CARDIOVASCULAR JOURNAL OF AFRICA • Vol 21, No 4, July/August 2010
AFRICA
197
training on the FRA scores of young males with few CHD risk
factors. A finding that a combination of aerobic and resistance
training could reduce several CHD risk factors simultaneously
would be of critical importance, due to the synergistic benefits
to be gained from each mode of exercise.
Methods
Thirty-seven sedentary young adult males volunteered to partici-
pate in this study (mean age 25 years and six months).
Demographic data are presented in Table 1. Age was ascertained
from date of birth. Since females may have a greater variability
in CHD risk factors than males, only males were selected.
13
The
subjects were required to be free of any medical conditions that
could have prevented them from optimising the benefits of their
exercise training, they had to be inactive and weight stable at
least six months before the study started and were not allowed to
be on any weight-management programmes or pharmacological
agents that could have affected the measured CHD risk factors.
All subjects underwent an identical battery of tests before and
after the 16-week intervention period. All subjects were evalu-
ated in the post-absorptive state following a 12- to 14-hour fast
and at least 48 hours prior to or following any exercise. Prior
to participation in the investigation, all volunteers gave written
informed consent and underwent a screening history and physi-
cal examination. They were allowed to discontinue the study at
any time.
This investigation was approved by the Institutional Review
Board at the University of Johannesburg (formerly Rand
Afrikaans University). Random assignment was made to one of
the experimental exercise groups: aerobic training (AT) (
n
=
12)
or concurrent aerobic and resistance training (CART) (
n
=
13),
or to the non-exercising (NO) group (
n
=
12), using a schedule
generated from a table of random numbers.
For descriptive purposes, anthropometric measurements
were carried out according to the methods proposed by the
International Society for the Advancement of Kinanthropometry
(ISAK).
14
Subjects were weighed to the nearest 0.1 kg on a cali-
brated medical scale (Mettler DT Digitol, Mettler-Toledo AG,
Ch-8606 GreiFensee, Switzerland) wearing only running shorts.
Each subject’s height was measured to the nearest 0.1 cm via a
standard wall-mounted stadiometer.
FRA score calculation
The variables used in FRA calculation to estimate risk in adults
who do not yet have CHD are age, smoking status, systolic blood
pressure, total cholesterol value and high-density lipoprotein
cholesterol value. Information on smoking habits in terms of
the number of cigarettes smoked daily was obtained by a self-
administered seven-day questionnaire a week before the pre- and
post-test.
15
This was done in order to establish whether any
modifications in the subject’s smoking habits took place during
the course of the treatment period. At entry into the study, all
subjects participated in a half-hour session on how to estimate
the number of cigarettes smoked daily and how to complete the
smoking form.
Each subject’s resting systolic (SBP) and diastolic blood pres-
sure (DBP) was measured in the supine (recumbent) position
after five minutes’ rest using a mercury sphygmomanometer
(Alpk2 Sphygmomanometer, Japan). The mercury column was
positioned at the same level as the subject’s heart during moni-
toring. The left arm of each subject was supported and utilised
throughout the investigation. Subjects provided blood samples in
the sitting position and samples were analysed for total choles-
terol and high-density lipoprotein cholesterol concentrations
following a nine- to 12-hour fast and prior to any exercise.
16
Each
parameter was assayed on a single day to eliminate inter-assay
variability. For estimation of each subject’s FRA score, the present
study utilised the point system of the Framingham Heart study.
6
Training design
All subjects participated in three 60-minute exercise sessions
each week for 16 weeks. The aerobic training sessions started
with the subjects warming up by cycling for five minutes at a
heart rate of less than 100 beats per minute, followed by rowing,
stepping, cycling and walking on a treadmill for a total of 45
minutes at 60% of their individual heart rate maximum. They
cooled down with a five-minute cycle at a heart rate of less than
100 beats per minute. Age-predicted maximum heart rates were
determined by subtracting their age from 220. Heart rate was
measured continuously during the training sessions with a heart
rate monitor (Polar Fitwatch, Polar Electro Oy, Finland).
The intensity of exercise was increased by 5% every four
weeks.
17,18
In an attempt to equalise for time across the two exer-
cise groups, the subjects in the CART group had to perform 22
minutes of both aerobic training and resistance training.
The resistance training component of the programme required
that the subjects perform two sets of 15 repetitions at 60% of
one-repetition maximum (1-RM) for each of the eight prescribed
exercises, which included shoulder press, latissimus dorsi pull-
downs, seated chest press, low pulley row, crunches, unilateral leg
press, unilateral knee extensions and unilateral prone hamstring
curls. Subjects were under direct supervision during the training
sessions, and all subjects were familiarised with the equipment
before commencement of the experimental programmes.
The CART subjects had to perform a similar warm-up and
cool-down protocol to that of theAT subjects. The weight training
intensity was re-evaluated through 10-RM testing and the training
programmes were adjusted by increasing the resistance accord-
ingly to maintain 60% of the estimated 1-RM every four weeks.
The subjects in the NO group were instructed to remain inac-
tive during the 16-week period.
Statistical analyses
Quantitative data are expressed as means and standard deviations
(SD). While Levene’s test was used to determine the equality or
homogeneity of variance of the groups, the Brown and Forsythe
F
-test was utilised to determine equality of means. Following
this, the present investigation also computed dependent
t
-tests
TABLE 1. BASELINE SUBJECT DESCRIPTIVE DATA
Variables
Group
NO (
n
=
12)
AT (
n
=
12)
CART (
n
=
13)
Age (years)
25
±
2.4
25
±
5.6
26
±
3.1
Height (cm)
179.3
±
11.9
176.8
±
3.8 178.7
±
7.0
Body mass (kg)
80.3
±
12.8
74.7
±
8.2
85.0
±
12.8
Values are means
±
standard deviation
