ABSTRACT
Background: The global escalating prevalence of lifestyle-related non-communicable diseases places a significant burden on health systems. Chronic diseases of lifestyle (CDL) are a group of diseases that share similar modifiable risk factors that can result in long-term disease processes. Considering the socio-behavioral-metabolic risk profiles of communities and risk factors predictive of the presence of CDL can assist in the development of focused and effective community-based prevention, intervention, and treatment programs for CDL. Aim: To determine the socio-behavioral-metabolic risk profiles and identify associated factors for the following CDL: obesity, cardiovascular disease, hypertension, and type 2 diabetes mellitus in rural and urban communities in central South Africa. Methodology: This cross-sectional study included adults aged 25-65 years in the rural Southern Free State and urban Mangaung. Social determinants, behavioral and metabolic risk factors, and inflammatory biomarkers for CDL were determined. Results: In total, 575 rural (mean age: 42 years; 71% female) and 429 urban (mean age: 44 years; 76% female) participants were included in the study. More than 20% of participants in both communities reported being previously diagnosed with cardiovascular diseases; with reported hypertension and diabetes mellitus more prevalent among rural participants. Insufficient intake of fruit and vegetables, alcohol use, and high blood pressure were among the top five risk factors in both communities. Physical inactivity ranked among the top two risk factors in the urban community; while alcohol and tobacco use was significantly higher in the rural community. Fibrinogen was the most prevalent inflammatory marker in both communities (32.9 rural vs. 48.3% urban). High sensitivity C-reactive protein (Hs-CRP), only available for rural participants, was high with increased levels in more than 80% of participants. In both communities, being female, having high blood pressure and increased fibrinogen levels were associated with obesity. Conclusion: This study illustrated the high prevalence of socio-behavioral-metabolic risk factors for CDL, and identified similarities and distinct differences in the risk profiles of rural and urban communities. Considering the CDL risk profiles of communities can assist in prioritizing health needs and contribute to the development of tailor-made community-based primary health care prevention, intervention, and health promotion programs.
