too physically active or were currently taking medications that would
influence the dependent variables of the study.
All subjects were free of overt coronary artery disease as
assessed by medical history, physical examination, and resting and maximal exercise ECGs. Fifty-one of the 52 subjects
were postmenopausal as documented by plasma folliclestimulating hormone levels exceeding 30 mU/ml (32). One
subject (a runner) was perimenopausal, but her data were
included because they were not obviously different from the
other subjects in her group and did not alter the mean values
of the dependent variables. HRT was currently being used
(for at least 1 yr) by 8 of the 18 (44%) physically active women
and by 17 of the 34 (50%) controls. The majority (18 of 25) of
the HRT users were receiving oral estrogen in combination
with progesterone. Other regimens included oral estrogen
alone (5), an estrogen patch (1), and a combined estrogen and
progesterone patch (1). None of the subjects smoked or took
other medications that could affect any of the dependent
variables of the study.
The experimental protocol was approved by the Human
Research Committee at the University of Colorado at Boulder; voluntary written informed consent was obtained from
each subject after the nature, purpose, and risks of the study
had been explained.
653
654
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
tions of the above factors to the BP-related risk factors of the
study.
Table 2. Casual systolic and diastolic arterial blood
pressures at rest in physically active women vs. control
RESULTS
BP-Related CVD Risk Factors in Physically Active
vs. Less-Active Women
Table 1. Subject characteristics in physically active
women vs. controls
n
Age, yr
Height, cm
Weight, kg
BMI, kg/m2
Sum of skinfolds, cm
Estimated %body fat
Estimated fat-free mass, kg
Waist circumference, cm
Waist-to-hip ratio
Estimated energy expenditure,
kcal · kg21 · day21
V̇O2 max , ml · kg21 · min21
Active Women
Controls
18
55 6 1
167 6 1
57.7 6 1.2*
20.7 6 0.3*
66.9 6 5.8*
18.2 6 1.3*
47.0 6 0.9
70 6 1*
0.74 6 0.01*
34
59 6 1
164 6 1
68.8 6 1.6
25.6 6 0.5
153.2 6 6.3
34.2 6 1.1
44.9 6 0.9
84 6 2
0.80 6 0.01
45 6 1*
43.7 6 2.1*
35 6 1
24.2 6 0.8
Values are means 6 SE; n, no. of subjects. BMI, body mass index;
V̇O2 max , maximal oxygen consumption. * P , 0.01.
DBP
Sitting
SBP
DBP
Standing
SBP
DBP
Supine to standing
SBP
DBP
Controls (n 5 34)
113 6 2
(101–138)
71 6 1
(58–80)
118 6 3
(100–167)
74 6 2
(62–99)
109 6 2
(95–139)
74 6 2
(65–89)
115 6 3
(91–161)
76 6 1
(63–99)
107 6 3
(93–136)
78 6 2
(67–95)
115 6 3
(88–163)
78 6 2
(59–103)
26 6 1
(218 to 111)
7 6 1*
(23 to 115)
23 6 1
(217 to 116)
361
(211 to 116)
Values are means 6 SE given in mmHg; n, no. of subjects. Nos. in
parentheses denote ranges. SBP, systolic blood pressure; DBP, diastolic blood pressure.
decreases, did not differ between the two groups. SBP
variability was lower (P , 0.04) during both the
daytime and nighttime hours in the physically active
women, although there was no group difference in SBP
variability over the full 24-h period (Table 4). DBP
variability also tended to be lower in the active women,
although this was statistically significant only during
the daytime hours (P 5 0.001).
SBP response to submaximal and maximal exercise
(Table 5). SBP response to submaximal treadmill exercise was lower in the physically active vs. sedentary
women. Both the absolute levels of SBP during treadmill walking at a workload of 6.4 METs as well as the
increase in SBP from standing rest to this submaximal
workload were lower (by 12 and 43%, respectively) in
the active women. In addition, only 7% (1 of 14) of the
physically active women demonstrated an SBP increase from rest to submaximal exercise at 6.4 METs
that exceeded 7 mmHg/MET, whereas 65% (22 of 34) of
the sedentary women had such a response. There were
no significant differences in absolute levels of SBP
during preexercise standing rest or at maximal exercise. There was also no difference in the increase in SBP
from preexercise levels to maximal exercise.
