A STATISTICAL APPROACH TO THE DETERMINATION OF THE MAJOR CONTRIBUTING ANTHROPOMETRIC PARAMETER(S) FOR REGIONAL VARIATION IN BODY MASS INDEX IN COASTAL AND PLAIN REGIONS OF INDIA: A PILOT COHORT STUDY

An estimate of body mass index (BMI) is a convenient technique to determine a healthy weight in accordance with height and is based on certain anthropometric parameters. This study was undertaken to statistically analyze the differential significance of anthropometric parameters in contributing to r...

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Bibliographic Details
Main Authors: J. P. Verma (Author), Harinder Jaseja (Author), Nikolay Boyadjiev (Author), Priti Gurjar (Author), Amey Bhojane (Author), Ajeet Singh (Author)
Format: Book
Published: Scientific Publishing House. NSA Press, 2018-07-01T00:00:00Z.
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Summary:An estimate of body mass index (BMI) is a convenient technique to determine a healthy weight in accordance with height and is based on certain anthropometric parameters. This study was undertaken to statistically analyze the differential significance of anthropometric parameters in contributing to regional and age variation in BMI in a cohort population. The study population comprised of 101 school teachers from Mumbai (coastal) and Gwalior (plains) regions of both sex (males=76) and (females=25). The data on age, waist circumference and hip circumference was obtained and subjected to regression analysis using the IBM SPSS version 22 software. In general, the results show that, waist in males and hip circumference in females is the single most important parameter in estimating the BMI. However, by considering all the three parameters i.e. age, waist and hip circumferences, the accuracy of BMI estimation can be enhanced both in males and females. The results exhibit a significant effect of regional influence but marginal influence of age in estimating the BMI.A definite and interesting difference in the contribution of anthropometric parameters in the regional variation of BMI was detected. The observations strongly suggest development of region-wise as well as age-wise BMI estimation models.
Item Description:10.37393/jass.2018.01.8
2534-9597
2535-0145