CARDIOVASCULAR JOURNAL OF AFRICA • Vol 23, No 7, August 2012
390
AFRICA
Methods
As described in detail previously,
6,7
the 3 500-bed Chris Hani
Baragwanath Hospital (case load of
>
125 000 in-patients per
annum) services the tertiary care needs of Soweto (population of
1.1 million) and surrounding communities. All cases of suspected
heart disease are referred to the Hospital’s Cardiology unit
for advanced diagnostic testing and gold-standard treatments.
This prospective clinical registry of all
de novo
presentations
(2006–2008) as part of the Heart of Soweto study
7
represents
sub-Saharan Africa’s largest and most detailed study of advanced
forms of heart disease to date.
6,7
The Heart of Soweto cohort of
de novo
case presentations
comprised 5 328 patients. Of these, 2 185 (40%) patients
simultaneously had a fasting serum TC level performed (as
analysed by on-site routine chemistry laboratory). Of these,
there were 1 964 cases with recorded LDL-C levels (90%),
1 996 with HDL-C levels (91%) and 1 969 with TG levels (90%).
Complete lipid profiles were available for 1 945 cases (89%).
None of the patients were on lipid-lowering agents at the time of
presentation, as this medication would only be prescribed at the
tertiary institution at the time of the study.
Overall, 518 of 5 328
de novo
cases of heart disease were
identified as HIV positive (9.7%) with 54% of these prescribed
highly active anti-retroviral therapies on presentation.
8
In this
sub-study, 116 participants (5.3%) were confirmed HIV positive.
Some of the patients had been placed on anti-hypertensive
medication prior to their first assessment at the cardiac clinic at
Baragwanath Hospital. The study was approved by the University
of the Witwatersrand Ethical Committee and conforms to the
principles outlined in the Declaration of Helsinki.
A complete list of study data captured by the registry,
comprising basic socio-demographic (including self-reported
ethnicity, years of education, and determination of birthplace
as Soweto) and advanced clinical profiling has been described
previously.
6,7
The registry captured all advanced clinical
investigative procedures (e.g. coronary angiography, which
was undertaken in all people diagnosed with coronary artery
disease). Echocardiography (performed on all patients) criteria
used in the study have been described in detail previously.
6,7
Risk factor definition
Previous reports provide a range of thresholds for dyslipidaemia
in African populations (e.g. a TC level from
>
3.8 mmol/l
9
to
>
5.2 mmol/l).
10
In this study, optimum lipid levels and treatment
goals for patients with established CVD and associated conditions
were defined according to European guidelines on cardiovascular
disease prevention in clinical practice,
11
as adopted by the Lipid
and Atherosclerosis Society of South Africa and the South
African Heart Association:
12
high TC:
>
4.5 mmol/l, high TGs:
>
1.7 mmol/l and low HDL-C:
<
1.0 mmol/l for males and
<
1.2 mmol/l for females. Importantly, these guidelines echo
the recommended LDL-C level of
>
2.5 mmol/l as set by NCEP
ATP III.
13
Other risk factors for cardiovascular disease were measured,
as previously described, on a clinical basis.
7
As described in a
previous report, hypertensive patients were identified on the basis
of a documented blood pressure (BP) of
≥
140/90 mmHg and/
or prescribed antihypertensive treatment. In both the cardiology
unit and primary care clinics, BP was assessed following
five minutes’ rest; seated systolic (SBP) and diastolic (DBP)
blood pressure (in mmHg) and heart rate (beats per minute)
measurements were performed using an appropriately sized arm
cuff via a calibrated Dynamap (Critikon, Johannesburg, South
Africa) monitor. The mean of three successive readings, each
separated by two minutes’ rest, was taken.
Anthropometric measurements were available for calculation
of body mass index (BMI, kg/m
2
) in 1 593 (73%) cases, the low
reporting rate restricted to ambulatory patients. Obesity was
defined as BMI
≥
30 kg/m
2
. Serum C-reactive protein (CRP)
was measured in a sub-set of 664 patients (30% of all cases)
if clinically indicated (e.g. suspected infection). Patients were
stratified into risk tertiles.
14
However, as levels of
<
1.0 mg/l
were not reported, we have used patients with a CRP of 1.0 mg/l
(
n
=
40) as our ‘low-risk’ reference group for this parameter.
This group was then compared to medium (1.1–3.0 mg/l,
n
=
50)
and high (
>
3.0 mg/l,
n
=
567) CRP risk categories.
Due to incomplete data to formally assess the presence of
familial hypercholesterolaemia (FH) according to the Dutch
Lipid Clinic Network criteria,
15
we examined the proportion of
patients with an LDL-C
≥
4.9 mmol/l and/or TC
≥
7.5 mmol/l to
determine potential cases of FH.
Statistical analyses
Normally distributed continuous data are presented as the mean
±
standard deviation, and non-Gaussian distributed variables as
the median (inter-quartile range). Categorical data are presented
as percentages with 95% confidence intervals (CI) where
appropriate. For group comparisons, we initially used Chi
square (
χ
2
)
analysis with calculation of odds ratios (OR)
and 95% CI (where appropriate) for discrete variables, and
one-way analysis of variance (ANOVA) for normally distributed
continuous variables, and Kruskal-Wallis test for non-parametric
continuous variables, with Tukey’s
post hoc
tests. Multiple
logistic regression analyses (entry model) were used to derive
age-, gender- and BMI-adjusted ORs for the risk of presenting
with dyslipidaemia.
Owing to the lower sample sizes of white Europeans, mixed-
ancestry patients and Indians, these data were pooled when
calculating ORs, relative to individuals of African descent.
Significance was accepted at the two-sided level of
p
<
0.05
and
p
<
0.01 (Bonferroni correction) for ANOVA and Kruskal-
Wallis analyses.
Results
Table 1
shows the socio-demographic and clinical profiles of this
cohort according to ethnicity. While there were no differences in
mean age across ethnicities, there were significant differences in
the proportion of females; ranging from 61% in those of African
descent to 36% in white Europeans. Overall, compared to all
other ethnicities, African patients were more likely to be obese
(OR 1.56, 95% CI: 1.15
–
2.13,
p
<
0.01 in age- and gender-
adjusted model) and have fewer than six years’ education (OR
1.72, 95% CI: 1.28–2.31,
p
<
0.0001).
White European patients recorded the lowest prevalence
of poor education (23%) but higher rates of smoking; when
compared to patients of African descent, white Europeans were
three-fold more likely to be current smokers (OR 3.4, 95% CI:
1.86–5.64,
p
<
0.001). Patients of mixed ancestry were twice as
likely to be current smokers than patients of African descent (OR