Relationships among physical activity levels, aerobic
fitness, and BP-related CVD risk factors. From univariate analysis, the BP-related CVD risk factors that were
associated with both physical activity and V̇O2 max levels
were daytime SBP and DBP variability (r 5 20.33 to
20.36; P , 0.02), as well as both the absolute level of
SBP at the submaximal workload of 6.4 METs (r 5
20.30 to 20.33; P , 0.05) and the increase in SBP from
preexercise levels to this submaximal exercise workload (r 5 20.41 to 20.55; P , 0.005). In addition, there
were inverse relationships between physical activity
and daytime DBP variability as well as between V̇O2 max
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Physical characteristics (Table 1). The physically
active women and controls were similar in age, height,
and estimated fat-free mass, whereas body weight,
waist-to-hip ratio, body mass index (BMI), sum of
skinfolds, estimated percent body fat, and waist circumference were lower (P , 0.01) in the active women. In
addition, V̇O2 max and levels of physical activity were
higher (P , 0.01) in the active women vs. the controls.
Dietary intake. Estimated daily caloric intake was
not different for the two groups (1,894 6 97 vs. 1,799 6
80 kcal, physically active women vs. controls). The
physically active women, however, consumed a marginally lower percentage of fat (24 6 2 vs. 29 6 1%; P 5
0.08) and a higher percentage of carbohydrates (60 6 2
vs. 54 6 1%; P , 0.01). Percentage of protein intake,
dietary sodium intake, daily sodium excretion, urinary
sodium concentrations, and caffeine and alcohol intake
did not differ in the two groups.
Casual BP recordings at rest (Table 2). Although
there were no significant differences in casual levels of
supine, sitting, and standing BP in the two groups at
rest, there was a trend for lower levels of SBP (5–8
mmHg; P 5 0.10) in the physically active women. On
average, SBP decreased and DBP increased from the
supine to the standing position. The increase in DBP
was greater (P , 0.05) in the active women.
Ambulatory BP recordings (Tables 3 and 4). In general, mean 24-h ambulatory BP levels were similar to or
slightly higher than casual values at rest. The highest
BP levels were attained during the daytime hours in
both groups; both SBP and DBP fell at night during
sleep. There was a trend for lower levels of 24-h,
daytime, and nighttime ambulatory SBP (4–5 mmHg;
P 5 0.08–0.15) and 24-h and daytime SBP loads (P 5
0.11–0.18) in the physically active vs. sedentary women.
DBP levels and loads, as well as day-to-night BP
Supine
SBP
Active Women (n 5 18)
655
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
Table 3. Values from 24-h ambulatory blood pressure
recordings in physically active women vs. controls
Active Women
(n 5 18)
24-h, mmHg
SBP
DBP
Daytime, mmHg
SBP
DBP
Nighttime, mmHg
SBP
DBP
DBP
BP loads, %
24-h
SBP
DBP
Daytime
SBP
DBP
Nighttime
SBP
DBP
P Values
116 6 2
(104–127)
73 6 1
(61–83)
121 6 2
(108–154)
72 6 1
(57–95)
0.09
121 6 2
(107–134)
77 6 2
(63–90)
126 6 2
(111–158)
76 6 1
(58–99)
0.08
106 6 2
(95–119)
65 6 2
(55–81)
110 6 2
(91–144)
63 6 1
(51–83)
0.15
214 6 2
(224 to 14)
213 6 1
(223 to 22)
215 6 1
(224 to 21)
212 6 1
(222 to 23)
0.91
461
(0–15)
662
(0–30)
963
(0–82)
762
(0–62)
0.18
562
(0–21)
863
(0–44)
14 6 4
(0–89)
10 6 3
(0–81)
0.11
060
(0–0)
060
(0–5)
462
(0–64)
161
(0–16)
0.48
24-h
SBP
DBP
0.55
Daytime
SBP
DBP
0.42
Nighttime
SBP
DBP
0.89
0.77
0.69
0.20
0.21
Values are means 6 SE; n, no. of subjects. Nos. in parentheses
denote ranges. BP, blood pressure.
and 24-h, daytime, and casual SBP, 24-h and daytime
SBP variability, nighttime DBP variability, and daytime SBP load (r 5 20.28 to 20.34; all P , 0.05). When
stepwise multiple regression was performed, V̇O2 max
was a significant predictor of 24-h SBP variability and
levels of SBP before treadmill exercise and at maximal
exercise.
