Does glucose variability influence the relationship between mean plasma glucose and HbA1c levels in type 1 and type 2 diabetic patients?

OBJECTIVE: The A1C-Derived Average Glucose (ADAG) study demonstrated a linear relationship between HbA(1c) and mean plasma glucose (MPG). As glucose variability (GV) may contribute to glycation, we examined the association of several glucose variability indices and the MPG-HbA(1c) relationship. RESEARCH DESIGN AND METHODS: Analyses included 268 patients with type 1 diabetes and 159 with type 2 diabetes. MPG during 3 months was calculated from 7-point self-monitored plasma glucose and continuous glucose monitoring. We calculated three different measures of GV and used a multiple-step regression model to determine the contribution of the respective GV measures to the MPG-HbA(1c) relationship. RESULTS: GV, as reflected by SD and continuous overlapping net glycemic action, had a significant effect on the MPG-HbA(1c) relationship in type 1 diabetic patients so that high GV led to a higher HbA(1c) level for the same MPG. In type 1 diabetes, the impact of confounding and effect modification of a low versus high SD at an MPG level of 160 mg/dL on the HbA(1c) level is 7.02 vs. 7.43 and 6.96 vs. 7.41. All GV measures showed the same tendency. CONCLUSIONS: In only type 1 diabetic patients, GV shows a significant interaction with MPG in the association with HbA(1c). This effect is more pronounced at higher HbA(1c) levels. However, the impact of GV on the HbA(1c) level in type 1 diabetes is modest, particularly when HbA(1c) is close to the treatment target of 7%.

Associations between features of glucose exposure and A1C: the A1C-Derived Average Glucose (ADAG) study.

OBJECTIVE: Various methods are used to quantify postprandial glycemia or glucose variability, but few have been compared and none are standardized. Our objective was to examine the relationship among common indexes of postprandial glycemia, overall hyperglycemia, glucose variability, and A1C using detailed glucose measures obtained during everyday life and to study which blood glucose values of the day provide the strongest prediction of A1C. RESEARCH DESIGN AND METHODS: In the A1C-Derived Average Glucose (ADAG) study, glucose levels were monitored in 507 participants (268 type 1 diabetic, 159 type 2 diabetic, and 80 nondiabetic subjects) with continuous glucose monitoring (CGM) and frequent self-monitoring of blood glucose (SMBG) during 16 weeks. We calculated several indexes of glycemia and analyzed their intercorrelations. The association between glucose measurements at different times of the day (pre- and postprandial) and A1C was examined using multiple linear regression. RESULTS: Indexes of glucose variability showed strong intercorrelation. Among postprandial indexes, the area under the glucose curve calculated from CGM 2 h after a meal correlated well with the 90-min SMBG postprandial measurements. Fasting blood glucose (FBG) levels were only moderately correlated with indexes of hyperglycemia and average or postprandial glucose levels. Indexes derived with SMBG strongly correlated with those from CGM. Some SMBG time points had a stronger association with A1C than others. Overall, preprandial glucose values had a stronger association with A1C than postprandial values for both diabetes types, particularly for type 2 diabetes. CONCLUSIONS: Indexes of glucose variability and average and postprandial glycemia intercorrelate strongly within each category. Variability indexes are weakly correlated with the other categories, indicating that these measures convey different information. FBG is not a clear indicator of general glycemia. Preprandial glucose values have a larger impact on A1C levels than postprandial values.