Abstract
BACKGROUND: Sociodemographic factors have been implicated in cardiovascular health with differential morbidity and mortality. It is essential to comprehend how sociodemographic factors contribute to the improvement of Metabolic Syndrome (MetS), the primary cardiovascular diseases indicator. OBJECTIVE: Determine the role of sociodemographic factors in improving MetS among adults residing in the Slums of Nairobi, Kenya. METHODS: Adults with MetS participated in this randomized controlled trial study for a period of 12-months. A random assignment was used to place eligible participants in the intervention or control groups. The intervention group received lifestyle intervention that entails not using tobacco products or alcohol, exercising, and adhering to recommended dietary guidelines, while the control group had standard medical care. Clinical, biochemistry, and lifestyle habits were measured before and a year after the intervention. The association between the sociodemographic factors and the improvement in MetS was examined using a multiple logistic regression model with backward conditional. RESULTS: In the intervention group, lack of improvement in metabolic syndrome was significantly higher among aged (≥50 years) respondents [AOR = 9.097; P < .001]; Protestants [AOR = 7.292; P = .017] and Catholics [AOR = 5.270; P = .050]. Compared to unemployed, formally employed respondents had an 84.6% lower chance of having MetS [AOR = 0.154; P = .005]. Within the control group, lack of improvement in metabolic syndrome was significantly higher among aged (≥50 years) respondents [AOR = 5.013; P = .047]. Compared to respondents who had less than $100, individuals with monthly incomes between $100 and $500 had a roughly 10-fold [AOR = 10.499; P = .024] higher chance of having MetS. CONCLUSION: In the current study, the findings show that sociodemographic factors namely: advanced age, unemployment, being Protestants and Catholics as well as higher income were negatively associated with improvement in MetS. The findings indicate that social factors have impact in the management and intervention outcomes of CVDs. Programmers and policy makers should plan interventions for CVD prevention and response with these factors in mind.