Can Gamma-glutamyl Transferase Predict Unhealthy Metabolic Phenotypes Among Healthcare Workers in Azar Cohort Study?

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Background

Although various studies have assessed the correlation between gamma-glutamyl transferase (GGT) and cardiometabolic risk factors in obesity, no research has differentiated among metabolically-healthy obese (MHO) and metabolically unhealthy obese (MUHO), metabolically-healthy lean (MHL), and metabolically-unhealthy lean (MUHL).

Objectives

Accordingly, this study evaluated the correlation between GGT and cardiometabolic phenotypes among healthcare workers.

Methods

In this study, there were anthropometric measurements as well as the measurements of fasting blood sugar (FBS), GGT, cholesterol, triglyceride (TG), high lipoprotein density (HDL), and blood pressure in 1458 healthcare workers enrolled in the Azar Cohort Study. Metabolic syndrome (MetS) was defined according to the National Cholesterol Education Program Adult Treatment Panel III (ATP III). Accordingly, the participants were divided into four cardiometabolic phenotypes.

Results

In this cross-sectional study, there was a significant difference in the prevalence of cardiometabolic phenotypes regarding the GGT tertiles (P ≤ 0.001). The highest prevalence of MHO was observed in the third GGT tertile. The mean waist circumference, TG, FBS, HDL, and systolic and diastolic blood pressure levels increased in the MHO, MUHO, and MHL groups in a dose dependent manner with an increase in the GGT tertiles (P < 0.05). In comparing the highest and lowest GGT tertile, the risk of MHO and MUHO increased by 2.84 (95%CI 2.01 - 4.01) and 9.12 (95%CI 5.54 - 15), respectively. However, the correlation between the GGT tertile and MUHL did not reveal a similar trend. The ROC curve shows the cutoff value of 18.5 U/L for GGT, which allowed us to distinguish between the MUHO and MHO individuals.

Conclusions

The findings revealed that GGT can indicate the risk of MetS as such, it can be used to detect at-risk MHO individuals and administer proper interventions.

Language:
English
Published:
Hepatitis Monthly, Volume:22 Issue: 1, Dec 2022
Page:
15
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