**2.4 Statistical analysis**

*Lifestyle and Epidemiology - The Double Burden of Poverty and Cardiovascular Diseases...*

found in clinical settings were infrequent [4, 5].

vascular risk in young adults at Ellisras.

**2. Methods and materials**

**2.2 Blood pressure measurements**

body mass index (BMI) [18].

DBP in the left and right arms was calculated.

**2.3 Cardiovascular risk factor measurements**

**2.1 Sample**

diabetic patients as well as 4% of the general population [5].

and seems acceptable to patients. Circumstances in which differences in BP were

When undetected, varying measurements of BP between arms can lead to inaccuracies in the interpretation and management of blood pressure consequently putting individuals in an avoidable risk through sub-optimal blood pressure control [6]. Furthermore it has been reported that systolic BP difference of 10 mmHg or greater between both arms was related with cardiovascular risk/complications [7, 8]. Moreover an inter arm difference is mostly encountered with differences in systolic of 10 mmHg or greater prevalent in 11% of hypertensive patients, 7%

Past studies have discovered a rise in the incidence of big inter arm difference in hypertensive [9] and diabetic patients [10]. The association between inter arm difference and atherosclerosis-related diseases, such as coronary artery disease [11], and other peripheral artery disease were also reported [12, 13]. Nevertheless, the majority of these studies took place in populations that were Westernized/ urbanized with little sample sizes and comprising of certain disease groups. The prevalence of selected cardiovascular risk factors has been reported in young adults at Ellisras including BP/hypertension [14], but the inter arm BP difference was not investigated. Furthermore as far as we are aware, such a study was not reported among black South Africans in Limpopo Province. Therefore the study aimed to determine the blood pressure difference between arms and its association to cardio-

The study constituted of 624 young adults (306 males; 318 females) aged 18 to 29 years old from the Ellisras Longitudinal Study (ELS) in Lephalale, Limpopo province in South Africa. The details of ELS are explained elsewhere [15]. The study was approved by the Ethics Committee at the University of Limpopo prior to the

Participants with factors that could influence the reliability of the study includ-

Prior to being measured the participants rested for approximately 5 minutes. Afterwards, three blood pressure (BP) readings of systolic blood pressure (SBP) And diastolic blood pressure (DBP) were measured five minutes apart in both the left and right arms using an electronic Micronta monitoring kit, [16, 17]. Average BP was calculated for both arms. Then the difference between the average SBP and

All participants underwent height and weight measurements according to the standard procedures [18]. The weight and height were then used to determine the

There was fasting of between 8–10 hours before the collection of blood samples. All blood sample collections were carried out in schools by qualified nurses from the

study commencing. Consent forms were also signed by the participants.

ing pregnancy and chronic diseases or hospitalization were excluded.

**100**

Inter arm systolic blood pressure difference (IASBPD) and inter arm diastolic blood pressure difference (IADBPD) were described as the absolute value of the left arm SBP/DBP minus the right arm SBP/DBP respectively. Both the IASBPD and IADBPD were grouped into two categories based on a cut-off point: <10 mmHg which is normal and ≥ 10 mmHg which is the category increasing cardiovascular risk [22]. Continuous variables were articulated as mean ± standard deviation while categorical variables were articulated as frequencies and percentages. Moreover comparisons of the variables were performed between the two cut-off groups using independent *t* test for continuous variables, and chi-square test for categorical variables. A multivariate logistic regression model was used to analyze the association between IASBPD and IADBPD, height, weight, BMI, SBP, DBP, fasting glucose, TC, TG, HDL-C, LDL-C, diabetes and hypertension. All analyses were performed using SPSS software version 14.0 and P-value of ≤0.05 was considered statistically significant.
