CARDIOVASCULAR JOURNAL OF AFRICA • Volume 25, No 1, January/February 2014
28
AFRICA
Methods
This was a cross-sectional study on cardiovascular (CV) risk
factors, conducted from 2009 to 2010 in employees of a public
university in Luanda, Angola. Participants aged 20 years and
older (
n
=
625) visited the Department of Physiology, Faculty of
Medicine of Agostinho Neto University, Luanda, Angola to be
submitted to clinical and laboratorial examinations to identify
cardiovascular risk.
A total of 615 subjects with complete data were included in this
study. Details of the study design are described elsewhere.
26,27
The
study was conducted according to the tenets of the Declaration
of Helsinki and participants signed an informed consent form
approved by the Ethics Committee of the Faculty of Medicine,
Agostinho Neto University.
Clinical examinations were performed between 08:00
and noon in temperature-controlled rooms (22–23°C) after a
12-hour fast. Participants were asked to refrain from smoking,
physical exercise and caffeinated beverages for at least 12 hours
before the visit. Venous blood samples were obtained from the
forearm by standard techniques and processed immediately
using commercially available kits (BioSystems SA, Costa
Brava 30, Barcelona, Spain) for determination of levels of
serum triglycerides, total cholesterol, high-density lipoprotein
cholesterol (HDL-C), glucose, creatinine and uric acid.
Biochemical parameters were analysed using enzymatic
methods on a spectrophotometer (BioSystems BTS-310,
Barcelona, Spain). In subjects with triglyceride levels
<
400 mg/
dl (4.52 mmol/l), low-density lipoprotein cholesterol (LDL-C)
was calculated according to Friedewald’s formula,
28
and very
low-density lipoprotein cholesterol (VLDL-C) was calculated as
previously described.
4
Diabetes was defined as a fasting glucose level
≥
126 mg/dl
(6.99 mmol/l) or the use of antidiabetic drugs.
29
Dyslipidaemia
was defined as the presence of one or more of the following: total
cholesterol
≥
200 mg/dl (5.18 mmol/l), triglycerides
≥
150 mg/
dl (1.70 mmol/l), LDL-C
≥
160 mg/dl (4.14 mmol/l), or HDL-C
<
40 mg/dl (1.04 mmol/l) (men),
<
50 mg/dl (1.30 mmol/l)
(women).
4
Demographics including socio-economic level, educational
data and medical history were collected using a structured
questionnaire. Participants were classified as non-smokers (never
and ex-smokers) and current smokers (daily and occasional
smokers).
Anthropometric measures included weight, height, WC and
hip circumference (HC), obtained from individuals wearing
underwear and no shoes. Weight was measured to the nearest 0.1
kg using a previously calibrated mechanical scale (SECA GmbH
& Co, Germany) with a maximum capacity of 220 kg.
Height was measured with a precision of 0.5 cm using a
stadiometer fixed to the SECA scale. WC and HC were each
measured twice using an inextensible, 1-cm-wide tape measure.
The WC was measured at the end of normal expiration, at the
midpoint between the lower border of the rib cage and the top of
the iliac crest,
30
and recorded nearest to the 0.1 cm. The waist:hip
ratio (WHR) was calculated from the WC and HC.
BMI was calculated from the weight divided by the square of
the height (kg/m
2
). According to BMI values, individuals were
classified as normal (18.5–24.9 kg/m
2
), overweight (25.0–29.9
kg/m
2
) and obese (
≥
30.0 kg/m
2
).
31
Socio-economic status was classified into quartiles according
to average monthly household income;
27
first quartile (low socio-
economic class), second quartile (middle class), third quartile
(upper middle class), and fourth quartile (upper class). Education
was classified into three levels based on the number of years of
education: low (
≤
four years of education), middle (five to 12
years of education), and high (
≥
13 years of education).
27
Blood pressure and heart rate were measured in triplicate in
the non-dominant arm after five minutes of resting in a seated
position with the arm at the level of the heart. These parameters
were measured using a validated, automated digital oscillometric
sphygmomanometer (Omron 705CP, Tokyo, Japan). The readings
were repeated at three-minute intervals. The mean of the last two
readings was recorded.
The pulse pressure (PP) was computed as the difference
between basal systolic blood pressure (SBP) and diastolic blood
pressure (DBP). Mean blood pressure (MBP) was computed
as the DBP
+
(PP/3). Hypertension was defined as SBP
≥
140 mmHg, and/or DBP
≥
90 mmHg, and/or the use of
antihypertensive drugs.
Both the ATP III
4
and JIS
7
criteria were used to define the
metabolic syndrome. The ATP III definition was based on the
presence of three or more of the following components: WC
>
102 cm (men), 88 cm (women); SBP
≥
130 mmHg and/
or DBP
≥
85 mmHg and/or BP-lowering treatment; fasting
triglyceride levels
≥
150 mg/dl (1.70 mmol/l) or treatment for
hypertriglyceridaemia; HDL-C
<
40 mg/dl (1.04 mmol/l) (men),
50 mg/dl (1.30 mmol/l) (women), or treatment for dyslipidaemia;
fasting glucose level
≥
110 mg/dl or on antidiabetic medication.
The JIS definition was based on the presence of three or
more of the following components: WC
≥
94 cm (men), 80 cm
(women); SBP
≥
130 mmHg and/or DBP
≥
85 mmHg and/or
BP-lowering treatment; fasting triglyceride levels
≥
150 mg/dl
(1.70 mmol/l) or treatment for hypertriglyceridaemia; HDL-C
<
40 mg/dl (1.04 mmol/l) (men), 50 mg/dl (1.30 mmol/l) (women)
or treatment for dyslipidaemia; fasting glucose level
≥
100 mg/
dl (5.55 mmol/l) or on antidiabetic medication.
Statistical analysis
Data were analysed using SPSS software, version 13.0 (SPSS
Inc, Chicago, IL). Continuous variables are reported as mean
±
standard deviation, and compared by gender using the
independent-samples
t-
test. Categorical variables were expressed
as proportions and compared using the chi-square test or Fisher’s
exact test if appropriate. Prevalence of the metabolic syndrome
was age-standardised by direct method using as reference the
world population distribution as projected by the WHO for 2000
to 2025.
32
Age-specific prevalence of the metabolic syndrome
was estimated per age decades (
<
30, 30–39, 40–49, 50–59 and
≥
60 years).
ROC curve analysis was performed to determine the
appropriate cut-off points of WC for identifying subjects with
two or more components of the metabolic syndrome (except
for WC), as defined by the JIS criteria. For the purpose of this
analysis, we considered the presence or absence of the metabolic
syndrome as an outcome variable and WC as a testing variable.
Optimal values of WC were obtained from the Youden index
[maximum (sensitivity
+
specificity – 1)].
33
Positive predictive
values (PPV) and negative predictive values (NPV) were also
presented. The kappa coefficient was used to assess the statistical
