Generación de Nuevo Conocimiento: Artículos publicados en revistas especializadas - Electrónicos
Obesity- and Lipid-Related Parameters in the Identification of Older Adults with a High Risk of Prediabetes According to the American Diabetes Association: An Analysis of the 2015 Health, Well-Being, and Aging Study
Fecha
2020-03-19Autor
Ramírez-Vélez, Robinson
Pérez-Sousa, Miguel Ángel
González-Ruíz, Katherine
Cano-Gutierrez, Carlos A.
Schmidt-RioValle, Jacqueline
Correa-Rodríguez, María
Izquierdo, Mikel
Romero-García, Jesús Astolfo
Campos-Rodríguez, Adriana Yolanda
Triana-Reina, Héctor Reynaldo
González-Jiménez, Emilio
Institución
Resumen
This study evaluated the predictive ability of 11 obesity- and lipid-related parameters,
including body mass index (BMI), waist circumference (WC), waist-to-height ratio (WtHR), body
roundness index (BRI), “A” body-shape index (ABSI), conicity index (C), visceral adiposity index
(VAI), triglyceride-to-glucose fasting index (TyG), triglyceride-to-glucose fasting related to BMI
(TyG-BMI), triglyceride-to-glucose fasting related to WC (TyG-WC), and triglyceride-to-glucose
fasting related to WtHR (TyG-WtHR), to identify patients from an elderly Colombian population with
a high risk of prediabetes according to the 2016 American Diabetes Association criteria. The data
were obtained from the 2015 Colombian Health and Wellbeing and Aging Survey. A total of 3307
elderly Colombian individuals (aged over 60 years) were included. Anthropometric data, fasting
plasma glucose, blood lipid profiles, family history, and health-related behaviors were assessed, and
prediabetes was defined as a fasting plasma glucose of 100 to 125 mg/dL. The areas under the receiver
operating characteristic (ROC) curves (AUCs) were calculated for each anthropometric indicator,
using the prediabetes classification to identify their sensitivity and specificity, and these indicated that
the prevalence of prediabetes was 25.3% in this population. After adjusting for potential confounding
factors, the TyG index was strongly associated with the odds of having prediabetes in both sexes,
and multivariate logistic regression analysis showed that the ORs for prediabetes increased across
quartiles (p < 0.001). The TyG index was best able to identify prediabetes in either sex (AUC and
optimal cut-o = 0.700 and 8.72, and 0.695 and 8.92 for men and women, respectively), suggestingthat compared to the other parameters, the TyG index has the best discriminative power to predict
prediabetes in the whole population. Thus, we propose the TyG index be used as a complementary
marker for assessing prediabetes in older adults.