Background: Reliable burden of disease (BOD) estimates are needed to support decision making in health care. Objectives: The objective of this study was to introduce an analysis approach based on individual-level longitudinal survey data that estimates the burden of diabetes in patients with coronary heart disease in terms of quality-adjusted life-years (QALYs) lost. Methods: Data from two postal surveys (2006, N = 1022; 2010-2011, N = 716) of survivors from the KORA Myocardial Infarction Registry in Southern Germany were analyzed. Accumulated QALYs were calculated for each participant over a mean observation time of 4.1 years, considering the noninformative censoring structure of the follow-up study. Linear regression models were used to estimate the loss in (quality-unadjusted) life-years and QALYs between patients with and without diabetes, and generalized additive models were used to analyze the nonlinear association with age. The cross-sectional and longitudinal association with quality of life (QOL) and QOL change and the impact on mortality were analyzed to enhance the understanding of the observed results. Results: Diabetes was associated with a reduced QOL at baseline (cross-sectional: β = -0.069; P < 0.001), but not with a significant longitudinal QOL change. Mortality in patients with diabetes was increased (hazard ratio = 1.68; P < 0.005). This resulted in a loss of 0.14 life-years (P = 0.003) and 0.37 QALYs (P < 0.001). Results from generalized additive models indicated that the burden of diabetes is less pronounced in older subjects. Conclusions: The application of the proposed approach provides confounder-adjusted BOD estimates for the studied time horizon and can be used to compare the BOD across different chronic conditions. Curative efforts are needed to diminish the substantial diabetes-related QALY gap.