VOLUME 10 NUMBER 2 • JUNE 2013
55
SA JOURNAL OF DIABETES & VASCULAR DISEASE
REVIEW
diastolic) was measured three times on the right arm/wrist of the
seated respondent using an automated recording device (OMRON
R6 Wrist Blood Pressure Monitor, HEM-6000-E, Omron Healthcare
Europe, BV, Hoofddorp and The Netherlands).
Out of three measurements, the average of the last two
readings was used. In accordance with the Seventh Report of the
Joint National Committee on Prevention, Detection, Evaluation and
Treatment of High Blood Pressure, individuals with systolic blood
pressure ≥ 140 mmHg and/or diastolic blood pressure ≥ 90 mmHg
and/or who reported the current use of antihypertensive medication
were considered to be suffering from high blood pressure.
28
Awareness was defined as history of hypertension based on
diagnosis by a healthcare provider. Treatment was defined as taking
any medication or other treatment for hypertension in the last two
weeks prior to the survey, and control was defined as blood pressure
< 140 and < 90 mmHg at the time of the survey.
Lifetime tobacco users were asked ‘Do you currently use (smoke,
sniff or chew) any tobacco products such as cigarettes, cigars, pipes,
chewing tobacco or snuff?’ The response options were ‘Yes, daily’,
‘Yes, but not daily’ and ‘No, not at all’. Daily tobacco use was coded
= 1, and not daily and not at all = 0.
29
Lifetime alcohol users were asked about current (past month)
alcohol use. Past month alcohol use was coded = 1 and no past
month alcohol use = 0.
Height and weight were measured. Body mass index (BMI) was
used as an indicator of obesity (≥ 30 kg/m
2
), calculated as weight in
kg divided by height in metres squared. Overweight and/or obesity
were defined as BMI ≥ 25 kg/m
2
and underweight as < 18.5 kg/m
2
.
Social cohesion was measured with nine items, starting with
the introduction ‘How often in the last 12 months have you… e.g.
attended any group, club, society, union or organisational meeting?’
All nine items were summed to get a social cohesion index. Response
options ranged from never = 1 to daily = 5. Cronbach alpha for the
social cohesion index in this sample was 0.73.
Physical activity was measured using the General Physical
Activity Questionnaire (GPAQ). The instrument gathers information
on physical activity in three domains (activity at work, travel to and
from places, and recreational activities), as well as time spent sitting.
The questionnaire also assesses vigorous and moderate activities
performed at work and for recreational activities. Information
on the number of days a week spent on different activities, and
time spent in a typical day for each activity was also recorded.30
Cronbach alpha for the GPAQ in this sample was 0.77.
For physical activity, in addition to the total minutes of activity,
the activity volume was also computed by weighting each type of
activity by its energy requirement in metabolic equivalents (METs).
One MET was defined as the energy cost of sitting quietly, and
was equivalent to a caloric consumption of 1 kcal/kg/h. A MET-
minute showed the total activity volume on a weekly basis, and
was calculated by multiplying the time spent on each activity during
a week by the MET-values of each level of activity. MET-values for
different levels of activities were set as 4 MET for moderate intensity
physical activity, 8 MET for vigorous physical activity, and 4 MET for
transport-related walking or cycling.
The total physical activity for GPAQ2 was calculated as the sum
of the total moderate, vigorous, and transport-related activities per
week. The number of days and total physical activity MET-minutes
per week were used to classify respondents into three categories of
low, moderate and high level of physical activities. Less than 600
MET-minutes per week was classified as low physical activity.
30
Fruit and vegetable consumption was assessed with the
questions ‘How many servings of fruit do you eat on a typical day?’
and ‘How many servings of vegetables do you eat on a typical day?’
Insufficient fruit and vegetable consumption was defined as less
than five servings of fruits and/or vegetables a day.
Overall self-rated health status was based on respondents’
assessment of their current health status on a five-point scale
in response to the question: ‘In general, how would you rate
your health today?’ Response categories were: very good, good,
moderate, bad and very bad. Very good and good were grouped
together and coded = 1, moderate = 2 and bad and very bad were
grouped together and coded = 3.
Activity limitation (difficulty an individual may have in executing
task or actions) was assessed with one item ‘Overall in the last 30
days, how much difficulty did you have with work or household
activities?’ Response options ranged from 1 = none to 5 = extreme/
cannot do. None were coded = 1, mild = 2, moderate = 3 and
severe and extreme were grouped together and coded = 4.
Finally, participants were asked about a list of chronic and other
conditions they had been diagnosed with, including diabetes,
hypertension, stroke, angina and arthritis. Of participants who
responded to having been diagnosed with hypertension, the
question was asked, ‘Have you been taking any medication or other
treatment for it during the last two weeks?’ Other treatment might
include a weight-loss programme or change in eating habits.
Attendance at out-patient care was assessed with the question,
‘Over the last 12 months, did you receive ant healthcare not
including an overnight stay in hospital or long-term care facility?’
Of those who indicated ‘yes’ they had to report the number of
times they had received healthcare or consultation in the last 12
months. Frequency of attendance at out-patient care was grouped
into none = 0, one to four = 2, five or more = 3.
To estimate economic or wealth status, a random-effects probit
model was used to identify indicator-specific thresholds that
represent the point on the wealth scale above which a household
is more likely to own a particular asset than not. This enabled
an estimation of an asset ladder. These estimates of thresholds,
combined with actual assets observed to be owned for any given
household, were used to produce an estimate of household-level
wealth status. This was used to create wealth quintiles.
31
Lowest
and second-lowest wealth quintiles were grouped together as low
= 1, the middle wealth quintile was medium = 2 and the fourth
and highest wealth quintiles were grouped together as high = 3.
Statistical analysis
The data were entered using CSPro and analysed using STATA
Version 10. The data were weighted using post-stratified individual
probability weights based on the selection probability at each stage
of selection. Individual weights were post-stratified by province,
gender and age groups according to the 2009 medium mid-year
population estimates from Statistics South Africa, available at:
/ P0302/P03022009.pdf.
Computed estimates and odds ratios were reported with 95%
confidence intervals and a two-tailed p-value of 0.05 was used as
the cut-off point for statistical significance. Associations between
key outcomes of hypertension, and socio-demographic and health
variables were evaluated calculating odds ratios (OR).
Multivariate logistic regression was used for evaluation of the
impact of explanatory variables for key outcome of hypertension
(binary dependent variable). All variables statistically significant at
