54 / 66
CARDIOVASCULAR JOURNAL OF AFRICA • Volume 30, No 6, November/December 2019
362
AFRICA
A positive correlation between BMI and BP has been reported
among Ghanaian adults aged 30 to 50 years old.
24
Certain
occupations, especially white-collar jobs, are characterised by sitting
for long periods of time, such as employees in financial institutions
and administration offices, and this predisposes individuals to a
sedentary lifestyle.
25
These individuals tend to spend the majority of
their adult working lives less engaged in physical activity outside of
working hours, thereby predisposing them to obesity and diseases.
26
A study in India reported a higher prevalence of hypertension,
which was more positively correlated to obesity among employees
than the general population of the country.
27
A recent systematic review among workers in West Africa
reported a prevalence of hypertension of 12 to 69% among
employees.
28
The prevalence of obesity ranged from 2% among
automobile garage employees in Kumasi, Ghana,
29
to 42.1%
among healthcare workers in Umuahia, Nigeria.
30
The prevalence
of hypertension ranged from 27.9 to 78.9% among obese workers
compared with 7.3 to 65.4% among non-obese employees in
West Africa.
31
Among healthcare workers in a university teaching
hospital, there appeared an unusual ratio in the association
between obesity and hypertension, which was 2.2 (
p
=
0.004).
32
In Kaduna, civil servants younger than 40 years old who were
overweight or obese were five times as likely to have hypertension
compared with healthy-weight workers.
33
Schutte
et al
.
34
reported
a prevalence of 48% overweight and obesity among South
African employees from 18 companies participating in health-
screening programmes. Cardiovascular risk factors, specifically
diabetes and hypertension, were found to be associated with
obesity among public service workers in Ondo State, Nigeria.
35
This study will be first of its kind to study employees in the
Vhembe district municipalities of the Limpopo Province to
investigate the relationship between obesity and BP.
Methods
The research was based on a cross-sectional design on an
available population sample of local government employees
in the Vhembe district municipality of the Limpopo Province,
South Africa. Participants voluntarily participated in the study.
There were 452 (men
=
207; women
=
245) participants from
local government employees in the Vhembe district, which is one
of the five districts of the Limpopo Province of South Africa
(local government is a form of public administration in South
Africa, which exists as the lowest tier of administration in the
provinces). Vhembe district is located in the northern part of
the country and shares its borders with the Beitbridge district
in Matabeleland south, Zimbabwe. According to the 2001
census, 800 000 Vhembe district residents speak Tshivenda as
their mother tongue, while 400 000 speak Tsonga and 27 000
speak Northern Sotho.
36
The majority of the participants in
this study were employed as grounds maintenance workers,
clerical workers, managers and councillors. The employees were
categorised into three age groups as follows: 24–29, 30–44 and
45–65 years. Participants were included in the study if they were
within the age categories and deemed healthy.
Standing height was measured to the nearest 0.1 cm, using a
Harpenden portable stadiometer (Holtain Ltd, Crymych, Dyfed,
UK). Body mass was measured using a portable calibrated scale
(SECA) and recorded to the nearest 0.5 kg. BMI was calculated
as body mass (kg) divided by height (m) squared (kg/m²).
Waist circumference (WC) was measured using a steel tape
measure and in accordance with the procedure recommended by
the American College of Sports Medicine.
37
For men, low WC in
this classification is defined as less than 94 cm, high is 94 to 102
cm, and very high is greater than 102 cm. For women, low WC is
less than 80 cm, high is 80 to 88 cm, and very high is greater than
88 cm.
38,39
Waist-to-height ratio (WHtR) was determined from
waist circumferences (cm) divided by height (cm). The norms for
WHtR were as follows: normal is WHtR
<
0.5, while WHtR
>
0.5 indicates increased risk for both males and females.
40
BP was measured by using an automated sphygmomanometer
(Omron, Health Care, Inc, USA). The participants were
seated, and systolic (SBP) and diastolic (DBP) blood pressure
measurements were determined according to the protocols
suggested by the American College of Sports Medicine
(ACSM).
37
The ACSM has identified thresholds above which individuals
may be at an increased risk for cardiovascular disease.
37
The
thresholds that were used to describe risk included the following:
•
overweight
=
BMI between 25 and 29.9 kg/m
2
; obesity
=
BMI
≥
30 kg/m²
•
hypertension
=
SBP
≥
140 mmHg and DBP
≥
90 mmHg, as
well as for participants on hypertension treatment.
The aim of the study was explained to the participants and
their employers, who were also informed that the data would be
treated confidentially and would only be used for the purposes of
research. The participants were requested to complete and sign
an informed consent form before participating in the study. The
measurements took place during weekdays, as arranged with the
participants. The researcher (a biokineticist registered with the
Health Professions Council of South Africa: registration number
BK 0016195-HPCSA) was assisted by well-trained research
assistants conducting the measurements. The anthropometric
measurements of height, weight, WC and BP were taken in
allocated separate rooms for males and females. The study
received ethical approval (Ref: NWU-00125-13-S1) from the
ethics committee of North West University, Potchefstroom,
South Africa.
Statistical analysis
Descriptive statistics were calculated for all variables according
to gender. Numerical data are expressed as mean and standard
deviation (mean
±
SD) and categorical data are expressed as
percentages. A
t-
test was used to determined differences in the
means of variables (age, height, weight, BMI, WC, WHtR, and
SBP and DBP between the study groups), and the chi-squared
test was used to compare the prevalence of general obesity and
central/abdominal obesity in men and women. The differences
in BMI and WC across age groups were described by gender,
and the chi-squared test was used to compare the prevalence
of obesity between the various age groups. To determine the
differences between the BMI categories/groups, an analysis of
variance (ANOVA) was calculated for all variables. Descriptive
characteristics of the hypertensive and normotensive groups
were determined and compared. Pearson correlation coefficients
were used to determine the relationship between obesity and BP
among employees. All statistical analyses were performed with
the SPSS, version 21. The statistical level of the
p
-values was set
at
p
≤
0.05.