Metabolic syndrome prediction based on body composition indices

Area of Science:

• Endocrinology
• Public Health
• Anthropometry

Background:

• Metabolic syndrome (MetS) poses a significant and increasing global public health challenge.
• Understanding predictive factors for MetS is crucial for early intervention and management.

Purpose of the Study:

• To identify anthropometric and body composition indices that can predict Metabolic Syndrome (MetS) in adult Jordanian females.
• To evaluate the prognostic accuracy of various indices for MetS in this population.

Main Methods:

• A cross-sectional study involving 656 Jordanian adult females was conducted.
• Measurements included weight, height, waist/hip circumference, lipid profiles, fasting glucose, and blood pressure.
• Calculated indices: Fat Mass Index (FMI), Body Mass Index (BMI), fat-to-muscle ratio, and Waist-to-Hip Ratio (WHR). Receiver operating characteristic (ROC) analyses were performed.

Main Results:

• 40.6% of participants had MetS; 90.2% of those with MetS were classified as obese by body fat percentage.
• MetS participants exhibited significantly higher means for most anthropometric indices (FMI, BMI, WHR) compared to non-MetS participants.
• Indices like FMI, BMI, and WHR showed fair prediction power (AUC 0.66-0.72) for MetS, while the fat-to-muscle ratio demonstrated poor predictive ability.

Conclusions:

• Fat mass percentage, FMI, BMI, and WHR are viable predictors of MetS in Jordanian adult females.
• The fat-to-muscle ratio was found to be an unreliable predictor for MetS in this cohort.
• Further research with larger, diverse samples is recommended to develop superior MetS predictors in Jordan.