Optimal cut‐off points of fat mass index and visceral adiposity index associated with type 2 diabetes mellitus. Issue 8 (18th April 2022)

• Record Type: Journal Article
• Authors: Bagheri, Amir; Khosravy, Tina; Moradinazar, Mehdi; Nachvak, Seyed Mostafa; Pasdar, Yahya; Soleimani, Davood; Samadi, Mehnoosh
• Is Part Of: Food science & nutrition. Volume 10:Issue 8(2022)
• Page Start: 2710
• Page End: 2717
• Publication Date: 2022-04-18
• Subjects: fat mass index -- obesity -- type 2 diabetes -- visceral adiposity index; Food industry and trade -- Periodicals; Food -- Periodicals; Nutrition -- Periodicals; 664
• DOI: 10.1002/fsn3.2874
• Languages: English
• ISSNs: 2048-7177

Abstract

Abstract: Background: Indices, based on anthropometrics with or without non‐anthropometric components, are predictive of cardio‐metabolic outcomes. Fat mass index (FMI) is similar to BMI except measured fat mass replaces body weight. The visceral adiposity index (VAI) combines anthropometric measures with lipid measurements TG/HDL. The relationship of these indices to incident type 2 diabetes (T2DM) has not been established. Therefore, we have evaluated the predictive power and optimal cut‐off points of FMI, and VAI with T2DM in a cross‐sectional population study. Methods: These population‐based cross‐sectional study comprised 8411 adults aged 35–65 years using data from the Ravansar Non‐Communicable Diseases (RaNCD) cohort. VAI and FMI were defined as previously published. Optimal cut‐off points for association with incident T2DM were determined from receiver‐operating curves (ROC). Results: The optimal cut‐off point for VAI was 4.86 (AUC: 0.673; 95% CI: 0.65–0.69) and FMI 9.3 (AUC: 0.57; 95% CI: 0.55–0.59), and for T2DM in our study population. The odds ratios (OR) for T2DM were nearly identical, for VAI 1.098 (95% CI: 1.08–1.11) and for FMI 1.08 (95% CI: 1.05–1.10). Conclusions: In the current population study, VAI and FMI were weakly associated with T2DM. Therefore, it seems that anthropometric measures are unlikely to be strong mediators of T2DM compared to historical and other factors in the population studied. Abstract : We found that VAI had more predictive power to diagnose T2DM than FMI.