OBJECTIVE: To compare the abilities of body mass index (BMI), percent body fat (%BF), waist circumference (WC), waist-hip ratio (WHR) and waist-height ratio (WHtR) to identify cardiovascular disease risk factors. METHODS: This cross-sectional study is comprised of 1,391 Thai participants (451 men and 940 women) receiving annual health check-ups. Spearman's rank correlation was used to determine the association of the five anthropometric indices with metabolic parameters including fasting plasma glucose, triglyceride, high density lipoprotein and blood pressure. The prevalence of cardiovascular disease risk factors was determined according to tertile of each anthropometric measure. Receiver operating characteristic (ROC) curves were plotted to compare anthropometric measure as predictors of the prevalence of cardiovascular risk factors. RESULTS: Metabolic parameters were more strongly associated with %BF and WHR and least correlated with BMI in men. Among women, BMI was most strongly correlated with metabolic parameters. In both genders, the prevalence of cardiovascular disease risk factors increased across successive tertiles for each anthropometric measure. Review of ROC curves indicated that %BF and WHR performed slightly better than other measures in identifying differences in CVD risk factors among men. BMI performed at least as well or better than other measures of adiposity among women. CONCLUSIONS: These findings confirm high correlations between anthropometric measures and metabolic parameters. BMI, WC and other measures were not materially different in identifying cardiovascular disease risk factors. Although small differences were observed, the magnitudes of those differences are not likely to be of public health or clinical significance.
OBJECTIVE: To compare the abilities of body mass index (BMI), percent body fat (%BF), waist circumference (WC), waist-hip ratio (WHR) and waist-height ratio (WHtR) to identify cardiovascular disease risk factors. METHODS: This cross-sectional study is comprised of 1,391 Thai participants (451 men and 940 women) receiving annual health check-ups. Spearman's rank correlation was used to determine the association of the five anthropometric indices with metabolic parameters including fasting plasma glucose, triglyceride, high density lipoprotein and blood pressure. The prevalence of cardiovascular disease risk factors was determined according to tertile of each anthropometric measure. Receiver operating characteristic (ROC) curves were plotted to compare anthropometric measure as predictors of the prevalence of cardiovascular risk factors. RESULTS: Metabolic parameters were more strongly associated with %BF and WHR and least correlated with BMI in men. Among women, BMI was most strongly correlated with metabolic parameters. In both genders, the prevalence of cardiovascular disease risk factors increased across successive tertiles for each anthropometric measure. Review of ROC curves indicated that %BF and WHR performed slightly better than other measures in identifying differences in CVD risk factors among men. BMI performed at least as well or better than other measures of adiposity among women. CONCLUSIONS: These findings confirm high correlations between anthropometric measures and metabolic parameters. BMI, WC and other measures were not materially different in identifying cardiovascular disease risk factors. Although small differences were observed, the magnitudes of those differences are not likely to be of public health or clinical significance.
Entities:
Keywords:
Body Fat; Body Mass Index; Cardiovascular Risk Factors; Epidemiology; Waist Circumference; Waist-Height Ratio; Waist-Hip Ratio
Authors: D A Smith; E M Ness; R Herbert; C B Schechter; R A Phillips; J A Diamond; P J Landrigan Journal: Diabetes Obes Metab Date: 2005-07 Impact factor: 6.577
Authors: Eunyoung Cho; JoAnn E Manson; Meir J Stampfer; Caren G Solomon; Graham A Colditz; Frank E Speizer; Walter C Willett; Frank B Hu Journal: Diabetes Care Date: 2002-07 Impact factor: 19.112
Authors: Julienne N Rutherford; Thomas W McDade; Nanette R Lee; Linda S Adair; Christopherw Kuzawa Journal: Am J Hum Biol Date: 2010 May-Jun Impact factor: 1.937
Authors: K M Knowles; L L Paiva; S E Sanchez; L Revilla; T Lopez; M B Yasuda; N D Yanez; B Gelaye; M A Williams Journal: Int J Hypertens Date: 2011-01-24 Impact factor: 2.420