At baseline, we studied a multiethnic cohort of 1,156 obese children and adolescents (Caucasian 36%/African American 35%/Hispanic 29%, 469 male and 687 female) (Supplementary Table 1
). Their mean age was 13.2 ± 2.8 (range 4.8–23.1) years; except for the 23.1-year-old subject, the oldest subjects were aged 21 years. The median age of our population was 13.3 years, and the mode of the age was 14.7 years. The mean z
score BMI was 2.39 ± 0.38.
Of 1,156 subjects, 31 (9 male and 22 female) had type 2 diabetes (10 Caucasians, 15 African Americans, and 6 Hispanics) according to the OGTT criteria. The mean age of this group was 13.7 ± 2.25 years, the mean z score BMI was 2.35 ± 0.41, the mean fasting glucose was 116.1 ± 20.2 mg/dL, and the mean 2-h glucose was 230.7 ± 29.4 mg/dL. None of them was positive for GAD 65, ICA 512, or IA.
The average A1C level in the entire cohort was 5.41 ± 0.42% (4.10–8.00). Of note, there was a significant ethnic difference in the mean A1C among the three ethnic groups, with African Americans showing the highest A1C levels (5.55 ± 0.45), Caucasians showing the lowest A1C levels (5.28 ± 0.36), and Hispanics showing middle A1C levels (5.38 ± 0.38) (P < 0.001). This ethnic difference persisted even after controlling for fasting and 2-h glucose levels (P < 0.001).
There was a modest, albeit significant, positive relationship between A1C and fasting glucose (r = 0.29; P < 0.001), and between A1C and 2-h glucose (r = 0.32; P < 0.001).
Baseline characteristics of the study cohort according to A1C categories
At baseline, we stratified the population according to A1C categories based on the ADA 2009 recommendations: NGT (A1C <5.7%), at risk for diabetes (A1C 5.7–6.4%), and type 2 diabetes (>6.5%) ().
Clinical features of the study population according to A1C categories at baseline
According to this classification, 77% were in the NGT category, 21% were in the at risk for diabetes category, and only 1% were in the type 2 diabetes category (A1C >6.5%). Both age and sex distribution were not different among the three categories; however, it should be noted that there was a trend toward a greater number of female subjects in the higher categories of A1C. The ethnic differences among the A1C categories are particularly noteworthy; specifically, there was a higher prevalence of African Americans in the at risk for diabetes and type 2 diabetes categories (P < 0.0001). Across the A1C categories, subjects tended to be heavier in the at risk for diabetes and type 2 diabetes groups (P = 0.01). Moreover, subjects belonging to these two latter categories showed higher fasting glucose, fasting insulin, and 2-h glucose (P < 0.0001), lower insulin sensitivity (WBISI) (P < 0.0001), a trend toward lower first-phase insulin secretion (IGI, P = 0.13), and significantly lower DI (P < 0.0001) than subjects with A1C <5.7%. Plasma triglyceride levels were higher in the NGT category compared with both the prediabetic and type 2 diabetes categories (P = 0.004), probably because of the ethnic difference among the categories, with a lower prevalence of African Americans in the lower A1C group.
Baseline distribution of glucose tolerance status according to A1C categories
describes the proportion of each type of glucose tolerance status (NGT, IGT, IFG, IFG/IGT, and type 2 diabetes, derived from the OGTT) within categories of A1Cs. First, although the majority (72%) of the subjects with an A1C <5.7% were classified as NGT by the OGTT, 27% were classified with prediabetes. Second, of the subjects in the at risk category, 47% of them showed laboratory values indicative of prediabetes or diabetes, whereas the majority (53%) were NGT. Last, the majority (62%) of subjects with an A1C >6.5% were classified as having type 2 diabetes by the OGTT; however, there were also 12.5% classified as NGT and 24% classified as having prediabetes (IFG and IGT). Thus, of the 247 subjects categorized as at risk for diabetes on the basis of their A1C value, only 103 (47%) were categorized as being at risk on the basis of their OGTT, and of the 16 classified with type 2 diabetes by A1C categories, only 10 (62%) would be indicated as having diabetes. On the other hand, of those considered as having type 2 diabetes by using A1C criteria, 6 of 16 (38%) were missed by the OGTT, whereas among those in the at risk category according to A1C criteria, 144 of 247 (58%) were missed by the OGTT. In other words, the OGTT missed approximately half of the subjects who were considered as at risk for diabetes or having type 2 diabetes by using the A1C criteria. κ and weighted κ coefficient calculated on the basis of were 0.17 (95% CI 0.11–0.23) and 0.20 (0.14–0.26), respectively, which also indicated a poor agreement between A1C criteria and OGTT status.
