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Bertoli, S., Leone, A., Krakauer, N.Y., Bedogni, G., Vanzulli, A., Redaelli, V.I., De Amicis, R., Vignati, L., Krakauer, J.C. and Battezzati, A. (2017) Association of Body Shape Index (ABSI) with Cardio-Metabolic Risk Factors: A Cross-Sectional Study of 6081 Caucasian Adults. PLoS ONE, 12, e0185013.
https://doi.org/10.1371/journal.pone.0185013

has been cited by the following article:

• TITLE: Anthropometric Markers as a Paradigm for Obesity Risk Assessment

  AUTHORS: Anita Garg Mangla, Neeru Dhamija, Urvashi Gupta, Meenal Dhall

  KEYWORDS: Adiposity, Anthropometric Markers, Risk, Body Fat, Obesity

  JOURNAL NAME: Journal of Biosciences and Medicines, Vol.8 No.2, January 19, 2020

  ABSTRACT: Background: Quantification of obesity/adiposity is feasible with different anthropometric characteristics along with the bioelectrical impedance analysis techniques. Recent advancements are now witnessing development of further computations derived from previously established measures to gauge obesity. Objective: Main aim of our study was to evaluate the association of anthropometric determinants of obesity with body compositional adiposity variables, and thus identifying the best marker among them emerging out as the probable predictor for compositional adiposity. Participants and Setting: 550 female participants within the age of 18 to 23 years were enrolled under this study attending graduation course at University of Delhi. Ethical clearance was received from the institutional head. Informed written consent was taken from every participant. Design: All the body measurements were recorded by trained staff using standard techniques. Derived measurements were calculated further. Analysis: Data, hence, gathered was undertaken for descriptive and infer-ential statistical analysis with SPSS 20.0. Variables Measured and Results: WHR over-estimated the count for those at risk compared to waist circumference and WHtR. Skeletal muscle fat associated negatively with all anthropometric adiposity indicators. BMI, BAI, WHtR and waist circumference related closely with all body composition cum obesity markers compared to WHR, CI and ABSI. BAI overrated the risk for fat determining body composition parameters the most followed by BMI. ABSI revealed an underestimated risk for augmenting fat content in body, compared to other markers. Conclusion and Implications: It is difficult to establish with compliance as to which of the measures used in the study could better predict the perils of obesity but it could be ascertained that some of the newly verified anthropometric adiposity indicators could be administered for determining clinical situations after further validation.