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.

通过分析 2015 年 BRFSS 数据，我们深入研究了糖尿病与一系列健康指标之间的复杂关系，特别关注了收入这一新添加的变量。我们的综合分析不仅考察了每个因素的孤立影响，还探究了它们之间的相互关系以及对糖尿病的集体影响。我们的研究揭示了一个明显的趋势，低收入阶层与糖尿病发病率更高有着关联。在分析了 33 个变量，包括健康因素和生活方式选择后，我们发现高血压、高胆固醇、胆固醇检查、收入和身体质量指数（BMI）等因素具有较大的意义，这表明它们在糖尿病的发病和管理中扮演着重要的角色。