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Introduction: Chronic kidney disease (CKD) has become more common in recent decades, putting significant strain on healthcare systems worldwide. CKD is a global health issue that can lead to severe complications such as kidney failure and death. Objective: The purpose of this study was to investigate the actual causes of the alarming increase of kidney failure cases in Saudi Arabia using the supersaturated design analysis and edge design analysis. Materials and methods: A cross-sectional questionnaire was distributed to the general population in the KSA, and data were collected using Google Forms. A total of 401 responses were received. To determine the actual causes of kidney failure, edge and supersaturated designs analysis methods were used, which resulted in statistical significance. All variables were studied from factor h1 to factor h18 related to the causes of kidney failure. Results: The supersaturated analysis method revealed that the reasons for the increase in kidney failure cases are as follows: h9(Bad diet), h8(Recurrent urinary tract infection), h1 (Not drinking fluids), h6 (Lack of exercise), h14 (drinking from places not designated for valleys and reefs), h18 (Rheumatic diseases), h10 (Smoking and alcohol consumption), h13 (Direct damage to the kidneys), h2 (take medications), h17 (excessive intake of soft drinks), h12 (Infection), h5 (heart disease), h3 (diabetes), h4 (pressure disease), h15 (Dyes used in X-rays), and h11 (The presence of kidney stones) are all valid. The design analysis method by edges revealed that the following factors contributed to an increase in kidney failure cases: h8 (Recurrent urinary tract infection), h6 (Lack of exercise), h7 (Obesity), and h11. Conclusion: The findings showed that there were causes of kidney failure that led to the statistical significance, which is h8 (Recurrent urinary tract infection) and h11 (The presence of kidney stones) [ABSTRACT FROM AUTHOR]

The objective of this research is to ascertain the elements that have an impact on and drive domestic violence in Saudi Arabia, a phenomenon that has a prevalence rate of around 35% among women globally. The researchers administered a survey to a sample of 550 individuals and used exploratory factor analysis (EFA) to analyze the collected data. The findings revealed three factors: a lack of familial unity, encouragement of detrimental characteristics, and economic turmoil. The authors examined the consequences of these characteristics on preventive and intervention programs and proposed suggestions for policymakers and researchers. This research enhances the existing body of knowledge on domestic violence by conducting a statistical analysis to examine the factors that lead to it and the resulting outcomes within a particular cultural setting. [ABSTRACT FROM AUTHOR]

The modeling of pandemics is significant in understanding and addressing the spread of infectious diseases. This study introduces a novel and highly flexible extension of the asymmetric unit Burr–Hatke distribution, termed the power Burr–Hatke distribution (PUBHD), and comprehensively investigates its mathematical properties. Multiple parameter estimation methods are employed, and their asymptotic behavior is analyzed through simulation experiments. The different estimation techniques are compared to identify the most efficient approach for estimating the distribution's parameters. To demonstrate the applicability and usefulness of the PUBHD model, we conducted a case study using a sample from the COVID-19 dataset and compared its performance with other established models. Our findings show that the PUBHD model provides a superior fit to the COVID-19 dataset and offers a valuable tool for accurately modeling real-life pandemics. [ABSTRACT FROM AUTHOR]