Clinical Usefulness of Anthropometric Indices to Predict the Presence of Prediabetes. Data from the ILERVAS Cohort
2021
Sánchez, Marta | Sánchez, Enric | Bermúdez-López, Marcelino | Torres, Gerard | Farràs-Sallés, Cristina | Pamplona, Reinald | Castro-Boqué, Eva | Valdivielso, José Manuel | Purroy, Francisco | Martínez-Alonso, Montserrat | Godoy, Pere | Mauricio, Didac | Fernández, Elvira | Hernández, Marta | Rius, Ferran | Lecube, Albert | On Behalf of the ILERVAS Project Collaborators,
Prediabetes is closely related to excess body weight and adipose distribution. For this reason, we aimed to assess and compare the diagnostic usefulness of ten anthropometric adiposity indices to predict prediabetes. Cross-sectional study with 8188 overweight subjects free of type 2 diabetes from the ILERVAS project (NCT03228459). Prediabetes was diagnosed by levels of glycated hemoglobin (HbA1c). Total body adiposity indices [BMI, Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) and Deurenberg’s formula] and abdominal adiposity (waist and neck circumferences, conicity index, waist to height ratio, Bonora’s equation, A body shape index, and body roundness index) were calculated. The area under the receiver-operating characteristic (ROC) curve, the best cutoff and the prevalence of prediabetes around this value were calculated for every anthropometric index. All anthropometric indices other than the A body adiposity were higher in men and women with prediabetes compared with controls (p < 0.001 for all). In addition, a slightly positive correlation was found between indices and HbA1c in both sexes (r ≤ 0.182 and p ≤ 0.026 for all). None of the measures achieved acceptable levels of discrimination in ROC analysis (area under the ROC ≤ 0.63 for all). Assessing BMI, the prevalence of prediabetes among men increased from 20.4% to 36.2% around the cutoff of 28.2 kg/m², with similar data among women (from 29.3 to 44.8% with a cutoff of 28.6 kg/m²). No lonely obesity index appears to be the perfect biomarker to use in clinical practice to detect individuals with prediabetes.
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