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Published on: March 21, 2021
Metabolic syndrome prediction based on body composition indices
Buthaina Alkhatib1, Aliaa Orabi2, Lana M Agraib3,4
1Department of Clinical Nutrition and Dietetics, Faculty of Applied Medical Sciences, The Hashemite University, Zarqa, Jordan. bkhatib@hu.edu.jo.
Background:
Metabolic syndrome (MetS) is an important public health issue that has been lately linked as a growing concern worldwide.
The Objective:
To find out which anthropometric and body composition indices can prognosticate MetS in Jordanian adult females.
Methods:
A sample of 656 Jordanian adult females was recruited (January-March 2024) in the middle of Jordan. Weight, height, waist and hip circumference, lipid profile (triglycerides and high-density lipoprotein), fasting plasma glucose, and blood pressure were measured. Fat mass index (FMI), body mass index (BMI), fat-to-muscle ratio, and waist-to-hip ratio (WHR) were calculated. The presence or absence of MetS was the outcome of interest. Receiver operating characteristic (ROC) analyses were used to examine the predictive accuracy of the indices, and the area under the curve (AUC) was measured.
Results:
40.6% had MetS, and their mean age was 45.5 years. 90.2% of the participants with MetS were obese based on body fat percentage. The MetS participants had significantly higher means of all the anthropometric indices except the fat-to-muscle ratio. None of the MetS participants were underweight, and 70.8% and 73.8% were obese based on BMI and WHR, respectively (p < 0.001). The highest proportion of the MetS participants (35.5%) was within the Q4 of the FMI compared to those without MetS (p<0.001). The discrimination ability for all indices was almost equal in predicting the existence of MetS (fair prediction power; AUC = 0.66-0.72), except for the fat-to-muscle ratio, which had poor prediction power.
Conclusion:
Fat mass %, muscle mass %, FMI, BMI, and WHR could be used as predictors of MetS in Jordanian females, while the fat-to-muscle ratio was not. We suggested that more extensive sample size studies from both genders and different age categories are necessary to develop a superior predictor for MetS in Jordan.
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