Relationships among regional body fat distribution,
diet, and BP-related CVD risk factors. Univariate analysis indicated that the major correlates of casual resting
and ambulatory (24-h, daytime, and nighttime) SBP, as
well as SBP load, were waist circumference (r 5
0.38–0.55; P , 0.02), BMI (r 5 0.29–0.42; P , 0.04),
and sum of skinfolds (r 5 0.28–0.38; P , 0.05). When
forward stepwise multiple regression was performed,
waist circumference appeared as the primary predictor
of all of the above SBP measures, accounting for
15–31% of the observed variance. In addition, whereas
univariate analysis indicated that waist circumference,
BMI, and sum of skinfolds were all related to nighttime
BP variability (r 5 0.28–0.51; P , 0.05), waist circumference was the only significant predictor (forward
Active Women
(n 5 18)
Controls
(n 5 32)
11 6 1
(7–16)
961
(6–14)
12 6 0
(8–16)
10 6 0
(8–14)
0.21
960
(7–13)
660
(5–9)
10 6 0
(7–14)
860
(5–12)
0.04
760
(4–10)
660
(3–8)
961
(3–16)
760
(3–12)
0.04
P Values
0.10
0.001
0.11
Values are means 6 SE; n, no. of subjects.
stepwise multiple regression), accounting for 21 and
31% of the variance in DBP and SBP variabilities,
respectively. Absolute levels of SBP immediately before
and during submaximal (6.4 METs) and maximal exercise, as well as the increase in SBP from rest to
submaximal exercise, were all related to waist circumference (r 5 0.29–0.65; P , 0.05), which was also the
primary predictor of each of these exercise BP measurements (accounting for 10–45% of the variance).
Dietary measures, including macronutrient and total
caloric intakes, were not related to any of the BPrelated CVD risk factors by either univariate analysis
or forward stepwise multiple regression.
BP-Related CVD Risk Factors in HRT Users
vs. Nonusers
Physical characteristics. There were no differences in
the physical characteristics, including body composition, V̇O2 max, and levels of physical activity, of the users
(n 5 25) and nonusers (n 5 27) of HRT. In addition, the
dietary intake and composition of these two groups
were similar.
Casual and ambulatory BP recordings (Table 6).
Levels of casual SBP and DBP at rest were not significantly different in the two groups. The ambulatory
recordings showed a trend for lower (3–4 mmHg; P 5
Table 5. Systolic blood pressure recordings during
submaximal and maximal treadmill exercise
in physically active women vs. controls
Resting standing SBP
Submaximal SBP at 6.4
METs
SBP at maximal exercise
DSBP at 6.4 METs
DSBP at maximal exercise
Active Women
(n 5 14)
Controls
(n 5 34)
P Values
125 6 4
121 6 3
0.42
152 6 4
187 6 4
29 6 3
61 6 4
172 6 5
186 6 4
52 6 3
65 6 3
0.007
0.93
,0.001
0.42
Values are means 6 SE given in mmHg; n, no. of subjects. DSBP,
increase in SBP from standing rest to exercise; METs, metabolic
equivalents.
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Day-to-night difference,
mmHg
SBP
Controls
(n 5 32)
Table 4. Blood pressure variability as assessed
by the SD of 24-h blood pressure recordings (mmHg)
in physically active women vs. controls
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PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
Table 6. Casual blood pressures and values from 24-h
ambulatory blood pressure recordings in HRT
users vs. nonusers
HRT Users (n 5 25)
Casual*
SBP
DBP
24-h
SBP
DBP
Daytime
SBP
DBP
Nighttime
SBP
P Values
114 6 3
(95–152)
75 6 1
(65–91)
113 6 3
(96–164)
76 6 2
(63–100)
0.75
119 6 2
(108–139)
70 6 1
(57–81)
119 6 2
(104–154)
74 6 2
(61–95)
0.87
125 6 2
(111–148)
75 6 1
(58–89)
123 6 2
(107–158)
78 6 2
(63–99)
0.69
109 6 2
(91–127)
62 6 1
(51–71)
109 6 2
(95–144)
65 6 2
(53–83)
0.86
0.48
0.07
0.12
0.07
Values are means 6 SE given in mmHg; n, no. of subjects. Nos. in
parentheses denote ranges. HRT, hormone replacement therapy.
* Casual blood pressures were calculated as means of blood pressure
recordings in supine, sitting, and standing positions.
0.07) 24-h and nighttime DBP in the HRT users. Both
daytime and 24-hr DBP loads (Fig. 1) were substantially lower in the HRT users vs. nonusers (2 6 5 vs.
10 6 14% for 24-h; 5 6 10 vs. 13 6 19% for daytime; P ,
0.04 for both). However, there were no group differences
in SBP loads or BP variability.
SBP responses to submaximal and maximal exercise.
There were no differences in the absolute levels of SBP
during preexercise standing rest, submaximal exercise
at 6.4 METs, and maximal exercise in the HRT users
vs. nonusers. There were also no differences in the
increases in SBP from rest in response to both submaximal and maximal exercise in the two groups.
