• Sikandar Hayat Khan, Rahat Shahid, Nadeem Fazal, and Aamir Ijaz.
• Department of Pathology, PNS Hafeez, Islamabad, Pakistan.
• J Coll Physicians Surg Pak. 2019 Dec 1; 29 (12): 1159-1164.

ObjectiveTo evaluate abdominal volume index (AVI), body roundness index (BRI), body adiposity index (BAI), a body shape index (ABSI) and conicity index (C-Index) for differences in subjects with or without metabolic syndrome, diabetes, nephropathy, and dyslipidemia; and secondly, to evaluate the diagnostic performance through measuring area under curve (AUC) by ROC curve analysis for new and conventional obesity measures in diagnosing metabolic syndrome.Study DesignCross-sectional analytical study.Place And Duration Of StudyPNS Hafeez Hospital, Islamabad, from January 2016 to December 2018.MethodologyBaseline anthropometric measures including BMI, WHpR, WHtR, AVI, BRI, BAI, ABSI and C-Index were measured for 232 subjects along with measurement of various biochemical parameters. Differences among subjects with and without metabolic syndrome, diabetes, nephropathy, and groups based upon insulin resistance were noted. ROC curve analysis was utilised to measure AUC for all anthropometric measures for diagnosing metabolic syndrome.ResultsPearson's correlation between obesity measures and lipid indices suggested highest correlation for AVI for most lipid indices followed by WHpR and WHtR. Mean AUC for obesity measures were greater than 0.80 for WHtR and AVI, followed by other parameters. The least AUC i.e. 0.320, was observed for ABSI. The differences between various anthropometric measures for groups based upon metabolic syndrome, diabetes, nephropathy, and insulin resistance remain variable indicating that each anthropometric index may depict a different aspect of the metabolic risk.ConclusionWHtR and AVI showed the highest AUC to diagnose metabolic syndrome and were better associated with metabolic diseases.

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