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RESEARCH ARTICLE
SA JOURNAL OF DIABETES & VASCULAR DISEASE
46
VOLUME 15 NUMBER 2 • NOVEMBER 2018
dyslipidaemia was defined by the Castelli index as TC/HDL-C
> 3.4.
30
The physical activity level of participants was assessed with
the World Health Organisation (WHO) Global Physical Activity
Questionnaire-2 (GPAQ-2), which assesses physical activity in four
domains of work, travel, recreational and resting.
31
The product of
the exercise intensity in metabolic equivalents (METs), duration of
activity in hours and the number of times per week, expressed as
METs/hour was regarded as exercise volume. A MET/hour value less
than 600 per week was taken as physical inactivity.
31
Statistical analysis
Data entry and analysis were done with the Statistical Package
for the Social Sciences 17.0 version (SPSS, Inc, Chicago, IL, USA).
Continous data are presented as mean and standard deviation.
Categorical variables are expressed as proportions. Pearson’s
correlation was used to determine how some independent
numerical variables (age, BMI, number of years of professional
driving and number of driving hours/week) correlated with the
major outcome variables (systolic and diastolic BP, and abnormal
glucose profile). Furthermore, the independent variables were
dichotomised to look for an association between them and the
outcome variables, hypertension and abnormal glucose profile
using the chi-squared test. Level of statistical significance was set at
p
< 0.05 and confidence interval at 95%.
Multivariate analysis was done using a forward stepwise binary
logistic regression in order to assess for independent predictors of
hypertension and abnormal glucose. We included predictor variables
with associations at a significance level of
p
≤ 0.2 on univariate
analysis in order to accommodate for important risk factors.
Results
A total of 308 drivers were recruited for the study. Fifteen were
excluded due to incomplete data. Therefore 293 were used for
data analysis, giving a response rate of 95.1%.
The age range of the study population was between 25 and 76
years with a mean of 44.8 ± 9.7 years. Two hundred and eighty
six (97.6%) of the subjects were aged between 25 and 65 years.
The rest of their socio-demographic characteristics is shown in
Table 1.
Fifty-seven of the drivers (19.5%; 95% CI: 14.9–24.0%) were
active smokers while 217 (74.1%) and 19 (6.5%) were non-
smokers and ex-smokers, respectively. The prevalence of alcohol
intake was 71.1% (95% CI: 65.7–76.2%). The majority consumed
various types of alcoholic beverages: beer, spirits and alcohol-based
Fig. 1.
Consort diagram describing how participants were recruited into the study. LDD: long-distance commercial drivers.