Fig. 1. Levels of systolic (SBP) and diastolic (DBP) blood pressure
(BP) loads in users (k) vs. nonusers (j) of hormone replacement
therapy. Values are means 6 SE. BP load is defined as percentage of
BP recordings over a 24-h period that exceed 140/90 mmHg. * P ,
0.02.
To our knowledge, this study is the first to address
the question of whether BP-related CVD risk factors,
considered collectively, are more favorable in physically
active aerobically fit postmenopausal women compared
with their sedentary peers. Such a finding could explain, at least in part, the lower prevalence of CVD in
the former (25). Our results suggest that, in general,
highly physically active postmenopausal women demonstrate more favorable SBP-related CVD risk factors
relative to healthy nonobese but less-active women of
the same age, which may be mediated, at least in part,
by a lower level of abdominal fat, as estimated by waist
circumference.
A secondary aim of this study was to determine
whether BP-related CVD risk factors are lower in
healthy postmenopausal women on vs. not on HRT. In
contrast to physical activity levels, HRT was primarily
associated with DBP. Specifically, DBP loads were
lower, and there was a strong tendency for lower levels
of 24-h and nighttime DBP in the HRT users.
Casual BP at Rest
Elevated levels of casually determined BP at rest
have consistently been associated with a higher incidence of coronary arterial disease and a greater risk of
future cardiovascular morbidity (9). Epidemiological
studies report both lower and similar levels of casual
resting BP in physically active vs. sedentary adults;
however, most of these studies were on men (1).
An earlier cross-sectional study by Reaven et al. (26)
showed a strong inverse relationship between physical
activity and SBP levels in women. They reported
unadjusted levels of resting SBP of 143 mmHg in the
sedentary women vs. 123 mmHg in the most-active
women. Consistent with our results, however, there
was no effect of physical activity status on DBP at rest.
The greater SBP differences observed in physically
active vs. sedentary women in the two studies are likely
explained by the fact that the sedentary controls in the
Reaven et al. study were older, on average, than ours
and included women with established hypertension or
evidence of coronary heart disease (CHD). Thus the
results of the present study extend these earlier findings by demonstrating that the effects of habitual
physical activity per se (i.e., independent of disease,
and so on) on SBP at rest are relatively modest in
healthy middle-aged and older women. Moreover, our
findings and those of Reaven and colleagues document
that physical activity levels have no obvious influence
on DBP in normotensive postmenopausal women.
In addition to physical activity, there is some evidence that aerobic fitness, as assessed by time to
exhaustion during graded treadmill exercise, is associated with reduced levels of casual BP in women (6). The
significant correlation between casual levels of SBP
and V̇O2 max observed in the present study supports this
earlier observation.
There is little information concerning the relationship between HRT and casual BP levels at rest. An
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DBP
HRT Nonusers (n 5 27)
DISCUSSION
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
earlier study (17) reported no significant differences in
casual BP in users vs. nonusers of HRT, which is
consistent with the findings of the present study.
In the present study, waist circumference was the
strongest correlate and predictor of casual SBP. Its
predictive importance may explain, in part, the 5- to
8-mmHg differences we observed in levels of casual
SBP between the physically active women and controls
because the physically active women had lower waist
circumferences. It may also explain the lack of differences in casual SBP in the users vs. nonusers of HRT
because waist circumferences were similar in these two
groups. Previous studies also support a relationship
between central body fat distribution and elevated
casual SBP at rest in both men and women over a wide
age range (4).
Twenty-Four-Hour Ambulatory BP
BP Load
Results of a study by White et al. (39) indicate that
measurement of BP load is a better predictor of target
organ damage (e.g., left ventricular hypertrophy) than
are both casual and 24-h ambulatory BP measurements (41). The absolute levels of BP load observed in
our study were generally consistent with those re-
ported in a recent study for normotensive postmenopausal women (41).
We are aware of no previous cross-sectional findings
on BP loads in women (or men) differing in levels of
physical activity, aerobic fitness, or use of HRT. We
found that active fit postmenopausal women had lower
SBP loads than did sedentary women. Because ,24% of
the variance in 24-h and daytime SBP loads was
accounted for by waist circumference, the lower waist
circumferences in the active women may explain their
reduced SBP loads.
Markedly lower DBP loads were observed in the
users vs. nonusers of HRT. Specifically, the majority
(.50%) of the HRT users had all of their DBP readings
below 90 mmHg, whereas only 21% of the nonusers
satisfied this condition. Thus our findings suggest that
a lower 24-h DBP load could contribute to the lower risk
of CVD in postmenopausal women on HRT.
Nocturnal BP Decline
Blunted or absent nocturnal fall in BP has been
associated with increased target organ damage in
women, but not men, with essential hypertension (37).
