Abstract
Kidney diseases, particularly chronic kidney disease (CKD), represent a significant health concern, particularly as one ages. This paper delves into an in-depth analysis of CKD, exploring its prevalence, risk factors, and the complex interplay of conventional and nontraditional determinants. Notably, socioeconomic, genetic, and lifestyle factors are pivotal in understanding CKD's multifaceted etiology. The research employs a diverse dataset from Bangladesh, applying statistical techniques including ANOVA, logistic regression, recursive feature elimination, and random forest to identify and evaluate crucial factors associated with CKD. The study aims to construct a robust predictive model for CKD risk assessment, integrating traditional and lesser-explored variables. This comprehensive approach holds promise in refining risk assessment models and guiding targeted intervention strategies for enhanced CKD prevention and management. The findings emphasize the necessity for a holistic understanding of CKD, emphasizing personalized approaches for effective disease management and prevention.
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