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Methods
Study population
This study was conducted as part of an ongoing longitudinal study, The Young
Hearts Project, which initially examined the prevalence of coronary risk factors in a
random sample of young people (n=1015; aged 12 years and 15 years) in Northern
Ireland. Sampling procedures, study design and response rates of the first two
screening phases (YH1 and YH2) are described in detail elsewhere (21, 22). All
subjects in the original cohort were invited to participate in the third screening phase
(YH3; October 1997-October 1999), when aged between 20 and 25 years. Ethical
approval was gained from the Medical Research Ethical Committee of The Queen’s
University of Belfast, and written informed consent was obtained from all
participating subjects.
Measurements of height and weight and blood pressure were carried out on
each subject. Standing height was measured to the nearest millimetre using a
Harpenden portable stadiometer and body weight was measured to the nearest 0.1kg
using a SECA electronic balance. For both measurements, subjects wore light indoor
clothing and no shoes. Resting blood pressure was measured twice using a Hawskley
random zero sphygmomanometer with the mean of the measurements used in
subsequent analyses. Information on socio-economic position, family and past
medical history and lifestyle (including smoking habit, alcohol intake etc.) were
obtained by questionnaire. Habitual dietary habits were assessed using a diet history
method (23).
Data on frequency, duration and type of physical activity usually undertaken
were obtained using a modification of the Baecke questionnaire of habitual physical
activity (24) which was designed to quantify work activity, sports activity and non-
sports leisure activity. Indices of work activity, sports activity and non-sports leisure
activity, based on a five-point Likert scale, were calculated with a total physical
activity score obtained from the sum of the three indices, with higher scores
representing subjects reporting greater physical activity.
Fitness testing
All subjects underwent fitness testing, using the Physical Work Capacity at a
heart rate of 170 beats per minute (PWC170) cycle ergometer test (25). The test is a
progressive, sub maximal, predictive measure of endurance using cycle ergometer
(Seca Cardiotest 100 electronically braked cycle ergometer; SECA, Germany).
PWC170 was calculated as the workload corresponding to a heart rate of 170 beats per
minute (26) and expressed per kg body weight. Maximum oxygen consumption (VO2
max) was calculated by extrapolation of VO2 at predicted maximum heart rate against
PWCmax. (Quinton QMC metabolic cart; Quinton, USA)
Arterial compliance
The velocity characteristics of the arterial pulse wave (associated with left
ventricular ejection) were used to determine arterial compliance using a non-invasive
optical method (27). The technique used was a modification of that developed by
Greenwald and colleagues (28). This method determines the transit time of the wave
of dilatation propagating in the arterial wall resulting from the pressure wave
generated by contraction of the left ventricle. Pulse wave velocity (PWV) is
calculated as the time taken to travel a known distance, timed from the ECG R-wave,
to the arrival of the pressure wave at a distal site, using a photoplethysmographic
probe. All distances were measured from the sternal notch, to the site of application of
the probe, which remained consistent throughout the period of recording. This
technique samples data every millisecond enabling the detection of differences in
transit times of 1-2 milliseconds. Pulse wave velocity is inversely related to the square
root of the compliance of the vessel wall; therefore high pulse wave velocity indicates
a stiffer arterial wall. This method yields consistent results (29, 30) similar, to those
obtained by Doppler ultrasonograph y (28) that have previously been shown to give
reproducible estimates of arterial compliance in population studies (31).
Pulse wave velocities (m/s) were measured in three arterial segments: the
aorto-iliac segment, from proximal common carotid artery into the femoral artery at
the inguinal ligament (pwva); aorto-radial segment from the carotid into the radial
artery (pwvb); and the aorto-dorsalis-pedis segment (pwvf), from the carotid into the
posterior tibial artery immediately posterior to the dorsalis-pedis artery.
All subjects were assessed by one skilled observer, blind to genotype, with
measurements taken on the left side of the body. In some subjects it was not possible
to obtain pulse wave measurements of adequate quality. This was usually due to
attenuation of the optical signal by subcutaneous fat or because of the difficulty in
accessing the position of the artery. Estimations of pulse wave velocity based on
fewer than 10 cycles or those in which the coefficient of variance of arterial transit
times was greater than 20% were rejected.
COL1A1 Intron 1Sp1 site polymorphism genotyping
DNA was extracted from whole blood as previously described (32). COL1A1
2046G>T genotypes were determined using a polymerase chain reaction (PCR) in
which a mismatched primer introduces a restriction site for the enzyme Bal1 in the
rare T-allele (thymidine at position +2046) (20). PCR products were digested
overnight with Bal1. Genotypes were resolved by agarose gel electrophoresis yielding
a 246bp cleaved (T allele) fragment, and a 264bp wild type, G allele band.
Statistical analysis
All data were analysed using STATA Release 6 for Windows. Raw data were
analysed for those that were normally distributed. Otherwise, data were subjected to
log-transformation prior to analysis (pwva), with the geometric means and standard
errors being quoted in the results. Variation in arterial compliance between genotypes
was assessed by ANOVA and by students’ t-tests for unpaired data. One-way analysis
of covariance (ANCOVA) was performed to test whether the COL1A1 polymorphism
was associated with differences in compliance using age, sex, BMI (kg/m2), smoking,
mean arterial pressure (MAP), fitness and activity scores, VO2 max (ml/min) and
family history of hypertension as covariates. Allele frequencies were estimated by
gene counting. A 2 test was used to compare the observed numbers of each genotype
with those expected for a population in Hardy-Weinberg equilibrium.