Baseline glucose tolerance according to the A1C categories and OGTT
Comparisons between A1C and fasting glucose: AUC analysis at baseline
The AUCs shown in represent the diagnostic accuracy of the A1C, compared with fasting glucose, for IGT and type 2 diabetes, respectively. For IGT, the AUC for A1C was 0.60 (95% CI 0.56–0.65) and the AUC for fasting glucose was 0.67 (0.63–0.72) (). The optimal threshold of A1C was 5.5%, with a specificity of 59.9% and sensitivity of 57.0%. The two areas differed significantly from each other (P = 0.01). In contrast, in the type 2 diabetes category, the diagnostic accuracy of A1C and fasting glucose was not significantly different (P = 0.13). The AUC for A1C was 0.81 (0.70–0.92), and the AUC fasting glucose was 0.89 (0.82–0.97) (). The optimal threshold of A1C was 5.8% in identifying type 2 diabetes, with a specificity of 87.64% and sensitivity of 67.7%.
Figure 1 Comparison between the AUCs of the A1C and fasting glucose for IGT (A) and type 2 diabetes (B) at baseline. The red discontinuous line indicates the curve defining the area for the A1C, and the blue continuous curve defines the area for fasting glucose. (more ...)
To test the predictive value of A1C to diagnose prediabetes and type 2 diabetes, we analyzed data from 218 subjects on whom we had repeated measures after a mean of 1.68 ± 0.92 years. The follow-up group did not differ from the subjects lost to follow-up in terms of ethnicity (Caucasian 41.5%/African American 30.2%/Hispanic 28.3%, P = 0.2), sex distribution (male 36.3%, female 63.7%, P = 0.16), and A1C levels (5.39 ± 0.39 vs. 5.41 ± 0.42, range 4.3–6.5, P = 0.3).
At baseline, 139 subjects (63.76%) had NGT, 26 subjects (6.88%) had IFG only, 23 subjects (10.55%) had IGT only, 26 subjects (11.92%) had IGT and IFG, and 4 subjects (1.83%) had type 2 diabetes. Subjects in the follow-up group tended to be younger (mean age 12.53 ± 2.83 years, range 5.8–21; P = 0.001) than those who did not come to follow-up visits (mean age 13.36 ± 2.8 years, range 4.8–23.1).
Baseline and follow-up A1C were highly correlated (r = 0.78, P < 0.0001). The correlation between baseline A1C and follow-up fasting and 2-h glucose (r = 0.33; P < 0.0001 and r = 0.32; P < 0.0001, respectively) were similar to those observed in the whole population at baseline. A multivariate analysis showed that the strongest predictors of 2-h glucose at follow-up were baseline A1C and baseline 2-h glucose levels (P = 0.001 and P < 0.0001, respectively) independently of age, ethnicity, sex, baseline fasting glucose, changes in BMI z score, and follow-up time. Baseline A1C strongly predicted follow-up prediabetes/diabetes; the results from multivariate analysis showed a 1% increase in baseline A1C corresponding to 13-fold (95% CI 4.79–36.88) increases in the likelihood of having prediabetes/diabetes at follow-up, after adjusting for age, sex, race, and follow-up time. After additional adjusting for baseline fasting glucose and 2-h glucose, the strong effect of A1C still existed (odds ratio 6.6 [2.27–19.24]). Subjects with a baseline A1C ≥5.7 had a greater chance (odds ratio 5.7 [CI 1.54–10.31]) of having prediabetes/diabetes at the follow-up visit than their peers with a lower A1C (<5.7) at baseline, after controlling for age, sex, ethnicity, and follow-up time.