Objective: This study investigates the socioeconomic and behavioral determinants of Type II Diabetes outcomes using a health data analytics framework. Drawing from publicly available medical expenditure and demographic data, the research examines how variables such as age, education, income, employment status, and smoking behavior influence the prevalence and economic impact of the disease. Key findings highlight that older adults and individuals with lower educational attainment or who engage in smoking incur higher medical expenditures.

Methods: A Random Forest classifier was employed to predict patient gender based on socioeconomic and behavioral features, demonstrating moderate predictive accuracy and reinforcing the relevance of non-clinical data in chronic disease profiling.

Results: Statistical analysis further revealed significant correlations between social disadvantage and elevated diabetes-related costs. The study advocates for an integrated “health in all policies” approach, emphasizing the need for cross-sectoral interventions in education, employment, and community health promotion.

Conclusion: These findings contribute to the growing body of literature on the social determinants of health and underscore the value of data-driven strategies in addressing the Type II Diabetes epidemic. Future research should focus on longitudinal and intersectional analyses to enhance causal inference and inform targeted policy responses.

Type II Diabetes, socioeconomic determinants, health data analytics, medical expenditure, smoking behavior, education level

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