Cardiovascular disease (CVD) is a significant global health issue and a leading cause of morbidity and mortality across different countries. Despite the identification of various risk factors associated with CVD, challenges such as inadequate understanding of disease epidemiology, weak healthcare systems, high treatment costs, persistent poverty, and insufficient public awareness about prevention contribute to the underreporting of CVD cases, particularly in low- and middle-income countries. This study aims to identify the critical risk factors influencing CVD within this context. A generalized linear model (GLM) was employed to analyze data from 400 patients under follow-up for anti-hypertension and other CVD-related conditions at the University of Abuja Teaching Hospital (UATH), Nigeria, between July 2014 and July 2024. The analysis revealed a notable gender disparity in CVD prevalence, with a higher incidence among males. Furthermore, 34.8% of CVD patients had two or more comorbid conditions, compared to only 10.8% among non-CVD patients. Univariate analysis indicated that marital status and comorbidity were significantly associated with CVD risk; however, gender, employment status, and BMI were not. Multivariable analysis using binary logistic regression demonstrated that married individuals had nearly four times the odds of developing CVD compared to unmarried individuals, while those with more than two comorbidities had approximately seven times the likelihood of CVD development. The findings underscore the need for regular medical check-ups and targeted public health education campaigns focusing on the prevention and management of CVD, particularly among high-risk groups in the study area. This research contributes valuable insights into the interplay of marital status and comorbidities in CVD risk within the context of Nigeria, addressing significant gaps in understanding disease epidemiology in low- and middle-income countries.
Key words: Logistic Regression Models, Odd Ratio, BMI, Hypertension, CVD, Nigeria
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