Journal of Clinical and Diagnostic Research. 2018 Mar, Vol-12(3): TC01-TC04 1 1 DOI: 10.7860/JCDR/2018/34263.11254 Original Article Radiology Section Utility of Sonographic Parameters in Prediction of Obesity and their Correlation with Body Mass Index SHRUTI CHANDAK 1 , ARJIT AGARWAL 2 , MOHINI CHAUDHARY 3 , ADIL KHAN 4 , SHALINI SARASWAT 5 , ASHUTOSH KUMAR 6 Keywords: Body mass index, Skin thickness, Subcutaneous abdominal fat thickness, Ultrasonography ABSTRACT Introduction: Obesity has become widely prevalent in the world with a desperate need to search the population at risk for complications of obesity for timely intervention. Ultrasonography (USG) has been previously used to measure the Subcutaneous Abdominal Fat Thickness (SAFT); however, its role has not been adequately defined. Aim: To establish the role of USG as a quantitative measure of obesity by measurement of SAFT and Skin Thickness (ST). Materials and Methods: The study was done on a total of 406 patients. Body Mass Index (BMI) was calculated for all the patients who were categorised into four pre defined BMI based subgroups. The patients then underwent USG measurement of SAFT and ST. Statistical analysis with intergroup comparison was done using one-way ANOVA test. Results: Of the total, 146 patients had BMI≥25 kg/m 2 and belonged to the obese category. Mean values of SAFT and ST showed statistically significant results. Box and whiskers plots for all the variables showed least overlapping of the Interquartile Range (IQR) for SAFT. SAFT showed significantly higher median value for the overweight and obese categories. SAFT showed highest area under the curve with 79% sensitivity and 72% specificity for prediction of obesity (BMI≥30 kg/m 2 ) at a value of 18.65 mm. SAFT showed the strongest correlation with increasing BMI. Conclusion: The findings of the present study showed that USG is an excellent modality for the measurement of SAFT and ST which may be useful in future epidemiological studies. Addition of these sonographic parameters may significantly enhance the prediction and categorisation of adiposity over other anthropometric variables like BMI. INTRODUCTION Obesity as a disease has become an epidemic, not only in the developed world but in developing countries as well. It is a major public health problem due to its connection with increased morbidity and reduced quality of life [1,2]. Obesity is linked with many types of cardiometabolic disturbances and metabolic syndrome [3]. It is now labeled by the World Health Organization as one of the most serious public health problems of the 21 st century [4]. A precise analysis of body composition is imperative to recognise health risks associated with excessive body fat, observe changes in body composition linked with certain diseases, as a support to developing weight loss or weight gain programs and assessing the success of nutrition and exercise interventions, and to supervise age-related changes in body composition. BMI is generally used to categorise obesity; although, it is a very crude measure of obesity, as it does not distinguish between tissues like muscle and fat [5]. Standard BMI cut off values may not be suitable to use in the elderly population due to age-related changes in body composition [6,7] like there is progressive loss of muscle mass and increase in fat mass [8,9]. For diagnosis of obesity, it is imperative to measure only the fat compartment of the body and this is best done by the measurement of visceral and subcutaneous fat. Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) are the reference methods for estimating visceral and subcutaneous fat quantities and distribution, the use of which in large scale studies is often restricted by their costs, convenience and due to radiation exposure [10]. Abdominal USG can easily be used to obtain an indirect one-dimensional estimate of the fat component and has been validated against MRI and CT as a way of estimating the visceral and subcutaneous fat distribution in large scale studies [11]. In contrast to the disadvantages of CT, MRI and anthropometric measurements, USG has shown to be a simple, cost-effective method without radiation risk, and with already proven reproducibility and reliability [12-14]. USG has been used competently to evaluate body fat since time immemorial; however, this technique has not been employed as a body composition technique. This is because many students, researchers, and clinicians are unfamiliar with its usefulness and versatility as a body composition assessment tool [15]. Therefore, this study was carried out with an aim to establish the role of USG as a quantitative measure of obesity by measurement of SAFT and ST. MATERIALS AND METHODS This prospective correlation study was done on a total of 406 patients, irrespective of their age and gender, who underwent abdominal USG at Department of Radiodiagnosis for various indications. The study was approved by the Institutional Review Board and was conducted over a short duration of three months from May to July 2017. The sample size was calculated using the standard formula with power of the study set at 80%. An informed written consent was taken from all the patients. Patients with abdominal hernia, ascites, pregnancy, skeletal abnormalities like physiological dwarfs and severe kyphosis or any other condition which may lead to false weight, height and BMI calculation were excluded from the study. Also, excluded were very sick and non ambulatory patients as it was not possible to measure their BMI. An electronic digital weighing machine was kept in the USG room and weight of all the patients, barefoot, was measured in kilograms up to two decimal places. Height was measured using surgical height measuring scale in centimetres. BMI was calculated for all the patients using standard formula, [BMI=Weight (in kilograms)/ Height (in metres) 2 ]. The patients were then broadly categorised into non obese (BMI<30 kg/m 2 ) and obese groups (BMI≥30 kg/m 2 ). Another categorisation of the cohort was done into four categories