Verdecchia et al. (37) reported an 11% nocturnal decline
in SBP and a 16% decline in DBP in a group of 25
postmenopausal women who were free of CHD. In the
present study, physical activity status was not associated with nocturnal decline in BP. Our values (12% for
SBP and 16–17% for DBP) were similar to those
reported by Verdecchia and colleagues. The relative
nocturnal SBP and DBP declines for the users and
nonusers of HRT were not significantly different. Overall, no significant univariate correlates or predictors
(using stepwise multiple regression) of nocturnal BP
decline were found. To our knowledge, the present
study is the first to investigate these relationships.
BP Variability
High BP variability as assessed by intra-arterial BP
recordings has been associated with an elevated prevalence and severity of target organ damage (22), as well
as with vascular structural changes (27). BP variability, as measured by the SD of ambulatory recordings,
has been shown to be similar to that obtained from
continuous intra-arterial monitoring, provided that the
interval between two subsequent measurements does
not exceed 20 min (2), a condition satisfied in the
present study. Furthermore, our values for BP variability compare favorably with those in a previous study by
Mancia et al. (14), which were calculated from intraarterial BP recordings over a 24-h period.
The present study demonstrated significantly lower
daytime and nighttime BP variability in the physically
active women vs. controls. This may be due, in part, to
the finding that waist circumference, which was lower
in the physically active women, was the primary determinant of SBP and DBP variabilities in the pooled
population. This finding may also explain why BP
variability did not differ between the users and nonusers of HRT: waist circumference did not differ between
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Because of the high variability in casual BP readings,
24-h recordings provide a more reliable indicator of
overall BP levels during typical daily activities (41).
Twenty-four-hour ambulatory recordings have been
shown to be more strongly correlated with target organ
damage than is casual BP (24). In the present study,
daytime ambulatory SBP in both the physically active
women and the controls was 11–12 mmHg higher than
casual SBP, calculated as the mean of the BP levels in
the supine, standing, and sitting positions (Table 2).
This finding is consistent with that reported by Zachariah et al. (41) in their recent study on ambulatory SBP
characteristics in healthy normotensive men and women
20–84 yr of age.
In the present study, 24-h, daytime, and nighttime
SBP levels were consistently ,5 mmHg lower in the
active women, whereas DBP levels were similar. This is
consistent with results from a recent study on physically active vs. nonphysically active men (21). To our
knowledge, there are no other cross-sectional data
relating physical activity or aerobic fitness to 24-h BP
in women.
In the present study, waist circumference and, to a
lesser extent, BMI and sum of skinfolds were significantly related to 24-h, daytime, and nighttime SBP (by
univariate analysis), but waist circumference was the
only significant independent predictor. There were no
significant correlates or predictors of 24-h, daytime,
and nighttime DBP. These findings may explain the
differences we observed in ambulatory SBP between
the physically active and sedentary women (waist
circumferences were lower in the physically active
women). We are unaware of previous data relating
regional fat distribution to 24-h ambulatory BP levels.
657
658
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
these two groups. We are aware of no previous crosssectional studies that have reported body composition
or HRT correlates of BP variability.
SBP Response to Acute Exercise
Clinical Significance
Considered together, the present results indicate
that highly physically active postmenopausal women
demonstrate lower SBP-related CVD risk factors than
do healthy but less-active women of similar age. These
differences in SBP-related CVD risk factors may be
partially mediated by lower abdominal adiposity as
indicated by the lower waist-to-hip ratios and waist
circumferences of the active women. This finding of
lower SBP-related CVD risk factors in physically active
middle-aged and older women may contribute to their
lower prevalence of CVD.
It is important to note that, although the lower levels
of casual SBP (5–8 mmHg) and DBP (2–3 mmHg) in
Limitations
There are four limitations in the present study that
we wish to emphasize. First, with the cross-sectional
design employed it is possible that genetic or other
constitutional factors may have influenced BP-related
CVD risk factors independent of physical activity or
other factors associated with our group comparisons.
Hence, it is not possible to determine whether physical
activity led to the observed favorable SBP-related CVD
risk factors in the active women or whether their lower
SBP risk profile is part of a broader phenotype that
includes a high level of physical activity and fitness.
Second, our subjects were healthy with mean levels
of casual BP in the normotensive range. If a lesshealthy control group had been used for comparison to
the physically active women, it is likely that greater
differences in BP-related CVD risk factors would have
been observed in the active vs. sedentary women.
Third, although the age range of the women in our
study extended to 70 yr, the mean ages of the two
groups were 55–59 yr. It is possible that habitual
physical activity has a greater impact on BP-related
risk factors in a more uniformly older group of postmenopausal women than that studied here.
