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Updated: Sep 22, 2025

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
Association Between Anthropometric Indices and Nonanthropometric Components of Metabolic Syndrome in Saudi Adults
Jawaher Al-Ahmadi1,2,3, Sumia Enani1,2,4, Suhad Bahijri1,2,5
1Saudi Diabetes Research Group, King Fahd Medical Research Center, King Abdulaziz University, Jeddah 3270, Saudi Arabia.
Context:
Waist circumference (WC) is used in screening for metabolic syndrome (MetS) based on its association with cardiometabolic risk. This might apply differently in ethnically different populations. Associations with other measures are also unclear.
Objective:
This work aimed to investigate the association between neck circumference (NC), WC, WC:hip circumference, WC:height (WC:Ht), NC:Ht, fat percentage, body mass index (BMI), conicity index, abdominal volume index, and weight-adjusted waist index with nonanthropometric components of MetS in nondiabetic Saudi adults.
Methods:
This cross-sectional study took place in public health centers in Jeddah, comprising 1365 Saudi adults (772 men and 593 women) aged 18 years or older not previously diagnosed with diabetes.
Main Outcome Measures Included:
the presence of 2 or more nonanthropometric components of the MetS were used to define clinical metabolic abnormality (CMA). The predictive ability of studied anthropometric indices for CMA was determined using the area under receiver operating characteristics (AUC) curve and binary logistic regression.
Results:
A total of 157 men and 83 women had CMA. NC and NC:Ht had the highest predictive ability for CMA in men (odds ratio [OR]NC = 1.79, P < .001 and ORNC:Ht = 1.68, P < .001; AUCNC = 0.69 [95% CI, 0.64-0.74] and AUCNC:Ht = 0.69 [95% CI, 0.64-0.73]). In women, WC had the highest predictive ability ORWC = 1.81, P < .001; AUCWC = 0.75 [95% CI, 0.69-0.80]).
Conclusion:
Upper-body anthropometric indicators that were associated with subcutaneous fat had the highest predictive ability for CMA in men whereas abdominal obesity indictors had the best predictive ability in women, suggesting that fat distribution might contribute to CMA in a sex-specific manner.
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