Utility Decrements Associated With Diabetes and Related Complications: Estimates From a Population-Based Study in Germany

Objectives: Health utility decrement estimates for diabetes and complications are needed for parametrization of simulation models that aim to assess the cost-utility of diabetes prevention and care strategies. This study estimates health utility decrements associated with diabetes and cardiovascular and microvascular complications from a population-based German study. Methods: Data were obtained from the population based cross-sectional KORA (Cooperative Health Research in the Augsburg Region) health questionnaire 2016 and comprised n = 1072 individuals with type 2 diabetes and n = 7879 individuals without diabetes. Health utility was assessed through the EQ-5D-5L. We used linear regression models with interaction terms between type 2 diabetes and different cardiovascular and microvascular complications while adjusting for demographic and socio-economic factors and other comorbidities. Results: Type 2 diabetes (β = −0.028, standard error [SE] = 0.014), stroke (β = −0.070, SE = 0.010), cardiac arrhythmia (β = −0.031, SE = 0.006), heart failure (β = −0.073, SE = 0.009), coronary heart disease (β = −0.028, SE = 0.010), myocardial infarction (β = −0.020, SE = 0.011, estimates of main effect), and neuropathy (β = −0.067, SE = 0.020), diabetic foot (β = −0.042, SE = 0.030), nephropathy (β = −0.032, SE = 0.025), and blindness (β = −0.094, SE = 0.056, estimates of interaction terms) were negatively associated with health utility. The interaction term for diabetes x stroke (β = −0.052, SE = 0.021) showed that the utility decrement for stroke is significantly larger in people with type 2 diabetes than in people without diabetes. Conclusions: Diabetes, cardiovascular, and microvascular conditions are associated with significant health utility decrements. Utility decrements for some conditions differ between people with and without type 2 diabetes. These results are of high relevance for the parametrization of decision analytic simulation models and applied health economic evaluations in the field of prevention and management of type 2 diabetes in Germany.