Finally, the measurement of BP at least 20 h after the
last bout of exercise in the physically active women
eliminated any potential effects of postexercise hypotension (11). Hence, because these women exercise most
days of the week, we likely overestimated the daily BP
levels of these active women. If so, the contribution of
their lower BP-related risk to the lower prevalence of
CVD observed in this population may be underestimated.
Conclusions
In general, highly physically active postmenopausal
women demonstrate lower levels of SBP-related CVD
risk factors relative to healthy nonobese but less-active
women. This effect, which appears to be mediated in
part by lower levels of abdominal adiposity, may play a
role in the lower prevalence of CVD observed in physically active middle-aged and older women.
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The SBP response to acute exercise has been expressed in the literature in several ways, including 1)
the absolute level of SBP at a given submaximal
workload (18), 2) the absolute level of SBP at maximal
exercise (40), and 3) the increase in SBP from rest to a
predetermined level of submaximal exercise (5). An
augmented SBP response to both acute submaximal
and maximal exercise is associated with both future
hypertension in normotensive individuals (1) and cardiovascular mortality in mildly hypertensive middleaged men (18).
Previous studies on physically active vs. sedentary
healthy postmenopausal women have reported both
lower (20) and similar (16) absolute levels of SBP in
response to submaximal and maximal exercise in the
active women. The finding in the present study of a
lower absolute level of SBP as well as a smaller
increase in SBP above preexercise levels among the
physically active women in response to the same submaximal workload is likely due to their superior level of
aerobic fitness: the same absolute workload represents
a lower relative workload to the active women. This
finding is also consistent with the smaller waist circumferences, the primary predictor of these exercise BP
responses, found in the active women. These findings,
together with those from the two previous studies
described above (16, 20), are consistent with a lower
SBP response to exercise in physically active postmenopausal women.
Very little data are available concerning the SBP
response to acute exercise in users vs. nonusers of HRT.
A previous study by Martin et al. (16) reported lower
levels of DBP and a trend for lower levels of SBP at rest
and during submaximal and maximal exercise in small
groups of older women who were using HRT relative to
nonusers. In the present study, there were no significant differences in the SBP responses to submaximal
and maximal exercise in HRT users vs. nonusers.
Therefore, the available data do not support a strong
association between HRT use and the SBP response to
acute exercise.
the physically active vs. sedentary women did not
achieve statistical significance, they may be of clinical
relevance. Although both groups had casual SBP levels
in the normotensive range (mean of 113 mmHg for the
active women; 118 mmHg for the sedentary women),
the slightly higher levels in the sedentary women
placed them at a significantly elevated risk of CHD
mortality based on current epidemiological data (33).
Furthermore, it has been estimated that in a normotensive population, a 5-mmHg lower SBP is associated
with a 7–14% lower mortality (34) while a 1- to
3-mmHg lower DBP could reduce the incidence of
future hypertension by 20–50% (33). Hence, the tendency for lower mean levels of SBP and DBP observed
in the physically active postmenopausal women of the
present study could have important implications for
their future cardiovascular health.
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
In addition, users of HRT demonstrated lower DBP
loads, as well as a strong tendency for lower levels of
24-h and nighttime DBP. This, too, could contribute, in
part, to the link between HRT use and reduced risk of
CVD.
This study was supported by Andrus Foundation Grant AARPAFOCG0937B and National Institutes of Health (NIH) Grants HL39966, AG-06537, and AG-13038. E. T. Stevenson, K. P. Davy, and
P. P. Jones were supported by NIH Individual National Research
Service Awards HL-08870, HL-08834, and AG-05705, respectively.
D. R. Seals was supported in part by NIH Research Career Development Award AG-00423.
Address for reprint requests: E. T. Stevenson, Univ. of Colorado,
Dept. of Kinesiology, Campus Box 354, Boulder, CO 80309.
Received 28 June 1995; accepted in final form 23 September 1996.
REFERENCES
17. Matthews, K. A., E. Meilahn, L. H. Kuller, S. F. Kelsey, A.
Caggiula, and R. R. Wing. Menopause and risk factors for
coronary heart disease. N. Engl. J. Med. 321: 641–646, 1989.
18. Mundal, R., S. Kjeldsen, L. Sandvik, G. Erikssen, E.
Thaulow, and J. Erikssen. Exercise blood pressure predicts
cardiovascular mortality in middle-aged men. Hypertension 24:
56–62, 1994.
19. Naughton, J. Exercise Testing: Physiological, Biomechanical,
and Clinical Principles. Mount Kisco, NY: Futura, 1988.
