Predicting Type 2 Diabetes Risk Using Combined Lifestyle and Socioeconomic Indicators: A Population-Based Cohort Study

Antoine Lefevre¹, Camille Dubois², Hugo Moreau³

Abstract

Background: The global burden of type 2 diabetes mellitus (T2DM) continues to increase, particularly among populations experiencing rapid lifestyle transitions. Early identification of high-risk individuals is essential for prevention strategies.

Methods: A prospective cohort study was conducted among 8,462 adults aged 25–70 years from five urban regions in France between 2020 and 2025. Baseline assessments included physical activity, dietary habits, smoking status, educational attainment, household income, and body mass index. Participants were followed for incident T2DM. Cox proportional hazards models were used to estimate risk factors.

Results: During a median follow-up of 4.8 years, 614 participants developed T2DM (7.3%). Individuals with low physical activity levels had a significantly higher risk of diabetes (adjusted HR 1.92; 95% CI 1.61–2.28; p<0.001). Obesity increased risk nearly fourfold (HR 3.87; 95% CI 3.18–4.70; p<0.001). Participants in the lowest income quartile demonstrated a 46% higher risk than those in the highest quartile (HR 1.46; p=0.003). A combined prediction model incorporating lifestyle and socioeconomic variables achieved an AUC of 0.88, outperforming conventional risk assessment models (AUC 0.76; p<0.001).

Conclusion: Integrating socioeconomic indicators with traditional lifestyle risk factors substantially improves diabetes risk prediction and may support targeted prevention programs.