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Updated: May 11, 2026

Clinical Anthropometrics and Body Composition from 3-Dimensional Optical Imaging
Published on: June 7, 2024
Anthropometry: a new approach to identify communal body fat status in an urban south Indian population
K B Kishore Mohan1, V Sapthagirivasan, M Anburajan
1Department of Biomedical Engineering, SRM University, Kattankulathur, Chennai, Tamil Nadu, India. kishorekbmtech@yahoo.co.in
Background And Objectives:
Deep penetration of obesity into geographical and ethnic communities based on profession is being highly evidenced by researchers. Impact of this penetration in the Indian urban population is addressed by the accepted factors of professional and cultural changes. High risk of Atherosclerosis, hyperinsulinaemia, impaired glucose tolerance; prothrombotic is not addressed by the relationship between BMI vs. body fat, while body fat plays major role in all risks. The present study attempts to prove an anthropometrical empirical formula which can be an indicator of body fat in a group, based on profession or life style.
Methods:
A total number of 159 (77 males of age 36.95 ± 14.795, 82 females of age 38.07 ± 13.16) subjects participated in the study. Body composition analysis and anthropometric measurements were performed after conducting careful clinical examination. Body fat was measured using body composition analyzer and used as a reference to justify indication of anthropometrical empirical indicator (AEI). Indicative accuracy of AEI was cross verified by male and female analysis individually.
Results:
Community specific mean body fat 23.15 ± 8.47 (kg) for the mean weight of 66.05 ± 13.46 (kg) indicated prevalence of excess 35% body fat. This much of body fat has not been addressed by mean BMI 25.56 ± 4.66 (kg/m(2)).
Conclusions And Interpretation:
Statistical relation between AEI and body fat reflects original information of risk (where as BMI does not) in the selected community. AEI outperforms the identification of obesity affected profession or life style based communities over BMI analysis.