20. Ogawa, T., R. J. Spina, W. H. Martin, W. M. Kohrt, K. B.
Schechtman, J. O. Holloszy, and A. A. Ehsani. Effects of
aging, sex, and physical training on cardiovascular responses to
exercise. Circulation 86: 494–503, 1992.
21. Palatini, P., G. Graniero, P. Mormino, L. Nicolosi, L. Mos, P.
Visentin, and A. Pessina. Relation between physical training
and ambulatory blood pressure in stage I hypertensive subjects.
Circulation 90: 2870–2876, 1994.
22. Parati, G., G. Pomidossi, F. Albini, D. Malaspina, and G.
Mancia. Relationship of 24-hour blood pressure mean and
variability to severity of target-organ damage in hypertension. J.
Hypertens. 5: 93–98, 1987.
23. Perloff, D., C. Grim, J. Flack, E. D. Frohlich, M. Hill, M.
McDonald, and B. Z. Morgenstern. Human blood pressure
determination by sphygmomanometry. Circulation 88: 2460–
2470, 1993.
24. Pickering, T. G., and R. B. Devereux. Ambulatory monitoring
of blood pressure as a predictor of cardiovascular risk. Am. Heart
J. 114: 925–928, 1987.
25. Powell, K. E., P. D. Thompson, C. J. Caspersen, and J. S.
Kendrick. Physical activity and the incidence of coronary heart
disease. Annu. Rev. Public Health 8: 253–287, 1987.
26. Reaven, P. D., E. Barrett-Connor, and S. Edelstein. Relation
between leisure-time physical activity and blood pressure in
older women. Circulation 83: 559–565, 1991.
27. Rizzoni, D., M. L. Muiesan, G. Montani, R. Zulli, S. Calebich, and E. Agabiti-Rosei. Relationship between initial cardiovascular structural changes and daytime and nighttime blood
pressure monitoring. Am. J. Hypertens. 5: 180–186, 1992.
28. Rosenthal, M., W. Haskell, R. Solomon, A. Widstrom, and G.
Reaven. Demonstration of a relationship between level of physical training and insulin-stimulated glucose utilization in normal
humans. Diabetes 32: 408–411, 1983.
29. Sallis, J. F., W. L. Haskell, P. D. Wood, S. P. Fortmann, T.
Rogers, and S. N. Blair. Physical activity assessment methodology in the Five-City Project. Am. J. Epidemiol. 121: 91–106,
1985.
30. Seals, D. R., W. K. Allen, B. F. Hurley, G. P. Dalsky, A. A.
Ehsani, and J. M. Hagberg. Elevated high-density lipoprotein
cholesterol levels in older endurance athletes. Am. J. Cardiol. 54:
390–393, 1984.
31. Seals, D. R., and M. J. Reiling. Effect of regular exercise on
24-hour arterial pressure in older hypertensive humans. Hypertension 18: 583–592, 1991.
32. Sherman, B. M., J. H. West, and S. G. Lorenman. The
menopausal transition: analysis of LH, FSH, estradiol, and
progesterone concentrations during menstrual cycles of older
women. J. Clin. Endocrinol. Metab. 42: 629–636, 1976.
33. Stamler, R., J. Stamler, and F. C. Gosch. Primary prevention
of hypertension by nutritional-hygienic means: final report of a
randomized, controlled trial. JAMA 262: 1801–1807, 1989.
34. Stamler, J., R. Stamler, and J. Neaton. Blood presssure,
systolic and diastolic, and cardiovascular risks: U. S. population
data. Arch. Intern. Med. 153: 598–615, 1993.
35. Stevenson, E. T., K. P. Davy, and D. R. Seals. Maximal aerobic
capacity and total blood volume in highly trained middle-aged
and older female endurance athletes. J. Appl. Physiol. 77:
1691–1696, 1994.
36. Stevenson, E. T., K. P. Davy, and D. R. Seals. Physical activity
is associated with favorable hemostatic and metabolic risk
factors for coronary heart disease in healthy nonobese postmenopausal women. Arterioscler. Thromb. Vasc. Biol. 15: 669–677,
1995.
37. Verdecchia, P., G. Schillaci, C. Gatteschi, I. Zampi, M.
Battistelli, C. Bartoccini, and C. Porcellati. Blunted noctur-
Downloaded from http://jap.physiology.org/ by 10.220.32.247 on June 18, 2017
1. American College of Sports Medicine. Physical activity,
physical fitness, and hypertension (position stand). Med. Sci.
Sports Exercise 25: i–x, 1993.
2. DiRienzo, M., G. Mancia, and A. Pedotti. Problems involved
in automatic blood pressure monitoring. Clin. Exp. Hypertens.
