Logistic Regression Analysis on Cardiovascular Diseases in Jos Metropolis
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Abstract
Cardiovascular diseases (CVDs) remain a leading cause of morbidity and mortality worldwide, with a rising burden in low- and middle-income countries such as Nigeria, yet localized evidence on CVD risk determinants in Jos Metropolis is limited. This study aimed to develop and validate a multivariate logistic regression model to identify and quantify significant predictors of CVD among adults in Jos Metropolis using routinely collected data. A descriptive cross-sectional analysis was conducted among 489 adults (≥18 years) using retrospective electronic health records (2015–2023) and patient survey data from Jos University Teaching Hospital and the Plateau State Ministry of Health. Candidate predictors included hypertension, diabetes, obesity, smoking, physical inactivity, age, gender, and occupation. Logistic regression with backward elimination was employed for model development, and model performance was evaluated using split-sample validation and goodness-of-fit assessments. The findings revealed hypertension as the strongest predictor, with hypertensive individuals having 4.3-fold higher odds of CVD (95% CI: 2.74–6.88, p < 0.001). Smoking, diabetes, and obesity increased CVD odds by 2.7-, 2.8-, and 1.8-fold, respectively, while age showed a modest but significant effect, with each additional year associated with a 2.3% increase in CVD risk (p = 0.002). Gender approached statistical significance, suggesting potential male vulnerability (OR = 1.47, p = 0.053). Overall, the model demonstrated moderate explanatory power (Nagelkerke R² = 0.21) and acceptable discrimination (AUC = 0.73). The study concludes that hypertension and other modifiable lifestyle-related factors are critical drivers of CVD risk in Jos Metropolis and supports the prioritization of community-based hypertension screening, smoking cessation initiatives, and lifestyle-focused health education as key public health strategies.
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