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Correlation between the percentage of body fat and surrogate indices of obesity among adult population in rural block of Haryana

INTRODUCTION: The increasing prevalence of overweight and obesity has raised concerns regarding the importance of different techniques, which are used to assess body growth composition that can be used at the level of primary health care settings with minimal knowledge. The purpose of this study was...

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Detalles Bibliográficos
Autores principales: Verma, Madhur, Rajput, Meena, Sahoo, Soumya Swaroop, Kaur, Navjot, Rohilla, Ravi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4943124/
https://www.ncbi.nlm.nih.gov/pubmed/27453862
http://dx.doi.org/10.4103/2249-4863.184642
Descripción
Sumario:INTRODUCTION: The increasing prevalence of overweight and obesity has raised concerns regarding the importance of different techniques, which are used to assess body growth composition that can be used at the level of primary health care settings with minimal knowledge. The purpose of this study was to evaluate the relationship between different surrogate indices of fatness (body mass index [BMI], waist circumference [WC], waist-to-hip ratio [WHR], waist-to-height ratio [WHtR], and body fat percentage [BF%]) with the percentage of body fat and their usefulness as a predictor of obesity among adult population. MATERIALS AND METHODS: The community-based cross-sectional study done over a period of 1-year involved 1080 adult participants from a rural area in Haryana. Anthropometry, along with BF% (using hand held analyzer) were recorded using standard procedures. RESULTS: The prevalence of overweight and obesity as per the modified criteria of BMI for the Asian Indians was found to be 15.0% and 34.6%, respectively. Positive correlation was seen among all the indices except between the WHR and body adiposity index (BAI) using Pearson's correlation analysis. Maximum correlation was seen between WHtR and WC (r = 0.923), whereas WHtR depicted maximum correlation (r = 0.810) with BF%. Receiver operating characteristic curve analysis revealed that the WHtR was the most sensitive and specific indicator for the study population to predict overweight and obesity comparable to that calculated by body fat analyser followed by BAI, BMI, and WHR. CONCLUSION: A single value of WHtR irrespective of gender and the area of residence can be used as a universal screening tool for the identification of individuals at high risk of development of metabolic complications.