Literature DB >> 35852580

Cutoff values of body fat composition to predict metabolic risk factors with normal waist circumference in Asian Indian population.

Binit Sureka1, Thomas George2, Mahendra Kumar Garg3, Mithu Banerjee4, Surender Deora5, Ravinder Sukhla6, Akhil Goel7, Pawan Kumar Garg2, Taruna Yadav2, Pushpinder Singh Khera2.   

Abstract

OBJECTIVES: The aim of the study is to see if visceral fat volume (VFV), subcutaneous fat volume (SFV), and visceral-subcutaneous fat ratio (VSR) can be used to detect metabolically obese normal weight individuals in Asian Indian population.
METHODS: This is a single center prospective cross-sectional study and 80 cases having either hypertension, diabetes, or hyperlipidemia with normal waist circumference and 80 controls having normal metabolic parameters with normal waist circumference were evaluated. Visceral and subcutaneous fat volumes and visceral to subcutaneous fat ratios were determined by computed tomography (CT) at L4-L5 level with a slice thickness of 5 mm.
RESULTS: Visceral fat volume, subcutaneous fat volume, and VSR are significantly higher in patients with metabolic risk factors as compared to those without risk factors. Volume of subcutaneous fat is significantly higher in females as compared to males. VSR is higher in males in our study. The cutoff values for VFV, SFV, and VSR to predict at least one metabolic syndrome are 8.5 cm3, 15.7 cm3, and 0.61 in males and 7.0 cm3, 16.5 cm3, and 0.44 in females.
CONCLUSIONS: For individuals with normal waist circumference, VFV, SFV, and VSR can effectively predict the presence of one metabolic risk factor. KEY POINTS: • Visceral fat volume, subcutaneous fat volume, and visceral-subcutaneous fat ratio can predict individuals at risk of metabolic syndrome having normal waist circumference. • Higher VSR in Indian population is due to low reservoir of primary adipose tissue fat compartment which leads to diversion of adipocytes into the secondary adipose tissue fat compartment. • This data can be used as a screening tool in preventive radiology for identifying individuals at risk of developing metabolic syndrome.
© 2022. The Author(s), under exclusive licence to European Society of Radiology.

Entities:  

Keywords:  Computed tomography; Metabolic syndrome; Obesity; Subcutaneous fat; Visceral fat

Year:  2022        PMID: 35852580     DOI: 10.1007/s00330-022-09009-6

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   7.034


  43 in total

Review 1.  An overview on the nutrition transition and its health implications: the Bellagio meeting.

Authors:  Barry M Popkin
Journal:  Public Health Nutr       Date:  2002-02       Impact factor: 4.022

Review 2.  Obesity-associated hypertension: new insights into mechanisms.

Authors:  Kamal Rahmouni; Marcelo L G Correia; William G Haynes; Allyn L Mark
Journal:  Hypertension       Date:  2004-12-06       Impact factor: 10.190

3.  Obesity and cancer.

Authors:  Eugenia E Calle
Journal:  BMJ       Date:  2007-11-06

Review 4.  Body mass index, abdominal fatness and the risk of gallbladder disease.

Authors:  Dagfinn Aune; Teresa Norat; Lars J Vatten
Journal:  Eur J Epidemiol       Date:  2015-09-15       Impact factor: 8.082

Review 5.  Characteristics of metabolically obese normal-weight (MONW) subjects.

Authors:  Florence Conus; Rémi Rabasa-Lhoret; François Péronnet
Journal:  Appl Physiol Nutr Metab       Date:  2007-02       Impact factor: 2.665

6.  Weight gain as a risk factor for clinical diabetes mellitus in women.

Authors:  G A Colditz; W C Willett; A Rotnitzky; J E Manson
Journal:  Ann Intern Med       Date:  1995-04-01       Impact factor: 25.391

Review 7.  Obesity and dyslipidemia.

Authors:  Jelena Vekic; Aleksandra Zeljkovic; Aleksandra Stefanovic; Zorana Jelic-Ivanovic; Vesna Spasojevic-Kalimanovska
Journal:  Metabolism       Date:  2018-11-14       Impact factor: 8.694

Review 8.  The epidemiology of obesity.

Authors:  Yu Chung Chooi; Cherlyn Ding; Faidon Magkos
Journal:  Metabolism       Date:  2018-09-22       Impact factor: 8.694

9.  Body Mass Index: Obesity, BMI, and Health: A Critical Review.

Authors:  Frank Q Nuttall
Journal:  Nutr Today       Date:  2015-04-07

10.  Prevalence and clinical characteristics of metabolically healthy obese individuals and other obese/non-obese metabolic phenotypes in a working population: results from the Icaria study.

Authors:  Albert Goday; Eva Calvo; Luis Alberto Vázquez; Elena Caveda; Teresa Margallo; Carlos Catalina-Romero; Jesús Reviriego
Journal:  BMC Public Health       Date:  2016-04-01       Impact factor: 3.295

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.