Table 1.
Characteristics of the study population.
Table 2.
Partial correlations1 between anthropometric measurements and cardiometabolic variables, stratified by gender.
Fig 1.
Odds ratios (95% CI) of having three or more cardiometabolic risk features for a one standard deviation increase in each obesity measure.
Results are stratified by gender and adjusted for age. All models exclude subjects with type 2 diabetes.
Fig 2.
Odds ratios (95% CI) of having type 2 diabetes for a one standard deviation increase in each obesity measure.
Results are stratified by gender and adjusted for age.
Fig 3.
Adjusted area under the receiver operating characteristic curve values for selected obesity measures to discriminate subjects with three or more cardiometabolic risk features.
Bars represent AUC values. All models exclude subjects with type 2 diabetes. Statistical differences in the AUC values are shown in superscript Arabic numbers as: 1P<0.05 compared to WC midway; 2P<0.05 compared to BMI.
Fig 4.
Adjusted area under the receiver operating characteristic curve values for selected obesity measures to discriminate subjects with type 2 diabetes.
Bars represent AUC values. Statistical differences in the AUC values are shown in superscript Arabic numbers as: 1P<0.05 compared to WC midway; 2P<0.05 compared to BMI.
Fig 5.
False positive rates corresponding to 90%, 80%, 70% and 60% sensitivities for selected obesity measures to classify subjects with type 2 diabetes.
Results are stratified by gender and adjusted for age. Bars represent false positive rates (percentages).
Fig 6.
Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.
Figures show ROC curves for a model including BMI and a model including BMI and WC midway. All models include age and gender.
Fig 7.
Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.
Figures show ROC curves for a model including BMI and a model including BMI and WC rib. All models include age and gender.
Fig 8.
Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.
Figures show ROC curves for a model including BMI and a model including BMI and Rib/height ratio. All models include age and gender.
Fig 9.
Receiver operating characteristic curves for prediction models to discriminate subjects with type 2 diabetes.
Figures show ROC curves for a model including BMI and a model including BMI and Rib/pelvis ratio. All models include age and gender.
Table 3.
Tests of calibration, goodness-of-fit and discrimination for prediction models to identify subjects with type 2 diabetes.