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ARS Home » Pacific West Area » Davis, California » Western Human Nutrition Research Center » Obesity and Metabolism Research » Research » Publications at this Location » Publication #325815
Title: The value of anthropometric indices for identifying women with features of metabolic syndrome

Author
item WELCH, LUCAS - University Of California
item Horn, William
item KRISHNAN, SHRIDEVI - University Of California
item Kishimura, Kathleen
item Que, Excel
item HOLGUIN, EVELYN - University Of California
item Keim, Nancy

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 2/1/2016
Publication Date: 4/2/2016
Citation: Welch, L.C., Horn, W.F., Krishnan, S., Kishimura, K.M., Que, E.S., Holguin, E., Keim, N.L. 2016. The value of anthropometric indices for identifying women with features of metabolic syndrome. Meeting Abstract. Experimental Biology 2016, San Diego, CA, April 2-6, 2016..

Interpretive Summary:

Technical Abstract: BMI is a widely used anthropometric measure for identifying CVD and metabolic syndrome (MetS) risk. Two new anthropometric indices are A Body Shape Index (ABSI) and Body Roundness Index (BRI) that may provide better correlations to features of MetS. Methods: Subject data were obtained from 91 overweight or obese (BMI 31.8 kg/m2 + 3.7) women who screened for participation in a dietary pattern intervention study (NCT02298725). The screening consisted of collecting anthropometric, blood biomarker, and blood pressure measures. The screening measures were performed to identify participants who have metabolic syndrome. Results: Ninety one participants were successfully screened for symptoms of metabolic syndrome. Three anthropometric indices, BMI, ABSI, and BRI, were used to find correlations with clinical measures of MetS. Fasting OGTT Glucose (FG), Two Hour OGTT Glucose (Gluc-2Hr), Hemoglobin A1c (HbA1C), and Quantitative Insulin Sensitivity Check Index (QUICKI) did not significantly correlate with any of these indices. All of these indices had a significant correlation with Triglyceride (TG) and log HOMA (Homeostatic Model Assessment). BRI and BMI had high correlations with several blood measures that are indicative of MetS. Out of the anthropometric indices studied, BRI was significantly correlated with TG (r=0.362), HDL (r=-0.418) and HOMA (r=0.303). BMI was significantly correlated with HOMA (r=0.400), log HOMA (r=0.405), and the Matsuda Index (r=-0.255). Although demonstrating significant correlations with several measures, ABSI had weaker correlations than both BRI and BMI in all cases. It is also of note that there is significant difference between the mean ABSI of participants who had one or less, two, or three or more primary parameters of MetS (p=0.0008). Similarly, the mean BRI of participants in these MetS groups were also different (p<0.001). Conclusion: In general, BRI showed a stronger relationship to dyslipidemic measures while BMI showed a stronger relationship to glucose intolerance. Both ABSI and BRI showed significant differences between participants who had 1 feature of MetS and those who had 3 features of MetS, suggesting a potential role of ABSI and BRI as anthropometric indices for predicting MetS. With our next 100 screened participants we will be using these indices to validate these relationships.