16 / 74
CARDIOVASCULAR JOURNAL OF AFRICA • Volume 29, No 6, November/December 2018
348
AFRICA
with hypertension in South Africa and call for interventions to
address gaps in CV-risk screening and management, especially
that each additional CV risk exponentially increases the risk of
CVD in a patient with hypertension.
28
Since most CV risk factors are modifiable, lowering BP alone
without intervening in co-existing CV risk factors can therefore
not be deemed optimal care. Regrettably, only four to 7% of
patients with multiple CV risk factors receive appropriate risk-
management interventions during clinical encounters,
12
signifying
enormous missed clinical opportunities and the need for strategies
to close this gap. Such strategies should include academic detailing
of CV risk factors in the management of hypertension to improve
healthcare providers’ screening behaviours and prompt them to
initiate management for these risk factors. Even when the burden
of CV risk factors is assessed to be low, primary prevention
should still be done, since the prevalence of CV risks tends to
increase with age and if not attended, a relatively low burden of
CV risks in the present may translate into higher lifetime risks of
CVD in a patient with hypertension.
29
In line with other African studies,
24,30
this study found that
obesity is prevalent (65.8%) among patients with hypertension;
higher than reported in two recent nationally representative
population surveys in South Africa: SADHS 2016 (29.01%)
26
and SANHNES-1 (29.07%).
27
This is possibly due to clustering
of CV risk factors in patients with hypertension.
The concurrent high prevalence of increased abdominal
circumference (80.8%) in this study also reiterates the
substantially higher risk of CVD in this population compared to
the general population, especially since abdominal circumference
is a strong predictor of adverse CV outcomes. Measurement of
abdominal circumference should therefore form part of the vital
signs in patients with hypertension during clinic visits in PHC.
This is to ensure that healthcare providers respond to abnormal
values by counselling on the need for weight loss, healthy diets
and increased physical activity.
31-33
In addition, health education
needs to be offered to dispel cultural myths that purport obesity
as a symbol of wealth and wellbeing.
34
Physical inactivity is a leading cause of mortality and there is
a graded inverse relationship between physical activity and risk
of CVD.
33
In this study, most participants (73.2%) reported being
physically inactive (Table 3), far greater than the prevalence
reported in previous South African studies.
35,36
A Libyan study
has found a similar prevalence (74.5% among men and 75.5%
in women).
37
The implication of this finding is the enormous clinical
and financial burden it places on the ever-stretched healthcare
system in South Africa. This is dire, considering the relative risk
for developing hypertension in sedentary men and women with
normal BP at rest is 35 to 70% higher than in their physically
active peers.
38
It is therefore important that clinic visits in
primary care be used as opportunities to promote a physically
active lifestyle, especially among patients with one or more CV
risks. This is imperative in the light of the emerging epidemic of
non-communicable diseases in South Africa.
Pensioners, men, blacks and participants of lower socio-
economic status were significantly more likely to report being
physically inactive (Table 6). While previous studies in South
Africa have reported poor engagement of old people in regular
exercise,
39
the significantly higher odds of physical inactivity
among men (compared to women) is contrary to the literature
26,27
Table 6. Sociodemographic determinants of CV risk factors
Risk factor
Odds ratio
95% CI
p
-value
Alcohol use
Age group, years
20–39
1.00
40–59
0.2227
0.0723–0.6853 0.0088
60–79
0.1830
0.0581–0.5764 0.0037
80+
0.2119
0.0185–2.4242 0.2121
Gender
Female
1.00
Male
4.2939
2.3918–7.7088 0.0000
Cigarette smoking
Race
Other
1.00
Black
0.1543
0.0668–0.3567 0.0000
Gender
Female
1.00
Male
6.2782
2.7958–14.0980 0.0000
Current snuff use
Education level
Below secondary
1.00
Secondary or higher
0.6100
0.3376–1.1021 0.1015
Race
Other
1.00
Black
10.9513
1.4475–82.8551 0.0204
Gender
Female
1.00
Male
0.0477
0.0065–0.3520 0.0028
Physical inactivity
Age group, years
20–39
1.00
40–59
0.6033
0.1806–2.0147 0.4114
60–79
0.8299
0.1753–3.9292 0.8141
80+
118865.6277 0.0000– > 1.0312 0.9641
Employment
Employed
1.00
Pensioner
3.4727
1.1946–10.0953 0.02
Unemployed
1.7198
0.9188–3.2192
0.10
Gender
Male
1.00
Female
0.4342
0.2162–0.8719
0.02
Diabetes mellitus
Gender
Female
1.00
Male
1.8634
1.0701–3.2448 0.0279
Hypercholesterolaemia
Race
Other
1.00
Black
0.3201
0.1131–0.9063 0.0319
Family history of hypercholesterolaemia
Race
Other
1.00
Black
0.1210
0.0296–0.4941 0.0033
Education
Below secondary
1.00
Secondary or higher
0.7258
0.1094–4.8153 0.7399
Family history of fatal CV event
Race
Other
1.00
Black
0.1210
0.0296–0.4941 0.0033
BMI > 30 kg/m
2
Gender
Female
1.00
Male
0.1859
0.1053–0.3283 0.0000