Temporal changes in the cardiometabolic disease risk profile of the Bellville south mixed-ancestry community between 2008/09 AND 2014/16

Doctoral Thesis


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Background/purpose: The burden of cardiovascular disease (CVD) is growing rapidly and has shifted from high-income countries to low-middle income countries, including South Africa. In the South African Mixed-ancestry population, there is a dearth of trend studies examining the changes in cardiometabolic risk factors and their behavioural, socio-demographic, and lifestyle determinants. This thesis aimed to determine the temporal changes between 2008/09 and 2014/16 in (1) absolute blood pressure levels and hypertension prevalence; (2) distribution and change in obesity or body size phenotypes; and (3) the prevalence of insulin resistance (IR), inflammatory biomarkers, and their determinants. Methodology: Participants, aged ≥20 years, residing in Bellville South and Belhar, Cape Town, were recruited in two independent cross-sectional surveys conducted during 2008/09 (N=928) and 2014/16 (N=1969). Data were obtained through questionnaires, clinical measurements (anthropometric measurements and BP), and biochemical assessments (oral glucose tolerance tests, lipid profile, and sub-clinical inflammation markers). Obesity phenotype was defined using a combination of body mass index (BMI) categories and abnormal cardiometabolic status. The latter was defined as the presence of ≥ 2 cardiometabolic risk factors. Indices used to assess IR included: insulin fasting, HOMA-IR, QUICKI, McAuley and Matsuda. Biomarkers defining sub-clinical inflammation included Ultra-Sensitive-C-Reactive Protein (usCRP) and gamma-glutamyl transferase (gamma GT). Statistical packages used for data analysis were Statistica v.13 (TIBCO Software Inc., 2017) and SPSS v.25 (IBM Corp, 2011). Measures of central tendencies and dispersion characteristics are reported to summarize survey data. The crude and age standardised prevalence of hypertension were compared across years. With regards to obesity phenotype, IR, and sub-clinical inflammation, change in the distribution was investigated using interaction tests across the years of study. Linear and logistic regression analyses adjusted for year of study, age, and gender, were applied for all three studies. Results: Participants were older in 2008/09 (54.3 years) compared to 2014/16 (49.6 years), the majority (>75%) of whom were female. Mean systolic blood pressure increased from 124 to 136 mmHg and mean diastolic blood pressure from 75 to 85 mmHg over the 7-year period. The prevalence of newly detected hypertension increased from 11.6% to 24.8% and remained significant after adjusting for confounding variables. Importantly, there was a shift in the peak prevalence of hypertension from older ages (≥ 70 years) in 2008/09 to younger individuals (40-49 years) in 2014/16. The BMI distribution between 2008/09 vs 2014/16 improved significantly with decreases in overweight (27.4% vs 23.6%) and obese (45.3% vs 42.2%) participants (p=0.001). However, across all BMI categories in both metabolic healthy and abnormal participants, anthropometric and biochemical measurements, and glucose and lipid profiles linearly increased (all p ≤ 0.018 for linear trends). Over the 7-year period, there was an increase in the prevalence of sub-clinical inflammation: us-CRP (54.7% vs 57.1%) and gamma-GT (29.6% vs 33.4%). Furthermore, multivariable analyses revealed that obesity levels, glycated haemoglobin, and fasting insulin levels were prominent risk factors associated with increased IR or subclinical inflammation, after adjusting for confounding variables. Conclusion: A significant increase in hypertension prevalence was uncovered with a rightward shift in absolute BP. The majority of these increases were amongst newly detected hypertension, suggesting a non-optimal detection of the disease. Therefore, increased awareness and screening drives for hypertension detection is crucial to reduce the prevalence of hypertension in this population group. Complications and nominal costs related to severity of hypertension must be incorporated on a greater scale than is currently practised in order to manage and prevent CVD development. A significant proportion of normal weight participants presented with metabolic abnormalities, while a substantial percentage of obese participants presented as metabolically healthy. Additional research is required to improve risk stratification for obesity phenotypes. Additionally, sub-clinical inflammation increased over the seven-year period, and was linked to strong predictors of CVDs, i.e., IR and metabolic syndrome components. Therefore, before substantial changes in CVD are observed in the population, monitoring the pathophysiological development of sub-clinical inflammation and IR biomarkers may provide early information on the trajectory of CVD burden.