CARDIOVASCULAR JOURNAL OF AFRICA • Volume 34, No 1, January–April 2023 24 AFRICA with selected demographic and lifestyle variables among South African adults living in informal settlements. Gauteng is the smallest of the nine provinces in South Africa, but comprises the largest portion of the South African population, at about 13 million. The province serves as the economic hub of the country and is responsible for over 34.8% of the country’s total gross domestic product.42 Gauteng province remains a desirable place to live and work compared to other regions in South Africa, therefore, the province is likely to experience in-migration.43 Migrants often settle in informal settlements on the periphery of cities,44 with the province being one of three out of the nine provinces in South Africa with the highest number of households living in informal settlements.45 The literature has documented the difficulties of obtaining reliable figures for informal settlement backlog in South Africa,46 which is estimated to be at least two million.47 Rao software was used to calculate a sample size, taking into consideration the population size, estimated at two million, a 5% margin of error and 95% confidence level. A minimum sample size of 329 adults, aged 18 years, was obtained and convenience sampling was used to select the participants. Ndlovu48 indicated a loss of interest of informal settlers to take part in community activities due to poor service delivery, hence, sampling was challenged by the willingness of residents to participate in the study. The study was conducted among presumably healthy adults, not diagnosed with any CVD and not on any medication.49 Data were collected between October 2016 and April 2017 during the pilot study of a faith-based organisation during a health expo for the identified informal settlement community. The health expo consisted of a number of health services, health education and health-promotion activities, which were offered at no cost to the community members. The health expo team of volunteers included medical practitioners, nurses, dentists and public health practitioners. Treatment for minor illnesses, screening for medical and dental conditions and referring of members to mobile clinics or hospitals was done, according to individual needs. As part of the health expo programme, the metabolic screening team conducted specific screening activities. An adapted WHO STEPwise questionnaire was used for this study.50 Three readings of each of systolic (SBP) and diastolic (DBP) blood pressure were measured at intervals of at least one minute, while participants were seated, as per the Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure.51 Body weight was measured to the nearest 0.1 kg using a calibrated smart D-quip electronic scale, while height was measured to the nearest 0.5 cm with a wall-mounted stadiometer. Body mass index (BMI) was calculated as weight divided by height squared (kg/m2). Waist and hip circumferences were measured to the nearest 0.1 cm using a non-stretchable plastic tape. Abdominal obesity was computed as waist circumference (WC), waist-to-hip ratio (WHR)45,52 and waist-to-height ratio (WHtR).53 Capillary blood was taken using disposable lancets to determine cholesterol and glucose levels with an Accutrend® GCT (Roche Diagnostics, Basel, Switzerland). Two consecutive measurements were taken, and the mean value was used for the study. Risk factors determined in this study were central/abdominal obesity determined by a WC of ≥ 94 cm in males and ≥ 80 cm in females, or a BMI > 30 kg/m2 (in the case of a BMI > 30 kg/ m2, central obesity can be assumed and WC does not need to be measured). In addition to overweight/obesity, hypertension (≥ 130/85 mmHg) and glucose level were determined. We used ≤ 7.8 mmol/l instead of 5.6 mmol/l for fasting glucose, since we could not confirm that participants had fasted overnight. These risk factors were adapted from the criteria of the International Diabetes Federation (IDF) and the National Cholesterol Education Program Adult Treatment Panel III for the metabolic syndrome (ATPIII),54 which was used to determine the presence of the MetS by a combination of any three. The study was conducted according to the guidelines laid down in the Declaration of Helsinki,55 and all procedures involving human subjects were approved by the Sefako Makgatho Health Sciences University Research and Ethics Committee [SMUREC/ H/74/2016:IR]. Written informed consent was obtained from all participants. Statistical analysis Statistical analyses were performed using STATA (Intercooled Stata® version 14). Skewness and kurtosis tests for normality were performed to check the distribution of data. All variables had chi-squared p-values less than 0.05, which indicated skewed data. The medians for continuous data were compared using the Mann–Whitney test by gender. Results are presented as median [interquartile range (IQR)]. A chi-squared test was used to compare the cardiometabolic risk factors and the MetS, stratified by gender and age to generate the proportions, and the results are presented as categorical variables [frequency (n) and percentage (%)]. Fisher’s exact test was applied to variables with expected values less than five in a cell. Multivariate logistic regression analysis was used to determine the association of the MetS (outcome measure) with selected independent variables. Adjusted odds ratios (AOR) with a 95% confidence interval (CI) were generated and used to determine the independent strength of the relationship. Significance was considered at p < 0.05. Results Three hundred and twenty-nine informal settlers participated in the study. Sample size variations were observed due to the difficulty of full participation experienced during data collection. The demographic characteristics of participants are presented in Table 1. Participants were characterised by singlehood (56%) and unemployment (81%), and they lived in households with a monthly income below R5 000 (73%). A parity of one to two children was found in 55%, and 35% had more than two children. Some participants (41%) had never visited a healthcare facility, while 34% reported having visited a healthcare facility a year or more ago. Alcohol use was observed among 35% while only 14% used cigarettes. Medians of variables are compared between males and females in Table 2. Forty-eight per cent of participants were male, while females accounted for 52%. The median (IQR) for age of the participants was 35 years (25–42), ranging from 18 to 81 years. Significant differences of medians were observed for BMI, WC, WHR, WHtR, SBP and DBP between males and females.
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