During the 5-year follow-up period, 128 (15.5%) of 826 IRAS participants developed type 2 diabetes: 44 (7.9%) of 557 participants with normal glucose tolerance at baseline, and 84 (31.2%) of 269 participants with IGT at baseline. Those participants converting to type 2 diabetes did not differ from nonconverters in terms of sex or ethnicity (). However, older age and family history of diabetes were more common among converters. Converters also had higher BMI and waist circumference, higher glucose and insulin levels, and lower SI, AIR, DI, and SG.
Baseline characteristics by diabetes status at follow-up
In linear regression models, SG was directly related to SI (parameter estimate × 1 SD, 0.11 ± 0.02, P < 0.001), AIR (parameter estimate × 1 SD, 0.22 ± 0.03, P < 0.001), and DI (parameter estimate × 1 SD, 0.29 ± 0.05, P < 0.001) after accounting for the effects of age, sex, race/ethnicity, and research center. There was no interaction effect of family history of diabetes on the relation of SG to SI (P = 0.534), AIR (P = 0.139), and DI (P = 0.990).
We used the AUC to quantify the ability of DI to predict conversion to diabetes relative to that of a model with both SI
and AIR (found in the supplemental figure, available in an online appendix at http://care.diabetesjournals.org/cgi/content/full/dc10-0165/DC1
). The AUC of the model with SI
and AIR was similar to that of DI (0.767 vs. 0.774, P
= 0.543). The 5-year incidence of diabetes by baseline tertiles of SG
and each one of the other measures (SI
, AIR, or DI) are presented in .
Figure 1 Five-year incidence of diabetes by tertiles of SI, AIR, DI, and SG. Results were adjusted for age, sex, race/ethnicity, research center, IGT, family history of diabetes, and BMI. Cut points for tertiles of SI (× 10−4 min−1 · (more ...)
SG predicted future development of diabetes after adjusting for age, sex, race/ethnicity, and research center (OR × 1 SD, 0.50 [0.40–0.64]), as did DI (OR × 1 SD, 0.47 [0.40–0.56]). In a multivariate logistic regression model that included SG and DI as independent variables, the odds remained statistically significant for both SG (OR × 1 SD, 0.61 [0.47–0.80]) and DI (OR × 1 SD, 0.68 [0.54–0.85]) (). Age, sex, race/ethnicity, research center, family history of diabetes, fasting glucose, 2-h glucose, BMI, and waist circumference were also included as covariates. In a different model that included SI, AIR, and SG, these three measures were all independent predictors of diabetes.
Predictors of conversion to type 2 diabetes by multiple logistic regression analysis
In separate logistic regression models, we examined the impact of age, sex, race/ethnicity, research center, BMI, glucose tolerance status, family history of diabetes on the relationship between SG (or DI), and incident diabetes. None of these variables had a significant impact on the relation of SG and DI to conversion to diabetes (P ≥ 0.16 for all potential interactions) except for age on the relationship between DI and conversion to diabetes (P = 0.038). The strength of the relation of DI and SG to conversion to diabetes differed little between categories of age, sex, race/ethnicity, glucose tolerance status, BMI, and family history of diabetes (A–F). Additionally, the interaction term DI × SG was not statistically significant (P ≥ 0.71). DI and SG were independent risk factors across different degrees of insulin sensitivity and insulin secretion (G and H).
Figure 2 Risk of developing diabetes associated with DI and SG by ethnicity, sex, glucose tolerance status, BMI and age categories, family history of diabetes, and tertiles of SI and AIR. Estimates expressed for a 1 SD unit change. Age, sex, race/ethnicity, research (more ...)