We followed-up 6,095 men and women aged >=16 years who participated 1977--79 in a community based health study and were anonymously linked with the Swiss National Cohort until the end of 2008. During follow-up, 727 participants died of CVD. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and fasting glucose or total cholesterol. The mean Brier score (BS), area under the receiver-operating characteristic curve (AUC) and integrated discrimination improvement (IDI) were used for model comparison. We validated our models internally using cross-validation and externally using another data set.In our models, the p-value of total cholesterol was 0.046, that of glucose was p < 0.001. The model with glucose had a slightly better predictive capacity (BS: 2216x10-5 vs. 2232x10-5; AUC: 0.9181 vs. 0.9169, IDI: 0.009 with p-value 0.026) and could well discriminate the overall risk of persons with high and low concentrations. The external validation confirmed these findings.Our study suggests that instead of total cholesterol glucose can be used in models predicting overall CVD mortality risk.