Waist height ratio: A universal screening tool for prediction of metabolic syndrome in urban and rural population of Haryana

• Main Authors: Rajesh Rajput, Meena Rajput, Mohan Bairwa, Jasminder Singh, Ompal Saini, Vijay Shankar
• Format: Article
• Language: English
• Published: Wolters Kluwer Medknow Publications 2014-01-01
• Series: Indian Journal of Endocrinology and Metabolism
• Subjects: Anthropometric variables; metabolic syndrome; waist-height ratio
• Online Access: http://www.ijem.in/article.asp?issn=2230-8210;year=2014;volume=18;issue=3;spage=394;epage=399;aulast=Rajput
• ISSN: 2230-8210; 2230-9500

Aims: To compare waist circumference (WC), body mass index (BMI), waist hip ratio (WHR), and waist-to-height ratio (WHtR) and define an appropriate cut-off, which is most closely predictive of the non-adipose components of the IDF metabolic syndrome (MetS) definition. Methods and Results: A total of 3,042 adults (1,693 in rural area and 1,349 in urban area) were screened for the presence of MetS according to the IDF definition. Among 3,042 adults selected as subjects, 1,518 were male and 1,524 were female. The receiver operating curve (ROC) analysis was done to determine the optimal cut-off value and the best discriminatory value of each of these anthropometric parameters to predict two or more non-obese components of metabolic syndrome. The area under ROC (AURC) for WC was superior to that for other anthropometric variables. The optimal cut-off value of WC in urban and rural males was >89 cm, which is higher than that in urban and rural females at 83 cm and 79 cm, respectively; the optimal cut-off for WHtR was >0.51 in rural females, 0.52 in rural males, and 0.53 in both urban males and females. Both parameters were found to be better than BMI and WHR. ROC and AURC values for WC were better than those for WHtR in men and women in both urban and rural areas (P = 0.0054); however, when the entire study cohort was analyzed together, irrespective of gender and place of residence, then at a value of 0.52, WHtR scored over WC as a predictor of metabolic syndrome (P = 0.001). Conclusion: Although the predictive value of different gender-specific WC values is clearly superior to other anthropometric measures for predicting two or more non-adipose components of MetS, a single value of WHtR irrespective of gender and the area of residence can be used as a universal screening tool for the identification of individuals at high risk of development of metabolic complications.