ABSI is a poor predictor of insulin resistance in Chinese adults and elderly without diabetes
Arch. endocrinol. metab. (Online); 62 (5), 2018
Publication year: 2018
ABSTRACT Objective:
Recently, a new obesity index (A Body Shape Index, ABSI) based on waist circumference (WC) was developed, and high ABSI corresponds to a more central concentration of body volume. It is well known that central obesity is closely linked with insulin resistance (IR). Therefore, our study aimed to examine the discriminatory power of ABSI for IR in Chinese adults and elderly without diabetes.Subjects and methods:
In 2007, a cross-sectional study was made. In this study, 570 individuals without diabetes were available for analysis (male: 56.1%, mean age: 62.3 ± 6.5 years). Insulin resistance was assessed by homeostasis model assessment (HOMA-IR). Areas under the receiver operating characteristic (ROC) curves were determined to identify variables/models that could predict insulin resistance.Results:
ABSI was associated with IR, the cut-off points was 0.0785 m11/6kg-2/3 to identifying IR and the area under the ROC (AUC) curve was 0.618 (95%CI: 0.561-0.675), which was not better than body mass index BMI (AUC = 0.753; 95%CI: 0.706-0.801), WC (AUC = 0.749; 95%CI: 0.700-0.797), and fasting plasma glucose (FPG, AUC = 0.752; 95%CI: 0.705-0.799). Furthermore, combination with ABSI could improve the discriminatory power of other variables for IR. The AUC curve increased from 0.753 to 0.771for BMI, 0.749 to 0.754 for WC, 0.752 to 0.769 for FPG, respectively.Conclusions:
ABSI is associated with IR in the general Chinese adults and elderly without diabetes, but the discriminatory power for IR is poor. It is recommended that ABSI be used in combination with other variables.
Pueblo Asiatico, Glucemia/análisis, Índice de Masa Corporal, Tamaño Corporal/etnología, Tamaño Corporal/fisiología, China, Estudios Transversales, Homeostasis/fisiología, Resistencia a la Insulina/etnología, Resistencia a la Insulina/fisiología, Estándares de Referencia, Valores de Referencia, Factores de Riesgo, Sensibilidad y Especificidad, Estadísticas no Paramétricas, Somatotipos