The study aimed to define the mathematical relationship between A1C and average glucose (AG) levels and determine if A1C could be reported as AG in the same units as used in self-monitoring. A total of 507 subjects, including 268 with type 1 diabetes, 159 with type 2 diabetes, and 80 non-diabetic individuals, were analyzed. A1C levels were compared with AG levels over the previous 3 months. AG was calculated using data from continuous glucose monitoring and self-monitoring. The linear regression equation AG (mg/dl) = 28.7 × A1C - 46.7 (R² = 0.84, P < 0.0001) showed a strong correlation between A1C and AG. This equation was consistent across subgroups based on age, sex, diabetes type, race/ethnicity, and smoking status. The study concluded that A1C levels can be expressed as eAG for most patients with type 1 and type 2 diabetes. The A1C assay is widely used to assess chronic glycemia and is associated with long-term complications. The study supports the notion of a close relationship between A1C levels and AG for both type 1 and type 2 diabetes. The results of the ADAG study support the translation of A1C to estimated AG (eAG) and suggest that eAG can be reported in the same units as used for day-to-day monitoring. The study also found that the relationship between A1C and AG was consistent across subgroups, suggesting that for many patients with diabetes, there are no important factors affecting the relationship between mean glucose levels and A1C. The study had limitations, including underrepresentation of certain ethnic/racial groups and reliance on two methods for glucose estimation. The results support the reporting of measured A1C as eAG, providing a more useful index of chronic glycemia for healthcare providers.The study aimed to define the mathematical relationship between A1C and average glucose (AG) levels and determine if A1C could be reported as AG in the same units as used in self-monitoring. A total of 507 subjects, including 268 with type 1 diabetes, 159 with type 2 diabetes, and 80 non-diabetic individuals, were analyzed. A1C levels were compared with AG levels over the previous 3 months. AG was calculated using data from continuous glucose monitoring and self-monitoring. The linear regression equation AG (mg/dl) = 28.7 × A1C - 46.7 (R² = 0.84, P < 0.0001) showed a strong correlation between A1C and AG. This equation was consistent across subgroups based on age, sex, diabetes type, race/ethnicity, and smoking status. The study concluded that A1C levels can be expressed as eAG for most patients with type 1 and type 2 diabetes. The A1C assay is widely used to assess chronic glycemia and is associated with long-term complications. The study supports the notion of a close relationship between A1C levels and AG for both type 1 and type 2 diabetes. The results of the ADAG study support the translation of A1C to estimated AG (eAG) and suggest that eAG can be reported in the same units as used for day-to-day monitoring. The study also found that the relationship between A1C and AG was consistent across subgroups, suggesting that for many patients with diabetes, there are no important factors affecting the relationship between mean glucose levels and A1C. The study had limitations, including underrepresentation of certain ethnic/racial groups and reliance on two methods for glucose estimation. The results support the reporting of measured A1C as eAG, providing a more useful index of chronic glycemia for healthcare providers.