Relative contributions of preprandial and postprandial glucose exposures, glycemic variability, and non-glycemic factors to HbA 1c in individuals with and without diabetes

Abstract

Background/objective: There is substantial interest in dietary approaches to reducing postprandial glucose (PPG) responses, but the quantitative contribution of PPG to longer-term glycemic control (reflected in glycated hemoglobin, HbA_1c) in the general population is not known. This study quantified the associations of preprandial glucose exposure, PPG exposure, and glycemic variability with HbA_1c and estimated the explained variance in HbA_1c in individuals with and without type 2 diabetes (T2D).

Subjects/methods: Participants in the A1c-Derived Average Glucose (ADAG) study without T2D (n = 77) or with non-insulin-treated T2D and HbA_1c<6.5% (T2D_{HbA1c < 6.5%}, n = 63) or HbA_1c ≥ 6.5% (T2D_{HbA1c ≥ 6.5%}, n = 34) were included in this analysis. Indices of preprandial glucose, PPG, and glycemic variability were calculated from continuous glucose monitoring during four periods over 12 weeks prior to HbA_1c measurement. In linear regression models, we estimated the associations of the glycemic exposures with HbA_1c and calculated the proportion of variance in HbA_1c explained by glycemic and non-glycemic factors (age, sex, body mass index, and ethnicity).

Results: The factors in the analysis explained 35% of the variance in HbA_1c in non-diabetic individuals, 49% in T2D_{HbA1c < 6.5%}, and 78% in T2D_{HbA1c ≥ 6.5%}. In non-diabetic individuals PPG exposure was associated with HbA_1c in confounder-adjusted analyses (P < 0.05). In the T2D_{HbA1c < 6.5%} group, all glycemic measures were associated with HbA_1c (P < 0.05); preprandial glucose and PPG accounted for 14 and 18%, respectively, of the explained variation. In T2D_{HbA1c ≥ 6.5%}, these glycemic exposures accounted for more than 50% of the variation in HbA_1c and with equal relative contributions.

Conclusions: Among the glycemic exposures, PPG exposure was most strongly predictive of HbA_1c in non-diabetic individuals, suggesting that interventions targeting lowering of the PPG response may be beneficial for long-term glycemic maintenance. In T2D, preprandial glucose and PPG exposure contributed equally to HbA_1c.

Fig. 1

Scatter plot of HbA_1c measurements vs. measurements of pre-breakfast glucose (a), nocturnal glucose (b), AUC glucose (c), incremental AUC glucose (d), peak glucose (e), MAGE (f), SD (g), and CV (h) obtained from continues glucose monitoring (P < 0.001 for all associations). Light blue: No diabetes; blue: T2D_{HbA1c < 6.5%}; dark blue: T2D_{HbA1c ≥ 6.5%}

Fig. 2

Mean (95% CI) difference in HbA_1c by an SD difference in glycemia for participants without diabetes, T2D_{HbA1c < 6.5%}: non-insulin-treated diabetes and HbA_1c < 6.5%/48 mmol/mol or T2D_{HbA1c ≥ 6.5%}: non-insulin-treated diabetes and HbA_1c ≥ 6.5%/48 mmol/mol. Estimated differences are unadjusted (gray) or adjusted for age, sex, BMI, and ethnicity (black)

Fig. 3

Proportion of variance explained in HbA_1c by non-glycemic factors (age, sex, BMI, ethnicity), preprandial glucose (pre-breakfast and nocturnal glucose), postprandial glucose (total and incremental area under the curve as well as peak glucose), and glycemic variability (MAGE, SD, and CV) by diabetes status and HbA_1c levels.