Association of body composition assessed by bioelectrical impedance analysis with metabolic risk factor clustering among middle-aged Chinese.

Author: Zhang L1, Wang Z1, Chen Z1, Wang X1, Zhu M1
1Division of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Peking Union Medical College, Chinese Academy of Medical Science, Beijing, China.
Conference/Journal: Prev Med Rep.
Date published: 2017 Mar 23
Other: Volume ID: 6 , Pages: 191-196 , Special Notes: doi: 10.1016/j.pmedr.2017.03.011. eCollection 2017. , Word Count: 251

Body composition monitor (BCM) based on the bioelectric impedance analysis is very convenient to use. However, whether percentage body fat (PBF) and visceral fat index (VFI) that acquired by BCM are superior to anthropometric measures is unknown. The study explored whether PBF and VFI are better than anthropometric indexes [body mass index (BMI), waist circumference (WC) and waist circumference to height ratio(WHtR)] in predicating metabolic risk factor clustering in a representive sample across China which included 9574 Chinese men and women that were investigated in 2009-2010. PBF and VFI were compared with the BMI, WC, and WHtR through the area under the curve (AUC) of the receiver operating characteristic (ROC) curve and logistic regression. The results showed that the AUC for VFI was higher than BMI and PBF but lower than WHtR and WC in both men and Women. The AUC for WHtR, WC, VFI, BMI and PBF was 0.710, 0.706, 0.700, 0.693, 0.656 in men and 0.705, 0.699, 0.698, 0.675, 0.657 in women, respectively. After adjusting for the potential confounding factors, the odds ratios (ORs) tended to increase with all the indexes. The curve of ORs for WHtR was steepest and the curve for PBF was flattest in both men and women; the curve for VFI was similar to WC in women, but flatter than WC in men. From the data we concluded that VFI seems better than BMI and PBF, but not superior to WC and WHtR in predicating metabolic risk factor clustering in the middle-aged Chinese.

KEYWORDS: Bioelectrical impedance analysis; Epidemiology; Obesity

PMID: 28367400 PMCID: PMC5369856 DOI: 10.1016/j.pmedr.2017.03.011