A7: 309–318, 1985.
3. Eaker, E. D., J. H. Chesebro, F. M. Sacks, N. K. Wenger, J. P.
Whisnant, and M. Winston. Cardiovascular disease in women.
Circulation 88: 1999–2009, 1993.
4. Emery, E. M., T. L. Schmid, H. S. Kahn, and P. P. Filozof. A
review of the association between abdominal fat distribution,
health outcome measures, and modifiable risk factors. Am. J.
Health Promotion 7: 342–353, 1993.
5. Filipovsky, J., P. Ducimetiere, and M. E. Safar. Prognostic
significance of exercise blood pressure and heart rate in middleaged men. Hypertension 20: 333–339, 1992.
6. Gibbons, L., S. Blair, K. Cooper, and M. Smith. Association
between coronary heart disease risk factors and physical fitness
in healthy adult women. Circulation 67: 977–983, 1983.
7. Jackson, A. S., M. L. Pollack, and A. Ward. Generalized
equations for predicting body density of women. Med. Sci. Sports
Exercise 12: 175–182, 1980.
8. Kannel, W. Status of risk factors and their consideration in
antihypertensive therapy. Am. J. Cardiol. 59: 80A–90A, 1987.
9. Kannel, W., J. Doyle, A. Ostfeld, C. Jenkins, L. Kuller, R.
Podell, and J. Stamler. Original resources for primary prevention of atherosclerotic diseases. Circulation 70: 157A–205A,
1984.
10. Kannel, W., M. C. Hjortland, P. M. McNamara, and T.
Gordon. Menopause and risk of cardiovascular disease: the
Framingham Study. Ann. Intern. Med. 85: 447–452, 1976.
11. Kenney, M. J., and D. R. Seals. Postexercise hypotension: key
features, mechanisms, and clinical significance. Hypertension 22:
653–664, 1993.
12. Krummel, D., T. D. Etherton, S. Peterson, and P. M. KrisEtherton. Effects of exercise on plasma lipids and lipoproteins of
women. Proc. Soc. Exp. Biol. Med. 204: 123–137, 1993.
13. Lindheim, S. R., M. Notelovitz, E. B. Feldman, S. Larsen,
F. Y. Khan, and R. A. Lobo. The independent effects of exercise
and estrogen on lipids and lipoproteins in postmenopausal
women. Obstet. Gynecol. 83: 167–172, 1994.
14. Mancia, G., A. Ferrari, L. Gregorini, G. Parati, G. Pomidossi, G. Bertinieri, G. Grassi, M. di Rienzo, A. Pedotti, and
A. Zanchetti. Blood pressure and heart rate variabilities in
normotensive and hypertensive human beings. Circ. Res. 53:
96–104, 1983.
15. Manolio, T. A., C. D. Furberg, L. Shemanski, B. M. Psaty,
D. H. O’Leary, R. P. Tracy, and T. L. Bush. Associations of
postmenopausal estrogen use with cardiovascular disease and its
risk factors in older women. Circulation 88: 2163–2171, 1993.
16. Martin, W. H., III, T. Ogawa, W. M. Kohrt, M. T. Malley, E.
Korte, P. S. Keiffer, and K. B. Schechtman. Effects of aging,
gender, and physical training on peripheral vascular function.
Circulation 84: 654–664, 1991.
659
660
PHYSICAL ACTIVITY, HORMONE REPLACEMENT, AND BLOOD PRESSURE
nal fall in blood pressure in hypertensive women with future
cardiovascular morbid events. Circulation 88: 986–992, 1993.
38. Weinsier, R., D. Norris, R. Birch, R. Bernstein, J. Wang,
M.-U. Yang, R. Pierson, and T. VanItallie. The relative
contribution of body fat and fat pattern to blood pressure level.
Hypertension 7: 578–585, 1985.
39. White, W., H. Dey, and P. Schulman. Assessment of the daily
blood pressure load as a determinant of cardiac function in
patients with mild-to-moderate hypertension. Am. Heart J. 118:
782–795, 1989.
40. Wilson, M. F., B. H. Sung, G. A. Pincomb, and W. R. Lovallo.
Exaggerated pressure response to exercise in men at risk for
systemic hypertension. Am. J. Cardiol. 66: 731–736, 1990.
41. Zachariah, P., S. Sheps, K. Bailey, C. Wiltgen, and A. Moore.
Age-related characteristics of ambulatory blood pressure load
and mean blood pressure in normotensive subjects. JAMA 265:
1414–1417, 1991.
Downloaded from http://jap.physiology.org/ by 10.220.32.247 on June 18, 2017