  In this study, we delve into the intricate relationships between diabetes and
a range of health indicators, with a particular focus on the newly added
variable of income. Utilizing data from the 2015 Behavioral Risk Factor
Surveillance System (BRFSS), we analyze the impact of various factors such as
blood pressure, cholesterol, BMI, smoking habits, and more on the prevalence of
diabetes. Our comprehensive analysis not only investigates each factor in
isolation but also explores their interdependencies and collective influence on
diabetes. A novel aspect of our research is the examination of income as a
determinant of diabetes risk, which to the best of our knowledge has been
relatively underexplored in previous studies. We employ statistical and machine
learning techniques to unravel the complex interplay between socio-economic
status and diabetes, providing new insights into how financial well-being
influences health outcomes. Our research reveals a discernible trend where
lower income brackets are associated with a higher incidence of diabetes. In
analyzing a blend of 33 variables, including health factors and lifestyle
choices, we identified that features such as high blood pressure, high
cholesterol, cholesterol checks, income, and Body Mass Index (BMI) are of
considerable significance. These elements stand out among the myriad of factors
examined, suggesting that they play a pivotal role in the prevalence and
management of diabetes.
