Binary Logistic Regression Study to Determine the Risk of Heart Attack in 2023

Background: This paper presents an analytical study of the characteristics of participants in a health study aimed at understanding the relationship between several demographic and health factors. Objectives: To analyze how demographic variables and health-related conditions such as hypertension, diabetes, stroke history, smoking, and chest infections relate to health outcomes. Methods: Data were collected on gender, age, and selected health conditions. Participants were distributed based on these variables. Logistic regression analysis was applied to identify factors influencing the likelihood of developing specific health conditions. Results: The study revealed gender differences (61.8% males and 38.2% females) and a higher concentration of participants in older age groups. Logistic regression analysis showed negative effects for chest infections, smoking, blood pressure, and diabetes, while male gender had a positive effect. Conclusions: Understanding complex interactions among demographic and health variables is essential. The study emphasizes the need for further research to clarify their broader effects on public health.