Please use this identifier to cite or link to this item: https://doi.org/10.1186/S40608-016-0114-4
Title: Correlation of adiposity indices with cardiovascular disease risk factors in healthy adults of Singapore: A crosssectional study
Authors: Bi, X
Tey, S.L
Leong, C
Quek, R
Loo, Y.T
Henry, C.J 
Keywords: cholesterol
high density lipoprotein cholesterol
low density lipoprotein cholesterol
triacylglycerol
adult
aged
anthropometric parameters
Article
body adiposity index
body fat
body mass
body weight
cardiovascular risk
cross-sectional study
diastolic blood pressure
dual energy X ray absorptiometry
female
gender
glucose blood level
hip circumference
human
human tissue
immunochemistry
impedance
insulin blood level
insulin resistance
lipid analysis
male
normal human
priority journal
systolic blood pressure
waist circumference
waist hip ratio
Issue Date: 2016
Citation: Bi, X, Tey, S.L, Leong, C, Quek, R, Loo, Y.T, Henry, C.J (2016). Correlation of adiposity indices with cardiovascular disease risk factors in healthy adults of Singapore: A crosssectional study. BMC Obesity 3 (1) : 33. ScholarBank@NUS Repository. https://doi.org/10.1186/S40608-016-0114-4
Rights: Attribution 4.0 International
Abstract: Background: Obesity has long been highlighted for its association with increased incidence of cardiovascular disease (CVD). Nonetheless, the best adiposity indices to evaluate the CVD risk factors remain contentious and few studies have been performed in Asian populations. In the present study, we compared the association strength of percent body fat (PBF) to indirect anthropometric measures of general adiposity (body mass index (BMI) and body adiposity index (BAI)) and central adiposity (waist circumference (WC), and waist-to-hip ratio (WHR)) for the prediction of CVD risk factors in healthy men and women living in Singapore. Methods: A total of 125 individuals (63 men and 62 women) took part in this study. PBF was measured by using three different techniques, including bioelectrical impedance analysis (BIA), BOD POD, and dual-energy X-ray absorptiometry (DEXA). Anthropometric measurements (WC, hip circumference (HC), height, and weight), fasting blood glucose (FBG), fasting serum insulin (FSI), and lipid profiles were determined according to standard protocols. Correlations of anthropometric measurements and PBF with CVD risk factors were compared. Results: Irrespective of the measuring techniques, PBF showed strong positive correlations with FSI, HOMA-IR, TC/HDL, TG/HDL, and LDL/HDL in both genders. While PBF was highly correlated with FBG, SBP, and DBP in females, no significant relationships were observed in males. Amongst the five anthropometric measures of adiposity, BAI was the best predictor for CVD risk factors in female participants (r = 0.593 for HOMA-IR, r = 0.542 for TG/HDL, r = 0. 474 for SBP, and r = 0.448 for DBP). For males, the combination of WC (r = 0.629 for HOMA-IR, and r = 0.446 for TG/HDL) and WHR (r = 0.352 for SBP, and r = 0.366 for DBP) had the best correlation with CVD risk factors. Conclusion: Measurement of PBF does not outperform the simple anthropometric measurements of obesity, i.e. BAI, WC, and WHR, in the prediction of CVD risk factors in healthy Asian adults. While measures of central adiposity (WC and WHR) tend to show stronger associations with CVD risk factors in males, measures of general adiposity (BAI) seems to be the best predictor in females. The gender differences in the association between adiposity indices and CVD risk factors may relate to different body fat distribution in males and females living in Singapore. These results may find further clinical utility to identify patients with CVD risk factors in a more efficient way. © 2016 The Author(s).
Source Title: BMC Obesity
URI: https://scholarbank.nus.edu.sg/handle/10635/180292
ISSN: 20529538
DOI: 10.1186/S40608-016-0114-4
Rights: Attribution 4.0 International
Appears in Collections:Elements
Staff Publications

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
10_1186_S40608-016-0114-4.pdf450.32 kBAdobe PDF

OPEN

NoneView/Download

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons