Abstract

Objectives Aim of the study was to develop a ‘composite body size score’ (CBSS) using anthropometric traits to estimate body size and to assess the nutritional status of each study individual on the basis of CBSS. Materials and Methods Data on seventeen anthropometric traits were collected from 710 individuals (Male, Female) from fishermen community inhabiting coastal villages of West Bengal, India. For estimating body sizes, Structural Equation Model (SEM) was constructed with Path Analysis (PA). Later, second order Confirmatory Factor Analysis (CFA) was applied on SEM to determine CBSS. It was hypothesized in the models that CBSS is composed with three sets of latent variables viz., linear, circular and skinfold, constructed from anthropometric traits. Applying new derived optimal cut off points of CBSS was used to determine lean, normal and robust body sizes. Individuals with negative values of CBSS were categorised as lean body size,. Positive values of CBSS were categorised into two categories- normal and robust body size. Results On the basis of CBSS, result showed that 50.6%, 48.8% and 0.6% of the individuals were categorised under lean, normal and robust body size respectively. Females showed relatively higher percent of lean body size i.e. under nutrition (73.8%) compared to males (26.2%). Conclusion The hypothesized model estimate more accurate composite body size score, based on anthropometric traits. All the traits are highly significant on the model. The lean body size category can be use in predicting ‘Undernutrition’.

Highlights

  • The assessment of body size in adult populations has been established by several methods using different parameters [1, 2, 3]

  • The use of methods like, body mass index (BMI), waist hip ratio (WHR), fat mass index (FMI) and conicity index (CI), derived from anthropometric variables are mainly used to assess the nutritional status of a population

  • Since Composite Body Size Score (CBSS) is independent of age and sex it can be considered as a unique method to classify the distinct body size in any population

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Summary

Introduction

The assessment of body size in adult populations has been established by several methods using different parameters [1, 2, 3]. The use of methods like, body mass index (BMI), waist hip ratio (WHR), fat mass index (FMI) and conicity index (CI), derived from anthropometric variables are mainly used to assess the nutritional status of a population. These techniques are perhaps neither comprehensive to assess the body size nor an appropriate measure of assessing nutritional status of individuals [4, 5, 6]. The use of statistical modelling in determining the best model fit of the data, association and distribution pattern among the parameters has come to use during the end of the 20th century [9,10,11,12,13,14] highlighted statistical model for predicting the human head shape and [15] developed a statistical model for estimating the relationship between different anthropometric measures and standing height

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